ArticleBMC genomics2014
Identification of candidate risk gene variations by whole-genome sequence analysis of four rat strains commonly used in inflammation research.
Article in BMC genomics, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
8 citing papers in PubMed.
- Get Spliced: Uniting Alternative Splicing and Arthritis.International journal of molecular sciences · 2024Review
- Endophilin A2 deficiency protects rodents from autoimmune arthritis by modulating T cell activation.Nature communications · 2021Article
- Genome-to-phenome research in rats: progress and perspectives.International journal of biological sciences · 2021Review
- Rat models of human diseases and related phenotypes: a systematic inventory of the causative genes.Journal of biomedical science · 2020Review
- Identification of Clec4b as a novel regulator of bystander activation of auto-reactive T cells and autoimmune disease.PLoS genetics · 2020Article
- C-type lectin receptors Mcl and Mincle control development of multiple sclerosis-like neuroinflammation.The Journal of clinical investigation · 2020Article
- Article
- Applications of Next-generation Sequencing in Systemic Autoimmune Diseases.Genomics, proteomics & bioinformatics · 2015Review
Corrections and comments
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Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundThe 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.
resultsThe 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.
conclusionThis 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.
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