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Integrative profiling of Epstein–Barr virus transcriptome using a multiplatform approach
BACKGROUND: Epstein–Barr virus (EBV) is an important human pathogenic gammaherpesvirus with carcinogenic potential. The EBV transcriptome has previously been analyzed using both Illumina-based short read-sequencing and Pacific Biosciences RS II-based long-read sequencing technologies. Since the vari...
Autores principales: | , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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BioMed Central
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8740505/ https://www.ncbi.nlm.nih.gov/pubmed/34991630 http://dx.doi.org/10.1186/s12985-021-01734-6 |
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author | Fülöp, Ádám Torma, Gábor Moldován, Norbert Szenthe, Kálmán Bánáti, Ferenc Almsarrhad, Islam A. A. Csabai, Zsolt Tombácz, Dóra Minárovits, János Boldogkői, Zsolt |
author_facet | Fülöp, Ádám Torma, Gábor Moldován, Norbert Szenthe, Kálmán Bánáti, Ferenc Almsarrhad, Islam A. A. Csabai, Zsolt Tombácz, Dóra Minárovits, János Boldogkői, Zsolt |
author_sort | Fülöp, Ádám |
collection | PubMed |
description | BACKGROUND: Epstein–Barr virus (EBV) is an important human pathogenic gammaherpesvirus with carcinogenic potential. The EBV transcriptome has previously been analyzed using both Illumina-based short read-sequencing and Pacific Biosciences RS II-based long-read sequencing technologies. Since the various sequencing methods have distinct strengths and limitations, the use of multiplatform approaches have proven to be valuable. The aim of this study is to provide a more complete picture on the transcriptomic architecture of EBV. METHODS: In this work, we apply the Oxford Nanopore Technologies MinION (long-read sequencing) platform for the generation of novel transcriptomic data, and integrate these with other’s data generated by another LRS approach, Pacific BioSciences RSII sequencing and Illumina CAGE-Seq and Poly(A)-Seq approaches. Both amplified and non-amplified cDNA sequencings were applied for the generation of sequencing reads, including both oligo-d(T) and random oligonucleotide-primed reverse transcription. EBV transcripts are identified and annotated using the LoRTIA software suite developed in our laboratory. RESULTS: This study detected novel genes embedded into longer host genes containing 5′-truncated in-frame open reading frames, which potentially encode N-terminally truncated proteins. We also detected a number of novel non-coding RNAs and transcript length isoforms encoded by the same genes but differing in their start and/or end sites. This study also reports the discovery of novel splice isoforms, many of which may represent altered coding potential, and of novel replication-origin-associated transcripts. Additionally, novel mono- and multigenic transcripts were identified. An intricate meshwork of transcriptional overlaps was revealed. CONCLUSIONS: An integrative approach applying multi-technique sequencing technologies is suitable for reliable identification of complex transcriptomes because each techniques has different advantages and limitations, and the they can be used for the validation of the results obtained by a particular approach. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12985-021-01734-6. |
format | Online Article Text |
id | pubmed-8740505 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-87405052022-01-07 Integrative profiling of Epstein–Barr virus transcriptome using a multiplatform approach Fülöp, Ádám Torma, Gábor Moldován, Norbert Szenthe, Kálmán Bánáti, Ferenc Almsarrhad, Islam A. A. Csabai, Zsolt Tombácz, Dóra Minárovits, János Boldogkői, Zsolt Virol J Research BACKGROUND: Epstein–Barr virus (EBV) is an important human pathogenic gammaherpesvirus with carcinogenic potential. The EBV transcriptome has previously been analyzed using both Illumina-based short read-sequencing and Pacific Biosciences RS II-based long-read sequencing technologies. Since the various sequencing methods have distinct strengths and limitations, the use of multiplatform approaches have proven to be valuable. The aim of this study is to provide a more complete picture on the transcriptomic architecture of EBV. METHODS: In this work, we apply the Oxford Nanopore Technologies MinION (long-read sequencing) platform for the generation of novel transcriptomic data, and integrate these with other’s data generated by another LRS approach, Pacific BioSciences RSII sequencing and Illumina CAGE-Seq and Poly(A)-Seq approaches. Both amplified and non-amplified cDNA sequencings were applied for the generation of sequencing reads, including both oligo-d(T) and random oligonucleotide-primed reverse transcription. EBV transcripts are identified and annotated using the LoRTIA software suite developed in our laboratory. RESULTS: This study detected novel genes embedded into longer host genes containing 5′-truncated in-frame open reading frames, which potentially encode N-terminally truncated proteins. We also detected a number of novel non-coding RNAs and transcript length isoforms encoded by the same genes but differing in their start and/or end sites. This study also reports the discovery of novel splice isoforms, many of which may represent altered coding potential, and of novel replication-origin-associated transcripts. Additionally, novel mono- and multigenic transcripts were identified. An intricate meshwork of transcriptional overlaps was revealed. CONCLUSIONS: An integrative approach applying multi-technique sequencing technologies is suitable for reliable identification of complex transcriptomes because each techniques has different advantages and limitations, and the they can be used for the validation of the results obtained by a particular approach. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12985-021-01734-6. BioMed Central 2022-01-06 /pmc/articles/PMC8740505/ /pubmed/34991630 http://dx.doi.org/10.1186/s12985-021-01734-6 Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open AccessThis 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/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data. |
spellingShingle | Research Fülöp, Ádám Torma, Gábor Moldován, Norbert Szenthe, Kálmán Bánáti, Ferenc Almsarrhad, Islam A. A. Csabai, Zsolt Tombácz, Dóra Minárovits, János Boldogkői, Zsolt Integrative profiling of Epstein–Barr virus transcriptome using a multiplatform approach |
title | Integrative profiling of Epstein–Barr virus transcriptome using a multiplatform approach |
title_full | Integrative profiling of Epstein–Barr virus transcriptome using a multiplatform approach |
title_fullStr | Integrative profiling of Epstein–Barr virus transcriptome using a multiplatform approach |
title_full_unstemmed | Integrative profiling of Epstein–Barr virus transcriptome using a multiplatform approach |
title_short | Integrative profiling of Epstein–Barr virus transcriptome using a multiplatform approach |
title_sort | integrative profiling of epstein–barr virus transcriptome using a multiplatform approach |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8740505/ https://www.ncbi.nlm.nih.gov/pubmed/34991630 http://dx.doi.org/10.1186/s12985-021-01734-6 |
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