Combining global genome and transcriptome approaches to identify the candidate genes of small-effect quantitative trait loci in collagen-induced arthritis

Non-MHC risk alleles in rheumatoid arthritis and in the syntenic chromosome regions of corresponding animal models

Rheumatoid arthritis (RA) is a polygenic autoimmune disease primarily affecting the synovial joints. Numerous animal models show similarities to RA in humans; some of them not only mimic the clinical phenotypes but also demonstrate the involvement of homologous genomic regions in RA. This paper compares corresponding non-MHC genomic regions identified in rodent and human genome-wide association studies (GWAS). To date, over 30 non-MHC RA-associated loci have been identified in humans, and over 100 arthritis-associated loci have been identified in rodent models of RA. The genomic regions associated with the disease are designated by the name(s) of the gene having the most frequent and consistent RA-associated SNPs or a function suggesting their involvement in inflammatory or autoimmune processes. Animal studies on rats and mice preferentially have used single sequence length polymorphism (SSLP) markers to identify disease-associated qualitative and quantitative trait loci (QTLs) in the genome of F2 hybrids of arthritis-susceptible and arthritis-resistant rodent strains. Mouse GWAS appear to be far ahead of rat studies, and significantly more mouse QTLs correspond to human RA risk alleles.

Evidence of a role for Th17 cells in the breach of immune tolerance in arthritis

Th17 cells are thought to play a pathogenic role in various autoimmune diseases. Cytokines secreted by Th17 cells like IL-17, IL-17F and IL-22 have the capacity to mediate a massive inflammatory response. These proinflammatroy cytokines are likely to mediate the pathogenic potential of Th17 cells. Recent evidence suggests a role for Th17 cells in the breach of immune tolerance. This might shed some new light on the pathogenic role of Th17 cells in autoimmunity.

Serious limitations of the QTL/microarray approach for QTL gene discovery

BACKGROUND

It has been proposed that the use of gene expression microarrays in nonrecombinant parental or congenic strains can accelerate the process of isolating individual genes underlying quantitative trait loci (QTL). However, the effectiveness of this approach has not been assessed.

RESULTS

Thirty-seven studies that have implemented the QTL/microarray approach in rodents were reviewed. About 30% of studies showed enrichment for QTL candidates, mostly in comparisons between congenic and background strains. Three studies led to the identification of an underlying QTL gene. To complement the literature results, a microarray experiment was performed using three mouse congenic strains isolating the effects of at least 25 biometric QTL. Results show that genes in the congenic donor regions were preferentially selected. However, within donor regions, the distribution of differentially expressed genes was homogeneous once gene density was accounted for. Genes within identical-by-descent (IBD) regions were less likely to be differentially expressed in chromosome 2, but not in chromosomes 11 and 17. Furthermore, expression of QTL regulated in cis (cis eQTL) showed higher expression in the background genotype, which was partially explained by the presence of single nucleotide polymorphisms (SNP).

CONCLUSIONS

The literature shows limited successes from the QTL/microarray approach to identify QTL genes. Our own results from microarray profiling of three congenic strains revealed a strong tendency to select cis-eQTL over trans-eQTL. IBD regions had little effect on rate of differential expression, and we provide several reasons why IBD should not be used to discard eQTL candidates. In addition, mismatch probes produced false cis-eQTL that could not be completely removed with the current strains genotypes and low probe density microarrays. The reviewed studies did not account for lack of coverage from the platforms used and therefore removed genes that were not tested. Together, our results explain the tendency to report QTL candidates as differentially expressed and indicate that the utility of the QTL/microarray as currently implemented is limited. Alternatives are proposed that make use of microarray data from multiple experiments to overcome the outlined limitations.

High resolution mapping of Cia3: a common arthritis quantitative trait loci in different species

Murine collagen induced arthritis (CIA) is a widely used model of rheumatoid arthritis (RA). Identification of CIA susceptibility genes will aid in the understanding of RA pathogenesis and development of therapeutic targets. This study aims to identify and refine quantitative trait loci (QTL) controlling CIA. Major CIA clinical traits were evaluated in both (DBA/1xFVB/N) F(2) and advanced intercross line (AIL) mice; QTLs were confirmed and refined in AIL. To search for candidate genes, we applied multiple approaches, including gene expression profiling, identification of nonsynonymous polymorphism, and comparative genomic mapping. We identified six suggestive QTLs controlling CIA clinical traits in the F(2) progeny; one of these was confirmed and refined in AIL. This QTL is located on chromosome 6 and overlaps with Cia3, which was identified previously. We refined the 2-log support interval of Cia3 into a 5.6 Mb genomic region; 15 of 77 genes are differentially expressed or carry nonsynonymous polymorphisms between two parental strains. The counterpart genomic region of Cia3 on the rat and human genomes are linked to RA. Twenty-nine of 77 genes are located in the arthritis-linked genomic regions of all three species. Five of those 29 genes are differentially expressed or carry nonsynonymous polymorphisms between parental strains: Timp4, Tmem40, Mbd4, Cacna1c, and Lrtm2. Taken together, we refined Cia3 into a 5.6 Mb genomic region on mouse chromosome 6 and identified candidate genes. This will aid in the search for susceptibility gene(s) controlling arthritis development within Cia3 and its counterpart regions in rat and human genomes.