{"paper_id":"3d4f5bca-6841-48c3-afab-a70f9a95fdc4","body_text":"Genomic measures of inbreeding coefficients and genome-wide scan for runs of homozygosity islands in Iranian river buffalo, Bubalus bubalis | 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 Genomic measures of inbreeding coefficients and genome-wide scan for runs of homozygosity islands in Iranian river buffalo, Bubalus bubalis Seyed Mohammad Ghoreishifar, Hossein Moradi-Shahrbabak, Mohammad Hossein Fallahi, and 4 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.2.17561/v5 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 10 Feb, 2020 Read the published version in BMC Genetics → Version 5 posted You are reading this latest preprint version Show more versions Abstract Background: Consecutive homozygous fragments of a genome inherited by offspring from a common ancestor are known as runs of homozygosity (ROH). ROH can be used to calculate genomic inbreeding and to identify genomic regions that are potentially under historical selection pressure. The dataset of our study consisted of 254 Azeri (AZ) and 115 Khuzestani (KHZ ) river buffalo genotyped for ~65000 SNPs for the following two purposes: 1) to estimate and compare inbreeding calculated using ROH (FROH), excess of homozygosity (FHOM), correlation between uniting gametes (FUNI), and diagonal elements of the genomic relationship matrix (FGRM); 2) to identify frequently occurring ROH (i.e. ROH islands) for our selection signature and gene enrichment studies. Results: In this study, 9102 ROH were identified, with an average number of 21.2±13.1 and 33.2±15.9 segments per animal in AZ and KHZ breeds, respectively. On average in AZ, 4.35% (108.8±120.3 Mb), and in KHZ, 5.96% (149.1±107.7 Mb) of the genome was autozygous. The estimated inbreeding values based on FHOM, FUNI and FGRM were higher in AZ than they were in KHZ, which was in contrast to the FROH estimates. We identified 11 ROH islands (four in AZ and seven in KHZ). In the KHZ breed, the genes located in ROH islands were enriched for multiple Gene Ontology (GO) terms (P≤0.05). The genes located in ROH islands were associated with diverse biological functions and traits such as body size and muscle development (BMP2), immune response (CYP27B1), milk production and components (MARS, ADRA1A, and KCTD16), coat colour and pigmentation (PMEL and MYO1A), reproductive traits (INHBC, INHBE, STAT6 and PCNA), and bone development (SUOX). Conclusion: The calculated FROH was in line with expected higher inbreeding in KHZ than in AZ because of the smaller effective population size of KHZ. Thus, we find that FROH can be used as a robust estimate of genomic inbreeding. Further, the majority of ROH peaks were overlapped with or in close proximity to the previously reported genomic regions with signatures of selection. This tells us that it is likely that the genes in the ROH islands have been subject to artificial or natural selection. Population Genetics water buffalo river buffalo genetic diversity inbreeding gene enrichment runs of homozygosity selection signatures Figures Figure 1 Figure 2 Figure 3 Figure 4 Background There are two main species of buffalo: the Asian water buffalo ( Bubalus bubalis ) and the African wild buffalo ( Syncerus caffer ), the second of which is also known as the cape buffalo [1, 2]. Domestication of B. bubalis , including of the river ( B. bubalis bubalis , 2n=50) and swamp ( B. bubalis carabanensis , 2n=48) subspecies, occurred approximately 3000–6000 years ago [3]. The domestication of river buffalo occurred in the Indo–Pakistani area, and domestication of swamp buffalo occurred close to the border of China [4]. River buffalo expanded broadly from India, Egypt and Southeast Asia to Europe, and the swamp buffalo is the most common type of buffalo in China and Southeast Asia [3-5]. The worldwide water buffalo population accounts for only approximately 11% of the entire cattle population. However, the population of water buffalo has increased in the past five decades by approximately 1.65% annually [5]. India, Pakistan and Europe (with 5.3%, 4.8% and 4.5% rates of increase, respectively) have the highest rates of annual increase [6]. In many tropical and subtropical countries, river buffalo are raised for both meat and milk production [7]. In Iran and in other developing nations, river buffalo production is of great economic importance because of the ability of buffalo to make the best use of low-quality feed in the production of their valuable milk, which has a unique taste and curd properties, high resistance to local parasites, high adaptation to harsh climate conditions, and long productive lifespan. The three major Iranian river buffalo breeds are Azeri (AZ), Khuzestani (KHZ) and Mazandarani (MZ), and each of these breeds belongs to different geographical zone [2]. The AZ, KHZ and MZ are common in the north-west and north, west and south-west, and north of the country, respectively. In Iran, the recording of milk and meat production, and the selective breeding of buffalo for better dairy performance (i.e. in milk production, and fat and protein percentage) and better meat production are performed by the Animal Breeding Centre of Iran (ABCI) [2]. Following performance and pedigree recording in some herds, and genetic analysis, candidate bulls are selected from rural herds based on their genetic merits, and the semen of these selected bulls is collected and distributed to all herds [2]. However, despite buffalo production being important in Iran, particularly in rural regions, controlling inbreeding and ensuring genetic improvement of desired traits through traditional breeding programmes are difficult because of a shortage of reliable pedigree and performance records for water buffalo in the country. The inbreeding coefficient measured from pedigree information (F PED ) has been the most common parameter for describing the level of inbreeding since Wright [8] However, the reliability of the estimated F PED depends on the completeness and correctness of pedigree. With the availability of high-density SNP-chip markers, inbreeding can also be defined according to genomic information such as genome-wide autozygosity [9] Autozygosity occurs when parents pass identical chromosomal fragments, which they already inherited from a common ancestor, on to their offspring [10]; these genomic regions of homozygosity are known as runs of homozygosity (ROH) [11, 12]. Estimated inbreeding based on ROH (F ROH ) can discriminate between homozygous (i.e. identical by descent [IBD]) and non-autozygous (i.e. identical by state [IBS]) positions in the genome [9]. Further, well-recorded pedigree information is not required to have reliable F ROH . Thus, using genetic markers instead of pedigree information to calculate inbreeding can produce more robust estimates [13, 14]. Identifying ROH can also help to find the footprints of genetic selection on the genome [15-17]. However, ROH are suggestive, but not conclusive, of genomic regions under natural or artificial selection because the incidence, extent and distribution of ROH across the genome are influenced by many factors other than ROH, such as recombination rate, population structure, mutation rate and inbreeding [16]. Nevertheless, ROH that frequently occur among individuals may contain genes associated with different traits that have been under historical selection, so that the genes located in ROH islands can be important for selective breeding [13, 15, 18]. ROH can also provide detailed information on the genetic relatedness of animals, which allows breeders to better control inbreeding in the population [16]. This allows mate allocation aiming to minimise inbreeding at the genome level to be achieved more precisely, and the individual animals that have high proportions of ROH coverage to be excluded or used less frequently in mating [16]. The distribution and the occurrence of ROH have been studied in humans [10, 11, 19, 20], cattle [13-15, 18, 21-26], pigs [27-29] and sheep [17, 30-32] but are poorly studied in some species, for example, in water buffalo. The current study aims to estimate autozygosity in the genome of AZ and KHZ buffalo breeds, and identify ROH spots that frequently occur among the individuals. The study also examines the function of the genes located in ROH islands to identify potential selection signature regions. Moreover, the study compares F ROH with other genomic methods of inbreeding estimation. Results Runs of homozygosity The AZ and KHZ are two major buffalo breeds adapted to distinct geographical areas in Iran [2, 5] (Fig. 1). The PC analysis of the IBS matrix derived from SNP data confirmed two separate populations with no overlap, which means that the samples from the AZ and KHZ breeds were genetically different (Fig. 2). Although Mokhber et al. [5] reported that AZ and KHZ are two distinct populations, they reported a moderate level of admixture between the AZ and MZ breeds. Thus, we excluded the MZ breed from our study. In total, 9102 ROH were detected, 5352 ROH in the AZ genome and 3750 in the KHZ genome (Table 1; Additional file 1). The average number of ROH per individual was 21.23±13.06 in the AZ breed (ranging from 4 to 88) and 33.2±15.92 in the KHZ breed (ranging from 4 to 132). Moreover, all of the individuals in our study had at least four ROH longer than 1 Mb. The variation between samples in total number of ROH and total length of ROH are presented in Fig. 3. Individuals with an almost equal portion of the genome covered by ROH had different numbers and lengths of ROH, which could be an indication of different combinations of recent and distant inbreeding events in the samples. Evaluation of different methods of genomic inbreeding Table 2 presents the averages of the estimated inbreeding coefficients using different methods (see also Additional file 2). The average F ROH calculated from ROH >1 Mb in length was 0.043±0.05 in the AZ breed and 0.059±0.04 in the KHZ breed (Table 2; Additional file 1). The estimated inbreeding values based on F HOM , F UNI and F GRM were higher in AZ than they were in KHZ, which was in contrast to the F ROH estimates. However, the Pearson’s correlations between F ROH and the estimated inbreeding with other methods were high (Table 3). Candidate genes inside frequently occurring runs of homozygosity regions A genome-wide search for SNPs that have frequently occurred within ROH hotspots revealed 11 regions on BTA1, BTA2, BTA5, BTA7, BTA13, BTA14, BTA19 and BTA29 (Fig. 4; Additional file 3). The detected ROH islands on BTA7, BTA13 and BTA14 were partially overlapped in AZ and KHZ. The strongest peaks detected in approximately 30% of the individuals were located on BTA19 (19:411,773–3,701,223 bp) in AZ and on BTA5 (5:55,217,391–57,476,442 bp) in KHZ. In the KHZ breed, the genes located in the ROH islands were significantly enriched (P≤0.05) in 40 GO terms. These GO terms belonged to 23 biological processes (BP), 12 cellular component (CC) and 5 molecular function (MF) groups (Additional file 4). Co-location of ROH islands and the identified selection signatures using iHS The majority of ROH hotspots detected in our study (Fig. 4; Additional file 3) overlapped with selection signature regions reported by Mokhber et al. [5] for the AZ and KHZ breeds using the haplotype-based method (i.e. iHS) (Additional files 5, 6). For example, the SNP Affx-79610232 on BTA5 (55,271,590 bp) with the highest iHS was located in our detected ROH island in the KHZ breed. On BTA13, the eight SNPs with the largest iHS values were located in our detected ROH region. The SNP Affx-79540796 on BTA14 (52,933,269 bp) had the second-highest iHS value in our reported ROH hotspot. On BTA29, the SNP Affx-79545556 (3,274,219 bp) was the SNP with the sixth-highest iHS value that was located in our reported ROH islands. Discussion We defined ROH as the lengths of homozygous genotypes that were >1 Mb and contained only up to one heterozygous genotype. Given the strong linkage disequilibrium (LD) between SNPs with a distance up to 100 Kb [33], short homozygous haplotypes are expected to be prevalent in the buffalo genome. Thus, we set a minimum length of 1 Mb and a minimum number of 40 (AZ) and 38 (KHZ) SNP (as described in methods section) to avoid detecting small and prevalent haplotypes as ROH. Unlike human populations, livestock species generally have higher levels of autozygosity and longer ROHs [13, 20, 21]. However, genotyping errors can always affect the quality of ROH calling [12]. Therefore, we allowed one heterozygous SNP in ROH [25, 30, 31] to avoid losing particularly long ROH because of a single genotyping error. As presented in Table 1, more than 53% of the detected ROH were 2–4 Mb in length. The proportion of different lengths of ROH can be used as an indicator of the number of past generations in which inbreeding has occurred, because the recombination events can rearrange the chromosomes and reduce the length of ROH. Thus, recent inbreeding results in longer ROH because of long IBD stretches. In contrast, short ROHs arise as a result of ancient inbreeding because in meiosis across generations, the long IBD segments are broken down [19]. We detected ROH with a length from 2 to 4 Mb in all of the samples (Additional file 1), which might indicate that some inbreeding events occurred about 20 generations ago [9]. However, our results should be interpreted with caution. As reported by Ferenčaković et al. [34], a medium-density chip could result in overestimation of the number of long-length ROHs (>4 Mb), probably because some heterozygous genotypes tend to appear in these ROHs by increasing the density of markers. Nevertheless, our results were in line with a previous report of a relatively sharp decrease in the effective population size (N e ) of AZ and KHZ breeds and the consequent increased rate of inbreeding since 20 generations ago [33]. The portion of the genome that was autozygote in the AZ and KHZ breeds was lower than the reported ROH coverage in the Marchigiana beef breed (7%) [15], Austrian dual purpose breeds (9%) [35], and Holstein cattle (10%) [36]. This could be because of lower inbreeding in Iranian water buffalo or because we ignored ROH of <1 Mb in length in our study. On average, F HOM , F UNI and F GRM were higher in AZ than they were in KHZ. However, the previously reported N e for AZ (477) was larger than it was for KHZ (212) [33]. Therefore, we expected a lower inbreeding level in AZ. The only comparable estimated inbreeding with our expectation was F ROH , which showed lower inbreeding for AZ (0.043) than for KHZ (0.059). The highest correlation was observed between F UNI and F ROH (AZ=0.98 and KHZ=0.94). Literature has reported different correlation coefficients between F UNI and F ROH (0.15–0.80) [14], between F HOM and F ROH (0.06–0.95) [14, 21, 27], and between F GRM and F ROH (0.17–0.81) [21, 37, 38]. The considerable variation among different studies may be because of a strong dependency of F HOM , F UNI and F GRM on allelic frequencies [39]. The F PED of 0.03 previously reported in Iranian buffalo [40] was lower than the estimated F ROH in the current study. Given that pedigree data were not available for our study, we could not calculate F PED and compare it with F ROH . However, previous studies reported moderate to high (0.47–0.82) and low to moderate (0.12–0.76) correlations between F PED and F ROH in cattle and sheep, respectively [14, 17]. A low to moderate correlation between F PED and F ROH was also reported by Peripolli et al. [13] in Gyr cattle, suggesting that F PED may not accurately capture small IBD segments that result from ancient inbreeding. Further, accurate and in-depth pedigree records are required to measure F PED . Additionally, methods based on allelic frequency have demonstrated considerable variation among different breeds [14]. Given that ROH does not depend on allele frequencies, and can capture recent and ancient inbreeding, it seems to be a suitable method for measuring inbreeding. The total length of ROH islands were about 6 and 15 Mb in the AZ and KHZ breeds, respectively (Additional file 3). Consequently, fewer genes were identified in ROH islands in the AZ breed than in the KHZ breed; that is probably why the genes located in ROH islands of the AZ breed were not enriched in any GO terms ( P >0.05). In the KHZ breed, however, the genes located in the ROH islands were significantly enriched (P≤0.05) in 40 GO terms (Additional file 4). These GO terms belonged to 23 biological processes (BP), 12 cellular component (CC) and 5 molecular function (MF) groups. In this paper, we focused principally on the GO terms that include the genes with known large effects on important traits in livestock. Five genes were identified with positive regulation of DNA metabolic development (GO:0051054) in the BP group. Among these genes, STAT6 (signal transducer and activator of transcription 6, on BTA5) has been reported to have large effects on the growth efficiency and the quality of carcass in cattle [41]. Additionally, using co-expression network analysis, Nguyen et al. [42]. reported the critical role of STAT6, PBX2 (PBX homeobox2) and PBRM1 (Protein polybromo1) as transcription factors in regulating pubertal development in Brahman heifers. Twelve genes in ROH islands were associated with lipid