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Open AccessArticle

A Novel Software and Method for the Efficient Development of Polymorphic SSR Loci Based on Transcriptome Data

Northwest A&F University, State Key Laboratory of Crop Stress Biology for Arid Areas, Key Laboratory of Integrated Pest Management on Crops in Northwestern Loess Plateau, Ministry of Agriculture and Rural Affairs, Yangling 712100, China
Author to whom correspondence should be addressed.
Genes 2019, 10(11), 917;
Received: 17 October 2019 / Revised: 4 November 2019 / Accepted: 5 November 2019 / Published: 11 November 2019
(This article belongs to the Section Technologies and Resources for Genetics)
Traditional methods for developing polymorphic microsatellite loci without reference sequences are time-consuming and labor-intensive, and the polymorphisms of simple sequence repeat (SSR) loci developed from expressed sequence tag (EST) databases are generally poor. To address this issue, in this study, we developed a new software (PSSRdt) and established an effective method for directly obtaining polymorphism details of SSR loci by analyzing diverse transcriptome data. The new method includes three steps, raw data processing, PSSRdt application, and loci extraction and verification. To test the practicality of the method, we successfully obtained 1940 potential polymorphic SSRs from the transcript dataset combined with 44 pea aphid transcriptomes. Fifty-two SSR loci obtained by the new method were selected for validating the polymorphic characteristics by genotyping in pea aphid individuals. The results showed that over 92% of SSR loci were polymorphic and 73.1% of loci were highly polymorphic. Our new software and method provide an innovative approach to microsatellite development based on RNA-seq data, and open a new path for the rapid mining of numerous loci with polymorphism to add to the body of research on microsatellites. View Full-Text
Keywords: SSR; transcriptomes; polymorphic; method SSR; transcriptomes; polymorphic; method
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Tian, R.; Zhang, C.; Huang, Y.; Guo, X.; Chen, M. A Novel Software and Method for the Efficient Development of Polymorphic SSR Loci Based on Transcriptome Data. Genes 2019, 10, 917.

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