Gene expression data produced from expression microarrays have not only greatly improved our understanding of cell biology, but also provided invaluable resources to guide the diagnosis and treatment of human diseases. However, the pace of incorporating gene expression signatures into medical practice has been relatively slow. This is mainly due to the limitations of gene expression microarrays and the natural variation of gene expression across tissues or developmental stages. This research project aims to overcome these limitations by joint study of germline DNA polymorphisms and allele-specific expression (ASE) obtained from RNA-seq data. Since germline DNA polymorphisms are stable across tissues and developmental stages, inclusion of DNA information will help us establish more reliable biomarkers for patients'clinical care. More specifically, we will study the genetic basis of ASE in both normal and tumor tissues, dissect genetic and parent-of-origin effects on ASE in human cell lines, and identify genes that escape X inactivation in both mouse reciprocal cross and human cell lines.

Public Health Relevance

We propose to develop statistical methods and software for RNA-seq data analysis, with specific aims on dissecting the genetic basis of allele-specific expression (ASE), quantitative assessment of autosomal imprinting in humans, as well as the genetically controlled measurement of escape from X-inactivation in mouse and human. The deliverables of this project will help biomedical researchers to harvest the huge amount of knowledge accumulated in DNA variations and RNA-seq data and translate them into strategies of personalized disease prevention and treatment.

Agency
National Institute of Health (NIH)
Institute
National Institute of General Medical Sciences (NIGMS)
Type
Research Project (R01)
Project #
1R01GM105785-01A1
Application #
8704544
Study Section
Genomics, Computational Biology and Technology Study Section (GCAT)
Program Officer
Krasnewich, Donna M
Project Start
2014-05-15
Project End
2018-04-30
Budget Start
2014-05-15
Budget End
2015-04-30
Support Year
1
Fiscal Year
2014
Total Cost
Indirect Cost
Name
University of North Carolina Chapel Hill
Department
Biostatistics & Other Math Sci
Type
Schools of Public Health
DUNS #
City
Chapel Hill
State
NC
Country
United States
Zip Code
27599
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