Human Molecular Genetics Advance Access originally published online on April 11, 2007
Human Molecular Genetics 2007 16(11):1381-1390; doi:10.1093/hmg/ddm089
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An integrative genomics strategy for systematic characterization of genetic loci modulating phenotypes
1 Department of Molecular Sciences, 2 Center of Genomics and Bioinformatics and 3 Department of Anatomy and Neurobiology, University of Tennessee Health Science Center, Memphis, TN 38163, USA and 4 Key Laboratory of Nerve Regeneration, Nantong University, Jiangsu Province, China
* To whom correspondence should be addressed at: Department of Molecular Sciences, University of Tennessee Health Science Center, 858 Madison Avenue, Memphis, TN 38163, USA. Tel: +1 9014483240; Fax: +1 9014487360; Email: ycui2{at}utmem.edu
Received December 11, 2006; Revised February 8, 2007; Accepted April 1, 2007
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.