This study harnessed bioinformatics tools and a novel analytical framework to estimate mutation parameters for each STR in the human genome by correlating STR genotypes with local sequence heterozygosity.
Identifying regions of the genome that are depleted of mutations can distinguish potentially deleterious variants. Short tandem repeats (STRs), also known as microsatellites, are among the largest contributors of de novo mutations in humans; however, per-locus studies of STR mutations have been limited to highly ascertained panels of several dozen loci. The current study applied its method to obtain robust estimates of the impact of local sequence features on mutation parameters and used these estimates to create a framework for measuring constraint at STRs by comparing observed versus expected mutation rates. Constraint scores identified known pathogenic variants with early-onset effects. This metric will provide a valuable tool for prioritizing pathogenic STRs in medical genetics studies. (publisher abstract modified)
Report (Grant Sponsored)
Date Published: January 1, 2017
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