通过预测扰乱基因表达谱的染色质可及性变化来识别药物反应增强子。

IF 3.5 2区 生物学 Q1 MATHEMATICAL & COMPUTATIONAL BIOLOGY
Yongcui Wang, Yong Wang
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引用次数: 0

摘要

由于增强子中的基因变异,个体对药物治疗的反应可能不同。这些变异可改变转录因子(TF)的结合强度,影响增强子的染色质活性或相互作用,并最终改变下游基因的表达水平。在这里,我们提出了一个预测增强子对药物反应的计算框架--PERD。我们利用从 ENCODE 和 ROADMAP 收集的成对表达和染色质可及性数据,训练了一个机器学习模型来预测转录组数据中的全基因组染色质可及性。然后,将该模型应用于连接图(CMAP)和癌症药物诱导基因表达特征数据库(CDS-DB)中的扰动基因表达数据,并识别出染色质可及性发生显著改变的药物反应性增强子。此外,药物反应增强子还与药物基因组学全基因组关联研究(PGx GWAS)有关。在传统药物相关基因特征的基础上,PERD有望通过提供药物相关基因的候选调控元件来增强药物扰动的因果关系。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Identification of drug responsive enhancers by predicting chromatin accessibility change from perturbed gene expression profiles.

Identification of drug responsive enhancers by predicting chromatin accessibility change from perturbed gene expression profiles.

Individual may response to drug treatment differently due to their genetic variants located in enhancers. These variants can alter transcription factor's (TF) binding strength, affect enhancer's chromatin activity or interaction, and eventually change expression level of downstream gene. Here, we propose a computational framework, PERD, to Predict the Enhancers Responsive to Drug. A machine learning model was trained to predict the genome-wide chromatin accessibility from transcriptome data using the paired expression and chromatin accessibility data collected from ENCODE and ROADMAP. Then the model was applied to the perturbed gene expression data from Connectivity Map (CMAP) and Cancer Drug-induced gene expression Signature DataBase (CDS-DB) and identify drug responsive enhancers with significantly altered chromatin accessibility. Furthermore, the drug responsive enhancers were related to the pharmacogenomics genome-wide association studies (PGx GWAS). Stepping on the traditional drug-associated gene signatures, PERD holds the promise to enhance the causality of drug perturbation by providing candidate regulatory element of those drug associated genes.

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来源期刊
NPJ Systems Biology and Applications
NPJ Systems Biology and Applications Mathematics-Applied Mathematics
CiteScore
5.80
自引率
0.00%
发文量
46
审稿时长
8 weeks
期刊介绍: npj Systems Biology and Applications is an online Open Access journal dedicated to publishing the premier research that takes a systems-oriented approach. The journal aims to provide a forum for the presentation of articles that help define this nascent field, as well as those that apply the advances to wider fields. We encourage studies that integrate, or aid the integration of, data, analyses and insight from molecules to organisms and broader systems. Important areas of interest include not only fundamental biological systems and drug discovery, but also applications to health, medical practice and implementation, big data, biotechnology, food science, human behaviour, broader biological systems and industrial applications of systems biology. We encourage all approaches, including network biology, application of control theory to biological systems, computational modelling and analysis, comprehensive and/or high-content measurements, theoretical, analytical and computational studies of system-level properties of biological systems and computational/software/data platforms enabling such studies.
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