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.
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