Liu Xianxian, Zhang Junjie, Xiong Xinwei, Chen Congying, Xing Yuyun, Duan Yanyu, Xiao Shijun, Yang Bin, Ma Junwu
State Key Laboratory of Pig Genetic Improvement and Production Technology, Jiangxi Agricultural University, Nanchang, China.
Front Genet. 2021 Oct 21;12:748070. doi: 10.3389/fgene.2021.748070. eCollection 2021.
Understanding the genetic factors behind meat quality traits is of great significance to animal breeding and production. We previously conducted a genome-wide association study (GWAS) for meat quality traits in a White Duroc × Erhualian F2 pig population using Illumina porcine 60K SNP data. Here, we further investigate the functional candidate genes and their network modules associated with meat quality traits by integrating transcriptomics and GWAS information. Quantitative trait transcript (QTT) analysis, gene expression QTL (eQTL) mapping, and weighted gene co-expression network analysis (WGCNA) were performed using the digital gene expression (DGE) data from 493 F2 pig's muscle and liver samples. Among the quantified 20,108 liver and 23,728 muscle transcripts, 535 liver and 1,014 muscle QTTs corresponding to 416 and 721 genes, respectively, were found to be significantly ( < 5 × 10) correlated with 22 meat quality traits measured on longissiums dorsi muscle (LM) or semimembranosus muscle (SM). Transcripts associated with muscle glycolytic potential (GP) and pH values were enriched for genes involved in metabolic process. There were 42 QTTs (for 32 genes) shared by liver and muscle tissues, of which 10 QTTs represent GP- and/or pH-related genes, such as , , and . Furthermore, a genome-wide eQTL mapping revealed a total of 3,054 eQTLs for all annotated transcripts in muscle ( < 2.08 × 10), including 1,283 -eQTLs and 1771 -eQTLs. In addition, WGCNA identified five modules relevant to glycogen metabolism pathway and highlighted the connections between variations in meat quality traits and genes involved in energy process. Integrative analysis of GWAS loci, eQTL, and QTT demonstrated and as strong candidate genes for drip loss and pH drop from postmortem 45 min to 24 h, respectively. Our findings provide valuable insights into the genetic basis of meat quality traits and greatly expand the number of candidate genes that may be valuable for future functional analysis and genetic improvement of meat quality.
了解肉质性状背后的遗传因素对动物育种和生产具有重要意义。我们之前利用Illumina猪60K SNP数据，对白杜洛克×二花脸F2猪群体的肉质性状进行了全基因组关联研究（GWAS）。在此，我们通过整合转录组学和GWAS信息，进一步研究与肉质性状相关的功能候选基因及其网络模块。使用来自493头F2猪的肌肉和肝脏样本的数字基因表达（DGE）数据进行数量性状转录本（QTT）分析、基因表达QTL（eQTL）定位和加权基因共表达网络分析（WGCNA）。在定量的20,108个肝脏转录本和23,728个肌肉转录本中，分别发现535个肝脏QTT和1,014个肌肉QTT与在背最长肌（LM）或半膜肌（SM）上测量的22个肉质性状显著相关（<5×10），这些QTT分别对应416个和721个基因。与肌肉糖酵解潜能（GP）和pH值相关的转录本富含参与代谢过程的基因。肝脏和肌肉组织共有42个QTT（对应32个基因），其中10个QTT代表与GP和/或pH相关的基因，如 、 和 。此外，全基因组eQTL定位揭示了肌肉中所有注释转录本共有3,054个eQTL（<2.08×10），包括1,283个顺式eQTL和1,771个反式eQTL。此外，WGCNA确定了与糖原代谢途径相关的五个模块，并突出了肉质性状变异与能量过程相关基因之间的联系。GWAS位点、eQTL和QTT的综合分析表明， 和 分别是宰后45分钟至24小时滴水损失和pH下降的强候选基因。我们的研究结果为肉质性状的遗传基础提供了有价值的见解，并大大扩展了可能对未来肉质功能分析和遗传改良有价值的候选基因数量。
