TFRank: network-based prioritization of regulatory associations underlying transcriptional responses
TFRank: network-based prioritization of regulatory associations underlying transcriptional responses
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DOI：
10.1093/bioinformatics/btr546
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发表时间：
2011-11-15
期刊：
影响因子：
5.8
通讯作者：
Madeira, Sara C.
中科院分区：
文献类型：
--
作者：
Goncalves, Joana P.;Francisco, Alexandre P.;Madeira, Sara C.
动机：揭示基因表达控制的机制对于理解复杂的细胞反应至关重要。基因调控研究通常旨在识别参与感兴趣的生物过程的调控参与者，要么是共同调控一组目标基因的转录因子，要么是最终由一组调控因子控制的基因。这些通常根据特定上下文的相关性分数来确定优先级。目前的方法依赖于专门考虑直接转录因子-靶标相互作用的相关性测量，即结合位点或靶标比率的过度表达。然而，基因调控具有复杂的行为，具有重叠的、间接的影响，不容忽视。此外，监管数据的快速积累已经能够通过基于图论的方法来预测适合更高层次探索的大规模网络。因此，范式转变正在出现，孤立和受限的分析可能会被全网络、系统感知策略所取代。结果：我们提出了 TFRank，一个基于图的框架，用于优先考虑生物体调控网络内参与转录反应的调控参与者，从而探索包含感兴趣基因的每条调控路径并将其纳入分析中。 TFRank 选择了酵母适应奎宁和乙酸诱导的应激的重要调节因子，而直接效应方法则忽略了这些调节因子。值得注意的是，据报道它们具有对化学物质的抵抗力。在一项针对人类的初步研究中，TFRank 揭示了涉及乳腺肿瘤生长和转移的调节因子，这些调节因子应用于表达特征与短转移间隔相关的基因。
Motivation: Uncovering mechanisms underlying gene expression control is crucial to understand complex cellular responses. Studies in gene regulation often aim to identify regulatory players involved in a biological process of interest, either transcription factors coregulating a set of target genes or genes eventually controlled by a set of regulators. These are frequently prioritized with respect to a context-specific relevance score. Current approaches rely on relevance measures accounting exclusively for direct transcription factor-target interactions, namely overrepresentation of binding sites or target ratios. Gene regulation has, however, intricate behavior with overlapping, indirect effect that should not be neglected. In addition, the rapid accumulation of regulatory data already enables the prediction of large-scale networks suitable for higher level exploration by methods based on graph theory. A paradigm shift is thus emerging, where isolated and constrained analyses will likely be replaced by whole-network, systemic-aware strategies.Results: We present TFRank, a graph-based framework to prioritize regulatory players involved in transcriptional responses within the regulatory network of an organism, whereby every regulatory path containing genes of interest is explored and incorporated into the analysis. TFRank selected important regulators of yeast adaptation to stress induced by quinine and acetic acid, which were missed by a direct effect approach. Notably, they reportedly confer resistance toward the chemicals. In a preliminary study in human, TFRank unveiled regulators involved in breast tumor growth and metastasis when applied to genes whose expression signatures correlated with short interval to metastasis.