Analysis of the Relationship between Short Tandem Repeats and Lactation Performance of Xinjiang Holstein Cows

Analysis of the Relationship between Short Tandem Repeats and Lactation Performance of Xinjiang Holstein Cows | 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 Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Analysis of the Relationship between Short Tandem Repeats and Lactation Performance of Xinjiang Holstein Cows Yongqing LI, Li LIU, Zunongjiang ABULA, Lijun CAO, Yikai FAN, and 2 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-2537800/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 15 Jun, 2023 Read the published version in Tropical Animal Health and Production → Version 1 posted 3 You are reading this latest preprint version Abstract Microsatellite markers, also known as short tandem repeats (STRs), are important for marker-assisted selection to detect genetic polymorphism, and they are uniformly distributed in eukaryotic genomes. To analyze the relationship between microsatellite loci and lactation traits of Holstein cows in Xinjiang, 175 lactating cows with similar birth dates, the same parity, and similar calving dates were selected, and 10 STR loci closely linked to quantitative trait loci were used to analyze the correlation between each STR locus and 4 lactation traits (daily milk yield, milk fat percentage, milk protein percentage, and lactose percentage). All loci showed different degrees of genetic polymorphism. The average values of observed alleles, effective alleles, expected heterozygosity, observed heterozygosity, and polymorphic information content of the 10 STR loci were 10, 3.11, 0.62, 0.64, and 0.58, respectively. Chi-square and G-square tests showed that all populations of loci were in accordance with the Hardy–Weinberg equilibrium. Analysis of the correlation between STR locus genotype and lactation performance in the whole lactation period showed 3 loci (namely, BM143, BM415, and BP7) with no significant correlation with all lactation traits, 2 loci (BM302 and UWCA9) related to milk yield, 3 loci (BM103, BM302, and BM6425) related to milk fat percentage, 2 loci (BM302 and BM6425) related to milk protein percentage, and 3 loci (BM1443, BM302, and BMS1943) related to lactose percentage. The microsatellite loci selected in this study showed rich polymorphism in the experimental dairy cow population and were related to the lactation traits, which can be used for the evaluation of genetic resources and early breeding and improvement of Holstein dairy cows in Xinjiang. Xinjiang Holstein cow STR Lactation performance Microsatellite loci Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Figure 8 Figure 9 Figure 10 Introduction Genetic polymorphism, as the basis of animal evolution and development, is an important part of biodiversity and gene improvement (Williams et al. 1990). Microsatellite markers, also known as short tandem repeats (STRs) or simple sequence repeats (SSRs), are uniformly distributed in the genome of eukaryotes and composed of 1–6 nucleotide tandem repeats, including single type, compound type, and interval type; microsatellite markers are used in marker-assisted selection to detect genetic polymorphism (Takezaki et al. 1996). Microsatellite loci have broad applications in pedigree tracing and gene improvement because of their co-dominant inheritance, rich polymorphism, conservative flanking sequences, and easy design of universal primers. Comprehensive studies performed worldwide have found that quantitative trait loci for milk yield, milk fat, and milk protein located using microsatellite markers in dairy cows are distributed on chromosomes 3, 6, 7, 8, 9, 10, 11, 14, 17, 18, 20, 21, 23, 25, 26, 27, and 28. Yin Bin et al. (2016) selected 8 microsatellite loci from the database of the International Society of Animal Genetics to analyze the relationship between their corresponding genotypes and production traits and obtain a molecular basis for early breeding of Holstein cows. In 2018, Polish scientist Dux discovered a microsatellite locus in the intron 23 region of insulin-like growth factor receptor 2 and significantly associated different genotypes of this locus with high milk yield, high milk fat percentage, and high milk protein level (Dux M et al. 2018). Recently, many studies have analyzed STRs and SSRs in plants and microorganisms, for example, genetic diversity of Venturia inaequalis in Latvia (Sokolova et al. 2022), STR locus comparison of cherry germplasm in Europe (Ordidge et al. 2021), microsatellite loci related to drought tolerance traits in potato (Schumacher et al. 2021), apotheciate Usnea florida (Degtjarenko et al. 2020), and resistance to scab in European triticale (Ollier et al. 2020). However, relatively few studies have analyzed STRs and SSRs in animals. In 2022, Griciuvien et al. (2022) used STRs to analyze genetic structure changes in the wild boar ( Sus scrofa ) in Lithuania, following an outbreak of African swine fever. In addition, STR site mining of the weevil (Apriyanto et al. 2021), great-billed seed-finch (de Melo et al. 2020), and copper butterfly (Trense et al. 2019) has been performed. Microsatellite technology has been used to analyze the genetic diversity and genetic bottleneck of buffalo (Ali et al. 2021), genetic identification of Zavot cattle (Boğa et al. 2022), identification of phenotype and genetic diversity of high-altitude yaks in Pakistan (Hameed et al. 2022), relationship between genetic diversity and phylogeny of cattle in Senegal (Sambe et al. 2022), relationship between genetic diversity and phylogeny of Siberian black-skinned cattle (Aitnazarov et al. 2021), genetic diversity of cattle in Kerala, India, and relationship between STR genetic diversity and quantitative trait variations of bull semen (Gororo et al. 2021). There has been limited research on the correlation between microsatellite loci and milk production traits of Holstein cows, and there are no reports on microsatellite locus analysis of Holstein cows in Xinjiang. In addition, the correlation analysis results between microsatellite loci and lactation performance obtained by previous researchers were compared, and the correlations between some established loci and traits were found to be inconsistent. To identify and confirm the correlation between microsatellite loci and lactation performance of Holstein cows in Xinjiang, in this study, 10 STR markers and milk production traits (milk yield, milk fat percentage, milk protein percentage, and lactose percentage) of Holstein cows were analyzed in a complete lactation period in Xinjiang. Our findings can be used for the protection and utilization of high-quality genetic resources of Holstein cows in Xinjiang and elimination of cows with relatively weak lactation performance. Materials And Methods Animal population According to the experimental design, a total of 175 Holstein cows with born in 2016, first birth, and calving in 2018 were selected as the experimental group in a large-scale dairy farm in northern Xinjiang. Collection of phenotypic traits The FOSS milk composition analyzer (Fossomatic 5000basic 75710), Foss Denmark Ltd., was used to measure 4 lactation-related traits: milk yield (kg), milk fat percentage, milk protein percentage, and lactose percentage. The traits were measured once a month for 10 consecutive months. Blood collection and DNA extraction Venous blood (3–4 ml) was collected from the tail root of the cattle in EDTA tubes, shaken well, transferred to 5 ml freezing tubes, and placed in a liquid nitrogen tank for storage. The whole-blood genome was extracted using a DNA extraction kit (Tiangen, DP304-02), and the DNA quality was detected with 0.75% agarose gel electrophoresis; DNA concentration and purity were detected using a spectrophotometer, and the DNA samples were stored at -20℃. Selection and amplification of microsatellite loci According to the recommendation of the Food and Agriculture Organization of the United Nations ( http://www.fao.org ) and Chu et al. (2003), 10 microsatellite loci closely adjacent to quantitative trait loci were selected as candidate loci (Table 1 ). The primers were synthesized by Shanghai Shenggong Bioengineering Co., Ltd. The amplification volume was 25 µl: 2.5 µl of 10× Taq buffer (with MgCl 2 ), 0.5 µl of 10 µm DNTP (mix), 0.5 µl of 10 µmol/l forward and reverse primers, 0.2 µl of 5 U/µl Taq enzyme, and ddH 2 O (up to 25 µl). The optimized thermocycling conditions were as follows: initial denaturation at 95℃ for 5 min; 10 cycles of denaturation at 94℃ for 30 s, annealing at 60℃ for 30 s, and extension at 72℃ for 30 s; 30 cycles of denaturation at 94℃ for 30 s, annealing at 55℃ for 30 s, and extension at 72℃ for 30 s; and preservation at 4℃. Table 1 Microsatellite sites and primer information Number Microsatellite site Primer sequence, 5′-3′ Chromosome Annealing temperature, ℃ Size, bp 1 BM203 F:5’-GGGTGTGACATTTTGTTCCC-3’ 27 61 217–234 R:5'-CTGCTCGCCACTAGTCCTTC-3’ 2 BM302 F:5'-GAATTCCCATCACTCTCTCAGC-3’ 14 65 137–152 R:5'-GTTCTCCATTGAACCAACTTCA-3’ 3 UWCA9 F:5’-CCTTCTCTGAATTTTTGTTGAAAGC-3’ 9 63.1 76–110 R:5’-GGACAGAAGTGAGTGACTGAGA-3’ 4 BM143 F:5’-ACCTGGGAAGCCTCCATATC-3’ 6 60.4 207–237 R:5'-CTGCAGGCAGATTCTTTATCG − 3' 5 BM1443 F:5'-AATAAAGAGACATGGTCACCGG − 3' 23 64 232–314 R:5'-TCGAGGTGTGGGAGGAAG − 3' 6 BM415 F: 5'-GCTACAGCCCTTCTGGTTTG − 3' 8 60.4 155–171 R:5’-GAGCTAATCACCAACAGCAAG-3’ 7 BM6425 F:5’-AGTTGAACCTGGGTCTCCTG-3’ 14 61.5 159–196 R:5’-TGCAATGGCAGTGAAAAAAG-3’ 8 BM103 F:5’-CTAGCTGCTGGCTACTTGGG-3’ 21 58 148–206 R:5’-GGCTGCTCTGGGCTATTG-3’ 9 BP7 F:5’-GACCTTTTCACTGCCCTCTG-3’ 6 60 294–305 R:5’-TTTATTTCTGAGTGTTTGGGGC-3’ 10 BMS1943 F:ATCAGTCGTTCCCAGAATGTC 9 56 93–131 R:TTGATATCCTCTCTGTCAAGCC STR detection A mixture of 990 µl HIDI and 10 µl Liz 500 was added to a 96-well reaction plate and centrifuged for 15 s at 10 µl and 1200 rpm per well; then, 1 µl of the amplified sample was added and centrifuged for 15 s at 1200 rpm after shaking. Denaturation was performed at 98℃ for 5 min, and the 96-well plate was immediately placed in an ice-water mixture and cooled rapidly. Capillary electrophoresis was performed with an ABI sequencer (3730XL). The GeneMapper software was used to analyze the STR data. The alleles were numbered A–V, according to fragment lengths. Genetic diversity analysis Multi-population descriptive statistics were conducted using PopGen32 software. The statistical genetic parameters included observed allele number (Na), effective allele number (Ne), Shannon index (I), expected heterozygosity (He), observed heterozygosity (Ho), and polymorphic information content (PIC). Variance analysis between STR variation and lactation performance SPSS 27.0 was used for multivariate variance analysis of the general linear model, and variance analysis of different genotypes and milk production traits was conducted. The general linear model was as follows: Y ij =u་G i ་e ij where Yij is the jth measured value of milk production traits of the ith genotype; U, population average; Gi, fixed effect of the ith genotype; and Eij, random residual effect. Results Detection of amplified products at different STR loci and results of capillary electrophoresis The PCR amplification products of 10 microsatellite loci were detected using 1% agarose gel electrophoresis (Fig. 1 ). The target bands were clear and bright, and the fragment sizes met our expectations. The PCR products were detected using capillary electrophoresis with the ABI3730 sequencer (Fig. 2 ). Allele fragment length and genotype frequency of different STR loci The sequencing results of STR loci were sorted and screened, and 108 alleles were observed at 10 STR loci. The highest number of alleles was detected at BM1443 (22 alleles) and the lowest numbers at BM143, BMS1943, BM302, and BP7 (5, 6, 7, and 7, respectively). The genotype individuals with 4 or more samples at each microsatellite locus were counted, but the genotype individuals with less than 4 samples were not counted (Table 2 ). Table 2 Allele number and genotype frequency of different microsatellite loci Number Microsatellite site Allele number and fragment length Genotype number and individual number 1 BM103 9 (A-148, B-150, C-152, D-153, E-155, F-157, G-159, H-161, I-206) 6 (AG−16, BG−32, CE−12, CG−28, EG−32, GG−24) 2 BM143 5 (A-208, B-209, C-214, D-218, E-237) 2 (AA−18, BB−144) 3 BM1443 22 (A-232,B-233, C-239, D-240, E-243, F-248, G-252, H-255, I-257, J-258, K-262, L-266, M-282, N-283, O-289, P-290, Q-291, R-297, S-300, T-302, U-306, V-314) 6 (CI−28, DI−36, GJ−16, JQ−28, JT−16, JV−16) 4 BM203 15 (A-213, B-217, C-218, D-220, E-222, F-223, G-225, H-226, I-228, J-229, K-230, L-231, M-232, N-233, O-234) 6 (BE−32, BH−39, BN−17, HN−32, MM−15, NN−17) 5 BM302 7 (A-137, B-139, C-140, D-142, E-144, F-146, G-152) 7 (CD−24, DD−30, DE−24, DF−15, DG−27, EE−12, EG−21) 6 BM415 13 (A-155, B-156, C-158, D-161, E-162, F-163, G-164, H-165, I-166, J-167, K-168, L-169, M-171) 5 (EG−40, EJ−35, FH−20, GG−35, GJ−20) 7 BM6425 11 (A-159, B-170, C-171, D-172, E-173, F-176, G-177, H-181, I-183, J-192, K-196) 7 (BF−24, BG−16, BI−20, DI−16, GG−24, GI−20, II−20) 8 BMS1943 6 (A-93, B-124, C-125, D-126, E-127, F-131) 5 (CE−30, CF−30, EE−36, EF−48, FF−12) 9 BP7 7 (A-294, B-297, C-299, D-300, E-301, F-302, G-305) 5 (AC−35, CE−25, CG−30, EE−30, EG−40) 10 UWCA9 13 (A-76, B-82, C-83, D-88, E-89, F-93, G-95, H-102, I-103, J-104, K-106, L-108, M-110) 7 (DD−18, DK−12, EE−21, EF−12, EJ−18, EK−33, EL−18) Genetic diversity analysis The Na, Ne, I, He, Ho, and PIC of each microsatellite locus calculated using PopGen32 software are listed in Table 3 . The average of Na was 10, and Ne was 3.11. The highest Ho (BM103) and lowest Ho (BM143) were 0.81 and 0.02, respectively. The highest He (BM103) and lowest He (BM143) were 0.78 and 0.12, respectively. The PIC ranged from 0.11 (BM143) to 0.74 (BM103); 2 loci, namely, BM143 and BM1443, were less than 0.5, which indicated that the polymorphism of these 10 microsatellite loci was relatively rich. The chi-square and G-square test results are shown in Table 4 . The results showed no significant differences between Ho and He of the 10 loci, except BM143, which is consistent with the Hardy–Weinberg equilibrium. Table 3 Statistical table of genetic parameters Microsatellite site Na Ne I He Ho PIC BM103 9.00 4.41 1.70 0.78 0.81 0.74 BM143 5.00 1.13 0.31 0.12 0.02 0.11 BM1443 22.00 1.56 1.05 0.36 0.39 0.36 BM203 15.00 4.16 1.56 0.77 0.79 0.72 BM302 7.00 3.46 1.44 0.72 0.72 0.67 BM415 13.00 3.43 1.43 0.71 0.76 0.66 BM6425 11.00 3.93 1.57 0.75 0.74 0.71 BMS1943 6.00 2.82 1.10 0.65 0.66 0.58 BP7 7.00 3.58 1.36 0.73 0.77 0.67 UWCA9 13.00 2.57 1.32 0.62 0.76 0.57 mean 10.00 3.11 1.28 0.62 0.64 0.58 Table 4 The Hardy–Weinberg equilibrium of microsatellite loci of the Holstein cows was tested using chi-square and G-square tests. Microsatellite site df Chi-square G-square Significance BM103 36 26.72 22.52 N BM143 10 345.03 *** 34.36 *** S BM1443 153 115.88 16.11 N BM203 28 72.68 *** 33.92 N BM302 15 13.91 17.38 N BM415 28 14.64 16.63 N BM6425 28 49.79 22.37 N BMS1943 6 3.19 3.29 N BP7 10 14.33 15.17 N UWCA9 36 70.35 41.79 N Note: df, degrees of freedom; s, significant. *P ≤ 0.05, **P ≤ 0.01, ***P ≤ 0.001. Association analysis of different STR loci genotypes with lactation traits Multivariate analysis of variance of the general linear model was conducted using SPSS 27.0. The results showed that, among the 10 microsatellite loci, 7 loci were related to lactation traits, whereas the other 3 loci, BM143, BM415, and BP7, had no correlation with lactation traits. Histograms of the differential analysis of lactation traits of individuals with different genotypes were created using GraphPad Prism 5 software. BM103 site The BM103 locus was correlated with the fat percentage of Holstein cows, but not milk yield, protein percentage, and lactose percentage (Table 5 ). A significant difference was observed between AG genotype and GG genotype at this locus (P < 0.05; Fig. 3 ), which indicates that allele A has a positive effect on fat percentage when compared with allele G. Table 5 Differences in the fat percentage of different genotypes of the Holstein cows at the BM103 locus Genotype Number of individuals Fat percentage, % AG 16 3.78 ± 0.11 a BG 32 3.59 ± 0.26 ab CE 12 3.55 ± 0.33 ab CG 28 3.62 ± 0.5 ab EG 32 3.6 ± 0.35 ab GG 24 3.25 ± 0.26 b Note: Expressions not listed in the table have no correlation with the trait at this locus. Different lowercase letters in the same column indicate significant differences (P 0.05). BM1443 site The BM1443 locus was correlated with lactose percentage, but not with the other traits (Table 6 ). A significant difference was observed between GJ and JQ genotypes at this locus (P < 0.05; Fig. 4), which indicates that allele G has a positive effect on lactose percentage when compared with allele Q. Table 6 Differences in the lactose percentage of different genotypes of the Holstein cows at the BM1443 locus Genotype Number of individuals Lactose percentage, % CI 28 5.15 ± 0.1 ab DI 36 5.12 ± 0.12 ab GJ 16 5.23 ± 0.15 a JQ 28 5.05 ± 0.16 b JT 16 5.22 ± 0.09 a JV 16 5.2 ± 0.12 ab Note: Expressions not listed in the table have no correlation with the trait at this locus. Different lowercase letters in the same column indicate significant differences (P 0.05). BM203 site The BM203 locus was correlated with lactose percentage (Table 7 ). A significant difference was found between BN and HN genotypes (P < 0.05) and between HN and MM genotypes (P < 0.05) at this locus (Fig. 5 ), which indicates that allele B has a positive effect on lactose percentage when compared with allele H and allele M also has a positive effect. Table 7 Differences in the lactose percentage of different genotypes of the Holstein cows at the BM203 locus Genotype Number of individuals Lactose percentage, % BE 32 5.15 ± 0.1 ab BH 39 5.12 ± 0.12 ab BN 17 5.23 ± 0.15 a HN 32 5.05 ± 0.16 b MM 15 5.22 ± 0.09 a NN 17 5.2 ± 0.12 ab Note: Expressions not listed in the table have no correlation with the trait at this locus. Different lowercase letters in the same column indicate significant differences (P 0.05). BM302 site The BM302 locus was related to milk yield, fat percentage, and protein percentage of the Holstein cows (Table 8 ). Significant differences were detected between EG genotype individuals and CD, DE, and EE genotype individuals (P < 0.05) and between DD and EE genotype individuals (P < 0.05) for milk yield. This shows that allele D has a positive effect and allele E has a negative effect on milk yield. Significant differences were found between individuals with CD, DE, and EE genotypes and individuals with EG genotypes (P < 0.05) for fat percentage, which indicates that G allele has a negative effect on fat percentage. Significant differences were observed between DE and EE genotype individuals and EG genotype individuals (P < 0.05) for protein percentage, which indicates that G allele has a negative effect. The histogram for the differential analysis of the milk yield of individuals with different genotypes is shown in Fig. 6 . The histogram for the differential analysis of fat percentage and protein percentage is shown in Fig. 7 . Table 8 Differences in the milk yield, fat percentage and protein percentage of different genotypes of the Holstein cows at the BM302 locus Genotype Number of individuals Milk yield, kg Fat percentage, % Protein percentage, % CD 24 31.85 ± 7.63 bc 3.74 ± 0.43 a 3.2 ± 0.11 ab DD 30 35.08 ± 3.77 ab 3.58 ± 0.4 ab 3.17 ± 0.16 ab DE 24 31.4 ± 4.15 bc 3.73 ± 0.27 a 3.27 ± 0.15 a DF 15 33.48 ± 5.65 abc 3.53 ± 0.23 ab 3.16 ± 0.07 ab DG 27 33.48 ± 6.33 abc 3.58 ± 0.41 ab 3.22 ± 0.12 ab EE 12 27.13 ± 7.28 c 3.91 ± 0.15 a 3.35 ± 0.32 a EG 21 38.24 ± 4.6 a 3.32 ± 0.2 b 3.09 ± 0.2 b Note: Expressions not listed in the table have no correlation with the trait at this locus. Different lowercase letters in the same column indicate significant differences (P 0.05). BM6425 site The BM6425 locus was related to fat percentage and protein percentage (Table 9 ). A significant difference in fat percentage was detected between DI genotype individuals (3.94%) and BJ genotype individuals (3.28%; P < 0.05), and a significant difference in protein percentage was found between BI genotype individuals and BF, BG, DI, GG, and GI genotype individuals (P < 0.05; Fig. 8 ). Table 9 Differences in the fat percentage and protein percentage of different genotypes of the Holstein cows at the BM6425 locus Genotype Number of individuals Fat percentage, % Protein percentage, % BF 24 3.58 ± 0.25 ab 3.15 ± 0.07 c BG 16 3.28 ± 0.4 b 3.16 ± 0.2 c BI 20 3.7 ± 0.63 ab 3.39 ± 0.23 a DI 16 3.94 ± 0.19 a 3.1 ± 0.1 c GG 24 3.52 ± 0.34 ab 3.15 ± 0.17 c GI 20 3.6 ± 0.3 ab 3.17 ± 0.2 bc II 20 3.78 ± 0.33 ab 3.29 ± 0.11 abc Note: Expressions not listed in the table have no correlation with the trait at this locus. Different lowercase letters in the same column indicate significant differences (P 0.05). BMS1943 site A correlation was found between the BMS1943 locus and lactose percentage (Table 10 ). A significant difference in lactose percentage was observed between EE and EF genotype individuals and FF genotype individuals (P < 0.05; Fig. 9 ), indicating that allele E has a positive effect and allele F has a negative effect on lactose percentage. Table 10 Differences in the lactose percentage of different genotypes of the Holstein cows at the BMS1943 locus Genotype Number of individuals Lactose percentage, % CE 30 5.15 ± 0.08 ab CF 30 5.15 ± 0.15 ab EE 36 5.17 ± 0.1 a EF 48 5.16 ± 0.1 a FF 12 5.03 ± 0.18 b Note: Expressions not listed in the table have no correlation with the trait at this locus. Different lowercase letters in the same column indicate significant differences (P 0.05). UWCA9 site The UWCA9 locus was related to milk yield (Table 11 ). A significant difference in milk yield was observed between DD genotype individuals and EK genotype individuals (P < 0.05; Fig. 10 ), which indicates that allele D has a positive effect on milk yield. Table 11 Differences in the milk yield of different genotypes of the Holstein cows at the UWCA9 locus Genotype Number of individuals Milk yield, kg DD 18 37.78 ± 4.91 a DK 12 34.73 ± 6.39 ab EE 21 33.13 ± 4.09 ab EF 12 31.53 ± 7.5 ab EJ 18 35.42 ± 4.79 ab EK 33 31.21 ± 5.56 b EL 18 33.27 ± 6.94 ab Note: Expressions not listed in the table have no correlation with the trait at this locus. Different lowercase letters in the same column indicate significant differences (P 0.05). Discussion Genetic parameter analysis Ho and He are the best indicators to measure the degree of genetic variation in a population (Wang et al. 2007). In Indian water buffaloes, Vani et al. (2022) found that Ho of the BM415 locus was 0.097, which is far lower than 0.76 in this study; this indicated that the polymorphism of dairy cows was abundant at this locus. In this study, the average Ho and He values were 0.64 and 0.62, respectively; the values are close to each other, indicating that the genotype distribution of the experimental population is close to equilibrium. In this study, the maximum and minimum Na values were 22 (BM1443 locus) and 5 (BM143), respectively, and the maximum and minimum Ne values were 4.41 (BM103) and 1.13 (BM143), respectively. The difference between Ne and Na was large, indicating that the distribution of alleles in some loci is uneven. In this study, 3 effective alleles were found at the UWCA9 locus, which is lower than the 5 reported by Vani et al (2022). When this study was compared with that by Vani et al. (2022), differences in Na were observed at the BM1443 locus (22 and 4, respectively). The differences in Na may be caused by the differences in the number of samples and change in components. PIC refers to the value of a marker used to detect polymorphism in a population. The value depends on the number of detected alleles and their frequency distribution (Nei, 1987), and it is calculated using PIC_CALC 0.6 software (Sambe, 2022). The results of this study showed that the 10 microsatellite loci have low to moderate polymorphism in Holstein dairy cattle, and the PIC ranged from 0.11 (BM143) to 0.74 (BM103). In the genetic analysis of a population, genetic markers with PIC value more than 0.5 are usually regarded as more informative (Botstein et al. 1980). The average PIC value of all loci in this study was 0.58, indicating that, overall, the polymorphism was abundant. Correlation analysis Vani et al. (2022) used 21 microsatellite loci of dairy cows to study the relationship with the lactation traits of buffalo. Among them, 3 microsatellite loci (BM1443, BM415, and BM143) were the same as those used in this study, but the results are inconsistent. Vani et al. (2022) found no significant correlation between the BM1443 locus and lactation performance of water buffalo (P > 0.05). In this