AUTHOR=Liu Dengying , Xu Zhong , Zhao Wei , Wang Shiyi , Li Tuowu , Zhu Kai , Liu Guanglei , Zhao Xiaoduo , Wang Qishan , Pan Yuchun , Ma Peipei 

TITLE=Genetic parameters and genome-wide association for milk production traits and somatic cell score in different lactation stages of Shanghai Holstein population

JOURNAL=Frontiers in Genetics

VOLUME=13

YEAR=2022

URL=https://www.frontiersin.org/journals/genetics/articles/10.3389/fgene.2022.940650

DOI=10.3389/fgene.2022.940650

ISSN=1664-8021

ABSTRACT=<p>The aim of this study was to investigate the genetic parameters and genetic architectures of six milk production traits in the Shanghai Holstein population. The data used to estimate the genetic parameters consisted of 1,968,589 test-day records for 305,031 primiparous cows. Among the cows with phenotypes, 3,016 cows were genotyped with Illumina Bovine SNP50K BeadChip, GeneSeek Bovine 50K BeadChip, GeneSeek Bovine LD BeadChip v4, GeneSeek Bovine 150K BeadChip, or low-depth whole-genome sequencing. A genome-wide association study was performed to identify quantitative trait loci and genes associated with milk production traits in the Shanghai Holstein population using genotypes imputed to whole-genome sequences and both fixed and random model circulating probability unification and a mixed linear model with rMVP software. Estimated heritabilities (h2) varied from 0.04 to 0.14 for somatic cell score (SCS), 0.07 to 0.22 for fat percentage (FP), 0.09 to 0.27 for milk yield (MY), 0.06 to 0.23 for fat yield (FY), 0.09 to 0.26 for protein yield (PY), and 0.07 to 0.35 for protein percentage (PP), respectively. Within lactation, genetic correlations for SCS, FP, MY, FY, PY, and PP at different stages of lactation estimated in random regression model were ranged from -0.02 to 0.99, 0.18 to 0.99, 0.04 to 0.99, 0.04 to 0.99, 0.01 to 0.99, and 0.33 to 0.99, respectively. The genetic correlations were highest between adjacent DIM but decreased as DIM got further apart. Candidate genes included those related to production traits (<italic>DGAT1</italic>, <italic>MGST1</italic>, <italic>PTK2</italic>, and <italic>SCRIB</italic>), disease-related (<italic>LY6K</italic>, <italic>COL22A1</italic>, <italic>TECPR2</italic>, and <italic>PLCB1</italic>), heat stress–related (<italic>ITGA9</italic>, <italic>NDST4</italic>, <italic>TECPR2</italic>, and <italic>HSF1</italic>), and reproduction-related (<italic>7SK</italic> and <italic>DOCK2</italic>) genes. This study has shown that there are differences in the genetic mechanisms of milk production traits at different stages of lactation. Therefore, it is necessary to conduct research on milk production traits at different stages of lactation as different traits. Our results can also provide a theoretical basis for subsequent molecular breeding, especially for the novel genetic loci.</p>