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Turk J Biol. 2019 Aug 5;43(4):264-273. doi: 10.3906/biy-1903-16. eCollection 2019.

Characterizing microsatellite polymorphisms using assembly-based and mapping-based tools.

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1
Department of Computer Engineering, Faculty of Engineering, Bilkent University, Bilkent, Ankara Turkey.

Abstract

Microsatellite polymorphism has always been a challenge for genome assembly and sequence alignment due to sequencing errors, short read lengths, and high incidence of polymerase slippage in microsatellite regions. Despite the information they carry being very valuable, microsatellite variations have not gained enough attention to be a routine step in genome sequence analysis pipelines. After the completion of the 1000 Genomes Project, which aimed to establish the most detailed genetic variation catalog for humans, the consortium released only two microsatellite prediction sets generated by two tools. Many other large research efforts have failed to shed light on microsatellite variations. We evaluated the performance of three different local assembly methods on three different experimental settings, focusing on genotype-based performance, coverage impact, and preprocessing including flanking regions. All these experiments supported our initial expectations on assembly. We also demonstrate that overlap-layout-consensus (OLC)-basedassembly methods show higher sensitivity to microsatellite variant calling when compared to a de Bruijn graph-based approach. We conclude that assembly with OLC is the better method for genotyping microsatellites. Our pipeline is available at https://github.com/gulfemd/STRAssembly.

KEYWORDS:

genomics; whole genome sequencing; Microsatellites

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