HRH Prince Alwaleed Bin Talal Bin Abdulaziz Alsaud Institute for Computational Biomedicine, Weill Cornell Medical College, Cornell University, New York, New York 10021, USA.
Genome Res. 2013 Aug;23(8):1295-306. doi: 10.1101/gr.149419.112. Epub 2013 Apr 3.
Genome-wide binding assays can determine where individual transcription factors bind in the genome. However, these factors rarely bind chromatin alone, but instead frequently bind to cis-regulatory elements (CREs) together with other factors thus forming protein complexes. Currently there are no integrative analytical approaches that can predict which complexes are formed on chromatin. Here, we describe a computational methodology to systematically capture protein complexes and infer their impact on gene expression. We applied our method to three human cell types, identified thousands of CREs, inferred known and undescribed complexes recruited to these CREs, and determined the role of the complexes as activators or repressors. Importantly, we found that the predicted complexes have a higher number of physical interactions between their members than expected by chance. Our work provides a mechanism for developing hypotheses about gene regulation via binding partners, and deciphering the interplay between combinatorial binding and gene expression.
全基因组结合分析可以确定单个转录因子在基因组中的结合位置。然而,这些因子很少单独结合染色质,而是经常与其他因子一起结合顺式调控元件(CREs),从而形成蛋白质复合物。目前还没有整合分析方法可以预测哪些复合物在染色质上形成。在这里,我们描述了一种计算方法来系统地捕获蛋白质复合物,并推断它们对基因表达的影响。我们将该方法应用于三种人类细胞类型,鉴定了数千个 CREs,推断出已知和未描述的复合物被招募到这些 CREs 上,并确定了这些复合物作为激活剂或抑制剂的作用。重要的是,我们发现预测的复合物中其成员之间的物理相互作用数量高于随机预期。我们的工作为通过结合伙伴开发关于基因调控的假说提供了一种机制,并阐明了组合结合与基因表达之间的相互作用。