Dissecting the genetic basis of computer-assisted fresh semen traits in goats using multi-locus genome-wide association methods

Dissecting the genetic basis of computer-assisted fresh semen traits in goats using multi-locus genome-wide association methods | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Dissecting the genetic basis of computer-assisted fresh semen traits in goats using multi-locus genome-wide association methods Ahmet Eser, Aslıhan Çakır Cihangiroğlu, Abdurrahman Alakuş, Kemal Bağcı, and 7 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6721731/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Background Improving sperm quality through genetic selection is a critical strategy for enhancing reproductive efficiency in farm animals. Dissecting the molecular basis of complex reproductive traits requires identifying genetic variants linked to key semen characteristics. Genome-wide association studies (GWAS) provide a robust framework for exploring the genetic architecture of economically significant traits, including fertility. In this study, both conventional sperm parameters—semen volume (mL), mass activity (scale 1–4), sperm concentration (×10 9 /mL), and total sperm count per ejaculation (×10 9 )—and CASA-derived motility traits—total motility (%), progressive motility (%), average path velocity (VAP, µm/s), straight-line velocity (VSL, µm/s), curvilinear velocity (VCL, µm/s), amplitude of lateral head displacement (ALH, µm), beat cross frequency (BCF, Hz), straightness (STR, %), linearity (LIN, %), and wobble (WOB, %)—were evaluated in 24 bucks from three breeds (Boer, n = 11; Anglo-Nubian, n = 8; Murcia-Granada, n = 5) during the breeding season. To investigate the genetic basis of these traits, three advanced multi-locus GWAS models—BLINK, FarmCPU, and MLMM—were applied. Subsequent gene annotation, functional enrichment, and network analyses were performed for candidate genes located within ± 100 Kb of the associated SNPs, offering novel insights into the molecular mechanisms underlying spermatological characteristics. Results A total of 98 SNPs were found to be significantly associated with various semen parameters. Of these, 12 SNPs exhibited high statistical significance, with p-values ranging from 1 × 10⁻ 6 to 1 × 10⁻ 15 . Noteworthy SNPs included rs268240712 (upstream of TLE4 ) and rs268235538 (upstream of SOX5 ), significantly associated with mass activity and sperm concentration, respectively. Additionally, rs268283792 (downstream of STIM2 ), rs268247301 (downstream of TPCN2 ), and rs268257690 (located within an intronic region of PIDD1 ) were significantly linked to total motility. Gene annotation within ± 100 Kb of each SNP identified 49 candidate genes. Enrichment and network analyses suggested that sperm structural and functional development plays a pivotal role in determining semen quality. Conclusion This study reveals candidate genomic regions influencing CASA-derived sperm traits in goats, offering potential for marker-assisted selection. However, further validation in larger and independent populations is warranted to confirm these associations and to assess their practical utility in genetic improvement programs. Genome-wide association study goat semen computer-assisted sperm analysis BLINK FarmCPU MLMM. Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 1. Introduction Goat farming plays a pivotal role in global agriculture and rural development by offering a multifaceted solution to food security, economic sustenance, and social empowerment. The inherent resiliency and versatile nature of goats, such as their remarkable ability to withstand heat stress and adapt to marginal environments, render them particularly valuable in regions affected by climatic extremes and resource limitations [ 1 ]. Increasing the goat population and productivity in underdeveloped and developing countries is considered a critical strategic step [ 2 ]. Reproductive efficiency is a cornerstone of goat production, directly influencing both the biological value of the animal and the economic viability of goat farming enterprises. High reproductive efficiency, generally measured by parameters such as litter size, age at first kidding, and kidding interval, is vital to maximizing herd productivity, optimizing resource use, and enhancing genetic progress [ 3 , 4 ]. Efficient reproduction not only increases the number of offspring per doe but also minimizes production costs, thereby strengthening the overall sustainability of goat farming systems. Reproductive efficiency is shaped by the complex interaction between environmental conditions and genetic factors, which together affect various stages of reproduction in both males and females [ 5 ]. In recent years, rapidly advancing molecular technologies have enabled the implementation of genomic testing in animal breeding studies and the development of genomic selection methods. Through genomic testing, genes associated with productivity traits in animals can be identified, and the genomic regions detected facilitate the prediction of both the current and heritable productivity characteristics of the animals [ 6 ]. Genetic factors fundamentally determine reproductive efficiency. However, studies investigating genetic variants associated with fertility have primarily focused on female individuals rather than male animals [ 5 ]. Although animals may have genetically high productivity, they cannot be used as breeding stock unless they can transmit these traits to subsequent generations. Therefore, the reproductive parameters of male breeding animals are regularly monitored. Sperm quality in animals can be influenced by numerous non-genetic factors, including age, nutrition, endocrine dysfunction, season, sperm collection method, and ejaculation frequency [ 7 , 8 ], as well as individual genetic factors [ 9 – 11 ]. Therefore, when environmental factors are standardized among individuals, the remaining variation is assumed to be attributable to genetic factors. Thus, optimizing environmental conditions alone does not guarantee an improvement in spermatological parameters; genetic factors must also be considered. In laboratories where sperm production and quality assessments are conducted, the primary parameters evaluated include sperm motility (%), sperm concentration (×10 9 /ml), and semen volume (mL) [ 8 , 12 ]. While semen volume and sperm concentration are used to determine the optimal number of spermatozoa per straw, sperm motility is regarded as the principal indicator of an animal’s potential fertilization capacity [ 13 , 14 ]. Fertility-related parameters in males generally exhibit low to moderate heritability estimates (ranging from 0.05 to 0.22), yet the genetic influence on these traits remains significant [ 15 ]. Therefore, identifying genetic variations associated with fertility traits—such as spermatological characteristics—in conjunction with other production and phenotypic attributes is highly valuable. Understanding the inheritance patterns of these traits can enhance reproductive success through genomic selection and enable the early prediction of the potential fertility of breeding candidates. Improving sperm quality through selective breeding is an established strategy to achieve higher fertility rates in livestock and other animal populations [ 16 ]. Hodge et al. [ 5 ] emphasized that elucidating the molecular mechanisms underlying complex reproductive traits may be achieved through the identification of genetic variants. Genome-wide association studies (GWAS) have become an indispensable tool in goat genetics research, providing insights into the genetic architecture underlying economically relevant traits, including reproductive efficiency. These studies play a crucial role in identifying single nucleotide polymorphisms (SNPs) and candidate genes that influence traits such as litter size, intersexual syndromes, and overall prolificacy, which are paramount for advancing selective breeding programs in goats [ 17 , 18 ]. Recent GWAS reports have identified SNPs associated with sperm quality parameters in various species, including cattle [ 19 – 26 ], pigs [ 18 , 27 – 31 ], rams [ 5 , 12 , 32 ], and humans [ 8 , 33 , 34 ]. However, such studies in goats remain scarce and inadequate, creating a significant knowledge gap in the literature. Despite the importance of understanding these parameters for optimizing production systems, research specifically focused on goats has been notably limited compared to other livestock species. To our knowledge, only two studies exist that address sperm quality traits and reproductive characteristics, highlighting the urgent need for more comprehensive investigations in this area. GWAS studies focusing on goat sperm quality remain limited both in number and in the range of associated parameters investigated. Existing studies have predominantly relied on conventional assessments of sperm motility, concentration [ 35 ], and semen volume [ 36 ] for genotype–phenotype association analyses. To date, no study has investigated the genetic basis of objectively measured sperm parameters derived from Computer-Assisted Sperm Analysis (CASA) in goats. This paucity of research hinders our ability to develop evidence-based management strategies tailored specifically for caprine production systems. It is noteworthy that in these association studies, basic/conventional spermatological parameters (such as subjective motility, semen volume, sperm concentration, etc.) are commonly used as phenotypic data. Relying on basic spermatological parameters in association studies represents a pragmatic approach, primarily due to constraints related to cost, feasibility, and the historical availability of such data. While these parameters have proven valuable for elucidating genetic influences on male reproductive performance, incorporating additional, more reliable and objective assessment methods—such as CASA and flow cytometry—would enhance the robustness and precision of future findings. CASA, a widely adopted technology in the industry, offers objective evaluation of sperm motility. Several CASA-derived parameters—such as curvilinear velocity, mean path velocity, and beat-cross frequency—have been linked to higher in vivo fertility, underscoring the utility of CASA in assessing semen quality [ 37 ]. Investigating the genetic background of many economically important traits in livestock, the Mixed Linear Model (MLM) has emerged as a frequently employed method that is widely adopted in GWAS. This statistical approach is particularly valued for its ability to correct for confounding factors such as population structure and polygenic background variation, which can otherwise lead to spurious associations and misinterpretation of results. The incorporation of both fixed and random effects within the MLM framework allows researchers to account for complex relationships between individuals and adjust for environmental variables that might influence phenotypic expression. However, because this model evaluates each marker independently in a univariate manner, it may fail to capture the combined effects of multiple loci contributing to complex traits, which are often governed by intricate networks of interacting genes. This fundamental limitation becomes particularly problematic when studying polygenic traits where numerous genetic variants of small effect collectively influence the phenotype [ 38 – 40 ]. Thus, the analysis of complex traits through GWAS has prompted the development of several advanced statistical models, with notable examples including the Bayesian-information and Linkage-disequilibrium Iteratively Nested Keyway (BLINK), Fixed and Random Model Circulating Probability Unification (FarmCPU), and the multi-locus mixed model (MLMM). Each of these models is engineered to overcome specific challenges associated with the genetic analysis of quantitative traits. BLINK is a statistical framework designed to enhance the efficiency of GWAS by leveraging both individual and marker information at a genomic scale. It utilizes linkage disequilibrium (LD) information to handle the inherent complexities of genetic association mapping. BLINK is characterized by its iterative strategy, which identifies associations based on the structure of LD while optimizing the detection process through the inclusion of principal component analysis (PCA) derived covariates to account for population structure. Furthermore, it simplifies the computation of kinship matrices by focusing solely on markers posited to be trait-associated, thereby refining statistical power while controlling for false positives [ 41 ]. FarmCPU represents an innovative integration of fixed and random effects models, offering a powerful approach for robust GWAS. It utilizes pseudo quantitative trait nucleotides (QTNs) derived from a method called SUPER, wherein these bins are optimized to reflect genetic variance effectively. The computational efficiency of FarmCPU has been demonstrated to surpass traditional models due to its ability to address both marker-specific kinship and the population structure. This model introduces an iterative process for enhancing statistical power by refining the blueprint of pseudoQTNs and their relationship to underlying genetic architectures. FarmCPU's design notably minimizes the risk of false discovery while maximizing the accuracy of associations, thus providing a comprehensive analytical tool for large-scale genomic datasets [ 42 ]. MLMM stands out in the landscape of GWAS methodologies for its capacity to incorporate multiple markers as covariates simultaneously, a crucial advance in controlling for confounding factors such as population stratification and kinship. By implementing a stepwise mixed model approach, MLMM partitions phenotypic variance into genetic and residual components, facilitating a more nuanced understanding of the genetic architectures of complex traits. This method allows for the identification of significant associations while effectively managing Type I errors through rigorous variance component optimization. Additionally, MLMM can be adapted to binary phenotypic responses associated with diseases, making it versatile across different types of traits [ 43 ]. In the present study, three state-of-the-art multi-locus GWAS models—BLINK, FarmCPU, and MLMM—were employed to uncover the genetic architecture underlying both conventional and CASA-derived sperm traits in goats. These models were selected for their ability to overcome the limitations of single-locus approaches by simultaneously considering multiple markers, thereby improving the detection of true associations while accounting for population structure, cryptic relatedness, and multiple testing. Ultimately, where applicable, the study aimed to evaluate the potential for genomic selection based on semen quality traits in breeding and artificial insemination bucks. 2. Materials and methods 2.1. Material and animal management In this study, a total of 24 goats from three different breeds—Boer (n = 11), Anglo-Nubian (n = 8), and Murcia-Granada (n = 5)—aged between 2 and 3 years, were used. The animal material used in this study belongs to Small Ruminant Reproductive Biotechnology Research Center in Siirt, Türkiye [37°55′30″ N latitude, 41°56′45″ E longitude; 895 m above sea level]. All experimental procedures were performed at the Small Ruminant Reproductive Biotechnology Research Center. Prior to the initiation of the study, all necessary institutional permissions for the use of animals were obtained from the center. The study material, consisting of all bucks, was maintained under similar feeding, care, and management conditions before and throughout the study period. Before the study, the goats tested negative for Mycobacterium Tuberculosis , Mycobacterium Paratuberculosis , Brucella Melitensis , Leptospirosis , Bluetongue Virus, Caprine Arthritis Encephalitis Virus , and Border Disease Virus , and their health was confirmed to be satisfactory throughout the study period. 2.2. Semen collection and evaluation Seven replicate semen samples were collected from each Boer and Anglo-Nubian goat during the breeding season. For the Murcia-Granada goats, five replicate samples were obtained. Semen collection was performed twice a week using an electroejaculation device (e320, Minitube, Tiefenbach, Germany), following the procedure described by Ungerfeld et al. [ 44 ]. During the procedure, the goats were sedated with intramuscular injections of xylazine (0.22 mg/kg; Ege Vet, Izmir, Türkiye) and flunixin meglumine (1.10 mg/kg; Intervet, Istanbul, Türkiye). In total, spermatological analyses were performed on 158 ejaculates. 2.2.1. Sperm examinations The semen samples were immediately transported to the laboratory and placed in a water bath maintained at 32°C. The volume of each ejaculate was measured using a graduated conical tube with 0.1 mL scale intervals. Sperm concentration (per mL) was determined by the photometric method (Ovine-caprine AccuRead, IMV Technologies, France). The total number of sperm per ejaculate was calculated by multiplying the ejaculate volume (mL) by the sperm concentration (sperm/mL). Mass activity of the semen was evaluated using a 4-point scale under a phase-contrast microscope (Eclipse Ci-L, Nikon, Japan) at 10× magnification. For the evaluation of total motility (MOT, %), progressive motility (pMOT, %), and kinetic velocity parameters [average path velocity (VAP, µm/s), straight-linear velocity (VSL, µm/s), curvilinear velocity (VCL, µm/s), amplitude of lateral head displacement (ALH, µm), beat cross frequency (BCF, Hz), straightness (STR = VSL/VAP), movement linearity (LIN = VSL/VCL, %), and wobble (WOB = VAP/VCL, %)], CASA system (SCA, Microptics, S.L., Version 3.2.0, Barcelona, Spain) specifically calibrated for goat sperm was used. The Basler camera (Basler Vision Tecnologie™ ACA1300-200UC, Ahrensburg, Germany), operating at 60 frames per second, was set with an image brightness of 60, contrast of 750, and light intensity of 1000. Threshold settings were defined as follows: VCL > 80 µm/s, VSL > 50 µm/s, and VAP > 25 µm/s. Progressive motility was identified as spermatozoa with STR > 80%. Total motility was calculated as the sum of progressive and non-progressive motility percentages [ 45 ]. Prior to analysis, sperm samples were diluted 1:30 (v/v) in pre-warmed medium (Optixell®). A 3 µL aliquot of each sample was placed on a pre-warmed microscope slide, covered with a coverslip, and positioned on the heated stage (37°C) of a phase-contrast microscope (Eclipse Ci-L, Nikon, Japan) integrated with the CASA system. Each sample was evaluated under a 10× negative phase-contrast objective, with at least three different fields scanned and 600–800 spermatozoa analyzed per sample. 2.3. Genetic analyses 2.3.1. Genotyping and Quality Controls For DNA extraction, 5–6 mL of blood was collected from each animal via aseptic venipuncture of the jugular vein. DNA extraction was performed using a commercial kit (QIAamp® DNA Blood Mini Kit, QIAGEN, Hilden, Germany). Following blood collection, the animals were maintained under standardized care protocols that ensured the continuity of routine husbandry and nutritional management, and no euthanasia/sacrifice procedures were performed. Genotyping of the goats was performed using the GoatSNP 85K BeadChip on the ILLUMINA platform, achieving an overall genotyping rate of 0.995. Sex chromosomes and markers with unknown genomic positions were excluded from further analysis. Quality control (QC) was conducted using PLINK v1.9 [ 46 ], applying the following criteria: Minor Allele Frequency (MAF) ≥ 0.05, individual missing genotype rate (mind) ≤ 0.1, SNP call rate ≥ 0.95, and Hardy-Weinberg equilibrium (HWE) p-value ≥ 1×10E-6. After QC, a total of 56,669 markers were retained for downstream analyses. 2.3.2. Association Study BLINK, FarmCPU, and MLMM, which collectively represent advancements in statistical modelling designed to address the complexities of GWAS, were therefore employed in this study to investigate the genetic basis of semen parameters in bucks. Prior to conducting the analyses, the normality of all parameters was assessed using the Anderson-Darling test. The supplementary data confirmed that all analyzed parameters followed a normal distribution (see Additional file 1). For the GWAS, multi-locus models—BLINK, FarmCPU, and MLMM—were implemented using the GAPIT v3 R package [ 41 – 43 ]. This package not only enables analyses with all three models but also facilitates the construction of the genomic relationship matrix (GRM) and the execution of Principal Component Analysis (PCA). To account for potential systematic bias due to cryptic kinship, the GRM was incorporated into each model. Breed, as a fixed effect, was incorporated into the multi-locus models as a covariate, while the first five principal components (PCs) were also included to control for population stratification. Following the analyses, genomic inflation factors (λ) were calculated using QCEWAS v1.2 R package [ 47 ] to evaluate potential inflation in test statistics, and Quantile-Quantile (QQ) plots were generated (Fig. 1 ). Manhattan plots were also employed to visualize the results (see Additional file 2). 2.3.3. Genomic Annotation, Gene Ontology, and Pathway Analysis Gene annotation was carried out based on the Capra hircus ARS1 genome assembly using the Ensembl database ( https://www.ensembl.org/index.html ). To explore the functional relevance of the identified loci, genes located within a ± 100 Kb window of each significant SNP were subjected to further investigation. Functional enrichment analyses, including Gene Ontology (GO) terms and biological pathways, were performed using the ShinyGO platform [ 48 ], referencing the Capra hircus ARS1 genome. Statistical significance was assessed using a false discovery rate (FDR) threshold of 0.05. Visual representations of enriched pathways and gene interaction networks were generated within the same framework. 2.4. Statistical analyses Statistical analyses were performed using SPSS Version 22.0 for Windows (SPSS Inc., Chicago, IL, USA). Spermatological parameters were checked for normality and homogeneity. The one-way analysis of variance (ANOVA) test was conducted for the statistical analysis of spermatological examination results, followed by the Duncan test for post hoc comparison of means. Relationships among the parameters were evaluated using the Pearson correlation test. The results are presented as mean ± standard error (SE). Differences with p values less than 0.05 were considered statistically significant (p < 0.05). 3. Results According to the data presented in Table 1 , spermatological parameters during the breeding season were assessed across three goat breeds. Boer goats had the highest ejaculate volume (mL) (p < 0.05). Anglo-Nubian goats showed significantly higher sperm concentration (×10⁹) than both Boer and Murcia-Granada breeds (p 0.05). In terms of total sperm count per ejaculate (×10⁹), Boer and Anglo-Nubian breeds had significantly higher values than Murcia-Granada (p 0.05). Mass motility (1–4), total and progressive motility (%), and all kinetic parameters—VAP, VSL, VCL (µm/s), ALH (µm), BCF (Hz), STR (%), and LIN (%)—were statistically similar among breeds (p > 0.05), except for WOB (%), which was significantly higher in Boer compared to Murcia-Granada (p 0.05). Table 1 Macroscopic and CASA spermatological parameters of Boer, Anglo-Nubian, and Murcia-Granada fresh semen (Mean ± SE). Parameters Boer (n = 11) Anglo-Nubian (n = 8) Murcia-Granada (n = 5) Semen volume (mL) 2.85 ± 0.87 a 2.34 ± 0.13 b 1.98 ± 0.15 b Concentration (×10 9 /mL) 1.19 ± 0.06 b 1.56 ± 0.11 a 1.24 ± 0.11 b Total sperm count (×10 9 ) 3.46 ± 0.22 a 3.74 ± 0.37 a 2.44 ± 0.26 b Mass activity (1–4) 2.97 ± 0.08 3.21 ± 0.09 3.16 ± 0.16 Total motility (%) 94.11 ± 0.78 94.31 ± 0.55 93.88 ± 0.76 Progressive motility (%) 63.04 ± 1.31 62.50 ± 1.31 61.57 ± 1.71 VAP (µm/s) 124.86 ± 3.28 120.98 ± 4.04 115.43 ± 4.68 VSL (µm/s) 105.32 ± 2.97 102.58 ± 3.55 96.66 ± 3.93 VCL (µm/s) 177.61 ± 5.50 174.56 ± 6.61 173.25 ± 8.03 ALH (µm) 3.01 ± 0.10 3.00 ± 0.11 3.05 ± 0.13 BCF (Hz) 20.37 ± 0.49 20.61 ± 0.52 20.24 ± 0.65 STR (%) 79.22 ± 0.68 78.48 ± 0.69 78.24 ± 0.82 LIN (%) 59.20 ± 1.10 57.00 ± 1.09 55.36 ± 1.43 WOB (%) 71.08 ± 0.92 a 69.08 ± 0.94 ab 67.37 ± 1.26 b abc : Different literals within lines mean statistical differences, p < 0.05. VAP, average path velocity; VSL, straight-linear velocity; VCL, curvilinear velocity; ALH, amplitude of lateral head displacement; BCF, beat cross frequency; STR, straightness; LIN, movement linearity; WOB, wobble. The chromosomal distribution of the 56,669 markers that passed the QC procedures is presented in Fig. 2 . Examination of the population structure revealed five distinct genetic clusters based on the first three principal components (PCs), which together accounted for approximately 44% of the total genetic variation (Fig. 3 ). This substantial proportion of explained variation indicates a pronounced population structure within the dataset. Given that the sample consisted of unrelated individuals from three different breeds, the presence of strong genetic differentiation among groups is expected. Such a clear stratification underscores the importance of accounting for breed effects and underlying genetic structure in the GWAS models to avoid confounding and spurious associations. According to the multi-locus GWAS results, while the BLINK and FarmCPU models effectively accounted for population stratification and/or cryptic kinship for all parameters, the MLMM model failed to adequately correct for these factors in the analysis of total motility, VAP, VLC, BCF, STR, and WOB. Therefore, the MLMM results for these traits are not presented here. Consequently, only the association results from all three multi-locus models with genomic inflation factor (λ) values between 0.95 and 1.05 across all 14 semen parameters were considered for interpretation. The GWAS results identified 98 SNPs associated with various semen parameters (Table 2 ). Gene annotation within ± 100 Kb of each SNP revealed 49 genes, with their associated traits presented in Table 3 . Notably, seven SNPs were associated with more than one parameter. Two of these were associated with STR and LIN, four with LIN and WOB, and one with total and progressive motility. To enhance the accuracy of genotype–phenotype associations, correlation analysis among semen traits was also conducted to support the identification of genes linked to multiple parameters (Fig. 4 ). A strong positive correlation was observed between STR and LIN, as well as between LIN and WOB (p < 0.001). Additionally, total motility and progressive motility were positively correlated (p < 0.01). Therefore, it seems plausible that a SNP could be associated with two positively correlated traits. Table 2 Associated SNPs that identified three multi-locus methods. Phenotype Method SNP CHR BP p -value Beta MAF Allele Association type Volume (mL) BLINK snp35236-scaffold422-1121897 2 122400178 2,56E-05 -1,006 0,15 G CHR wide FarmCPU 2,56E-05 -1,006 MLMM 6,35E-05 -1,006 BLINK snp5343-scaffold1185-90259 6 285102 4,78E-05 0,695 0,25 G CHR wide FarmCPU 4,78E-05 0,695 MLMM snp9844-scaffold1352-23038 6 97704927 2,47E-05 -0,555 0,23 A CHR wide BLINK snp51942-scaffold764-72415 8 23255940 2,70E-05 -0,652 0,27 G CHR wide FarmCPU 2,70E-05 -0,652 MLMM snp51985-scaffold764-1931368 8 25105228 3,31E-05 -0,501 0,33 A CHR wide BLINK snp11194-scaffold1400-52817 10 63215096 4,52E-05 -0,735 0,42 A CHR wide FarmCPU 4,52E-05 -0,735 MLMM snp8082-scaffold1293-900596 12 81887040 8,35E-05 -0,626 0,40 G CHR wide BLINK snp39373-scaffold500-335693 16 22105436 4,06E-05 0,807 0,35 A CHR wide FarmCPU 4,06E-05 0,807 MLMM 22_48206613_AF-PAKI 22 48206613 8,47E-05 -0,543 0,42 G CHR wide Mass activity (1–4) MLMM snp16950-scaffold177-869780 1 123284237 7,18E-05 -0,218 0,38 G CHR wide BLINK snp7782-scaffold128-754268 8 55242185 9,81E-05 -0,565 0,46 G CHR wide FarmCPU 9,81E-05 -0,565 MLMM 2,99E-09 -0,619 Genome wide MLMM snp3729-scaffold112-2926089 16 62332705 3,13E-05 -0,205 0,50 G CHR wide MLMM snp6468-scaffold123-403108 16 34183983 1,36E-06 -0,485 0,44 A Suggestive MLMM snp3410-scaffold1103-101967 21 52616716 6,35E-05 -0,199 0,35 C CHR wide MLMM snp1044-scaffold1028-386572 28 39162602 5,63E-05 0,257 0,35 A CHR wide Concentration (×10 9 /mL) MLMM snp38986-scaffold494-4405023 4 41767359 7,10E-06 0,533 0,29 A Suggestive BLINK snp2475-scaffold107-8145419 5 84371248 3,42E-05 0,797 0,31 A CHR wide FarmCPU 3,42E-05 0,797 MLMM 2,81E-07 0,705 Genome wide MLMM 7_24258258 7 24258258 7,62E-05 -0,231 0,46 G CHR wide BLINK snp17472-scaffold1807-99659 9 863011 3,49E-05 0,562 0,44 A CHR wide FarmCPU 3,49E-05 0,562 MLMM snp4635-scaffold1149-659137 19 39920786 1,77E-05 -0,328 0,40 A CHR wide MLMM snp25274-scaffold2598-218661 21 58428724 2,72E-05 0,306 0,46 G CHR wide Total sperm count (×10 9 ) MLMM 4_99044606 4 99044606 4,71E-05 -1,078 0,33 A CHR wide MLMM snp24926-scaffold255-744265 4 100269334 3,23E-05 0,913 0,48 G CHR wide BLINK snp38904-scaffold494-615717 4 37963800 2,53E-05 -1,506 0,44 A CHR wide FarmCPU 2,53E-05 -1,506 BLINK snp43484-scaffold579-5242102 9 61084856 7,01E-05 -2,229 0,50 G CHR wide FarmCPU 7,01E-05 -2,229 BLINK snp6065-scaffold1214-284375 11 4999651 7,49E-05 