PSSRdt

PSSRdt is a newly developed software tool that enables the rapid and efficient identification of polymorphic microsatellite loci directly from diverse transcriptome data without the need for reference sequences. This innovative approach overcomes the limitations of traditional methods, which are time-consuming and labor-intensive and often result in poor polymorphism when using expressed sequence tag (EST) databases.

The method involving PSSRdt consists of three main steps:

1. Raw data processing

2. Application of the PSSRdt software

3. Loci extraction and verification

To demonstrate the effectiveness of this method, the authors successfully identified 1,940 potentially polymorphic simple sequence repeats (SSRs) from a combined dataset of 44 pea aphid transcriptomes. They further validated the polymorphic characteristics of 52 selected SSR loci through genotyping in pea aphid individuals. The results showed that over 92% of the SSR loci were polymorphic, with 73.1% polymorphic.

Topic

DNA polymorphism;Transcriptomics;RNA-Seq;Gene transcripts;Genotype and phenotype

Detail

  • Operation: De-novo assembly;Repeat sequence analysis;Genotyping;Transcriptome assembly;PCR primer design

  • Software interface: Command-line user interface

  • Language: Perl

  • License: Not stated

  • Cost: Free of charge

  • Version name: -

  • Credit: National Natural Science Foundation of China and The Coordinated Research Project (CRP) of the International Atomic Energy Agency.

  • Input: -

  • Output: -

  • Contact: Maohua Chen maohua.chen@nwsuaf.edu.cn

  • Collection: -

  • Maturity: -

Publications

  • A Novel Software and Method for the Efficient Development of Polymorphic SSR Loci Based on Transcriptome Data.
  • Tian R, et al. A Novel Software and Method for the Efficient Development of Polymorphic SSR Loci Based on Transcriptome Data. A Novel Software and Method for the Efficient Development of Polymorphic SSR Loci Based on Transcriptome Data. 2019; 10:(unknown pages). doi: 10.3390/genes10110917
  • https://doi.org/10.3390/GENES10110917
  • PMID: 31717904
  • PMC: PMC6895799

Download and documentation

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