Gene expression is a fundamental function of any cell. It is the main mechanism by which information is transmitted from the nucleus to the rest of the cell and eventually to other cells and the body of the organism. Genetic variation in components of the transcriptional machinery and signals that regulate gene function generates variation in transcriptional response and consequently variation in phenotypes. It has become apparent that many of the common genetic signals associated with disease are found away from the DNA sequence that encodes for protein sequence and is likely to be functioning in regulating gene expression. In this project we propose to develop methodologies that will explore the consequences of genetic variation in gene expression. There are three main goals of this project. First we will explore and develop methodologies to mine information from experiments that perform deep sequencing of the human transcriptome. The new sequencing technologies are providing us with unprecedented resolution into the transcriptome but are also raising challenges in the computational and biological models to use to interpret such large amounts of data. Secondly, we will use high-resolution genetic data to develop and use methodologies to dissect the fine structure of genetic variants that affect regulation of gene expression. Finally, we will implement and test models to infer the higher-order interactions of genome function so as to dig deeply into the biological consequences of genetic variants and how the signal is transmitted from the DNA sequence to higher levels of cell and body function. Our goals is to develop methodologies that will significantly improve our insight to the variability in human populations and assist in interpreting predisposition to genetic diseases.

Public Health Relevance

Project narrative The proposed project aims at the development of statistical methods for the interpretation and study of the impact of genetic variants in cell function. Understanding the cellular effects of genetic variants provides a fundamental framework for the deep understanding of human genetic disease and increases the potential for the development of relevant treatments and drugs. It is the understanding of the basic molecular functions in health and disease that will provide the utmost resolution of information for the improvement of human health.

Agency
National Institute of Health (NIH)
Institute
National Institute of Mental Health (NIMH)
Type
Research Project (R01)
Project #
5R01MH090941-02
Application #
8144831
Study Section
Special Emphasis Panel (ZRG1-GGG-A (52))
Program Officer
Bender, Patrick
Project Start
2010-09-17
Project End
2013-07-31
Budget Start
2011-08-01
Budget End
2013-07-31
Support Year
2
Fiscal Year
2011
Total Cost
$315,416
Indirect Cost
Name
University of Geneva
Department
Type
DUNS #
481076537
City
Geneva
State
Country
Switzerland
Zip Code
CH-12-11
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