Computational analysis of tissue-specific combinatorial gene regulation: predicting interaction between transcription factors in human tissues

被引:127
作者
Yu, Xueping
Lin, Jimmy
Zack, Donald J.
Qian, Jiang
机构
[1] Johns Hopkins Univ, Sch Med, Wilmer Inst, Baltimore, MD 21287 USA
[2] Johns Hopkins Univ, Sch Med, Dept Mol Biol & Genet, Baltimore, MD 21287 USA
[3] Johns Hopkins Univ, Sch Med, Dept Neurosci, Baltimore, MD 21287 USA
[4] Johns Hopkins Univ, Sch Med, McKusick Nathans Inst Genet Med, Baltimore, MD 21287 USA
关键词
D O I
10.1093/nar/gkl595
中图分类号
Q5 [生物化学]; Q7 [分子生物学];
学科分类号
071010 ; 081704 ;
摘要
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.
引用
收藏
页码:4925 / 4936
页数:12
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