study, the BM1443 locus was significantly correlated with lactose percentage (P < 0.05). The results for BM415 and BM143 loci were consistent with those of this study, with no significant correlation. Van Tassell et al. (2000) thought that BM415 and BP7 were significantly correlated with protein percentage, but these 2 loci were not correlated with protein percentage in this study. The results of correlation between the BM302 locus and lactation traits were consistent with those of Zhao et al. (2010), and this locus may be significantly correlated with milk yield, fat percentage, and protein percentage (P < 0.05). When the effects of UWCA9 on lactation traits were analyzed, the results of this study were inconsistent with those of Guo et al. (2007) but consistent with those of Vilkki et al. (1997). Guo et al. (2007) reported that UWCA9 has an influence on fat percentage and protein percentage, but we and Vilkki et al. (1997) found that UWCA9 has an influence on only milk yield and no correlation with other traits. In this study, the effects of BM103 and BM302 on fat percentage were consistent with the results of Ashwell et al. (1997). In addition, we found a new locus (BM302) significantly related to protein percentage and 3 loci (BM1443, BM302, and BMS1943) significantly related to lactose percentage. Conclusions The correlation analysis showed 3 loci (namely, BM143, BM415 and BP7) with no significant correlation with all lactation traits. Two other loci (namely, BM302 and UWCA9) were found to be related to milk yield, 3 loci (BM103, BM302, and BM6425) were related to fat percentage, 2 loci (BM302 and BM6425) were related to protein percentage, and 3 loci (BM1443, BM302, and BMS1943) were related to lactose percentage. However, the number of experimental animals was an important limiting factor. In the future, it will be necessary to increase the number of experimental cattle, sample size, and microsatellite markers and constantly track the correlation between microsatellite loci and milk production performance of Holstein cows, to obtain consistent microsatellite markers for screening excellent milk production traits of Holstein cows. Declarations STATEMENTS AND DECLARATIONS Funding The study was supported by the Region Youth Fundation of Xinjiang Uygur Autonomous in China (2021D01B85). Competing Interests The authors have no relevant financial or non-financial interests to disclose Author Contributions All authors contributed to the study conception and design. Material preparation, data collection and analysis were performed by Yongqing LI and Li LIU. The first draft of the manuscript was written by Yongqing LI and all authors commented on previous versions of the manuscript. All authors read and approved the final manuscript. Data Availability The datasets generated during and/or analysed during the current study are not publicly available due to [REASON(S) WHY DATA ARE NOT PUBLIC] but are available from the corresponding author on reasonable request. Ethics approval This study was performed in line with the principles of the Declaration of Helsinki. Approval was granted by the Care and Use of Laboratory Animals at Xinjiang Academy of Animal Science. Consent to participate Informed consent was obtained from the dairy farm owners in the study. Consent to publish The manuscript doesn’t contain any other individual person’s data in any form. References Williams, J. G., A. R. Kubelik, and K. J. Livak. 1990. DNA polymorphisms amplified by arbitrary primers are useful as genetic markers. Nucleic Acids Research. 18: 6531 – 6535. Takezaki‚N., and M. Nei. 1996. Genetic distance and reconstruction of phylogenetic trees from microsatellite DNA. Genetics. 144: 389 – 399༎ Yin, B. 2016. Screening of microsatellite markers for molecular genealogy identification of dairy cows and its correlation analysis with production performance. MS Thesis. Shandong Agricultural University, Taian. Dux, M., M. Muranowicz, E. Siadkowska, D. Robakowska-Hyżorek, K. Flisikowski, E. Bagnicka, and L. Zwierzchowski. 2018. Association of SNP and STR polymorphisms of insulin-like growth factor 2 receptor (IGF2R) gene with milk traits in Holstein-Friesian cows. Journal of Dairy Research. 85(2): 138 – 141. doi: 10.1017/S0022029918000110. Sokolova, O., I. 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Exploration of allelic variants in short tandem repeats (STRs) flanking milk production QTLs and their association with milk production traits in Indian water buffaloes. Tropical Animal Health and Production. 54(4): 222. doi: 10.1007/s11250-022-03215-6. Nei, M. 1987. Molecular evolutionary genetics. Pages in 506 in progress in Columbia University Press, New York (Etat-Unis). Botstein, D., R.L. White, M. Skolnick, and R.W. Davis. 1980. Construction of a genetic linkage map in man using restriction fragment length polymorphisms. American Journal of Human Genetics, 32 (3): 314. Van, T. P., M. S. Ashwell, and T. S. Sonstegard. 2000. Detection of putative loci affecting milk, health, and conformation traits in a US Holstein population using 105 microsatellite markers. Journal of Dairy Science. 83(8): 1865 – 72. doi: 10.3168/jds.S0022-0302(00)75058-2. Zhao, Z. S., J. G. Guo, and Z. B. Wang. 2010. Correlation between seven microsatellite markers and milk production traits of China holstein cows. Heilongjiang animal husbandry veterinarian. 19: 19 – 22. Guo, J. G. 2007. Microsatellite marker study on milk production traits of holstein cows. MS Thesis. Shihezi University, Shihezi. Vilkki, H. J., D. J. de Koning, and K. Elo. 1997. Multiple marker mapping of quantitative trait loci of Finnish dairy cattle by regression. Journal of Dairy Science. 80: 198 – 204. Ashwell, M. S., J. C. Rexroad, and R. H. Miller. 1997. Detection of loci affecting milk production and health traits in an elite US Holstein population using microsatellite markers. Animal Genetics. 28: 216 − 2 22. Cite Share Download PDF Status: Published Journal Publication published 15 Jun, 2023 Read the published version in Tropical Animal Health and Production → Version 1 posted Reviewers agreed at journal 14 Feb, 2023 Editor assigned by journal 07 Feb, 2023 First submitted to journal 06 Feb, 2023 You are reading this latest preprint version 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 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-2537800","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":176108940,"identity":"834cd64e-eced-4d27-811f-4a78f2631f6a","order_by":0,"name":"Yongqing 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2","display":"","copyAsset":false,"role":"figure","size":27097,"visible":true,"origin":"","legend":"\u003cp\u003eDetection of the BMS1493 site by using capillary electrophoresis\u003c/p\u003e","description":"","filename":"F2.png","url":"https://assets-eu.researchsquare.com/files/rs-2537800/v1/fcf7a1608094ffde0155a0ba.png"},{"id":33037978,"identity":"005097c0-690b-4264-881b-c784fc4c245e","added_by":"auto","created_at":"2023-02-16 15:08:41","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":278287,"visible":true,"origin":"","legend":"\u003cp\u003eAnalysis of differences in milk fat percentage of individuals with different genotypes at the BM103 locus\u003c/p\u003e","description":"","filename":"F3.png","url":"https://assets-eu.researchsquare.com/files/rs-2537800/v1/e559240c6b40b4a30f69ddee.png"},{"id":33037974,"identity":"b6920f2c-0e19-4c2a-97ea-02cce32bf38a","added_by":"auto","created_at":"2023-02-16 15:08:40","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":335852,"visible":true,"origin":"","legend":"\u003cp\u003eAnalysis of lactose percentage differences among individuals with different genotypes at the BM1443 locus\u003c/p\u003e","description":"","filename":"F4.png","url":"https://assets-eu.researchsquare.com/files/rs-2537800/v1/f259bbc68e7725bb4a039f1f.png"},{"id":33039051,"identity":"0ac3099a-70bc-4a95-9497-d669d56f9a49","added_by":"auto","created_at":"2023-02-16 15:16:40","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":347689,"visible":true,"origin":"","legend":"\u003cp\u003eAnalysis of lactose percentage differences among individuals with different genotypes at the BM203 locus\u003c/p\u003e","description":"","filename":"F5.png","url":"https://assets-eu.researchsquare.com/files/rs-2537800/v1/6e42d208d4045b526fe6e5bf.png"},{"id":33039050,"identity":"9a061547-6084-48b3-a6ca-aec1a1a81cc8","added_by":"auto","created_at":"2023-02-16 15:16:40","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":206734,"visible":true,"origin":"","legend":"\u003cp\u003eDifferential analysis of daily milk yield of different genotypes at the BM302 locus\u003c/p\u003e","description":"","filename":"F6.png","url":"https://assets-eu.researchsquare.com/files/rs-2537800/v1/ffd6887568e8d53986ab4016.png"},{"id":33037972,"identity":"4e3a17c7-c5fa-41fb-9000-06554bd72908","added_by":"auto","created_at":"2023-02-16 15:08:40","extension":"png","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":219886,"visible":true,"origin":"","legend":"\u003cp\u003eDifferential analysis of milk components of different genotypes at the BM302 locus\u003c/p\u003e","description":"","filename":"F7.png","url":"https://assets-eu.researchsquare.com/files/rs-2537800/v1/85615a54cee231cf851e55c9.png"},{"id":33037977,"identity":"a5c7362c-2f77-489a-b24c-38245476cec3","added_by":"auto","created_at":"2023-02-16 15:08:41","extension":"png","order_by":8,"title":"Figure 8","display":"","copyAsset":false,"role":"figure","size":218276,"visible":true,"origin":"","legend":"\u003cp\u003eDifferential analysis of milk components of different genotypes at the BM6425 locus\u003c/p\u003e","description":"","filename":"F8.png","url":"https://assets-eu.researchsquare.com/files/rs-2537800/v1/a88406f9e16db3bec66ca264.png"},{"id":33039762,"identity":"6b5f8197-b201-4a41-8035-d276dac38aa3","added_by":"auto","created_at":"2023-02-16 15:24:41","extension":"png","order_by":9,"title":"Figure 9","display":"","copyAsset":false,"role":"figure","size":272811,"visible":true,"origin":"","legend":"\u003cp\u003eDifferential analysis of lactose percentage of different genotypes at the BMS1943 locus\u003c/p\u003e","description":"","filename":"F9.png","url":"https://assets-eu.researchsquare.com/files/rs-2537800/v1/23a1f94fe1ab8a6c6842f270.png"},{"id":33039053,"identity":"5cd27c9c-78ea-40f3-b1b6-723621cde1d2","added_by":"auto","created_at":"2023-02-16 15:16:41","extension":"png","order_by":10,"title":"Figure 10","display":"","copyAsset":false,"role":"figure","size":328573,"visible":true,"origin":"","legend":"\u003cp\u003eAnalysis of milk yield differences of different genotypes at the UWCA9 locus\u003c/p\u003e","description":"","filename":"F10.png","url":"https://assets-eu.researchsquare.com/files/rs-2537800/v1/1bab7c1ff5fd1c50a436f1ca.png"},{"id":44731269,"identity":"82c97eb8-d48b-4ddd-a3e4-ee8ad6d6d32a","added_by":"auto","created_at":"2023-10-16 21:40:56","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":2642498,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-2537800/v1/b9576516-be31-413b-909b-8f9cafa0d791.pdf"}],"financialInterests":"","formattedTitle":"Analysis of the Relationship between Short Tandem Repeats and Lactation Performance of Xinjiang Holstein Cows","fulltext":[{"header":"Introduction","content":"\u003cp\u003eGenetic polymorphism, as the basis of animal evolution and development, is an important part of biodiversity and gene improvement (Williams et al. 1990). Microsatellite markers, also known as short tandem repeats (STRs) or simple sequence repeats (SSRs), are uniformly distributed in the genome of eukaryotes and composed of 1\u0026ndash;6 nucleotide tandem repeats, including single type, compound type, and interval type; microsatellite markers are used in marker-assisted selection to detect genetic polymorphism (Takezaki et al. 1996). Microsatellite loci have broad applications in pedigree tracing and gene improvement because of their co-dominant inheritance, rich polymorphism, conservative flanking sequences, and easy design of universal primers. Comprehensive studies performed worldwide have found that quantitative trait loci for milk yield, milk fat, and milk protein located using microsatellite markers in dairy cows are distributed on chromosomes 3, 6, 7, 8, 9, 10, 11, 14, 17, 18, 20, 21, 23, 25, 26, 27, and 28. Yin Bin et al. (2016) selected 8 microsatellite loci from the database of the International Society of Animal