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Genome Res:美学者发表基因表达研究进展

摘要 : 近日,国际著名学术期刊《Genome Research》杂志在线发表了达纳-法伯癌症研究所刘小乐教授的一项研究,证明了将一个大的表观遗传学数据库整合到转录调控基因组学研究中的优势。

近日,国际著名学术期刊《Genome Research》杂志在线发表了达纳-法伯癌症研究所刘小乐教授的一项研究,证明了将一个大的表观遗传学数据库整合到转录调控基因组学研究中的优势。

研究指出,基于模型的基因表达调控分析(MARGE),是解释H3K27ac染色质环境与差异表达基因集合之间关系的一个框架。该框架有三个主要功能:MARGE-potential、MARGE-express和MARGE-cistrome。MARGE-potential将每一个基因的一个调控potential (RP)定义为H3K27ac ChIP-seq信号的总和,按“从转录起始位点的基因组距离的功能”计算。MARGE框架包括来自365个人的RPs集合。

使用这个数据集按比例确定的相对RPs,优于预测BET((bromodomain and extraterminal结构域)-抑制剂抑制基因中的超级增强子。MARGE-express,采用逻辑回归来检索来自数据集的相关H3K27ac属性,以精确地模仿一组输入的差异表达基因,在来自MSigDB的671个不同基因集合上进行了检测。MARGE-cistrome采用一种新型半监督学习方法,来确定调节一个基因集合的顺式调控元件。MARGE-cistrome采用来自DNase I超敏位点上的H3K27ac信号的信息,这些位点是从已公布的人类和小鼠DNase-seq数据中确定而来的。

在前列腺癌细胞系(LNCaP-abl)中多个转录和表观遗传学调节因子的siRNA调控之后,该研究小组在新生成的rna-seq和H3K27ac ChIP-seq文件上测试了该框架。MARGE-cistrome可以预测沉默的转录因子的结合位点,不必与H3K27ac ChIP-seq数据匹配。即使当匹配的H3K27ac ChIP-seq文件是可用的时候,MARGE也可能用公共H3K27ac文件来增强这些数据。这项研究展示了将一个大的表观遗传学数据集合,整合到转录调节基因组研究中的优势。

原文链接:

Modeling cis-regulation with a compendium of genome-wide histone H3K27ac profiles

原文摘要:

Model-based analysis of regulation of gene expression (MARGE) is a framework for interpreting the relationship between the H3K27ac chromatin environment and differentially expressed gene sets. The framework has three main functions: MARGE-potential, MARGE-express, and MARGE-cistrome. MARGE-potential defines a regulatory potential (RP) for each gene as the sum of H3K27ac ChIP-seq signals weighted by a function of genomic distance from the transcription start site. The MARGE framework includes a compendium of RPs derived from 365 human and 267 mouse H3K27ac ChIP-seq data sets. Relative RPs, scaled using this compendium, are superior to superenhancers in predicting BET (bromodomain and extraterminal domain) -inhibitor repressed genes. MARGE-express, which uses logistic regression to retrieve relevant H3K27ac profiles from the compendium to accurately model a query set of differentially expressed genes, was tested on 671 diverse gene sets from MSigDB. MARGE-cistrome adopts a novel semisupervised learning approach to identify cis-regulatory elements regulating a gene set. MARGE-cistrome exploits information from H3K27ac signal at DNase I hypersensitive sites identified from published human and mouse DNase-seq data. We tested the framework on newly generated RNA-seq and H3K27ac ChIP-seq profiles upon siRNA silencing of multiple transcriptional and epigenetic regulators in a prostate cancer cell line, LNCaP-abl. MARGE-cistrome can predict the binding sites of silenced transcription factors without matched H3K27ac ChIP-seq data. Even when the matching H3K27ac ChIP-seq profiles are available, MARGE leverages public H3K27ac profiles to enhance these data. This study demonstrates the advantage of integrating a large compendium of historical epigenetic data for genomic studies of transcriptional regulation.

doi:10.1101/gr.201574.115

作者:刘小乐 点击:

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