Department of Genetics, Stanford University School of Medicine, Stanford, CA 94305, USA.
Proc Natl Acad Sci U S A. 2011 Aug 9;108(32):13353-8. doi: 10.1073/pnas.1103105108. Epub 2011 Jul 26.
Regulation of gene expression at the transcriptional level is achieved by complex interactions of transcription factors operating at their target genes. Dissecting the specific combination of factors that bind each target is a significant challenge. Here, we describe in detail the Allele Binding Cooperativity test, which uses variation in transcription factor binding among individuals to discover combinations of factors and their targets. We developed the ALPHABIT (a large-scale process to hunt for allele binding interacting transcription factors) pipeline, which includes statistical analysis of binding sites followed by experimental validation, and demonstrate that this method predicts transcription factors that associate with NFκB. Our method successfully identifies factors that have been known to work with NFκB (E2A, STAT1, IRF2), but whose global coassociation and sites of cooperative action were not known. In addition, we identify a unique coassociation (EBF1) that had not been reported previously. We present a general approach for discovering combinatorial models of regulation and advance our understanding of the genetic basis of variation in transcription factor binding.
转录水平的基因表达调控是通过在靶基因上发挥作用的转录因子的复杂相互作用来实现的。解析与每个靶标结合的特定因子组合是一项重大挑战。在这里,我们详细描述了等位基因结合协同性测试,该测试利用个体之间转录因子结合的变化来发现因子及其靶标的组合。我们开发了 ALPHABIT(大规模搜索等位基因结合相互作用转录因子的过程)管道,该管道包括结合位点的统计分析,随后进行实验验证,并证明该方法可预测与 NFκB 相关的转录因子。我们的方法成功地鉴定了已知与 NFκB (E2A、STAT1、IRF2)一起工作的因子,但它们的全局共关联和协同作用的位点尚不清楚。此外,我们还鉴定了一个以前没有报道过的独特共关联(EBF1)。我们提出了一种发现调控组合模型的通用方法,推进了我们对转录因子结合变异的遗传基础的理解。