Genetics to analyze the relationship between their corresponding genotypes and production traits and obtain a molecular basis for early breeding of Holstein cows. In 2018, Polish scientist Dux discovered a microsatellite locus in the intron 23 region of insulin-like growth factor receptor 2 and significantly associated different genotypes of this locus with high milk yield, high milk fat percentage, and high milk protein level (Dux M et al. 2018). Recently, many studies have analyzed STRs and SSRs in plants and microorganisms, for example, genetic diversity of \u003cem\u003eVenturia inaequalis\u003c/em\u003e in Latvia (Sokolova et al. 2022), STR locus comparison of cherry germplasm in Europe (Ordidge et al. 2021), microsatellite loci related to drought tolerance traits in potato (Schumacher et al. 2021), apotheciate \u003cem\u003eUsnea florida\u003c/em\u003e (Degtjarenko et al. 2020), and resistance to scab in European triticale (Ollier et al. 2020). However, relatively few studies have analyzed STRs and SSRs in animals. In 2022, Griciuvien et al. (2022) used STRs to analyze genetic structure changes in the wild boar (\u003cem\u003eSus scrofa\u003c/em\u003e) in Lithuania, following an outbreak of African swine fever. In addition, STR site mining of the weevil (Apriyanto et al. 2021), great-billed seed-finch (de Melo et al. 2020), and copper butterfly (Trense et al. 2019) has been performed. Microsatellite technology has been used to analyze the genetic diversity and genetic bottleneck of buffalo (Ali et al. 2021), genetic identification of Zavot cattle (Boğa et al. 2022), identification of phenotype and genetic diversity of high-altitude yaks in Pakistan (Hameed et al. 2022), relationship between genetic diversity and phylogeny of cattle in Senegal (Sambe et al. 2022), relationship between genetic diversity and phylogeny of Siberian black-skinned cattle (Aitnazarov et al. 2021), genetic diversity of cattle in Kerala, India, and relationship between STR genetic diversity and quantitative trait variations of bull semen (Gororo et al. 2021). There has been limited research on the correlation between microsatellite loci and milk production traits of Holstein cows, and there are no reports on microsatellite locus analysis of Holstein cows in Xinjiang. In addition, the correlation analysis results between microsatellite loci and lactation performance obtained by previous researchers were compared, and the correlations between some established loci and traits were found to be inconsistent. To identify and confirm the correlation between microsatellite loci and lactation performance of Holstein cows in Xinjiang, in this study, 10 STR markers and milk production traits (milk yield, milk fat percentage, milk protein percentage, and lactose percentage) of Holstein cows were analyzed in a complete lactation period in Xinjiang. Our findings can be used for the protection and utilization of high-quality genetic resources of Holstein cows in Xinjiang and elimination of cows with relatively weak lactation performance.\u003c/p\u003e"},{"header":"Materials And Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eAnimal population\u003c/h2\u003e \u003cp\u003e According to the experimental design, a total of 175 Holstein cows with born in 2016, first birth, and calving in 2018 were selected as the experimental group in a large-scale dairy farm in northern Xinjiang.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003eCollection of phenotypic traits\u003c/h2\u003e \u003cp\u003eThe FOSS milk composition analyzer (Fossomatic 5000basic 75710), Foss Denmark Ltd., was used to measure 4 lactation-related traits: milk yield (kg), milk fat percentage, milk protein percentage, and lactose percentage. The traits were measured once a month for 10 consecutive months.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003eBlood collection and DNA extraction\u003c/h2\u003e \u003cp\u003eVenous blood (3\u0026ndash;4 ml) was collected from the tail root of the cattle in EDTA tubes, shaken well, transferred to 5 ml freezing tubes, and placed in a liquid nitrogen tank for storage. The whole-blood genome was extracted using a DNA extraction kit (Tiangen, DP304-02), and the DNA quality was detected with 0.75% agarose gel electrophoresis; DNA concentration and purity were detected using a spectrophotometer, and the DNA samples were stored at -20℃.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003eSelection and amplification of microsatellite loci\u003c/h2\u003e \u003cp\u003eAccording to the recommendation of the Food and Agriculture Organization of the United Nations (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://www.fao.org\u003c/span\u003e\u003cspan address=\"http://www.fao.org\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e) and Chu et al. (2003), 10 microsatellite loci closely adjacent to quantitative trait loci were selected as candidate loci (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). The primers were synthesized by Shanghai Shenggong Bioengineering Co., Ltd. The amplification volume was 25 \u0026micro;l: 2.5 \u0026micro;l of 10\u0026times; Taq buffer (with MgCl\u003csub\u003e2\u003c/sub\u003e), 0.5 \u0026micro;l of 10 \u0026micro;m DNTP (mix), 0.5 \u0026micro;l of 10 \u0026micro;mol/l forward and reverse primers, 0.2 \u0026micro;l of 5 U/\u0026micro;l Taq enzyme, and ddH\u003csub\u003e2\u003c/sub\u003eO (up to 25 \u0026micro;l). The optimized thermocycling conditions were as follows: initial denaturation at 95℃ for 5 min; 10 cycles of denaturation at 94℃ for 30 s, annealing at 60℃ for 30 s, and extension at 72℃ for 30 s; 30 cycles of denaturation at 94℃ for 30 s, annealing at 55℃ for 30 s, and extension at 72℃ for 30 s; and preservation at 4℃.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eMicrosatellite sites and primer information\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNumber\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMicrosatellite site\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003ePrimer sequence, 5\u0026prime;-3\u0026prime;\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eChromosome\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eAnnealing temperature, ℃\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eSize, bp\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eBM203\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eF:5\u0026rsquo;-GGGTGTGACATTTTGTTCCC-3\u0026rsquo;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e27\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e61\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e217\u0026ndash;234\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eR:5'-CTGCTCGCCACTAGTCCTTC-3\u0026rsquo;\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eBM302\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eF:5'-GAATTCCCATCACTCTCTCAGC-3\u0026rsquo;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e65\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e137\u0026ndash;152\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eR:5'-GTTCTCCATTGAACCAACTTCA-3\u0026rsquo;\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eUWCA9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eF:5\u0026rsquo;-CCTTCTCTGAATTTTTGTTGAAAGC-3\u0026rsquo;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e63.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e76\u0026ndash;110\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eR:5\u0026rsquo;-GGACAGAAGTGAGTGACTGAGA-3\u0026rsquo;\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eBM143\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eF:5\u0026rsquo;-ACCTGGGAAGCCTCCATATC-3\u0026rsquo;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e60.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e207\u0026ndash;237\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eR:5'-CTGCAGGCAGATTCTTTATCG \u0026minus;\u0026thinsp;3'\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eBM1443\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eF:5'-AATAAAGAGACATGGTCACCGG \u0026minus;\u0026thinsp;3'\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e64\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e232\u0026ndash;314\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eR:5'-TCGAGGTGTGGGAGGAAG \u0026minus;\u0026thinsp;3'\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eBM415\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eF: 5'-GCTACAGCCCTTCTGGTTTG \u0026minus;\u0026thinsp;3'\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e60.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e155\u0026ndash;171\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eR:5\u0026rsquo;-GAGCTAATCACCAACAGCAAG-3\u0026rsquo;\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eBM6425\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eF:5\u0026rsquo;-AGTTGAACCTGGGTCTCCTG-3\u0026rsquo;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e61.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e159\u0026ndash;196\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eR:5\u0026rsquo;-TGCAATGGCAGTGAAAAAAG-3\u0026rsquo;\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eBM103\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eF:5\u0026rsquo;-CTAGCTGCTGGCTACTTGGG-3\u0026rsquo;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e58\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e148\u0026ndash;206\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eR:5\u0026rsquo;-GGCTGCTCTGGGCTATTG-3\u0026rsquo;\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eBP7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eF:5\u0026rsquo;-GACCTTTTCACTGCCCTCTG-3\u0026rsquo;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e60\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e294\u0026ndash;305\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eR:5\u0026rsquo;-TTTATTTCTGAGTGTTTGGGGC-3\u0026rsquo;\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eBMS1943\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eF:ATCAGTCGTTCCCAGAATGTC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e56\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e93\u0026ndash;131\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eR:TTGATATCCTCTCTGTCAAGCC\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003eSTR detection\u003c/h2\u003e \u003cp\u003eA mixture of 990 \u0026micro;l HIDI and 10 \u0026micro;l Liz 500 was added to a 96-well reaction plate and centrifuged for 15 s at 10 \u0026micro;l and 1200 rpm per well; then, 1 \u0026micro;l of the amplified sample was added and centrifuged for 15 s at 1200 rpm after shaking. Denaturation was performed at 98℃ for 5 min, and the 96-well plate was immediately placed in an ice-water mixture and cooled rapidly. Capillary electrophoresis was performed with an ABI sequencer (3730XL). The GeneMapper software was used to analyze the STR data. The alleles were numbered A\u0026ndash;V, according to fragment lengths.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eGenetic diversity analysis\u003c/h2\u003e \u003cp\u003eMulti-population descriptive statistics were conducted using PopGen32 software. The statistical genetic parameters included observed allele number (Na), effective allele number (Ne), Shannon index (I), expected heterozygosity (He), observed heterozygosity (Ho), and polymorphic information content (PIC).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003eVariance analysis between STR variation and lactation performance\u003c/h2\u003e \u003cp\u003eSPSS 27.0 was used for multivariate variance analysis of the general linear model, and variance analysis of different genotypes and milk production traits was conducted. The general linear model was as follows:\u003c/p\u003e \u003cp\u003eY\u003csub\u003eij\u003c/sub\u003e=u་G\u003csub\u003ei\u003c/sub\u003e་e\u003csub\u003eij\u003c/sub\u003e\u003c/p\u003e \u003cp\u003ewhere Yij is the jth measured value of milk production traits of the ith genotype; U, population average; Gi, fixed effect of the ith genotype; and Eij, random residual effect.