1,744 0,48 A CHR wide FarmCPU 7,49E-05 1,744 BLINK snp43351-scaffold578-578990 17 47954912 6,15E-05 -1,805 0,40 G CHR wide FarmCPU 6,15E-05 -1,805 BLINK snp6575-scaffold1234-59930 24 58622476 4,42E-05 -1,880 0,40 A CHR wide FarmCPU 4,42E-05 -1,880 BLINK snp58693-scaffold957-211283 28 38564501 2,36E-05 -1,301 0,42 G CHR wide FarmCPU 2,36E-05 -1,301 MLMM 3,58E-05 -1,301 BLINK snp58695-scaffold957-295440 28 38479922 7,24E-05 2,080 0,44 A CHR wide FarmCPU 7,24E-05 2,080 Total motility (%) FarmCPU GoatD01.024190 1 133947992 7,11E-05 8,553 0,15 G CHR wide BLINK snp15726-scaffold1652-791798 1 27716205 8,54E-07 -1,414 0,38 A Genome wide BLINK snp20372-scaffold202-336144 2 105501498 2,26E-05 -0,810 0,23 G CHR wide FarmCPU GoatD01.052225_v2 5 30760584 4,92E-05 8,119 0,10 A CHR wide BLINK snp52129-scaffold771-1016279 6 46982221 1,60E-15 11,710 0,13 G Genome wide FarmCPU 5,66E-07 11,810 FarmCPU snp53996-scaffold821-424571 6 41873350 7,39E-07 11,804 0,46 A Genome wide FarmCPU snp30598-scaffold339-1734537 7 63549163 2,51E-05 4,415 0,25 A CHR wide FarmCPU snp59874-scaffold995-2507995 7 77148449 7,46E-05 9,178 0,08 G CHR wide FarmCPU snp993-scaffold1026-156620 8 70907910 7,15E-05 8,397 0,38 A CHR wide BLINK snp9098-scaffold133-1208420 10 18330706 7,22E-05 -0,741 0,35 G CHR wide FarmCPU snp9251-scaffold1336-1612195 12 7146179 4,71E-05 -8,030 0,33 A CHR wide BLINK A792 14 64562445 6,25E-05 0,696 0,46 G CHR wide FarmCPU GoatD01.022536 15 53517877 8,88E-05 -6,687 0,25 G CHR wide FarmCPU LoF409 15 33753596 7,46E-05 9,178 0,08 A CHR wide FarmCPU LoF612 15 37774237 7,46E-05 9,178 0,08 T CHR wide FarmCPU snp8651-scaffold131-3195017 16 56193227 3,35E-05 4,498 0,21 G CHR wide FarmCPU snp23992-scaffold244-245992 19 26470696 2,87E-05 9,893 0,46 G CHR wide FarmCPU snp38526-scaffold488-10203 19 41369930 2,00E-05 8,625 0,44 G CHR wide BLINK snp4873-scaffold1163-331369 19 16549290 9,30E-05 -0,636 0,33 A CHR wide FarmCPU snp10992-scaffold1395-169570 21 36704386 3,07E-05 -8,302 0,23 A CHR wide FarmCPU GoatD01.006091 22 43081967 7,46E-05 9,178 0,08 G CHR wide BLINK snp4538-scaffold1146-363529 23 18313706 5,37E-07 1,975 0,21 A Genome wide FarmCPU snp59320-scaffold975-1213737 23 36114720 7,46E-05 9,178 0,08 A CHR wide BLINK snp2218-scaffold1068-446882 27 652034 1,14E-05 -0,701 0,23 G CHR wide FarmCPU snp14549-scaffold1587-647949 29 47667204 5,99E-06 8,398 0,13 A Suggestive FarmCPU snp25314-scaffold2606-438718 29 45709872 5,66E-07 11,810 0,13 A Genome wide Progressive motility (%) MLMM 3_38161381 3 38161381 7,35E-05 -6,893 0,40 A CHR wide BLINK snp7363-scaffold1269-4371892 7 49696660 9,86E-05 -8,988 0,38 A CHR wide FarmCPU 9,86E-05 -8,988 MLMM snp58321-scaffold947-1587606 10 68167372 3,61E-05 7,056 0,42 C CHR wide BLINK snp36763-scaffold445-3253592 15 49010309 9,08E-05 10,484 0,25 G CHR wide FarmCPU 9,08E-05 10,484 MLMM snp19685-scaffold1986-1695739 16 3050709 9,16E-05 7,521 0,38 A CHR wide BLINK snp23992-scaffold244-245992 19 26470696 2,51E-05 21,662 0,46 G CHR wide FarmCPU 2,51E-05 21,662 MLMM 3,59E-05 21,662 BLINK GoatD01.044219_v2 20 67138199 3,37E-05 8,542 0,33 A CHR wide FarmCPU 3,37E-05 8,542 VAP (µm/s) BLINK snp38110-scaffold4753-76823 6 114594989 5,83E-05 -13,704 0,50 CHR wide FarmCPU 5,83E-05 -13,704 BLINK A1575 20 43746225 9,82E-05 -21,090 0,46 CHR wide FarmCPU 9,82E-05 -21,090 VSL (µm/s) BLINK snp43478-scaffold579-5029795 9 61297537 7,12E-05 -18,313 0,42 G CHR wide FarmCPU 7,12E-05 -18,313 BLINK snp49837-scaffold711-2598917 20 18780503 9,99E-05 -19,869 0,38 A CHR wide FarmCPU 9,99E-05 -19,869 VCL (µm/s) BLINK snp2775-scaffold1080-665 6 102038298 1,50E-05 17,951 0,44 C CHR wide FarmCPU 1,50E-05 17,951 BLINK snp38110-scaffold4753-76823 6 114594989 2,39E-05 -16,023 0,50 G CHR wide FarmCPU 2,39E-05 -16,023 BLINK snp1170-scaffold1030-1260582 12 76170101 9,63E-05 -26,272 0,33 A CHR wide FarmCPU 9,63E-05 -26,272 BLINK snp29978-scaffold327-1284363 17 16340012 1,34E-05 25,362 0,33 A CHR wide FarmCPU 1,34E-05 25,362 BLINK A1575 20 43746225 1,60E-05 -25,383 0,46 A CHR wide FarmCPU 1,60E-05 -25,383 ALH (µm) BLINK snp57642-scaffold923-1345250 2 80592997 4,94E-05 -0,425 0,44 G CHR wide FarmCPU 4,94E-05 -0,425 MLMM snp15905-scaffold167-936306 3 36389985 5,89E-05 -0,144 0,10 G CHR wide MLMM 6_13684715 6 13684715 9,08E-05 0,057 0,38 A CHR wide MLMM snp24565-scaffold25-173044 8 19463548 8,06E-09 0,246 0,23 G Genome wide BLINK snp18149-scaffold185-14576357 10 35200343 8,47E-05 -0,382 0,29 A CHR wide FarmCPU 8,47E-05 -0,382 BLINK 14_37245469 14 37245469 4,40E-05 -0,419 0,38 T CHR wide FarmCPU 4,40E-05 -0,419 BLINK snp46140-scaffold636-264016 14 60702098 1,65E-05 -0,313 0,46 G CHR wide FarmCPU 1,65E-05 -0,313 MLMM snp45763-scaffold628-558823 15 39665713 7,56E-05 0,051 0,50 G CHR wide BLINK 17_15100698 17 15100698 6,85E-05 0,276 0,46 A CHR wide FarmCPU 6,85E-05 0,276 BLINK snp48755-scaffold692-975828 23 46351526 6,63E-05 0,301 0,40 A CHR wide FarmCPU 6,63E-05 0,301 MLMM 1,10E-11 0,277 Genome wide MLMM snp53185-scaffold800-210113 24 27412359 4,34E-05 0,060 0,40 A CHR wide BCF (Hz) BLINK snp58914-scaffold965-443131 9 10256970 4,37E-05 2,232 0,31 A CHR wide FarmCPU 4,37E-05 2,232 BLINK snp26630-scaffold2784-22752 11 92623887 4,53E-05 3,705 0,23 A CHR wide FarmCPU 4,53E-05 3,705 BLINK snp9775-scaffold135-3133622 11 26001683 9,90E-05 -3,345 0,40 G CHR wide FarmCPU 9,90E-05 -3,345 BLINK snp55623-scaffold862-1529277 26 23110814 3,85E-05 2,555 0,35 G CHR wide FarmCPU 3,85E-05 2,555 STR (%) BLINK 1_99698938 1 99698938 7,19E-05 3,761 0,48 A CHR wide FarmCPU 7,19E-05 3,761 BLINK snp56631-scaffold895-535141 2 13915 7,47E-05 4,638 0,25 C CHR wide FarmCPU 7,47E-05 4,638 BLINK snp2385-scaffold107-4230753 5 80455454 6,02E-05 -7,751 0,15 C CHR wide FarmCPU 6,02E-05 -7,751 BLINK GoatD01.044219_v2 20 67138199 7,52E-05 3,700 0,33 A CHR wide FarmCPU 7,52E-05 3,700 BLINK snp15610-scaffold165-834474 21 56176354 6,39E-05 4,491 0,17 A CHR wide FarmCPU 6,39E-05 4,491 LIN (%) BLINK 1_88732772_AF-PAKI 1 88732772 9,18E-05 6,376 0,44 A CHR wide FarmCPU 9,18E-05 6,376 BLINK 1_99698938 1 99698938 7,84E-05 6,057 0,48 A CHR wide FarmCPU 7,84E-05 6,057 MLMM 3_92567967 3 92567967 9,61E-05 3,729 0,48 G CHR wide BLINK snp34388-scaffold404-485812 4 115826699 5,17E-05 6,839 0,48 A CHR wide FarmCPU 5,17E-05 6,839 BLINK snp56732-scaffold898-750442 4 113829449 5,06E-05 6,482 0,25 G CHR wide FarmCPU 5,06E-05 6,482 BLINK snp2385-scaffold107-4230753 5 80455454 8,38E-05 -12,377 0,15 C CHR wide FarmCPU 8,38E-05 -12,377 BLINK snp9047-scaffold1329-313566 5 36127871 7,01E-05 -10,645 0,23 G CHR wide FarmCPU 7,01E-05 -10,645 BLINK 11_59883656 11 59883656 3,53E-05 -6,155 0,50 T CHR wide FarmCPU 3,53E-05 -6,155 MLMM 4,99E-05 -6,155 MLMM snp47857-scaffold674-659869 14 94209933 2,93E-05 -3,404 0,38 G CHR wide BLINK snp27852-scaffold299-1799687 16 75206653 7,82E-05 -5,615 0,50 G CHR wide FarmCPU 7,82E-05 -5,615 BLINK GoatD01.024417 22 8289498 8,47E-05 9,745 0,25 G CHR wide FarmCPU 8,47E-05 9,745 WOB (%) BLINK snp34388-scaffold404-485812 4 115826699 4,36E-05 5,389 0,48 A CHR wide FarmCPU 4,36E-05 5,389 BLINK snp56732-scaffold898-750442 4 113829449 8,73E-05 4,983 0,25 G CHR wide FarmCPU 8,73E-05 4,983 BLINK snp9047-scaffold1329-313566 5 36127871 4,98E-05 -8,439 0,23 G CHR wide FarmCPU 4,98E-05 -8,439 BLINK 11_59883656 11 59883656 2,36E-05 -4,881 0,50 T CHR wide FarmCPU 2,36E-05 -4,881 BLINK snp20770-scaffold204-3864726 11 77724268 3,50E-05 5,714 0,38 G CHR wide FarmCPU 3,50E-05 5,714 BLINK snp27852-scaffold299-1799687 16 75206653 9,13E-05 -4,376 0,50 G CHR wide FarmCPU 9,13E-05 -4,376 BLINK GoatD01.024417 22 8289498 5,92E-05 7,733 0,25 G CHR wide FarmCPU 5,92E-05 7,733 SNP: Single nucleotide polymorphism; CHR: Chromosome; BP: Base pair position; MAF: Minor allele frequency; VAP: Average path velocity; VSL: Straight-linear velocity; VCL: Curvilinear velocity; ALH: Amplitude of lateral head displacement; BCF: Beat cross frequency; STR: Straightness; LIN: Movement linearity; WOB: wobble. Table 3 Annotation of genes located within a ± 100 Kb window of associated SNPs. CHR Marker rs ID Genes Localization Phenotype 1 GoatD01.024190 na EPHB1 Intron Total motility 1 1_99698938 na ZBBX Downstream STR, LIN 2 snp20372-scaffold202-336144 rs268252883 CSRNP3 Intron Total motility 2 snp57642-scaffold923-1345250 rs268289163 LRP1B Intron ALH 2 snp35236-scaffold422-1121897 rs268267360 DNAJC10 Upstream Volume 3 3_38161381 na ATG4C Intron Progressive motility 3 snp15905-scaffold167-936306 rs268248620 NFIA Intron ALH 3 3_92567967 na NGF Upstream LIN 4 snp34388-scaffold404-485812 rs268266522 COBL Intron LIN, WOB 4 snp24926-scaffold255-744265 rs268257313 TMEM106B Upstream Total sperm count 5 snp2385-scaffold107-4230753 rs268235451 PTHLH Intron STR, LIN 5 snp9047-scaffold1329-313566 rs268241950 TMEM117 Intron LIN, WOB 5 GoatD01.052225_v2 na KANSL2 Upstream Total motility 6 snp2775-scaffold1080-665 rs268235829 PTPN13 Intron VCL 6 snp9844-scaffold1352-23038 rs268242725 ENOPH1 Intron Volume 7 snp7363-scaffold1269-4371892 rs268240304 AFAP1L1 Intron Progressive motility 8 snp51942-scaffold764-72415 rs268283606 HACD4 Intron Volume 8 snp51985-scaffold764-1931368 rs268283648 SAXO1 Intron Volume 9 snp43478-scaffold579-5029795 rs268275364 PDE7B Intron VSL 9 snp43484-scaffold579-5242102 rs268275370 PDE7B Intron Total sperm count 9 snp58914-scaffold965-443131 rs268290402 DOP1A Intron VAP 10 snp9098-scaffold133-1208420 rs268242000 NUMB Intron Total motility 10 snp11194-scaffold1400-52817 rs268244035 MDGA2 Downstream Volume 10 snp18149-scaffold185-14576357 rs268250761 KTN1 Upstream ALH 11 snp6065-scaffold1214-284375 rs268239042 AFF3 Intron Total sperm count 11 snp26630-scaffold2784-22752 rs268258978 NDUFA8 Intron BCF 11 11_59883656 na XPC1 Upstream LIN, WOB 14 snp47857-scaffold674-659869 rs268279637 KCNQ5 Intron LIN 15 GoatD01.022536 na SCN4B Intron Total motility 15 snp45763-scaffold628-558823 rs268277594 SBF2 Intron ALH 15 LoF612 na TUB Intergenic Total motility 16 snp27852-scaffold299-1799687 rs268260163 DENND1B Intron LIN, WOB 16 snp8651-scaffold131-3195017 rs268241564 PAPPA2 Upstream Total motility 17 17_15100698 na HSPB8 Downstream ALH 17 snp29978-scaffold327-1284363 rs268262235 CUX2 Upstream VCL 19 snp4635-scaffold1149-659137 rs268237642 LRRC3C Intron Concentration 19 snp23992-scaffold244-245992 rs268256400 PELP1 Intron Total motility, progressive motility 19 snp38526-scaffold488-10203 rs268270589 KRT15 Intron Total motility 19 snp4873-scaffold1163-331369 rs268237874 ASIC2 Upstream Total motility 20 snp49837-scaffold711-2598917 rs268281559 DEPDC1B Downstream VSL 21 snp15610-scaffold165-834474 rs268248334 FBLN5 Upstream STR 22 22_48206613_AF-PAKI na NT5DC2 Intron Volume 22 GoatD01.006091 na FLNB Intron Total motility 23 snp59320-scaffold975-1213737 rs268290798 DNAH8 Intron Total motility 23 snp4538-scaffold1146-363529 rs268237548 BTN2A2 Upstream Total motility 24 snp6575-scaffold1234-59930 rs268239534 CCBE1 Intron Total sperm count 28 snp1044-scaffold1028-386572 rs268234149 PCNX2 Intron Mass activity 29 snp25314-scaffold2606-438718 rs268257690 PIDD1 Intron Total motility 29 snp14549-scaffold1587-647949 rs268247301 SNORD14 Upstream Total motility CHR: Chromosome; rs: Reference SNP; VAP: Average path velocity; VSL: Straight-linear velocity; VCL: Curvilinear velocity; ALH: Amplitude of lateral head displacement; BCF: Beat cross frequency; STR: Straightness; LIN: Movement linearity; WOB: wobble. Note: SNPs highlighted in bold are associated with multiple semen parameters. Gene enrichment and network analyses of candidate genes located within ± 100 Kb of SNPs associated with semen parameters are presented in Fig. 5 . 4. Discussion The assessment of semen quality in ruminants constitutes a critical component in efforts to improve productivity and sustainability within animal production systems. In an era marked by the widespread application of reproductive biotechnologies, comprehensive evaluation of sperm parameters in prospective breeding males plays a pivotal role in determining the success of both natural mating and artificial insemination. The integration of CASA technology further enhances precision and reliability in the evaluation process [ 49 ], facilitating more informed decision-making in breeding program management. CASA is regarded as a superior method for assessing fresh semen quality, not only because of its speed but also due to its ability to accurately measure multiple aspects of sperm fertility [ 50 ]. The comparison of semen quality across different buck breeds reveals significant variations, which are influenced by breed-specific characteristics, environmental factors, and management practices. Understanding these disparities is crucial for optimizing breeding strategies and improving reproductive efficiency within goat production systems [ 51 ]. In this study, semen volume was found to be higher in Boer bucks, while sperm concentration was higher in Anglo-Nubian bucks compared to other breeds (p 0.05), but both breeds were found to be more successful than Murcia-Granada bucks (p 0.05), the WOB value was found to be higher in the Boer compared to the Murcia-Granada (p < 0.05). Among the three multi-locus GWAS methods employed in this study, FarmCPU and BLINK exhibited a high degree of consistency, identifying nearly identical sets of SNPs across all semen parameters except total motility, where some divergence was observed (Table 2 ). This strong concordance, approaching 100% agreement, highlights the robustness and reliability of these two methods when applied to the dataset. In contrast, the MLMM model identified a distinct set of SNPs for most traits, which can be attributed to differences in its underlying statistical framework and model assumptions compared to FarmCPU and BLINK. Importantly, the repeated identification of the same SNPs by multiple models—particularly those based on fundamentally different algorithmic principles—serves as compelling evidence of the statistical strength and credibility of the detected associations. Such convergence across diverse analytical approaches reinforces the confidence in these SNPs as true genetic signals rather than artefacts of model-specific biases. The genes harboring or located near the SNPs identified in the study are involved in diverse molecular functions and biological processes—including cancer and immunity—and many are directly linked to sperm quality or male reproductive biology. The FLNB gene encodes filamin B, a large actin-binding protein that plays a fundamental role in crosslinking actin filaments and thereby establishing key aspects of the cytoskeletal architecture [ 52 , 53 ]. Although FLNB has been mostly investigated in the context of skeletal development, cell migration, and vascular formation, its role in reproductive tissues, particularly in sperm or seminal fluid, has not been explored in depth in the current literature. The association of FLNB mutations with 46,XY gonadal dysgenesis Upadhyay et al. [ 54 ] raises the hypothesis that FLNB could be important for gonadal development and, by extension, aspects of sperm biology. The SCN4B gene encodes the β4 subunit of voltage‐gated sodium channels, a regulatory protein that modulates channel gating and influences the kinetic properties of the channel complex in excitable tissues [ 55 ]. While SCN4B has been primarily studied for its roles in cardiac and neuronal systems, where mutations are linked to arrhythmias and behavioral alterations [ 55 , 56 ], its potential involvement in sperm physiology remains unexplored. Although sperm ion channel studies have mainly focused on CatSper, Hv1, and potassium channels, sodium channels also play a role in sperm function [ 57 ]. Given SCN4B 's modulatory effect on voltage-gated sodium channels in other tissues, it may similarly influence sodium channels in sperm. The EPHB1 gene encodes a receptor tyrosine kinase that is implicated in mediating cell–cell communication, cellular adhesion, and migration [ 58 ]. Variants in key signaling molecules have been shown to influence crucial semen traits, including sperm morphology, motility, and count [ 59 ]. EPHB1 protein was abundantly detected in porcine seminal plasma, and although its function remains unclear, GO annotations such as 'regulation of cell motility', 'response to stimulus', and 'phosphorylation' imply a potential role in sperm functionality [ 60 ]. The protein products of the PCNX2 gene have no described function [ 61 ]; however, PCNX2 has been proposed as a candidate gene for eggshell strength in chickens [ 62 ]. The PTHLH gene encodes a neuroendocrine peptide that regulates cell and organ growth, development, migration, differentiation, and survival [ 63 ]. GWAS results identified varying numbers of candidate genes in Qinchuan, Belgian Red Bull, and Belgian Red and White cattle, including PTHLH , associated with growth, development, and reproduction [ 64 ]. Although PTHLH is not yet widely characterized within reproductive biology, its established role in calcium regulation in other tissues [ 65 ] provides a plausible basis for hypothesizing a contribution to the maintenance of seminal plasma composition and the modulation of sperm function. The non-receptor type protein tyrosine phosphatase PTPN13 has been characterized in various biological contexts, including cancer, where it plays roles in regulating cell adhesion, migration, and apoptosis [ 66 ]. In cattle-yak, upregulation of the lncRNA targeting PTPN13 has been associated with abnormal apoptosis or growth arrest in sperm cells [ 67 ]. The Leucine Rich Repeat Containing 3C gene ( LRRC3C ) has primarily been investigated in non-reproductive contexts. Although LRRC3C has been associated with inflammatory bowel disease and displays a tissue-specific expression pattern excluding the lung [ 68 ], direct evidence linking it to sperm or seminal function is currently lacking. However, advances in sperm transcriptomics offer new opportunities to explore the potential reproductive roles of understudied genes such as LRRC3C in male fertility. The CCBE1 gene, primarily known for its role in lymphangiogenesis and extracellular matrix remodeling, has been extensively studied in the context of vascular and cardiac development [ 69 ]. However, its expression in non-classical tissues, such as sperm and early embryos, suggests potential sensitivity to epigenetic reprogramming triggered by paternal dietary factors. Previous studies have demonstrated that dietary modifications in male breeding stock can result in discernible shifts in sperm epigenetic markers [ 70 ]. Enhanced levels of methionine have been associated with improvements in sperm DNA quality, including increased methylation of genes that are otherwise crucial for fertility and development [ 71 ]. Thus, integrating the developmental role of CCBE1 with the findings of Townsend et al. [ 70 ] supports the hypothesis that paternal methionine supplementation may influence embryonic development through epigenetic modulation of genes like CCBE1. Actin filament-associated protein 1‐like 1 ( AFAP1L1 ) is primarily recognized as an adaptor protein that plays a significant role in cytoskeletal dynamics and the modulation of cell motility. Takahashi et al. [ 72 ] demonstrated that AFAP1L1 associates with vinculin, influencing cellular morphology and motility. Although these studies were conducted in the context of colorectal cancer progression, the molecular functions they elucidate may provide insights into AFAP1L1 ’s potential role in sperm biology, where the regulation of cytoskeletal architecture is critical for sperm motility and morphology. TMEM117 , which encodes a transmembrane protein, has emerged in recent genomic studies for its involvement in various biological processes, although its direct role in sperm or semen remains largely unexplored. Notably, TMEM117 has been implicated in selection signatures and expression traits in livestock, including body condition and fatty acid composition [ 73 , 74 ]. In a GWAS study conducted in cattle, SNPs within the TMEM117 gene were primarily associated with biological regulation, metabolic activity, and developmental processes [ 75 ]. These associations suggest that TMEM117 may exert an indirect influence on fertility by modulating seminal fluid quality and, consequently, sperm function. The NUMB gene, a key regulator of cell fate determination, plays a crucial role in the regulation of various signaling pathways. Functioning primarily as an adaptor protein, NUMB influences Notch signaling and endocytic processes—both of which are critically involved in cell proliferation, differentiation, and the maintenance of undifferentiated cellular states [ 76 ]. Although direct experimental evidence linking NUMB to specific sperm or semen functions is limited, NUMB-associated signaling pathways may indirectly influence sperm motility and function. The Nuclear Factor I ( NFI ) family ( NFIA , NFIB , NFIC , and NFIX ) is primarily involved in regulating stem cell development. All members of the NFI family have been shown to exhibit high expression levels in the caput region of the epididymis [ 77 ]. Among its members, NFIX is notably expressed in spermatocytes and plays a critical role in spermatogenesis. Deficiency in NFIX has been shown to cause multinucleation in spermatocytes, structural abnormalities in the synaptonemal complex, and other defects, ultimately resulting in impaired spermatogenesis [ 78 ]. Zhang et al. [ 79 ] reported that abnormal expression of the NFIA gene was associated with infertility and a down-regulation of testosterone levels in monkeys with diet-induced obesity. Proline, glutamate, and leucine-rich protein 1 ( PELP1 ) serves as an estrogen receptor (ESR) coregulator and plays a multifaceted role in mediating both genomic and non-genomic signal transduction [ 80 ]. Skibińska et al. [ 81 ] demonstrated that increased PELP1 expression in human sperm is linked to abnormal sperm parameters, including altered motility and morphology. Additionally, the PELP1 gene has been reported to be associated with sperm morphology abnormalities in pigs [ 27 ]. The NDUFA8 gene encodes a nuclear-encoded subunit of NADH:ubiquinone oxidoreductase (Complex I) of the mitochondrial respiratory chain, which is essential for efficient electron transport and ATP production [ 82 ]. NDUFA8 has been reported to be involved in thermogenesis and the oxidative phosphorylation pathway, playing an important role in ram sperm cryotolerance [ 83 ]. DENND1B , primarily involved in immune regulation [ 84 ], hosts a circRNA associated with sperm motility in pigs [ 85 ]. Kunnath et al. [ 86 ] also linked a DENND1B variant to semen quality differences in Holstein Friesian and Hallikar bulls. COBL (cordon-bleu WH2 repeat protein) is primarily known for its role in actin nucleation and cytoskeletal organization [ 87 ]. It is also expressed in testicular tissue [ 88 ], and an intronic variant in COBL gene has been associated with idiopathic male infertility [ 89 ], as well as with oligozoospermia or azoospermia [ 90 ] in previous GWAS studies. The role of the KRT15 gene in male reproduction remains unclear; however, its expression was significantly lower in fresh ram sperm than in frozen-thawed samples [ 91 ]. The phosphodiesterase PDE7B is a cAMP-specific enzyme that has garnered attention due to its tissue-specific expression, including in the testis. Sasaki et al. [ 92 ] reported that in rat spermatocytes, PDE7B mRNA is expressed in a stage-specific manner during spermatogenesis, suggesting that PDE7B may play an essential role in the regulation of cAMP signaling during sperm development. This regulation is critical because cAMP is a central intracellular messenger that modulates sperm motility, capacitation, and other aspects of sperm function, as highlighted by studies on sperm capacitation and motility [ 93 ]. The SBF2 gene, also known as SET-binding factor 2 or MTMR13 , is primarily characterized for its role as a regulatory protein within the myotubularin family [ 94 ]. Myotubularin and its related proteins (MTMs) are highly conserved phosphatases and pseudophosphatases present across eukaryotes, from fungi to humans [ 95 ]. Among them, only MTMR2 and MTMR5 have been implicated in spermatogenesis, as knockout mice ( MTMR2 ⁻/⁻ and MTMR5 ⁻/⁻) exhibit aspermatogenesis and azoospermia, supported by both in vitro and in vivo studies [ 96 – 99 ]. In this study, a variation in the SBF2 ( MTMR13 ) gene was identified, although its involvement in spermatogenesis or sperm function remains uncharacterized in the literature. The KCNQ5 gene encodes a voltage-gated potassium channel that has primarily been studied in the context of neuronal excitability and vascular function [ 100 ]. Potassium channels are critical for sperm function by regulating the membrane potential, a key factor required for processes such as capacitation, the acrosome reaction, and ultimately fertilization [ 57 ]. In contrast to KCNQ5 , other potassium channel isoforms—for example, KCNQ1 —have been identified in human sperm and are involved in sperm motility and capacitation [ 101 ]. However, no direct evidence currently links KCNQ5 expression or activity to sperm-specific processes, and studies have not reported its expression in sperm. The SAXO1 gene encodes a protein essential for stabilizing axonemal microtubules, particularly in the sperm flagellum endpiece [ 102 ]. Structural studies have shown that SAXO1 binds along microtubule protofilaments via a conserved Mn motif, thereby supporting flagellar integrity and sperm motility required for successful fertilization [ 102 , 103 ]. LRP1B , a member of the low-density lipoprotein (LDL) receptor family, is involved in various cellular processes [ 104 ] and has been proposed as a potential marker of spermatogonial stem cell (SSC) function in Shaziling pigs [ 105 ]. The DNAH8 gene encodes an axonemal dynein heavy chain essential for the formation, structural integrity, and motility of the sperm flagellum. Studies in humans and mice have shown that bi-allelic deleterious variants in DNAH8 cause male infertility associated with multiple morphological abnormalities of the sperm flagella (MMAF9 [ 106 ]. Chromosomal mapping studies have identified regions containing DNAH8 as potentially associated with asthenozoospermia, a condition characterized by reduced sperm motility [ 107 ]. Furthermore, the presence of DNAH8 variants in cohorts of infertile men supports the view that subtle genetic alterations in this gene may contribute to a range of sperm dysfunctions [ 108 ]. The nucleotide excision repair (NER) pathway is activated in response to severe DNA lesions such as pyrimidine dimers and intrachain cross-links, which disrupt the DNA helical structure [ 109 ]. The XPC protein plays a key role in this repair mechanism. Notably, XPC expression is significantly higher in the testis compared to other tissues in both mice and humans [ 110 ]. Moreover, XPC heterozygous mice exhibit smaller litter sizes and prolonged birth intervals, indicating that XPC mutations may impair reproductive function and spermatogenesis [ 111 ]. Elevated heat shock protein levels are thought to be associated with immature spermatozoa [ 112 ]. A GWAS study in beef bulls reported a significant SNP for post-thaw motility located near the HSPB8 gene, which encodes heat shock protein family B (small) member 8 [ 21 ]. The nerve growth factor ( NGF ) gene and its SNPs play a significant role in male reproductive physiology, particularly in the context of sperm quality and semen characteristics. It has been demonstrated that NGF enhances the motility of spermatozoa in various species, including humans and rabbits, through mechanisms that potentially involve its action on the sperm’s cytoskeleton and capacitation processes [ 113 , 114 ]. Furthermore, NGF ’s receptor, TrkA , is expressed in the male reproductive tract, indicating a direct role in male fertility [ 114 , 115 ]. In the context of genetic variations, SNPs in the NGF gene have been studied concerning their potential impact on reproductive traits. For example, a non-synonymous SNP in the NGF gene [rs6330], which results in an amino acid substitution, has been associated with altered NGF function and could influence sperm quality [ 116 , 117 ]. Additionally, variations in NGF have been linked to broader issues of male infertility, such as low sperm motility and concentration, underscoring the gene's importance in reproductive success [ 118 , 119 ]. The TUB [tubby] gene encodes a major cytoskeletal protein in the sperm tail, and its reduced expression is associated with impaired motility and structural defects in spermatozoa [ 120 ]. The PAPPA2 gene, which encodes pregnancy-associated plasma protein A2, regulates insulin-like growth factor bioavailability—crucial for spermatogenesis and sperm quality—and its deletion in mice has been linked to altered male fertility, suggesting a role in sperm maturation and function beyond reproductive frequency [ 121 – 123 ]. The MDGA2 gene is involved in protein metabolism and cell–cell interactions, and Khayatzadeh et al. [ 124 ] reported an association between MDGA2 and seminal volume in bulls. Additionally, the MDGA2 gene is suggested to serve as a potential functional marker for spermatogonial stem cells in Shaziling pigs [ 105 ]. The SNORD14 gene, encoding a small nucleolar RNA, has attracted attention for its role in RNA processing and potential impact on various biological processes. Within the