Department of Computational Mathematics, Science and Engineering, Michigan State University, 428 S. Shaw Ln., East Lansing, MI 48824, USA.
Center for Immunobiology, Department of Investigative Medicine, Western Michigan University Homer Stryker M.D. School of Medicine, 300 Portage St., Kalamazoo, MI 49007, USA.
Methods. 2021 May;189:22-33. doi: 10.1016/j.ymeth.2020.10.010. Epub 2020 Oct 21.
Identifying genes and non-coding genetic variants that are genetically associated with complex diseases and the underlying mechanisms is one of the most important questions in functional genomics. Due to the limited statistical power and the lack of mechanistic modeling, traditional genome-wide association studies (GWAS) is restricted to fully address this question. Based on multi-omics data integration, cell-type specific regulatory networks can be built to improve GWAS analysis. In this study, we developed a new computational infrastructure, APRIL, to incorporate 3D chromatin interactions into regulatory network construction, which can extend the networks to include long-range cis-regulatory links between non-coding GWAS SNPs and target genes. Combinatorial transcription factors that co-regulate groups of genes are also inferred to further expand the networks with trans-regulation. A suite of machine learning predictions and statistical tests are incorporated in APRIL to predict novel disease-associated genes based on the expanded regulatory networks. Important features of non-coding regulatory elements and genetic variants are prioritized in network-based predictions, providing systems-level insights on the mechanisms of transcriptional dysregulation associated with complex diseases.
鉴定与复杂疾病相关的基因和非编码遗传变异，并阐明其潜在机制，是功能基因组学中最重要的问题之一。由于统计能力有限且缺乏机制建模，传统的全基因组关联研究（GWAS）难以完全解决这个问题。基于多组学数据整合，可以构建细胞类型特异性调控网络来改进 GWAS 分析。在这项研究中，我们开发了一种新的计算基础设施 APRIL，将 3D 染色质相互作用纳入调控网络构建中，从而可以扩展网络，包括非编码 GWAS SNPs 与靶基因之间的长距离顺式调控联系。还推断了共同调控基因群的组合转录因子，以通过转调控进一步扩展网络。APRIL 中整合了一系列机器学习预测和统计测试，以便基于扩展的调控网络来预测新的疾病相关基因。在基于网络的预测中，对非编码调控元件和遗传变异的重要特征进行优先级排序，为与复杂疾病相关的转录失调机制提供系统层面的见解。
