TF-centered downstream gene set enrichment analysis: Inference of causal regulators by integrating TF-DNA interactions and protein post-translational modifications information

BMC Bioinformatics

Research

Zhidong Tu¹  Hongyue Dai¹  Yejun Tan²  Qi Liu³  Yixue Li³  Guohui Ding⁴  Lu Xie⁴  Tao Huang⁴  Lei Liu⁴ 

[1] Merck Research Laboratory, 02115, Boston, MA, USA;Merck Research Laboratory, 07065, Rahway, NJ, USA;School of Life Sciences & Biotechnology, Shanghai Jiao Tong University, 200240, Shanghai, China;Shanghai Center for Bioinformation Technology, 200235, Shanghai, China;Shanghai Center for Bioinformation Technology, 200235, Shanghai, China;

关键词: Knockout Experiment;    Pheromone Response;    Direct Transcription;    Diauxic Shift;    Overexpression Experiment;   

DOI  :  10.1186/1471-2105-11-S11-S5

来源: Springer

【 摘 要 】

BackgroundInference of causal regulators responsible for gene expression changes under different conditions is of great importance but remains rather challenging. To date, most approaches use direct binding targets of transcription factors (TFs) to associate TFs with expression profiles. However, the low overlap between binding targets of a TF and the affected genes of the TF knockout limits the power of those methods.ResultsWe developed a TF-centered downstream gene set enrichment analysis approach to identify potential causal regulators responsible for expression changes. We constructed hierarchical and multi-layer regulation models to derive possible downstream gene sets of a TF using not only TF-DNA interactions, but also, for the first time, post-translational modifications (PTM) information. We verified our method in one expression dataset of large-scale TF knockout and another dataset involving both TF knockout and TF overexpression. Compared with the flat model using TF-DNA interactions alone, our method correctly identified five more actual perturbed TFs in large-scale TF knockout data and six more perturbed TFs in overexpression data. Potential regulatory pathways downstream of three perturbed regulators— SNF1, AFT1 and SUT1 —were given to demonstrate the power of multilayer regulation models integrating TF-DNA interactions and PTM information. Additionally, our method successfully identified known important TFs and inferred some novel potential TFs involved in the transition from fermentative to glycerol-based respiratory growth and in the pheromone response. Downstream regulation pathways of SUT1 and AFT1 were also supported by the mRNA and/or phosphorylation changes of their mediating TFs and/or “modulator” proteins.ConclusionsThe results suggest that in addition to direct transcription, indirect transcription and post-translational regulation are also responsible for the effects of TFs perturbation, especially for TFs overexpression. Many TFs inferred by our method are supported by literature. Multiple TF regulation models could lead to new hypotheses for future experiments. Our method provides a valuable framework for analyzing gene expression data to identify causal regulators in the context of TF-DNA interactions and PTM information.

【 授权许可】

CC BY   
© Liu et al; licensee BioMed Central Ltd. 2010