Gangwar Munish, Kumar Subodh, Ahmad Sheikh Firdous, Singh Akansha, Agarwal Swati, P L Anitta, C S Celus, Kumar Amit
Division of Animal Genetics, ICAR-Indian Veterinary Research Institute, Izatnangar, Bareilly, 243 122, Uttar Pradesh, India.
Livestock Production and Management Section, ICAR-Indian Veterinary Research Institute, Izatnagar, Bareilly, 243 122, Uttar Pradesh, India.
Trop Anim Health Prod. 2025 Mar 6;57(2):104. doi: 10.1007/s11250-025-04348-0.
The present study delves into the relationship between single nucleotide polymorphisms (SNPs) and production performance, employing genome-wide association study (GWAS) approach. A total of 96 randomly selected Vrindavani cows were genotyped with Illumina Bovine 50K BeadChip platform. The study employed a linear regression model within the PLINK program, with an attempt to associate genome-wide SNP markers with key production traits i.e., total lactation milk yield (TLMY), lactation length (LL), and peak yield (PY) across the first three lactations. The study involved mining relevant databases to uncover biological pathways linked to genes and quantitative trait loci (QTLs) affecting production performance of cows. The results revealed 70 SNP markers dispersed across various chromosomes that showed profound impact on the variation in TLMY (21 SNPs), LL (10 SNPs), and PY (39 SNPs). The GWAS approach uncovered novel/ potential candidate genes such as PTPRT, RBMS3, CENPE, IFNT, ESR1, ARMC1, LCORL, MED28, NCAPG, LAP3, MYH9, ITPR2, IFNT, ETV6, PARVB, ARNTL2, and PLA2G12A that showed association with different economic traits. These significant SNPs and genes hold relevance for production traits, besides offering valuable insights into potential biomarkers for enhancing production performance in bovine populations.
本研究采用全基因组关联研究（GWAS）方法，深入探讨单核苷酸多态性（SNP）与生产性能之间的关系。总共随机选择了96头弗林达瓦尼奶牛，使用Illumina牛50K芯片平台进行基因分型。该研究在PLINK程序中采用线性回归模型，试图将全基因组SNP标记与关键生产性状关联起来，即头三个泌乳期的总泌乳量（TLMY）、泌乳期长度（LL）和产奶峰值（PY）。该研究还涉及挖掘相关数据库，以揭示与影响奶牛生产性能的基因和数量性状位点（QTL）相关的生物途径。结果显示，分布在不同染色体上的70个SNP标记对TLMY（21个SNP）、LL（10个SNP）和PY（39个SNP）的变异有深远影响。GWAS方法发现了一些新的/潜在的候选基因，如PTPRT、RBMS3、CENPE、IFNT、ESR1、ARMC1、LCORL、MED28、NCAPG、LAP3、MYH9、ITPR2、IFNT、ETV6、PARVB、ARNTL2和PLA2G12A，这些基因与不同的经济性状相关。这些显著的SNP和基因不仅与生产性状相关，还为提高牛群生产性能的潜在生物标志物提供了有价值的见解。
