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Ten Genetic Loci Identified for Milk Yield, Fat, and Protein in Holstein Cattle
bioRxiv - Genomics Pub Date : 2020-08-04 , DOI: 10.1101/2020.06.17.158386 Liyuan Liu , Jinghang Zhou , Chunpeng James Chen , Juan Zhang , Wan Wen , Jia Tian , Zhiwu Zhang , Yaling Gu
bioRxiv - Genomics Pub Date : 2020-08-04 , DOI: 10.1101/2020.06.17.158386 Liyuan Liu , Jinghang Zhou , Chunpeng James Chen , Juan Zhang , Wan Wen , Jia Tian , Zhiwu Zhang , Yaling Gu
High-yield and high-quality of milk are the primary goals of dairy production. Understanding the genetic architecture underlying these milk production traits is beneficial so that genetic variants can be targeted toward the genetic improvement. In this study, we measured five milk production traits in Holstein cattle population from China. These traits included milk yield, protein yield, fat yields; fat percentage and protein percentages. We used the estimated breeding values as dependent variables to conduct the genome-wide association studies (GWAS). Breeding values were estimated through pedigree relationships by using a mixed linear model for individuals with and without phenotypic data. Genotyping was carried out on the individuals with phenotypes by using the Illumina BovineSNP150 BeadChip. The association analyses were conducted by using the Fixed and random model Circulating Probability Unification (FarmCPU) method. A total of ten SNPs was detected above the genome-wide significant threshold, including six located in previously reported QTL regions. We found eight candidate genes within distances of 120 kb upstream or downstream to the associated SNPs. The most significant SNP is on DGAT1 gene affecting milk fat and protein percentage. These genetic variants and candidate genes would be valuable resources to enhance dairy cattle breeding.
更新日期:2020-08-04