bioRxivGenomicsPreprint
Absence of pathogenic Short Tandem Repeat expansions in Systemic Lupus Erythematosus disease-associated genes
Abstract
Short tandem repeat (STR) expansions have been shown to be pathogenic in human neurological diseases, such as Huntington disease. Yet, the potential role of STRs in non-neurological diseases has yet to be fully investigated. In this study, the potential role of STR expansions in the pathogenesis of systemic lupus erythematosus (SLE) was investigated using patient genomic data and two computational tools, HipSTR and exSTRa. The length variability of STRs in 76 SLE-associated genes was compared using exome data from 271 SLE affected individuals and 158 of their unaffected relatives. We conclude that no large STR expansions associated with SLE were present in these affected individuals within the 76 genes investigated. Lack of evidence does not negate a pathogenic role for STR expansions in SLE, yet given the number of individuals included in this study, we expect that this is not a common source of pathogenesis in SLE.\n\nSignificance statementThe increasing availability and decreasing cost of sequencing genomes lends itself to computational analysis, extracting information to aid diagnosis, guide treatment or discover disease mechanisms and new treatments. Computational tools have been developed to look for various types of mutations, including short tandem repeats (STRs), which has been shown to cause diseases such as Huntington disease. Limited research on the possible role of STR expansions in systemic lupus erythematosus (SLE) has been done. Here we use computational tools to compare the length of STRs in 76 SLE-associated genes in patients and their unaffected relatives. Our results did not identify any large STR expansions associated with SLE, and further research is required to gain a better understanding of this complex disease.
- organism: human
- assay: whole-exome sequencing
- research focus: differential expression
- research focus: variant calling
- research focus: benchmarking
- approach: statistical model
- approach: experimental assay
- Citations
- 0
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