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The Candidate Chromosomal Regions Responsible for Milk Yield of Cow: A GWAS Meta-Analysis

SIMPLE SUMMARY: Milk production is one of the most important economic traits in dairy cattle. Therefore, determining the genomic regions influencing this trait can improve milk yield. In this study, we collected data from 16 articles associated with milk yield genome-wide association studies (GWAS)...

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Autores principales: Taherkhani, Lida, Banabazi, Mohammad Hossein, EmamJomeh-Kashan, Nasser, Noshary, Alireza, Imumorin, Ikhide
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8909671/
https://www.ncbi.nlm.nih.gov/pubmed/35268150
http://dx.doi.org/10.3390/ani12050582
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author Taherkhani, Lida
Banabazi, Mohammad Hossein
EmamJomeh-Kashan, Nasser
Noshary, Alireza
Imumorin, Ikhide
author_facet Taherkhani, Lida
Banabazi, Mohammad Hossein
EmamJomeh-Kashan, Nasser
Noshary, Alireza
Imumorin, Ikhide
author_sort Taherkhani, Lida
collection PubMed
description SIMPLE SUMMARY: Milk production is one of the most important economic traits in dairy cattle. Therefore, determining the genomic regions influencing this trait can improve milk yield. In this study, we collected data from 16 articles associated with milk yield genome-wide association studies (GWAS) on different cattle breeds. Based on the information from the analysis and level of significance (p-value < 2.5 × 10(−6)), we identified different genomic regions on chromosomes with the highest marker density, markers with the highest effect, genes within or near these regions, chromosomes with the greatest effects on milk yield. ABSTRACT: Milk yield (MY) is highly heritable and an economically important trait in dairy livestock species. To increase power to detect candidate genomic regions for this trait, we carried out a meta-analysis of genome-wide association studies (GWAS). In the present study, we identified 19 studies in PubMed for the meta-analysis. After review of the studies, 16 studies passed the filters for meta-analysis, and the number of chromosomes, detected markers and their positions, number of animals, and p-values were extracted from these studies and recorded. The final data set based on 16 GWAS studies had 353,698 cows and 3950 markers and was analyzed using METAL software. Our findings revealed 1712 significant (p-value < 2.5 × 10(−6)) genomic loci related to MY, with markers associated with MY found on all autosomes and sex chromosomes and the majority of them found on chromosome 14. Furthermore, gene ontology (GO) annotation was used to explore biological functions of the genes associated with MY; therefore, different regions of this chromosome may be suitable as genomic regions for further research into gene expression.
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spelling pubmed-89096712022-03-11 The Candidate Chromosomal Regions Responsible for Milk Yield of Cow: A GWAS Meta-Analysis Taherkhani, Lida Banabazi, Mohammad Hossein EmamJomeh-Kashan, Nasser Noshary, Alireza Imumorin, Ikhide Animals (Basel) Article SIMPLE SUMMARY: Milk production is one of the most important economic traits in dairy cattle. Therefore, determining the genomic regions influencing this trait can improve milk yield. In this study, we collected data from 16 articles associated with milk yield genome-wide association studies (GWAS) on different cattle breeds. Based on the information from the analysis and level of significance (p-value < 2.5 × 10(−6)), we identified different genomic regions on chromosomes with the highest marker density, markers with the highest effect, genes within or near these regions, chromosomes with the greatest effects on milk yield. ABSTRACT: Milk yield (MY) is highly heritable and an economically important trait in dairy livestock species. To increase power to detect candidate genomic regions for this trait, we carried out a meta-analysis of genome-wide association studies (GWAS). In the present study, we identified 19 studies in PubMed for the meta-analysis. After review of the studies, 16 studies passed the filters for meta-analysis, and the number of chromosomes, detected markers and their positions, number of animals, and p-values were extracted from these studies and recorded. The final data set based on 16 GWAS studies had 353,698 cows and 3950 markers and was analyzed using METAL software. Our findings revealed 1712 significant (p-value < 2.5 × 10(−6)) genomic loci related to MY, with markers associated with MY found on all autosomes and sex chromosomes and the majority of them found on chromosome 14. Furthermore, gene ontology (GO) annotation was used to explore biological functions of the genes associated with MY; therefore, different regions of this chromosome may be suitable as genomic regions for further research into gene expression. MDPI 2022-02-25 /pmc/articles/PMC8909671/ /pubmed/35268150 http://dx.doi.org/10.3390/ani12050582 Text en © 2022 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Taherkhani, Lida
Banabazi, Mohammad Hossein
EmamJomeh-Kashan, Nasser
Noshary, Alireza
Imumorin, Ikhide
The Candidate Chromosomal Regions Responsible for Milk Yield of Cow: A GWAS Meta-Analysis
title The Candidate Chromosomal Regions Responsible for Milk Yield of Cow: A GWAS Meta-Analysis
title_full The Candidate Chromosomal Regions Responsible for Milk Yield of Cow: A GWAS Meta-Analysis
title_fullStr The Candidate Chromosomal Regions Responsible for Milk Yield of Cow: A GWAS Meta-Analysis
title_full_unstemmed The Candidate Chromosomal Regions Responsible for Milk Yield of Cow: A GWAS Meta-Analysis
title_short The Candidate Chromosomal Regions Responsible for Milk Yield of Cow: A GWAS Meta-Analysis
title_sort candidate chromosomal regions responsible for milk yield of cow: a gwas meta-analysis
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8909671/
https://www.ncbi.nlm.nih.gov/pubmed/35268150
http://dx.doi.org/10.3390/ani12050582
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