Computational analysis of tissue-specific combinatorial gene regulation: predicting interaction between transcription factors in human tissues.
Tissue-specific gene expression is generally regulated by more than a single transcription factor (TF). Multiple TFs work in concert to achieve tissue specificity. In order to explore these complex TF interaction networks, we performed a large-scale analysis of TF interactions for 30 human tissues. We first identified tissue-specific genes for 30 tissues based on gene expression databases. We then evaluated the relationships between TFs using the relative position and co-occurrence of their binding sites in the promoters of tissue-specific genes. The predicted TF-TF interactions were validated by both known protein-protein interactions and co-expression of their target genes. We found that our predictions are enriched in known protein-protein interactions (>80 times that of random expectation). In addition, we found that the target genes show the highest co-expression in the tissue of interest. Our findings demonstrate that non-tissue specific TFs play a large role in regulation of tissue-specific genes. Furthermore, they show that individual TFs can contribute to tissue specificity in different tissues by interacting with distinct TF partners. Lastly, we identified several tissue-specific TF clusters that may play important roles in tissue-specific gene regulation.
Yu
Xueping
X
Wilmer Institute, Johns Hopkins University School of Medicine, Maumenee Building 844, 600 N. Wolfe Street, Baltimore, MD 21287, USA.
Lin
Jimmy
J
Zack
Donald J
DJ
Qian
Jiang
J
D001665:Binding Sites; D001842:Bone and Bones / Q000378:metabolism; D019295:Computational Biology / Q000379:methods*; D005786:Gene Expression Regulation; D006801:Humans; D007668:Kidney / Q000378:metabolism; D008099:Liver / Q000378:metabolism; D008957:Models, Genetic; D009132:Muscles / Q000378:metabolism; D011401:Promoter Regions, Genetic; D014157:Transcription Factors / Q000378:metabolism*
D014157:Transcription Factors