Combining global genome and transcriptome approaches to identify the candidate genes of small-effect quantitative...

Quantitative traits such as complex diseases are controlled by many small-effect genes that are difficult to identify. Here we present a novel strategy to identify the candidate genes for small-effect quantitative trait loci (QTL) in collagen induced arthritis (CIA) using global genome and transcriptome approaches. First, we performed genome linkage analysis in F2 progeny of the CIA susceptible and resistant strains to search for small-effect QTL. Second, we detected gene expression patterns of both strains during CIA. The candidate genes were identified using three criteria: they are located in a genomic region linked to CIA; they are disease-specific differentially expressed during CIA; and they are strain-specific differentially expressed regarding the two parental strains. Eight small-effect QTL controlling CIA severity were identified. Of 22,000 screened genes, 117 were both strain-specific and disease-specific differentially expressed during CIA. Of these 117 genes, 21 were located inside the support intervals of the 8 small-effect QTL and thus were considered as candidate genes.