long non-coding RNA-target regulatory network, several small nucleolar RNA-encoding genes, including SNORD14 , have been reported to show a strong correlation with the upregulated MSTRG.14719.6 [ 125 ], highlighting its significant role in the post-transcriptional modification of ribosomal RNAs (rRNAs), which are crucial for sperm viability and male fertility [ 126 , 127 ]. Fibulins are extracellular matrix glycoproteins that modulate cellular behavior and function, primarily through interactions with laminin and calcium. Among them, Fibulin-5 ( FBLN5 ) plays a key role in extracellular matrix regulation and cellular adhesion, and has been identified as a candidate gene associated with sperm DNA integrity in the testicular tissue of male pigs [ 128 ]. Kinectin-1, a member of the kinesin superfamily of motor proteins, plays a crucial role in the organized transport of organelles and cellular components along microtubules [ 129 ]. The KTN1 gene, which encodes this protein, has been identified as commonly differentially expressed in asthenozoospermia [ 130 ]. The DNAJC10 gene, which encodes a member of the DnaJ heat shock protein family involved in cellular stress responses and protein folding, has been found to be highly expressed in the caput and corpus regions of the epididymis [ 131 ]. It is noteworthy that a total of 12 high-effect SNPs, with p-values ranging from 1 × 10⁻¹⁵ to 1 × 10⁻⁶, were identified. Among these SNPs, rs268283792, is located approximately 120 Kb downstream of the Stromal Interaction Molecule 2 ( STIM2 ) gene and showed a genome-wide significant association with total sperm motility percentage (p = 1.60 × 10⁻¹⁵). STIM2 , which is involved in cellular calcium ion homeostasis and store-operated calcium channel activity [ 132 ], has also been associated with spermatozoon count in rams [ 12 ]. The TLE4 gene encodes a transcriptional corepressor involved in the Wnt signaling pathway, exhibits testis-specific splicing variants [ 133 ], and has been associated with genetic variation in total sperm motility and progressive motility in Italian Holstein bulls [ 134 ], as well as with total sperm number in boars [ 28 ]. In this study, a SNP (rs268240712) located upstream of the TLE4 gene was found to be genome-wide significantly associated with sperm mass activity (2.99 × 10⁻ 9 ). Polymorphisms identified in the SRY (Sex-Determining Region Y)-box 5 ( SOX5 ) gene have been reported to influence sperm motility [ 19 , 135 ] and concentration [ 135 ] in bulls and have also been strongly associated with nonobstructive azoospermia in humans [ 136 ]. Similarly, in this GWAS study, the SNP rs268235538, located upstream of the SOX5 gene, was found to be associated with sperm concentration in goats (p = 2.81 × 10 − 7 ). Two-pore channels (TPCs) have been found to share structural homology with both the transient receptor potential (TRP) channel superfamily and the cation channel of sperm (CatSper), each of which comprises tetrameric, single-domain channels [ 137 ]. The SNP rs268247301, located approximately 207 Kb downstream of the Two Pore Segment Channel 2 ( TPCN2 ) gene, was found to be associated with total sperm motility (p = 5.99 × 10 − 6 ). p53-induced death domain protein 1 (PIDD1) is best known for its role in orchestrating cell cycle control and programmed cell death through the formation of the multiprotein PIDDosome complex, which typically facilitates caspase‐2 activation in response to centrosome aberrations and DNA damage [ 138 ]. Spermatogenesis is highly dependent on the stringent regulation of cell cycle checkpoints and apoptosis to ensure proper genomic integrity and to eliminate damaged germ cells. Liu et al. [ 139 ] reported that the expression level of the PIDD transcript significantly decreased in July and October, suggesting that this reduction may contribute to the suppression of apoptotic effects in the testis of P. sinensis and support the preservation of germ cells lost during intermediate and late stages of spermatogenesis. In this study, an intronic variant (rs268257690) in the PIDD1 gene was found to be significantly associated with total sperm motility (p = 5.66 × 10 − 6 ). Morphogenetic pathways play a crucial role in the structural and functional development of sperm. The plasma membrane bounded cell projection morphogenesis pathway is responsible for the formation of membrane-bound structures such as the acrosome and flagellum. These structures are crucial for sperm function: the acrosome contains hydrolytic enzymes required for penetrating the zona pellucida [ 140 ], while the flagellum provides motility, being ensheathed by the plasma membrane and powered by internal axonemal structures [ 141 ]. Additionally, this pathway regulates membrane reorganization during capacitation, a key step in acquiring fertilization competence [ 142 ]. The cell projection morphogenesis pathway regulates the overall development of cellular projections. It governs the precise assembly of the axoneme, a 9 + 2 microtubule structure critical for flagellar motion [ 143 ], and orchestrates nuclear shaping during spermatid maturation [ 144 ]. It also ensures the helical organization of mitochondria around the midpiece, supporting energy production for motility [ 145 ]. The cell part morphogenesis pathway focuses on the differentiation of specific subcellular structures. This includes chromatin condensation through histone-to-protamine exchange [ 146 ], acrosome-nucleus attachment via the acroplaxome [ 147 ], and the formation of the annulus, a diffusion barrier between the midpiece and principal piece of the flagellum [ 148 ]. The cellular component morphogenesis pathway regulates large-scale cellular remodeling during spermiogenesis. This involves the reduction of excess cytoplasm [ 149 ], the strategic repositioning of mitochondria to the midpiece [ 145 ], and the elongation and differentiation of spermatids into mature spermatozoa [ 149 ]. Consideration and limitations The genotype-phenotype associations established through three different multi-locus GWAS models, using objective CASA parameters as phenotypes, enhance the power of the study, while the relatively low sample size constitutes a significant limitation. Therefore, a careful evaluation is necessary when considering the use of the SNPs reported here for genomic selection studies. 5. Conclusion This genome-wide association study (GWAS) uncovered several genomic regions and putative causal SNPs linked to fresh semen quality traits in goats. Although further validation in larger populations is warranted to confirm these associations and evaluate their potential for enhancing reproductive performance, the findings lay a solid groundwork for future large-scale studies and contribute meaningful insights into the genetic architecture of reproductive traits in goats. Declarations Acknowledgments The authors would like to acknowledge the invaluable contributions of the staff at the Siirt University Reproductive Biotechnology Center. Funding This study was supported by Siirt University Agriculture and Livestock Specialization Coordination Center with the project number of 2023- IHTVET-04. Ethical statement This study was conducted in compliance with the guidelines of the Animal Experiments Local Ethics Committee and with an experimental protocol approved by the Ethics Committee for the Use of Animals in Research and Experimentation at the Siirt University Animal Research Local Ethic Committee (29.06.2022-2022/15), and the authors complied with the ARRIVE guidelines. Consent for publication Not applicable. Competing interests The authors declare no competing interests. Author contributions AE: Writing – review & editing, Writing – original draft, Data curation, Conceptualization, Project administration. AÇC, AA, KB, RA, SY, KD, ÖG, MK, and VB: Methodology. YY: Writing – review & editing, Writing – original draft, Data curation, Validation, Software, Conceptualization. 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The area shaded in grey indicates the 95% confidence interval under the null hypothesis.\u003c/p\u003e\n\u003cp\u003eA: Semen volume (mL); B: Mass activity (1-4); C: Sperm concentration (×10\u003csup\u003e9\u003c/sup\u003e); D: Total sperm count per ejaculation (×10\u003csup\u003e9\u003c/sup\u003e); E: Total motility (%); F: Progressive motility (%); G: Average path velocity (VAP, µm/s); H: straight-linear velocity (VSL, µm/s); I: curvilinear velocity (VCL, µm/s); J: amplitude of lateral head displacement (ALH, µm); K: beat cross frequency (BCF, Hz); L: straightness (STR, %); M: movement linearity (LIN, %); N: wobble (WOB, %).\u003c/p\u003e","description":"","filename":"Figure1.jpg","url":"https://assets-eu.researchsquare.com/files/rs-6721731/v1/faf0f91c1a8b0a1407b35ab6.jpg"},{"id":84090056,"identity":"e84646ef-b69c-4588-b7d1-52165c8898db","added_by":"auto","created_at":"2025-06-06 16:00:26","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":81426,"visible":true,"origin":"","legend":"\u003cp\u003eChromosomal distribution of the 56,669 markers that passed quality control (QC) procedures.\u003c/p\u003e","description":"","filename":"Figure2.png","url":"https://assets-eu.researchsquare.com/files/rs-6721731/v1/4fcd78b1a5194e0a21724781.png"},{"id":84090064,"identity":"76fc89ec-5adb-463e-82ea-7fbba0cdbe4f","added_by":"auto","created_at":"2025-06-06 16:00:26","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":49879,"visible":true,"origin":"","legend":"\u003cp\u003eA 3D illustration of the first three principal components (PCs).\u003c/p\u003e","description":"","filename":"Figure3.png","url":"https://assets-eu.researchsquare.com/files/rs-6721731/v1/d05f787293f30ff14b4a599e.png"},{"id":84090661,"identity":"5d6b8671-2df9-416e-974b-ce4aaf69c89a","added_by":"auto","created_at":"2025-06-06 16:08:26","extension":"jpeg","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":209888,"visible":true,"origin":"","legend":"\u003cp\u003eIllustration of the correlation analysis between semen parameters.\u003c/p\u003e\n\u003cp\u003eVAP: Average path velocity; VSL: Straight-linear velocity; VCL: Curvilinear velocity; ALH: Amplitude of lateral head displacement; BCF: Beat cross frequency; STR: Straightness; LIN: Movement linearity; WOB: wobble.\u003c/p\u003e","description":"","filename":"Figure4.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-6721731/v1/9c736e71eb661093eac9f35d.jpeg"},{"id":84090682,"identity":"7c4ba903-2309-4d20-b181-eae0fe734086","added_by":"auto","created_at":"2025-06-06 16:08:27","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":196846,"visible":true,"origin":"","legend":"\u003cp\u003eGene enrichment (a) and network analyses (b) of candidate genes located within ±100 Kb of each associated SNP. In (a), dot size represents the number of genes linked to each molecular function (2–6), the x-axis denotes Fold Enrichment (0–50), and color gradient [−log₁₀FDR] indicates statistical significance—ranging from purple (1.35) to red (1.60). In (b), the network visualization illustrates functional relationships among molecular functions: green circles represent nodes [distinct molecular functions], and grey edges indicate functional associations.\u003c/p\u003e","description":"","filename":"Figure5.png","url":"https://assets-eu.researchsquare.com/files/rs-6721731/v1/ed2e70cdca4b08475e505d71.png"},{"id":102496760,"identity":"79466b27-71ed-491e-9782-e0021a374941","added_by":"auto","created_at":"2026-02-12 09:43:24","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":3247012,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6721731/v1/818000f3-5742-42e1-94c9-d441a5f11de9.pdf"},{"id":84090065,"identity":"6b91fde5-1352-43cb-acd9-341fc68f6067","added_by":"auto","created_at":"2025-06-06 16:00:26","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"supplement","size":3503634,"visible":true,"origin":"","legend":"","description":"","filename":"Additionalfile1.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6721731/v1/52c2a30fab3d669cea568fd1.pdf"},{"id":84090061,"identity":"3c7f3b0c-0e90-41b2-9c66-df5bfd2dbd98","added_by":"auto","created_at":"2025-06-06 16:00:26","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":810140,"visible":true,"origin":"","legend":"","description":"","filename":"Additionalfile2.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6721731/v1/efef32f692daa86d2e0d6214.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Dissecting the genetic basis of computer-assisted fresh semen traits in goats using multi-locus genome-wide association methods","fulltext":[{"header":"1. Introduction","content":"\u003cp\u003eGoat farming plays a pivotal role in global agriculture and rural development by offering a multifaceted solution to food security, economic sustenance, and social empowerment. The inherent resiliency and versatile nature of goats, such as their remarkable ability to withstand heat stress and adapt to marginal environments, render them particularly valuable in regions affected by climatic extremes and resource limitations [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eIncreasing the goat population and productivity in underdeveloped and developing countries is considered a critical strategic step [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. Reproductive efficiency is a cornerstone of goat production, directly influencing both the biological value of the animal and the economic viability of goat farming enterprises. High reproductive efficiency, generally measured by parameters such as litter size, age at first kidding, and kidding interval, is vital to maximizing herd productivity, optimizing resource use, and enhancing genetic progress [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e, \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. Efficient reproduction not only increases the number of offspring per doe but also minimizes production costs, thereby strengthening the overall sustainability of goat farming systems. Reproductive efficiency is shaped by the complex interaction between environmental conditions and genetic factors, which together affect various stages of reproduction in both males and females [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eIn recent years, rapidly advancing molecular technologies have enabled the implementation of genomic testing in animal breeding studies and the development of genomic selection methods. Through genomic testing, genes associated with productivity traits in animals can be identified, and the genomic regions detected facilitate the prediction of both the current and heritable productivity characteristics of the animals [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. Genetic factors fundamentally determine reproductive efficiency. However, studies investigating genetic variants associated with fertility have primarily focused on female individuals rather than male animals [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eAlthough animals may have genetically high productivity, they cannot be used as breeding stock unless they can transmit these traits to subsequent generations. Therefore, the reproductive parameters of male breeding animals are regularly monitored. Sperm quality in animals can be influenced by numerous non-genetic factors, including age, nutrition, endocrine dysfunction, season, sperm collection method, and ejaculation frequency [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e], as well as individual genetic factors [\u003cspan additionalcitationids=\"CR10\" citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. Therefore, when environmental factors are standardized among individuals, the remaining variation is assumed to be attributable to genetic factors. Thus, optimizing environmental conditions alone does not guarantee an improvement in spermatological parameters; genetic factors must also be considered.\u003c/p\u003e \u003cp\u003eIn laboratories where sperm production and quality assessments are conducted, the primary parameters evaluated include sperm motility (%), sperm concentration (\u0026times;10\u003csup\u003e9\u003c/sup\u003e/ml), and semen volume (mL) [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. While semen volume and sperm concentration are used to determine the optimal number of spermatozoa per straw, sperm motility is regarded as the principal indicator of an animal\u0026rsquo;s potential fertilization capacity [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eFertility-related parameters in males generally exhibit low to moderate heritability estimates (ranging from 0.05 to 0.22), yet the genetic influence on these traits remains significant [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. Therefore, identifying genetic variations associated with fertility traits\u0026mdash;such as spermatological characteristics\u0026mdash;in conjunction with other production and phenotypic attributes is highly valuable. Understanding the inheritance patterns of these traits can enhance reproductive success through genomic selection and enable the early prediction of the potential fertility of breeding candidates.\u003c/p\u003e \u003cp\u003eImproving sperm quality through selective breeding is an established strategy to achieve higher fertility rates in livestock and other animal populations [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. Hodge et al. [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e] emphasized that elucidating the molecular mechanisms underlying complex reproductive traits may be achieved through the identification of genetic variants.\u003c/p\u003e \u003cp\u003eGenome-wide association studies (GWAS) have become an indispensable tool in goat genetics research, providing insights into the genetic architecture underlying economically relevant traits, including reproductive efficiency. These studies play a crucial role in identifying single nucleotide polymorphisms (SNPs) and candidate genes that influence traits such as litter size, intersexual syndromes, and overall prolificacy, which are paramount for advancing selective breeding programs in goats [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e, \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. Recent GWAS reports have identified SNPs associated with sperm quality parameters in various species, including cattle [\u003cspan additionalcitationids=\"CR20 CR21 CR22 CR23 CR24 CR25\" citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e], pigs [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e, \u003cspan additionalcitationids=\"CR28 CR29 CR30\" citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e], rams [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e, \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e], and humans [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e, \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e, \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eHowever, such studies in goats remain scarce and inadequate, creating a significant knowledge gap in the literature. Despite the importance of understanding these parameters for optimizing production systems, research specifically focused on goats has been notably limited compared to other livestock species. To our knowledge, only two studies exist that address sperm quality traits and reproductive characteristics, highlighting the urgent need for more comprehensive investigations in this area. GWAS studies focusing on goat sperm quality remain limited both in number and in the range of associated parameters investigated. Existing studies have predominantly relied on conventional assessments of sperm motility, concentration [\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e], and semen volume [\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e] for genotype\u0026ndash;phenotype association analyses. To date, no study has investigated the genetic basis of objectively measured sperm parameters derived from Computer-Assisted Sperm Analysis (CASA) in goats. This paucity of research hinders our ability to develop evidence-based management strategies tailored specifically for caprine production systems.\u003c/p\u003e \u003cp\u003eIt is noteworthy that in these association studies, basic/conventional spermatological parameters (such as subjective motility, semen volume, sperm concentration, etc.) are commonly used as phenotypic data. Relying on basic spermatological parameters in association studies represents a pragmatic approach, primarily due to constraints related to cost, feasibility, and the historical availability of such data. While these parameters have proven valuable for elucidating genetic influences on male reproductive performance, incorporating additional, more reliable and objective assessment methods\u0026mdash;such as CASA and flow cytometry\u0026mdash;would enhance the robustness and precision of future findings. CASA, a widely adopted technology in the industry, offers objective evaluation of sperm motility. Several CASA-derived parameters\u0026mdash;such as curvilinear velocity, mean path velocity, and beat-cross frequency\u0026mdash;have been linked to higher \u003cem\u003ein vivo\u003c/em\u003e fertility, underscoring the utility of CASA in assessing semen quality [\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eInvestigating the genetic background of many economically important traits in livestock, the Mixed Linear Model (MLM) has emerged as a frequently employed method that is widely adopted in GWAS. This statistical approach is particularly valued for its ability to correct for confounding factors such as population structure and polygenic background variation, which can otherwise lead to spurious associations and misinterpretation of results. The incorporation of both fixed and random effects within the MLM framework allows researchers to account for complex relationships between individuals and adjust for environmental variables that might influence phenotypic expression. However, because this model evaluates each marker independently in a univariate manner, it may fail to capture the combined effects of multiple loci contributing to complex traits, which are often governed by intricate networks of interacting genes. This fundamental limitation becomes particularly problematic when studying polygenic traits where numerous genetic variants of small effect collectively influence the phenotype [\u003cspan additionalcitationids=\"CR39\" citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThus, the analysis of complex traits through GWAS has prompted the development of several advanced statistical models, with notable examples including the Bayesian-information and Linkage-disequilibrium Iteratively Nested Keyway (BLINK), Fixed and Random Model Circulating Probability Unification (FarmCPU), and the multi-locus mixed model (MLMM). Each of these models is engineered to overcome specific challenges associated with the genetic analysis of quantitative traits.\u003c/p\u003e \u003cp\u003eBLINK is a statistical framework designed to enhance the efficiency of GWAS by leveraging both individual and marker information at a genomic scale. It utilizes linkage disequilibrium (LD) information to handle the inherent complexities of genetic association mapping. BLINK is characterized by its iterative strategy, which identifies associations based on the structure of LD while optimizing the detection process through the inclusion of principal component analysis (PCA) derived covariates to account for population structure. Furthermore, it simplifies the computation of kinship matrices by focusing solely on markers posited to be trait-associated, thereby refining statistical power while controlling for false positives [\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eFarmCPU represents an innovative integration of fixed and random effects models, offering a powerful approach for robust GWAS. It utilizes pseudo quantitative trait nucleotides (QTNs) derived from a method called SUPER, wherein these bins are optimized to reflect genetic variance effectively. The computational efficiency of FarmCPU has been demonstrated to surpass traditional models due to its ability to address both marker-specific kinship and the population structure. This model introduces an iterative process for enhancing statistical power by refining the blueprint of pseudoQTNs and their relationship to underlying genetic architectures. FarmCPU's design notably minimizes the risk of false discovery while maximizing the accuracy of associations, thus providing a comprehensive analytical tool for large-scale genomic datasets [\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eMLMM stands out in the landscape of GWAS methodologies for its capacity to incorporate multiple markers as covariates simultaneously, a crucial advance in controlling for confounding factors such as population stratification and kinship. By implementing a stepwise mixed model approach, MLMM partitions phenotypic variance into genetic and residual components, facilitating a more nuanced understanding of the genetic architectures of complex traits. This method allows for the identification of significant associations while effectively managing Type I errors through rigorous variance component optimization. Additionally, MLMM can be adapted to binary phenotypic responses associated with diseases, making it versatile across different types of traits [\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eIn the present study, three state-of-the-art multi-locus GWAS models\u0026mdash;BLINK, FarmCPU, and MLMM\u0026mdash;were employed to uncover the genetic architecture underlying both conventional and CASA-derived sperm traits in goats. These models were selected for their ability to overcome the limitations of single-locus approaches by simultaneously considering multiple markers, thereby improving the detection of true associations while accounting for population structure, cryptic relatedness, and multiple testing. Ultimately, where applicable, the study aimed to evaluate the potential for genomic selection based on semen quality traits in breeding and artificial insemination bucks.\u003c/p\u003e"},{"header":"2. Materials and methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003e2.1. Material and animal management\u003c/h2\u003e \u003cp\u003eIn this study, a total of 24 goats from three different breeds\u0026mdash;Boer (n\u0026thinsp;=\u0026thinsp;11), Anglo-Nubian (n\u0026thinsp;=\u0026thinsp;8), and Murcia-Granada (n\u0026thinsp;=\u0026thinsp;5)\u0026mdash;aged between 2 and 3 years, were used. The animal material used in this study belongs to Small Ruminant Reproductive Biotechnology Research Center in Siirt, T\u0026uuml;rkiye [37\u0026deg;55\u0026prime;30\u0026Prime; N latitude, 41\u0026deg;56\u0026prime;45\u0026Prime; E longitude; 895 m above sea level]. All experimental procedures were performed at the Small Ruminant Reproductive Biotechnology Research Center. Prior to the initiation of the study, all necessary institutional permissions for the use of animals were obtained from the center. The study material, consisting of all bucks, was maintained under similar feeding, care, and management conditions before and throughout the study period. Before the study, the goats tested negative for \u003cem\u003eMycobacterium Tuberculosis\u003c/em\u003e, \u003cem\u003eMycobacterium Paratuberculosis\u003c/em\u003e, \u003cem\u003eBrucella Melitensis\u003c/em\u003e, \u003cem\u003eLeptospirosis\u003c/em\u003e, \u003cem\u003eBluetongue Virus, Caprine Arthritis Encephalitis Virus\u003c/em\u003e, and \u003cem\u003eBorder Disease Virus\u003c/em\u003e, and their health was confirmed to be satisfactory throughout the study period.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003e2.2. Semen collection and evaluation\u003c/h2\u003e \u003cp\u003eSeven replicate semen samples were collected from each Boer and Anglo-Nubian goat during the breeding season. For the Murcia-Granada goats, five replicate samples were obtained. Semen collection was performed twice a week using an electroejaculation device (e320, Minitube, Tiefenbach, Germany), following the procedure described by Ungerfeld et al. [\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e]. During the procedure, the goats were sedated with intramuscular injections of xylazine (0.22 mg/kg; Ege Vet, Izmir, T\u0026uuml;rkiye) and flunixin meglumine (1.10 mg/kg; Intervet, Istanbul, T\u0026uuml;rkiye). In total, spermatological analyses were performed on 158 ejaculates.\u003c/p\u003e \u003cdiv id=\"Sec5\" class=\"Section3\"\u003e \u003ch2\u003e2.2.1. Sperm examinations\u003c/h2\u003e \u003cp\u003eThe semen samples were immediately transported to the laboratory and placed in a water bath maintained at 32\u0026deg;C. The volume of each ejaculate was measured using a graduated conical tube with 0.1 mL scale intervals. Sperm concentration (per mL) was determined by the photometric method (Ovine-caprine AccuRead, IMV Technologies, France). The total number of sperm per ejaculate was calculated by multiplying the ejaculate volume (mL) by the sperm concentration (sperm/mL). Mass activity of the semen was evaluated using a 4-point scale under a phase-contrast microscope (Eclipse Ci-L, Nikon, Japan) at 10\u0026times; magnification.