SSREnricher: a computational approach for large-scale identification of polymorphic microsatellites based on comparative transcriptome analysis

Abstract

<jats:p>Microsatellite (SSR) markers are the most popular markers for genetic analyses and molecular selective breeding in plants and animals. However, the currently available methods to develop SSRs are relatively time-consuming and expensive. One of the most factors is low frequency of polymorphic SSRs. In this study, we developed a software, SSREnricher, which composes of six core analysis procedures, including SSR mining, sequence clustering, sequence modification, enrichment containing polymorphic SSR sequences, false-positive removal and results output and multiple sequence alignment. After running of transcriptome sequences on this software, a mass of polymorphic SSRs can be identified. The validation experiments showed almost all markers (&gt;90%) that were identified by the SSREnricher as putative polymorphic markers were indeed polymorphic. The frequency of polymorphic SSRs identified by SSREnricher was significantly higher (<jats:italic>P</jats:italic> &lt; 0.05) than that of traditional and HTS approaches. The software package is publicly accessible on GitHub (<jats:uri xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="https://github.com/byemaxx/SSREnricher">https://github.com/byemaxx/SSREnricher</jats:uri>).</jats:p>