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Identification of Common Regulators of Genes in Co-Expression Networks Affecting Muscle and Meat Properties

机译:共同表达网络中影响肌肉和肉类特性的基因的常见调控因子的鉴定

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摘要

Understanding the genetic contributions behind skeletal muscle composition and metabolism is of great interest in medicine and agriculture. Attempts to dissect these complex traits combine genome-wide genotyping, expression data analyses and network analyses. Weighted gene co-expression network analysis (WGCNA) groups genes into modules based on patterns of co-expression, which can be linked to phenotypes by correlation analysis of trait values and the module eigengenes, i.e. the first principal component of a given module. Network hub genes and regulators of the genes in the modules are likely to play an important role in the emergence of respective traits. In order to detect common regulators of genes in modules showing association with meat quality traits, we identified eQTL for each of these genes, including the highly connected hub genes. Additionally, the module eigengene values were used for association analyses in order to derive a joint eQTL for the respective module. Thereby major sites of orchestrated regulation of genes within trait-associated modules were detected as hotspots of eQTL of many genes of a module and of its eigengene. These sites harbor likely common regulators of genes in the modules. We exemplarily showed the consistent impact of candidate common regulators on the expression of members of respective modules by RNAi knockdown experiments. In fact, Cxcr7 was identified and validated as a regulator of genes in a module, which is involved in the function of defense response in muscle cells. Zfp36l2 was confirmed as a regulator of genes of a module related to cell death or apoptosis pathways. The integration of eQTL in module networks enabled to interpret the differentially-regulated genes from a systems perspective. By integrating genome-wide genomic and transcriptomic data, employing co-expression and eQTL analyses, the study revealed likely regulators that are involved in the fine-tuning and synchronization of genes with trait-associated expression.
机译:在医学和农业领域,了解骨骼肌成分和代谢背后的遗传贡献非常重要。剖析这些复杂特征的尝试结合了全基因组基因分型,表达数据分析和网络分析。加权基因共表达网络分析(WGCNA)基于共表达模式将基因分为模块,可通过特征值与模块特征基因(即给定模块的第一个主要成分)的相关分析将其与表型联系起来。网络中心基因和模块中基因的调节剂可能在各自性状的出现中起重要作用。为了检测与肉品质性状相关的模块中基因的常见调节子,我们为每个基因鉴定了eQTL,包括高度连接的中枢基因。另外,模块本征值被用于关联分析,以便得出各个模块的联合eQTL。因此,性状相关模块内基因的协调调控的主要位点被检测为模块及其本征基因的许多基因的eQTL热点。这些位点可能在模块中包含基因的共同调节物。我们通过RNAi敲低实验示例性地显示了候选通用调节剂对各个模块成员表达的一致影响。实际上,Cxcr7被鉴定并确认为模块中基因的调节剂,该模块参与了肌肉细胞防御反应的功能。 Zfp36l2被确认为与细胞死亡或细胞凋亡途径相关的模块基因的调节剂。 eQTL在模块网络中的集成能够从系统角度解释差异调节基因。通过整合全基因组的基因组和转录组数据,采用共表达和eQTL分析,该研究揭示了可能的调节子,它们参与了与性状相关表达的基因的微调和同步。

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