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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



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.


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.


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.