\u003c/p\u003e \u003cp\u003eFor the evaluation of total motility (MOT, %), progressive motility (pMOT, %), and kinetic velocity parameters [average path velocity (VAP, \u0026micro;m/s), straight-linear velocity (VSL, \u0026micro;m/s), curvilinear velocity (VCL, \u0026micro;m/s), amplitude of lateral head displacement (ALH, \u0026micro;m), beat cross frequency (BCF, Hz), straightness (STR\u0026thinsp;=\u0026thinsp;VSL/VAP), movement linearity (LIN\u0026thinsp;=\u0026thinsp;VSL/VCL, %), and wobble (WOB\u0026thinsp;=\u0026thinsp;VAP/VCL, %)], CASA system (SCA, Microptics, S.L., Version 3.2.0, Barcelona, Spain) specifically calibrated for goat sperm was used. The Basler camera (Basler Vision Tecnologie\u0026trade; ACA1300-200UC, Ahrensburg, Germany), operating at 60 frames per second, was set with an image brightness of 60, contrast of 750, and light intensity of 1000. Threshold settings were defined as follows: VCL\u0026thinsp;\u0026gt;\u0026thinsp;80 \u0026micro;m/s, VSL\u0026thinsp;\u0026gt;\u0026thinsp;50 \u0026micro;m/s, and VAP\u0026thinsp;\u0026gt;\u0026thinsp;25 \u0026micro;m/s. Progressive motility was identified as spermatozoa with STR\u0026thinsp;\u0026gt;\u0026thinsp;80%. Total motility was calculated as the sum of progressive and non-progressive motility percentages [\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e]. Prior to analysis, sperm samples were diluted 1:30 (v/v) in pre-warmed medium (Optixell\u0026reg;). A 3 \u0026micro;L aliquot of each sample was placed on a pre-warmed microscope slide, covered with a coverslip, and positioned on the heated stage (37\u0026deg;C) of a phase-contrast microscope (Eclipse Ci-L, Nikon, Japan) integrated with the CASA system. Each sample was evaluated under a 10\u0026times; negative phase-contrast objective, with at least three different fields scanned and 600\u0026ndash;800 spermatozoa analyzed per sample.\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003e2.3. Genetic analyses\u003c/h2\u003e \u003cdiv id=\"Sec7\" class=\"Section3\"\u003e \u003ch2\u003e2.3.1. Genotyping and Quality Controls\u003c/h2\u003e \u003cp\u003eFor DNA extraction, 5\u0026ndash;6 mL of blood was collected from each animal via aseptic venipuncture of the jugular vein. DNA extraction was performed using a commercial kit (QIAamp\u0026reg; DNA Blood Mini Kit, QIAGEN, Hilden, Germany). Following blood collection, the animals were maintained under standardized care protocols that ensured the continuity of routine husbandry and nutritional management, and no euthanasia/sacrifice procedures were performed.\u003c/p\u003e \u003cp\u003eGenotyping of the goats was performed using the GoatSNP 85K BeadChip on the ILLUMINA platform, achieving an overall genotyping rate of 0.995. Sex chromosomes and markers with unknown genomic positions were excluded from further analysis. Quality control (QC) was conducted using PLINK v1.9 [\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e], applying the following criteria: Minor Allele Frequency (MAF)\u0026thinsp;\u0026ge;\u0026thinsp;0.05, individual missing genotype rate (mind)\u0026thinsp;\u0026le;\u0026thinsp;0.1, SNP call rate\u0026thinsp;\u0026ge;\u0026thinsp;0.95, and Hardy-Weinberg equilibrium (HWE) p-value\u0026thinsp;\u0026ge;\u0026thinsp;1\u0026times;10E-6. After QC, a total of 56,669 markers were retained for downstream analyses.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section3\"\u003e \u003ch2\u003e2.3.2. Association Study\u003c/h2\u003e \u003cp\u003eBLINK, FarmCPU, and MLMM, which collectively represent advancements in statistical modelling designed to address the complexities of GWAS, were therefore employed in this study to investigate the genetic basis of semen parameters in bucks.\u003c/p\u003e \u003cp\u003ePrior to conducting the analyses, the normality of all parameters was assessed using the Anderson-Darling test. The supplementary data confirmed that all analyzed parameters followed a normal distribution (see Additional file 1). For the GWAS, multi-locus models\u0026mdash;BLINK, FarmCPU, and MLMM\u0026mdash;were implemented using the GAPIT v3 R package [\u003cspan additionalcitationids=\"CR42\" citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e]. This package not only enables analyses with all three models but also facilitates the construction of the genomic relationship matrix (GRM) and the execution of Principal Component Analysis (PCA). To account for potential systematic bias due to cryptic kinship, the GRM was incorporated into each model. Breed, as a fixed effect, was incorporated into the multi-locus models as a covariate, while the first five principal components (PCs) were also included to control for population stratification. Following the analyses, genomic inflation factors (λ) were calculated using QCEWAS v1.2 R package [\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e] to evaluate potential inflation in test statistics, and Quantile-Quantile (QQ) plots were generated (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). Manhattan plots were also employed to visualize the results (see Additional file 2).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec9\" class=\"Section3\"\u003e \u003ch2\u003e2.3.3. Genomic Annotation, Gene Ontology, and Pathway Analysis\u003c/h2\u003e \u003cp\u003eGene annotation was carried out based on the \u003cem\u003eCapra hircus\u003c/em\u003e ARS1 genome assembly using the Ensembl database (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.ensembl.org/index.html\u003c/span\u003e\u003cspan address=\"https://www.ensembl.org/index.html\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e). To explore the functional relevance of the identified loci, genes located within a\u0026thinsp;\u0026plusmn;\u0026thinsp;100 Kb window of each significant SNP were subjected to further investigation. Functional enrichment analyses, including Gene Ontology (GO) terms and biological pathways, were performed using the ShinyGO platform [\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e], referencing the \u003cem\u003eCapra hircus\u003c/em\u003e ARS1 genome. Statistical significance was assessed using a false discovery rate (FDR) threshold of 0.05. Visual representations of enriched pathways and gene interaction networks were generated within the same framework.\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003e2.4. Statistical analyses\u003c/h2\u003e \u003cp\u003eStatistical analyses were performed using SPSS Version 22.0 for Windows (SPSS Inc., Chicago, IL, USA). Spermatological parameters were checked for normality and homogeneity. The one-way analysis of variance (ANOVA) test was conducted for the statistical analysis of spermatological examination results, followed by the Duncan test for post hoc comparison of means. Relationships among the parameters were evaluated using the Pearson correlation test. The results are presented as mean\u0026thinsp;\u0026plusmn;\u0026thinsp;standard error (SE). Differences with p values less than 0.05 were considered statistically significant (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05).\u003c/p\u003e \u003c/div\u003e"},{"header":"3. Results","content":"\u003cp\u003eAccording to the data presented in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e, spermatological parameters during the breeding season were assessed across three goat breeds. Boer goats had the highest ejaculate volume (mL) (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05). Anglo-Nubian goats showed significantly higher sperm concentration (\u0026times;10⁹) than both Boer and Murcia-Granada breeds (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05), whereas no significant difference was found between Boer and Murcia-Granada (p\u0026thinsp;\u0026gt;\u0026thinsp;0.05). In terms of total sperm count per ejaculate (\u0026times;10⁹), Boer and Anglo-Nubian breeds had significantly higher values than Murcia-Granada (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05), with no significant difference between the former two (p\u0026thinsp;\u0026gt;\u0026thinsp;0.05). Mass motility (1\u0026ndash;4), total and progressive motility (%), and all kinetic parameters\u0026mdash;VAP, VSL, VCL (\u0026micro;m/s), ALH (\u0026micro;m), BCF (Hz), STR (%), and LIN (%)\u0026mdash;were statistically similar among breeds (p\u0026thinsp;\u0026gt;\u0026thinsp;0.05), except for WOB (%), which was significantly higher in Boer compared to Murcia-Granada (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05). No differences in WOB were found between Boer and Anglo-Nubian or between Anglo-Nubian and Murcia-Granada (p\u0026thinsp;\u0026gt;\u0026thinsp;0.05).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eMacroscopic and CASA spermatological parameters of Boer, Anglo-Nubian, and Murcia-Granada fresh semen (Mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SE).\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eParameters\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBoer (n\u0026thinsp;=\u0026thinsp;11)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eAnglo-Nubian (n\u0026thinsp;=\u0026thinsp;8)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eMurcia-Granada (n\u0026thinsp;=\u0026thinsp;5)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSemen volume (mL)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.85\u0026thinsp;\u0026plusmn;\u0026thinsp;0.87\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.34\u0026thinsp;\u0026plusmn;\u0026thinsp;0.13\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.98\u0026thinsp;\u0026plusmn;\u0026thinsp;0.15\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eConcentration (\u0026times;10\u003c/b\u003e\u003csup\u003e\u003cb\u003e9\u003c/b\u003e\u003c/sup\u003e\u003cb\u003e/mL)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.19\u0026thinsp;\u0026plusmn;\u0026thinsp;0.06\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.56\u0026thinsp;\u0026plusmn;\u0026thinsp;0.11\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.24\u0026thinsp;\u0026plusmn;\u0026thinsp;0.11\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eTotal sperm count (\u0026times;10\u003c/b\u003e\u003csup\u003e\u003cb\u003e9\u003c/b\u003e\u003c/sup\u003e\u003cb\u003e)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3.46\u0026thinsp;\u0026plusmn;\u0026thinsp;0.22\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3.74\u0026thinsp;\u0026plusmn;\u0026thinsp;0.37\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.44\u0026thinsp;\u0026plusmn;\u0026thinsp;0.26\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eMass activity (1\u0026ndash;4)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.97\u0026thinsp;\u0026plusmn;\u0026thinsp;0.08\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3.21\u0026thinsp;\u0026plusmn;\u0026thinsp;0.09\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3.16\u0026thinsp;\u0026plusmn;\u0026thinsp;0.16\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eTotal motility (%)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e94.11\u0026thinsp;\u0026plusmn;\u0026thinsp;0.78\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e94.31\u0026thinsp;\u0026plusmn;\u0026thinsp;0.55\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e93.88\u0026thinsp;\u0026plusmn;\u0026thinsp;0.76\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eProgressive motility (%)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e63.04\u0026thinsp;\u0026plusmn;\u0026thinsp;1.31\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e62.50\u0026thinsp;\u0026plusmn;\u0026thinsp;1.31\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e61.57\u0026thinsp;\u0026plusmn;\u0026thinsp;1.71\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eVAP (\u0026micro;m/s)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e124.86\u0026thinsp;\u0026plusmn;\u0026thinsp;3.28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e120.98\u0026thinsp;\u0026plusmn;\u0026thinsp;4.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e115.43\u0026thinsp;\u0026plusmn;\u0026thinsp;4.68\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eVSL (\u0026micro;m/s)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e105.32\u0026thinsp;\u0026plusmn;\u0026thinsp;2.97\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e102.58\u0026thinsp;\u0026plusmn;\u0026thinsp;3.55\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e96.66\u0026thinsp;\u0026plusmn;\u0026thinsp;3.93\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eVCL (\u0026micro;m/s)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e177.61\u0026thinsp;\u0026plusmn;\u0026thinsp;5.50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e174.56\u0026thinsp;\u0026plusmn;\u0026thinsp;6.61\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e173.25\u0026thinsp;\u0026plusmn;\u0026thinsp;8.03\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eALH (\u0026micro;m)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3.01\u0026thinsp;\u0026plusmn;\u0026thinsp;0.10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3.00\u0026thinsp;\u0026plusmn;\u0026thinsp;0.11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3.05\u0026thinsp;\u0026plusmn;\u0026thinsp;0.13\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eBCF (Hz)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e20.37\u0026thinsp;\u0026plusmn;\u0026thinsp;0.49\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e20.61\u0026thinsp;\u0026plusmn;\u0026thinsp;0.52\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e20.24\u0026thinsp;\u0026plusmn;\u0026thinsp;0.65\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSTR (%)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e79.22\u0026thinsp;\u0026plusmn;\u0026thinsp;0.68\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e78.48\u0026thinsp;\u0026plusmn;\u0026thinsp;0.69\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e78.24\u0026thinsp;\u0026plusmn;\u0026thinsp;0.82\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eLIN (%)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e59.20\u0026thinsp;\u0026plusmn;\u0026thinsp;1.10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e57.00\u0026thinsp;\u0026plusmn;\u0026thinsp;1.09\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e55.36\u0026thinsp;\u0026plusmn;\u0026thinsp;1.43\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eWOB (%)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e71.08\u0026thinsp;\u0026plusmn;\u0026thinsp;0.92\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e69.08\u0026thinsp;\u0026plusmn;\u0026thinsp;0.94\u003csup\u003eab\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e67.37\u0026thinsp;\u0026plusmn;\u0026thinsp;1.26\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"4\"\u003e\u003csup\u003eabc\u003c/sup\u003e: Different literals within lines mean statistical differences, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05. VAP, average path velocity; VSL, straight-linear velocity; VCL, curvilinear velocity; ALH, amplitude of lateral head displacement; BCF, beat cross frequency; STR, straightness; LIN, movement linearity; WOB, wobble.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eThe chromosomal distribution of the 56,669 markers that passed the QC procedures is presented in Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eExamination of the population structure revealed five distinct genetic clusters based on the first three principal components (PCs), which together accounted for approximately 44% of the total genetic variation (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). This substantial proportion of explained variation indicates a pronounced population structure within the dataset. Given that the sample consisted of unrelated individuals from three different breeds, the presence of strong genetic differentiation among groups is expected. Such a clear stratification underscores the importance of accounting for breed effects and underlying genetic structure in the GWAS models to avoid confounding and spurious associations.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eAccording to the multi-locus GWAS results, while the BLINK and FarmCPU models effectively accounted for population stratification and/or cryptic kinship for all parameters, the MLMM model failed to adequately correct for these factors in the analysis of total motility, VAP, VLC, BCF, STR, and WOB. Therefore, the MLMM results for these traits are not presented here. Consequently, only the association results from all three multi-locus models with genomic inflation factor (λ) values between 0.95 and 1.05 across all 14 semen parameters were considered for interpretation.\u003c/p\u003e \u003cp\u003eThe GWAS results identified 98 SNPs associated with various semen parameters (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). Gene annotation within \u0026plusmn;\u0026thinsp;100 Kb of each SNP revealed 49 genes, with their associated traits presented in Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e. Notably, seven SNPs were associated with more than one parameter. Two of these were associated with STR and LIN, four with LIN and WOB, and one with total and progressive motility. To enhance the accuracy of genotype\u0026ndash;phenotype associations, correlation analysis among semen traits was also conducted to support the identification of genes linked to multiple parameters (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e). A strong positive correlation was observed between STR and LIN, as well as between LIN and WOB (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). Additionally, total motility and progressive motility were positively correlated (p\u0026thinsp;\u0026lt;\u0026thinsp;0.01). Therefore, it seems plausible that a SNP could be associated with two positively correlated traits.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eAssociated SNPs that identified three multi-locus methods.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"10\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c10\" colnum=\"10\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePhenotype\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMethod\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSNP\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eCHR\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eBP\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cem\u003ep\u003c/em\u003e-value\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eBeta\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003eMAF\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c9\"\u003e \u003cp\u003eAllele\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c10\"\u003e \u003cp\u003eAssociation type\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"14\" rowspan=\"15\"\u003e \u003cp\u003eVolume\u003c/p\u003e \u003cp\u003e(mL)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBLINK\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003esnp35236-scaffold422-1121897\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e122400178\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2,56E-05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-1,006\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e0,15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eG\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eCHR wide\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFarmCPU\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2,56E-05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-1,006\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMLMM\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e6,35E-05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-1,006\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBLINK\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003esnp5343-scaffold1185-90259\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e285102\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e4,78E-05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0,695\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0,25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eG\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eCHR wide\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFarmCPU\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e4,78E-05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0,695\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMLMM\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003esnp9844-scaffold1352-23038\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e97704927\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2,47E-05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-0,555\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0,23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003eCHR wide\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBLINK\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003esnp51942-scaffold764-72415\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e23255940\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2,70E-05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-0,652\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0,27\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eG\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eCHR wide\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFarmCPU\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2,70E-05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-0,652\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMLMM\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003esnp51985-scaffold764-1931368\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e25105228\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e3,31E-05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-0,501\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0,33\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003eCHR wide\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBLINK\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003esnp11194-scaffold1400-52817\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e63215096\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e4,52E-05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-0,735\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0,42\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eCHR wide\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFarmCPU\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e4,52E-05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-0,735\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMLMM\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003esnp8082-scaffold1293-900596\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e81887040\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e8,35E-05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-0,626\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0,40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eG\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003eCHR wide\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBLINK\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003esnp39373-scaffold500-335693\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e22105436\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e4,06E-05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0,807\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0,35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eCHR wide\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFarmCPU\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e4,06E-05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0,807\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMLMM\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e22_48206613_AF-PAKI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e48206613\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e8,47E-05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-0,543\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0,42\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eG\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003eCHR wide\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"7\" rowspan=\"8\"\u003e \u003cp\u003eMass activity\u003c/p\u003e \u003cp\u003e(1\u0026ndash;4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMLMM\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003esnp16950-scaffold177-869780\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e123284237\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e7,18E-05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-0,218\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0,38\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eG\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003eCHR wide\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBLINK\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003esnp7782-scaffold128-754268\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e55242185\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e9,81E-05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-0,565\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e0,46\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eG\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eCHR wide\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFarmCPU\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e9,81E-05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-0,565\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMLMM\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e2,99E-09\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-0,619\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e\u003cb\u003eGenome wide\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMLMM\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003esnp3729-scaffold112-2926089\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e62332705\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e3,13E-05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-0,205\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0,50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eG\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003eCHR wide\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMLMM\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003esnp6468-scaffold123-403108\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e34183983\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e1,36E-06\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-0,485\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0,44\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e\u003cb\u003eSuggestive\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMLMM\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003esnp3410-scaffold1103-101967\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e52616716\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e6,35E-05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-0,199\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0,35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003eCHR wide\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMLMM\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003esnp1044-scaffold1028-386572\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e39162602\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e5,63E-05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0,257\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0,35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003eCHR wide\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"8\" rowspan=\"9\"\u003e \u003cp\u003eConcentration\u003c/p\u003e \u003cp\u003e(\u0026times;10\u003csup\u003e9\u003c/sup\u003e/mL)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMLMM\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003esnp38986-scaffold494-4405023\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e41767359\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e7,10E-06\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0,533\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0,29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e\u003cb\u003eSuggestive\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBLINK\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003esnp2475-scaffold107-8145419\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e84371248\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e3,42E-05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0,797\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e0,31\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eCHR wide\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFarmCPU\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e3,42E-05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0,797\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMLMM\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e2,81E-07\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0,705\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e\u003cb\u003eGenome wide\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMLMM\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7_24258258\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e24258258\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e7,62E-05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-0,231\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0,46\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eG\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003eCHR