Xie Lei, Qin Jiangtao, Rao Lin, Cui Dengshuai, Tang Xi, Chen Liqing, Xiao Shijun, Zhang Zhiyan, Huang Lusheng
State Key Laboratory for Pig Genetic Improvement and Production Technology, Jiangxi Agricultural University, Nanchang, 330045, China.
J Anim Sci Biotechnol. 2023 Sep 3;14(1):116. doi: 10.1186/s40104-023-00914-4.
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.
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.
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.
随着预切和预包装冷藏肉越来越受欢迎,将胴体切割过程融入生猪产业链已成为一种趋势。识别猪肉切块的数量性状位点(QTL)将有助于选择具有更高总体价值的猪。然而,以往的研究仅专注于评估猪肉切块的表型和遗传参数,而忽略了对影响这些性状的QTL的研究。本研究涉及来自四个群体的2012头猪的17种猪肉切块和12种形态性状,使用CC1猪SNP50芯片进行基因分型。我们的目的是识别QTL并评估猪肉切块的基因组估计育种值(GEBV)的准确性。
我们分别使用单倍型和填充基因型通过全基因组关联研究(GWAS)为17种猪肉切块鉴定了14个QTL和112个QTL。具体而言,我们发现HMGA1、VRTN和BMP2与体长和体重相关。随后的分析表明,HMGA1主要影响前腿骨的大小,VRTN主要影响脊椎骨的数量,BMP2主要影响椎骨的长度和后腿骨的大小。预测准确性定义为验证群体中调整后的表型与GEBV之间的相关性除以性状遗传力的平方根。猪肉切块的GEBV预测准确性在0.342至0.693之间变化。值得注意的是,肋骨、去骨野餐肩、里脊肉、后腿骨和肩胛骨的预测准确性超过0.600。采用更好的模型、通过基因型填充增加标记密度以及预先选择标记显著提高了GEBV的预测准确性。
我们进行了首次研究以剖析猪肉切块的遗传机制,并鉴定了大量显著的QTL和潜在候选基因。这些发现对通过标记辅助和基因组选择进行猪肉切块育种具有重要意义。此外,我们构建了首个用于猪基因组选择猪肉切块的参考群体。