Metabolomics,Unknown,Transcriptomics,Genomics,Proteomics

Dataset Information

Mapping the Genetic Architecture of Gene Expression in Human Liver

ABSTRACT: To uncover the genetic determinants affecting expression in a metabolically active tissue relevant to the study of obesity, diabetes, atherosclerosis, and other common human diseases, we profiled 427 human liver samples on a comprehensive gene expression microarray targeting greater than 40,000 transcripts and genotyped DNA from each of these samples at greater than 1,000,000 SNPs. The relatively large sample size of this study and the large number of SNPs genotyped provided the means to assess the relationship between genetic variants and gene expression and it provided this look for the first time in a non-blood derived, metabolically active tissue. A comprehensive analysis of the liver gene expression traits revealed that thousands of these traits are under the control of well defined genetic loci, with many of the genes having already been implicated in a number of human diseases. Clincal data was requested, but not provided by submitter. Keywords: eQTL Liver samples (1-2 g) were acquired from Caucasian individuals from three independent liver collections at tissue resource centers at Vanderbilt University, University of Pittsburg, and Merck Research Laboratories. All individuals were compared to a common pool created from equal portions of RNA from 191 (111 from Vanderbilt University and 80 from University of Pittsburg) samples.

ORGANISM(S): Homo sapiens

SUBMITTER: eric schadt

PROVIDER: E-GEOD-9588 | biostudies-arrayexpress |

REPOSITORIES: biostudies-arrayexpress

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Publications

Correction for hidden confounders in the genetic analysis of gene expression.

Listgarten Jennifer J Kadie Carl C Schadt Eric E EE Heckerman David D

Proceedings of the National Academy of Sciences of the United States of America 20100901 38

Understanding the genetic underpinnings of disease is important for screening, treatment, drug development, and basic biological insight. One way of getting at such an understanding is to find out which parts of our DNA, such as single-nucleotide polymorphisms, affect particular intermediary processes such as gene expression. Naively, such associations can be identified using a simple statistical test on all paired combinations of genetic variants and gene transcripts. However, a wide variety of ...[more]

PMID: 20810919

Publication: 1/2

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Dataset Information

Mapping the Genetic Architecture of Gene Expression in Human Liver

Publications

Correction for hidden confounders in the genetic analysis of gene expression.

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