{"title":"Genome-wide association studies and genetic architecture of carcass traits in Angus beef cattle using imputed whole-genome sequences data","authors":"Hasan Baneh, Nikolay Elatkin, Laurent Gentzbittel","doi":"10.1186/s12711-025-00970-6","DOIUrl":null,"url":null,"abstract":"Carcass related traits are economically important traits for the beef industry, which affect quantity, quality and pricing of meat and farmers profitability. The current study was carried out to identify genomic regions associated with carcass traits including carcass weight (CW), marbling score (MS), rib-eye area (REA), and back fat thickness (BFT). Genome-wide association studies (GWAS) were performed using linear mixed models on 6,511,978 imputed whole genome sequence (WGS) variants in a population of 13,241 Angus beef cattle. The genetic architecture of the traits was evaluated based on the GWAS results. With a threshold of p-value < 3.96 × 10–7, 842, 745, 340, and 101 SNPs located in 13 genomic regions were significantly associated with CW, MS, REA, and BFT, respectively. While the majority of the identified quantitative trait loci (QTL) were trait-specific, two QTLs with pleiotropic effect were identified, including a QTL on BTA7 (88.25–91.96 Mb) affecting CW, MS and REA, and a QTL on BTA20 (4.55–5.01 Mb) affecting CW and BFT. Several important genes are harbored by the detected QTLs, which can be considered potential candidate genes for carcass traits in Angus beef cattle. Our findings also showed that higher density panels are more powerful in GWAS, such that the signals on BTA6 affecting CW, and two signals on BTA17 and BTA18 affecting MS were not detectable using medium SNP array genotypes. The allele substitution effects and additive genetic variances of the imputed variants followed a bell-shaped and a scaled inverse chi-squared distribution, respectively. Among functional categories, missense variants had the highest allele substitution effects for CW, MS and BFT, while 3′ UTR variants had higher effects for REA, compared to other functional classes. Our findings highlight the power of using imputation to perform GWAS and provide some valuable information for a better understanding of the underlying genetic background and architecture of carcass traits in beef cattle.","PeriodicalId":55120,"journal":{"name":"Genetics Selection Evolution","volume":"168 1","pages":""},"PeriodicalIF":3.1000,"publicationDate":"2025-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Genetics Selection Evolution","FirstCategoryId":"99","ListUrlMain":"https://doi.org/10.1186/s12711-025-00970-6","RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"AGRICULTURE, DAIRY & ANIMAL SCIENCE","Score":null,"Total":0}
引用次数: 0
Abstract
Carcass related traits are economically important traits for the beef industry, which affect quantity, quality and pricing of meat and farmers profitability. The current study was carried out to identify genomic regions associated with carcass traits including carcass weight (CW), marbling score (MS), rib-eye area (REA), and back fat thickness (BFT). Genome-wide association studies (GWAS) were performed using linear mixed models on 6,511,978 imputed whole genome sequence (WGS) variants in a population of 13,241 Angus beef cattle. The genetic architecture of the traits was evaluated based on the GWAS results. With a threshold of p-value < 3.96 × 10–7, 842, 745, 340, and 101 SNPs located in 13 genomic regions were significantly associated with CW, MS, REA, and BFT, respectively. While the majority of the identified quantitative trait loci (QTL) were trait-specific, two QTLs with pleiotropic effect were identified, including a QTL on BTA7 (88.25–91.96 Mb) affecting CW, MS and REA, and a QTL on BTA20 (4.55–5.01 Mb) affecting CW and BFT. Several important genes are harbored by the detected QTLs, which can be considered potential candidate genes for carcass traits in Angus beef cattle. Our findings also showed that higher density panels are more powerful in GWAS, such that the signals on BTA6 affecting CW, and two signals on BTA17 and BTA18 affecting MS were not detectable using medium SNP array genotypes. The allele substitution effects and additive genetic variances of the imputed variants followed a bell-shaped and a scaled inverse chi-squared distribution, respectively. Among functional categories, missense variants had the highest allele substitution effects for CW, MS and BFT, while 3′ UTR variants had higher effects for REA, compared to other functional classes. Our findings highlight the power of using imputation to perform GWAS and provide some valuable information for a better understanding of the underlying genetic background and architecture of carcass traits in beef cattle.
期刊介绍:
Genetics Selection Evolution invites basic, applied and methodological content that will aid the current understanding and the utilization of genetic variability in domestic animal species. Although the focus is on domestic animal species, research on other species is invited if it contributes to the understanding of the use of genetic variability in domestic animals. Genetics Selection Evolution publishes results from all levels of study, from the gene to the quantitative trait, from the individual to the population, the breed or the species. Contributions concerning both the biological approach, from molecular genetics to quantitative genetics, as well as the mathematical approach, from population genetics to statistics, are welcome. Specific areas of interest include but are not limited to: gene and QTL identification, mapping and characterization, analysis of new phenotypes, high-throughput SNP data analysis, functional genomics, cytogenetics, genetic diversity of populations and breeds, genetic evaluation, applied and experimental selection, genomic selection, selection efficiency, and statistical methodology for the genetic analysis of phenotypes with quantitative and mixed inheritance.