ArticleJournal of animal science and biotechnology2023
Genetic dissection and genomic prediction for pork cuts and carcass morphology traits in pig.
Article in Journal of animal science and biotechnology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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Who cites it
8 citing papers in PubMed, 10 citations in OpenAlex.
- CT scanning technology to asses the genetic and phenotypic correlations, and selection potential of carcass traits in mutton sheep.Animal bioscience · 2026Article
- Review
- Metabolomic, lipidomic and transcriptomic profiles provide insights into meat quality differences among four pork cuts.BMC genomics · 2025Article
- Comparative phosphoproteomics provides insights into the differences of porcineFood chemistry. Molecular sciences · 2025Article
- Multi-omics integration reveals Chr1 associated QTL mediating backfat thickness in pigs.Journal of animal science and biotechnology · 2025Article
- Latitude-driven adaptive evolution of body length in diverse pig breeds across China.BMC biology · 2025Article
- Identification of Gene Expression and Splicing QTLs in Porcine Muscle Associated with Meat Quality Traits.Animals : an open access journal from MDPI · 2025Article
- Advancements in Genetic Marker Exploration for Livestock Vertebral Traits with a Focus on China.Animals : an open access journal from MDPI · 2024Review
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Authors and funding
9 authors at 1 institution in 1 country.
Funding
Abstract
backgroundAs 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.
resultsWe 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.
conclusionsWe 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.
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