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使用奥恩斯坦-乌伦贝克模型鉴定与转录因子结合和染色质活性变化相关的谱系特异性顺式调控模块

Identification of Lineage-Specific Cis-Regulatory Modules Associated with Variation in Transcription Factor Binding and Chromatin Activity Using Ornstein-Uhlenbeck Models.

作者信息

Naval-Sánchez Marina, Potier Delphine, Hulselmans Gert, Christiaens Valerie, Aerts Stein

机构信息

Laboratory of Computational Biology, Department of Human Genetics, University of Leuven, Leuven, Belgium.

Laboratory of Computational Biology, Department of Human Genetics, University of Leuven, Leuven, Belgium

出版信息

Mol Biol Evol. 2015 Sep;32(9):2441-55. doi: 10.1093/molbev/msv107. Epub 2015 May 4.

Abstract

Scoring the impact of noncoding variation on the function of cis-regulatory regions, on their chromatin state, and on the qualitative and quantitative expression levels of target genes is a fundamental problem in evolutionary genomics. A particular challenge is how to model the divergence of quantitative traits and to identify relationships between the changes across the different levels of the genome, the chromatin activity landscape, and the transcriptome. Here, we examine the use of the Ornstein-Uhlenbeck (OU) model to infer selection at the level of predicted cis-regulatory modules (CRMs), and link these with changes in transcription factor binding and chromatin activity. Using publicly available cross-species ChIP-Seq and STARR-Seq data we show how OU can be applied genome-wide to identify candidate transcription factors for which binding site and CRM turnover is correlated with changes in regulatory activity. Next, we profile open chromatin in the developing eye across three Drosophila species. We identify the recognition motifs of the chromatin remodelers, Trithorax-like and Grainyhead as mostly correlating with species-specific changes in open chromatin. In conclusion, we show in this study that CRM scores can be used as quantitative traits and that motif discovery approaches can be extended towards more complex models of divergence.

摘要

评估非编码变异对顺式调控区域功能、其染色质状态以及靶基因定性和定量表达水平的影响是进化基因组学中的一个基本问题。一个特别的挑战是如何对数量性状的差异进行建模,以及如何识别基因组不同水平、染色质活性景观和转录组之间变化的关系。在这里,我们研究了使用奥恩斯坦 - 乌伦贝克(OU)模型在预测的顺式调控模块(CRM)水平上推断选择,并将这些与转录因子结合和染色质活性的变化联系起来。利用公开可用的跨物种ChIP-Seq和STARR-Seq数据,我们展示了OU如何在全基因组范围内应用,以识别其结合位点和CRM周转率与调控活性变化相关的候选转录因子。接下来,我们分析了三种果蝇物种发育中的眼睛中的开放染色质。我们确定染色质重塑因子Trithorax-like和Grainyhead的识别基序大多与开放染色质中的物种特异性变化相关。总之,我们在本研究中表明,CRM评分可以用作数量性状,并且基序发现方法可以扩展到更复杂的差异模型。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d70a/4540964/bc03283e424c/msv107f1p.jpg

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