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

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.

Keywords: Chinese holstein; genetic parameters; genome-wide association study (GWAS); milk-related traits; test-day model.

FIGURE 1

Variance component estimates of milk-related traits during the lactation (red line, additive genetic variance; blue line, permanent environmental variance; black line, heritability; (A) MY, milk yield; (B) MFP, milk fat percentage; (C) MFY, milk fat yield; (D) MPP, milk protein percentage; (E) MPY, milk protein yield).

FIGURE 2

Genetic correlations of milk-related traits in different DIM during lactation ((A) MY, milk yield; (B) MFP, milk fat percentage; (C) MFY, milk fat yield; (D) MPP, milk protein percentage; (E) MPY, milk protein yield).

FIGURE 3

The linkage disequilibrium decay analysis (A) and the principal component analysis (B) according to the 84,407 single nucleotide polymorphisms (SNPs) for the 984 cows.

FIGURE 4

Manhattan plots (A) and quantile-quantile (QQ) plots (B) demonstrated from the genome-wide association study (GWAS) results of the milk-related traits. The significance threshold was 5.90 × 10⁻⁷. The red dots represent the significant SNPs. The abscissas and ordinates in the Manhattan plots represent the 30 chromosomes of cows and the negative logarithms of the p-values of the variants, respectively (A). The abscissas and ordinates in the QQ plots represent negative logarithms of the expected p-values and negative logarithms of the observed p-values of each SNP (B) (MY. milk yield; MFP. milk fat percentage; MFY. milk fat yield; MPP. milk protein percentage; MPY. milk protein yield, λ. inflation factor value).

FIGURE 5

Significant Gene Ontology (GO) terms enriched by the genes within 200 kb of significant SNPs. After quality control, 13 GO terms that are enriched by eight genes are revealed in the circus plots (p < 0.05).