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A framework to interpret short tandem repeat variations in humans

Melissa Gymrek, Thomas Willems, David Reich, Yaniv Erlich
doi: https://doi.org/10.1101/092734
Melissa Gymrek
1Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
2New York Genome Center, New York, NY, USA
3Department of Medicine, University of California San Diego, La Jolla, CA USA
4Department of Computer Science and Engineering, University of California San Diego, La Jolla, CA USA
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  • For correspondence: mgymrek@ucsd.edu
Thomas Willems
2New York Genome Center, New York, NY, USA
5Computational and Systems Biology Program, MIT, Cambridge, MA USA
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David Reich
6Department of Genetics, Harvard Medical School, Boston, MA USA
7Howard Hughes Medical Institute, Harvard Medical School, Boston, MA USA
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Yaniv Erlich
2New York Genome Center, New York, NY, USA
8Department of Computer Science, Fu Foundation School of Engineering, Columbia University, New York, NY, USA
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Abstract

Identifying regions of the genome that are depleted of mutations can reveal potentially deleterious variants. Short tandem repeats (STRs), comprised of repeating motifs of 1-6bp, are among the largest contributors of de novo mutations in humans and are implicated in a variety of human disorders. However, because of the challenges STRs pose to bioinformatics tools, studies of STR mutations have been limited to highly ascertained panels of several dozen loci. Here, we harnessed novel bioinformatics tools and an analytical framework to estimate mutation parameters at each STR in the human genome. We then developed a model of the STR mutation process that allows us to obtain accurate estimates of mutation parameters at each STR by correlating genotypes with local sequence heterozygosity. Finally, we used our method to obtain robust estimates of the impact of local sequence features on mutation parameters and used this to create a framework for measuring constraint at STRs by comparing observed vs. expected mutation rates. Constraint scores identified known pathogenic variants with early onset effects. Our constraint metrics will provide a valuable tool for prioritizing pathogenic STRs in medical genetics studies.

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The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY-NC-ND 4.0 International license.
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Posted December 09, 2016.
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A framework to interpret short tandem repeat variations in humans
Melissa Gymrek, Thomas Willems, David Reich, Yaniv Erlich
bioRxiv 092734; doi: https://doi.org/10.1101/092734
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A framework to interpret short tandem repeat variations in humans
Melissa Gymrek, Thomas Willems, David Reich, Yaniv Erlich
bioRxiv 092734; doi: https://doi.org/10.1101/092734

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