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eDetection of amplified products at different STR loci and results of capillary electrophoresis\u003c/h2\u003e \u003cp\u003eThe PCR amplification products of 10 microsatellite loci were detected using 1% agarose gel electrophoresis (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e1\u003c/span\u003e). The target bands were clear and bright, and the fragment sizes met our expectations. The PCR products were detected using capillary electrophoresis with the ABI3730 sequencer (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003eAllele fragment length and genotype frequency of different STR loci\u003c/h2\u003e \u003cp\u003eThe sequencing results of STR loci were sorted and screened, and 108 alleles were observed at 10 STR loci. The highest number of alleles was detected at BM1443 (22 alleles) and the lowest numbers at BM143, BMS1943, BM302, and BP7 (5, 6, 7, and 7, respectively). The genotype individuals with 4 or more samples at each microsatellite locus were counted, but the genotype individuals with less than 4 samples were not counted (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eAllele number and genotype frequency of different microsatellite loci\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNumber\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMicrosatellite site\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eAllele number and fragment length\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eGenotype number and individual number\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBM103\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e9\u003c/b\u003e(A-148, B-150, C-152, D-153, E-155, F-157, G-159, H-161, I-206)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e6\u003c/b\u003e(AG\u0026minus;16, BG\u0026minus;32, CE\u0026minus;12, CG\u0026minus;28, EG\u0026minus;32, GG\u0026minus;24)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBM143\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e5\u003c/b\u003e(A-208, B-209, C-214, D-218, E-237)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e2\u003c/b\u003e(AA\u0026minus;18, BB\u0026minus;144)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBM1443\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e22\u003c/b\u003e(A-232,B-233, C-239, D-240, E-243, F-248, G-252, H-255, I-257, J-258, K-262, L-266, M-282, N-283, O-289, P-290, Q-291, R-297, S-300, T-302, U-306, V-314)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e6\u003c/b\u003e(CI\u0026minus;28, DI\u0026minus;36, GJ\u0026minus;16, JQ\u0026minus;28, JT\u0026minus;16, JV\u0026minus;16)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBM203\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e15\u003c/b\u003e(A-213, B-217, C-218, D-220, E-222, F-223, G-225, H-226, I-228, J-229, K-230, L-231, M-232, N-233, O-234)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e6\u003c/b\u003e(BE\u0026minus;32, BH\u0026minus;39, BN\u0026minus;17, HN\u0026minus;32, MM\u0026minus;15, NN\u0026minus;17)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBM302\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e7\u003c/b\u003e(A-137, B-139, C-140, D-142, E-144, F-146, G-152)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e7\u003c/b\u003e(CD\u0026minus;24, DD\u0026minus;30, DE\u0026minus;24, DF\u0026minus;15, DG\u0026minus;27, EE\u0026minus;12, EG\u0026minus;21)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBM415\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e13\u003c/b\u003e(A-155, B-156, C-158, D-161, E-162, F-163, G-164, H-165, I-166, J-167, K-168, L-169, M-171)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e5\u003c/b\u003e(EG\u0026minus;40, EJ\u0026minus;35, FH\u0026minus;20, GG\u0026minus;35, GJ\u0026minus;20)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBM6425\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e11\u003c/b\u003e(A-159, B-170, C-171, D-172, E-173, F-176, G-177, H-181, I-183, J-192, K-196)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e7\u003c/b\u003e(BF\u0026minus;24, BG\u0026minus;16, BI\u0026minus;20, DI\u0026minus;16, GG\u0026minus;24, GI\u0026minus;20, II\u0026minus;20)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBMS1943\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e6\u003c/b\u003e(A-93, B-124, C-125, D-126, E-127, F-131)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e5\u003c/b\u003e(CE\u0026minus;30, CF\u0026minus;30, EE\u0026minus;36, EF\u0026minus;48, FF\u0026minus;12)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBP7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e7\u003c/b\u003e(A-294, B-297, C-299, D-300, E-301, F-302, G-305)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e5\u003c/b\u003e(AC\u0026minus;35, CE\u0026minus;25, CG\u0026minus;30, EE\u0026minus;30, EG\u0026minus;40)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eUWCA9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e13\u003c/b\u003e(A-76, B-82, C-83, D-88, E-89, F-93, G-95, H-102, I-103, J-104, K-106, L-108, M-110)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e7\u003c/b\u003e(DD\u0026minus;18, DK\u0026minus;12, EE\u0026minus;21, EF\u0026minus;12, EJ\u0026minus;18, EK\u0026minus;33, EL\u0026minus;18)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003eGenetic diversity analysis\u003c/h2\u003e \u003cp\u003eThe Na, Ne, I, He, Ho, and PIC of each microsatellite locus calculated using PopGen32 software are listed in Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e. The average of Na was 10, and Ne was 3.11. The highest Ho (BM103) and lowest Ho (BM143) were 0.81 and 0.02, respectively. The highest He (BM103) and lowest He (BM143) were 0.78 and 0.12, respectively. The PIC ranged from 0.11 (BM143) to 0.74 (BM103); 2 loci, namely, BM143 and BM1443, were less than 0.5, which indicated that the polymorphism of these 10 microsatellite loci was relatively rich. The chi-square and G-square test results are shown in Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e. The results showed no significant differences between Ho and He of the 10 loci, except BM143, which is consistent with the Hardy\u0026ndash;Weinberg equilibrium.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eStatistical table of genetic parameters\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMicrosatellite site\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNa\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNe\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eI\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eHe\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eHo\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003ePIC\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBM103\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e9.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e4.41\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.70\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.78\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.81\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.74\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBM143\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e5.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.31\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.11\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBM1443\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e22.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.56\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.36\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.39\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.36\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBM203\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e15.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e4.16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.56\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.77\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.79\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.72\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBM302\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e7.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e3.46\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.44\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.72\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.72\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.67\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBM415\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e13.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e3.43\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.43\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.71\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.76\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.66\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBM6425\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e11.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e3.93\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.57\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.75\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.74\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.71\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBMS1943\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e6.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2.82\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.65\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.66\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.58\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBP7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e7.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e3.58\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.36\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.73\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.77\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.67\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUWCA9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e13.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2.57\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.32\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.62\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.76\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.57\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003emean\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e10.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e3.11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.62\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.64\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.58\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eThe Hardy\u0026ndash;Weinberg equilibrium of microsatellite loci of the Holstein cows was tested using chi-square and G-square tests.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMicrosatellite site\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003edf\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eChi-square\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eG-square\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eSignificance\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBM103\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e36\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e26.72\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e22.52\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eN\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBM143\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e345.03 ***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e34.36 ***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eS\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBM1443\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e153\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e115.88\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e16.11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eN\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBM203\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e72.68 ***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e33.92\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eN\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBM302\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e13.91\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e17.38\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eN\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBM415\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e14.64\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e16.63\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eN\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBM6425\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e49.79\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e22.37\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eN\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBMS1943\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e3.19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e3.29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eN\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBP7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e14.33\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e15.17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eN\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUWCA9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e36\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e70.35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e41.79\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eN\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"5\"\u003eNote: df, degrees of freedom; s, significant. *P\u0026thinsp;\u0026le;\u0026thinsp;0.05, **P\u0026thinsp;\u0026le;\u0026thinsp;0.01, ***P\u0026thinsp;\u0026le;\u0026thinsp;0.001.