metabolic process (GO:0006629) in the BP group. Of these genes, BMP2 (bone morphogenetic protein 2, on BTA13) plays a major role in rebuilding hair follicles in goats [43]. Further, BMP2 in porcine, cattle and sheep has been reported to have an influence on regulating body size and muscle development [44-47]. Kim et al. [48] found several signatures of selection containing genes such as BMP2 associated with body size and development in goats and sheep native to Egypt. These researchers concluded that the genes influencing body size may be important in regulating adaptation to hot, arid habitats because efficiency in thermoregulation can be associated with body size. Supporting their conclusion is the fact that most breeds in tropical zones have smaller body size than breeds in temperate zones because tropical breeds can regulate their body temperature more efficiently [49]. However, other factors that differ between temperate and arid zones may also contribute to variations in the body sizes of breeds living in different climates. CYP27B1 (cytochrome P450 family 27 subfamily B member 1) located on BTA5 was also one of the genes enriched in the lipid metabolic process (GO:0006629). This gene is important for making 1-α-hydroxylase, which is required in vitamin D bio-activation, and has been reported to be up-regulated as a result of bacterial infection, suggesting that this gene plays a role in modulating innate immune responses [50]. In ROH islands on BTA13, three genes were associated with the positive regulation of DNA replication (GO:0045740) in the BP group. Proliferating cell nuclear antigen (PCNA) has been reported to be associated with follicular development and growth in buffalo ovaries [51], and may therefore be related to fertility performance. Single-organism cellular process (GO:0044763) with 64 genes was significantly enriched ( P =0.05) in ROH islands, including MARS (methionyl-tRNA synthetase, on BTA5), and ADRA1D (adrenoceptor alpha 1D, on BTA13). MARS has been reported to influence milk and protein production in Chinese [52] and Portuguese [53] Holstein cattle, and ADRA1D largely affects milk protein in Murrah dairy buffalo [54]. INHBC and INHBE (inhibin beta C and E subunits, on BTA5) have been reported as candidate genes associated with reproductive performance in tropical young bulls [55], and composite reproductive traits in Lori-Bakhtiari sheep [56]. KCTD16 (potassium channel tetramerization domain containing 16, on BTA7) was reported as a candidate gene for meat quality in Simmental beef cattle [57], for residual feed intake in Junmu White pigs [58], and for fat yield in Nordic Holstein cattle [59]. PMEL (premelanosome protein) and MYO1A (myosin IA) on BTA5 have been reported as putative candidate genes related to coat colour phenotypes in cattle [60, 61]. PMEL is required for the melanin biosynthesis process in the pigmentation of hair, mucous membranes and eyes [62]. In cattle, PMEL is reported as a candidate gene associated with the dilution of coat colour and consequently colour intensity [63, 64]. Light coat colouring can be beneficial for animals in adapting to hot climates because it can help them to reduce sunlight absorption [65]. However, most of the AZ and KHZ buffalo have a dark coat, which could be a result of some other favourable traits associated with a darker coat colour or the result of artificial selection caused by human interference. SUOX (Sulphite oxidase, on BTA5), within this BP category, was reported to be associated with bone development in cattle [66]. The average LD (r 2 ) between adjacent SNPs in ROH islands was higher than the r 2 of adjacent SNPs located on the same chromosome (Additional file 3). Thus, the recombination rates in the ROH islands were lower than those in the rest of the genome. These results are in line with some previous studies [13, 17]. However, a moderate recombination rate has been reported between the SNPs in ROH islands in Valle del Belice sheep [67]. Additionally, ROH hotspots can result from a wide range of underlying causes such as inbreeding and selection [12]. Peripolli et al. [13] argued that the high LD observed in most ROH hotspots is not necessarily caused by selection or conserved IBD haplotypes, but can be an indication of a lower recombination rate in those regions. Nevertheless, most of the ROH hotspots in our study overlapped with selection signature regions found with iHS, which supports the theory that ROH can be used to find genomic regions that have been under natural and/or artificial selection. Buffalo species have a relatively lower heat tolerance capability than some other livestock species because of their inadequately dispersed sweat glands and their dark coat colour [68]. However, Iranian buffalo breeds have historically been raised in a hot climate [69]. Therefore, selection for higher heat tolerance may have occurred in Iranian buffalo for better adaptation to heat stress [5]. It has been reported that combined networks of multiple genes are often involved in the regulation of complex traits such as adaptation to hot climates [48, 70, 71]. Thus, selection for complex traits would leave only minor footprints because of the selection for numerous regions with lower intensity across the genome [70]. Therefore, we expected to find several genes directly or indirectly influencing different traits that were under artificial selection or important for adaptation and survival in hot areas. We found genes influencing energy and digestive metabolism (KCTD16), autoimmune response (CYP27B1), thermoregulation (BMP2), embryonic development and reproduction (STAT6, PCNA, INHBC and INHBE). These genes seem to be important for species such as water buffalo that have adapted to a hot climate [48]. Conclusion The inbreeding coefficients based on F HOM , F UNI and F GRM were higher in the AZ breed than they were in the KHZ breed, which contradicted our expectations according to higher N e in AZ breed. Given that F ROH was the only measurement of inbreeding in our study that showed AZ water buffalo were more inbred, this measurement seems to be a suitable measure of genomic inbreeding. This is most likely because it is less affected by allele frequencies. Further, knowing the distribution of ROH across the genome, inbreeding can be avoided more efficiently through mating allocation. Additionally, frequently occurring ROH can be used as suggestive evidence of historical selection. In our study, we found some overlap between ROH islands and genomic regions showing signatures of selection in previous studies of AZ and KHZ breeds. Therefore, the genes located in ROH islands could be under the influence of artificial and/or natural selection. We found that the genes located in ROH islands were associated with biological pathways such as adaptation to a hot climate, immune response, milk production, growth efficiency, reproduction performance and bone development. Methods Sample collection, ethical statement, and data quality control Hair roots and blood samples were obtained from 112 herds of AZ and 47 herds of KHZ breeds. Samples of the AZ breed were gathered from East and West Azerbaijan, Gilan and Ardabil (37.02° – 38.78° N, 44.81° 49.52°E), which are north-western provinces of Iran. Samples of the KHZ breed were obtained from Kermanshah (34.54°N, 45.60°E) and Khuzestan (30.68–32.55° N, 48.02°–48.97° E), which are the south and south-western provinces of Iran, respectively (Fig. 1). All practices relating to data collection were reviewed and confirmed by the research ethics committee of the College of Agriculture and Natural Resources of the University of Tehran, Iran and by the ABCI. Three hundred and sixty-nine buffalo (254 AZ and 115 KHZ) were genotyped using 90K SNPChip (Axiom ® Buffalo 90K Genotyping Array), which consisted of 89 988 almost evenly distributed SNPs throughout the genome. The same dataset was previously used by Mokhber et al. [5], and it partially overlapped with the dataset used by Colli et al. [4] and by Fallahi et al. [72]. The SNPs in the 90K SNPChip were selected using buffalo DNA sequence, but similar to methods used in previous studies [1, 5, 33, 72-75], were reported according to the location on the cattle reference genome assembly (UMD3.1 [76]) Although chromosome-level assembly of the water buffalo genome (UOA_WB_1) has been published recently [77], we used the UMD3.1 assembly in our study because it is more reliable and has better gene annotation information. Genotypes were obtained through AffyPipe [78], and all the monomorphic and polymorphic SNPs with high resolution (n=64 750) were stored. According to the filtration criteria, samples with more than 5% missing genotype and SNPs with 5% missing rate were eliminated from further analyses. We also filtered out SNPs with unidentified position in the UMD3.1 assembly, positioned on the sex chromosomes, with minor allele frequency of <2%, and with p-value for the Hardy–Weinberg equilibrium chi-square test <10 -6 . In total, 62 122 SNPs and 369 samples with an average call rate of 99.6% passed the quality-control filters. Genetic distance between breeds Genetic distance, which is based on the IBS matrix, was estimated through the --ibs-matrix command in PLINK v1.9 [79]. Principal component (PC) analysis of genetic distances was performed to visualise the genetic diversity of the samples, and was depicted using R ( http://www.R-project.org/ ). According to the first and second PCs, we removed four samples: two from each breed that were placed outside their expected breed cluster. Runs of homozygosity analyses ROH can be detected in the genome through two main approaches: 1) genotype-counting algorithms in which the genome is scanned to identify long stretches of consecutive homozygous genotypes like the one implemented in PLINK v1.9 [79], and 2) model-based methods that utilize Hidden Markov Models (HMM) like the one implemented in RzooRoH [80]. This package can enable a better assessment of the contribution of various generations to the current level of inbreeding, estimating inbreeding at both genome-wide and local scales, and classifying homozygous‐by‐descent (HBD) segments into age-based classes [81]. However, we used PLINK in our study because of the simplicity of running the sliding-window approach to detect ROH with sufficiently high assurance [82]. A genome scan for ROH was conducted for the AZ (n=252) and KHZ (n=113) breeds, separately. For each individual, ROH segments with the following attributes were identified: 1) each ROH stretch was at least 1 Mb in length; 2) there was at the most only one heterozygous and one missing SNP in each ROH; 3) there was a minimum number of SNPs that could form ROH in each breed, calculated according to Eq. 1 to control the false positive rate of the identified ROH. (see Equation 1 in the Supplementary Files) where l is the minimum number of SNPs in ROH, α is the false positive rate of the identified ROH (set at 0.5); n a and n s are the number of individuals and the number of SNPs per individual, respectively; and het is the average heterozygosity across individuals. l was calculated to be 40 and 38 in AZ and KHZ breeds, respectively; 4) each ROH contained at least one SNP over 100 Kb; and 5) the maximum gap between two neighbouring SNPs in ROH had to be less than 1 Mb. The ROH that had these five attributes were divided into the following five groups: 1-2, 2-4, 4-8, 8-16 and >16 Mb, as suggested in the literature [13, 15, 25]. Then for each breed, the frequency and the average length (Mb) of ROH within each category, the percentage of each ROH category, and the percentage of genome coverage by each ROH category were calculated, using R ( http://www.R-project.org/ ). Inbreeding coefficient estimations The coefficient of inbreeding was estimated using ROH (F ROH ), excess of homozygosity (F HOM ), correlation between uniting gametes (F UNI ) and diagonal elements of the genomic relationship matrix (F GRM ). F ROH was calculated for each individual using Eq. 2 [20]: (see Equation 2 in the Supplementary Files) where is the inbreeding coefficient of animal i ; n is the total number of ROH; and is the length of the j th ROH in animal i ; L aut is the total autosome length covered by the SNP markers (2.5 Gb in our study). We also calculated the following three different genomic inbreeding estimations: F GRM (Eq. 3), F HOM (Eq. 4) and F UNI (Eq. 5) using --ibc command in GCTA software [39]. (see Equations 3-5 in the Supplementary Files) where x i and p i are the number of copies and the frequency of the reference allele for SNP i , respectively; h i is 2 p i (1-2 p i ); and n is the total number of SNPs. The Pearson’s correlation coefficient between F ROH and the other genomic inbreeding estimates was also calculated. Frequently appearing runs of homozygosity and gene enrichment analyses To detect the genomic regions frequently covered with ROH in the AZ and KHZ populations, the number of times each SNP occurred in ROH was calculated separately in each breed. The ROH repeated in more than 20% of the individuals in each breed (approximately less than 1% of the SNPs) were nominated ROH islands, as suggested in previous studies [25, 67]. Further, the frequency of ROHs were plotted against their physical position along UMD3.1. To identify genes in ROH islands, we used UMD3.1 map viewer from the NCBI website ( https://www.ncbi.nlm.nih.gov/mapview/ ). Additionally, to find significantly enriched Gene Ontology (GO) terms ( P ≤0.05) of the genes located in ROH peaks, we used DAVID v6.8 tool [83, 84]. Finally, we performed an extensive literature review to explore the biological function of the annotated genes in ROH islands. To discover whether ROH islands were associated with regions of the genome with a low recombination rate, the average LD of all the adjacent SNPs across each chromosome was compared with the average LD between adjacent SNPs inside the ROH islands located on the same chromosome. Additionally, to discover whether the ROH hotspots were associated with genomic regions that showed signatures of selection through other methods, we compared ROH islands with integrated haplotype homozygosity scores (iHS) that had already been published for AZ and KHZ breeds [5]. An iHS is a measure of haplotype homozygosity based on the difference between observed LD structure around a selected allele relative to the expected LD pattern according to the whole genome [85]. Therefore, it can be used to detect regions under historical selection [85]. List Of Abbreviations ROH: runs of homozygosity; SNP: single nucleotide polymorphism; AZ: Azeri breed; KHZ: Khuzestani breed; MZ: Mazandarani breed; GO: Gene Ontology; IBD: identical by descent; IBS: identical by state; Ne: effective population size; FROH: inbreeding coefficient calculated using ROH; FHOM: inbreeding coefficient calculated using excess of homozygosity; FUNI: inbreeding coefficient calculated using correlation between uniting gametes; FGRM: inbreeding coefficient calculated using diagonal elements of the genomic relationship matrix; LD: linkage disequilibrium; ABCI: Animal Breeding Centre of Iran; PC: principal component; iHS: integrated haplotype homozygosity score. Declarations Ethics approval and consent to participate The procedure was in accordance with animal ethics and approved by the University of Tehran and Animal Breeding Centre of Iran (ABCI) authorized representatives. Indications, risks, and benefits explained to animal owners and depending on his/her literacy, written or verbal informed consent obtained before the initiation of sampling. Consent for publication Not applicable. Availability of data and material All data generated or analyzed during this study are included in this published article and its supplementary information files. Competing interest The authors declare that they have no competing interests. Funding We have received no specific funding for the current study. Authors’ contributions SMG, HMS and MMS conceived and designed the study, SMG, MHF and AJS analysed the data and SMG wrote the paper. RAA and MKH revised the manuscript. All authors read and approved the final manuscript. Acknowledgments The authors gratefully acknowledge the Animal Breeding Centre of Iran (ABCI) and Towsee Kesht va Dam Noandish Alborz Co (Takdna) for giving us access to the animals and recording. 