Genetic association of the ACACB gene with milk yield and composition traits in dairy cattle

Previously, we re‐sequenced the whole genomes of eight Holstein bulls with high or low milk protein and fat percentage, and we detected two indels in the ACACB (acetyl‐CoA carboxylase beta) gene that were polymorphic between the two groups. Thus, we considered ACACB as a promising candidate gene potentially affecting milk composition traits. Herein, we verified the genetic effects of ACACB on five milk traits in a Chinese Holstein population. We identified six SNPs in the 5′‐promoter region, five in the 5′‐ untranslated region (UTR), 11 in exons, four in the 3′‐UTR and three in the 3′‐flanking region by re‐sequencing the entire coding and regulatory regions of ACACB. One of these SNPs (ss1987461005) is reported here for the first time, and three of the SNPs (rs109482081, rs110819816 and rs109281947) were predicted to result in amino acid replacements. Genotype–phenotype association analyses showed that all the identified SNPs, except for ss1987461005, rs208919019 and rs134447911, were significantly associated with milk yield, fat yield, fat percentage, protein yield or protein percentage (P < 0.0001 to 0.0484). Linkage disequilibrium analyses were conducted among the identified SNPs to confirm the genetic associations. Two SNPs—rs135874354 (g.66218726T>C) and rs210928430 (g.66218117G>A)—were predicted to alter transcription factor binding sites in the 5′‐promoter region of ACACB. A luciferase activity assay showed that the promoter activity of haplotype TG was significantly higher than that of CG (P = 0.0002) and that the promoter activity of haplotype TA was remarkably higher than that of CA (P = 7.4285E−09), showing that the T allele of rs135874354 increased promoter activity. Thus, rs135874354 was considered to be a potentially functional mutation. Our findings have, for the first time, profiled the genetic effect of ACACB on milk production traits in dairy cattle and revealed a potentially causal mutation that requires further the in‐depth validation.