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003eAssociation analysis of different STR loci genotypes with lactation traits\u003c/h2\u003e \u003cp\u003eMultivariate analysis of variance of the general linear model was conducted using SPSS 27.0. The results showed that, among the 10 microsatellite loci, 7 loci were related to lactation traits, whereas the other 3 loci, BM143, BM415, and BP7, had no correlation with lactation traits. Histograms of the differential analysis of lactation traits of individuals with different genotypes were created using GraphPad Prism 5 software.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec15\" class=\"Section2\"\u003e \u003ch2\u003eBM103 site\u003c/h2\u003e \u003cp\u003eThe BM103 locus was correlated with the fat percentage of Holstein cows, but not milk yield, protein percentage, and lactose percentage (Table\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e). A significant difference was observed between AG genotype and GG genotype at this locus (P\u0026thinsp;\u0026lt;\u0026thinsp;0.05; Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e3\u003c/span\u003e), which indicates that allele A has a positive effect on fat percentage when compared with allele G.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab5\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 5\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eDifferences in the fat percentage of different genotypes of the Holstein cows at the BM103 locus\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"3\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGenotype\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNumber of individuals\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eFat percentage, %\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAG\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3.78\u0026thinsp;\u0026plusmn;\u0026thinsp;0.11\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBG\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e32\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3.59\u0026thinsp;\u0026plusmn;\u0026thinsp;0.26\u003csup\u003eab\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCE\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3.55\u0026thinsp;\u0026plusmn;\u0026thinsp;0.33\u003csup\u003eab\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCG\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3.62\u0026thinsp;\u0026plusmn;\u0026thinsp;0.5\u003csup\u003eab\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEG\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e32\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3.6\u0026thinsp;\u0026plusmn;\u0026thinsp;0.35\u003csup\u003eab\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGG\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3.25\u0026thinsp;\u0026plusmn;\u0026thinsp;0.26\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"3\"\u003eNote: Expressions not listed in the table have no correlation with the trait at this locus. Different lowercase letters in the same column indicate significant differences (P\u0026thinsp;\u0026lt;\u0026thinsp;0.05). The same letter or no letter indicates no significant difference (P\u0026thinsp;\u0026gt;\u0026thinsp;0.05).\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec16\" class=\"Section2\"\u003e \u003ch2\u003eBM1443 site\u003c/h2\u003e \u003cp\u003eThe BM1443 locus was correlated with lactose percentage, but not with the other traits (Table\u0026nbsp;\u003cspan refid=\"Tab6\" class=\"InternalRef\"\u003e6\u003c/span\u003e). A significant difference was observed between GJ and JQ genotypes at this locus (P\u0026thinsp;\u0026lt;\u0026thinsp;0.05; Fig.\u0026nbsp;4), which indicates that allele G has a positive effect on lactose percentage when compared with allele Q.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab6\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 6\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eDifferences in the lactose percentage of different genotypes of the Holstein cows at the BM1443 locus\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"3\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGenotype\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNumber of individuals\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eLactose percentage, %\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5.15\u0026thinsp;\u0026plusmn;\u0026thinsp;0.1\u003csup\u003eab\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e36\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5.12\u0026thinsp;\u0026plusmn;\u0026thinsp;0.12\u003csup\u003eab\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGJ\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5.23\u0026thinsp;\u0026plusmn;\u0026thinsp;0.15\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eJQ\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5.05\u0026thinsp;\u0026plusmn;\u0026thinsp;0.16\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eJT\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5.22\u0026thinsp;\u0026plusmn;\u0026thinsp;0.09\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eJV\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5.2\u0026thinsp;\u0026plusmn;\u0026thinsp;0.12\u003csup\u003eab\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"3\"\u003eNote: Expressions not listed in the table have no correlation with the trait at this locus. Different lowercase letters in the same column indicate significant differences (P\u0026thinsp;\u0026lt;\u0026thinsp;0.05). The same letter or no letter indicates no significant difference (P\u0026thinsp;\u0026gt;\u0026thinsp;0.05).\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec17\" class=\"Section2\"\u003e \u003ch2\u003eBM203 site\u003c/h2\u003e \u003cp\u003eThe BM203 locus was correlated with lactose percentage (Table\u0026nbsp;\u003cspan refid=\"Tab7\" class=\"InternalRef\"\u003e7\u003c/span\u003e). A significant difference was found between BN and HN genotypes (P\u0026thinsp;\u0026lt;\u0026thinsp;0.05) and between HN and MM genotypes (P\u0026thinsp;\u0026lt;\u0026thinsp;0.05) at this locus (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e5\u003c/span\u003e), which indicates that allele B has a positive effect on lactose percentage when compared with allele H and allele M also has a positive effect.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab7\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 7\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eDifferences in the lactose percentage of different genotypes of the Holstein cows at the BM203 locus\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"3\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGenotype\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNumber of individuals\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eLactose percentage, %\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBE\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e32\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5.15\u0026thinsp;\u0026plusmn;\u0026thinsp;0.1\u003csup\u003eab\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBH\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e39\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5.12\u0026thinsp;\u0026plusmn;\u0026thinsp;0.12\u003csup\u003eab\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBN\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5.23\u0026thinsp;\u0026plusmn;\u0026thinsp;0.15\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHN\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e32\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5.05\u0026thinsp;\u0026plusmn;\u0026thinsp;0.16\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMM\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5.22\u0026thinsp;\u0026plusmn;\u0026thinsp;0.09\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNN\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5.2\u0026thinsp;\u0026plusmn;\u0026thinsp;0.12\u003csup\u003eab\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"3\"\u003eNote: Expressions not listed in the table have no correlation with the trait at this locus. Different lowercase letters in the same column indicate significant differences (P\u0026thinsp;\u0026lt;\u0026thinsp;0.05). The same letter or no letter indicates no significant difference (P\u0026thinsp;\u0026gt;\u0026thinsp;0.05).\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec18\" class=\"Section2\"\u003e \u003ch2\u003eBM302 site\u003c/h2\u003e \u003cp\u003eThe BM302 locus was related to milk yield, fat percentage, and protein percentage of the Holstein cows (Table\u0026nbsp;\u003cspan refid=\"Tab8\" class=\"InternalRef\"\u003e8\u003c/span\u003e). Significant differences were detected between EG genotype individuals and CD, DE, and EE genotype individuals (P\u0026thinsp;\u0026lt;\u0026thinsp;0.05) and between DD and EE genotype individuals (P\u0026thinsp;\u0026lt;\u0026thinsp;0.05) for milk yield. This shows that allele D has a positive effect and allele E has a negative effect on milk yield. Significant differences were found between individuals with CD, DE, and EE genotypes and individuals with EG genotypes (P\u0026thinsp;\u0026lt;\u0026thinsp;0.05) for fat percentage, which indicates that G allele has a negative effect on fat percentage. Significant differences were observed between DE and EE genotype individuals and EG genotype individuals (P\u0026thinsp;\u0026lt;\u0026thinsp;0.05) for protein percentage, which indicates that G allele has a negative effect. The histogram for the differential analysis of the milk yield of individuals with different genotypes is shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e6\u003c/span\u003e. The histogram for the differential analysis of fat percentage and protein percentage is shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig9\" class=\"InternalRef\"\u003e7\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab8\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 8\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eDifferences in the milk yield, fat percentage and protein percentage of different genotypes of the Holstein cows at the BM302 locus\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGenotype\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNumber of individuals\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMilk yield, kg\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eFat percentage,\u003c/p\u003e \u003cp\u003e%\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eProtein percentage,\u003c/p\u003e \u003cp\u003e%\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e31.85\u0026thinsp;\u0026plusmn;\u0026thinsp;7.63\u003csup\u003ebc\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3.74\u0026thinsp;\u0026plusmn;\u0026thinsp;0.43\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3.2\u0026thinsp;\u0026plusmn;\u0026thinsp;0.11\u003csup\u003eab\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e35.08\u0026thinsp;\u0026plusmn;\u0026thinsp;3.77\u003csup\u003eab\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3.58\u0026thinsp;\u0026plusmn;\u0026thinsp;0.4\u003csup\u003eab\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3.17\u0026thinsp;\u0026plusmn;\u0026thinsp;0.16\u003csup\u003eab\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDE\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e31.4\u0026thinsp;\u0026plusmn;\u0026thinsp;4.15\u003csup\u003ebc\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3.73\u0026thinsp;\u0026plusmn;\u0026thinsp;0.27\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3.27\u0026thinsp;\u0026plusmn;\u0026thinsp;0.15\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDF\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e33.48\u0026thinsp;\u0026plusmn;\u0026thinsp;5.65\u003csup\u003eabc\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3.53\u0026thinsp;\u0026plusmn;\u0026thinsp;0.23\u003csup\u003eab\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3.16\u0026thinsp;\u0026plusmn;\u0026thinsp;0.07\u003csup\u003eab\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDG\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e27\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e33.48\u0026thinsp;\u0026plusmn;\u0026thinsp;6.33\u003csup\u003eabc\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3.58\u0026thinsp;\u0026plusmn;\u0026thinsp;0.41\u003csup\u003eab\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3.22\u0026thinsp;\u0026plusmn;\u0026thinsp;0.12\u003csup\u003eab\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEE\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e27.13\u0026thinsp;\u0026plusmn;\u0026thinsp;7.28\u003csup\u003ec\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3.91\u0026thinsp;\u0026plusmn;\u0026thinsp;0.15\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3.35\u0026thinsp;\u0026plusmn;\u0026thinsp;0.32\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEG\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e38.24\u0026thinsp;\u0026plusmn;\u0026thinsp;4.6\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3.32\u0026thinsp;\u0026plusmn;\u0026thinsp;0.2\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3.09\u0026thinsp;\u0026plusmn;\u0026thinsp;0.2\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"5\"\u003eNote: Expressions not listed in the table have no correlation with the trait at this locus. Different lowercase letters in the same column indicate significant differences (P\u0026thinsp;\u0026lt;\u0026thinsp;0.05). The same letter or no letter indicates no significant difference (P\u0026thinsp;\u0026gt;\u0026thinsp;0.05).\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec19\" class=\"Section2\"\u003e \u003ch2\u003eBM6425 site\u003c/h2\u003e \u003cp\u003eThe BM6425 locus was related to fat percentage and protein percentage (Table\u0026nbsp;\u003cspan refid=\"Tab9\" class=\"InternalRef\"\u003e9\u003c/span\u003e). A significant difference in fat percentage was detected between DI genotype individuals (3.94%) and BJ genotype individuals (3.28%; P\u0026thinsp;\u0026lt;\u0026thinsp;0.05), and a significant difference in protein percentage was found between BI genotype individuals and BF, BG, DI, GG, and GI genotype individuals (P\u0026thinsp;\u0026lt;\u0026thinsp;0.05; Fig.\u0026nbsp;\u003cspan refid=\"Fig11\" class=\"InternalRef\"\u003e8\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab9\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 9\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eDifferences in the fat percentage and protein percentage of different genotypes of the Holstein cows at the BM6425 locus\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGenotype\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNumber of individuals\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eFat percentage, %\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eProtein percentage, %\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBF\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3.58\u0026thinsp;\u0026plusmn;\u0026thinsp;0.25\u003csup\u003eab\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3.15\u0026thinsp;\u0026plusmn;\u0026thinsp;0.07\u003csup\u003ec\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBG\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3.28\u0026thinsp;\u0026plusmn;\u0026thinsp;0.4\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3.16\u0026thinsp;\u0026plusmn;\u0026thinsp;0.2\u003csup\u003ec\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3.7\u0026thinsp;\u0026plusmn;\u0026thinsp;0.63\u003csup\u003eab\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3.39\u0026thinsp;\u0026plusmn;\u0026thinsp;0.23\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3.94\u0026thinsp;\u0026plusmn;\u0026thinsp;0.19\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3.1\u0026thinsp;\u0026plusmn;\u0026thinsp;0.1\u003csup\u003ec\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGG\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3.52\u0026thinsp;\u0026plusmn;\u0026thinsp;0.34\u003csup\u003eab\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3.15\u0026thinsp;\u0026plusmn;\u0026thinsp;0.17\u003csup\u003ec\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3.6\u0026thinsp;\u0026plusmn;\u0026thinsp;0.3\u003csup\u003eab\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3.17\u0026thinsp;\u0026plusmn;\u0026thinsp;0.2\u003csup\u003ebc\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eII\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3.78\u0026thinsp;\u0026plusmn;\u0026thinsp;0.33\u003csup\u003eab\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3.29\u0026thinsp;\u0026plusmn;\u0026thinsp;0.11\u003csup\u003eabc\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"4\"\u003eNote: Expressions not listed in the table have no correlation with the trait at this locus. Different lowercase letters in the same column indicate significant differences (P\u0026thinsp;\u0026lt;\u0026thinsp;0.05). The same letter or no letter indicates no significant difference (P\u0026thinsp;\u0026gt;\u0026thinsp;0.05).\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec20\" class=\"Section2\"\u003e \u003ch2\u003eBMS1943 site\u003c/h2\u003e \u003cp\u003eA correlation was found between the BMS1943 locus and lactose percentage (Table\u0026nbsp;\u003cspan refid=\"Tab10\" class=\"InternalRef\"\u003e10\u003c/span\u003e). A significant difference in lactose percentage was observed between EE and EF genotype individuals and FF genotype individuals (P\u0026thinsp;\u0026lt;\u0026thinsp;0.05; Fig.\u0026nbsp;\u003cspan refid=\"Fig12\" class=\"InternalRef\"\u003e9\u003c/span\u003e), indicating that allele E has a positive effect and allele F has a negative effect on lactose percentage.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab10\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 10\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eDifferences in the lactose percentage of different genotypes of the Holstein cows at the BMS1943 locus\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"3\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGenotype\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNumber of individuals\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eLactose percentage, %\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCE\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5.15\u0026thinsp;\u0026plusmn;\u0026thinsp;0.08\u003csup\u003eab\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCF\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5.15\u0026thinsp;\u0026plusmn;\u0026thinsp;0.15\u003csup\u003eab\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEE\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e36\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5.17\u0026thinsp;\u0026plusmn;\u0026thinsp;0.1\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEF\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e48\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5.16\u0026thinsp;\u0026plusmn;\u0026thinsp;0.1\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFF\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5.03\u0026thinsp;\u0026plusmn;\u0026thinsp;0.18\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"3\"\u003eNote: Expressions not listed in the table have no correlation with the trait at this locus. Different lowercase letters in the same column indicate significant differences (P\u0026thinsp;\u0026lt;\u0026thinsp;0.05). The same letter or no letter indicates no significant difference (P\u0026thinsp;\u0026gt;\u0026thinsp;0.05).\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec21\" class=\"Section2\"\u003e \u003ch2\u003eUWCA9 site\u003c/h2\u003e \u003cp\u003eThe UWCA9 locus was related to milk yield (Table\u0026nbsp;\u003cspan refid=\"Tab11\" class=\"InternalRef\"\u003e11\u003c/span\u003e). A significant difference in milk yield was observed between DD genotype individuals and EK genotype individuals (P\u0026thinsp;\u0026lt;\u0026thinsp;0.05; Fig.\u0026nbsp;\u003cspan refid=\"Fig13\" class=\"InternalRef\"\u003e10\u003c/span\u003e), which indicates that allele D has a positive effect on milk yield.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab11\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 11\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eDifferences in the milk yield of different genotypes of the Holstein cows at the UWCA9 locus\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"3\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGenotype\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNumber of individuals\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMilk yield, kg\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e37.78\u0026thinsp;\u0026plusmn;\u0026thinsp;4.91\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDK\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e34.73\u0026thinsp;\u0026plusmn;\u0026thinsp;6.39\u003csup\u003eab\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEE\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e33.13\u0026thinsp;\u0026plusmn;\u0026thinsp;4.09\u003csup\u003eab\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEF\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e31.53\u0026thinsp;\u0026plusmn;\u0026thinsp;7.5\u003csup\u003eab\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEJ\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e35.42\u0026thinsp;\u0026plusmn;\u0026thinsp;4.79\u003csup\u003eab\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEK\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e33\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e31.21\u0026thinsp;\u0026plusmn;\u0026thinsp;5.56\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEL\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e33.27\u0026thinsp;\u0026plusmn;\u0026thinsp;6.94\u003csup\u003eab\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"3\"\u003eNote: Expressions not listed in the table have no correlation with the trait at this locus. Different lowercase letters in the same column indicate significant differences (P\u0026thinsp;\u0026lt;\u0026thinsp;0.05). The same letter or no letter indicates no significant difference (P\u0026thinsp;\u0026gt;\u0026thinsp;0.05).\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"Discussion","content":"\u003cdiv id=\"Sec23\" class=\"Section2\"\u003e \u003ch2\u003eGenetic parameter analysis\u003c/h2\u003e \u003cp\u003eHo and He are the best indicators to measure the degree of genetic variation in a population (Wang et al. 2007). In Indian water buffaloes, Vani et al. (2022) found that Ho of the BM415 locus was 0.097, which is far lower than 0.76 in this study; this indicated that the polymorphism of dairy cows was abundant at this locus. In this study, the average Ho and He values were 0.64 and 0.62, respectively; the values are close to each other, indicating that the genotype distribution of the experimental population is close to equilibrium. In this study, the maximum and minimum Na values were 22 (BM1443 locus) and 5 (BM143), respectively, and the maximum and minimum Ne values were 4.41 (BM103) and 1.13 (BM143), respectively. The difference between Ne and Na was large, indicating that the distribution of alleles in some loci is uneven. In this study, 3 effective alleles were found at the UWCA9 locus, which is lower than the 5 reported by Vani et al (2022). When this study was compared with that by Vani et al. (2022), differences in Na were observed at the BM1443 locus (22 and 4, respectively). The differences in Na may be caused by the differences in the number of samples and change in components.