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

Authors :
Xubin Lu
Abdelaziz Adam Idriss Arbab
Ismail Mohamed Abdalla
Dingding Liu
Zhipeng Zhang
Tianle Xu
Guosheng Su
Zhangping Yang
Source :
Frontiers in Genetics, Vol 12 (2022)
Publication Year :
2022
Publisher :
Frontiers Media S.A., 2022.

Abstract

Accurately estimating the genetic parameters and revealing more genetic variants underlying milk production and quality are conducive to the genetic improvement of dairy cows. In this study, we estimate 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 for 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 lactation 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. Two, six, four, six, and three single nucleotide polymorphisms (SNPs) were detected, which explained 5.44, 12.39, 8.89, 10.65, and 7.09% of the phenotypic variation in 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 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 that this study will provide useful information for in-depth understanding of the genetic architecture of milk production and quality traits, as well as contribute to the genomic selection work of dairy cows in the lower reaches of the Yangtze River.

Details

Language :
English
ISSN :
16648021
Volume :
12
Database :
Directory of Open Access Journals
Journal :
Frontiers in Genetics
Publication Type :
Academic Journal
Accession number :
edsdoj.308719b77d2b4fff84a08e7c287c5e49
Document Type :
article
Full Text :
https://doi.org/10.3389/fgene.2021.799664