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Raw transcriptomics data to gene specific SSRs: a validated free bioinformatics workflow for biologists
Recent advances in next-generation sequencing technologies have paved the path for a considerable amount of sequencing data at a relatively low cost. This has revolutionized the genomics and transcriptomics studies. However, different challenges are now created in handling such data with available b...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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Nature Publishing Group UK
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7588437/ https://www.ncbi.nlm.nih.gov/pubmed/33106560 http://dx.doi.org/10.1038/s41598-020-75270-8 |
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author | Naranpanawa, D. N. U. Chandrasekara, C. H. W. M. R. B. Bandaranayake, P. C. G. Bandaranayake, A. U. |
author_facet | Naranpanawa, D. N. U. Chandrasekara, C. H. W. M. R. B. Bandaranayake, P. C. G. Bandaranayake, A. U. |
author_sort | Naranpanawa, D. N. U. |
collection | PubMed |
description | Recent advances in next-generation sequencing technologies have paved the path for a considerable amount of sequencing data at a relatively low cost. This has revolutionized the genomics and transcriptomics studies. However, different challenges are now created in handling such data with available bioinformatics platforms both in assembly and downstream analysis performed in order to infer correct biological meaning. Though there are a handful of commercial software and tools for some of the procedures, cost of such tools has made them prohibitive for most research laboratories. While individual open-source or free software tools are available for most of the bioinformatics applications, those components usually operate standalone and are not combined for a user-friendly workflow. Therefore, beginners in bioinformatics might find analysis procedures starting from raw sequence data too complicated and time-consuming with the associated learning-curve. Here, we outline a procedure for de novo transcriptome assembly and Simple Sequence Repeats (SSR) primer design solely based on tools that are available online for free use. For validation of the developed workflow, we used Illumina HiSeq reads of different tissue samples of Santalum album (sandalwood), generated from a previous transcriptomics project. A portion of the designed primers were tested in the lab with relevant samples and all of them successfully amplified the targeted regions. The presented bioinformatics workflow can accurately assemble quality transcriptomes and develop gene specific SSRs. Beginner biologists and researchers in bioinformatics can easily utilize this workflow for research purposes. |
format | Online Article Text |
id | pubmed-7588437 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-75884372020-10-27 Raw transcriptomics data to gene specific SSRs: a validated free bioinformatics workflow for biologists Naranpanawa, D. N. U. Chandrasekara, C. H. W. M. R. B. Bandaranayake, P. C. G. Bandaranayake, A. U. Sci Rep Article Recent advances in next-generation sequencing technologies have paved the path for a considerable amount of sequencing data at a relatively low cost. This has revolutionized the genomics and transcriptomics studies. However, different challenges are now created in handling such data with available bioinformatics platforms both in assembly and downstream analysis performed in order to infer correct biological meaning. Though there are a handful of commercial software and tools for some of the procedures, cost of such tools has made them prohibitive for most research laboratories. While individual open-source or free software tools are available for most of the bioinformatics applications, those components usually operate standalone and are not combined for a user-friendly workflow. Therefore, beginners in bioinformatics might find analysis procedures starting from raw sequence data too complicated and time-consuming with the associated learning-curve. Here, we outline a procedure for de novo transcriptome assembly and Simple Sequence Repeats (SSR) primer design solely based on tools that are available online for free use. For validation of the developed workflow, we used Illumina HiSeq reads of different tissue samples of Santalum album (sandalwood), generated from a previous transcriptomics project. A portion of the designed primers were tested in the lab with relevant samples and all of them successfully amplified the targeted regions. The presented bioinformatics workflow can accurately assemble quality transcriptomes and develop gene specific SSRs. Beginner biologists and researchers in bioinformatics can easily utilize this workflow for research purposes. Nature Publishing Group UK 2020-10-26 /pmc/articles/PMC7588437/ /pubmed/33106560 http://dx.doi.org/10.1038/s41598-020-75270-8 Text en © The Author(s) 2020 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. |
spellingShingle | Article Naranpanawa, D. N. U. Chandrasekara, C. H. W. M. R. B. Bandaranayake, P. C. G. Bandaranayake, A. U. Raw transcriptomics data to gene specific SSRs: a validated free bioinformatics workflow for biologists |
title | Raw transcriptomics data to gene specific SSRs: a validated free bioinformatics workflow for biologists |
title_full | Raw transcriptomics data to gene specific SSRs: a validated free bioinformatics workflow for biologists |
title_fullStr | Raw transcriptomics data to gene specific SSRs: a validated free bioinformatics workflow for biologists |
title_full_unstemmed | Raw transcriptomics data to gene specific SSRs: a validated free bioinformatics workflow for biologists |
title_short | Raw transcriptomics data to gene specific SSRs: a validated free bioinformatics workflow for biologists |
title_sort | raw transcriptomics data to gene specific ssrs: a validated free bioinformatics workflow for biologists |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7588437/ https://www.ncbi.nlm.nih.gov/pubmed/33106560 http://dx.doi.org/10.1038/s41598-020-75270-8 |
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