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Gene set enrichment in eQTL data identifies novel annotations and pathway regulators.

Authors :
Chunlei Wu
David L Delano
Nico Mitro
Stephen V Su
Jeff Janes
Phillip McClurg
Serge Batalov
Genevieve L Welch
Jie Zhang
Anthony P Orth
John R Walker
Richard J Glynne
Michael P Cooke
Joseph S Takahashi
Kazuhiro Shimomura
Akira Kohsaka
Joseph Bass
Enrique Saez
Tim Wiltshire
Andrew I Su
Source :
PLoS Genetics, Vol 4, Iss 5, p e1000070 (2008)
Publication Year :
2008
Publisher :
Public Library of Science (PLoS), 2008.

Abstract

Genome-wide gene expression profiling has been extensively used to generate biological hypotheses based on differential expression. Recently, many studies have used microarrays to measure gene expression levels across genetic mapping populations. These gene expression phenotypes have been used for genome-wide association analyses, an analysis referred to as expression QTL (eQTL) mapping. Here, eQTL analysis was performed in adipose tissue from 28 inbred strains of mice. We focused our analysis on "trans-eQTL bands", defined as instances in which the expression patterns of many genes were all associated to a common genetic locus. Genes comprising trans-eQTL bands were screened for enrichments in functional gene sets representing known biological pathways, and genes located at associated trans-eQTL band loci were considered candidate transcriptional modulators. We demonstrate that these patterns were enriched for previously characterized relationships between known upstream transcriptional regulators and their downstream target genes. Moreover, we used this strategy to identify both novel regulators and novel members of known pathways. Finally, based on a putative regulatory relationship identified in our analysis, we identified and validated a previously uncharacterized role for cyclin H in the regulation of oxidative phosphorylation. We believe that the specific molecular hypotheses generated in this study will reveal many additional pathway members and regulators, and that the analysis approaches described herein will be broadly applicable to other eQTL data sets.

Subjects

Subjects :
Genetics
QH426-470

Details

Language :
English
ISSN :
15537390 and 15537404
Volume :
4
Issue :
5
Database :
Directory of Open Access Journals
Journal :
PLoS Genetics
Publication Type :
Academic Journal
Accession number :
edsdoj.fa80e29c71a0416faaa85e8ff6d947a7
Document Type :
article
Full Text :
https://doi.org/10.1371/journal.pgen.1000070