The use of congenics and systems biology to characterize complex traits quantitative trait loci.

摘要

The Quantitative Trait Locus (QTL) approach has had great success in mapping loci influencing complex traits relevant to common diseases, such as obesity and atherosclerosis. The identification of genes underlying these QTLs, however, has proved very difficult and success has been limited. The work described here addresses some of these difficulties and provides alternative approaches to facilitate gene discovery in mice.;One approach we explore is the use of congenic strains. A panel of overlapping and reciprocal subcongenics was used to study the architecture of a QTL for atherosclerosis. The results showed that the effect of this QTL on atherosclerosis is due to at least two genes within this region. The results are consistent with 5-Lipoxygenase variation contributing to lesion development.;We have also employed a "systems biology" approach in which mapping was complemented with gene expression profiling. In a study involving examination of differential gene expression, 13 differentially regulated biochemical and metabolic pathways in obese and lean F2 mice were identified. The genes involved in these pathways were shown to be controlled largely by four segregating loci, two of which were associated with adiposity.;In another study, a weighted gene co-expression network was constructed for liver. This network exhibited a modular suborganization and consisted of 12 distinct modules. Each module could be functionally linked to one or few physiological traits. Similar to the pathway analysis study, when the genotype information was integrated into this analysis module specific chromosomal hot-spots were identified.;The results presented in this work illustrate the complexities associated with studying QTL for multigenic traits and highlights the added value gained from integrating systems biology approach with the QTL study to expedite gene discovery for common diseases.