A Strategy for Identifying Quantitative Trait Genes Using Gene Expression Analysis and Causal Analysis

Abstract

Large numbers of quantitative trait loci (QTL) affecting complex diseases and other quantitative traits have been reported in humans and model animals. However, the genetic architecture of these traits remains elusive due to the difficulty in identifying causal quantitative trait genes (QTGs) for common QTL with relatively small phenotypic effects. A traditional strategy based on techniques such as positional cloning does not always enable identification of a single candidate gene for a QTL of interest because it is difficult to narrow down a target genomic interval of the QTL to a very small interval harboring only one gene. A combination of gene expression analysis and statistical causal analysis can greatly reduce the number of candidate genes. This integrated approach provides causal evidence that one of the candidate genes is a putative QTG for the QTL. Using this approach, I have recently succeeded in identifying a single putative QTG for resistance to obesity in mice. Here, I outline the integration approach and discuss its usefulness using my studies as an example.

Genetic identification of Ly75 as a novel quantitative trait gene for resistance to obesity in mice

“…In this study, we used segregating populations in the quantitative complementation tests and qualitative phenotypic analyses in order to reduce environmental effects, such as litter size, maternal genetic effects and epigenetic effects, on traits examined as much as possible by statistical adjustments for the environmental effects and to randomize the effects of genes located on the contaminated genomic regions from donor strains during development of KO and SR24 congenic strains, as described previously 11 , 17 . However, almost intact phenotypes were observed in KO/KO mice in the two F 2 populations between KO and B6J strains and between KO and SR24 strains.…”

“…In the previous study, CIT analysis successfully excluded the closely-linked genes from candidate genes for Pbwg1.5 . As very recently reviewed 17 , 25 , CIT analysis is an essential methodology for seeking out any genuine factor involved in the causal link between genetic variation and trait variation from confounding factors. In the present study, we used only Ly75 expression for CIT analysis.…”

“…The SR24 subcongenic strain with a wild-derived Pbwg1.5 region of approximately 3 Mb (Supplementary Fig. S1 ) was previously created from descendants of the original B6.Cg- Pbwg1 congenic strain in our laboratory 17 . Its B6JJcl background strain was purchased from Clea Japan, Inc. (Tokyo, Japan).…”

“…According to a previous report 17 , three KO females were crossed to two B6J males, and three SR24 females were crossed to two B6JJcl males. Two types of F 1 mice obtained from these two crosses were reciprocally crossed to each other to produce a four-way cross population.…”

QTLs identified for Biofortification Traits in Wheat: A Review

“…Experimental design, type of plant population analysed and the level of polymorphisms between parental genomes also affect the predictions of QTLs. Statistical methods to determine quantitative trait loci (QTL) require numerous molecular markers with high-resolution genetic maps [32,33]. This approach is also related to genomics methods which are geared toward the dissection of complex phenotypes [34].Genomic resources of wheat have provided important support for functional genomics and conservation biology (by conserving the important landraces) [35,36].…”