Abstract
Simple SummaryUnderstanding the genetic architecture underlying milk production traits in cattle is beneficial so that genetic variants can be targeted toward the genetic improvement. In this study, we performed a genome-wide association study for milk production and quality traits in Holstein cattle. In the total of ten significant single-nucleotide polymorphisms (SNPs) associated with milk fat and protein, six are located in previously reported quantitative traits locus (QTL) regions. The study not only identified the effect of DGAT1 gene on milk fat and protein but also found several novel candidate genes. In addition, some pleiotropic SNPs and QTLs were identified that associated with more than two traits, these results could provide some basis for molecular breeding in dairy cattle.High-yield and high-quality of milk are the primary goals of dairy production. Understanding the genetic architecture underlying these milk-related traits is beneficial so that genetic variants can be targeted toward the genetic improvement. In this study, we measured five milk production and quality traits in Holstein cattle population from China. These traits included milk yield, fat, and protein. We used the estimated breeding values as dependent variables to conduct the genome-wide association studies (GWAS). Breeding values were estimated through pedigree relationships by using a linear mixed model. Genotyping was carried out on the individuals with phenotypes by using the Illumina BovineSNP150 BeadChip. The association analyses were conducted by using the fixed and random model Circulating Probability Unification (FarmCPU) method. A total of ten single-nucleotide polymorphisms (SNPs) were detected above the genome-wide significant threshold (p < 4.0 × 10−7), including six located in previously reported quantitative traits locus (QTL) regions. We found eight candidate genes within distances of 120 kb upstream or downstream to the associated SNPs. The study not only identified the effect of DGAT1 gene on milk fat and protein, but also discovered novel genetic loci and candidate genes related to milk traits. These novel genetic loci would be an important basis for molecular breeding in dairy cattle.
Highlights
Milk production and quality are the most important economic traits in the dairy industry.Most milk phenotypes are quantitative traits that often controlled by both environmental factors and Animals 2020, 10, 2048; doi:10.3390/ani10112048 www.mdpi.com/journal/animalsAnimals 2020, 10, 2048 multiple genes
By drawing the Quantile-Quantile (QQ) plots, we found that the model for genome-wide association studies (GWAS) analysis in this study was reasonable, and the point at the upper right corner shown that some significant this study was reasonable, and the point at the upper right corner shown that some significant markers were found that associated with four milk quality traits (Figure 3)
We found ten single-nucleotide polymorphisms (SNPs) were significantly associated with four milk quality traits (FP, fat yield (FY), PP, and protein yield (PY)), one of the most significant SNPs was located in the diacylglycerol O-acyltransferase 1 (DGAT1) gene and shown closely related to milk fat and protein percentage
Summary
Milk production and quality are the most important economic traits in the dairy industry.Most milk phenotypes are quantitative traits that often controlled by both environmental factors and Animals 2020, 10, 2048; doi:10.3390/ani10112048 www.mdpi.com/journal/animalsAnimals 2020, 10, 2048 multiple genes. Regions for milk-related traits in dairy cattle population around the world over the past 20 years (CatttleQTLdb: https://www.animalgenome.org/cgi-bin/QTLdb/BT/index), and many researchers conducted meta-analysis to identify genetic variants based on GWAS results for milk-related traits in different cattle breeds [1,2,3]. Research has shown that high-density genotype could provide markers close to the QTL and help in fine mapping of causative mutations [5]. Vanraden et al reported that high-density marker increased the precision of QTL detection in cattle population [6]. A study reported that the genomic prediction accuracy increased when the marker density was increased in cattle [7]; it is necessary to use dense genotype to identify important genetic variation, and provide some useful information for molecular breeding of dairy cattle and understanding the genetic architecture of milk traits
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