Genome-wide in silico prediction of gene expression
Genome-wide in silico prediction of gene expression
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DOI：
10.1093/bioinformatics/bts529
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发表时间：
2012-11-01
期刊：
影响因子：
5.8
通讯作者：
Bailey, Timothy L.
中科院分区：
文献类型：
--
作者：
McLeay, Robert C.;Lesluyes, Tom;Bailey, Timothy L.
动机：对基因表达调控进行建模可以深入了解单个转录因子 (TF) 和组蛋白修饰的调控作用。最近，欧阳等人。 2009 年，使用 TF 结合的体内 ChIP-seq 测量对小鼠胚胎干 (mES) 细胞中的基因表达水平进行了建模。然而，ChIP-seq TF 结合数据是组织特异性的，并且相对难以获得。这限制了依赖 ChIP-seq TF 结合数据的基因表达模型的适用性。结果：在本研究中，我们构建了基于回归的模型，将基因表达与两种不同组织中 12 种不同 TF、7 种组蛋白修饰和染色质可及性（DNase I 超敏性）的结合联系起来。我们发现基于计算预测的 TF 结合的表达模型可以达到与使用体内 TF 结合数据相似的准确性，并且包括弱位点的结合对于准确预测基因表达至关重要。我们还发现，结合组蛋白修饰和染色质可及性数据可以提高准确性。令人惊讶的是，我们发现根本不使用 TF 结合数据而仅使用组蛋白修饰和染色质可及性数据的模型可以与基于体内 TF 结合数据的模型一样（或更）准确。
Motivation: Modelling the regulation of gene expression can provide insight into the regulatory roles of individual transcription factors (TFs) and histone modifications. Recently, Ouyang et al. in 2009 modelled gene expression levels in mouse embryonic stem (mES) cells using in vivo ChIP-seq measurements of TF binding. ChIP-seq TF binding data, however, are tissue-specific and relatively difficult to obtain. This limits the applicability of gene expression models that rely on ChIP-seq TF binding data.Results: In this study, we build regression-based models that relate gene expression to the binding of 12 different TFs, 7 histone modifications and chromatin accessibility (DNase I hypersensitivity) in two different tissues. We find that expression models based on computationally predicted TF binding can achieve similar accuracy to those using in vivo TF binding data and that including binding at weak sites is critical for accurate prediction of gene expression. We also find that incorporating histone modification and chromatin accessibility data results in additional accuracy. Surprisingly, we find that models that use no TF binding data at all, but only histone modification and chromatin accessibility data, can be as (or more) accurate than those based on in vivo TF binding data.