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Genetic dissection and genomic prediction for pork cuts and carcass morphology traits in pig

BACKGROUND: As pre-cut and pre-packaged chilled meat becomes increasingly popular, integrating the carcass-cutting process into the pig industry chain has become a trend. Identifying quantitative trait loci (QTLs) of pork cuts would facilitate the selection of pigs with a higher overall value. Howev...

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Autores principales: Xie, Lei, Qin, Jiangtao, Rao, Lin, Cui, Dengshuai, Tang, Xi, Chen, Liqing, Xiao, Shijun, Zhang, Zhiyan, Huang, Lusheng
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10475202/
https://www.ncbi.nlm.nih.gov/pubmed/37660101
http://dx.doi.org/10.1186/s40104-023-00914-4
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author Xie, Lei
Qin, Jiangtao
Rao, Lin
Cui, Dengshuai
Tang, Xi
Chen, Liqing
Xiao, Shijun
Zhang, Zhiyan
Huang, Lusheng
author_facet Xie, Lei
Qin, Jiangtao
Rao, Lin
Cui, Dengshuai
Tang, Xi
Chen, Liqing
Xiao, Shijun
Zhang, Zhiyan
Huang, Lusheng
author_sort Xie, Lei
collection PubMed
description BACKGROUND: As pre-cut and pre-packaged chilled meat becomes increasingly popular, integrating the carcass-cutting process into the pig industry chain has become a trend. Identifying quantitative trait loci (QTLs) of pork cuts would facilitate the selection of pigs with a higher overall value. However, previous studies solely focused on evaluating the phenotypic and genetic parameters of pork cuts, neglecting the investigation of QTLs influencing these traits. This study involved 17 pork cuts and 12 morphology traits from 2,012 pigs across four populations genotyped using CC1 PorcineSNP50 BeadChips. Our aim was to identify QTLs and evaluate the accuracy of genomic estimated breed values (GEBVs) for pork cuts. RESULTS: We identified 14 QTLs and 112 QTLs for 17 pork cuts by GWAS using haplotype and imputation genotypes, respectively. Specifically, we found that HMGA1, VRTN and BMP2 were associated with body length and weight. Subsequent analysis revealed that HMGA1 primarily affects the size of fore leg bones, VRTN primarily affects the number of vertebrates, and BMP2 primarily affects the length of vertebrae and the size of hind leg bones. The prediction accuracy was defined as the correlation between the adjusted phenotype and GEBVs in the validation population, divided by the square root of the trait's heritability. The prediction accuracy of GEBVs for pork cuts varied from 0.342 to 0.693. Notably, ribs, boneless picnic shoulder, tenderloin, hind leg bones, and scapula bones exhibited prediction accuracies exceeding 0.600. Employing better models, increasing marker density through genotype imputation, and pre-selecting markers significantly improved the prediction accuracy of GEBVs. CONCLUSIONS: We performed the first study to dissect the genetic mechanism of pork cuts and identified a large number of significant QTLs and potential candidate genes. These findings carry significant implications for the breeding of pork cuts through marker-assisted and genomic selection. Additionally, we have constructed the first reference populations for genomic selection of pork cuts in pigs. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s40104-023-00914-4.
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spelling pubmed-104752022023-09-04 Genetic dissection and genomic prediction for pork cuts and carcass morphology traits in pig Xie, Lei Qin, Jiangtao Rao, Lin Cui, Dengshuai Tang, Xi Chen, Liqing Xiao, Shijun Zhang, Zhiyan Huang, Lusheng J Anim Sci Biotechnol Research BACKGROUND: As pre-cut and pre-packaged chilled meat becomes increasingly popular, integrating the carcass-cutting process into the pig industry chain has become a trend. Identifying quantitative trait loci (QTLs) of pork cuts would facilitate the selection of pigs with a higher overall value. However, previous studies solely focused on evaluating the phenotypic and genetic parameters of pork cuts, neglecting the investigation of QTLs influencing these traits. This study involved 17 pork cuts and 12 morphology traits from 2,012 pigs across four populations genotyped using CC1 PorcineSNP50 BeadChips. Our aim was to identify QTLs and evaluate the accuracy of genomic estimated breed values (GEBVs) for pork cuts. RESULTS: We identified 14 QTLs and 112 QTLs for 17 pork cuts by GWAS using haplotype and imputation genotypes, respectively. Specifically, we found that HMGA1, VRTN and BMP2 were associated with body length and weight. Subsequent analysis revealed that HMGA1 primarily affects the size of fore leg bones, VRTN primarily affects the number of vertebrates, and BMP2 primarily affects the length of vertebrae and the size of hind leg bones. The prediction accuracy was defined as the correlation between the adjusted phenotype and GEBVs in the validation population, divided by the square root of the trait's heritability. The prediction accuracy of GEBVs for pork cuts varied from 0.342 to 0.693. Notably, ribs, boneless picnic shoulder, tenderloin, hind leg bones, and scapula bones exhibited prediction accuracies exceeding 0.600. Employing better models, increasing marker density through genotype imputation, and pre-selecting markers significantly improved the prediction accuracy of GEBVs. CONCLUSIONS: We performed the first study to dissect the genetic mechanism of pork cuts and identified a large number of significant QTLs and potential candidate genes. These findings carry significant implications for the breeding of pork cuts through marker-assisted and genomic selection. Additionally, we have constructed the first reference populations for genomic selection of pork cuts in pigs. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s40104-023-00914-4. BioMed Central 2023-09-03 /pmc/articles/PMC10475202/ /pubmed/37660101 http://dx.doi.org/10.1186/s40104-023-00914-4 Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
spellingShingle Research
Xie, Lei
Qin, Jiangtao
Rao, Lin
Cui, Dengshuai
Tang, Xi
Chen, Liqing
Xiao, Shijun
Zhang, Zhiyan
Huang, Lusheng
Genetic dissection and genomic prediction for pork cuts and carcass morphology traits in pig
title Genetic dissection and genomic prediction for pork cuts and carcass morphology traits in pig
title_full Genetic dissection and genomic prediction for pork cuts and carcass morphology traits in pig
title_fullStr Genetic dissection and genomic prediction for pork cuts and carcass morphology traits in pig
title_full_unstemmed Genetic dissection and genomic prediction for pork cuts and carcass morphology traits in pig
title_short Genetic dissection and genomic prediction for pork cuts and carcass morphology traits in pig
title_sort genetic dissection and genomic prediction for pork cuts and carcass morphology traits in pig
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10475202/
https://www.ncbi.nlm.nih.gov/pubmed/37660101
http://dx.doi.org/10.1186/s40104-023-00914-4
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