Ten Genetic Loci Identified for Milk Yield, Fat, and Protein in Holstein Cattle

AbstractHigh-yield and high-quality of milk are the primary goals of dairy production. Understanding the genetic architecture underlying these milk production traits is beneficial so that genetic variants can be targeted toward the genetic improvement. In this study, we measured five milk production traits in Holstein cattle population from China. These traits included milk yield, protein yield, fat yields; fat percentage and protein percentages. 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 mixed linear model for individuals with and without phenotypic data. 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 SNPs was detected above the genome-wide significant threshold, including six located in previously reported QTL regions. We found eight candidate genes within distances of 120 kb upstream or downstream to the associated SNPs. The most significant SNP is on DGAT1 gene affecting milk fat and protein percentage. These genetic variants and candidate genes would be valuable resources to enhance dairy cattle breeding.

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Identification of genetic markers associated with milk production traits in Chinese Holstein cattle based on post genome-wide association studies

Animal Biotechnology ◽

10.1080/10495398.2019.1653901 ◽

2019 ◽

pp. 1-10

Author(s):

Zhenwei Yang ◽

Zhiquan Lian ◽

Guangbin Liu ◽

Ming Deng ◽

Baoli Sun ◽

...

Keyword(s):

Genetic Markers ◽

Milk Production ◽

Association Studies ◽

Genome Wide Association ◽

Holstein Cattle ◽

Genome Wide Association Studies ◽

Production Traits ◽

Milk Production Traits ◽

Genome Wide ◽

Chinese Holstein Cattle

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GWAS-Based Identification of New Loci for Milk Yield, Fat, and Protein in Holstein Cattle

Animals ◽

10.3390/ani10112048 ◽

2020 ◽

Vol 10 (11) ◽

pp. 2048

Author(s):

Liyuan Liu ◽

Jinghang Zhou ◽

Chunpeng James Chen ◽

Juan Zhang ◽

Wan Wen ◽

...

Keyword(s):

Candidate Genes ◽

Milk Yield ◽

Milk Fat ◽

Association Studies ◽

High Yield ◽

Holstein Cattle ◽

Genome Wide Association Studies ◽

Genetic Loci ◽

Breeding Values ◽

Genome Wide

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.

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Meta-analysis of genome-wide association studies and gene networks analysis for milk production traits in Holstein cows

Livestock Science ◽

10.1016/j.livsci.2021.104605 ◽

2021 ◽

pp. 104605

Author(s):

Somayeh Bakhshalizadeh ◽

Saeed Zerehdaran ◽

Ali Javadmanesh

Keyword(s):

Milk Production ◽

Gene Networks ◽

Association Studies ◽

Meta Analysis ◽

Genome Wide Association ◽

Genome Wide Association Studies ◽

Production Traits ◽

Milk Production Traits ◽

Genome Wide ◽

Networks Analysis

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Confirmed effects of candidate variants for milk production, udder health, and udder morphology in dairy cattle

Genetics Selection Evolution ◽

10.1186/s12711-020-00575-1 ◽

2020 ◽

Vol 52 (1) ◽

Cited By ~ 1

Author(s):

Thierry Tribout ◽

Pascal Croiseau ◽

Rachel Lefebvre ◽

Anne Barbat ◽

Mekki Boussaha ◽

...

Keyword(s):

Dairy Cattle ◽

Candidate Genes ◽

Milk Production ◽

Association Studies ◽

Genome Wide Association Studies ◽

Nucleotide Polymorphisms ◽

Production Traits ◽

Milk Production Traits ◽

Udder Health ◽

Gwas Approach

Abstract Background Over the last years, genome-wide association studies (GWAS) based on imputed whole-genome sequences (WGS) have been used to detect quantitative trait loci (QTL) and highlight candidate genes for important traits. However, in general this approach does not allow to validate the effects of candidate mutations or determine if they are truly causative for the trait(s) in question. To address these questions, we applied a two-step, within-breed GWAS approach on 15 traits (5 linked with milk production, 2 with udder health, and 8 with udder morphology) in Montbéliarde (MON), Normande (NOR), and Holstein (HOL) cattle. We detected the most-promising candidate variants (CV) using imputed WGS of 2515 MON, 2203 NOR, and 6321 HOL bulls, and validated their effects in three younger populations of 23,926 MON, 9400 NOR, and 51,977 HOL cows. Results Bull sequence-based GWAS detected 84 QTL: 13, 10, and 30 for milk production traits; 3, 0, and 2 for somatic cell score (SCS); and 8, 2 and 16 for udder morphology traits, in MON, NOR, and HOL respectively. Five genomic regions with effects on milk production traits were shared among the three breeds whereas six (2 for production and 4 for udder morphology and health traits) had effects in two breeds. In 80 of these QTL, 855 CV were highlighted based on the significance of their effects and functional annotation. The subsequent GWAS on MON, NOR, and HOL cows validated 8, 9, and 23 QTL for production traits; 0, 0, and 1 for SCS; and 4, 1, and 8 for udder morphology traits, respectively. In 47 of the 54 confirmed QTL, the CV identified in bulls had more significant effects than single nucleotide polymorphisms (SNPs) from the standard 50K chip. The best CV for each validated QTL was located in a gene that was functionally related to production (36 QTL) or udder (9 QTL) traits. Conclusions Using this two-step GWAS approach, we identified and validated 54 QTL that included CV mostly located within functional candidate genes and explained up to 6.3% (udder traits) and 37% (production traits) of the genetic variance of economically important dairy traits. These CV are now included in the chip used to evaluate French dairy cattle and can be integrated into routine genomic evaluation.

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