Identification of candidate risk gene variations by whole-genome sequence analysis of four rat strains commonly used in inflammation research

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Abstract

Background: The DA rat strain is particularly susceptible to the induction of a number of chronic inflammatory diseases, such as models for rheumatoid arthritis and multiple sclerosis. Here we sequenced the genomes of two DA sub-strains and two disease resistant strains, E3 and PVG, previously used together with DA strains in genetically segregating crosses.Results: The data uncovers genomic variations, such as single nucleotide variations (SNVs) and copy number variations that underlie phenotypic differences between the strains. Comparisons of regional differences between the two DA sub-strains identified 8 genomic regions that discriminate between the strains that together cover 38 Mbp and harbor 302 genes. We analyzed 10 fine-mapped quantitative trait loci and our data implicate strong candidates for genetic variations that mediate their effects. For example we could identify a single SNV candidate in a regulatory region of the gene Il21r, which has been associated to differential expression in both rats and human MS patients. In the APLEC complex we identified two SNVs in a highly conserved region, which could affect the regulation of all APLEC encoded genes and explain the polygenic differential expression seen in the complex. Furthermore, the non-synonymous SNV modifying aa153 of the Ncf1 protein was confirmed as the sole causative factor.Conclusion: This complete map of genetic differences between the most commonly used rat strains in inflammation research constitutes an important reference in understanding how genetic variations contribute to the traits of importance for inflammatory diseases. © 2014 Bäckdahl et al.; licensee BioMed Central Ltd.

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Bäckdahl, L., Ekman, D., Jagodic, M., Olsson, T., & Holmdahl, R. (2014). Identification of candidate risk gene variations by whole-genome sequence analysis of four rat strains commonly used in inflammation research. BMC Genomics, 15(1). https://doi.org/10.1186/1471-2164-15-391

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