Genetic parameter estimation and fine-mapping of milk-production traits and somatic cell score in Chinese Simmental cattle

Chinese Simmental cattle serve as an important dual-purpose breed in sustainable livestock systems. Despite their economic value, the genetic architecture underlying milk-production traits in this breed under temperate conditions remains poorly characterized. In this study, we estimated genetic parameters and identified associated genomic loci for 9 milk-production traits in a Chinese Simmental population. Our dataset consisted of 17,556 test-day records from 1,788 cows (parities 1 to 3), including whole-genome sequencing data for 781 individuals. Using a random regression test-day model with Legendre polynomials, we estimated variance components, heritabilities, breeding values (EBVs), and genetic correlations between different DIM. Heritability estimates ranged from 0.09 (fat-to-protein ratio) to 0.52 (protein percentage), with intermediate values for fat percentage (0.28), lactose percentage (0.35), and total milk solids (0.35). Within-lactation genetic correlations varied by trait, ranging from -0.88 to 0.99, with the strongest correlations between adjacent DIM, which weakened as intervals widened. Genome-wide association analysis (using the mixed linear model in the SLEMM package) and Bayesian fine-mapping analysis identified significant SNPs near known candidate genes (BOP1, MROH1, NEGR1). These analyses also revealed putative novel associations with CACNB4, MTHFD2L, and SGMS1. Overall, the results enhance our understanding of the genetic regulation of milk production and provide practical targets for genomic selection to improve dairy performance in dual-purpose breeding programs.