Bivariate GWAS performed on rabbits divergently selected for intramuscular fat content reveals pleiotropic genomic regions and genes related to meat and carcass quality traits

对肌内脂肪含量差异选择的兔子进行双变量全基因组关联分析(GWAS),揭示了与肉质和胴体品质性状相关的多效性基因组区域和基因。

阅读:1

Abstract

BACKGROUND: Meat quality plays an important economic role in the meat industry and livestock breeding programmes. Intramuscular fat content (IMF) is one of the main meat quality parameters and its genetic improvement has led breeders to investigate its genomic architecture and correlation with other relevant traits. Genetic markers associated with causal variants for these traits can be identified by bivariate analyses. In this study, we used two rabbit lines divergently selected for IMF to perform bivariate GWAS with the aim of detecting pleiotropic genomic regions between IMF and several weight, fat, and meat quality traits. Additionally, whole-genome sequencing data from these lines were used to identify potential causal variants associated with the genetic markers. RESULTS: The main pleiotropic region was found on Oryctolagus cuniculus chromosome (OCC) 1 between 35.4 Mb and 38.2 Mb, explaining up to 2.66% of the IMF genetic variance and being associated with all traits analysed, except muscle lightness. In this region, the potentially causal variants found pointed to PLIN2, SH3GL2, CNTLN, and BNC2 as the main candidate genes affecting the different weight, fat depots and meat quality traits. Other relevant pleiotropic regions found were those on OCC3 (148.94-150.89 Mb) and on OCC7 (27.07-28.44 Mb). The first was associated with all fat depot traits and explained the highest percentage of genetic variance, up to 10.90% for scapular fat. Several allelic variants were found in this region, all located in the novel gene ENSOCUG00000000157 (orthologous to ST3GAL1 in other species), involved in lipid metabolism, suggesting it as the main candidate affecting fat deposition. The region on OCC7 was associated with most meat quality traits and explained 8.48% of the genetic variance for pH. No allele variants were found to segregate differently between the lines in this region; however, it remains a promising region for future functional studies. CONCLUSIONS: Our results showed that bivariate models assuming pleiotropic effects are valuable tools to identify genomic regions simultaneously associated with IMF and several weight, fat and meat quality traits. Overall, our results provided relevant insights into the correlations and relationships between traits at the genomic level, together with potential functional mutations, which would be relevant for exploration in rabbit and other livestock breeding programmes.

特别声明

1、本页面内容包含部分的内容是基于公开信息的合理引用;引用内容仅为补充信息,不代表本站立场。

2、若认为本页面引用内容涉及侵权,请及时与本站联系,我们将第一时间处理。

3、其他媒体/个人如需使用本页面原创内容,需注明“来源:[生知库]”并获得授权;使用引用内容的,需自行联系原作者获得许可。

4、投稿及合作请联系:info@biocloudy.com。