Integrating genotypic and expression data in a segregating mouse population to identify 5-lipoxygenase as a susceptibility gene for obesity and bone traits

  • An Erratum to this article was published on 01 December 2005

Abstract

Forward genetic approaches to identify genes involved in complex traits such as common human diseases have met with limited success. Fine mapping of linkage regions and validation of positional candidates are time-consuming and not always successful. Here we detail a hybrid procedure to map loci involved in complex traits that leverages the strengths of forward and reverse genetic approaches. By integrating genotypic and expression data in a segregating mouse population, we show how clusters of expression quantitative trait loci linking to regions of the genome accurately reflect the underlying perturbation to the transcriptional network induced by DNA variations in genes that control the complex traits. By matching patterns of gene expression in a segregating population with expression responses induced by single-gene perturbation experiments, we show how genes controlling clusters of expression and clinical quantitative trait loci can be mapped directly. We demonstrate the utility of this approach by identifying 5-lipoxygenase as underlying previously identified quantitative trait loci in an F2 cross between strains C57BL/6J and DBA/2J and showing that it has pleiotropic effects on body fat, lipid levels and bone density.

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Figure 1: Histograms of correlation coefficients computed between OFM and gene expression levels in five different gene sets.
Figure 2: Enrichment of genes linked to the Alox5 locus in the BXD set for genes in the Alox5−/− perturbation signature.
Figure 3: Intersecting perturbation signatures in gene expression data to map genes for complex traits.
Figure 4: Genetic subnetwork of genes in the Alox5−/− signature and linked to the Alox5 locus in the BXD cross.

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Gene Expression Omnibus

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Acknowledgements

We thank the Rosetta Gene Expression Lab for microarray work; J. Berger, K. Wong, J. Thompson, E. Tan and E. Muise for sharing the Pparg expression data; J.G. Menke for sharing the LTB4 data; and J. Zhu for discussion on network analysis. This work was supported in part by grants from the US National Institutes of Health (A.J.L.).

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Correspondence to Eric E Schadt.

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Supplementary information

Supplementary Fig. 1

Chromosome 6 lod score curves for fat mass, cholesterol, and bone traits in the BXD cross. (PDF 10 kb)

Supplementary Fig. 2

Portion of the 5LO gene sequence highlighting 2 mutations (I645V and V646I) identified in the CAST/Ei strain of mouse that lead to a dramatic decrease in the 5LO activity. (PDF 13 kb)

Supplementary Fig. 3

Chromosome 6 genomic region running from 113MB to 128MB (x-axis) and flanking the Alox5 locus in Alox5−/− mice comprised of DNA from the 129 strain. (PDF 85 kb)

Supplementary Fig. 4

Expression of Pparg and Alox5. (PDF 128 kb)

Supplementary Table 1

Liver gene expression traits from the BXD cross that were significantly linked to the Alox5 locus. (PDF 108 kb)

Supplementary Table 2

Liver gene expression signature for Alox5−/− mice, relative to control C57BL/6J mice, as described in the main text. (PDF 25 kb)

Supplementary Table 3

Genes in the liver gene expression signature for Alox5−/− mice that also have expression QTL that are linked to the Alox5 locus. (PDF 13 kb)

Supplementary Table 4

Genes in the liver gene expression signature for Alox5−/− mice that also have expression QTL that are linked to the Alox5 locus and that are correlated with fat mass in the BXD Set. (PDF 9 kb)

Supplementary Methods (PDF 122 kb)

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Mehrabian, M., Allayee, H., Stockton, J. et al. Integrating genotypic and expression data in a segregating mouse population to identify 5-lipoxygenase as a susceptibility gene for obesity and bone traits. Nat Genet 37, 1224–1233 (2005). https://doi.org/10.1038/ng1619

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