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Open Access Methodology article

Trait-trait dynamic interaction: 2D-trait eQTL mapping for genetic variation study

Wei Sun123, Shinsheng Yuan4 and Ker-Chau Li45*

Author Affiliations

1 Department of Biostatistics, University of North Carolina, Chapel Hill, NC, 27599, USA

2 Department of Genetics, University of North Carolina, Chapel Hill, NC, 27599, USA

3 Carolina Center for Genome Science, University of North Carolina, Chapel Hill, NC, 27599, USA

4 Institute of Statistical Science, Academia Sinica, Taipei, 115, Taiwan, China

5 Department of Statistics, University of California, Los Angeles, CA, 90095, USA

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BMC Genomics 2008, 9:242  doi:10.1186/1471-2164-9-242

Published: 23 May 2008

Abstract

Background

Many studies have shown that the abundance level of gene expression is heritable. Analogous to the traditional genetic study, most researchers treat the expression of one gene as a quantitative trait and map it to expression quantitative trait loci (eQTL). This is 1D-trait mapping. 1D-trait mapping ignores the trait-trait interaction completely, which is a major shortcoming.

Results

To overcome this limitation, we study the expression of a pair of genes and treat the variation in their co-expression pattern as a two dimensional quantitative trait. We develop a method to find gene pairs, whose co-expression patterns, including both signs and strengths, are mediated by genetic variations and map these 2D-traits to the corresponding genetic loci. We report several applications by combining 1D-trait mapping with 2D-trait mapping, including the contribution of genetic variations to the perturbations in the regulatory mechanisms of yeast metabolic pathways.

Conclusion

Our approach of 2D-trait mapping provides a novel and effective way to connect the genetic variation with higher order biological modules via gene expression profiles.