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Summary of the detected runs of homozygosity (ROH) grouped according to their length (Mb). ROH group nROH 1 Percentage Average length (Mb) Standard deviation (Mb) Percentage of genome coverage AZ KHZ AZ KHZ AZ KHZ AZ KHZ AZ KHZ ROH 1-2 841 629 15.71 16.77 1.83 1.81 0.13 0.15 0.06 0.05 ROH 2-4 2870 2119 53.62 56.51 2.70 2.71 0.53 0.53 0.31 0.23 ROH 4-8 855 609 15.98 16.24 5.44 5.38 1.09 1.08 0.19 0.13 ROH 8-16 484 241 9.04 6.42 11.23 11.22 2.25 2.21 0.22 0.11 ROH >16 302 152 5.64 4.05 26.70 26.19 11.06 9.32 0.32 0.16 Number of runs of homozygosity segments Table 2. Average inbreeding coefficients (± standard error) estimated using diagonal elements of genomic relationship matrix (F GRM ), excess of homozygosity (F HOM ), correlation between uniting gametes (F UNI ) and runs of homozygosity (ROH) > 1 Mb (F ROH ) in Azeri (AZ) and Khuzestani (KHZ) breeds. Breed F GRM F HOM F UNI F ROH AZ 0.026±0.05 0.026±0.0.05 0.026±0.05 0.043±0.05 KHZ 0.019±0.04 0.021±0.06 0.021±0.05 0.059±0.04 Table 3. Correlation between inbreeding coefficients calculated using runs of homozygosity (ROH) > 1 Mb (F ROH ) and estimated using diagonal elements of genomic relationship matrix (F GRM ), excess of homozygosity (F HOM ), and correlation between uniting gametes (F UNI ) in Azeri (AZ) and Khuzestani (KHZ) breeds. Breed Correlation coefficient F GRM -F ROH F HOM -F ROH F UNI -F ROH AZ 0.88 0.92 0.98 KHZ 0.78 0.93 0.94 Additional File Legends Additional file 1: List of the detected runs of homozygosity (ROH) in Azeri (AZ) and Khuzestani (KHZ) breeds. Additional file 2. The estimated inbreeding coefficient using runs of homozygosity (ROH) >1 Mb (F ROH ), diagonal elements of genomic relationship matrix (F GRM ), excess of homozygosity (F HOM ) and correlation between uniting gametes (F UNI ) in Azeri (AZ) and Khuzestani (KHZ) breeds. Additional file 3. Frequently occurring runs of homozygosity (ROH) regions (i.e. ROH islands) in Azeri (AZ) and Khuzestani (KHZ) breeds. The last column represents the average r 2 of ROH islands divided by the average r 2 of each chromosome. Additional file 4. The genes located in detected runs of homozygosity (ROH) islands in the Khuzestani (KHZ) breed that were significantly enriched ( P ≤0.05) in biological processes (BP), cellular component (CC) and molecular function (MF) Gene Ontology (GO) terms. Additional file 5. List of integrated haplotype homozygosity scores (iHS) for all SNPs in Azeri (AZ) and Khuzestani (KHZ) breeds. Additional file 6. Manhattan plot of integrated haplotype homozygosity score (iHS) across the genome. Supplementary Files Equations.pdf additionalfile5.csv Additionalfile1.csv AdditionalFile6.tif additionalfile2.csv additionalfile3.csv additionalfile4.csv Cite Share Download PDF Status: Published Journal Publication published 10 Feb, 2020 Read the published version in BMC Genetics → Version 5 posted You are reading this latest preprint version Show more versions Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {\"props\":{\"pageProps\":{\"initialData\":{\"identity\":\"rs-8193\",\"acceptedTermsAndConditions\":true,\"allowDirectSubmit\":false,\"archivedVersions\":[],\"articleType\":\"Research article\",\"associatedPublications\":[],\"authors\":[{\"id\":332196,\"identity\":\"cc4c4dcd-a857-412a-acc0-0832ab2e1967\",\"order_by\":1,\"name\":\"Seyed Mohammad Ghoreishifar\",\"email\":\"\",\"orcid\":\"\",\"institution\":\"University of Tehran\",\"correspondingAuthor\":false,\"submittingAuthor\":false,\"prefix\":\"\",\"firstName\":\"Seyed\",\"middleName\":\"Mohammad\",\"lastName\":\"Ghoreishifar\",\"suffix\":\"\"},{\"id\":332197,\"identity\":\"a90591ee-d754-4f4d-a533-b451098232e6\",\"order_by\":2,\"name\":\"Hossein Moradi-Shahrbabak\",\"email\":\"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAuUlEQVRIiWNgGAWjYBACAzDJJsHADxXgIV6LZAMzaVqAjAPMRDrMXOzwsQ8/yizsjW/kH2D4UcMgY95AQIvl7LTkmT3nJBK33UhmYOw5xsAjc4CQw27nGDPwtkkkmAG1MPA2MPBIEHIYSAvj3zYJe+MZQFv+EquFGWgL4waJZAZmIm1JS2aWAfplxpnHBodljkkQoyX5MOObsjp7/vbEhw/f1NjYE9SCAg4wMJCmYRSMglEwCkYBDgAA19g0vXbh0bQAAAAASUVORK5CYII=\",\"orcid\":\"https://orcid.org/0000-0002-6680-7662\",\"institution\":\"University of Tehran\",\"correspondingAuthor\":true,\"submittingAuthor\":false,\"prefix\":\"\",\"firstName\":\"Hossein\",\"middleName\":\"\",\"lastName\":\"Moradi-Shahrbabak\",\"suffix\":\"\"},{\"id\":332198,\"identity\":\"3e990d7a-4eb0-49b8-9209-2c1b7568ff5f\",\"order_by\":3,\"name\":\"Mohammad Hossein Fallahi\",\"email\":\"\",\"orcid\":\"\",\"institution\":\"University of Tehran\",\"correspondingAuthor\":false,\"submittingAuthor\":false,\"prefix\":\"\",\"firstName\":\"Mohammad\",\"middleName\":\"Hossein\",\"lastName\":\"Fallahi\",\"suffix\":\"\"},{\"id\":332199,\"identity\":\"7bf96490-79f2-48d3-8806-70b9e1a34706\",\"order_by\":4,\"name\":\"Ali Jalil Sarghale\",\"email\":\"\",\"orcid\":\"\",\"institution\":\"University of Tehran\",\"correspondingAuthor\":false,\"submittingAuthor\":false,\"prefix\":\"\",\"firstName\":\"Ali\",\"middleName\":\"Jalil\",\"lastName\":\"Sarghale\",\"suffix\":\"\"},{\"id\":332200,\"identity\":\"e104ac9a-c715-4c3d-95ae-22d06137a894\",\"order_by\":5,\"name\":\"Mohammad Moradi-Shahrbabak\",\"email\":\"\",\"orcid\":\"\",\"institution\":\"University of Tehran\",\"correspondingAuthor\":false,\"submittingAuthor\":false,\"prefix\":\"\",\"firstName\":\"Mohammad\",\"middleName\":\"\",\"lastName\":\"Moradi-Shahrbabak\",\"suffix\":\"\"},{\"id\":332201,\"identity\":\"db0553a8-f651-4153-b203-ebc5a69a48c4\",\"order_by\":6,\"name\":\"Rostam Abdollahi-Arpanahi\",\"email\":\"\",\"orcid\":\"\",\"institution\":\"University of Tehran\",\"correspondingAuthor\":false,\"submittingAuthor\":false,\"prefix\":\"\",\"firstName\":\"Rostam\",\"middleName\":\"\",\"lastName\":\"Abdollahi-Arpanahi\",\"suffix\":\"\"},{\"id\":332202,\"identity\":\"dfd4574e-67a1-4953-8845-dd7cc052868e\",\"order_by\":7,\"name\":\"Majid Khansefid\",\"email\":\"\",\"orcid\":\"\",\"institution\":\"AgriBio\",\"correspondingAuthor\":false,\"submittingAuthor\":false,\"prefix\":\"\",\"firstName\":\"Majid\",\"middleName\":\"\",\"lastName\":\"Khansefid\",\"suffix\":\"\"}],\"badges\":[],\"createdAt\":\"2019-11-19 12:45:03\",\"currentVersionCode\":5,\"declarations\":\"\",\"doi\":\"10.21203/rs.2.17561/v5\",\"doiUrl\":\"https://doi.org/10.21203/rs.2.17561/v5\",\"draftVersion\":[],\"editorialEvents\":[{\"content\":\"https://doi.org/10.1186/s12863-020-0824-y\",\"type\":\"published\",\"date\":\"2020-02-10T12:00:00+00:00\"}],\"editorialNote\":\"\",\"failedWorkflow\":false,\"files\":[{\"id\":453632,\"identity\":\"5df0efca-5351-4b43-a164-fed40f9f8d8a\",\"added_by\":\"auto\",\"created_at\":\"2020-02-05 18:35:02\",\"extension\":\"png\",\"order_by\":1,\"title\":\"Figure 1\",\"display\":\"\",\"copyAsset\":false,\"role\":\"figure\",\"size\":810069,\"visible\":true,\"origin\":\"\",\"legend\":\"Geographic distribution of Azeri (AZ) and Khuzestani (KHZ) breeds used in this study. The samples of the AZ breed were obtained from the provinces shown in red (located in north and north-western part of Iran i.e. East and West Azerbaijan, Ardabil and Gilan). The samples for the Khuzestani (KHZ) breed were taken from the provinces shown in green (located in the west and south-western part of Iran i.e. Khuzestan and Kermanshah). Reprinted from “A genome-wide scan for signatures of selection in Azeri and Khuzestani buffalo breeds,” by Mahdi Mokhber et al., 2018;BMC Genom., 19(1), 449. Copyright 2018 by the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/). Reprinted with permission.\",\"description\":\"\",\"filename\":\"fig1.png\",\"url\":\"https://assets-eu.researchsquare.com/files/eb474c10-ff68-41b9-9bf3-bf9a673b2dc9/v5/fig 1.png\"},{\"id\":453635,\"identity\":\"6f69df86-6873-40f4-85bb-5ca93357b728\",\"added_by\":\"auto\",\"created_at\":\"2020-02-05 18:35:03\",\"extension\":\"jpg\",\"order_by\":2,\"title\":\"Figure 2\",\"display\":\"\",\"copyAsset\":false,\"role\":\"figure\",\"size\":73145,\"visible\":true,\"origin\":\"\",\"legend\":\"Azeri (AZ) and Khuzestani (KHZ) breeds clustered according to principal component (PC) analysis of identical by state (IBS) distance matrix. The first and second PCs explain 7.02% and 5.63% of the total variance, respectively.\",\"description\":\"\",\"filename\":\"Fig2.jpg\",\"url\":\"https://assets-eu.researchsquare.com/files/eb474c10-ff68-41b9-9bf3-bf9a673b2dc9/v5/Fig 2.jpg\"},{\"id\":453637,\"identity\":\"41211ccc-5714-4a76-b336-7f8b9a7ba879\",\"added_by\":\"auto\",\"created_at\":\"2020-02-05 18:35:03\",\"extension\":\"jpg\",\"order_by\":3,\"title\":\"Figure 3\",\"display\":\"\",\"copyAsset\":false,\"role\":\"figure\",\"size\":96552,\"visible\":true,\"origin\":\"\",\"legend\":\"Number of runs of homozygosity (ROH) and the length of the genome covered by ROH in the samples taken from the Azeri (AZ) and Khuzestani (KHZ) breeds.\",\"description\":\"\",\"filename\":\"3new1.jpg\",\"url\":\"https://assets-eu.researchsquare.com/files/eb474c10-ff68-41b9-9bf3-bf9a673b2dc9/v5/3_new1.jpg\"},{\"id\":453639,\"identity\":\"1fd56ffe-3ada-4087-b33c-9adb584f9983\",\"added_by\":\"auto\",\"created_at\":\"2020-02-05 18:35:04\",\"extension\":\"jpg\",\"order_by\":4,\"title\":\"Figure 4\",\"display\":\"\",\"copyAsset\":false,\"role\":\"figure\",\"size\":323276,\"visible\":true,\"origin\":\"\",\"legend\":\"Manhattan plot of the distribution of frequently occurring runs of homozygosity (ROH) in Azeri (AZ) and Khuzestani (KHZ) Iranian water buffalo breeds. The X-axis shows the distribution of ROH over the genome, and the Y-axis shows the percentage of ROH shared among animals within each breed. The significance threshold of 20% (less than 1% of all SNPs) shown as a blue line is used for detecting ROH islands (green arrows).\",\"description\":\"\",\"filename\":\"Fig4.jpg\",\"url\":\"https://assets-eu.researchsquare.com/files/eb474c10-ff68-41b9-9bf3-bf9a673b2dc9/v5/Fig 4.jpg\"},{\"id\":13488040,\"identity\":\"eb300398-9123-4c44-ad5c-40e330ae4a70\",\"added_by\":\"auto\",\"created_at\":\"2021-09-16 22:13:06\",\"extension\":\"pdf\",\"order_by\":0,\"title\":\"\",\"display\":\"\",\"copyAsset\":false,\"role\":\"manuscript-pdf\",\"size\":1239449,\"visible\":true,\"origin\":\"\",\"legend\":\"\",\"description\":\"\",\"filename\":\"manuscript.pdf\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-8193/v5/5d7301aa-4b7f-4843-ac7e-d0b423f838ab.pdf\"},{\"id\":453642,\"identity\":\"68c8a603-84e4-46a9-9c8a-5c413e9977ed\",\"added_by\":\"auto\",\"created_at\":\"2020-02-05 18:35:04\",\"extension\":\"pdf\",\"order_by\":0,\"title\":\"\",\"display\":\"\",\"copyAsset\":false,\"role\":\"supplement\",\"size\":42830,\"visible\":true,\"origin\":\"\",\"legend\":\"\",\"description\":\"\",\"filename\":\"Equations.pdf\",\"url\":\"https://assets-eu.researchsquare.com/files/eb474c10-ff68-41b9-9bf3-bf9a673b2dc9/v5/Equations.pdf\"},{\"id\":453641,\"identity\":\"5044568e-0ff6-4f3e-a1dc-f1e094615c7e\",\"added_by\":\"auto\",\"created_at\":\"2020-02-05 18:35:04\",\"extension\":\"csv\",\"order_by\":0,\"title\":\"\",\"display\":\"\",\"copyAsset\":false,\"role\":\"supplement\",\"size\":3267582,\"visible\":true,\"origin\":\"\",\"legend\":\"\",\"description\":\"\",\"filename\":\"additionalfile5.csv\",\"url\":\"https://assets-eu.researchsquare.com/files/eb474c10-ff68-41b9-9bf3-bf9a673b2dc9/v5/additional file_5.csv\"},{\"id\":453640,\"identity\":\"0c522a29-56b8-466d-bc9f-fd4413f9cf05\",\"added_by\":\"auto\",\"created_at\":\"2020-02-05 18:35:04\",\"extension\":\"csv\",\"order_by\":0,\"title\":\"\",\"display\":\"\",\"copyAsset\":false,\"role\":\"supplement\",\"size\":659232,\"visible\":true,\"origin\":\"\",\"legend\":\"\",\"description\":\"\",\"filename\":\"Additionalfile1.csv\",\"url\":\"https://assets-eu.researchsquare.com/files/eb474c10-ff68-41b9-9bf3-bf9a673b2dc9/v5/Additional file_1.csv\"},{\"id\":453638,\"identity\":\"465a2a8f-b883-4e04-b7b7-c32aeacef5e1\",\"added_by\":\"auto\",\"created_at\":\"2020-02-05 18:35:03\",\"extension\":\"tif\",\"order_by\":0,\"title\":\"\",\"display\":\"\",\"copyAsset\":false,\"role\":\"supplement\",\"size\":200028,\"visible\":true,\"origin\":\"\",\"legend\":\"\",\"description\":\"\",\"filename\":\"AdditionalFile6.tif\",\"url\":\"https://assets-eu.researchsquare.com/files/eb474c10-ff68-41b9-9bf3-bf9a673b2dc9/v5/Additional File_6.tif\"},{\"id\":453636,\"identity\":\"0ca78a79-fd3b-4030-9af1-31a5928b33e1\",\"added_by\":\"auto\",\"created_at\":\"2020-02-05 18:35:03\",\"extension\":\"csv\",\"order_by\":0,\"title\":\"\",\"display\":\"\",\"copyAsset\":false,\"role\":\"supplement\",\"size\":19782,\"visible\":true,\"origin\":\"\",\"legend\":\"\",\"description\":\"\",\"filename\":\"additionalfile2.csv\",\"url\":\"https://assets-eu.researchsquare.com/files/eb474c10-ff68-41b9-9bf3-bf9a673b2dc9/v5/additional file_2.csv\"},{\"id\":453634,\"identity\":\"a8ffad02-920f-401c-96d0-b13d01d98db4\",\"added_by\":\"auto\",\"created_at\":\"2020-02-05 18:35:03\",\"extension\":\"csv\",\"order_by\":0,\"title\":\"\",\"display\":\"\",\"copyAsset\":false,\"role\":\"supplement\",\"size\":860,\"visible\":true,\"origin\":\"\",\"legend\":\"\",\"description\":\"\",\"filename\":\"additionalfile3.csv\",\"url\":\"https://assets-eu.researchsquare.com/files/eb474c10-ff68-41b9-9bf3-bf9a673b2dc9/v5/additional file_3.csv\"},{\"id\":453633,\"identity\":\"684c5fec-dab4-4c98-bad6-b4c542286d23\",\"added_by\":\"auto\",\"created_at\":\"2020-02-05 18:35:03\",\"extension\":\"csv\",\"order_by\":0,\"title\":\"\",\"display\":\"\",\"copyAsset\":false,\"role\":\"supplement\",\"size\":20202,\"visible\":true,\"origin\":\"\",\"legend\":\"\",\"description\":\"\",\"filename\":\"additionalfile4.csv\",\"url\":\"https://assets-eu.researchsquare.com/files/eb474c10-ff68-41b9-9bf3-bf9a673b2dc9/v5/additional file_4.csv\"}],\"financialInterests\":\"\",\"formattedTitle\":\"Genomic measures of inbreeding coefficients and genome-wide scan for runs of homozygosity islands in Iranian river buffalo, Bubalus bubalis\",\"fulltext\":[{\"header\":\"Background\",\"content\":\"\\u003cp\\u003eThere are two main species of buffalo: the Asian water buffalo (\\u003cem\\u003eBubalus bubalis\\u003c/em\\u003e) and the African wild buffalo (\\u003cem\\u003eSyncerus caffer\\u003c/em\\u003e), the second of which is also known as the cape buffalo [1, 2]. Domestication of \\u003cem\\u003eB.\\u003c/em\\u003e\\u003cem\\u003e bubalis\\u003c/em\\u003e, including of the river (\\u003cem\\u003eB. bubalis bubalis\\u003c/em\\u003e, 2n=50) and swamp (\\u003cem\\u003eB. bubalis\\u003c/em\\u003e \\u003cem\\u003ecarabanensis\\u003c/em\\u003e, 2n=48) subspecies, occurred approximately 3000\\u0026ndash;6000 years ago [3]. The domestication of river buffalo occurred in the Indo\\u0026ndash;Pakistani area, and domestication of swamp buffalo occurred close to the border of China [4]. River buffalo expanded broadly from India, Egypt and Southeast Asia to Europe, and the swamp buffalo is the most common type of buffalo in China and Southeast Asia [3-5]. The worldwide water buffalo population accounts for only approximately 11% of the entire cattle population. However, the population of water buffalo has increased in the past five decades by approximately 1.65% annually [5]. India, Pakistan and Europe (with 5.3%, 4.8% and 4.5% rates of increase, respectively) have the highest rates of annual increase [6]. \\u0026nbsp;\\u003c/p\\u003e\\n\\u003cp\\u003eIn many tropical and subtropical countries, river buffalo are raised for both meat and milk production [7]. In Iran and in other developing nations, river buffalo production is of great economic importance because of the ability of buffalo to make the best use of low-quality feed in the production of their valuable milk, which has a unique taste and curd properties, high resistance to local parasites, high adaptation to harsh climate conditions, and long productive lifespan. The three major Iranian river buffalo breeds are Azeri (AZ), Khuzestani (KHZ) and Mazandarani (MZ), and each of these breeds belongs to different geographical zone [2]. The AZ, KHZ and MZ are common in the north-west and north, west and south-west, and north of the country, respectively. In Iran, the recording of milk and meat production, and the selective breeding of buffalo for better dairy performance (i.e. in milk production, and fat and protein percentage) and better meat production are performed by the Animal Breeding Centre of Iran (ABCI) [2]. Following performance and pedigree recording in some herds, and genetic analysis, candidate bulls are selected from rural herds based on their genetic merits, and the semen of these selected bulls is collected and distributed to all herds [2]. However, despite buffalo production being important in Iran, particularly in rural regions, controlling inbreeding and ensuring genetic improvement of desired traits through traditional breeding programmes are difficult because of a shortage of reliable pedigree and performance records for water buffalo in the country.\\u003c/p\\u003e\\n\\u003cp\\u003eThe inbreeding coefficient measured from pedigree information (F\\u003csub\\u003ePED\\u003c/sub\\u003e) has been the most common parameter for describing the level of inbreeding since Wright [8] However, the reliability of the estimated F\\u003csub\\u003ePED\\u003c/sub\\u003e depends on the completeness and correctness of pedigree. With the availability of high-density SNP-chip markers, inbreeding can also be defined according to genomic information such as genome-wide autozygosity [9] Autozygosity occurs when parents pass identical chromosomal fragments, which they already inherited from a common ancestor, on to their offspring [10]; these genomic regions of homozygosity are known as runs of homozygosity (ROH) [11, 12]. Estimated inbreeding based on ROH (F\\u003csub\\u003eROH\\u003c/sub\\u003e) can discriminate between homozygous (i.e. identical by descent [IBD]) and non-autozygous (i.e. identical by state [IBS]) positions in the genome [9]. Further, well-recorded pedigree information is not required to have reliable F\\u003csub\\u003eROH\\u003c/sub\\u003e. Thus, using genetic markers instead of pedigree information to calculate inbreeding can produce more robust estimates [13, 14].