Computational Analysis of Tissue-specific Combinatorial Gene Regulation: Predicting Interaction Between Transcription Factors in Human Tissues.
From: Wilmer Institute, Johns Hopkins University School of Medicine, Maumenee Building 844, 600 N. Wolfe Street, Baltimore, MD 21287, USA.
Nucleic acids research
- Publish Date: 2006
- ISSN: 1362-4962
- Volume: 34
- Issue: 17
- Pages: 4925-36
- Medium: Internet
- Language: English
- Citation (JAMA): Yu Xueping, Lin Jimmy, Zack Donald J, et al. Computational Analysis of Tissue-specific Combinatorial Gene Regulation: Predicting Interaction Between Transcription Factors in Human Tissues.. Nucleic Acids Res. 2006;34:4925-36
Abstract
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.
Mesh Headings (Keywords): Binding Sites, Bone and Bones, Computational Biology, Gene Expression Regulation, Humans, Kidney, Liver, Models, Genetic, Muscles, Promoter Regions (Genetics), Transcription Factors
Check for Full Text / PubMed Unique Identifier (PMID): 16982645
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