Identification of key lncRNAs and mRNAs related intramuscular fat in pigs by WGCNA

Wenqiang Li, Suozhou Yang, Huixin Liu, Zhi Cao, Fei Xu, Chao Ning, Qin Zhang, Dan Wang, Hui Tang
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Abstract

Abstract Background: Intramuscular fat (IMF) is an important indicator of pork quality, whose content directly affects the tenderness, juiciness and other flavour traits of pork, and it also influences consumers' choice of pork. Long non-coding RNA (lncRNA) plays an important role as key regulators in IMF deposition, but its function and characteristics in IMF deposition are not fully understood. Weighted gene co-expression network analysis (WGCNA) is an accurate and powerful method for studying gene interactions of quantitative traits, but so far, there is no report on weighted gene co-expression network analysis on the regulation of fat deposition in porcine muscle based on both mRNA and lncRNA datasets. Therefore, this study aimed to construct an mRNA-lncRNA co-expression network using WGCNA to mine and identify potential candidate genes affecting IMF deposition in pigs. Results: We used whole-transcriptome sequencing data generated from 31 longest dorsal muscle tissues of Yimeng Black pigs to construct a gene expression matrix containing 8093 mRNAs and 198 lncRNAs. A total of nine co-expression modules were identified using the WGCNA method, of which the magenta and turquoise modules were significantly associated with IMF deposition. We identified 15 mRNAs and 4 lncRNAs as key genes that might play an important role in the regulation of IMF deposition. Conclusions: This study used WGCNA to construct a lncRNA-mRNA co-expression network and reveal key genes that regulate intramuscular fat deposition and to construct lncRNA-mRNA-pathway network. We provided new insights into the complex biology of IMF deposition in pigs and may help to improve pork quality.
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WGCNA鉴定猪肌内脂肪相关的关键lncrna和mrna
摘要背景:肌内脂肪(IMF)是猪肉品质的重要指标,其含量直接影响猪肉的嫩度、多汁性等风味性状,也影响着消费者对猪肉的选择。长链非编码RNA (Long non-coding RNA, lncRNA)在IMF沉积中起着重要的调控作用,但其在IMF沉积中的功能和特征尚不完全清楚。加权基因共表达网络分析(Weighted gene co-expression network analysis, WGCNA)是研究数量性状基因相互作用的一种准确而有力的方法,但迄今为止,基于mRNA和lncRNA数据集对猪肌肉脂肪沉积调控的加权基因共表达网络分析尚未见报道。因此,本研究旨在利用WGCNA构建mRNA-lncRNA共表达网络,挖掘和鉴定影响猪体内IMF沉积的潜在候选基因。结果:利用31只沂蒙黑猪最长背肌组织的全转录组测序数据,构建了包含8093个mrna和198个lncrna的基因表达矩阵。使用WGCNA方法共鉴定了9个共表达模块,其中品红和绿松石色模块与IMF沉积显著相关。我们鉴定出15个mrna和4个lncrna作为可能在调控IMF沉积中发挥重要作用的关键基因。结论:本研究利用WGCNA构建了lncRNA-mRNA共表达网络,揭示了调控肌内脂肪沉积的关键基因,构建了lncRNA-mRNA通路网络。我们为猪体内IMF沉积的复杂生物学提供了新的见解,可能有助于提高猪肉品质。
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