\\u003c/p\\u003e\\n\\u003cp\\u003eIdentifying ROH can also help to find the footprints of genetic selection on the genome [15-17]. However, ROH are suggestive, but not conclusive, of genomic regions under natural or artificial selection because the incidence, extent and distribution of ROH across the genome are influenced by many factors other than ROH, such as recombination rate, population structure, mutation rate and inbreeding [16]. Nevertheless, ROH that frequently occur among individuals may contain genes associated with different traits that have been under historical selection, so that the genes located in ROH islands can be important for selective breeding [13, 15, 18]. ROH can also provide detailed information on the genetic relatedness of animals, which allows breeders to better control inbreeding in the population [16]. This allows mate allocation aiming to minimise inbreeding at the genome level to be achieved more precisely, and the individual animals that have high proportions of ROH coverage to be excluded or used less frequently in mating [16]. The distribution and the occurrence of ROH have been studied in humans [10, 11, 19, 20], cattle [13-15, 18, 21-26], pigs [27-29] and sheep [17, 30-32] but are poorly studied in some species, for example, in water buffalo.\\u003c/p\\u003e\\n\\u003cp\\u003eThe current study aims to estimate autozygosity in the genome of AZ and KHZ buffalo breeds, and identify ROH spots that frequently occur among the individuals. The study also examines the function of the genes located in ROH islands to identify potential selection signature regions. Moreover, the study compares F\\u003csub\\u003eROH\\u003c/sub\\u003e with other genomic methods of inbreeding estimation.\\u003c/p\\u003e\"},{\"header\":\"Results \",\"content\":\"\\u003cp\\u003e\\u003cem\\u003eRuns of homozygosity\\u003c/em\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003eThe AZ and KHZ are two major buffalo breeds adapted to distinct geographical areas in Iran [2, 5] (Fig. 1). The PC analysis of the IBS matrix derived from SNP data confirmed two separate populations with no overlap, which means that the samples from the AZ and KHZ breeds were genetically different (Fig. 2). Although Mokhber et al. [5] reported that AZ and KHZ are two distinct populations, they reported a moderate level of admixture between the AZ and MZ breeds. Thus, we excluded the MZ breed from our study. In total, 9102 ROH were detected, 5352 ROH in the AZ genome and 3750 in the KHZ genome (Table\\u0026nbsp;1; Additional file\\u0026nbsp;1). The average number of ROH per individual was 21.23\\u0026plusmn;13.06 in the AZ breed (ranging from 4 to 88) and 33.2\\u0026plusmn;15.92 in the KHZ breed (ranging from 4 to 132). Moreover, all of the individuals in our study had at least four ROH longer than 1\\u0026nbsp;Mb. The variation between samples in total number of ROH and total length of ROH are presented in Fig. 3. Individuals with an almost equal portion of the genome covered by ROH had different numbers and lengths of ROH, which could be an indication of different combinations of recent and distant inbreeding events in the samples.\\u0026nbsp;\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cem\\u003eEvaluation of different methods of genomic inbreeding\\u003c/em\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003eTable 2 presents the averages of the estimated inbreeding coefficients using different methods (see also Additional file 2). The average F\\u003csub\\u003eROH\\u003c/sub\\u003e calculated from ROH \\u0026gt;1\\u0026nbsp;Mb in length was 0.043\\u0026plusmn;0.05 in the AZ breed and 0.059\\u0026plusmn;0.04 in the KHZ breed (Table 2; Additional file\\u0026nbsp;1). The estimated inbreeding values based on F\\u003csub\\u003eHOM\\u003c/sub\\u003e, F\\u003csub\\u003eUNI\\u003c/sub\\u003e and F\\u003csub\\u003eGRM\\u003c/sub\\u003e were higher in AZ than they were in KHZ, which was in contrast to the F\\u003csub\\u003eROH\\u003c/sub\\u003e estimates. However, the Pearson\\u0026rsquo;s correlations between F\\u003csub\\u003eROH\\u003c/sub\\u003e and the estimated inbreeding with other methods were high (Table 3).\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cem\\u003eCandidate genes inside frequently occurring runs of homozygosity regions\\u003c/em\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003eA genome-wide search for SNPs that have frequently occurred within ROH hotspots revealed 11 regions on BTA1, BTA2, BTA5, BTA7, BTA13, BTA14, BTA19 and BTA29 (Fig. 4; Additional file 3). The detected ROH islands on BTA7, BTA13 and BTA14 were partially overlapped in AZ and KHZ. The strongest peaks detected in approximately 30% of the individuals were located on BTA19 (19:411,773\\u0026ndash;3,701,223\\u0026nbsp;bp) in AZ and on BTA5 (5:55,217,391\\u0026ndash;57,476,442\\u0026nbsp;bp) in KHZ. In the KHZ breed, the genes located in the ROH islands were significantly enriched (P\\u0026le;0.05) in 40 GO terms. These GO terms belonged to 23 biological processes (BP), 12 cellular component (CC) and 5 molecular function (MF) groups (Additional file\\u0026nbsp;4).\\u003cem\\u003e\\u0026nbsp;\\u003c/em\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cem\\u003eCo-location of ROH islands and the identified selection signatures using iHS\\u003c/em\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003eThe majority of ROH hotspots detected in our study (Fig. 4; Additional file 3) overlapped with selection signature regions reported by Mokhber et al. [5] \\u0026nbsp;for the AZ and KHZ breeds using the haplotype-based method (i.e. iHS) (Additional files 5, 6). For example, the SNP Affx-79610232 on BTA5 (55,271,590\\u0026nbsp;bp) with the highest iHS was located in our detected ROH island in the KHZ breed. On BTA13, the eight SNPs with the largest iHS values were located in our detected ROH region. The SNP Affx-79540796 on BTA14 (52,933,269 bp) had the second-highest iHS value in our reported ROH hotspot. On BTA29, the SNP Affx-79545556 (3,274,219\\u0026nbsp;bp) was the SNP with the sixth-highest iHS value that was located in our reported ROH islands.\\u003c/p\\u003e\"},{\"header\":\"Discussion\",\"content\":\"\\u003cp\\u003eWe defined ROH as the lengths of homozygous genotypes that were \\u0026gt;1\\u0026nbsp;Mb and contained only up to one heterozygous genotype. Given the strong linkage disequilibrium (LD) between SNPs with a distance up to 100\\u0026nbsp;Kb [33], short homozygous haplotypes are expected to be prevalent in the buffalo genome. Thus, we set a minimum length of 1\\u0026nbsp;Mb and a minimum number of 40 (AZ) and 38 (KHZ) SNP (as described in methods section) to avoid detecting small and prevalent haplotypes as ROH. Unlike human populations, livestock species generally have higher levels of autozygosity and longer ROHs [13, 20, 21]. However, genotyping errors can always affect the quality of ROH calling [12]. Therefore, we allowed one heterozygous SNP in ROH [25, 30, 31] to avoid losing particularly long ROH because of a single genotyping error.\\u003c/p\\u003e\\n\\u003cp\\u003eAs presented in Table 1, more than 53% of the detected ROH were 2\\u0026ndash;4\\u0026nbsp;Mb in length. The proportion of different lengths of ROH can be used as an indicator of the number of past generations in which inbreeding has occurred, because the recombination events can rearrange the chromosomes and reduce the length of ROH. Thus, recent inbreeding results in longer ROH because of long IBD stretches. In contrast, short ROHs arise as a result of ancient inbreeding because in meiosis across generations, the long IBD segments are broken down [19]. We detected ROH with a length from 2 to 4\\u0026nbsp;Mb in all of the samples (Additional file\\u0026nbsp;1), which might indicate that some inbreeding events occurred about 20 generations ago [9]. However, our results should be interpreted with caution. As reported by Ferenčaković et al. [34], a medium-density chip could result in overestimation of the number of long-length ROHs (\\u0026gt;4\\u0026nbsp;Mb), probably because some heterozygous genotypes tend to appear in these ROHs by increasing the density of markers. Nevertheless, our results were in line with a previous report of a relatively sharp decrease in the effective population size (N\\u003csub\\u003ee\\u003c/sub\\u003e) of AZ and KHZ breeds and the consequent increased rate of inbreeding since 20 generations ago [33].\\u003c/p\\u003e\\n\\u003cp\\u003eThe portion of the genome that was autozygote in the AZ and KHZ breeds was lower than the reported ROH coverage in the Marchigiana beef breed (7%) [15], Austrian dual purpose breeds (9%) [35], and Holstein cattle (10%) [36]. This could be because of lower inbreeding in Iranian water buffalo or because we ignored ROH of \\u0026lt;1 Mb in length in our study.\\u003c/p\\u003e\\n\\u003cp\\u003eOn average, F\\u003csub\\u003eHOM\\u003c/sub\\u003e, F\\u003csub\\u003eUNI\\u003c/sub\\u003e and F\\u003csub\\u003eGRM\\u003c/sub\\u003e were higher in AZ than they were in KHZ. However, the previously reported N\\u003csub\\u003ee\\u003c/sub\\u003e for AZ (477) was larger than it was for KHZ (212) [33]. Therefore, we expected a lower inbreeding level in AZ. The only comparable estimated inbreeding with our expectation was F\\u003csub\\u003eROH\\u003c/sub\\u003e, which showed lower inbreeding for AZ (0.043) than for KHZ (0.059).\\u003c/p\\u003e\\n\\u003cp\\u003eThe highest correlation was observed between F\\u003csub\\u003eUNI\\u003c/sub\\u003e and F\\u003csub\\u003eROH\\u003c/sub\\u003e (AZ=0.98 and KHZ=0.94). Literature has reported different correlation coefficients between F\\u003csub\\u003eUNI\\u003c/sub\\u003e and F\\u003csub\\u003eROH\\u003c/sub\\u003e (0.15\\u0026ndash;0.80) [14], between F\\u003csub\\u003eHOM\\u003c/sub\\u003e and F\\u003csub\\u003eROH\\u003c/sub\\u003e (0.06\\u0026ndash;0.95) [14, 21, 27], and between F\\u003csub\\u003eGRM\\u003c/sub\\u003e and F\\u003csub\\u003eROH\\u003c/sub\\u003e (0.17\\u0026ndash;0.81) [21, 37, 38]. The considerable variation among different studies may be because of a strong dependency of F\\u003csub\\u003eHOM\\u003c/sub\\u003e, F\\u003csub\\u003eUNI\\u003c/sub\\u003e and F\\u003csub\\u003eGRM\\u003c/sub\\u003e on allelic frequencies [39].\\u003c/p\\u003e\\n\\u003cp\\u003eThe F\\u003csub\\u003ePED\\u003c/sub\\u003e of 0.03 previously reported in Iranian buffalo [40] was lower than the estimated F\\u003csub\\u003eROH\\u003c/sub\\u003e in the current study. Given that pedigree data were not available for our study, we could not calculate F\\u003csub\\u003ePED\\u003c/sub\\u003e and compare it with F\\u003csub\\u003eROH\\u003c/sub\\u003e. However, previous studies reported moderate to high (0.47\\u0026ndash;0.82) and low to moderate (0.12\\u0026ndash;0.76) correlations between F\\u003csub\\u003ePED\\u003c/sub\\u003e and F\\u003csub\\u003eROH\\u003c/sub\\u003e in cattle and sheep, respectively [14, 17]. A low to moderate correlation between F\\u003csub\\u003ePED\\u003c/sub\\u003e and F\\u003csub\\u003eROH \\u003c/sub\\u003ewas also reported by Peripolli et al. [13] in Gyr cattle, suggesting that F\\u003csub\\u003ePED\\u003c/sub\\u003e may not accurately capture small IBD segments that result from ancient inbreeding. Further, accurate and in-depth pedigree records are required to measure F\\u003csub\\u003ePED\\u003c/sub\\u003e. Additionally, methods based on allelic frequency have demonstrated considerable variation among different breeds [14]. Given that ROH does not depend on allele frequencies, and can capture recent and ancient inbreeding, it seems to be a suitable method for measuring inbreeding.\\u003c/p\\u003e\\n\\u003cp\\u003eThe total length of ROH islands were about 6 and 15\\u0026nbsp;Mb in the AZ and KHZ breeds, respectively (Additional file 3). Consequently, fewer genes were identified in ROH islands in the AZ breed than in the KHZ breed; that is probably why the genes located in ROH islands of the AZ breed were not enriched in any GO terms (\\u003cem\\u003eP\\u003c/em\\u003e\\u0026gt;0.05). In the KHZ breed, however, the genes located in the ROH islands were significantly enriched (P\\u0026le;0.05) in 40 GO terms (Additional file\\u0026nbsp;4). These GO terms belonged to 23 biological processes (BP), 12 cellular component (CC) and 5 molecular function (MF) groups. In this paper, we focused principally on the GO terms that include the genes with known large effects on important traits in livestock.\\u003c/p\\u003e\\n\\u003cp\\u003eFive genes were identified with positive regulation of DNA metabolic development (GO:0051054) in the BP group. Among these genes, STAT6 (signal transducer and activator of transcription 6, on BTA5) has been reported to have large effects on the growth efficiency and the quality of carcass in cattle [41]. Additionally, using co-expression network analysis, Nguyen et al. [42]. reported the critical role of STAT6, PBX2 (PBX homeobox2) and PBRM1 (Protein polybromo1) as transcription factors in regulating pubertal development in Brahman heifers.\\u003c/p\\u003e\\n\\u003cp\\u003e\\u0026nbsp;Twelve genes in ROH islands were associated with lipid metabolic process (GO:0006629) in the BP group. Of these genes, BMP2 (bone morphogenetic protein 2, on BTA13) plays a major role in rebuilding hair follicles in goats [43]. Further, BMP2 in porcine, cattle and sheep has been reported to have an influence on regulating body size and muscle development [44-47]. Kim et al. [48] found several signatures of selection containing genes such as BMP2 associated with body size and development in goats and sheep native to Egypt. These researchers concluded that the genes influencing body size may be important in regulating adaptation to hot, arid habitats because efficiency in thermoregulation can be associated with body size. Supporting their conclusion is the fact that most breeds in tropical zones have smaller body size than breeds in temperate zones because tropical breeds can regulate their body temperature more efficiently [49]. However, other factors that differ between temperate and arid zones may also contribute to variations in the body sizes of breeds living in different climates.\\u003c/p\\u003e\\n\\u003cp\\u003eCYP27B1 (cytochrome P450 family 27 subfamily B member 1) located on BTA5 was also one of the genes enriched in the lipid metabolic process (GO:0006629). This gene is important for making 1-\\u0026alpha;-hydroxylase, which is required in vitamin D bio-activation, and has been reported to be up-regulated as a result of bacterial infection, suggesting that this gene plays a role in modulating innate immune responses [50].\\u003c/p\\u003e\\n\\u003cp\\u003eIn ROH islands on BTA13, three genes were associated with the positive regulation of DNA replication (GO:0045740) in the BP group. Proliferating cell nuclear antigen (PCNA) has been reported to be associated with follicular development and growth in buffalo ovaries [51], and may therefore be related to fertility performance.\\u003c/p\\u003e\\n\\u003cp\\u003eSingle-organism cellular process (GO:0044763) with 64 genes was significantly enriched (\\u003cem\\u003eP\\u003c/em\\u003e=0.05) in ROH islands, including MARS (methionyl-tRNA synthetase, on BTA5), and ADRA1D (adrenoceptor alpha 1D, on BTA13). MARS has been reported to influence milk and protein production in Chinese [52] and Portuguese [53] Holstein cattle, and ADRA1D largely affects milk protein in Murrah dairy buffalo [54]. INHBC and INHBE (inhibin beta C and E subunits, on BTA5) have been reported as candidate genes associated with reproductive performance in tropical young bulls [55], and composite reproductive traits in Lori-Bakhtiari sheep [56]. KCTD16 (potassium channel tetramerization domain containing 16, on BTA7) was reported as a candidate gene for meat quality in Simmental beef cattle [57], for residual feed intake in Junmu White pigs [58], and for fat yield in Nordic Holstein cattle [59]. PMEL (premelanosome protein) and MYO1A (myosin IA) on BTA5 have been reported as putative candidate genes related to coat colour phenotypes in cattle [60, 61]. PMEL is required for the melanin biosynthesis process in the pigmentation of hair, mucous membranes and eyes [62]. In cattle, PMEL is reported as a candidate gene associated with the dilution of coat colour and consequently colour intensity [63, 64]. Light coat colouring can be beneficial for animals in adapting to hot climates because it can help them to reduce sunlight absorption [65]. However, most of the AZ and KHZ buffalo have a dark coat, which could be a result of some other favourable traits associated with a darker coat colour or the result of artificial selection caused by human interference. SUOX (Sulphite oxidase, on BTA5), within this BP category, was reported to be associated with bone development in cattle [66].\\u003c/p\\u003e\\n\\u003cp\\u003eThe average LD (r\\u003csup\\u003e2\\u003c/sup\\u003e) between adjacent SNPs in ROH islands was higher than the r\\u003csup\\u003e2\\u003c/sup\\u003e of adjacent SNPs located on the same chromosome (Additional file 3). Thus, the recombination rates in the ROH islands were lower than those in the rest of the genome. These results are in line with some previous studies [13, 17]. However, a moderate recombination rate has been reported between the SNPs in ROH islands in Valle del Belice sheep [67]. Additionally, ROH hotspots can result from a wide range of underlying causes such as inbreeding and selection [12]. Peripolli et al. [13] argued that the high LD observed in most ROH hotspots is not necessarily caused by selection or conserved IBD haplotypes, but can be an indication of a lower recombination rate in those regions. Nevertheless, most of the ROH hotspots in our study overlapped with selection signature regions found with iHS, which supports the theory that ROH can be used to find genomic regions that have been under natural and/or artificial selection.