Department of Kinesiology, McMaster University, Hamilton, ON, Canada.
Center for Therapeutic Innovation, University of Miami Miller School of Medicine, Miami, FL, USA.
Cell Rep. 2020 Aug 4;32(5):107980. doi: 10.1016/j.celrep.2020.107980.
Loading of skeletal muscle changes the tissue phenotype reflecting altered metabolic and functional demands. In humans, heterogeneous adaptation to loading complicates the identification of the underpinning molecular regulators. A within-person differential loading and analysis strategy reduces heterogeneity for changes in muscle mass by ∼40% and uses a genome-wide transcriptome method that models each mRNA from coding exons and 3' and 5' untranslated regions (UTRs). Our strategy detects ∼3-4 times more regulated genes than similarly sized studies, including substantial UTR-selective regulation undetected by other methods. We discover a core of 141 genes correlated to muscle growth, which we validate from newly analyzed independent samples (n = 100). Further validating these identified genes via RNAi in primary muscle cells, we demonstrate that members of the core genes were regulators of protein synthesis. Using proteome-constrained networks and pathway analysis reveals notable relationships with the molecular characteristics of human muscle aging and insulin sensitivity, as well as potential drug therapies.
骨骼肌的加载会改变组织表型，反映出代谢和功能需求的变化。在人类中，加载的异质性适应使潜在分子调节剂的识别变得复杂。个体内的差异加载和分析策略可将肌肉质量变化的异质性降低约 40%，并采用一种全基因组转录组方法，该方法对每个来自编码外显子和 3' 和 5' 非翻译区 (UTR) 的 mRNA 进行建模。我们的策略检测到的调节基因比类似大小的研究多约 3-4 倍，包括其他方法无法检测到的大量 UTR 选择性调节。我们发现了与肌肉生长相关的 141 个核心基因，我们从新分析的独立样本（n=100）中对其进行了验证。通过在原代肌肉细胞中进行 RNAi 进一步验证这些鉴定出的基因，我们证明了核心基因的成员是蛋白质合成的调节剂。使用受蛋白质组限制的网络和通路分析揭示了与人类肌肉衰老和胰岛素敏感性的分子特征以及潜在药物治疗的显著关系。
