AUTHOR=Lu Xubin , Arbab Abdelaziz Adam Idriss , Abdalla Ismail Mohamed , Liu Dingding , Zhang Zhipeng , Xu Tianle , Su Guosheng , Yang Zhangping 

TITLE=Genetic Parameter Estimation and Genome-Wide Association Study-Based Loci Identification of Milk-Related Traits in Chinese Holstein

JOURNAL=Frontiers in Genetics

VOLUME=Volume 12 - 2021

YEAR=2022

URL=https://www.frontiersin.org/journals/genetics/articles/10.3389/fgene.2021.799664

DOI=10.3389/fgene.2021.799664

ISSN=1664-8021

ABSTRACT=Accurately estimating the genetic parameters and revealing more genetic variants that underlying milk production and quality are conducive to the genetic improvement of dairy cows. In this study, we estimated the genetic parameters of five milk-related traits of cows, namely milk yield (MY), milk fat percentage (MFP), milk fat yield (MFY), milk protein percentage (MPP), and milk protein yield (MPY), based on a random regression test-day model. A total of 95,375 test-day records of 9,834 cows in the lower reaches of the Yangtze River were used in the estimation. In addition, genome-wide association studies (GWASs) for these traits were conducted based on adjusted phenotypes. The heritability as well as the standard errors of MY, MFP, MFY, MPP, and MPY during the lactation were ranged from 0.22±0.02 to 0.31±0.04, 0.06±0.02 to 0.15±0.03, 0.09±0.02 to 0.28±0.04, 0.07±0.01 to 0.16±0.03, and 0.14±0.02 to 0.27±0.03, respectively, and the genetic correlations between different days in milk (DIM) within lactations decreased as the time interval increased. There were 2, 6, 4, 6, and 3 single nucleotide polymorphisms (SNPs) were detected, and they explained 5.44 %, 12.39 %, 8.89 %, 10.65 %, and 7.09 % of the phenotypic variation of MY, MFP, MFY, MPP, and MPY, respectively. Ten Kyoto Encyclopedia of Genes and Genomes pathways and 25 Gene Ontology terms were enriched by analyzing the nearest genes and genes within 200 kb of the detected SNPs. Moreover, 17 genes in the enrichment results that may play roles in the milk production and quality were selected as candidates, including CAMK2G, WNT3A, WNT9A, PLCB4, SMAD9, PLA2G4A, ARF1, OPLAH, MGST1, CLIP1, DGAT1, PRMT6, VPS28, HSF1, MAF1, TMEM98, and F7. We hope this study could provide useful information for in-depth understanding of the genetic architecture of milk production and quality traits, and also contribute to the genomic selection work of dairy cows in the lower reaches of the Yangtze River.