wide\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBLINK\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003esnp17472-scaffold1807-99659\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e863011\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e3,49E-05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0,562\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0,44\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eCHR wide\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFarmCPU\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e3,49E-05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0,562\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMLMM\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003esnp4635-scaffold1149-659137\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e39920786\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1,77E-05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-0,328\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0,40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003eCHR wide\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMLMM\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003esnp25274-scaffold2598-218661\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e58428724\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2,72E-05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0,306\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0,46\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eG\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003eCHR wide\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"16\" rowspan=\"17\"\u003e \u003cp\u003eTotal\u003c/p\u003e \u003cp\u003esperm count\u003c/p\u003e \u003cp\u003e(\u0026times;10\u003csup\u003e9\u003c/sup\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMLMM\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4_99044606\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e99044606\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e4,71E-05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-1,078\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0,33\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003eCHR wide\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMLMM\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003esnp24926-scaffold255-744265\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e100269334\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e3,23E-05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0,913\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0,48\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eG\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003eCHR wide\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBLINK\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003esnp38904-scaffold494-615717\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e37963800\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2,53E-05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-1,506\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0,44\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eCHR wide\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFarmCPU\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2,53E-05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-1,506\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBLINK\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003esnp43484-scaffold579-5242102\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e61084856\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e7,01E-05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-2,229\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0,50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eG\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eCHR wide\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFarmCPU\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e7,01E-05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-2,229\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBLINK\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003esnp6065-scaffold1214-284375\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e4999651\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e7,49E-05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1,744\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0,48\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eCHR wide\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFarmCPU\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e7,49E-05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1,744\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBLINK\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003esnp43351-scaffold578-578990\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e47954912\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e6,15E-05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-1,805\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0,40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eG\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eCHR wide\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFarmCPU\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e6,15E-05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-1,805\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBLINK\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003esnp6575-scaffold1234-59930\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e58622476\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e4,42E-05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-1,880\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0,40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eCHR wide\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFarmCPU\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e4,42E-05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-1,880\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBLINK\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003esnp58693-scaffold957-211283\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e38564501\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2,36E-05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-1,301\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e0,42\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eG\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eCHR wide\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFarmCPU\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2,36E-05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-1,301\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMLMM\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e3,58E-05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-1,301\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBLINK\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003esnp58695-scaffold957-295440\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e38479922\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e7,24E-05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e2,080\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0,44\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eCHR wide\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFarmCPU\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e7,24E-05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e2,080\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"26\" rowspan=\"27\"\u003e \u003cp\u003eTotal motility\u003c/p\u003e \u003cp\u003e(%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFarmCPU\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eGoatD01.024190\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e133947992\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e7,11E-05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e8,553\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0,15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eG\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003eCHR wide\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBLINK\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003esnp15726-scaffold1652-791798\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e27716205\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e8,54E-07\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-1,414\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0,38\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e\u003cb\u003eGenome wide\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBLINK\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003esnp20372-scaffold202-336144\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e105501498\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2,26E-05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-0,810\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0,23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eG\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003eCHR wide\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFarmCPU\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eGoatD01.052225_v2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e30760584\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e4,92E-05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e8,119\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0,10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003eCHR wide\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBLINK\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003esnp52129-scaffold771-1016279\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e46982221\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e1,60E-15\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e11,710\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0,13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eG\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cb\u003eGenome wide\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFarmCPU\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e5,66E-07\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e11,810\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFarmCPU\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003esnp53996-scaffold821-424571\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e41873350\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e7,39E-07\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e11,804\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0,46\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e\u003cb\u003eGenome wide\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFarmCPU\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003esnp30598-scaffold339-1734537\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e63549163\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2,51E-05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e4,415\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0,25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003eCHR wide\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFarmCPU\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003esnp59874-scaffold995-2507995\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e77148449\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e7,46E-05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e9,178\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0,08\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eG\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003eCHR wide\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFarmCPU\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003esnp993-scaffold1026-156620\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e70907910\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e7,15E-05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e8,397\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0,38\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003eCHR wide\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBLINK\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003esnp9098-scaffold133-1208420\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e18330706\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e7,22E-05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-0,741\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0,35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eG\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003eCHR wide\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFarmCPU\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003esnp9251-scaffold1336-1612195\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e7146179\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e4,71E-05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-8,030\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0,33\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003eCHR wide\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBLINK\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eA792\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e64562445\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e6,25E-05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0,696\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0,46\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eG\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003eCHR wide\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFarmCPU\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eGoatD01.022536\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e53517877\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e8,88E-05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-6,687\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0,25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eG\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003eCHR wide\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFarmCPU\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eLoF409\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e33753596\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e7,46E-05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e9,178\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0,08\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003eCHR wide\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFarmCPU\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eLoF612\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e37774237\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e7,46E-05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e9,178\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0,08\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eT\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003eCHR wide\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFarmCPU\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003esnp8651-scaffold131-3195017\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e56193227\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e3,35E-05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e4,498\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0,21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eG\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003eCHR wide\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFarmCPU\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003esnp23992-scaffold244-245992\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e26470696\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2,87E-05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e9,893\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0,46\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eG\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003eCHR wide\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFarmCPU\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003esnp38526-scaffold488-10203\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e41369930\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2,00E-05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e8,625\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0,44\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eG\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003eCHR wide\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBLINK\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003esnp4873-scaffold1163-331369\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e16549290\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e9,30E-05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-0,636\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0,33\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003eCHR wide\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFarmCPU\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003esnp10992-scaffold1395-169570\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e36704386\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e3,07E-05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-8,302\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0,23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003eCHR wide\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFarmCPU\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eGoatD01.006091\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e43081967\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e7,46E-05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e9,178\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0,08\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eG\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003eCHR wide\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBLINK\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003esnp4538-scaffold1146-363529\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e18313706\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e5,37E-07\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1,975\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0,21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e\u003cb\u003eGenome wide\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFarmCPU\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003esnp59320-scaffold975-1213737\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e36114720\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e7,46E-05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e9,178\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0,08\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003eCHR wide\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBLINK\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003esnp2218-scaffold1068-446882\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e27\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e652034\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1,14E-05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-0,701\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0,23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eG\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003eCHR wide\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFarmCPU\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003esnp14549-scaffold1587-647949\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e47667204\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e5,99E-06\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e8,398\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0,13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e\u003cb\u003eSuggestive\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFarmCPU\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003esnp25314-scaffold2606-438718\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e45709872\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e5,66E-07\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e11,810\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0,13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e\u003cb\u003eGenome wide\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"11\" rowspan=\"12\"\u003e \u003cp\u003eProgressive\u003c/p\u003e \u003cp\u003emotility\u003c/p\u003e \u003cp\u003e(%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMLMM\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3_38161381\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e38161381\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e7,35E-05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-6,893\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0,40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003eCHR wide\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBLINK\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003esnp7363-scaffold1269-4371892\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e49696660\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e9,86E-05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-8,988\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0,38\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eCHR wide\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFarmCPU\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e9,86E-05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-8,988\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMLMM\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003esnp58321-scaffold947-1587606\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e68167372\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e3,61E-05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e7,056\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0,42\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003eCHR wide\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBLINK\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003esnp36763-scaffold445-3253592\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e49010309\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e9,08E-05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e10,484\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0,25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eG\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eCHR wide\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFarmCPU\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e9,08E-05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e10,484\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMLMM\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003esnp19685-scaffold1986-1695739\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e3050709\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e9,16E-05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e7,521\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0,38\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003eCHR wide\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBLINK\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003esnp23992-scaffold244-245992\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e26470696\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2,51E-05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e21,662\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e0,46\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eG\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eCHR wide\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFarmCPU\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2,51E-05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e21,662\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMLMM\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e3,59E-05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e21,662\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBLINK\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eGoatD01.044219_v2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e67138199\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e3,37E-05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e8,542\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0,33\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eCHR wide\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFarmCPU\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e3,37E-05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e8,542\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003eVAP\u003c/p\u003e \u003cp\u003e(\u0026micro;m/s)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBLINK\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003esnp38110-scaffold4753-76823\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e114594989\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e5,83E-05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-13,704\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0,50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eCHR wide\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFarmCPU\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e5,83E-05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-13,704\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBLINK\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eA1575\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e43746225\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e9,82E-05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-21,090\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0,46\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eCHR wide\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFarmCPU\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e9,82E-05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-21,090\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003eVSL\u003c/p\u003e \u003cp\u003e(\u0026micro;m/s)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBLINK\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003esnp43478-scaffold579-5029795\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e61297537\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e7,12E-05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-18,313\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0,42\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eG\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003eCHR wide\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFarmCPU\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e7,12E-05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-18,313\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBLINK\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003esnp49837-scaffold711-2598917\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e18780503\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e9,99E-05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-19,869\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0,38\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003eCHR wide\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFarmCPU\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e9,99E-05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-19,869\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"9\" rowspan=\"10\"\u003e \u003cp\u003eVCL\u003c/p\u003e \u003cp\u003e(\u0026micro;m/s)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBLINK\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003esnp2775-scaffold1080-665\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e102038298\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1,50E-05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e17,951\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0,44\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eCHR wide\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFarmCPU\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1,50E-05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e17,951\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBLINK\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003esnp38110-scaffold4753-76823\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e114594989\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2,39E-05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-16,023\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0,50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eG\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eCHR wide\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFarmCPU\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2,39E-05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-16,023\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBLINK\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003esnp1170-scaffold1030-1260582\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e76170101\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e9,63E-05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-26,272\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0,33\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eCHR