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从 DNA 序列和染色质可及性数据中准确推断转录因子结合。

Accurate inference of transcription factor binding from DNA sequence and chromatin accessibility data.

机构信息

Department of Human Genetics, University of Chicago, Chicago, Illinois 60637, USA.

出版信息

Genome Res. 2011 Mar;21(3):447-55. doi: 10.1101/gr.112623.110. Epub 2010 Nov 24.

Abstract

Accurate functional annotation of regulatory elements is essential for understanding global gene regulation. Here, we report a genome-wide map of 827,000 transcription factor binding sites in human lymphoblastoid cell lines, which is comprised of sites corresponding to 239 position weight matrices of known transcription factor binding motifs, and 49 novel sequence motifs. To generate this map, we developed a probabilistic framework that integrates cell- or tissue-specific experimental data such as histone modifications and DNase I cleavage patterns with genomic information such as gene annotation and evolutionary conservation. Comparison to empirical ChIP-seq data suggests that our method is highly accurate yet has the advantage of targeting many factors in a single assay. We anticipate that this approach will be a valuable tool for genome-wide studies of gene regulation in a wide variety of cell types or tissues under diverse conditions.

摘要

准确的调控元件功能注释对于理解全局基因调控至关重要。在这里,我们报告了人类淋巴母细胞系中 827,000 个转录因子结合位点的全基因组图谱,其中包括对应于已知转录因子结合基序的 239 个位置权重矩阵和 49 个新的序列基序。为了生成这个图谱,我们开发了一个概率框架,该框架整合了细胞或组织特异性的实验数据,如组蛋白修饰和 DNase I 切割模式,以及基因组信息,如基因注释和进化保守性。与经验性 ChIP-seq 数据的比较表明,我们的方法具有高度准确性,并且具有在单个测定中靶向许多因子的优势。我们预计,这种方法将成为在各种条件下对各种细胞类型或组织中的基因调控进行全基因组研究的有价值的工具。

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