The large majority of genetic variations (GVs) occur in non-coding regions particularly in intergenic regions. Understanding the functions of the GVs and revealing their regulatory impact on gene expression remain a great challenge because it is not trivial to link GVs to their target genes and consider collaborative effect of individual GVs. The availability of large amount of the ENCODE and Roadmap Epigenomics Project data provides an unprecedented opportunity to tackle these challenges. We will develop new computational methods to predict long-range promoter-enhancer interactions from epigenomic data. These predicted promoter-enhancer interactions will be integrated with the other ENCODE and Roadmap Epigenomics Project data including histone modification, ChIP-seq of DNA binding proteins, RNA-seq and open chromatin data to construct genetic networks that represent cell-type specific regulatory interactions. These networks will be used to annotate the GVs identified in patient samples to reveal disease-related GVs. Once completed, the proposed study will provide a suite of new computational methods for integrative analysis of the ENCODE/Epigenome Roadmap data and establish a resource of the digested ENCODE/Roadmap Epigenomics Project data. The proposed computational framework is general and can be easily applied to other public data.

Agency
National Institute of Health (NIH)
Institute
National Human Genome Research Institute (NHGRI)
Type
Research Project (R01)
Project #
5R01HG009626-02
Application #
9497610
Study Section
Special Emphasis Panel (ZRG1)
Program Officer
Gilchrist, Daniel A
Project Start
2017-06-03
Project End
2021-03-31
Budget Start
2018-04-01
Budget End
2019-03-31
Support Year
2
Fiscal Year
2018
Total Cost
Indirect Cost
Name
University of California, San Diego
Department
Biology
Type
Schools of Arts and Sciences
DUNS #
804355790
City
La Jolla
State
CA
Country
United States
Zip Code
92093
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Yu, Bingfei; Zhang, Kai; Milner, J Justin et al. (2017) Epigenetic landscapes reveal transcription factors that regulate CD8+ T cell differentiation. Nat Immunol 18:573-582