wide\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFarmCPU\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e9,63E-05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-26,272\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBLINK\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003esnp29978-scaffold327-1284363\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e16340012\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1,34E-05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e25,362\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0,33\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eCHR wide\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFarmCPU\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1,34E-05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e25,362\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBLINK\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eA1575\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e43746225\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1,60E-05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-25,383\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0,46\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eCHR wide\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFarmCPU\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1,60E-05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-25,383\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"17\" rowspan=\"18\"\u003e \u003cp\u003eALH\u003c/p\u003e \u003cp\u003e(\u0026micro;m)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBLINK\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003esnp57642-scaffold923-1345250\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e80592997\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e4,94E-05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-0,425\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0,44\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eG\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eCHR wide\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFarmCPU\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e4,94E-05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-0,425\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMLMM\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003esnp15905-scaffold167-936306\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e36389985\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e5,89E-05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-0,144\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0,10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eG\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003eCHR wide\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMLMM\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6_13684715\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e13684715\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e9,08E-05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0,057\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0,38\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003eCHR wide\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMLMM\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003esnp24565-scaffold25-173044\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e19463548\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e8,06E-09\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0,246\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0,23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eG\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e\u003cb\u003eGenome wide\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBLINK\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003esnp18149-scaffold185-14576357\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e35200343\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e8,47E-05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-0,382\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0,29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eCHR wide\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFarmCPU\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e8,47E-05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-0,382\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBLINK\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e14_37245469\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e37245469\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e4,40E-05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-0,419\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0,38\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eT\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eCHR wide\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFarmCPU\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e4,40E-05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-0,419\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBLINK\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003esnp46140-scaffold636-264016\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e60702098\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1,65E-05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-0,313\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0,46\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eG\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eCHR wide\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFarmCPU\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1,65E-05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-0,313\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMLMM\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003esnp45763-scaffold628-558823\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e39665713\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e7,56E-05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0,051\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0,50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eG\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003eCHR wide\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBLINK\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e17_15100698\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e15100698\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e6,85E-05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0,276\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0,46\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eCHR wide\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFarmCPU\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e6,85E-05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0,276\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBLINK\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003esnp48755-scaffold692-975828\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e46351526\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e6,63E-05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0,301\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e0,40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eCHR wide\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFarmCPU\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e6,63E-05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0,301\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMLMM\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e1,10E-11\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0,277\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e\u003cb\u003eGenome wide\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMLMM\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003esnp53185-scaffold800-210113\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e27412359\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e4,34E-05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0,060\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0,40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003eCHR wide\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"7\" rowspan=\"8\"\u003e \u003cp\u003eBCF\u003c/p\u003e \u003cp\u003e(Hz)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBLINK\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003esnp58914-scaffold965-443131\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e10256970\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e4,37E-05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e2,232\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0,31\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eCHR wide\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFarmCPU\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e4,37E-05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e2,232\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBLINK\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003esnp26630-scaffold2784-22752\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e92623887\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e4,53E-05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e3,705\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0,23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eCHR wide\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFarmCPU\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e4,53E-05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e3,705\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBLINK\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003esnp9775-scaffold135-3133622\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e26001683\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e9,90E-05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-3,345\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0,40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eG\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eCHR wide\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFarmCPU\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e9,90E-05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-3,345\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBLINK\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003esnp55623-scaffold862-1529277\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e23110814\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e3,85E-05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e2,555\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0,35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eG\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eCHR wide\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFarmCPU\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e3,85E-05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e2,555\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"9\" rowspan=\"10\"\u003e \u003cp\u003eSTR\u003c/p\u003e \u003cp\u003e(%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBLINK\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e1_99698938\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e99698938\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e7,19E-05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e3,761\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0,48\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eCHR wide\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFarmCPU\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e7,19E-05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e3,761\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBLINK\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003esnp56631-scaffold895-535141\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e13915\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e7,47E-05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e4,638\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0,25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eCHR wide\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFarmCPU\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e7,47E-05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e4,638\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBLINK\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003esnp2385-scaffold107-4230753\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e80455454\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e6,02E-05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-7,751\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0,15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eCHR wide\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFarmCPU\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e6,02E-05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-7,751\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBLINK\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eGoatD01.044219_v2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e67138199\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e7,52E-05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e3,700\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0,33\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eCHR wide\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFarmCPU\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e7,52E-05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e3,700\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBLINK\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003esnp15610-scaffold165-834474\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e56176354\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e6,39E-05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e4,491\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0,17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eCHR wide\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFarmCPU\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e6,39E-05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e4,491\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"20\" rowspan=\"21\"\u003e \u003cp\u003eLIN\u003c/p\u003e \u003cp\u003e(%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBLINK\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e1_88732772_AF-PAKI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e88732772\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e9,18E-05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e6,376\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0,44\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eCHR wide\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFarmCPU\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e9,18E-05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e6,376\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBLINK\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e1_99698938\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e99698938\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e7,84E-05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e6,057\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0,48\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eCHR wide\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFarmCPU\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e7,84E-05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e6,057\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMLMM\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3_92567967\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e92567967\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e9,61E-05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e3,729\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0,48\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eG\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003eCHR wide\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBLINK\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003esnp34388-scaffold404-485812\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e115826699\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e5,17E-05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e6,839\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0,48\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eCHR wide\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFarmCPU\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e5,17E-05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e6,839\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBLINK\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003esnp56732-scaffold898-750442\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e113829449\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e5,06E-05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e6,482\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0,25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eG\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eCHR wide\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFarmCPU\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e5,06E-05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e6,482\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBLINK\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003esnp2385-scaffold107-4230753\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e80455454\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e8,38E-05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-12,377\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0,15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eCHR wide\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFarmCPU\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e8,38E-05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-12,377\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBLINK\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003esnp9047-scaffold1329-313566\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e36127871\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e7,01E-05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-10,645\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0,23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eG\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eCHR wide\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFarmCPU\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e7,01E-05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-10,645\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBLINK\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e11_59883656\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e59883656\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e3,53E-05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-6,155\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e0,50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eT\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eCHR wide\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFarmCPU\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e3,53E-05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-6,155\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMLMM\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e4,99E-05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-6,155\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMLMM\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003esnp47857-scaffold674-659869\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e94209933\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2,93E-05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-3,404\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0,38\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eG\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003eCHR wide\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBLINK\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003esnp27852-scaffold299-1799687\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e75206653\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e7,82E-05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-5,615\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0,50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eG\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eCHR wide\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFarmCPU\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e7,82E-05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-5,615\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBLINK\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eGoatD01.024417\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e8289498\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e8,47E-05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e9,745\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0,25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eG\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eCHR wide\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFarmCPU\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e8,47E-05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e9,745\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"13\" rowspan=\"14\"\u003e \u003cp\u003eWOB\u003c/p\u003e \u003cp\u003e(%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBLINK\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003esnp34388-scaffold404-485812\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e115826699\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e4,36E-05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e5,389\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0,48\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eCHR wide\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFarmCPU\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e4,36E-05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e5,389\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBLINK\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003esnp56732-scaffold898-750442\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e113829449\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e8,73E-05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e4,983\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0,25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eG\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eCHR wide\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFarmCPU\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e8,73E-05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e4,983\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBLINK\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003esnp9047-scaffold1329-313566\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e36127871\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e4,98E-05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-8,439\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0,23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eG\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eCHR wide\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFarmCPU\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e4,98E-05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-8,439\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBLINK\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e11_59883656\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e59883656\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2,36E-05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-4,881\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0,50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eT\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eCHR wide\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFarmCPU\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2,36E-05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-4,881\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBLINK\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003esnp20770-scaffold204-3864726\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e77724268\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e3,50E-05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e5,714\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0,38\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eG\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eCHR wide\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFarmCPU\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e3,50E-05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e5,714\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBLINK\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003esnp27852-scaffold299-1799687\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e75206653\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e9,13E-05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-4,376\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0,50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eG\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eCHR wide\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFarmCPU\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e9,13E-05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-4,376\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBLINK\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eGoatD01.024417\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e8289498\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e5,92E-05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e7,733\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0,25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eG\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eCHR wide\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFarmCPU\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e5,92E-05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e7,733\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"10\"\u003eSNP: Single nucleotide polymorphism; CHR: Chromosome; BP: Base pair position; MAF: Minor allele frequency; VAP: Average path velocity; VSL: Straight-linear velocity; VCL: Curvilinear velocity; ALH: Amplitude of lateral head displacement; BCF: Beat cross frequency; STR: Straightness; LIN: Movement linearity; WOB: wobble.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eAnnotation of genes located within a\u0026thinsp;\u0026plusmn;\u0026thinsp;100 Kb window of associated SNPs.