\\u003c/p\\u003e\\n\\u003cp\\u003eBuffalo species have a relatively lower heat tolerance capability than some other livestock species because of their inadequately dispersed sweat glands and their dark coat colour [68]. However, Iranian buffalo breeds have historically been raised in a hot climate [69]. Therefore, selection for higher heat tolerance may have occurred in Iranian buffalo for better adaptation to heat stress [5]. It has been reported that combined networks of multiple genes are often involved in the regulation of complex traits such as adaptation to hot climates [48, 70, 71]. Thus, selection for complex traits would leave only minor footprints because of the selection for numerous regions with lower intensity across the genome [70]. Therefore, we expected to find several genes directly or indirectly influencing different traits that were under artificial selection or important for adaptation and survival in hot areas. We found genes influencing energy and digestive metabolism (KCTD16), autoimmune response (CYP27B1), thermoregulation (BMP2), embryonic development and reproduction (STAT6, PCNA, INHBC and INHBE). These genes seem to be important for species such as water buffalo that have adapted to a hot climate [48].\\u003c/p\\u003e\"},{\"header\":\"Conclusion\",\"content\":\"\\u003cp\\u003eThe inbreeding coefficients based on F\\u003csub\\u003eHOM\\u003c/sub\\u003e, F\\u003csub\\u003eUNI\\u003c/sub\\u003e and F\\u003csub\\u003eGRM\\u003c/sub\\u003e were higher in the AZ breed than they were in the KHZ breed, which contradicted our expectations according to higher N\\u003csub\\u003ee\\u003c/sub\\u003e in AZ breed. Given that F\\u003csub\\u003eROH\\u003c/sub\\u003e was the only measurement of inbreeding in our study that showed AZ water buffalo were more inbred, this measurement seems to be a suitable measure of genomic inbreeding. This is most likely because it is less affected by allele frequencies. Further, knowing the distribution of ROH across the genome, inbreeding can be avoided more efficiently through mating allocation. Additionally, frequently occurring ROH can be used as suggestive evidence of historical selection. In our study, we found some overlap between ROH islands and genomic regions showing signatures of selection in previous studies of AZ and KHZ breeds. Therefore, the genes located in ROH islands could be under the influence of artificial and/or natural selection. We found that the genes located in ROH islands were associated with biological pathways such as adaptation to a hot climate, immune response, milk production, growth efficiency, reproduction performance and bone development.\\u003c/p\\u003e\"},{\"header\":\"Methods\",\"content\":\"\\u003cp\\u003e\\u003cem\\u003eSample collection, ethical statement, and data quality control\\u003c/em\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003eHair roots and blood samples were obtained from 112 herds of AZ and 47 herds of KHZ breeds. Samples of the AZ breed were gathered from East and West Azerbaijan, Gilan and Ardabil (37.02\\u0026deg; \\u0026ndash; 38.78\\u0026deg; N, 44.81\\u0026deg; 49.52\\u0026deg;E), which are north-western provinces of Iran. Samples of the KHZ breed were obtained from Kermanshah (34.54\\u0026deg;N, 45.60\\u0026deg;E) and Khuzestan (30.68\\u0026ndash;32.55\\u0026deg; N, 48.02\\u0026deg;\\u0026ndash;48.97\\u0026deg; E), which are the south and south-western provinces of Iran, respectively (Fig. 1). All practices relating to data collection were reviewed and confirmed by the research ethics committee of the College of Agriculture and Natural Resources of the University of Tehran, Iran and by the ABCI. Three hundred and sixty-nine buffalo (254 AZ and 115 KHZ) were genotyped using 90K SNPChip (Axiom\\u003csup\\u003e\\u0026reg;\\u003c/sup\\u003e Buffalo 90K Genotyping Array), which consisted of 89\\u0026nbsp;988 almost evenly distributed SNPs throughout the genome. The same dataset was previously used by Mokhber et al. [5], \\u0026nbsp;and it partially overlapped with the dataset used by Colli et al. [4] and by Fallahi et al. [72].\\u003c/p\\u003e\\n\\u003cp\\u003eThe SNPs in the 90K SNPChip were selected using buffalo DNA sequence, but similar to methods used in previous studies [1, 5, 33, 72-75], were reported according to the location on the cattle reference genome assembly (UMD3.1 [76]) Although chromosome-level assembly of the water buffalo genome (UOA_WB_1) has been published recently [77], we used the UMD3.1 assembly in our study because it is more reliable and has better gene annotation information. Genotypes were obtained through AffyPipe [78], and all the monomorphic and polymorphic SNPs with high resolution (n=64\\u0026nbsp;750) were stored. According to the filtration criteria, samples with more than 5% missing genotype and SNPs with 5% missing rate were eliminated from further analyses. We also filtered out SNPs with unidentified position in the UMD3.1 assembly, positioned on the sex chromosomes, with minor allele frequency of \\u0026lt;2%, and with p-value for the Hardy\\u0026ndash;Weinberg equilibrium chi-square test \\u0026lt;10\\u003csup\\u003e-6\\u003c/sup\\u003e. In total, 62\\u0026nbsp;122 SNPs and 369 samples with an average call rate of 99.6% passed the quality-control filters.\\u003cem\\u003e\\u0026nbsp;\\u003c/em\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cem\\u003eGenetic distance between breeds\\u003c/em\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003eGenetic distance, which is based on the IBS matrix, was estimated through the --ibs-matrix command in PLINK v1.9 [79]. Principal component (PC) analysis of genetic distances was performed to visualise the genetic diversity of the samples, and was depicted using R (\\u003ca href=\\\"http://www.R-project.org/\\\"\\u003ehttp://www.R-project.org/\\u003c/a\\u003e). According to the first and second PCs, we removed four samples: two from each breed that were placed outside their expected breed cluster.\\u0026nbsp;\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cem\\u003eRuns of homozygosity analyses\\u003c/em\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003eROH can be detected in the genome through two main approaches: 1) genotype-counting algorithms in which the genome is scanned to identify long stretches of consecutive homozygous genotypes like the one implemented in PLINK v1.9 [79], and 2) model-based methods that utilize Hidden Markov Models (HMM) like the one implemented in RzooRoH [80]. This package can enable a better assessment of the contribution of various generations to the current level of inbreeding, estimating inbreeding at both genome-wide and local scales, and classifying homozygous‐by‐descent\\u0026nbsp; (HBD) segments into age-based classes [81]. However, we used PLINK in our study because of the simplicity of running the sliding-window approach to detect ROH with sufficiently high assurance [82].\\u003c/p\\u003e\\n\\u003cp\\u003eA genome scan for ROH was conducted for the AZ (n=252) and KHZ (n=113) breeds, separately. For each individual, ROH segments with the following attributes were identified:\\u0026nbsp;1) each ROH stretch was at least 1\\u0026nbsp;Mb in length; 2) there was at the most only one heterozygous and one missing SNP in each ROH; 3) there was a minimum number of SNPs that could form ROH in each breed, calculated according to Eq. 1 to control the false positive rate of the identified ROH. (see Equation 1 in the Supplementary Files)\\u003c/p\\u003e\\n\\u003cp\\u003ewhere \\u003cem\\u003el\\u003c/em\\u003e is the minimum number of SNPs in ROH, \\u0026alpha; is the false positive rate of the identified ROH (set at 0.5); n\\u003csub\\u003ea\\u003c/sub\\u003e and n\\u003csub\\u003es\\u003c/sub\\u003e are the number of individuals and the number of SNPs per individual, respectively; and \\u003cem\\u003ehet\\u003c/em\\u003e is the average heterozygosity across individuals. \\u003cem\\u003el\\u003c/em\\u003e was calculated to be 40 and 38 in AZ and KHZ breeds, respectively; 4) each ROH contained at least one SNP over 100\\u0026nbsp;Kb; and 5) the maximum gap between two neighbouring SNPs in ROH had to be less than 1\\u0026nbsp;Mb.\\u003c/p\\u003e\\n\\u003cp\\u003e\\u0026nbsp;The ROH that had these five attributes were divided into the following five groups: 1-2, 2-4, 4-8, 8-16 and \\u0026gt;16\\u0026nbsp;Mb, as suggested in the literature [13, 15, 25]. Then for each breed, the frequency and the average length (Mb) of ROH within each category, the percentage of each ROH category, and the percentage of genome coverage by each ROH category were calculated, using R (\\u003ca href=\\\"http://www.R-project.org/\\\"\\u003ehttp://www.R-project.org/\\u003c/a\\u003e).\\u003c/p\\u003e\\n\\u003cp\\u003e\\u0026nbsp;\\u003cem\\u003eInbreeding coefficient estimations\\u003c/em\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003eThe coefficient of inbreeding was estimated using ROH (F\\u003csub\\u003eROH\\u003c/sub\\u003e), excess of homozygosity (F\\u003csub\\u003eHOM\\u003c/sub\\u003e), correlation between uniting gametes (F\\u003csub\\u003eUNI\\u003c/sub\\u003e) and diagonal elements of the genomic relationship matrix (F\\u003csub\\u003eGRM\\u003c/sub\\u003e).\\u003c/p\\u003e\\n\\u003cp\\u003eF\\u003csub\\u003eROH\\u003c/sub\\u003e was calculated for each individual using Eq. 2 [20]: (see Equation 2 in the Supplementary Files)\\u003c/p\\u003e\\n\\u003cp\\u003ewhere \\u0026nbsp;is the inbreeding coefficient of animal \\u003cem\\u003ei\\u003c/em\\u003e; \\u003cem\\u003en\\u003c/em\\u003e is the total number of ROH; and is the length of the \\u003cem\\u003ej\\u003c/em\\u003e\\u003csup\\u003eth\\u003c/sup\\u003e ROH in animal \\u003cem\\u003ei\\u003c/em\\u003e; \\u003cem\\u003eL\\u003c/em\\u003e\\u003csub\\u003eaut\\u003c/sub\\u003e is the total autosome length covered by the SNP markers (2.5\\u0026nbsp;Gb in our study).\\u003c/p\\u003e\\n\\u003cp\\u003eWe also calculated the following three different genomic inbreeding estimations: F\\u003csub\\u003eGRM\\u003c/sub\\u003e (Eq. 3), F\\u003csub\\u003eHOM\\u003c/sub\\u003e (Eq. 4) and F\\u003csub\\u003eUNI \\u003c/sub\\u003e(Eq. 5) using --ibc command in GCTA software [39]. (see Equations 3-5 in the Supplementary Files)\\u003c/p\\u003e\\n\\u003cp\\u003ewhere \\u003cem\\u003ex\\u003csub\\u003ei\\u003c/sub\\u003e\\u003c/em\\u003e and \\u003cem\\u003ep\\u003c/em\\u003e\\u003csub\\u003ei \\u003c/sub\\u003eare the number of copies and the frequency of the reference allele for SNP \\u003cem\\u003ei\\u003c/em\\u003e, respectively; \\u003cem\\u003eh\\u003c/em\\u003e\\u003csub\\u003ei \\u003c/sub\\u003eis 2\\u003cem\\u003ep\\u003c/em\\u003e\\u003csub\\u003ei\\u003c/sub\\u003e(1-2\\u003cem\\u003ep\\u003c/em\\u003e\\u003csub\\u003ei\\u003c/sub\\u003e); and n is the total number of SNPs. The Pearson\\u0026rsquo;s correlation coefficient between F\\u003csub\\u003eROH\\u003c/sub\\u003e and the other genomic inbreeding estimates was also calculated.\\u0026nbsp;\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cem\\u003eFrequently appearing runs of homozygosity and gene enrichment analyses\\u003c/em\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003eTo detect the genomic regions frequently covered with ROH in the AZ and KHZ populations, the number of times each SNP occurred in ROH was calculated separately in each breed. The ROH repeated in more than 20% of the individuals in each breed (approximately less than 1% of the SNPs) were nominated ROH islands, as suggested in previous studies [25, 67]. Further, the frequency of ROHs were plotted against their physical position along UMD3.1.\\u003c/p\\u003e\\n\\u003cp\\u003eTo identify genes in ROH islands, we used UMD3.1 map viewer from the NCBI website (\\u003ca href=\\\"https://www.ncbi.nlm.nih.gov/mapview/\\\"\\u003ehttps://www.ncbi.nlm.nih.gov/mapview/\\u003c/a\\u003e). Additionally, to find significantly enriched Gene Ontology (GO) terms (\\u003cem\\u003eP\\u003c/em\\u003e\\u0026le;0.05) of the genes located in ROH peaks, we used DAVID v6.8 tool [83, 84]. Finally, we performed an extensive literature review to explore the biological function of the annotated genes in ROH islands.\\u003c/p\\u003e\\n\\u003cp\\u003eTo discover whether ROH islands were associated with regions of the genome with a low recombination rate, the average LD of all the adjacent SNPs across each chromosome was compared with the average LD between adjacent SNPs inside the ROH islands located on the same chromosome. Additionally, to discover whether the ROH hotspots were associated with genomic regions that showed signatures of selection through other methods, we compared ROH islands with integrated haplotype homozygosity scores (iHS) that had already been published for AZ and KHZ breeds [5]. An iHS is a measure of haplotype homozygosity based on the difference between observed LD structure around a selected allele relative to the expected LD pattern according to the whole genome [85]. Therefore, it can be used to detect regions under historical selection [85].\\u003c/p\\u003e\"},{\"header\":\"List Of Abbreviations\",\"content\":\"\\u003cp\\u003eROH: runs of homozygosity; SNP: single nucleotide polymorphism; AZ: Azeri breed; KHZ: Khuzestani breed; MZ: Mazandarani breed; GO: Gene Ontology; IBD: identical by descent; IBS: identical by state; Ne: effective population size; FROH: inbreeding coefficient calculated using ROH; FHOM: inbreeding coefficient calculated using excess of homozygosity; FUNI: inbreeding coefficient calculated using correlation between uniting gametes; FGRM: inbreeding coefficient calculated using diagonal elements of the genomic relationship matrix; LD: linkage disequilibrium; ABCI: Animal Breeding Centre of Iran; PC: principal component; iHS: integrated haplotype homozygosity score.\\u003c/p\\u003e\"},{\"header\":\"Declarations\",\"content\":\"\\u003cp\\u003e\\u003cstrong\\u003eEthics approval and consent to participate\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003eThe procedure was in accordance with animal ethics and approved by the University of Tehran and Animal Breeding Centre of Iran (ABCI) authorized representatives. Indications, risks, and benefits explained to animal owners and depending on his/her literacy, written or verbal informed consent obtained before the initiation of sampling.\\u003cstrong\\u003e\\u0026nbsp;\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eConsent for publication\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003eNot applicable.\\u003cstrong\\u003e\\u0026nbsp;\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eAvailability of data and material\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003eAll data generated or analyzed during this study are included in this published article and its supplementary information files.\\u003cstrong\\u003e\\u0026nbsp;\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eCompeting interest\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003eThe authors declare that they have no competing interests.\\u0026nbsp;\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eFunding\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003eWe have received no specific funding for the current study.\\u0026nbsp;\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eAuthors\\u0026rsquo; contributions\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003eSMG, HMS and MMS conceived and designed the study, SMG, MHF and AJS analysed the data and SMG wrote the paper. RAA and MKH revised the manuscript. All authors read and approved the final manuscript.\\u0026nbsp;\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eAcknowledgments\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003eThe authors gratefully acknowledge the Animal Breeding Centre of Iran (ABCI) and Towsee Kesht va Dam Noandish Alborz Co (Takdna) for giving us access to the animals and recording.\\u003c/p\\u003e\"},{\"header\":\"References\",\"content\":\"\\u003col\\u003e\\n\\u003cli\\u003eIamartino D, Nicolazzi EL, Van Tassell CP, Reecy JM, Fritz-Waters ER, Koltes JE, et al. Design and validation of a 90K SNP genotyping assay for the water buffalo (\\u003cem\\u003eBubalus bubalis\\u003c/em\\u003e). PLoS One. 2017;12(10):e0185220.\\u003c/li\\u003e\\n\\u003cli\\u003eSafari A, Ghavi Hossein-Zadeh N, Shadparvar AA, Abdollahi Arpanahi R. A review on breeding and genetic strategies in Iranian buffaloes (\\u003cem\\u003eBubalus bubalis\\u003c/em\\u003e). 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Gigascience. 2015;4(1):7.\\u003c/li\\u003e\\n\\u003cli\\u003eBertrand A, Kadri NK, Flori L, Gautier M, Druet T. RZooRoH: An R package to characterize individual genomic autozygosity and identify homozygous-by-descent segments. Methods Ecol Evol. 2019;10:860-6.\\u003c/li\\u003e\\n\\u003cli\\u003eDruet T, Gautier M. A model‐based approach to characterize individual inbreeding at both global and local genomic scales. Mol Ecol. 2017;26(20):5820-41.