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Meta-analytic approach for transcriptome profiling of herpes simplex virus type 1
In this meta-analysis, we re-analysed and compared herpes simplex virus type 1 transcriptomic data generated by eight studies using various short- and long-read sequencing techniques and different library preparation methods. We identified a large number of novel mRNAs, non-coding RNAs and transcrip...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7347551/ https://www.ncbi.nlm.nih.gov/pubmed/32647284 http://dx.doi.org/10.1038/s41597-020-0558-8 |
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author | Tombácz, Dóra Torma, Gábor Gulyás, Gábor Moldován, Norbert Snyder, Michael Boldogkői, Zsolt |
author_facet | Tombácz, Dóra Torma, Gábor Gulyás, Gábor Moldován, Norbert Snyder, Michael Boldogkői, Zsolt |
author_sort | Tombácz, Dóra |
collection | PubMed |
description | In this meta-analysis, we re-analysed and compared herpes simplex virus type 1 transcriptomic data generated by eight studies using various short- and long-read sequencing techniques and different library preparation methods. We identified a large number of novel mRNAs, non-coding RNAs and transcript isoforms, and validated many previously published transcripts. Here, we present the most complete HSV-1 transcriptome to date. Furthermore, we also demonstrate that various sequencing techniques, including both cDNA and direct RNA sequencing approaches, are error-prone, which can be circumvented by using integrated approaches. This work draws attention to the need for using multiple sequencing approaches and meta-analyses in transcriptome profiling studies to obtain reliable results. |
format | Online Article Text |
id | pubmed-7347551 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-73475512020-07-13 Meta-analytic approach for transcriptome profiling of herpes simplex virus type 1 Tombácz, Dóra Torma, Gábor Gulyás, Gábor Moldován, Norbert Snyder, Michael Boldogkői, Zsolt Sci Data Analysis In this meta-analysis, we re-analysed and compared herpes simplex virus type 1 transcriptomic data generated by eight studies using various short- and long-read sequencing techniques and different library preparation methods. We identified a large number of novel mRNAs, non-coding RNAs and transcript isoforms, and validated many previously published transcripts. Here, we present the most complete HSV-1 transcriptome to date. Furthermore, we also demonstrate that various sequencing techniques, including both cDNA and direct RNA sequencing approaches, are error-prone, which can be circumvented by using integrated approaches. This work draws attention to the need for using multiple sequencing approaches and meta-analyses in transcriptome profiling studies to obtain reliable results. Nature Publishing Group UK 2020-07-09 /pmc/articles/PMC7347551/ /pubmed/32647284 http://dx.doi.org/10.1038/s41597-020-0558-8 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 license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license 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 license, visit http://creativecommons.org/licenses/by/4.0/. |
spellingShingle | Analysis Tombácz, Dóra Torma, Gábor Gulyás, Gábor Moldován, Norbert Snyder, Michael Boldogkői, Zsolt Meta-analytic approach for transcriptome profiling of herpes simplex virus type 1 |
title | Meta-analytic approach for transcriptome profiling of herpes simplex virus type 1 |
title_full | Meta-analytic approach for transcriptome profiling of herpes simplex virus type 1 |
title_fullStr | Meta-analytic approach for transcriptome profiling of herpes simplex virus type 1 |
title_full_unstemmed | Meta-analytic approach for transcriptome profiling of herpes simplex virus type 1 |
title_short | Meta-analytic approach for transcriptome profiling of herpes simplex virus type 1 |
title_sort | meta-analytic approach for transcriptome profiling of herpes simplex virus type 1 |
topic | Analysis |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7347551/ https://www.ncbi.nlm.nih.gov/pubmed/32647284 http://dx.doi.org/10.1038/s41597-020-0558-8 |
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