In this project we propose to develop statistical methods for the analysis of microarray and RNA-sequencing data for expression QTL mapping. Our project is designed to address a number of important methodological issues, with particular relevance to the forthcoming GTEx study. We propose to extend a Bayesian hierarchical model for cis-eQTL mapping to enable simultaneous mapping in multiple tissues, and to improve the use of external biological information. We also propose to develop methods to allow more sensitive detection of trans-acting eQTLs that are correlated with networks or modules of co-regulated genes. Finally, we aim to develop methods for estimating transcript abundances from RNA sequencing data, for use in QTL mapping.

Public Health Relevance

The purpose of this project is to develop new tools for analyzing and interpreting eQTL (expression quantitative trait loci) studies. We will develop analytical tools for both microarray-based and RNA-sequence-based measurements of gene expression.

Agency
National Institute of Health (NIH)
Institute
National Institute of Mental Health (NIMH)
Type
Research Project (R01)
Project #
3R01MH090951-02S1
Application #
8509199
Study Section
Special Emphasis Panel (ZRG1-GGG-A (52))
Program Officer
Addington, Anjene M
Project Start
2010-09-17
Project End
2013-07-31
Budget Start
2012-08-01
Budget End
2013-07-31
Support Year
2
Fiscal Year
2012
Total Cost
$200,001
Indirect Cost
$68,349
Name
University of Chicago
Department
Genetics
Type
Schools of Medicine
DUNS #
005421136
City
Chicago
State
IL
Country
United States
Zip Code
60637
Zhang, Mingfeng; Lykke-Andersen, Soren; Zhu, Bin et al. (2018) Characterising cis-regulatory variation in the transcriptome of histologically normal and tumour-derived pancreatic tissues. Gut 67:521-533
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Yang, Bo; Zhou, Wei; Jiao, Jiao et al. (2017) Protein-altering and regulatory genetic variants near GATA4 implicated in bicuspid aortic valve. Nat Commun 8:15481
Manning, Alisa (see original citation for additional authors) (2017) A Low-Frequency Inactivating AKT2 Variant Enriched in the Finnish Population Is Associated With Fasting Insulin Levels and Type 2 Diabetes Risk. Diabetes 66:2019-2032
Calabrese, Gina M; Mesner, Larry D; Stains, Joseph P et al. (2017) Integrating GWAS and Co-expression Network Data Identifies Bone Mineral Density Genes SPTBN1 and MARK3 and an Osteoblast Functional Module. Cell Syst 4:46-59.e4
Picardi, Ernesto; D'Erchia, Anna Maria; Lo Giudice, Claudio et al. (2017) REDIportal: a comprehensive database of A-to-I RNA editing events in humans. Nucleic Acids Res 45:D750-D757

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