Physiol. Genomics AJP: Heart and Circulatory Physiology
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Physiol. Genomics 25: 294-302, 2006. First published January 31, 2006; doi:10.1152/physiolgenomics.00168.2005
1094-8341/06 $8.00
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Received 12 July 2005; accepted in final form 13 January 2006.
Physiological Genomics 25:294-302 (2006)
1094-8341/06 $8.00 © 2006 American Physiological Society

Mapping cis-acting regulatory variation in recombinant congenic strains

Peter D. Lee 1,3,4, Bing Ge 1,2, Celia M. T. Greenwood 5,6, Donna Sinnett 1, Yannick Fortin 1, Sebastien Brunet 1, Anny Fortin 7, Marina Takane 4, Emil Skamene 2,3,7, Tomi Pastinen 1, Michael Hallett 4, Thomas J. Hudson 1,2,3 and Robert Sladek 1,2,3

1 McGill University and Genome Quebec Innovation Centre, Montreal, Quebec
2 Research Institute of McGill University Health Centre, Montreal, Quebec
3 Department of Human Genetics, Faculty of Medicine, McGill University, Montreal, Quebec
4 McGill Centre for Bioinformatics, Montreal, Quebec
5 Program in Genetics and Genomic Biology, Hospital for Sick Children, Toronto, Ontario
6 Department of Public Health Sciences, University of Toronto, Toronto, Ontario
7 Emerillon Therapeutics, Montreal, Quebec, Canada

We present an integrated approach for the enriched detection of genes subject to cis-acting variation in the mouse genome. Gene expression profiling was performed with lung tissue from a panel of recombinant congenic strains (RCS) derived from A/J and C57BL/6J inbred mouse strains. A multiple-regression model measuring the association between gene expression level, donor strain of origin (DSO), and predominant strain background identified over 1,500 genes (P < 0.05) whose expression profiles differed according to the DSO. This model also identified over 1,200 genes whose expression showed dependence on background (P < 0.05), indicating the influence of background genetic context on transcription levels. Sequences obtained from 1-kb segments of 3'-untranslated regions identified single nucleotide polymorphisms in 64% of genes whose expression levels correlated with DSO status, compared with 29% of genes that displayed no association (P < 0.01, Fisher exact test). Allelic imbalance was identified in 50% of genes positive for expression-DSO association, compared with 22% of negative genes (P < 0.05, Fisher exact test). Together, these results demonstrate the utility of RCS mice for identifying the roles of proximal genetic determinants and background genetic context in determining gene expression levels. We propose the use of this integrated experimental approach in multiple tissues from this and other RCS panels as a means for genome-wide cataloging of genetic regulatory mechanisms in laboratory strains of mice.

allelic imbalance; gene networks; cis-acting regulatory variants




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