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCHR\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMarker\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003ers ID\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eGenes\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eLocalization\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003ePhenotype\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eGoatD01.024190\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003ena\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cem\u003eEPHB1\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eIntron\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eTotal motility\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e1_99698938\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003ena\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003eZBBX\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003eDownstream\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003eSTR, LIN\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003esnp20372-scaffold202-336144\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003ers268252883\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cem\u003eCSRNP3\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eIntron\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eTotal motility\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003esnp57642-scaffold923-1345250\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003ers268289163\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cem\u003eLRP1B\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eIntron\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eALH\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003esnp35236-scaffold422-1121897\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003ers268267360\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cem\u003eDNAJC10\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eUpstream\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eVolume\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3_38161381\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003ena\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cem\u003eATG4C\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eIntron\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eProgressive motility\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003esnp15905-scaffold167-936306\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003ers268248620\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cem\u003eNFIA\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eIntron\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eALH\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3_92567967\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003ena\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cem\u003eNGF\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eUpstream\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eLIN\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003esnp34388-scaffold404-485812\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003ers268266522\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003eCOBL\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003eIntron\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003eLIN, WOB\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003esnp24926-scaffold255-744265\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003ers268257313\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cem\u003eTMEM106B\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eUpstream\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eTotal sperm count\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003esnp2385-scaffold107-4230753\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003ers268235451\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003ePTHLH\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003eIntron\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003eSTR, LIN\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003esnp9047-scaffold1329-313566\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003ers268241950\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003eTMEM117\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003eIntron\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003eLIN, WOB\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eGoatD01.052225_v2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003ena\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cem\u003eKANSL2\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eUpstream\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eTotal motility\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003esnp2775-scaffold1080-665\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003ers268235829\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cem\u003ePTPN13\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eIntron\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eVCL\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003esnp9844-scaffold1352-23038\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003ers268242725\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cem\u003eENOPH1\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eIntron\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eVolume\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003esnp7363-scaffold1269-4371892\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003ers268240304\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cem\u003eAFAP1L1\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eIntron\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eProgressive motility\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003esnp51942-scaffold764-72415\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003ers268283606\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cem\u003eHACD4\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eIntron\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eVolume\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003esnp51985-scaffold764-1931368\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003ers268283648\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cem\u003eSAXO1\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eIntron\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eVolume\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003esnp43478-scaffold579-5029795\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003ers268275364\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cem\u003ePDE7B\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eIntron\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eVSL\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003esnp43484-scaffold579-5242102\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003ers268275370\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cem\u003ePDE7B\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eIntron\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eTotal sperm count\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003esnp58914-scaffold965-443131\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003ers268290402\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cem\u003eDOP1A\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eIntron\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eVAP\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003esnp9098-scaffold133-1208420\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003ers268242000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cem\u003eNUMB\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eIntron\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eTotal motility\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003esnp11194-scaffold1400-52817\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003ers268244035\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cem\u003eMDGA2\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eDownstream\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eVolume\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003esnp18149-scaffold185-14576357\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003ers268250761\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cem\u003eKTN1\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eUpstream\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eALH\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003esnp6065-scaffold1214-284375\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003ers268239042\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cem\u003eAFF3\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eIntron\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eTotal sperm count\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003esnp26630-scaffold2784-22752\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003ers268258978\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cem\u003eNDUFA8\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eIntron\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eBCF\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e11_59883656\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003ena\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003eXPC1\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003eUpstream\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003eLIN, WOB\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003esnp47857-scaffold674-659869\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003ers268279637\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cem\u003eKCNQ5\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eIntron\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eLIN\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eGoatD01.022536\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003ena\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cem\u003eSCN4B\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eIntron\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eTotal motility\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003esnp45763-scaffold628-558823\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003ers268277594\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cem\u003eSBF2\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eIntron\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eALH\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eLoF612\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003ena\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cem\u003eTUB\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eIntergenic\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eTotal motility\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003esnp27852-scaffold299-1799687\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003ers268260163\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003eDENND1B\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003eIntron\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003eLIN, WOB\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003esnp8651-scaffold131-3195017\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003ers268241564\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cem\u003ePAPPA2\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eUpstream\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eTotal motility\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e17_15100698\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003ena\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cem\u003eHSPB8\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eDownstream\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eALH\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003esnp29978-scaffold327-1284363\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003ers268262235\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cem\u003eCUX2\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eUpstream\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eVCL\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003esnp4635-scaffold1149-659137\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003ers268237642\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cem\u003eLRRC3C\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eIntron\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eConcentration\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003esnp23992-scaffold244-245992\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003ers268256400\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003ePELP1\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003eIntron\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003eTotal motility, progressive motility\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003esnp38526-scaffold488-10203\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003ers268270589\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cem\u003eKRT15\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eIntron\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eTotal motility\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003esnp4873-scaffold1163-331369\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003ers268237874\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cem\u003eASIC2\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eUpstream\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eTotal motility\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003esnp49837-scaffold711-2598917\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003ers268281559\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cem\u003eDEPDC1B\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eDownstream\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eVSL\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003esnp15610-scaffold165-834474\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003ers268248334\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cem\u003eFBLN5\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eUpstream\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eSTR\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e22_48206613_AF-PAKI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003ena\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cem\u003eNT5DC2\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eIntron\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eVolume\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eGoatD01.006091\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003ena\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cem\u003eFLNB\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eIntron\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eTotal motility\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003esnp59320-scaffold975-1213737\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003ers268290798\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cem\u003eDNAH8\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eIntron\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eTotal motility\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003esnp4538-scaffold1146-363529\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003ers268237548\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cem\u003eBTN2A2\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eUpstream\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eTotal motility\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003esnp6575-scaffold1234-59930\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003ers268239534\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cem\u003eCCBE1\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eIntron\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eTotal sperm count\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003esnp1044-scaffold1028-386572\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003ers268234149\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cem\u003ePCNX2\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eIntron\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eMass activity\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003esnp25314-scaffold2606-438718\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003ers268257690\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cem\u003ePIDD1\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eIntron\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eTotal motility\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003esnp14549-scaffold1587-647949\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003ers268247301\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cem\u003eSNORD14\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eUpstream\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eTotal motility\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"6\"\u003eCHR: Chromosome; rs: Reference SNP; VAP: Average path velocity; VSL: Straight-linear velocity; VCL: Curvilinear velocity; ALH: Amplitude of lateral head displacement; BCF: Beat cross frequency; STR: Straightness; LIN: Movement linearity; WOB: wobble. Note: SNPs highlighted in bold are associated with multiple semen parameters.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eGene enrichment and network analyses of candidate genes located within \u0026plusmn;\u0026thinsp;100 Kb of SNPs associated with semen parameters are presented in Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e"},{"header":"4. Discussion","content":"\u003cp\u003eThe assessment of semen quality in ruminants constitutes a critical component in efforts to improve productivity and sustainability within animal production systems. In an era marked by the widespread application of reproductive biotechnologies, comprehensive evaluation of sperm parameters in prospective breeding males plays a pivotal role in determining the success of both natural mating and artificial insemination. The integration of CASA technology further enhances precision and reliability in the evaluation process [\u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e], facilitating more informed decision-making in breeding program management. CASA is regarded as a superior method for assessing fresh semen quality, not only because of its speed but also due to its ability to accurately measure multiple aspects of sperm fertility [\u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe comparison of semen quality across different buck breeds reveals significant variations, which are influenced by breed-specific characteristics, environmental factors, and management practices. Understanding these disparities is crucial for optimizing breeding strategies and improving reproductive efficiency within goat production systems [\u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e]. In this study, semen volume was found to be higher in Boer bucks, while sperm concentration was higher in Anglo-Nubian bucks compared to other breeds (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05). The total spermatozoa count per ejaculation was similar in Boer and Anglo-Nubian bucks (p\u0026thinsp;\u0026gt;\u0026thinsp;0.05), but both breeds were found to be more successful than Murcia-Granada bucks (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05). Although no differences were found between breeds in terms of VAP and VCL values (p\u0026thinsp;\u0026gt;\u0026thinsp;0.05), the WOB value was found to be higher in the Boer compared to the Murcia-Granada (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05).\u003c/p\u003e \u003cp\u003eAmong the three multi-locus GWAS methods employed in this study, FarmCPU and BLINK exhibited a high degree of consistency, identifying nearly identical sets of SNPs across all semen parameters except total motility, where some divergence was observed (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). This strong concordance, approaching 100% agreement, highlights the robustness and reliability of these two methods when applied to the dataset. In contrast, the MLMM model identified a distinct set of SNPs for most traits, which can be attributed to differences in its underlying statistical framework and model assumptions compared to FarmCPU and BLINK. Importantly, the repeated identification of the same SNPs by multiple models\u0026mdash;particularly those based on fundamentally different algorithmic principles\u0026mdash;serves as compelling evidence of the statistical strength and credibility of the detected associations. Such convergence across diverse analytical approaches reinforces the confidence in these SNPs as true genetic signals rather than artefacts of model-specific biases.\u003c/p\u003e \u003cp\u003eThe genes harboring or located near the SNPs identified in the study are involved in diverse molecular functions and biological processes\u0026mdash;including cancer and immunity\u0026mdash;and many are directly linked to sperm quality or male reproductive biology.\u003c/p\u003e \u003cp\u003eThe \u003cem\u003eFLNB\u003c/em\u003e gene encodes filamin B, a large actin-binding protein that plays a fundamental role in crosslinking actin filaments and thereby establishing key aspects of the cytoskeletal architecture [\u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e52\u003c/span\u003e, \u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e53\u003c/span\u003e]. Although \u003cem\u003eFLNB\u003c/em\u003e has been mostly investigated in the context of skeletal development, cell migration, and vascular formation, its role in reproductive tissues, particularly in sperm or seminal fluid, has not been explored in depth in the current literature. The association of \u003cem\u003eFLNB\u003c/em\u003e mutations with 46,XY gonadal dysgenesis Upadhyay et al. [\u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e54\u003c/span\u003e] raises the hypothesis that \u003cem\u003eFLNB\u003c/em\u003e could be important for gonadal development and, by extension, aspects of sperm biology. The \u003cem\u003eSCN4B\u003c/em\u003e gene encodes the β4 subunit of voltage‐gated sodium channels, a regulatory protein that modulates channel gating and influences the kinetic properties of the channel complex in excitable tissues [\u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e55\u003c/span\u003e]. While \u003cem\u003eSCN4B\u003c/em\u003e has been primarily studied for its roles in cardiac and neuronal systems, where mutations are linked to arrhythmias and behavioral alterations [\u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e55\u003c/span\u003e, \u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e56\u003c/span\u003e], its potential involvement in sperm physiology remains unexplored. Although sperm ion channel studies have mainly focused on CatSper, Hv1, and potassium channels, sodium channels also play a role in sperm function [\u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e57\u003c/span\u003e]. Given \u003cem\u003eSCN4B\u003c/em\u003e's modulatory effect on voltage-gated sodium channels in other tissues, it may similarly influence sodium channels in sperm. The \u003cem\u003eEPHB1\u003c/em\u003e gene encodes a receptor tyrosine kinase that is implicated in mediating cell\u0026ndash;cell communication, cellular adhesion, and migration [\u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e58\u003c/span\u003e]. Variants in key signaling molecules have been shown to influence crucial semen traits, including sperm morphology, motility, and count [\u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e59\u003c/span\u003e]. EPHB1 protein was abundantly detected in porcine seminal plasma, and although its function remains unclear, GO annotations such as 'regulation of cell motility', 'response to stimulus', and 'phosphorylation' imply a potential role in sperm functionality [\u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e60\u003c/span\u003e]. The protein products of the \u003cem\u003ePCNX2\u003c/em\u003e gene have no described function [\u003cspan citationid=\"CR61\" class=\"CitationRef\"\u003e61\u003c/span\u003e]; however, \u003cem\u003ePCNX2\u003c/em\u003e has been proposed as a candidate gene for eggshell strength in chickens [\u003cspan citationid=\"CR62\" class=\"CitationRef\"\u003e62\u003c/span\u003e]. The \u003cem\u003ePTHLH\u003c/em\u003e gene encodes a neuroendocrine peptide that regulates cell and organ growth, development, migration, differentiation, and survival [\u003cspan citationid=\"CR63\" class=\"CitationRef\"\u003e63\u003c/span\u003e]. GWAS results identified varying numbers of candidate genes in Qinchuan, Belgian Red Bull, and Belgian Red and White cattle, including \u003cem\u003ePTHLH\u003c/em\u003e, associated with growth, development, and reproduction [\u003cspan citationid=\"CR64\" class=\"CitationRef\"\u003e64\u003c/span\u003e]. Although \u003cem\u003ePTHLH\u003c/em\u003e is not yet widely characterized within reproductive biology, its established role in calcium regulation in other tissues [\u003cspan citationid=\"CR65\" class=\"CitationRef\"\u003e65\u003c/span\u003e] provides a plausible basis for hypothesizing a contribution to the maintenance of seminal plasma composition and the modulation of sperm function. The non-receptor type protein tyrosine phosphatase \u003cem\u003ePTPN13\u003c/em\u003e has been characterized in various biological contexts, including cancer, where it plays roles in regulating cell adhesion, migration, and apoptosis [\u003cspan citationid=\"CR66\" class=\"CitationRef\"\u003e66\u003c/span\u003e]. In cattle-yak, upregulation of the lncRNA targeting \u003cem\u003ePTPN13\u003c/em\u003e has been associated with abnormal apoptosis or growth arrest in sperm cells [\u003cspan citationid=\"CR67\" class=\"CitationRef\"\u003e67\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe Leucine Rich Repeat Containing 3C gene (\u003cem\u003eLRRC3C\u003c/em\u003e) has primarily been investigated in non-reproductive contexts. Although \u003cem\u003eLRRC3C\u003c/em\u003e has been associated with inflammatory bowel disease and displays a tissue-specific expression pattern excluding the lung [\u003cspan citationid=\"CR68\" class=\"CitationRef\"\u003e68\u003c/span\u003e], direct evidence linking it to sperm or seminal function is currently lacking. However, advances in sperm transcriptomics offer new opportunities to explore the potential reproductive roles of understudied genes such as \u003cem\u003eLRRC3C\u003c/em\u003e in male fertility. The \u003cem\u003eCCBE1\u003c/em\u003e gene, primarily known for its role in lymphangiogenesis and extracellular matrix remodeling, has been extensively studied in the context of vascular and cardiac development [\u003cspan citationid=\"CR69\" class=\"CitationRef\"\u003e69\u003c/span\u003e]. However, its expression in non-classical tissues, such as sperm and early embryos, suggests potential sensitivity to epigenetic reprogramming triggered by paternal dietary factors. Previous studies have demonstrated that dietary modifications in male breeding stock can result in discernible shifts in sperm epigenetic markers [\u003cspan citationid=\"CR70\" class=\"CitationRef\"\u003e70\u003c/span\u003e]. Enhanced levels of methionine have been associated with improvements in sperm DNA quality, including increased methylation of genes that are otherwise crucial for fertility and development [\u003cspan citationid=\"CR71\" class=\"CitationRef\"\u003e71\u003c/span\u003e]. Thus, integrating the developmental role of \u003cem\u003eCCBE1\u003c/em\u003e with the findings of Townsend et al. [\u003cspan citationid=\"CR70\" class=\"CitationRef\"\u003e70\u003c/span\u003e] supports the hypothesis that paternal methionine supplementation may influence embryonic development through epigenetic modulation of genes like \u003cem\u003eCCBE1.