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Methods for high-resolution analysis of genetic effects on gene expression

Award Number: R01MH101814
ORGANIZATION: NATIONAL INSTITUTE OF MENTAL HEALTH
OPDIV: NIH
AWARD CLASS: DISCRETIONARY
AWARD ACTIVITY TYPE: SCIENTIFIC/HEALTH RESEARCH (INCLUDES SURVEYS)
PERIOD OF PERFORMANCE START DATE: 08/01/2013
PERIOD OF PERFORMANCE END DATE: 06/30/2017

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Methods for high-resolution analysis of genetic effects on gene expression - DESCRIPTION (provided by applicant): Assessing the impact of genetic variants on cellular phenotypes like gene expression provide new opportunities for understanding the biology of genomes and disease. By identifying expression and splicing quantitative trait loci (eQTL or sQTL), we can elucidate new mechanisms underlying trait-associated variation and gain new insights into gene regulatory mechanisms and pathways. With the availability of novel technologies and new large datasets we are now in a position to perform high resolution analysis of transcriptomes and elucidate causal cellular mechanisms for phenotypic variability and disease. In the proposed project we aim to do the following: Specific Aim 1: We will undertake detailed transcriptome analysis of the GTEx data. We will improve the workflow of transcriptome analysis by deploying novel computational methods. First, we will tackle the problem of identifying transcripts and estimating their abundances. Second, we will deploy a Bayesian approach for comparing transcript distribution within and among populations and tissues to develop a robust catalog of differentially expressed genes. Specific Aim 2: We will develop improved statistical methods to discover regulatory variation. Over the past 3-4 years, our collaborative group has developed many tools for mapping genetic variants underlying expression differences among individuals. Here, we will apply these tools to the GTEx data to map eQTL using the high-quality transcriptome feature quantifications from Aim 1. The approaches we will deploy include: (i) haplotype-based methods for mapping of cis eQTL, (ii) improved methods for quantifying Allele Specific Expression (ASE), (iii) Bayesian mapping of trans eQTL using GRNs, and (iv) integrated multi-tissue and multi-population eQTL mapping. Specific Aim 3: We will map putatively causal variants that affect gene expression or transcript structure and assess their functional attributes. To understand the molecular bases of human gene regulation, we will create a comprehensive catalog of causal variants influencing expression and their associated genomic features. We will focus on: (i) the study of patterns of chromatin states to define rules for the location and effect of eQTL; and (ii) the interpretation o loss of function variant effects on transcriptomes and individuals. Specific Aim 4: We will build quantitative genetic and gene regulatory models of cellular transcript abundance. Our main efforts under this aim will be: (i) to assess patterns of epistasis/penetrance between protein-coding and regulatory variation; and (ii) reconstruct gene regulatory networks. These models will provide biological insights into the causes and consequences of eQTL.


Issue Date FY	Funding FY	Legal Entity Name	Legal Entity Address	Legal Entity City	Legal Entity State	Legal Entity Zip Code	Legal Entity COUNTY	Legal Entity COUNTRY	Assistance Listing	Award Code	Budget Year	Action Date	Action Type	Action Amount

Issue Date FY: 2018 ( Subtotal = $0 )
2018	2015	UNIVERSITE DE GENEVE	RUE GENERAL-DUFOUR 24	GENEVE	GE	1204		CHE	Trans-NIH Research Support	000	3	11/29/2017	NON-COMPETING CONTINUATION	$0
														Subtotal = $0

Issue Date FY: 2016 ( Subtotal = $330,099 )
2016	2016	UNIVERSITY OF GENEVA	24, rue du General Dufour	Geneva				CHE	Trans-NIH Research Support	001	3	9/5/2016	SUPPLEMENT FOR EXPANSION	$330,099
2016	2015	UNIVERSITY OF GENEVA	24 RUE DU GENERAL DUFOUR	GENEVA				CHE	Trans-NIH Research Support	000	3	7/1/2016	NON-COMPETING CONTINUATION	$0
														Subtotal = $330,099

Issue Date FY: 2015 ( Subtotal = $622,903 )
2015	2015	UNIVERSITY OF GENEVA	24, rue du General Dufour	Geneva				CHE	Trans-NIH Research Support	000	3	8/5/2015	NON-COMPETING CONTINUATION	$622,903
														Subtotal = $622,903

Issue Date FY: 2014 ( Subtotal = $809,646 )
2014	2014	UNIVERSITY OF GENEVA	24, rue du General Dufour	Geneva				CHE	Trans-NIH Research Support	000	2	7/17/2014	NON-COMPETING CONTINUATION	$544,398
2014	2014	UNIVERSITY OF GENEVA	24, rue du General Dufour	Geneva				CHE	Human Genome Research	001	2	9/4/2014	SUPPLEMENT FOR EXPANSION	$142,018
2014	2014	UNIVERSITY OF GENEVA	24, rue du General Dufour	Geneva				CHE	Trans-NIH Research Support	002	2	9/9/2014	SUPPLEMENT FOR EXPANSION	$123,230
														Subtotal = $809,646

Issue Date FY: 2013 ( Subtotal = $576,303 )
2013	2013	UNIVERSITY OF GENEVA	24, rue du General Dufour	Geneva				CHE	Trans-NIH Research Support	000	1	8/1/2013	NEW	$576,303
														Subtotal = $576,303

Grand Total All Awards = $2,338,951

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Methods for high-resolution analysis of genetic effects on gene expression

Award Number: R01MH101814

ORGANIZATION: NATIONAL INSTITUTE OF MENTAL HEALTH

OPDIV: NIH

AWARD CLASS: DISCRETIONARY

AWARD ACTIVITY TYPE: SCIENTIFIC/HEALTH RESEARCH (INCLUDES SURVEYS)

PERIOD OF PERFORMANCE START DATE: 08/01/2013

PERIOD OF PERFORMANCE END DATE: 06/30/2017

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