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A Novel Software and Method for the Efficient Development of Polymorphic SSR Loci Based on Transcriptome Data
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 s...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6895799/ https://www.ncbi.nlm.nih.gov/pubmed/31717904 http://dx.doi.org/10.3390/genes10110917 |
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author | Tian, Ruizheng Zhang, Cunhuan Huang, Yixiao Guo, Xin Chen, Maohua |
author_facet | Tian, Ruizheng Zhang, Cunhuan Huang, Yixiao Guo, Xin Chen, Maohua |
author_sort | Tian, Ruizheng |
collection | PubMed |
description | 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. |
format | Online Article Text |
id | pubmed-6895799 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-68957992019-12-24 A Novel Software and Method for the Efficient Development of Polymorphic SSR Loci Based on Transcriptome Data Tian, Ruizheng Zhang, Cunhuan Huang, Yixiao Guo, Xin Chen, Maohua Genes (Basel) Article 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. MDPI 2019-11-11 /pmc/articles/PMC6895799/ /pubmed/31717904 http://dx.doi.org/10.3390/genes10110917 Text en © 2019 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Tian, Ruizheng Zhang, Cunhuan Huang, Yixiao Guo, Xin Chen, Maohua A Novel Software and Method for the Efficient Development of Polymorphic SSR Loci Based on Transcriptome Data |
title | A Novel Software and Method for the Efficient Development of Polymorphic SSR Loci Based on Transcriptome Data |
title_full | A Novel Software and Method for the Efficient Development of Polymorphic SSR Loci Based on Transcriptome Data |
title_fullStr | A Novel Software and Method for the Efficient Development of Polymorphic SSR Loci Based on Transcriptome Data |
title_full_unstemmed | A Novel Software and Method for the Efficient Development of Polymorphic SSR Loci Based on Transcriptome Data |
title_short | A Novel Software and Method for the Efficient Development of Polymorphic SSR Loci Based on Transcriptome Data |
title_sort | novel software and method for the efficient development of polymorphic ssr loci based on transcriptome data |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6895799/ https://www.ncbi.nlm.nih.gov/pubmed/31717904 http://dx.doi.org/10.3390/genes10110917 |
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