\\u003c/li\\u003e\\n\\u003cli\\u003eGusev A, Lowe JK, Stoffel M, Daly MJ, Altshuler D, Breslow JL, et al. Whole population, genome-wide mapping of hidden relatedness. Genome Res. 2009;19(2):318-26.\\u003c/li\\u003e\\n\\u003cli\\u003eHuang DW, Sherman BT, Lempicki RA. Bioinformatics enrichment tools: paths toward the comprehensive functional analysis of large gene lists. Nucleic Acids Res. 2008;37(1):1-13.\\u003c/li\\u003e\\n\\u003cli\\u003eHuang DW, Sherman BT, Lempicki RA. Systematic and integrative analysis of large gene lists using DAVID bioinformatics resources. Nat Protoc. 2008;4(1):44.\\u003c/li\\u003e\\n\\u003cli\\u003eVoight BF, Kudaravalli S, Wen X, Pritchard JK. A map of recent positive selection in the human genome. PLoS Biol. 2006;4(3):e72.\\u003c/li\\u003e\\n\\u003c/ol\\u003e\"},{\"header\":\"Tables\",\"content\":\"\\u003cp style=\\\"margin-top:0in;margin-right:0in;margin-bottom:8.0pt;margin-left:0in;line-height:115%;font-size:16px;font-family:\\u0026quot;Times New Roman\\u0026quot;,serif;\\\"\\u003e\\u003cspan style=\\\"color: rgb(0, 0, 0);\\\"\\u003eTable 1. Summary of the detected runs of homozygosity (ROH) grouped according to their length (Mb).\\u003c/span\\u003e\\u003c/p\\u003e\\n\\u003ctable border=\\\"0\\\" cellpadding=\\\"0\\\" cellspacing=\\\"0\\\" style=\\\"border-collapse:collapse;\\\" width=\\\"100%\\\"\\u003e\\n \\u003ctbody\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd rowspan=\\\"2\\\" style=\\\"width: 10.22%;border-top: 1pt solid windowtext;border-left: none;border-bottom: 1pt solid black;border-right: none;background: white;padding: 0in 5.4pt;height: 15pt;vertical-align: bottom;\\\" valign=\\\"bottom\\\" width=\\\"10.75268817204301%\\\"\\u003e\\n \\u003cp style=\\\"margin-top:0in;margin-right:0in;margin-bottom:.0001pt;margin-left:0in;line-height:normal;font-size:16px;font-family:\\u0026quot;Times New Roman\\u0026quot;,serif;text-align:center;\\\"\\u003e\\u003cspan style=\\\"color: rgb(0, 0, 0);\\\"\\u003e\\u003cspan style=\\\"font-size:12px;\\\"\\u003eROH group\\u0026nbsp;\\u003c/span\\u003e\\u003c/span\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd colspan=\\\"2\\\" style=\\\"width: 14.58%;border-top: 1pt solid windowtext;border-left: none;border-bottom: 1pt solid windowtext;border-right: none;background: white;padding: 0in 5.4pt;height: 15pt;vertical-align: bottom;\\\" valign=\\\"bottom\\\" width=\\\"15.053763440860216%\\\"\\u003e\\n \\u003cp style=\\\"margin-top:0in;margin-right:0in;margin-bottom:.0001pt;margin-left:0in;line-height:normal;font-size:16px;font-family:\\u0026quot;Times New Roman\\u0026quot;,serif;text-align:center;\\\"\\u003e\\u003cspan style=\\\"color: rgb(0, 0, 0);\\\"\\u003e\\u003cspan style=\\\"font-size: 12px;\\\"\\u003enROH\\u003csup\\u003e1\\u003c/sup\\u003e\\u003c/span\\u003e\\u003c/span\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd style=\\\"width: 2.96%;border-right: none;border-bottom: none;border-left: none;border-image: initial;border-top: 1pt solid windowtext;background: white;padding: 0in 5.4pt;height: 15pt;vertical-align: bottom;\\\" valign=\\\"bottom\\\" width=\\\"2.150537634408602%\\\"\\u003e\\n \\u003cp style=\\\"margin-top:0in;margin-right:0in;margin-bottom:.0001pt;margin-left:0in;line-height:normal;font-size:16px;font-family:\\u0026quot;Times New Roman\\u0026quot;,serif;text-align:center;\\\"\\u003e\\u003cspan style=\\\"color: rgb(0, 0, 0);\\\"\\u003e\\u003cspan style=\\\"font-size: 12px;\\\"\\u003e\\u0026nbsp;\\u003c/span\\u003e\\u003c/span\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd colspan=\\\"2\\\" style=\\\"width: 16.28%;border-top: 1pt solid windowtext;border-left: none;border-bottom: 1pt solid windowtext;border-right: none;background: white;padding: 0in 5.4pt;height: 15pt;vertical-align: bottom;\\\" valign=\\\"bottom\\\" width=\\\"17.204301075268816%\\\"\\u003e\\n \\u003cp style=\\\"margin-top:0in;margin-right:0in;margin-bottom:.0001pt;margin-left:0in;line-height:normal;font-size:16px;font-family:\\u0026quot;Times New Roman\\u0026quot;,serif;text-align:center;\\\"\\u003e\\u003cspan style=\\\"color: rgb(0, 0, 0);\\\"\\u003e\\u003cspan style=\\\"font-size: 12px;\\\"\\u003ePercentage\\u003c/span\\u003e\\u003c/span\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd style=\\\"width: 2.96%;border-right: none;border-bottom: none;border-left: none;border-image: initial;border-top: 1pt solid windowtext;background: white;padding: 0in 5.4pt;height: 15pt;vertical-align: bottom;\\\" valign=\\\"bottom\\\" width=\\\"2.150537634408602%\\\"\\u003e\\n \\u003cp style=\\\"margin-top:0in;margin-right:0in;margin-bottom:.0001pt;margin-left:0in;line-height:normal;font-size:16px;font-family:\\u0026quot;Times New Roman\\u0026quot;,serif;text-align:center;\\\"\\u003e\\u003cspan style=\\\"color: rgb(0, 0, 0);\\\"\\u003e\\u003cspan style=\\\"font-size: 12px;\\\"\\u003e\\u0026nbsp;\\u003c/span\\u003e\\u003c/span\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd colspan=\\\"2\\\" style=\\\"width: 14.8%;border-top: 1pt solid windowtext;border-left: none;border-bottom: 1pt solid windowtext;border-right: none;background: white;padding: 0in 5.4pt;height: 15pt;vertical-align: bottom;\\\" valign=\\\"bottom\\\" width=\\\"15.053763440860216%\\\"\\u003e\\n \\u003cp style=\\\"margin-top:0in;margin-right:0in;margin-bottom:.0001pt;margin-left:0in;line-height:normal;font-size:16px;font-family:\\u0026quot;Times New Roman\\u0026quot;,serif;text-align:center;\\\"\\u003e\\u003cspan style=\\\"color: rgb(0, 0, 0);\\\"\\u003e\\u003cspan style=\\\"font-size: 12px;\\\"\\u003eAverage length (Mb)\\u003c/span\\u003e\\u003c/span\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd style=\\\"width: 2.98%;border-right: none;border-bottom: none;border-left: none;border-image: initial;border-top: 1pt solid windowtext;background: white;padding: 0in 5.4pt;height: 15pt;vertical-align: bottom;\\\" valign=\\\"bottom\\\" width=\\\"2.150537634408602%\\\"\\u003e\\n \\u003cp style=\\\"margin-top:0in;margin-right:0in;margin-bottom:.0001pt;margin-left:0in;line-height:normal;font-size:16px;font-family:\\u0026quot;Times New Roman\\u0026quot;,serif;text-align:center;\\\"\\u003e\\u003cspan style=\\\"color: rgb(0, 0, 0);\\\"\\u003e\\u003cspan style=\\\"font-size: 12px;\\\"\\u003e\\u0026nbsp;\\u003c/span\\u003e\\u003c/span\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd colspan=\\\"2\\\" style=\\\"width: 14.8%;border-top: 1pt solid windowtext;border-left: none;border-bottom: 1pt solid windowtext;border-right: none;background: white;padding: 0in 5.4pt;height: 15pt;vertical-align: bottom;\\\" valign=\\\"bottom\\\" width=\\\"15.053763440860216%\\\"\\u003e\\n \\u003cp style=\\\"margin-top:0in;margin-right:0in;margin-bottom:.0001pt;margin-left:0in;line-height:normal;font-size:16px;font-family:\\u0026quot;Times New Roman\\u0026quot;,serif;text-align:center;\\\"\\u003e\\u003cspan style=\\\"color: rgb(0, 0, 0);\\\"\\u003e\\u003cspan style=\\\"font-size: 12px;\\\"\\u003eStandard deviation (Mb)\\u003c/span\\u003e\\u003c/span\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd style=\\\"width: 2.98%;border-right: none;border-bottom: none;border-left: none;border-image: initial;border-top: 1pt solid windowtext;background: white;padding: 0in 5.4pt;height: 15pt;vertical-align: bottom;\\\" valign=\\\"bottom\\\" width=\\\"2.150537634408602%\\\"\\u003e\\n \\u003cp style=\\\"margin-top:0in;margin-right:0in;margin-bottom:.0001pt;margin-left:0in;line-height:normal;font-size:16px;font-family:\\u0026quot;Times New Roman\\u0026quot;,serif;text-align:center;\\\"\\u003e\\u003cspan style=\\\"color: rgb(0, 0, 0);\\\"\\u003e\\u003cspan style=\\\"font-size: 12px;\\\"\\u003e\\u0026nbsp;\\u003c/span\\u003e\\u003c/span\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd colspan=\\\"2\\\" style=\\\"width: 17.42%;border-top: 1pt solid windowtext;border-left: none;border-bottom: 1pt solid windowtext;border-right: none;background: white;padding: 0in 5.4pt;height: 15pt;vertical-align: bottom;\\\" valign=\\\"bottom\\\" width=\\\"18.27956989247312%\\\"\\u003e\\n \\u003cp style=\\\"margin-top:0in;margin-right:0in;margin-bottom:.0001pt;margin-left:0in;line-height:normal;font-size:16px;font-family:\\u0026quot;Times New Roman\\u0026quot;,serif;text-align:center;\\\"\\u003e\\u003cspan style=\\\"color: rgb(0, 0, 0);\\\"\\u003e\\u003cspan style=\\\"font-size: 12px;\\\"\\u003ePercentage of genome coverage\\u003c/span\\u003e\\u003c/span\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd style=\\\"width: 7.18%;border-top: none;border-right: none;border-left: none;border-image: initial;border-bottom: 1pt solid windowtext;background: white;padding: 0in 5.4pt;height: 15pt;vertical-align: bottom;\\\" valign=\\\"bottom\\\" width=\\\"8.641975308641975%\\\"\\u003e\\n \\u003cp style=\\\"margin-top:0in;margin-right:0in;margin-bottom:.0001pt;margin-left:0in;line-height:normal;font-size:16px;font-family:\\u0026quot;Times New Roman\\u0026quot;,serif;text-align:center;\\\"\\u003e\\u003cspan style=\\\"color: rgb(0, 0, 0);\\\"\\u003e\\u003cspan style=\\\"font-size: 12px;\\\"\\u003eAZ\\u003c/span\\u003e\\u003c/span\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd style=\\\"width: 7.4%;border-top: none;border-right: none;border-left: none;border-image: initial;border-bottom: 1pt solid windowtext;background: white;padding: 0in 5.4pt;height: 15pt;vertical-align: bottom;\\\" valign=\\\"bottom\\\" width=\\\"8.641975308641975%\\\"\\u003e\\n \\u003cp style=\\\"margin-top:0in;margin-right:0in;margin-bottom:.0001pt;margin-left:0in;line-height:normal;font-size:16px;font-family:\\u0026quot;Times New Roman\\u0026quot;,serif;text-align:center;\\\"\\u003e\\u003cspan style=\\\"color: rgb(0, 0, 0);\\\"\\u003e\\u003cspan style=\\\"font-size: 12px;\\\"\\u003eKHZ\\u003c/span\\u003e\\u003c/span\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd style=\\\"width: 2.96%;border-top: none;border-right: none;border-left: none;border-image: initial;border-bottom: 1pt solid windowtext;background: white;padding: 0in 5.4pt;height: 15pt;vertical-align: bottom;\\\" valign=\\\"bottom\\\" width=\\\"2.4691358024691357%\\\"\\u003e\\n \\u003cp style=\\\"margin-top:0in;margin-right:0in;margin-bottom:.0001pt;margin-left:0in;line-height:normal;font-size:16px;font-family:\\u0026quot;Times New Roman\\u0026quot;,serif;text-align:center;\\\"\\u003e\\u003cspan style=\\\"color: rgb(0, 0, 0);\\\"\\u003e\\u003cspan style=\\\"font-size: 12px;\\\"\\u003e\\u0026nbsp;\\u003c/span\\u003e\\u003c/span\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd style=\\\"width: 7.4%;border-top: none;border-right: none;border-left: none;border-image: initial;border-bottom: 1pt solid windowtext;background: white;padding: 0in 5.4pt;height: 15pt;vertical-align: bottom;\\\" valign=\\\"bottom\\\" width=\\\"8.641975308641975%\\\"\\u003e\\n \\u003cp style=\\\"margin-top:0in;margin-right:0in;margin-bottom:.0001pt;margin-left:0in;line-height:normal;font-size:16px;font-family:\\u0026quot;Times New 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windowtext;background: white;padding: 0in 5.4pt;height: 15pt;vertical-align: bottom;\\\" valign=\\\"bottom\\\" width=\\\"6.172839506172839%\\\"\\u003e\\n \\u003cp style=\\\"margin-top:0in;margin-right:0in;margin-bottom:.0001pt;margin-left:0in;line-height:normal;font-size:16px;font-family:\\u0026quot;Times New Roman\\u0026quot;,serif;text-align:center;\\\"\\u003e\\u003cspan style=\\\"color: rgb(0, 0, 0);\\\"\\u003e\\u003cspan style=\\\"font-size: 12px;\\\"\\u003eAZ\\u003c/span\\u003e\\u003c/span\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd style=\\\"width: 11.56%;border-top: none;border-right: none;border-left: none;border-image: initial;border-bottom: 1pt solid windowtext;background: white;padding: 0in 5.4pt;height: 15pt;vertical-align: bottom;\\\" valign=\\\"bottom\\\" width=\\\"13.580246913580247%\\\"\\u003e\\n \\u003cp style=\\\"margin-top:0in;margin-right:0in;margin-bottom:.0001pt;margin-left:0in;line-height:normal;font-size:16px;font-family:\\u0026quot;Times New 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style=\\\"margin-top:0in;margin-right:0in;margin-bottom:.0001pt;margin-left:0in;line-height:normal;font-size:16px;font-family:\\u0026quot;Times New Roman\\u0026quot;,serif;text-align:center;\\\"\\u003e\\u003cspan style=\\\"color: rgb(0, 0, 0);\\\"\\u003e\\u003cspan style=\\\"font-size: 12px;\\\"\\u003e0.11\\u003c/span\\u003e\\u003c/span\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd style=\\\"width: 10.22%;border-top: none;border-right: none;border-left: none;border-image: initial;border-bottom: 1pt solid windowtext;background: white;padding: 0in 5.4pt;height: 15pt;vertical-align: bottom;\\\" valign=\\\"bottom\\\" width=\\\"10.989010989010989%\\\"\\u003e\\n \\u003cp style=\\\"margin-top:0in;margin-right:0in;margin-bottom:.0001pt;margin-left:0in;line-height: normal;font-size:16px;font-family:\\u0026quot;Times New Roman\\u0026quot;,serif;\\\"\\u003e\\u003cspan style=\\\"color: rgb(0, 0, 0);\\\"\\u003e\\u003cspan style=\\\"font-size: 12px;\\\"\\u003eROH\\u003csub\\u003e\\u0026gt;16\\u003c/sub\\u003e\\u003c/span\\u003e\\u003c/span\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd style=\\\"width: 7.18%;border-top: none;border-right: none;border-left: none;border-image: initial;border-bottom: 1pt solid windowtext;background: white;padding: 0in 5.4pt;height: 15pt;vertical-align: bottom;\\\" valign=\\\"bottom\\\" width=\\\"7.6923076923076925%\\\"\\u003e\\n \\u003cp style=\\\"margin-top:0in;margin-right:0in;margin-bottom:.0001pt;margin-left:0in;line-height:normal;font-size:16px;font-family:\\u0026quot;Times New Roman\\u0026quot;,serif;text-align:center;\\\"\\u003e\\u003cspan style=\\\"color: rgb(0, 0, 0);\\\"\\u003e\\u003cspan style=\\\"font-size: 12px;\\\"\\u003e302\\u003c/span\\u003e\\u003c/span\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd style=\\\"width: 7.4%;border-top: none;border-right: none;border-left: none;border-image: initial;border-bottom: 1pt solid windowtext;background: white;padding: 0in 5.4pt;height: 15pt;vertical-align: bottom;\\\" valign=\\\"bottom\\\" width=\\\"7.6923076923076925%\\\"\\u003e\\n \\u003cp style=\\\"margin-top:0in;margin-right:0in;margin-bottom:.0001pt;margin-left:0in;line-height:normal;font-size:16px;font-family:\\u0026quot;Times New Roman\\u0026quot;,serif;text-align:center;\\\"\\u003e\\u003cspan style=\\\"color: rgb(0, 0, 0);\\\"\\u003e\\u003cspan style=\\\"font-size: 12px;\\\"\\u003e152\\u003c/span\\u003e\\u003c/span\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd style=\\\"width: 2.96%;border-top: none;border-right: none;border-left: none;border-image: initial;border-bottom: 1pt solid windowtext;background: white;padding: 0in 5.4pt;height: 15pt;vertical-align: bottom;\\\" valign=\\\"bottom\\\" width=\\\"2.197802197802198%\\\"\\u003e\\n \\u003cp style=\\\"margin-top:0in;margin-right:0in;margin-bottom:.0001pt;margin-left:0in;line-height:normal;font-size:16px;font-family:\\u0026quot;Times New Roman\\u0026quot;,serif;text-align:center;\\\"\\u003e\\u003cspan style=\\\"color: rgb(0, 0, 0);\\\"\\u003e\\u003cspan style=\\\"font-size: 12px;\\\"\\u003e\\u0026nbsp;\\u003c/span\\u003e\\u003c/span\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd style=\\\"width: 7.4%;border-top: none;border-right: none;border-left: none;border-image: initial;border-bottom: 1pt solid windowtext;background: white;padding: 0in 5.4pt;height: 15pt;vertical-align: bottom;\\\" valign=\\\"bottom\\\" width=\\\"7.6923076923076925%\\\"\\u003e\\n \\u003cp style=\\\"margin-top:0in;margin-right:0in;margin-bottom:.0001pt;margin-left:0in;line-height:normal;font-size:16px;font-family:\\u0026quot;Times New Roman\\u0026quot;,serif;text-align:center;\\\"\\u003e\\u003cspan style=\\\"color: rgb(0, 0, 0);\\\"\\u003e\\u003cspan style=\\\"font-size: 12px;\\\"\\u003e5.64\\u003c/span\\u003e\\u003c/span\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd style=\\\"width: 8.88%;border-top: none;border-right: none;border-left: none;border-image: initial;border-bottom: 1pt solid windowtext;background: white;padding: 0in 5.4pt;height: 15pt;vertical-align: bottom;\\\" valign=\\\"bottom\\\" width=\\\"8.791208791208792%\\\"\\u003e\\n \\u003cp style=\\\"margin-top:0in;margin-right:0in;margin-bottom:.0001pt;margin-left:0in;line-height:normal;font-size:16px;font-family:\\u0026quot;Times New Roman\\u0026quot;,serif;text-align:right;\\\"\\u003e\\u003cspan style=\\\"color: rgb(0, 0, 0);\\\"\\u003e\\u003cspan style=\\\"font-size: 12px;\\\"\\u003e4.05\\u003c/span\\u003e\\u003c/span\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd style=\\\"width: 2.96%;border-top: none;border-right: none;border-left: none;border-image: initial;border-bottom: 1pt solid windowtext;background: white;padding: 0in 5.4pt;height: 15pt;vertical-align: bottom;\\\" valign=\\\"bottom\\\" width=\\\"2.197802197802198%\\\"\\u003e\\n \\u003cp style=\\\"margin-top:0in;margin-right:0in;margin-bottom:.0001pt;margin-left:0in;line-height:normal;font-size:16px;font-family:\\u0026quot;Times New Roman\\u0026quot;,serif;text-align:center;\\\"\\u003e\\u003cspan style=\\\"color: rgb(0, 0, 0);\\\"\\u003e\\u003cspan style=\\\"font-size: 12px;\\\"\\u003e\\u0026nbsp;\\u003c/span\\u003e\\u003c/span\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd style=\\\"width: 7.4%;border-top: none;border-right: none;border-left: none;border-image: initial;border-bottom: 1pt solid windowtext;background: white;padding: 0in 5.4pt;height: 15pt;vertical-align: bottom;\\\" valign=\\\"bottom\\\" width=\\\"7.6923076923076925%\\\"\\u003e\\n \\u003cp style=\\\"margin-top:0in;margin-right:0in;margin-bottom:.0001pt;margin-left:0in;line-height:normal;font-size:16px;font-family:\\u0026quot;Times New Roman\\u0026quot;,serif;text-align:center;\\\"\\u003e\\u003cspan style=\\\"color: rgb(0, 0, 0);\\\"\\u003e\\u003cspan style=\\\"font-size: 12px;\\\"\\u003e26.70\\u003c/span\\u003e\\u003c/span\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd style=\\\"width: 7.4%;border-top: none;border-right: none;border-left: none;border-image: initial;border-bottom: 1pt solid windowtext;background: white;padding: 0in 5.4pt;height: 15pt;vertical-align: bottom;\\\" valign=\\\"bottom\\\" width=\\\"7.6923076923076925%\\\"\\u003e\\n \\u003cp style=\\\"margin-top:0in;margin-right:0in;margin-bottom:.0001pt;margin-left:0in;line-height:normal;font-size:16px;font-family:\\u0026quot;Times New Roman\\u0026quot;,serif;text-align:center;\\\"\\u003e\\u003cspan style=\\\"color: rgb(0, 0, 0);\\\"\\u003e\\u003cspan style=\\\"font-size: 12px;\\\"\\u003e26.19\\u003c/span\\u003e\\u003c/span\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd style=\\\"width: 2.98%;border-top: none;border-right: none;border-left: none;border-image: initial;border-bottom: 1pt solid windowtext;background: white;padding: 0in 5.4pt;height: 15pt;vertical-align: bottom;\\\" valign=\\\"bottom\\\" width=\\\"2.197802197802198%\\\"\\u003e\\n \\u003cp style=\\\"margin-top:0in;margin-right:0in;margin-bottom:.0001pt;margin-left:0in;line-height:normal;font-size:16px;font-family:\\u0026quot;Times New Roman\\u0026quot;,serif;text-align:center;\\\"\\u003e\\u003cspan style=\\\"color: rgb(0, 0, 0);\\\"\\u003e\\u003cspan style=\\\"font-size: 12px;\\\"\\u003e\\u0026nbsp;\\u003c/span\\u003e\\u003c/span\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd style=\\\"width: 7.38%;border-top: none;border-right: none;border-left: none;border-image: initial;border-bottom: 1pt solid windowtext;background: white;padding: 0in 5.4pt;height: 15pt;vertical-align: bottom;\\\" valign=\\\"bottom\\\" width=\\\"7.6923076923076925%\\\"\\u003e\\n \\u003cp style=\\\"margin-top:0in;margin-right:0in;margin-bottom:.0001pt;margin-left:0in;line-height:normal;font-size:16px;font-family:\\u0026quot;Times New Roman\\u0026quot;,serif;text-align:center;\\\"\\u003e\\u003cspan style=\\\"color: rgb(0, 0, 0);\\\"\\u003e\\u003cspan style=\\\"font-size: 12px;\\\"\\u003e11.06\\u003c/span\\u003e\\u003c/span\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd style=\\\"width: 7.42%;border-top: none;border-right: none;border-left: none;border-image: initial;border-bottom: 1pt solid windowtext;background: white;padding: 0in 5.4pt;height: 15pt;vertical-align: bottom;\\\" valign=\\\"bottom\\\" width=\\\"7.6923076923076925%\\\"\\u003e\\n \\u003cp style=\\\"margin-top:0in;margin-right:0in;margin-bottom:.0001pt;margin-left:0in;line-height:normal;font-size:16px;font-family:\\u0026quot;Times New Roman\\u0026quot;,serif;text-align:center;\\\"\\u003e\\u003cspan style=\\\"color: rgb(0, 0, 0);\\\"\\u003e\\u003cspan style=\\\"font-size: 12px;\\\"\\u003e9.32\\u003c/span\\u003e\\u003c/span\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd style=\\\"width: 2.98%;border-top: none;border-right: none;border-left: none;border-image: initial;border-bottom: 1pt solid windowtext;background: white;padding: 0in 5.4pt;height: 15pt;vertical-align: bottom;\\\" valign=\\\"bottom\\\" width=\\\"2.197802197802198%\\\"\\u003e\\n \\u003cp style=\\\"margin-top:0in;margin-right:0in;margin-bottom:.0001pt;margin-left:0in;line-height:normal;font-size:16px;font-family:\\u0026quot;Times New Roman\\u0026quot;,serif;text-align:center;\\\"\\u003e\\u003cspan style=\\\"color: rgb(0, 0, 0);\\\"\\u003e\\u003cspan style=\\\"font-size: 12px;\\\"\\u003e\\u0026nbsp;\\u003c/span\\u003e\\u003c/span\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd style=\\\"width: 5.86%;border-top: none;border-right: none;border-left: none;border-image: initial;border-bottom: 1pt solid windowtext;background: white;padding: 0in 5.4pt;height: 15pt;vertical-align: bottom;\\\" valign=\\\"bottom\\\" width=\\\"5.4945054945054945%\\\"\\u003e\\n \\u003cp style=\\\"margin-top:0in;margin-right:0in;margin-bottom:.0001pt;margin-left:0in;line-height:normal;font-size:16px;font-family:\\u0026quot;Times New Roman\\u0026quot;,serif;text-align:center;\\\"\\u003e\\u003cspan style=\\\"color: rgb(0, 0, 0);\\\"\\u003e\\u003cspan style=\\\"font-size: 12px;\\\"\\u003e0.32\\u003c/span\\u003e\\u003c/span\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd style=\\\"width: 11.56%;border-top: none;border-right: none;border-left: none;border-image: initial;border-bottom: 1pt solid windowtext;background: white;padding: 0in 5.4pt;height: 15pt;vertical-align: bottom;\\\" valign=\\\"bottom\\\" width=\\\"12.087912087912088%\\\"\\u003e\\n \\u003cp style=\\\"margin-top:0in;margin-right:0in;margin-bottom:.0001pt;margin-left:0in;line-height:normal;font-size:16px;font-family:\\u0026quot;Times New Roman\\u0026quot;,serif;text-align:center;\\\"\\u003e\\u003cspan style=\\\"color: rgb(0, 0, 0);\\\"\\u003e\\u003cspan style=\\\"font-size: 12px;\\\"\\u003e0.16\\u003c/span\\u003e\\u003c/span\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003c/tbody\\u003e\\n\\u003c/table\\u003e\\n\\u003col start=\\\"1\\\" style=\\\"margin-bottom:0in;margin-top:0in;\\\" type=\\\"1\\\"\\u003e\\n \\u003cli style=\\\"margin-top:0in;margin-right:0in;margin-bottom:8.0pt;margin-left:0in;line-height:115%;font-size:16px;font-family:\\u0026quot;Times New Roman\\u0026quot;,serif;\\\"\\u003e\\u003cspan style=\\\"color: rgb(0, 0, 0);\\\"\\u003e\\u003csub\\u003e\\u003cspan style=\\\"line-height: 115%;\\\"\\u003eNumber of runs of homozygosity segments\\u003c/span\\u003e\\u003c/sub\\u003e\\u003c/span\\u003e\\u003c/li\\u003e\\n\\u003c/ol\\u003e\\n\\u003cp style=\\\"margin-top:0in;margin-right:0in;margin-bottom:8.0pt;margin-left:0in;line-height:115%;font-size:16px;font-family:\\u0026quot;Times New Roman\\u0026quot;,serif;\\\"\\u003e\\u003cspan style=\\\"color: rgb(0, 0, 0);\\\"\\u003e\\u0026nbsp;\\u003c/span\\u003e\\u003c/p\\u003e\\n\\u003cp style=\\\"margin-top:0in;margin-right:0in;margin-bottom:8.0pt;margin-left:0in;line-height:115%;font-size:16px;font-family:\\u0026quot;Times New Roman\\u0026quot;,serif;\\\"\\u003e\\u003cspan style=\\\"color: rgb(0, 0, 0);\\\"\\u003e\\u0026nbsp;\\u003c/span\\u003e\\u003c/p\\u003e\\n\\u003cp style=\\\"margin-top:0in;margin-right:0in;margin-bottom:8.0pt;margin-left:0in;line-height:115%;font-size:16px;font-family:\\u0026quot;Times New Roman\\u0026quot;,serif;\\\"\\u003e\\u003cspan style=\\\"color: rgb(0, 0, 0);\\\"\\u003eTable 2. Average inbreeding coefficients (± standard error) estimated using diagonal elements of genomic relationship matrix (F\\u003csub\\u003eGRM\\u003c/sub\\u003e), excess of homozygosity (F\\u003csub\\u003eHOM\\u003c/sub\\u003e), correlation between uniting gametes (F\\u003csub\\u003eUNI\\u003c/sub\\u003e) and runs of homozygosity\\u0026nbsp;\\u003cspan style=\\\"line-height:115%;\\\"\\u003e(ROH) \\u0026gt;\\u003c/span\\u003e1\\u003cspan style=\\\"line-height:115%;\\\"\\u003e\\u0026nbsp;\\u003c/span\\u003eMb (F\\u003csub\\u003eROH\\u003c/sub\\u003e) in Azeri (AZ) and Khuzestani (KHZ) breeds.\\u003c/span\\u003e\\u003c/p\\u003e\\n\\u003ctable border=\\\"0\\\" cellpadding=\\\"0\\\" cellspacing=\\\"0\\\" style=\\\"width:100.0%;border-collapse:collapse;\\\" width=\\\"100%\\\"\\u003e\\n \\u003ctbody\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd style=\\\"width:20.5%;border-top:solid windowtext 1.0pt;border-left:none;border-bottom:solid windowtext 1.0pt;border-right:none;background:white;padding:0in 5.4pt 0in 5.4pt;height:20.25pt;\\\" width=\\\"20.408163265306122%\\\"\\u003e\\n \\u003cp style=\\\"margin-top:0in;margin-right:0in;margin-bottom:.0001pt;margin-left:0in;line-height:normal;font-size:16px;font-family:\\u0026quot;Times New Roman\\u0026quot;,serif;text-align:center;\\\"\\u003e\\u003cspan style=\\\"color: rgb(0, 0, 0);\\\"\\u003e\\u003cspan style=\\\"font-size:12px;\\\"\\u003eBreed\\u003c/span\\u003e\\u003c/span\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd style=\\\"width:18.48%;border-top:solid windowtext 1.0pt;border-left:none;border-bottom:solid windowtext 1.0pt;border-right:none;background:white;padding:0in 5.4pt 0in 5.4pt;height:20.25pt;\\\" width=\\\"18.367346938775512%\\\"\\u003e\\n \\u003cp style=\\\"margin-top:0in;margin-right:0in;margin-bottom:.0001pt;margin-left:0in;line-height:normal;font-size:16px;font-family:\\u0026quot;Times New Roman\\u0026quot;,serif;text-align:center;\\\"\\u003e\\u003cspan style=\\\"color: rgb(0, 0, 0);\\\"\\u003e\\u003cspan style=\\\"font-size: 12px;\\\"\\u003eF\\u003csub\\u003eGRM\\u003c/sub\\u003e\\u003c/span\\u003e\\u003c/span\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd style=\\\"width:18.48%;border-top:solid windowtext 1.0pt;border-left:none;border-bottom:solid windowtext 1.0pt;border-right:none;background:white;padding:0in 5.4pt 0in 5.4pt;height:20.25pt;\\\" width=\\\"18.367346938775512%\\\"\\u003e\\n \\u003cp style=\\\"margin-top:0in;margin-right:0in;margin-bottom:.0001pt;margin-left:0in;line-height:normal;font-size:16px;font-family:\\u0026quot;Times New Roman\\u0026quot;,serif;text-align:center;\\\"\\u003e\\u003cspan style=\\\"color: rgb(0, 0, 0);\\\"\\u003e\\u003cspan style=\\\"font-size: 12px;\\\"\\u003eF \\u003csub\\u003eHOM\\u003c/sub\\u003e\\u003c/span\\u003e\\u003c/span\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd style=\\\"width:20.5%;border-top:solid windowtext 1.0pt;border-left:none;border-bottom:solid windowtext 1.0pt;border-right:none;background:white;padding:0in 5.4pt 0in 5.4pt;height:20.25pt;\\\" width=\\\"20.408163265306122%\\\"\\u003e\\n \\u003cp style=\\\"margin-top:0in;margin-right:0in;margin-bottom:.0001pt;margin-left:0in;line-height:normal;font-size:16px;font-family:\\u0026quot;Times New Roman\\u0026quot;,serif;text-align:center;\\\"\\u003e\\u003cspan style=\\\"color: rgb(0, 0, 0);\\\"\\u003e\\u003cspan style=\\\"font-size: 12px;\\\"\\u003eF\\u003csub\\u003eUNI\\u003c/sub\\u003e\\u003c/span\\u003e\\u003c/span\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd style=\\\"width:22.04%;border-top:solid windowtext 1.0pt;border-left:none;border-bottom:solid windowtext 1.0pt;border-right:none;background:white;padding:0in 5.4pt 0in 5.4pt;height:20.25pt;\\\" width=\\\"22.448979591836736%\\\"\\u003e\\n \\u003cp style=\\\"margin-top:0in;margin-right:0in;margin-bottom:.0001pt;margin-left:0in;line-height:normal;font-size:16px;font-family:\\u0026quot;Times New Roman\\u0026quot;,serif;text-align:center;\\\"\\u003e\\u003cspan style=\\\"color: rgb(0, 0, 0);\\\"\\u003e\\u003cspan style=\\\"font-size: 12px;\\\"\\u003eF\\u003csub\\u003eROH\\u003c/sub\\u003e\\u003c/span\\u003e\\u003c/span\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd style=\\\"width:20.5%;background:white;padding:0in 5.4pt 0in 5.4pt;height:22.5pt;\\\" width=\\\"20.408163265306122%\\\"\\u003e\\n \\u003cp style=\\\"margin-top:0in;margin-right:0in;margin-bottom:.0001pt;margin-left:0in;line-height:normal;font-size:16px;font-family:\\u0026quot;Times New Roman\\u0026quot;,serif;text-align:center;\\\"\\u003e\\u003cspan style=\\\"color: rgb(0, 0, 0);\\\"\\u003e\\u003cspan style=\\\"font-size: 12px;\\\"\\u003eAZ\\u003c/span\\u003e\\u003c/span\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd style=\\\"width:18.48%;background:white;padding:0in 5.4pt 0in 5.4pt;height:22.5pt;\\\" width=\\\"18.367346938775512%\\\"\\u003e\\n \\u003cp style=\\\"margin-top:0in;margin-right:0in;margin-bottom:.0001pt;margin-left:0in;line-height:normal;font-size:16px;font-family:\\u0026quot;Times New Roman\\u0026quot;,serif;text-align:center;\\\"\\u003e\\u003cspan style=\\\"color: rgb(0, 0, 0);\\\"\\u003e\\u003cspan style=\\\"font-size: 12px;\\\"\\u003e0.026±0.05\\u003c/span\\u003e\\u003c/span\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd style=\\\"width:18.48%;background:white;padding:0in 5.4pt 0in 5.4pt;height:22.5pt;\\\" width=\\\"18.367346938775512%\\\"\\u003e\\n \\u003cp style=\\\"margin-top:0in;margin-right:0in;margin-bottom:.0001pt;margin-left:0in;line-height:normal;font-size:16px;font-family:\\u0026quot;Times New Roman\\u0026quot;,serif;text-align:center;\\\"\\u003e\\u003cspan style=\\\"color: rgb(0, 0, 0);\\\"\\u003e\\u003cspan style=\\\"font-size: 12px;\\\"\\u003e0.026±0.0.05\\u003c/span\\u003e\\u003c/span\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd style=\\\"width:20.5%;background:white;padding:0in 5.4pt 0in 5.4pt;height:22.5pt;\\\" width=\\\"20.408163265306122%\\\"\\u003e\\n \\u003cp style=\\\"margin-top:0in;margin-right:0in;margin-bottom:.0001pt;margin-left:0in;line-height:normal;font-size:16px;font-family:\\u0026quot;Times New Roman\\u0026quot;,serif;text-align:center;\\\"\\u003e\\u003cspan style=\\\"color: rgb(0, 0, 0);\\\"\\u003e\\u003cspan style=\\\"font-size: 12px;\\\"\\u003e0.026±0.05\\u003c/span\\u003e\\u003c/span\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd style=\\\"width:22.04%;background:white;padding:0in 5.4pt 0in 5.4pt;height:22.5pt;\\\" width=\\\"22.448979591836736%\\\"\\u003e\\n \\u003cp style=\\\"margin-top:0in;margin-right:0in;margin-bottom:.0001pt;margin-left:0in;line-height:normal;font-size:16px;font-family:\\u0026quot;Times New Roman\\u0026quot;,serif;text-align:center;\\\"\\u003e\\u003cspan style=\\\"color: rgb(0, 0, 0);\\\"\\u003e\\u003cspan style=\\\"font-size: 12px;\\\"\\u003e0.043±0.05\\u003c/span\\u003e\\u003c/span\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd style=\\\"width:20.5%;border:none;border-bottom:solid windowtext 1.0pt;background:white;padding:0in 5.4pt 0in 5.4pt;height:19.5pt;\\\" width=\\\"20.408163265306122%\\\"\\u003e\\n \\u003cp style=\\\"margin-top:0in;margin-right:0in;margin-bottom:.0001pt;margin-left:0in;line-height:normal;font-size:16px;font-family:\\u0026quot;Times New Roman\\u0026quot;,serif;text-align:center;\\\"\\u003e\\u003cspan style=\\\"color: rgb(0, 0, 0);\\\"\\u003e\\u003cspan style=\\\"font-size: 12px;\\\"\\u003eKHZ\\u003c/span\\u003e\\u003c/span\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd style=\\\"width:18.48%;border:none;border-bottom:solid windowtext 1.0pt;background:white;padding:0in 5.4pt 0in 5.4pt;height:19.5pt;\\\" width=\\\"18.367346938775512%\\\"\\u003e\\n \\u003cp style=\\\"margin-top:0in;margin-right:0in;margin-bottom:.0001pt;margin-left:0in;line-height:normal;font-size:16px;font-family:\\u0026quot;Times New Roman\\u0026quot;,serif;text-align:center;\\\"\\u003e\\u003cspan style=\\\"color: rgb(0, 0, 0);\\\"\\u003e\\u003cspan style=\\\"font-size: 12px;\\\"\\u003e0.019±0.04\\u003c/span\\u003e\\u003c/span\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd style=\\\"width:18.48%;border:none;border-bottom:solid windowtext 1.0pt;background:white;padding:0in 5.4pt 0in 5.4pt;height:19.5pt;\\\" width=\\\"18.367346938775512%\\\"\\u003e\\n \\u003cp style=\\\"margin-top:0in;margin-right:0in;margin-bottom:.0001pt;margin-left:0in;line-height:normal;font-size:16px;font-family:\\u0026quot;Times New Roman\\u0026quot;,serif;text-align:center;\\\"\\u003e\\u003cspan style=\\\"color: rgb(0, 0, 0);\\\"\\u003e\\u003cspan style=\\\"font-size: 12px;\\\"\\u003e0.021±0.06\\u003c/span\\u003e\\u003c/span\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd style=\\\"width:20.5%;border:none;border-bottom:solid windowtext 1.0pt;background:white;padding:0in 5.4pt 0in 5.4pt;height:19.5pt;\\\" width=\\\"20.408163265306122%\\\"\\u003e\\n \\u003cp style=\\\"margin-top:0in;margin-right:0in;margin-bottom:.0001pt;margin-left:0in;line-height:normal;font-size:16px;font-family:\\u0026quot;Times New Roman\\u0026quot;,serif;text-align:center;\\\"\\u003e\\u003cspan style=\\\"color: rgb(0, 0, 0);\\\"\\u003e\\u003cspan style=\\\"font-size: 12px;\\\"\\u003e0.021±0.05\\u003c/span\\u003e\\u003c/span\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd style=\\\"width:22.04%;border:none;border-bottom:solid windowtext 1.0pt;background:white;padding:0in 5.4pt 0in 5.4pt;height:19.5pt;\\\" width=\\\"22.448979591836736%\\\"\\u003e\\n \\u003cp style=\\\"margin-top:0in;margin-right:0in;margin-bottom:.0001pt;margin-left:0in;line-height:normal;font-size:16px;font-family:\\u0026quot;Times New Roman\\u0026quot;,serif;text-align:center;\\\"\\u003e\\u003cspan style=\\\"color: rgb(0, 0, 0);\\\"\\u003e\\u003cspan style=\\\"font-size: 12px;\\\"\\u003e0.059±0.04\\u003c/span\\u003e\\u003c/span\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003c/tbody\\u003e\\n\\u003c/table\\u003e\\n\\u003cp style=\\\"margin-top:0in;margin-right:0in;margin-bottom:8.0pt;margin-left:0in;line-height:107%;font-size:16px;font-family:\\u0026quot;Times New Roman\\u0026quot;,serif;\\\"\\u003e\\u003cspan style=\\\"color: rgb(0, 0, 0);\\\"\\u003e\\u003cspan style=\\\"line-height:107%;\\\"\\u003e\\u0026nbsp;\\u003c/span\\u003e\\u003c/span\\u003e\\u003c/p\\u003e\\n\\u003cp style=\\\"margin-top:0in;margin-right:0in;margin-bottom:8.0pt;margin-left:0in;line-height:115%;font-size:16px;font-family:\\u0026quot;Times New Roman\\u0026quot;,serif;\\\"\\u003e\\u003cspan style=\\\"color: rgb(0, 0, 0);\\\"\\u003eTable 3. Correlation between inbreeding coefficients\\u003csup\\u003e\\u0026nbsp;\\u003c/sup\\u003ecalculated using runs of homozygosity\\u0026nbsp;\\u003cspan style=\\\"line-height:115%;\\\"\\u003e(ROH) \\u0026gt;\\u003c/span\\u003e1\\u003cspan style=\\\"line-height:115%;\\\"\\u003e\\u0026nbsp;\\u003c/span\\u003eMb (F\\u003csub\\u003eROH\\u003c/sub\\u003e) and estimated using diagonal elements of genomic relationship matrix (F\\u003csub\\u003eGRM\\u003c/sub\\u003e), excess of homozygosity (F\\u003csub\\u003eHOM\\u003c/sub\\u003e\\u003cspan style=\\\"line-height:115%;\\\"\\u003e),\\u003c/span\\u003e and correlation between uniting gametes (F\\u003csub\\u003eUNI\\u003c/sub\\u003e) in Azeri (AZ) and Khuzestani (KHZ) breeds.