\u003c/em\u003e Actin filament-associated protein 1‐like 1 (\u003cem\u003eAFAP1L1\u003c/em\u003e) is primarily recognized as an adaptor protein that plays a significant role in cytoskeletal dynamics and the modulation of cell motility. Takahashi et al. [\u003cspan citationid=\"CR72\" class=\"CitationRef\"\u003e72\u003c/span\u003e] demonstrated that \u003cem\u003eAFAP1L1\u003c/em\u003e associates with vinculin, influencing cellular morphology and motility. Although these studies were conducted in the context of colorectal cancer progression, the molecular functions they elucidate may provide insights into \u003cem\u003eAFAP1L1\u003c/em\u003e\u0026rsquo;s potential role in sperm biology, where the regulation of cytoskeletal architecture is critical for sperm motility and morphology. \u003cem\u003eTMEM117\u003c/em\u003e, which encodes a transmembrane protein, has emerged in recent genomic studies for its involvement in various biological processes, although its direct role in sperm or semen remains largely unexplored. Notably, \u003cem\u003eTMEM117\u003c/em\u003e has been implicated in selection signatures and expression traits in livestock, including body condition and fatty acid composition [\u003cspan citationid=\"CR73\" class=\"CitationRef\"\u003e73\u003c/span\u003e, \u003cspan citationid=\"CR74\" class=\"CitationRef\"\u003e74\u003c/span\u003e]. In a GWAS study conducted in cattle, SNPs within the \u003cem\u003eTMEM117\u003c/em\u003e gene were primarily associated with biological regulation, metabolic activity, and developmental processes [\u003cspan citationid=\"CR75\" class=\"CitationRef\"\u003e75\u003c/span\u003e]. These associations suggest that \u003cem\u003eTMEM117\u003c/em\u003e may exert an indirect influence on fertility by modulating seminal fluid quality and, consequently, sperm function. The \u003cem\u003eNUMB\u003c/em\u003e gene, a key regulator of cell fate determination, plays a crucial role in the regulation of various signaling pathways. Functioning primarily as an adaptor protein, \u003cem\u003eNUMB\u003c/em\u003e influences Notch signaling and endocytic processes\u0026mdash;both of which are critically involved in cell proliferation, differentiation, and the maintenance of undifferentiated cellular states [\u003cspan citationid=\"CR76\" class=\"CitationRef\"\u003e76\u003c/span\u003e]. Although direct experimental evidence linking \u003cem\u003eNUMB\u003c/em\u003e to specific sperm or semen functions is limited, NUMB-associated signaling pathways may indirectly influence sperm motility and function. The Nuclear Factor I (\u003cem\u003eNFI\u003c/em\u003e) family (\u003cem\u003eNFIA\u003c/em\u003e, \u003cem\u003eNFIB\u003c/em\u003e, \u003cem\u003eNFIC\u003c/em\u003e, and \u003cem\u003eNFIX\u003c/em\u003e) is primarily involved in regulating stem cell development. All members of the NFI family have been shown to exhibit high expression levels in the caput region of the epididymis [\u003cspan citationid=\"CR77\" class=\"CitationRef\"\u003e77\u003c/span\u003e]. Among its members, \u003cem\u003eNFIX\u003c/em\u003e is notably expressed in spermatocytes and plays a critical role in spermatogenesis. Deficiency in \u003cem\u003eNFIX\u003c/em\u003e has been shown to cause multinucleation in spermatocytes, structural abnormalities in the synaptonemal complex, and other defects, ultimately resulting in impaired spermatogenesis [\u003cspan citationid=\"CR78\" class=\"CitationRef\"\u003e78\u003c/span\u003e]. Zhang et al. [\u003cspan citationid=\"CR79\" class=\"CitationRef\"\u003e79\u003c/span\u003e] reported that abnormal expression of the \u003cem\u003eNFIA\u003c/em\u003e gene was associated with infertility and a down-regulation of testosterone levels in monkeys with diet-induced obesity. Proline, glutamate, and leucine-rich protein 1 (\u003cem\u003ePELP1\u003c/em\u003e) serves as an estrogen receptor (ESR) coregulator and plays a multifaceted role in mediating both genomic and non-genomic signal transduction [\u003cspan citationid=\"CR80\" class=\"CitationRef\"\u003e80\u003c/span\u003e]. Skibińska et al. [\u003cspan citationid=\"CR81\" class=\"CitationRef\"\u003e81\u003c/span\u003e] demonstrated that increased \u003cem\u003ePELP1\u003c/em\u003e expression in human sperm is linked to abnormal sperm parameters, including altered motility and morphology. Additionally, the \u003cem\u003ePELP1\u003c/em\u003e gene has been reported to be associated with sperm morphology abnormalities in pigs [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe \u003cem\u003eNDUFA8\u003c/em\u003e gene encodes a nuclear-encoded subunit of NADH:ubiquinone oxidoreductase (Complex I) of the mitochondrial respiratory chain, which is essential for efficient electron transport and ATP production [\u003cspan citationid=\"CR82\" class=\"CitationRef\"\u003e82\u003c/span\u003e]. \u003cem\u003eNDUFA8\u003c/em\u003e has been reported to be involved in thermogenesis and the oxidative phosphorylation pathway, playing an important role in ram sperm cryotolerance [\u003cspan citationid=\"CR83\" class=\"CitationRef\"\u003e83\u003c/span\u003e]. \u003cem\u003eDENND1B\u003c/em\u003e, primarily involved in immune regulation [\u003cspan citationid=\"CR84\" class=\"CitationRef\"\u003e84\u003c/span\u003e], hosts a circRNA associated with sperm motility in pigs [\u003cspan citationid=\"CR85\" class=\"CitationRef\"\u003e85\u003c/span\u003e]. Kunnath et al. [\u003cspan citationid=\"CR86\" class=\"CitationRef\"\u003e86\u003c/span\u003e] also linked a \u003cem\u003eDENND1B\u003c/em\u003e variant to semen quality differences in Holstein Friesian and Hallikar bulls. \u003cem\u003eCOBL\u003c/em\u003e (cordon-bleu WH2 repeat protein) is primarily known for its role in actin nucleation and cytoskeletal organization [\u003cspan citationid=\"CR87\" class=\"CitationRef\"\u003e87\u003c/span\u003e]. It is also expressed in testicular tissue [\u003cspan citationid=\"CR88\" class=\"CitationRef\"\u003e88\u003c/span\u003e], and an intronic variant in \u003cem\u003eCOBL\u003c/em\u003e gene has been associated with idiopathic male infertility [\u003cspan citationid=\"CR89\" class=\"CitationRef\"\u003e89\u003c/span\u003e], as well as with oligozoospermia or azoospermia [\u003cspan citationid=\"CR90\" class=\"CitationRef\"\u003e90\u003c/span\u003e] in previous GWAS studies. The role of the \u003cem\u003eKRT15\u003c/em\u003e gene in male reproduction remains unclear; however, its expression was significantly lower in fresh ram sperm than in frozen-thawed samples [\u003cspan citationid=\"CR91\" class=\"CitationRef\"\u003e91\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe phosphodiesterase \u003cem\u003ePDE7B\u003c/em\u003e is a cAMP-specific enzyme that has garnered attention due to its tissue-specific expression, including in the testis. Sasaki et al. [\u003cspan citationid=\"CR92\" class=\"CitationRef\"\u003e92\u003c/span\u003e] reported that in rat spermatocytes, \u003cem\u003ePDE7B\u003c/em\u003e mRNA is expressed in a stage-specific manner during spermatogenesis, suggesting that \u003cem\u003ePDE7B\u003c/em\u003e may play an essential role in the regulation of cAMP signaling during sperm development. This regulation is critical because cAMP is a central intracellular messenger that modulates sperm motility, capacitation, and other aspects of sperm function, as highlighted by studies on sperm capacitation and motility [\u003cspan citationid=\"CR93\" class=\"CitationRef\"\u003e93\u003c/span\u003e]. The \u003cem\u003eSBF2\u003c/em\u003e gene, also known as SET-binding factor 2 or \u003cem\u003eMTMR13\u003c/em\u003e, is primarily characterized for its role as a regulatory protein within the myotubularin family [\u003cspan citationid=\"CR94\" class=\"CitationRef\"\u003e94\u003c/span\u003e]. Myotubularin and its related proteins (MTMs) are highly conserved phosphatases and pseudophosphatases present across eukaryotes, from fungi to humans [\u003cspan citationid=\"CR95\" class=\"CitationRef\"\u003e95\u003c/span\u003e]. Among them, only \u003cem\u003eMTMR2\u003c/em\u003e and \u003cem\u003eMTMR5\u003c/em\u003e have been implicated in spermatogenesis, as knockout mice (\u003cem\u003eMTMR2\u003c/em\u003e⁻/⁻ and \u003cem\u003eMTMR5\u003c/em\u003e⁻/⁻) exhibit aspermatogenesis and azoospermia, supported by both \u003cem\u003ein vitro\u003c/em\u003e and \u003cem\u003ein vivo\u003c/em\u003e studies [\u003cspan additionalcitationids=\"CR97 CR98\" citationid=\"CR96\" class=\"CitationRef\"\u003e96\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR99\" class=\"CitationRef\"\u003e99\u003c/span\u003e]. In this study, a variation in the \u003cem\u003eSBF2\u003c/em\u003e (\u003cem\u003eMTMR13\u003c/em\u003e) gene was identified, although its involvement in spermatogenesis or sperm function remains uncharacterized in the literature.\u003c/p\u003e \u003cp\u003eThe \u003cem\u003eKCNQ5\u003c/em\u003e gene encodes a voltage-gated potassium channel that has primarily been studied in the context of neuronal excitability and vascular function [\u003cspan citationid=\"CR100\" class=\"CitationRef\"\u003e100\u003c/span\u003e]. Potassium channels are critical for sperm function by regulating the membrane potential, a key factor required for processes such as capacitation, the acrosome reaction, and ultimately fertilization [\u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e57\u003c/span\u003e]. In contrast to \u003cem\u003eKCNQ5\u003c/em\u003e, other potassium channel isoforms\u0026mdash;for example, \u003cem\u003eKCNQ1\u003c/em\u003e\u0026mdash;have been identified in human sperm and are involved in sperm motility and capacitation [\u003cspan citationid=\"CR101\" class=\"CitationRef\"\u003e101\u003c/span\u003e]. However, no direct evidence currently links \u003cem\u003eKCNQ5\u003c/em\u003e expression or activity to sperm-specific processes, and studies have not reported its expression in sperm. The \u003cem\u003eSAXO1\u003c/em\u003e gene encodes a protein essential for stabilizing axonemal microtubules, particularly in the sperm flagellum endpiece [\u003cspan citationid=\"CR102\" class=\"CitationRef\"\u003e102\u003c/span\u003e]. Structural studies have shown that \u003cem\u003eSAXO1\u003c/em\u003e binds along microtubule protofilaments via a conserved Mn motif, thereby supporting flagellar integrity and sperm motility required for successful fertilization [\u003cspan citationid=\"CR102\" class=\"CitationRef\"\u003e102\u003c/span\u003e, \u003cspan citationid=\"CR103\" class=\"CitationRef\"\u003e103\u003c/span\u003e]. \u003cem\u003eLRP1B\u003c/em\u003e, a member of the low-density lipoprotein (LDL) receptor family, is involved in various cellular processes [\u003cspan citationid=\"CR104\" class=\"CitationRef\"\u003e104\u003c/span\u003e] and has been proposed as a potential marker of spermatogonial stem cell (SSC) function in Shaziling pigs [\u003cspan citationid=\"CR105\" class=\"CitationRef\"\u003e105\u003c/span\u003e]. The \u003cem\u003eDNAH8\u003c/em\u003e gene encodes an axonemal dynein heavy chain essential for the formation, structural integrity, and motility of the sperm flagellum. Studies in humans and mice have shown that bi-allelic deleterious variants in \u003cem\u003eDNAH8\u003c/em\u003e cause male infertility associated with multiple morphological abnormalities of the sperm flagella (MMAF9 [\u003cspan citationid=\"CR106\" class=\"CitationRef\"\u003e106\u003c/span\u003e]. Chromosomal mapping studies have identified regions containing \u003cem\u003eDNAH8\u003c/em\u003e as potentially associated with asthenozoospermia, a condition characterized by reduced sperm motility [\u003cspan citationid=\"CR107\" class=\"CitationRef\"\u003e107\u003c/span\u003e]. Furthermore, the presence of \u003cem\u003eDNAH8\u003c/em\u003e variants in cohorts of infertile men supports the view that subtle genetic alterations in this gene may contribute to a range of sperm dysfunctions [\u003cspan citationid=\"CR108\" class=\"CitationRef\"\u003e108\u003c/span\u003e]. The nucleotide excision repair (NER) pathway is activated in response to severe DNA lesions such as pyrimidine dimers and intrachain cross-links, which disrupt the DNA helical structure [\u003cspan citationid=\"CR109\" class=\"CitationRef\"\u003e109\u003c/span\u003e]. The \u003cem\u003eXPC\u003c/em\u003e protein plays a key role in this repair mechanism. Notably, \u003cem\u003eXPC\u003c/em\u003e expression is significantly higher in the testis compared to other tissues in both mice and humans [\u003cspan citationid=\"CR110\" class=\"CitationRef\"\u003e110\u003c/span\u003e]. Moreover, \u003cem\u003eXPC\u003c/em\u003e heterozygous mice exhibit smaller litter sizes and prolonged birth intervals, indicating that \u003cem\u003eXPC\u003c/em\u003e mutations may impair reproductive function and spermatogenesis [\u003cspan citationid=\"CR111\" class=\"CitationRef\"\u003e111\u003c/span\u003e]. Elevated heat shock protein levels are thought to be associated with immature spermatozoa [\u003cspan citationid=\"CR112\" class=\"CitationRef\"\u003e112\u003c/span\u003e]. A GWAS study in beef bulls reported a significant SNP for post-thaw motility located near the \u003cem\u003eHSPB8\u003c/em\u003e gene, which encodes heat shock protein family B (small) member 8 [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe nerve growth factor (\u003cem\u003eNGF\u003c/em\u003e) gene and its SNPs play a significant role in male reproductive physiology, particularly in the context of sperm quality and semen characteristics. It has been demonstrated that \u003cem\u003eNGF\u003c/em\u003e enhances the motility of spermatozoa in various species, including humans and rabbits, through mechanisms that potentially involve its action on the sperm\u0026rsquo;s cytoskeleton and capacitation processes [\u003cspan citationid=\"CR113\" class=\"CitationRef\"\u003e113\u003c/span\u003e, \u003cspan citationid=\"CR114\" class=\"CitationRef\"\u003e114\u003c/span\u003e]. Furthermore, \u003cem\u003eNGF\u003c/em\u003e\u0026rsquo;s receptor, \u003cem\u003eTrkA\u003c/em\u003e, is expressed in the male reproductive tract, indicating a direct role in male fertility [\u003cspan citationid=\"CR114\" class=\"CitationRef\"\u003e114\u003c/span\u003e, \u003cspan citationid=\"CR115\" class=\"CitationRef\"\u003e115\u003c/span\u003e]. In the context of genetic variations, SNPs in the \u003cem\u003eNGF\u003c/em\u003e gene have been studied concerning their potential impact on reproductive traits. For example, a non-synonymous SNP in the \u003cem\u003eNGF\u003c/em\u003e gene [rs6330], which results in an amino acid substitution, has been associated with altered \u003cem\u003eNGF\u003c/em\u003e function and could influence sperm quality [\u003cspan citationid=\"CR116\" class=\"CitationRef\"\u003e116\u003c/span\u003e, \u003cspan citationid=\"CR117\" class=\"CitationRef\"\u003e117\u003c/span\u003e]. Additionally, variations in \u003cem\u003eNGF\u003c/em\u003e have been linked to broader issues of male infertility, such as low sperm motility and concentration, underscoring the gene's importance in reproductive success [\u003cspan citationid=\"CR118\" class=\"CitationRef\"\u003e118\u003c/span\u003e, \u003cspan citationid=\"CR119\" class=\"CitationRef\"\u003e119\u003c/span\u003e]. The \u003cem\u003eTUB\u003c/em\u003e [tubby] gene encodes a major cytoskeletal protein in the sperm tail, and its reduced expression is associated with impaired motility and structural defects in spermatozoa [\u003cspan citationid=\"CR120\" class=\"CitationRef\"\u003e120\u003c/span\u003e]. The \u003cem\u003ePAPPA2\u003c/em\u003e gene, which encodes pregnancy-associated plasma protein A2, regulates insulin-like growth factor bioavailability\u0026mdash;crucial for spermatogenesis and sperm quality\u0026mdash;and its deletion in mice has been linked to altered male fertility, suggesting a role in sperm maturation and function beyond reproductive frequency [\u003cspan additionalcitationids=\"CR122\" citationid=\"CR121\" class=\"CitationRef\"\u003e121\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR123\" class=\"CitationRef\"\u003e123\u003c/span\u003e]. The \u003cem\u003eMDGA2\u003c/em\u003e gene is involved in protein metabolism and cell\u0026ndash;cell interactions, and Khayatzadeh et al. [\u003cspan citationid=\"CR124\" class=\"CitationRef\"\u003e124\u003c/span\u003e] reported an association between \u003cem\u003eMDGA2\u003c/em\u003e and seminal volume in bulls. Additionally, the \u003cem\u003eMDGA2\u003c/em\u003e gene is suggested to serve as a potential functional marker for spermatogonial stem cells in Shaziling pigs [\u003cspan citationid=\"CR105\" class=\"CitationRef\"\u003e105\u003c/span\u003e]. The \u003cem\u003eSNORD14\u003c/em\u003e gene, encoding a small nucleolar RNA, has attracted attention for its role in RNA processing and potential impact on various biological processes. Within the long non-coding RNA-target regulatory network, several small nucleolar RNA-encoding genes, including \u003cem\u003eSNORD14\u003c/em\u003e, have been reported to show a strong correlation with the upregulated MSTRG.14719.6 [\u003cspan citationid=\"CR125\" class=\"CitationRef\"\u003e125\u003c/span\u003e], highlighting its significant role in the post-transcriptional modification of ribosomal RNAs (rRNAs), which are crucial for sperm viability and male fertility [\u003cspan citationid=\"CR126\" class=\"CitationRef\"\u003e126\u003c/span\u003e, \u003cspan citationid=\"CR127\" class=\"CitationRef\"\u003e127\u003c/span\u003e]. Fibulins are extracellular matrix glycoproteins that modulate cellular behavior and function, primarily through interactions with laminin and calcium. Among them, Fibulin-5 (\u003cem\u003eFBLN5\u003c/em\u003e) plays a key role in extracellular matrix regulation and cellular adhesion, and has been identified as a candidate gene associated with sperm DNA integrity in the testicular tissue of male pigs [\u003cspan citationid=\"CR128\" class=\"CitationRef\"\u003e128\u003c/span\u003e]. Kinectin-1, a member of the kinesin superfamily of motor proteins, plays a crucial role in the organized transport of organelles and cellular components along microtubules [\u003cspan citationid=\"CR129\" class=\"CitationRef\"\u003e129\u003c/span\u003e]. The \u003cem\u003eKTN1\u003c/em\u003e gene, which encodes this protein, has been identified as commonly differentially expressed in asthenozoospermia [\u003cspan citationid=\"CR130\" class=\"CitationRef\"\u003e130\u003c/span\u003e]. The \u003cem\u003eDNAJC10\u003c/em\u003e gene, which encodes a member of the DnaJ heat shock protein family involved in cellular stress responses and protein folding, has been found to be highly expressed in the caput and corpus regions of the epididymis [\u003cspan citationid=\"CR131\" class=\"CitationRef\"\u003e131\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eIt is noteworthy that a total of 12 high-effect SNPs, with p-values ranging from 1 \u0026times; 10⁻\u0026sup1;⁵ to 1 \u0026times; 10⁻⁶, were identified. Among these SNPs, rs268283792, is located approximately 120 Kb downstream of the Stromal Interaction Molecule 2 (\u003cem\u003eSTIM2\u003c/em\u003e) gene and showed a genome-wide significant association with total sperm motility percentage (p\u0026thinsp;=\u0026thinsp;1.60 \u0026times; 10⁻\u0026sup1;⁵). \u003cem\u003eSTIM2\u003c/em\u003e, which is involved in cellular calcium ion homeostasis and store-operated calcium channel activity [\u003cspan citationid=\"CR132\" class=\"CitationRef\"\u003e132\u003c/span\u003e], has also been associated with spermatozoon count in rams [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. The \u003cem\u003eTLE4\u003c/em\u003e gene encodes a transcriptional corepressor involved in the Wnt signaling pathway, exhibits testis-specific splicing variants [\u003cspan citationid=\"CR133\" class=\"CitationRef\"\u003e133\u003c/span\u003e], and has been associated with genetic variation in total sperm motility and progressive motility in Italian Holstein bulls [\u003cspan citationid=\"CR134\" class=\"CitationRef\"\u003e134\u003c/span\u003e], as well as with total sperm number in boars [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]. In this study, a SNP (rs268240712) located upstream of the \u003cem\u003eTLE4\u003c/em\u003e gene was found to be genome-wide significantly associated with sperm mass activity (2.99 \u0026times; 10⁻\u003csup\u003e9\u003c/sup\u003e). Polymorphisms identified in the \u003cem\u003eSRY\u003c/em\u003e (Sex-Determining Region Y)-box 5 (\u003cem\u003eSOX5\u003c/em\u003e) gene have been reported to influence sperm motility [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e, \u003cspan citationid=\"CR135\" class=\"CitationRef\"\u003e135\u003c/span\u003e] and concentration [\u003cspan citationid=\"CR135\" class=\"CitationRef\"\u003e135\u003c/span\u003e] in bulls and have also been strongly associated with nonobstructive azoospermia in humans [\u003cspan citationid=\"CR136\" class=\"CitationRef\"\u003e136\u003c/span\u003e]. Similarly, in this GWAS study, the SNP rs268235538, located upstream of the \u003cem\u003eSOX5\u003c/em\u003e gene, was found to be associated with sperm concentration in goats (p\u0026thinsp;=\u0026thinsp;2.81 \u0026times; 10\u003csup\u003e\u0026minus;\u0026thinsp;7\u003c/sup\u003e). Two-pore channels (TPCs) have been found to share structural homology with both the transient receptor potential (TRP) channel superfamily and the cation channel of sperm (CatSper), each of which comprises tetrameric, single-domain channels [\u003cspan citationid=\"CR137\" class=\"CitationRef\"\u003e137\u003c/span\u003e]. The SNP rs268247301, located approximately 207 Kb downstream of the Two Pore Segment Channel 2 (\u003cem\u003eTPCN2\u003c/em\u003e) gene, was found to be associated with total sperm motility (p\u0026thinsp;=\u0026thinsp;5.99 \u0026times; 10\u003csup\u003e\u0026minus;\u0026thinsp;6\u003c/sup\u003e). p53-induced death domain protein 1 (PIDD1) is best known for its role in orchestrating cell cycle control and programmed cell death through the formation of the multiprotein PIDDosome complex, which typically facilitates caspase‐2 activation in response to centrosome aberrations and DNA damage [\u003cspan citationid=\"CR138\" class=\"CitationRef\"\u003e138\u003c/span\u003e]. Spermatogenesis is highly dependent on the stringent regulation of cell cycle checkpoints and apoptosis to ensure proper genomic integrity and to eliminate damaged germ cells. Liu et al. [\u003cspan citationid=\"CR139\" class=\"CitationRef\"\u003e139\u003c/span\u003e] reported that the expression level of the PIDD transcript significantly decreased in July and October, suggesting that this reduction may contribute to the suppression of apoptotic effects in the testis of \u003cem\u003eP. sinensis\u003c/em\u003e and support the preservation of germ cells lost during intermediate and late stages of spermatogenesis. In this study, an intronic variant (rs268257690) in the \u003cem\u003ePIDD1\u003c/em\u003e gene was found to be significantly associated with total sperm motility (p\u0026thinsp;=\u0026thinsp;5.66 \u0026times; 10\u003csup\u003e\u0026minus;\u0026thinsp;6\u003c/sup\u003e).\u003c/p\u003e \u003cp\u003eMorphogenetic pathways play a crucial role in the structural and functional development of sperm. The plasma membrane bounded cell projection morphogenesis pathway is responsible for the formation of membrane-bound structures such as the acrosome and flagellum. These structures are crucial for sperm function: the acrosome contains hydrolytic enzymes required for penetrating the zona pellucida [\u003cspan citationid=\"CR140\" class=\"CitationRef\"\u003e140\u003c/span\u003e], while the flagellum provides motility, being ensheathed by the plasma membrane and powered by internal axonemal structures [\u003cspan citationid=\"CR141\" class=\"CitationRef\"\u003e141\u003c/span\u003e]. Additionally, this pathway regulates membrane reorganization during capacitation, a key step in acquiring fertilization competence [\u003cspan citationid=\"CR142\" class=\"CitationRef\"\u003e142\u003c/span\u003e]. The cell projection morphogenesis pathway regulates the overall development of cellular projections. It governs the precise assembly of the axoneme, a 9\u0026thinsp;+\u0026thinsp;2 microtubule structure critical for flagellar motion [\u003cspan citationid=\"CR143\" class=\"CitationRef\"\u003e143\u003c/span\u003e], and orchestrates nuclear shaping during spermatid maturation [\u003cspan citationid=\"CR144\" class=\"CitationRef\"\u003e144\u003c/span\u003e]. It also ensures the helical organization of mitochondria around the midpiece, supporting energy production for motility [\u003cspan citationid=\"CR145\" class=\"CitationRef\"\u003e145\u003c/span\u003e]. The cell part morphogenesis pathway focuses on the differentiation of specific subcellular structures. This includes chromatin condensation through histone-to-protamine exchange [\u003cspan citationid=\"CR146\" class=\"CitationRef\"\u003e146\u003c/span\u003e], acrosome-nucleus attachment via the acroplaxome [\u003cspan citationid=\"CR147\" class=\"CitationRef\"\u003e147\u003c/span\u003e], and the formation of the annulus, a diffusion barrier between the midpiece and principal piece of the flagellum [\u003cspan citationid=\"CR148\" class=\"CitationRef\"\u003e148\u003c/span\u003e]. The cellular component morphogenesis pathway regulates large-scale cellular remodeling during spermiogenesis. This involves the reduction of excess cytoplasm [\u003cspan citationid=\"CR149\" class=\"CitationRef\"\u003e149\u003c/span\u003e], the strategic repositioning of mitochondria to the midpiece [\u003cspan citationid=\"CR145\" class=\"CitationRef\"\u003e145\u003c/span\u003e], and the elongation and differentiation of spermatids into mature spermatozoa [\u003cspan citationid=\"CR149\" class=\"CitationRef\"\u003e149\u003c/span\u003e].\u003c/p\u003e \u003cp\u003e \u003cb\u003eConsideration and limitations\u003c/b\u003e \u003c/p\u003e \u003cp\u003eThe genotype-phenotype associations established through three different multi-locus GWAS models, using objective CASA parameters as phenotypes, enhance the power of the study, while the relatively low sample size constitutes a significant limitation. Therefore, a careful evaluation is necessary when considering the use of the SNPs reported here for genomic selection studies.\u003c/p\u003e"},{"header":"5. Conclusion","content":"\u003cp\u003eThis genome-wide association study (GWAS) uncovered several genomic regions and putative causal SNPs linked to fresh semen quality traits in goats. Although further validation in larger populations is warranted to confirm these associations and evaluate their potential for enhancing reproductive performance, the findings lay a solid groundwork for future large-scale studies and contribute meaningful insights into the genetic architecture of reproductive traits in goats.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledgments\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors would like to acknowledge the invaluable contributions of the staff at the Siirt University Reproductive Biotechnology Center.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study was supported by Siirt University Agriculture and Livestock Specialization Coordination Center with the project number of 2023- IHTVET-04.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthical statement\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study was conducted in compliance with the guidelines of the Animal Experiments Local Ethics Committee and with an experimental protocol approved by the Ethics Committee for the Use of Animals in Research and Experimentation at the Siirt University Animal Research Local Ethic Committee (29.06.2022-2022/15), and the authors complied with the ARRIVE guidelines.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare no competing interests.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAE:\u0026nbsp;\u003c/strong\u003eWriting \u0026ndash; review \u0026amp; editing, Writing \u0026ndash; original draft, Data curation, Conceptualization, Project administration. \u003cstrong\u003eA\u0026Ccedil;C, AA, KB, RA, SY, KD, \u0026Ouml;G, MK,\u0026nbsp;\u003c/strong\u003eand\u003cstrong\u003e\u0026nbsp;VB:\u003c/strong\u003e Methodology. \u003cstrong\u003eYY:\u003c/strong\u003e Writing \u0026ndash; review \u0026amp; editing, Writing \u0026ndash; original draft, Data curation, Validation, Software, Conceptualization.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData availability\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe datasets generated and/or analyzed during the current study are available in the https://figshare.com/ repository, https://figshare.com/articles/dataset/Boer_Anglo-Nubian_and_Murcia_Granada_50K_Genotype_data/29046281?file=54489395\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eDanso F, Iddrisu L, Lungu S, Zhou G, Ju X. 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Spermatogenesis. 2014;4(2):e979623. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.4161/21565562.2014.979623\u003c/span\u003e\u003cspan address=\"10.4161/21565562.2014.979623\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Genome-wide association study, goat semen, computer-assisted sperm analysis, BLINK, FarmCPU, MLMM.","lastPublishedDoi":"10.21203/rs.3.rs-6721731/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6721731/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e \u003cp\u003eImproving sperm quality through genetic selection is a critical strategy for enhancing reproductive efficiency in farm animals. Dissecting the molecular basis of complex reproductive traits requires identifying genetic variants linked to key semen characteristics. Genome-wide association studies (GWAS) provide a robust framework for exploring the genetic architecture of economically significant traits, including fertility. In this study, both conventional sperm parameters\u0026mdash;semen volume (mL), mass activity (scale 1\u0026ndash;4), sperm concentration (\u0026times;10\u003csup\u003e9\u003c/sup\u003e/mL), and total sperm count per ejaculation (\u0026times;10\u003csup\u003e9\u003c/sup\u003e)\u0026mdash;and CASA-derived motility traits\u0026mdash;total motility (%), progressive motility (%), average path velocity (VAP, \u0026micro;m/s), straight-line velocity (VSL, \u0026micro;m/s), curvilinear velocity (VCL, \u0026micro;m/s), amplitude of lateral head displacement (ALH, \u0026micro;m), beat cross frequency (BCF, Hz), straightness (STR, %), linearity (LIN, %), and wobble (WOB, %)\u0026mdash;were evaluated in 24 bucks from three breeds (Boer, n\u0026thinsp;=\u0026thinsp;11; Anglo-Nubian, n\u0026thinsp;=\u0026thinsp;8; Murcia-Granada, n\u0026thinsp;=\u0026thinsp;5) during the breeding season. To investigate the genetic basis of these traits, three advanced multi-locus GWAS models\u0026mdash;BLINK, FarmCPU, and MLMM\u0026mdash;were applied. Subsequent gene annotation, functional enrichment, and network analyses were performed for candidate genes located within \u0026plusmn;\u0026thinsp;100 Kb of the associated SNPs, offering novel insights into the molecular mechanisms underlying spermatological characteristics.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eA total of 98 SNPs were found to be significantly associated with various semen parameters. Of these, 12 SNPs exhibited high statistical significance, with p-values ranging from 1 \u0026times; 10⁻\u003csup\u003e6\u003c/sup\u003e to 1 \u0026times; 10⁻\u003csup\u003e15\u003c/sup\u003e. Noteworthy SNPs included rs268240712 (upstream of \u003cem\u003eTLE4\u003c/em\u003e) and rs268235538 (upstream of \u003cem\u003eSOX5\u003c/em\u003e), significantly associated with mass activity and sperm concentration, respectively. Additionally, rs268283792 (downstream of \u003cem\u003eSTIM2\u003c/em\u003e), rs268247301 (downstream of \u003cem\u003eTPCN2\u003c/em\u003e), and rs268257690 (located within an intronic region of \u003cem\u003ePIDD1\u003c/em\u003e) were significantly linked to total motility. Gene annotation within \u0026plusmn;\u0026thinsp;100 Kb of each SNP identified 49 candidate genes. Enrichment and network analyses suggested that sperm structural and functional development plays a pivotal role in determining semen quality.\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e \u003cp\u003eThis study reveals candidate genomic regions influencing CASA-derived sperm traits in goats, offering potential for marker-assisted selection. However, further validation in larger and independent populations is warranted to confirm these associations and to assess their practical utility in genetic improvement programs.\u003c/p\u003e","manuscriptTitle":"Dissecting the genetic basis of computer-assisted fresh semen traits in goats using multi-locus genome-wide association methods","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-06-06 16:00:21","doi":"10.21203/rs.3.rs-6721731/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"814bc85f-af34-45ad-aa09-b30739d21bca","owner":[],"postedDate":"June 6th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2026-02-12T09:42:26+00:00","versionOfRecord":[],"versionCreatedAt":"2025-06-06 16:00:21","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-6721731","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6721731","identity":"rs-6721731","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}