The long-term objective of this research proposal is to provide the tools, analysis, and a framework to establish the connection between tissue-specific expression and heritable causes of complex disease, using data from the GTEx Project. The proposal is divided into four Aims: (i) To extend our development of linear eQTL models to the analysis of RNA-Seq exon-level and total read-count (TReC) mapping, and to include eQTL fingerprinting and quality-weighted regression;(ii) to develop new statistical methods for multi-tissue eQTL analysis;(iii) to identify allele-specific and isoform-specific eQTLs across multiple tissues, and (iv) to comprehensively evaluate GTEx relationships with disease by intersecting common and tissue-specific eQTL findings with disease-specific databases. This proposal will extend or develop several tools that will be key to the success of GTEx. Current versions of the tools are either slow or not designed for the multi-tissue setting. We will apply these tools to GTEx and work closely with other GTEx analysis groups, and the tools will have wide utility for the eQTL analysis community.

Public Health Relevance

The GTEx Project will examine patterns of gene expression across numerous tissues in a large number of human donors, and relate these patterns to the underlying DNA of these individuals. The results will be used to better determine how genes act to cause disease, by describing which underlying genetic variants cause variation in expression in the organs and tissues most relevant for various diseases. This application aims to provide the tools, analysis, and framework to identify which DNA variants affect the expression of genes in a manner that is common to many tissues, and which are specific to one or a few tissues. The results will be used to gain a better understanding of the complex patterns of DNA variation in causing complex disease.

Agency
National Institute of Health (NIH)
Institute
National Institute of Mental Health (NIMH)
Type
Research Project (R01)
Project #
1R01MH101819-01
Application #
8585968
Study Section
Special Emphasis Panel (ZRG1-GGG-H (50))
Program Officer
Addington, Anjene M
Project Start
2013-08-15
Project End
2016-06-30
Budget Start
2013-08-15
Budget End
2014-06-30
Support Year
1
Fiscal Year
2013
Total Cost
$443,332
Indirect Cost
$102,883
Name
North Carolina State University Raleigh
Department
Biostatistics & Other Math Sci
Type
Schools of Arts and Sciences
DUNS #
042092122
City
Raleigh
State
NC
Country
United States
Zip Code
27695
Li, Gen; Jima, Dereje; Wright, Fred A et al. (2018) HT-eQTL: integrative expression quantitative trait loci analysis in a large number of human tissues. BMC Bioinformatics 19:95
Zhou, Yi-Hui; Marron, J S; Wright, Fred A (2018) Eigenvalue significance testing for genetic association. Biometrics 74:439-447
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
Agrawal, A; Chou, Y-L; Carey, C E et al. (2018) Genome-wide association study identifies a novel locus for cannabis dependence. Mol Psychiatry 23:1293-1302
Palowitch, John; Shabalin, Andrey; Zhou, Yi-Hui et al. (2018) Estimation of cis-eQTL effect sizes using a log of linear model. Biometrics 74:616-625
Collado-Torres, Leonardo; Nellore, Abhinav; Kammers, Kai et al. (2017) Reproducible RNA-seq analysis using recount2. Nat Biotechnol 35:319-321
Benítez-Buelga, Carlos; Baquero, Juan Miguel; Vaclova, Tereza et al. (2017) Genetic variation in the NEIL2 DNA glycosylase gene is associated with oxidative DNA damage in BRCA2 mutation carriers. Oncotarget 8:114626-114636
Tukiainen, Taru; Villani, Alexandra-Chloé; Yen, Angela et al. (2017) Landscape of X chromosome inactivation across human tissues. Nature 550:244-248
Chiang, Colby; Scott, Alexandra J; Davis, Joe R et al. (2017) The impact of structural variation on human gene expression. Nat Genet 49:692-699
Gudmundsson, Julius; Thorleifsson, Gudmar; Sigurdsson, Jon K et al. (2017) A genome-wide association study yields five novel thyroid cancer risk loci. Nat Commun 8:14517

Showing the most recent 10 out of 48 publications