Metabolic and Biomolecular Engineering National Research Laboratory, Department of Chemical and Biomolecular Engineering (BK21 Plus Program), Institute for the BioCentury, Korea Advanced Institute of Science and Technology (KAIST), Daejeon 34141, Republic of Korea.
BioInformatics Research Center, KAIST, Daejeon 34141, Republic of Korea.
Proc Natl Acad Sci U S A. 2017 Nov 7;114(45):E9740-E9749. doi: 10.1073/pnas.1713050114. Epub 2017 Oct 24.
Alternative splicing plays important roles in generating different transcripts from one gene, and consequently various protein isoforms. However, there has been no systematic approach that facilitates characterizing functional roles of protein isoforms in the context of the entire human metabolism. Here, we present a systematic framework for the generation of gene-transcript-protein-reaction associations (GeTPRA) in the human metabolism. The framework in this study generated 11,415 GeTPRA corresponding to 1,106 metabolic genes for both principal and nonprincipal transcripts (PTs and NPTs) of metabolic genes. The framework further evaluates GeTPRA, using a human genome-scale metabolic model (GEM) that is biochemically consistent and transcript-level data compatible, and subsequently updates the human GEM. A generic human GEM, Recon 2M.1, was developed for this purpose, and subsequently updated to Recon 2M.2 through the framework. Both PTs and NPTs of metabolic genes were considered in the framework based on prior analyses of 446 personal RNA-Seq data and 1,784 personal GEMs reconstructed using Recon 2M.1. The framework and the GeTPRA will contribute to better understanding human metabolism at the systems level and enable further medical applications.
可变剪接在从一个基因产生不同的转录本,进而产生各种蛋白质异构体方面发挥着重要作用。然而,目前还没有一种系统的方法可以方便地描述蛋白质异构体在整个人类代谢中的功能作用。在这里,我们提出了一个在人类代谢中生成基因-转录本-蛋白质-反应关联(GeTPRA)的系统框架。该框架共生成了 11415 个 GeTPRA,对应于代谢基因的主要和非主要转录本(PTs 和 NPTs)的 1106 个代谢基因。该框架进一步评估了 GeTPRA,使用了与生化一致且与转录水平数据兼容的人类基因组规模代谢模型(GEM),并随后更新了人类 GEM。为此目的开发了一个通用的人类 GEM,Recon 2M.1,并通过该框架更新到 Recon 2M.2。该框架基于对 446 个人 RNA-Seq 数据和使用 Recon 2M.1 重建的 1784 个人 GEM 的先前分析,考虑了代谢基因的 PTs 和 NPTs。该框架和 GeTPRA 将有助于更好地理解系统水平的人类代谢,并能够实现进一步的医学应用。