Systematic analysis of enhancer and promoter interactions
Transcriptional enhancers represent the primary basis for differential gene expression. These elements regulate cell type specificity, development, and evolution, with many human diseases resulting from altered enhancer activity. To date, a key gap in our knowledge is how enhancers select specific p...
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| Format: | Others |
| Language: | English |
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University of Iowa
2015
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| Online Access: | https://ir.uiowa.edu/etd/1972 https://ir.uiowa.edu/cgi/viewcontent.cgi?article=6308&context=etd |
| Summary: | Transcriptional enhancers represent the primary basis for differential gene expression. These elements regulate cell type specificity, development, and evolution, with many human diseases resulting from altered enhancer activity. To date, a key gap in our knowledge is how enhancers select specific promoters for activation.
To fill this gap, in this thesis, I first developed an Integrated Method for Predicting Enhancer Targets (IM-PET). Leveraging abundant “omics” data, I devised and characterized multiple genomic features for distinguishing true enhancer-promoter (EP) pairs from non-interacting pairs. I integrated these features into a probabilistic predictor for EP interactions. Multiple validation experiments demonstrated a significant improvement over extent state-of-the-art approaches. Systematic analyses of EP interactions across twelve human cell types reveals global features of EP interactions.
Second, we used a well-established viral infection model to map the dynamic changes of enhancers and super-enhancers during the CD8+ T cell responses. Our analysis illustrated the complexity and dynamics of the underlying EP interactome during cell differentiation. Taking advantage of the predicted EP interactions, we constructed stage-specific transcriptional regulatory networks, which is critical for understanding the regulatory mechanism during CD8+ T cell differentiation.
Third, recent progress in mapping technologies for chromatin interactions has led to a rapid increase in this type of interaction data. However, there is a lack of a comprehensive depository for chromatin interactions identified by all major technologies. To address this problem, we have developed the 4DGenome database through comprehensive literature curation of experimentally derived interactions. We envision a wide range of investigations will benefit from this carefully curated database. |
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