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ChIP-on-chip significance analysis reveals large-scale binding and regulation by human transcription factor oncogenes

机译:芯片上芯片的显着性分析揭示了人类转录因子致癌基因的大规模结合和调控

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摘要

ChIP-on-chip has emerged as a powerful tool to dissect the complex network of regulatory interactions between transcription factors and their targets. However, most ChIP-on-chip analysis methods use conservative approaches aimed at minimizing false-positive transcription factor targets. We present a model with improved sensitivity in detecting binding events from ChIP-on-chip data. Its application to human T cells, followed by extensive biochemical validation, reveals that 3 oncogenic transcription factors, NOTCH1, MYC, and HES1, bind to several thousand target gene promoters, up to an order of magnitude increase over conventional analysis methods. Gene expression profiling upon NOTCH1 inhibition shows broad-scale functional regulation across the entire range of predicted target genes, establishing a closer link between occupancy and regulation. Finally, the increased sensitivity reveals a combinatorial regulatory program in which MYC cobinds to virtually all NOTCH1-bound promoters. Overall, these results suggest an unappreciated complexity of transcriptional regulatory networks and highlight the fundamental importance of genome-scale analysis to represent transcriptional programs.
机译:芯片上芯片已经成为剖析转录因子与其靶标之间复杂的调控相互作用网络的强大工具。但是,大多数芯片上芯片分析方法都使用保守的方法,旨在最大程度地减少假阳性转录因子靶标。我们提出了一种从芯片上芯片数据检测结合事件中具有更高灵敏度的模型。它在人类T细胞中的应用,然后经过广泛的生化验证,揭示了3种致癌转录因子NOTCH1,MYC和HES1与数千种靶基因启动子结合,比传统分析方法提高了一个数量级。 NOTCH1抑制后的基因表达谱显示了在整个预测靶基因范围内的大规模功能调节,在占用和调节之间建立了更紧密的联系。最后,增加的敏感性揭示了组合调节程序,其中MYC与几乎所有NOTCH1结合的启动子结合。总体而言,这些结果表明转录调控网络的复杂性未得到认识,并突出了基因组规模分析对于代表转录程序的根本重要性。

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