Rahman Javid Ur, Kumar Devendra, Singh Satya Pal, Shahi Bijendra Narayan, Ghosh Ashis Kumar, Dar Aashaq Hussain, Togla Oshin
Dapartment of Animal Genetics and Breeding, College of Veterinary & Animal Sciences, Govind Ballabh Pant University of Agriculture and Technology, Pantnagar, Uttarakhand, 263145, India.
Silkworm Breeding and Genetics, CSRTI, Central Silk Board, Berhampore, West Bengal, 742101, India.
Trop Anim Health Prod. 2024 Dec 24;57(1):10. doi: 10.1007/s11250-024-04266-7.
Genome-wide association studies (GWAS) offer potential for discovering genomic regions that can be exploited to increase milk production. However, available GWAS and single nucleotide polymorphism (SNP) datasets are heavily skewed towards taurine breeds, which restricts their utility for genomic research in indicine cattle breeds. This study conducts a GWAS on the Badri breed of Indicine cattle to estimate variance components and identify significant variants associated with milk composition traits, utilizing double digest restriction-site associated DNA (ddRAD) sequencing data. A total of 65,483 high-confidence SNPs were identified and utilized to conduct GWAS on various milk composition traits, including fat percent (FP), protein percent (PP), casein percent (CP), lactose percent (LP), glucose percent (GP), galactose percent (GLP), total solids percent (TS), and solids-not-fat percent (SNF), each analysed separately. The heritability estimates for the studied milk composition traits were 0.386 for fat percent (FP), 0.427 for protein percent (PP), 0.469 for casein percent (CP), 0.567 for lactose percent (LP), 0.547 for glucose percent (GP), 0.590 for galactose percent (GLP), 0.437 for total solids percent (TS), and 0.476 for solids-not-fat percent (SNF). Several genomic regions and candidate genes, including SLC9A9, LPP, C2H2orf76, LGSN, HMGCS2, Bv1, SCYL2, PLAC8, SRGAP2, CR2, ZNF787, OTUB2, DSC2, SYNPO2, and CTNNA3 which may have a potential role in regulating milk production in indicine cattle were identified. The high confidence SNPs and candidate genes will be an important inclusion into commercial genotyping arrays for the early and best selection of breeding animals for desired milk composition and improved production.
全基因组关联研究（GWAS）为发现可用于提高牛奶产量的基因组区域提供了潜力。然而，现有的GWAS和单核苷酸多态性（SNP）数据集严重偏向于普通牛品种，这限制了它们在瘤牛品种基因组研究中的效用。本研究利用双酶切限制性位点关联DNA（ddRAD）测序数据，对瘤牛品种巴德里牛进行了GWAS，以估计方差成分并识别与牛奶成分性状相关的显著变异。共鉴定出65483个高可信度SNP，并用于对各种牛奶成分性状进行GWAS，包括脂肪百分比（FP）、蛋白质百分比（PP）、酪蛋白百分比（CP）、乳糖百分比（LP）、葡萄糖百分比（GP）、半乳糖百分比（GLP）、总固体百分比（TS）和非脂固体百分比（SNF），每个性状分别进行分析。所研究的牛奶成分性状的遗传力估计值分别为：脂肪百分比（FP）为0.386，蛋白质百分比（PP）为0.427，酪蛋白百分比（CP）为0.469，乳糖百分比（LP）为0.567，葡萄糖百分比（GP）为0.547，半乳糖百分比（GLP）为0.590，总固体百分比（TS）为0.437，非脂固体百分比（SNF）为0.476。鉴定出了几个基因组区域和候选基因，包括SLC9A9、LPP、C2H2orf76、LGSN、HMGCS2、Bv1、SCYL2、PLAC8、SRGAP2、CR2、ZNF787、OTUB2、DSC2、SYNPO2和CTNNA3，它们可能在调节瘤牛产奶中发挥潜在作用。这些高可信度SNP和候选基因将是商业基因分型阵列的重要补充，用于早期和最佳选择具有所需牛奶成分和提高产量的种畜。
