Predicting cell-type-specific gene expression from regions of open chromatin.
Predicting cell-type-specific gene expression from regions of open chromatin.
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DOI：
10.1101/gr.135129.111
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发表时间：
2012-09
期刊：
影响因子：
7
通讯作者：
Ohler U
中科院分区：
文献类型：
--
作者：
Natarajan A;Yardimci GG;Sheffield NC;Crawford GE;Ohler U
细胞类型特异性基因表达的复杂模式被认为是通过转录因子（TF）与调控区序列元件的组合结合来实现的。预测哺乳动物中细胞类型特异性表达一直受到远端调控区位置未知的阻碍。为了缓解这一瓶颈，我们使用了来自19种不同人类细胞类型的DNase-seq数据，以在全基因组范围内识别近端和远端调控元件。匹配的表达数据使我们能够将基因分为细胞类型特异性上调、下调和组成型表达的基因。CG二核苷酸含量和DNA的可及性在这三类基因的启动子显示出很大的差异，突出了包括这些方面的建模基因表达的重要性。我们将DNA酶I超敏位点（DHS）与基因相关联，并为不同的表达模式训练分类器。与使用近端启动子序列的典型基线方法相比，DHS中的TF序列基序匹配在预测基因表达方面提供了强大的性能改进。特别是，当区分来自不同细胞类型的上调基因或在相同条件下上调和下调的基因时，我们实现了竞争性能。我们确定了以前已知的和新的候选细胞类型特异性调节剂。该模型产生的监管机构的激活或抑制功能的可测试的预测。这些调节剂的DNA酶I足迹指示它们与DNA的直接结合。总之，我们成功地使用了开放染色质的信息，通过一个单一的测定，DNase-seq，以解决预测细胞类型特异性基因表达的问题，在哺乳动物生物体中直接从调控序列。
Complex patterns of cell-type–specific gene expression are thought to be achieved by combinatorial binding of transcription factors (TFs) to sequence elements in regulatory regions. Predicting cell-type–specific expression in mammals has been hindered by the oftentimes unknown location of distal regulatory regions. To alleviate this bottleneck, we used DNase-seq data from 19 diverse human cell types to identify proximal and distal regulatory elements at genome-wide scale. Matched expression data allowed us to separate genes into classes of cell-type–specific up-regulated, down-regulated, and constitutively expressed genes. CG dinucleotide content and DNA accessibility in the promoters of these three classes of genes displayed substantial differences, highlighting the importance of including these aspects in modeling gene expression. We associated DNase I hypersensitive sites (DHSs) with genes, and trained classifiers for different expression patterns. TF sequence motif matches in DHSs provided a strong performance improvement in predicting gene expression over the typical baseline approach of using proximal promoter sequences. In particular, we achieved competitive performance when discriminating up-regulated genes from different cell types or genes up- and down-regulated under the same conditions. We identified previously known and new candidate cell-type–specific regulators. The models generated testable predictions of activating or repressive functions of regulators. DNase I footprints for these regulators were indicative of their direct binding to DNA. In summary, we successfully used information of open chromatin obtained by a single assay, DNase-seq, to address the problem of predicting cell-type–specific gene expression in mammalian organisms directly from regulatory sequence.
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