AUTHOR=Zhou Chenghao , Li Cong , Cai Wentao , Liu Shuli , Yin Hongwei , Shi Shaolei , Zhang Qin , Zhang Shengli 

TITLE=Genome-Wide Association Study for Milk Protein Composition Traits in a Chinese Holstein Population Using a Single-Step Approach

JOURNAL=Frontiers in Genetics

VOLUME=Volume 10 - 2019

YEAR=2019

URL=https://www.frontiersin.org/journals/genetics/articles/10.3389/fgene.2019.00072

DOI=10.3389/fgene.2019.00072

ISSN=1664-8021

ABSTRACT=Genome-wide association studies (GWAS) have been widely used to inform the genetic architecture of quantifiable traits in dairy cattle. In this study, we conducted a GWAS for 9 milk protein composition traits (αS1-CN, αS2-CN, β-CN, κ-CN, α-LA, β-LG, casein index, protein percentage, and protein yield) in 614 Chinese Holstein cows using a single-step strategy. The aim of this research was to identify candidate genes affecting milk protein competition traits. We used the Illumina BovineSNP50 Bead chip and screened a total of 586,304 informative, high-quality single nucleotide polymorphisms. Phenotypic observations for all 6 major milk proteins (αS1-CN, αS2-CN, β-CN, κ-CN, α-LA, and β-LG) were evaluated as weight proportions of the total protein fraction (wt/wt%) using a commercial ELISA (enzyme-linked immunosorbent assay) kit. Informative windows comprised of 5 adjacent SNPs explaining no less than 0.5% genomic variance per window were selected for gene annotation as well as gene network and pathway analyses. A total of 178 genomic windows on 24 bovine autosomes were significantly associated with milk protein composition or protein percentage. Chromosome regions affecting milk protein composition traits were mainly observed on BTA 1, 6, 11, 13, 14, and 18. Of these, several windows were close to or within the CSN1S1, CSN1S2, CSN2, CSN3, LAP3, DGAT1, RPL8, and HSF1 genes, which have well-known effects on the milk protein composition traits of dairy cattle. Taken together with previously reported quantitative trait loci and the biological functions of the identified genes, we propose 19 novel candidate genes affecting milk protein composition traits: ARL6, SST, EHHADH, PCDHB4, PCDHB6, PCDHB7, PCDHB16, SLC36A2, GALNT14, FPGS, LARP4B, IDI1, COG4, FUK, WDR62, CLIP3, SLC25A21, IL5RA, and ACADSB. Our findings provide important insight into milk protein synthesis and potential targets for improving milk quality.