\u003c/p\u003e \u003cp\u003ePIC refers to the value of a marker used to detect polymorphism in a population. The value depends on the number of detected alleles and their frequency distribution (Nei, 1987), and it is calculated using PIC_CALC 0.6 software (Sambe, 2022). The results of this study showed that the 10 microsatellite loci have low to moderate polymorphism in Holstein dairy cattle, and the PIC ranged from 0.11 (BM143) to 0.74 (BM103). In the genetic analysis of a population, genetic markers with PIC value more than 0.5 are usually regarded as more informative (Botstein et al. 1980). The average PIC value of all loci in this study was 0.58, indicating that, overall, the polymorphism was abundant.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec24\" class=\"Section2\"\u003e \u003ch2\u003eCorrelation analysis\u003c/h2\u003e \u003cp\u003eVani et al. (2022) used 21 microsatellite loci of dairy cows to study the relationship with the lactation traits of buffalo. Among them, 3 microsatellite loci (BM1443, BM415, and BM143) were the same as those used in this study, but the results are inconsistent. Vani et al. (2022) found no significant correlation between the BM1443 locus and lactation performance of water buffalo (P\u0026thinsp;\u0026gt;\u0026thinsp;0.05). In this study, the BM1443 locus was significantly correlated with lactose percentage (P\u0026thinsp;\u0026lt;\u0026thinsp;0.05). The results for BM415 and BM143 loci were consistent with those of this study, with no significant correlation. Van Tassell et al. (2000) thought that BM415 and BP7 were significantly correlated with protein percentage, but these 2 loci were not correlated with protein percentage in this study. The results of correlation between the BM302 locus and lactation traits were consistent with those of Zhao et al. (2010), and this locus may be significantly correlated with milk yield, fat percentage, and protein percentage (P\u0026thinsp;\u0026lt;\u0026thinsp;0.05). When the effects of UWCA9 on lactation traits were analyzed, the results of this study were inconsistent with those of Guo et al. (2007) but consistent with those of Vilkki et al. (1997). Guo et al. (2007) reported that UWCA9 has an influence on fat percentage and protein percentage, but we and Vilkki et al. (1997) found that UWCA9 has an influence on only milk yield and no correlation with other traits. In this study, the effects of BM103 and BM302 on fat percentage were consistent with the results of Ashwell et al. (1997). In addition, we found a new locus (BM302) significantly related to protein percentage and 3 loci (BM1443, BM302, and BMS1943) significantly related to lactose percentage.\u003c/p\u003e \u003c/div\u003e"},{"header":"Conclusions","content":"\u003cp\u003eThe correlation analysis showed 3 loci (namely, BM143, BM415 and BP7) with no significant correlation with all lactation traits. Two other loci (namely, BM302 and UWCA9) were found to be related to milk yield, 3 loci (BM103, BM302, and BM6425) were related to fat percentage, 2 loci (BM302 and BM6425) were related to protein percentage, and 3 loci (BM1443, BM302, and BMS1943) were related to lactose percentage. However, the number of experimental animals was an important limiting factor. In the future, it will be necessary to increase the number of experimental cattle, sample size, and microsatellite markers and constantly track the correlation between microsatellite loci and milk production performance of Holstein cows, to obtain consistent microsatellite markers for screening excellent milk production traits of Holstein cows.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eSTATEMENTS AND DECLARATIONS\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe study was supported by the Region Youth Fundation of Xinjiang Uygur Autonomous in China (2021D01B85).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting Interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors have no relevant financial or non-financial interests to disclose\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor Contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll authors contributed to the study conception and design. Material preparation, data collection and analysis were performed by Yongqing LI and Li LIU. The first draft of the manuscript was written by Yongqing LI and all authors commented on previous versions of the manuscript. All authors read and approved the final manuscript.\u003c/p\u003e\n\u003ch4\u003eData Availability\u003c/h4\u003e\n\u003cp\u003eThe datasets generated during and/or analysed during the current study are not publicly available due to [REASON(S) WHY DATA ARE NOT PUBLIC] but are available from the corresponding author on reasonable request.\u003c/p\u003e\n\u003ch4\u003eEthics approval\u003c/h4\u003e\n\u003cp\u003eThis study was performed in line with the principles of the Declaration of Helsinki. Approval was granted by the\u0026nbsp;Care and Use of Laboratory Animals at\u0026nbsp;Xinjiang Academy of Animal Science.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eInformed consent was obtained from the dairy farm owners in the study.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent to publish\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe manuscript doesn\u0026rsquo;t contain any other individual person\u0026rsquo;s data in any form.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eWilliams, J. G., A. R. Kubelik, and K. J. Livak. 1990. DNA polymorphisms amplified by arbitrary primers are useful as genetic markers. Nucleic Acids Research. 18: 6531\u003cb\u003e\u0026ndash;\u003c/b\u003e6535.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eTakezaki\u0026#130;N., and M. Nei. 1996. Genetic distance and reconstruction of phylogenetic trees from microsatellite DNA. Genetics. 144: 389\u003cb\u003e\u0026ndash;\u003c/b\u003e399༎\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eYin, B. 2016. Screening of microsatellite markers for molecular genealogy identification of dairy cows and its correlation analysis with production performance. MS Thesis. Shandong Agricultural University, Taian.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDux, M., M. Muranowicz, E. Siadkowska, D. Robakowska-Hyżorek, K. Flisikowski, E. Bagnicka, and L. Zwierzchowski. 2018. Association of SNP and STR polymorphisms of insulin-like growth factor 2 receptor (IGF2R) gene with milk traits in Holstein-Friesian cows. Journal of Dairy Research. 85(2): 138\u003cb\u003e\u0026ndash;\u003c/b\u003e141. doi: 10.1017/S0022029918000110.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSokolova, O., I. Moročko-Bičevska, and G. Lācis. 2022. Genetic diversity of venturia inaequalis in latvia revealed by microsatellite markers. Pathogens. 11(10): 1165. doi: 10.3390/pathogens11101165.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eOrdidge, M., S. Litthauer, E. Venison, M. Blouin-Delmas, F. Fernandez-Fernandez, M. H\u0026ouml;fer, C. K\u0026auml;gi, M. Kellerhals, A. Marchese, S. Mariette, H. Nybom, and D. Giovannini. 2021. Towards a joint international database: alignment of SSR marker data for European collections of cherry germplasm. Plants (Basel). 10(6): 1243. doi: 10.3390/plants10061243.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSchumacher, C., C. T. Krannich, L. Maletzki, K. K\u0026ouml;hl, J. Kopka, H. Sprenger, D. K. Hincha, S. Seddig, R. Peters, S. Hamera, E. Zuther, M. Haas, and R. Horn. 2021. Unravelling differences in candidate genes for drought tolerance in potato (solanum tuberosum L.) by use of new functional microsatellite markers. 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Animal Genetics. 28: 216 \u003cb\u003e\u0026minus;\u0026thinsp;2\u003c/b\u003e22.\u003c/span\u003e\u003c/li\u003e\u003c/ol\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":true,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"tropical-animal-health-and-production","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"trop","sideBox":"Learn more about [Tropical Animal Health and Production](https://www.springer.com/journal/11250)","snPcode":"11250","submissionUrl":"https://submission.nature.com/new-submission/11250/3","title":"Tropical Animal Health and Production","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"Xinjiang, Holstein cow, STR, Lactation performance, Microsatellite loci","lastPublishedDoi":"10.21203/rs.3.rs-2537800/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-2537800/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eMicrosatellite markers, also known as short tandem repeats (STRs), are important for marker-assisted selection to detect genetic polymorphism, and they are uniformly distributed in eukaryotic genomes. To analyze the relationship between microsatellite loci and lactation traits of Holstein cows in Xinjiang, 175 lactating cows with similar birth dates, the same parity, and similar calving dates were selected, and 10 STR loci closely linked to quantitative trait loci were used to analyze the correlation between each STR locus and 4 lactation traits (daily milk yield, milk fat percentage, milk protein percentage, and lactose percentage). All loci showed different degrees of genetic polymorphism. The average values of observed alleles, effective alleles, expected heterozygosity, observed heterozygosity, and polymorphic information content of the 10 STR loci were 10, 3.11, 0.62, 0.64, and 0.58, respectively. Chi-square and G-square tests showed that all populations of loci were in accordance with the Hardy\u0026ndash;Weinberg equilibrium. Analysis of the correlation between STR locus genotype and lactation performance in the whole lactation period showed 3 loci (namely, BM143, BM415, and BP7) with no significant correlation with all lactation traits, 2 loci (BM302 and UWCA9) related to milk yield, 3 loci (BM103, BM302, and BM6425) related to milk fat percentage, 2 loci (BM302 and BM6425) related to milk protein percentage, and 3 loci (BM1443, BM302, and BMS1943) related to lactose percentage. The microsatellite loci selected in this study showed rich polymorphism in the experimental dairy cow population and were related to the lactation traits, which can be used for the evaluation of genetic resources and early breeding and improvement of Holstein dairy cows in Xinjiang.\u003c/p\u003e","manuscriptTitle":"Analysis of the Relationship between Short Tandem Repeats and Lactation Performance of Xinjiang Holstein Cows","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2023-02-16 15:08:36","doi":"10.21203/rs.3.rs-2537800/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"reviewerAgreed","content":"","date":"2023-02-14T18:48:29+00:00","index":0,"fulltext":""},{"type":"editorAssigned","content":"","date":"2023-02-08T04:47:57+00:00","index":"","fulltext":""},{"type":"submitted","content":"Tropical Animal Health and Production","date":"2023-02-07T04:24:08+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"tropical-animal-health-and-production","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"trop","sideBox":"Learn more about [Tropical Animal Health and Production](https://www.springer.com/journal/11250)","snPcode":"11250","submissionUrl":"https://submission.nature.com/new-submission/11250/3","title":"Tropical Animal Health and Production","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"1d3fa990-b803-4574-bc05-8425acfe2ed3","owner":[],"postedDate":"February 16th, 2023","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2023-10-16T21:23:54+00:00","versionOfRecord":{"articleIdentity":"rs-2537800","link":"https://doi.org/10.1007/s11250-023-03651-y","journal":{"identity":"tropical-animal-health-and-production","isVorOnly":false,"title":"Tropical Animal Health and Production"},"publishedOn":"2023-06-15 21:13:38","publishedOnDateReadable":"June 15th, 2023"},"versionCreatedAt":"2023-02-16 15:08:36","video":"","vorDoi":"10.1007/s11250-023-03651-y","vorDoiUrl":"https://doi.org/10.1007/s11250-023-03651-y","workflowStages":[]},"version":"v1","identity":"rs-2537800","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-2537800","identity":"rs-2537800","version":["v1"]},"buildId":"369fNeqWncA4NS6XSWjrt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}