\\u003c/span\\u003e\\u003c/p\\u003e\\n\\u003cp style=\\\"margin-top:0in;margin-right:0in;margin-bottom:8.0pt;margin-left:0in;line-height:115%;font-size:16px;font-family:\\u0026quot;Times New Roman\\u0026quot;,serif;\\\"\\u003e\\u003cspan style=\\\"color: rgb(0, 0, 0);\\\"\\u003e\\u0026nbsp;\\u003c/span\\u003e\\u003c/p\\u003e\\n\\u003ctable border=\\\"0\\\" cellpadding=\\\"0\\\" cellspacing=\\\"0\\\" style=\\\"width:100.0%;border-collapse:collapse;\\\" width=\\\"100%\\\"\\u003e\\n \\u003ctbody\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd rowspan=\\\"2\\\" style=\\\"width:20.76%;border-top:solid windowtext 1.0pt;border-left:none;border-bottom:solid black 1.0pt;border-right:none;background:white;padding:0in 5.4pt 0in 5.4pt;height:16.2pt;\\\" width=\\\"20.2020202020202%\\\"\\u003e\\n \\u003cp style=\\\"margin-top:0in;margin-right:0in;margin-bottom:.0001pt;margin-left:0in;line-height:normal;font-size:16px;font-family:\\u0026quot;Times New Roman\\u0026quot;,serif;text-align:center;\\\"\\u003e\\u003cspan style=\\\"color: rgb(0, 0, 0);\\\"\\u003e\\u003cspan style=\\\"font-size:11px;\\\"\\u003eBreed\\u003c/span\\u003e\\u003c/span\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd colspan=\\\"8\\\" style=\\\"width: 79.24%;border-right: none;border-bottom: none;border-left: none;border-image: initial;border-top: 1pt solid windowtext;background: white;padding: 0in 5.4pt;height: 16.2pt;vertical-align: bottom;\\\" valign=\\\"bottom\\\" width=\\\"79.79797979797979%\\\"\\u003e\\n \\u003cp style=\\\"margin-top:0in;margin-right:0in;margin-bottom:.0001pt;margin-left:0in;line-height:normal;font-size:16px;font-family:\\u0026quot;Times New Roman\\u0026quot;,serif;text-align:center;\\\"\\u003e\\u003cspan style=\\\"color: rgb(0, 0, 0);\\\"\\u003e\\u003cspan style=\\\"font-size: 12px;\\\"\\u003eCorrelation coefficient\\u003c/span\\u003e\\u003c/span\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd style=\\\"width:3.9%;border-top:solid windowtext 1.0pt;border-left:none;border-bottom:solid windowtext 1.0pt;border-right:none;background:white;padding:0in 5.4pt 0in 5.4pt;height:16.2pt;\\\" width=\\\"4%\\\"\\u003e\\n \\u003cp style=\\\"margin-top:0in;margin-right:0in;margin-bottom:.0001pt;margin-left:0in;line-height:normal;font-size:16px;font-family:\\u0026quot;Times New Roman\\u0026quot;,serif;text-align:center;\\\"\\u003e\\u003cspan style=\\\"color: rgb(0, 0, 0);\\\"\\u003e\\u003cspan style=\\\"font-size:11px;\\\"\\u003e\\u0026nbsp;\\u003c/span\\u003e\\u003c/span\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd style=\\\"width:4.5%;border:none;border-bottom:solid windowtext 1.0pt;background:white;padding:0in 5.4pt 0in 5.4pt;height:16.2pt;\\\" width=\\\"5.333333333333333%\\\"\\u003e\\n \\u003cp style=\\\"margin-top:0in;margin-right:0in;margin-bottom:.0001pt;margin-left:0in;line-height:normal;font-size:16px;font-family:\\u0026quot;Times New Roman\\u0026quot;,serif;text-align:center;\\\"\\u003e\\u003cspan style=\\\"color: rgb(0, 0, 0);\\\"\\u003e\\u003cspan style=\\\"font-size: 11px;\\\"\\u003e\\u0026nbsp;\\u003c/span\\u003e\\u003c/span\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd style=\\\"width:19.56%;border:none;border-bottom:solid windowtext 1.0pt;background:white;padding:0in 5.4pt 0in 5.4pt;height:16.2pt;\\\" width=\\\"25.333333333333332%\\\"\\u003e\\n \\u003cp style=\\\"margin-top:0in;margin-right:0in;margin-bottom:.0001pt;margin-left:0in;line-height:normal;font-size:16px;font-family:\\u0026quot;Times New Roman\\u0026quot;,serif;text-align:center;\\\"\\u003e\\u003cspan style=\\\"color: rgb(0, 0, 0);\\\"\\u003e\\u003cspan style=\\\"font-size: 12px;\\\"\\u003eF\\u003csub\\u003eGRM\\u0026nbsp;\\u003c/sub\\u003e-F\\u003csub\\u003eROH\\u003c/sub\\u003e\\u003c/span\\u003e\\u003c/span\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd style=\\\"width:4.6%;border:none;border-bottom:solid windowtext 1.0pt;background:white;padding:0in 5.4pt 0in 5.4pt;height:16.2pt;\\\" width=\\\"5.333333333333333%\\\"\\u003e\\n \\u003cp style=\\\"margin-top:0in;margin-right:0in;margin-bottom:.0001pt;margin-left:0in;line-height:normal;font-size:16px;font-family:\\u0026quot;Times New Roman\\u0026quot;,serif;text-align:center;\\\"\\u003e\\u003cspan style=\\\"color: rgb(0, 0, 0);\\\"\\u003e\\u003cspan style=\\\"font-size: 12px;\\\"\\u003e\\u0026nbsp;\\u003c/span\\u003e\\u003c/span\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd style=\\\"width:4.6%;border:none;border-bottom:solid windowtext 1.0pt;background:white;padding:0in 5.4pt 0in 5.4pt;height:16.2pt;\\\" width=\\\"5.333333333333333%\\\"\\u003e\\n \\u003cp style=\\\"margin-top:0in;margin-right:0in;margin-bottom:.0001pt;margin-left:0in;line-height:normal;font-size:16px;font-family:\\u0026quot;Times New Roman\\u0026quot;,serif;text-align:center;\\\"\\u003e\\u003cspan style=\\\"color: rgb(0, 0, 0);\\\"\\u003e\\u003cspan style=\\\"font-size: 12px;\\\"\\u003e\\u0026nbsp;\\u003c/span\\u003e\\u003c/span\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd style=\\\"width:20.04%;border:none;border-bottom:solid windowtext 1.0pt;background:white;padding:0in 5.4pt 0in 5.4pt;height:16.2pt;\\\" width=\\\"26.666666666666668%\\\"\\u003e\\n \\u003cp style=\\\"margin-top:0in;margin-right:0in;margin-bottom:.0001pt;margin-left:0in;line-height:normal;font-size:16px;font-family:\\u0026quot;Times New Roman\\u0026quot;,serif;text-align:center;\\\"\\u003e\\u003cspan style=\\\"color: rgb(0, 0, 0);\\\"\\u003e\\u003cspan style=\\\"font-size: 12px;\\\"\\u003eF\\u003csub\\u003eHOM\\u003c/sub\\u003e-F\\u003csub\\u003eROH\\u003c/sub\\u003e\\u003c/span\\u003e\\u003c/span\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd style=\\\"width:4.6%;border:none;border-bottom:solid windowtext 1.0pt;background:white;padding:0in 5.4pt 0in 5.4pt;height:16.2pt;\\\" width=\\\"5.333333333333333%\\\"\\u003e\\n \\u003cp style=\\\"margin-top:0in;margin-right:0in;margin-bottom:.0001pt;margin-left:0in;line-height:normal;font-size:16px;font-family:\\u0026quot;Times New Roman\\u0026quot;,serif;text-align:center;\\\"\\u003e\\u003cspan style=\\\"color: rgb(0, 0, 0);\\\"\\u003e\\u003cspan style=\\\"font-size: 12px;\\\"\\u003e\\u0026nbsp;\\u003c/span\\u003e\\u003c/span\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd style=\\\"width:17.46%;border:none;border-bottom:solid windowtext 1.0pt;background:white;padding:0in 5.4pt 0in 5.4pt;height:16.2pt;\\\" width=\\\"22.666666666666668%\\\"\\u003e\\n \\u003cp style=\\\"margin-top:0in;margin-right:0in;margin-bottom:.0001pt;margin-left:0in;line-height:normal;font-size:16px;font-family:\\u0026quot;Times New Roman\\u0026quot;,serif;text-align:center;\\\"\\u003e\\u003cspan style=\\\"color: rgb(0, 0, 0);\\\"\\u003e\\u003cspan style=\\\"font-size: 12px;\\\"\\u003eF\\u003csub\\u003eUNI\\u003c/sub\\u003e-F\\u003csub\\u003eROH\\u003c/sub\\u003e\\u003c/span\\u003e\\u003c/span\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd style=\\\"width:20.76%;background:white;padding:0in 5.4pt 0in 5.4pt;height:30.1pt;\\\" width=\\\"21.05263157894737%\\\"\\u003e\\n \\u003cp style=\\\"margin-top:0in;margin-right:0in;margin-bottom:.0001pt;margin-left:0in;line-height:normal;font-size:16px;font-family:\\u0026quot;Times New Roman\\u0026quot;,serif;text-align:center;\\\"\\u003e\\u003cspan style=\\\"color: rgb(0, 0, 0);\\\"\\u003e\\u003cspan style=\\\"font-size: 11px;\\\"\\u003eAZ\\u003c/span\\u003e\\u003c/span\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd style=\\\"width:3.9%;background:white;padding:0in 5.4pt 0in 5.4pt;height:30.1pt;\\\" width=\\\"3.1578947368421053%\\\"\\u003e\\n \\u003cp style=\\\"margin-top:0in;margin-right:0in;margin-bottom:.0001pt;margin-left:0in;line-height:normal;font-size:16px;font-family:\\u0026quot;Times New Roman\\u0026quot;,serif;text-align:center;\\\"\\u003e\\u003cspan style=\\\"color: rgb(0, 0, 0);\\\"\\u003e\\u003cspan 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width=\\\"4.2105263157894735%\\\"\\u003e\\u003cspan style=\\\"color: rgb(0, 0, 0);\\\"\\u003e\\n \\u003cbr\\u003e\\n \\u003c/span\\u003e\\u003c/td\\u003e\\n \\u003ctd style=\\\"width:4.6%;background:white;padding:0in 5.4pt 0in 5.4pt;height:30.1pt;\\\" width=\\\"4.2105263157894735%\\\"\\u003e\\u003cspan style=\\\"color: rgb(0, 0, 0);\\\"\\u003e\\n \\u003cbr\\u003e\\n \\u003c/span\\u003e\\u003c/td\\u003e\\n \\u003ctd style=\\\"width:20.04%;background:white;padding:0in 5.4pt 0in 5.4pt;height:30.1pt;\\\" width=\\\"21.05263157894737%\\\"\\u003e\\n \\u003cp style=\\\"margin-top:0in;margin-right:0in;margin-bottom:.0001pt;margin-left:0in;line-height:normal;font-size:16px;font-family:\\u0026quot;Times New Roman\\u0026quot;,serif;text-align:center;\\\"\\u003e\\u003cspan style=\\\"color: rgb(0, 0, 0);\\\"\\u003e\\u003cspan style=\\\"font-size: 11px;\\\"\\u003e0.92\\u003c/span\\u003e\\u003c/span\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd 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0);\\\"\\u003e\\u003cspan style=\\\"font-size: 11px;\\\"\\u003e0.94\\u003c/span\\u003e\\u003c/span\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003c/tbody\\u003e\\n\\u003c/table\\u003e\"},{\"header\":\"Additional File Legends\",\"content\":\"\\u003cp\\u003eAdditional file 1: List of the detected runs of homozygosity (ROH) in Azeri (AZ) and Khuzestani (KHZ) breeds.\\u003c/p\\u003e\\n\\u003cp\\u003e\\u0026nbsp;\\u003c/p\\u003e\\n\\u003cp\\u003eAdditional file 2. The estimated inbreeding coefficient using runs of homozygosity (ROH) \\u0026gt;1\\u0026nbsp;Mb (F\\u003csub\\u003eROH\\u003c/sub\\u003e), diagonal elements of genomic relationship matrix (F\\u003csub\\u003eGRM\\u003c/sub\\u003e), excess of homozygosity (F\\u003csub\\u003eHOM\\u003c/sub\\u003e) and correlation between uniting gametes (F\\u003csub\\u003eUNI\\u003c/sub\\u003e) in Azeri (AZ) and Khuzestani (KHZ) breeds.\\u003c/p\\u003e\\n\\u003cp\\u003e\\u0026nbsp;\\u003c/p\\u003e\\n\\u003cp\\u003eAdditional file 3. Frequently occurring runs of homozygosity (ROH) regions (i.e. ROH islands) in Azeri (AZ) and Khuzestani (KHZ) breeds. The last column represents the average r\\u003csup\\u003e2\\u003c/sup\\u003e of ROH islands divided by the average r\\u003csup\\u003e2\\u003c/sup\\u003e of each chromosome.\\u003c/p\\u003e\\n\\u003cp\\u003e\\u0026nbsp;\\u003c/p\\u003e\\n\\u003cp\\u003eAdditional file 4. The genes located in detected runs of homozygosity (ROH) islands in the Khuzestani (KHZ) breed that were significantly enriched (\\u003cem\\u003eP\\u003c/em\\u003e\\u0026le;0.05) in biological processes (BP), cellular component (CC) and molecular function (MF) Gene Ontology (GO) terms.\\u003c/p\\u003e\\n\\u003cp\\u003e\\u0026nbsp;\\u003c/p\\u003e\\n\\u003cp\\u003eAdditional file 5. List of integrated haplotype homozygosity scores (iHS) for all SNPs in Azeri (AZ) and Khuzestani (KHZ) breeds.\\u003c/p\\u003e\\n\\u003cp\\u003e\\u0026nbsp;\\u003c/p\\u003e\\n\\u003cp\\u003eAdditional file 6. Manhattan plot of integrated haplotype homozygosity score (iHS) across the genome.\\u003c/p\\u003e\"}],\"fulltextSource\":\"\",\"fullText\":\"\",\"funders\":[],\"hasAdminPriorityOnWorkflow\":false,\"hasManuscriptDocX\":true,\"hasOptedInToPreprint\":true,\"hasPassedJournalQc\":\"\",\"hasAnyPriority\":false,\"hideJournal\":false,\"highlight\":\"\",\"institution\":\"\",\"isAcceptedByJournal\":true,\"isAuthorSuppliedPdf\":false,\"isDeskRejected\":\"\",\"isHiddenFromSearch\":false,\"isInQc\":false,\"isInWorkflow\":false,\"isPdf\":false,\"isPdfUpToDate\":true,\"isWithdrawnOrRetracted\":false,\"journal\":{\"display\":true,\"email\":\"info@researchsquare.com\",\"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\":\"water buffalo; river buffalo; genetic diversity; inbreeding; gene enrichment; runs of homozygosity; selection signatures\",\"lastPublishedDoi\":\"10.21203/rs.2.17561/v5\",\"lastPublishedDoiUrl\":\"https://doi.org/10.21203/rs.2.17561/v5\",\"license\":{\"name\":\"CC BY 4.0\",\"url\":\"https://creativecommons.org/licenses/by/4.0/\"},\"manuscriptAbstract\":\"Background: Consecutive homozygous fragments of a genome inherited by offspring from a common ancestor are known as runs of homozygosity (ROH). ROH can be used to calculate genomic inbreeding and to identify genomic regions that are potentially under historical selection pressure. The dataset of our study consisted of 254 Azeri (AZ) and 115 Khuzestani (KHZ ) river buffalo genotyped for ~65000 SNPs for the following two purposes: 1) to estimate and compare inbreeding calculated using ROH (FROH), excess of homozygosity (FHOM), correlation between uniting gametes (FUNI), and diagonal elements of the genomic relationship matrix (FGRM); 2) to identify frequently occurring ROH (i.e. ROH islands) for our selection signature and gene enrichment studies.\\nResults: In this study, 9102 ROH were identified, with an average number of 21.2±13.1 and 33.2±15.9 segments per animal in AZ and KHZ breeds, respectively. On average in AZ, 4.35% (108.8±120.3 Mb), and in KHZ, 5.96% (149.1±107.7 Mb) of the genome was autozygous. The estimated inbreeding values based on FHOM, FUNI and FGRM were higher in AZ than they were in KHZ, which was in contrast to the FROH estimates. We identified 11 ROH islands (four in AZ and seven in KHZ). In the KHZ breed, the genes located in ROH islands were enriched for multiple Gene Ontology (GO) terms (P≤0.05). The genes located in ROH islands were associated with diverse biological functions and traits such as body size and muscle development (BMP2), immune response (CYP27B1), milk production and components (MARS, ADRA1A, and KCTD16), coat colour and pigmentation (PMEL and MYO1A), reproductive traits (INHBC, INHBE, STAT6 and PCNA), and bone development (SUOX).\\nConclusion: The calculated FROH was in line with expected higher inbreeding in KHZ than in AZ because of the smaller effective population size of KHZ. Thus, we find that FROH can be used as a robust estimate of genomic inbreeding. Further, the majority of ROH peaks were overlapped with or in close proximity to the previously reported genomic regions with signatures of selection. This tells us that it is likely that the genes in the ROH islands have been subject to artificial or natural selection.\",\"manuscriptTitle\":\"Genomic measures of inbreeding coefficients and genome-wide scan for runs of homozygosity islands in Iranian river buffalo, Bubalus bubalis\",\"msid\":\"\",\"msnumber\":\"\",\"nonDraftVersions\":[{\"code\":5,\"date\":\"2020-02-05 18:35:01\",\"doi\":\"10.21203/rs.2.17561/v5\",\"editorialEvents\":[{\"type\":\"communityComments\",\"content\":0}],\"status\":\"published\",\"journal\":{\"display\":true,\"email\":\"info@researchsquare.com\",\"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}},{\"code\":4,\"date\":\"2020-01-29 18:43:17\",\"doi\":\"10.21203/rs.2.17561/v4\",\"editorialEvents\":[{\"type\":\"communityComments\",\"content\":0}],\"status\":\"published\",\"journal\":{\"display\":true,\"email\":\"info@researchsquare.com\",\"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}},{\"code\":3,\"date\":\"2020-01-21 15:48:31\",\"doi\":\"10.21203/rs.2.17561/v3\",\"editorialEvents\":[{\"type\":\"communityComments\",\"content\":0}],\"status\":\"published\",\"journal\":{\"display\":true,\"email\":\"info@researchsquare.com\",\"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}},{\"code\":2,\"date\":\"2020-01-16 18:46:13\",\"doi\":\"10.21203/rs.2.17561/v2\",\"editorialEvents\":[{\"type\":\"communityComments\",\"content\":0}],\"status\":\"published\",\"journal\":{\"display\":true,\"email\":\"info@researchsquare.com\",\"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}},{\"code\":1,\"date\":\"2019-11-25 21:30:10\",\"doi\":\"10.21203/rs.2.17561/v1\",\"editorialEvents\":[{\"type\":\"communityComments\",\"content\":0}],\"status\":\"published\",\"journal\":{\"display\":true,\"email\":\"info@researchsquare.com\",\"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\":\"8f26b091-752b-4dba-8eb2-39bca5b72ba1\",\"owner\":[],\"postedDate\":\"February 5th, 2020\",\"published\":true,\"recentEditorialEvents\":[],\"rejectedJournal\":[],\"revision\":\"\",\"amendment\":\"\",\"status\":\"published-in-journal\",\"subjectAreas\":[{\"id\":54183,\"name\":\"Population Genetics\"}],\"tags\":[],\"updatedAt\":\"\",\"versionOfRecord\":{\"articleIdentity\":\"rs-8193\",\"link\":\"https://doi.org/10.1186/s12863-020-0824-y\",\"journal\":{\"identity\":\"bmc-genetics\",\"isVorOnly\":true,\"title\":\"BMC Genetics\"},\"publishedOn\":\"2020-02-10 12:00:00\",\"publishedOnDateReadable\":\"February 10th, 2020\"},\"versionCreatedAt\":\"2020-02-05 18:35:01\",\"video\":\"\",\"vorDoi\":\"10.1186/s12863-020-0824-y\",\"vorDoiUrl\":\"https://doi.org/10.1186/s12863-020-0824-y\",\"workflowStages\":[]},\"version\":\"v5\",\"identity\":\"rs-8193\",\"journalConfig\":\"researchsquare\"},\"__N_SSP\":true},\"page\":\"/article/[identity]/[[...version]]\",\"query\":{\"identity\":\"rs-8193\",\"version\":[\"v5\"]},\"buildId\":\"7rjqhiLT3MXkJMwkYKINL\",\"isFallback\":false,\"isExperimentalCompile\":false,\"dynamicIds\":[84888],\"gssp\":true,\"scriptLoader\":[]}","source_license":"CC-BY-4.0","license_restricted":false}