A novel method for large-scale identification of polymorphic microsatellites through comparative transcriptome analysis

ABSTRACTMicrosatellite (SSR) is one of the most popular markers for applied genetic research, but generally the current methods to develop SSRs are relatively time-consuming and expensive. Although high-throughput sequencing (HTS) approach has become a practical and relatively inexpensive option so far, only a small percentage of SSR markers turn out to be polymorphic. Here, we designed a new method to enrich polymorphic SSRs through the comparative transcriptome analysis. This program contains five main steps: 1) transcriptome data downloading or RNA-seq; 2) sequence assembly; 3) SSR mining and enrichment of sequences containing SSRs; 4) sequence alignment; 5) enrichment of sequences containing polymorphic SSRs. A validation experiment was performed and the results showed almost all markers (> 90%) that were indicated as putatively polymorphic by this method were indeed polymorphic. The frequency of polymorphic SSRs was significantly higher (P < 0.05) but the cost and running time were much lower than those of traditional and HTS approaches. The method has a practical value for polymorphic SSRs development and might be widely used for genetic analyses in any species.