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

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 (>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 (P < 0.05) than that of traditional and HTS approaches. The software package is publicly accessible on GitHub (https://github.com/byemaxx/SSREnricher).