Li Wenran, Wang Meng, Sun Jinghao, Wang Yong, Jiang Rui
MOE Key Laboratory of Bioinformatics, Bioinformatics Division and Center for Synthetic & Systems Biology, TNLIST, Department of Automation, Tsinghua University, Beijing 100084, China.
Mol Biosyst. 2017 Oct 24;13(11):2428-2439. doi: 10.1039/c7mb00430c.
Genome sequencing technology has generated a vast amount of genomic and epigenomic data, and has provided us a great opportunity to study gene functions on a global scale from an epigenomic view. In the last decade, network-based studies, such as those based on PPI networks and co-expression networks, have shown good performance in capturing functional relationships between genes. However, the functions of a gene and the mechanism of interaction of genes with each other to elucidate their functions are still not entirely clear. Here, we construct a gene co-opening network based on chromatin accessibility of genes. We show that genes related to a specific biological process or the same disease tend to be clustered in the co-opening network. This understanding allows us to detect functional clusters from the network and to predict new functions for genes. We further apply the network to prioritize disease genes for Psoriasis, and demonstrate the power of the joint analysis of the co-opening network and GWAS data in identifying disease genes. Taken together, the co-opening network provides a new viewpoint for the elucidation of gene associations and the interpretation of disease mechanisms.
基因组测序技术已产生了大量的基因组和表观基因组数据，并为我们提供了一个从表观基因组角度在全球范围内研究基因功能的绝佳机会。在过去十年中，基于网络的研究，如基于蛋白质-蛋白质相互作用（PPI）网络和共表达网络的研究，在捕捉基因之间的功能关系方面表现出良好的性能。然而，基因的功能以及基因相互作用以阐明其功能的机制仍不完全清楚。在此，我们基于基因的染色质可及性构建了一个基因共开放网络。我们表明，与特定生物学过程或同一种疾病相关的基因倾向于在共开放网络中聚类。这种认识使我们能够从网络中检测功能簇并预测基因的新功能。我们进一步将该网络应用于对银屑病疾病基因进行优先级排序，并证明了共开放网络与全基因组关联研究（GWAS）数据联合分析在识别疾病基因方面的强大作用。综上所述，共开放网络为阐明基因关联和解释疾病机制提供了一个新的视角。
