Literature DB >> 17428815

An integrative genomics strategy for systematic characterization of genetic loci modulating phenotypes.

Lei Bao1, Jeremy L Peirce, Mi Zhou, Hongqiang Li, Dan Goldowitz, Robert W Williams, Lu Lu, Yan Cui.   

Abstract

Naturally occurring genetic variations may affect certain phenotypes through influencing transcript levels of the genes that are causally related to those phenotypes. Genomic regions harboring common sequence variants that modulate gene expression can be mapped as quantitative trait loci (QTLs) using a newly developed genetical genomics approach. This enables a new strategy for systematically mapping novel genetic loci underlying various phenotypes. In this work, we started from a seed set of genes with variants that are known to affect behavioral and neurological phenotypes (as recorded in Mammalian Phenotype Ontology Database) and used microarrays to analyze their expression levels in brain samples of a panel of BXD recombinant inbred mouse strains. We then systematically mapped the QTLs controlling the expression of these genes. Candidate causal genes in the QTL intervals were evaluated for evidence of functional genetic polymorphisms. Using this method, we were able to predict novel genetic loci and causal genes for a number of behavioral and neurological phenotypes. Lines of independent evidence supporting some of our results were provided by transcription factor binding site analysis and by biomedical literature. This strategy integrates gene-phenotype relations from decades of experimental mutagenesis studies and new genomic resources to provide an approach to rapidly expand knowledge on genetic loci modulating phenotypes.

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Year:  2007        PMID: 17428815     DOI: 10.1093/hmg/ddm089

Source DB:  PubMed          Journal:  Hum Mol Genet        ISSN: 0964-6906            Impact factor:   6.150


  11 in total

1.  Identifying genetic loci and spleen gene coexpression networks underlying immunophenotypes in BXD recombinant inbred mice.

Authors:  Rachel M Lynch; Sudhir Naswa; Gary L Rogers; Stephen A Kania; Suchita Das; Elissa J Chesler; Arnold M Saxton; Michael A Langston; Brynn H Voy
Journal:  Physiol Genomics       Date:  2010-02-23       Impact factor: 3.107

2.  Genetical toxicogenomics in Drosophila identifies master-modulatory loci that are regulated by developmental exposure to lead.

Authors:  Douglas M Ruden; Lang Chen; Debra Possidente; Bernard Possidente; Parsa Rasouli; Luan Wang; Xiangyi Lu; Mark D Garfinkel; Helmut V B Hirsch; Grier P Page
Journal:  Neurotoxicology       Date:  2009-09-06       Impact factor: 4.294

3.  An ontology-based comparative anatomy information system.

Authors:  Ravensara S Travillian; Kremena Diatchka; Tejinder K Judge; Katarzyna Wilamowska; Linda G Shapiro
Journal:  Artif Intell Med       Date:  2010-12-10       Impact factor: 5.326

Review 4.  The mammalian phenotype ontology: enabling robust annotation and comparative analysis.

Authors:  Cynthia L Smith; Janan T Eppig
Journal:  Wiley Interdiscip Rev Syst Biol Med       Date:  2009 Nov-Dec

5.  Serious limitations of the QTL/microarray approach for QTL gene discovery.

Authors:  Ricardo A Verdugo; Charles R Farber; Craig H Warden; Juan F Medrano
Journal:  BMC Biol       Date:  2010-07-12       Impact factor: 7.431

6.  Expression QTL modules as functional components underlying higher-order phenotypes.

Authors:  Lei Bao; Xuefeng Xia; Yan Cui
Journal:  PLoS One       Date:  2010-12-13       Impact factor: 3.240

7.  A GPU-accelerated algorithm for biclustering analysis and detection of condition-dependent coexpression network modules.

Authors:  Anindya Bhattacharya; Yan Cui
Journal:  Sci Rep       Date:  2017-06-23       Impact factor: 4.379

8.  Using transcriptome profiling to characterize QTL regions on chicken chromosome 5.

Authors:  Guillaume Le Mignon; Colette Désert; Frédérique Pitel; Sophie Leroux; Olivier Demeure; Gregory Guernec; Behnam Abasht; Madeleine Douaire; Pascale Le Roy; Sandrine Lagarrigue
Journal:  BMC Genomics       Date:  2009-12-02       Impact factor: 3.969

9.  Understanding Disease Susceptibility through Population Genomics.

Authors:  Seonggyun Han; Junnam Lee; Sangsoo Kim
Journal:  Genomics Inform       Date:  2012-12-31

10.  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
Journal:  PLoS Genet       Date:  2008-05-09       Impact factor: 5.917

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