Time-Course Transcriptome Profiling of a Poxvirus Using Long-Read Full-Length Assay.

gene expression long-read sequencing nanopore sequencing transcriptome profiling vaccinia virus

Journal

Pathogens (Basel, Switzerland)
ISSN: 2076-0817
Titre abrégé: Pathogens
Pays: Switzerland
ID NLM: 101596317

Informations de publication

Date de publication:
21 Jul 2021
Historique:
received: 24 05 2021
revised: 29 06 2021
accepted: 12 07 2021
entrez: 28 8 2021
pubmed: 29 8 2021
medline: 29 8 2021
Statut: epublish

Résumé

Viral transcriptomes that are determined using first- and second-generation sequencing techniques are incomplete. Due to the short read length, these methods are inefficient or fail to distinguish between transcript isoforms, polycistronic RNAs, and transcriptional overlaps and readthroughs. Additionally, these approaches are insensitive for the identification of splice and transcriptional start sites (TSSs) and, in most cases, transcriptional end sites (TESs), especially in transcript isoforms with varying transcript ends, and in multi-spliced transcripts. Long-read sequencing is able to read full-length nucleic acids and can therefore be used to assemble complete transcriptome atlases. Although vaccinia virus (VACV) does not produce spliced RNAs, its transcriptome has a high diversity of TSSs and TESs, and a high degree of polycistronism that leads to enormous complexity. We applied single-molecule, real-time, and nanopore-based sequencing methods to investigate the time-lapse transcriptome patterns of VACV gene expression.

Identifiants

pubmed: 34451383
pii: pathogens10080919
doi: 10.3390/pathogens10080919
pmc: PMC8398953
pii:
doi:

Types de publication

Journal Article

Langues

eng

Subventions

Organisme : Nemzeti Kutatási Fejlesztési és Innovációs Hivatal
ID : FK 128252
Organisme : Nemzeti Kutatási Fejlesztési és Innovációs Hivatal
ID : K 128247

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Auteurs

Dóra Tombácz (D)

Department of Medical Biology, Faculty of Medicine, University of Szeged, 6720 Szeged, Hungary.
Department of Genetics, School of Medicine, Stanford University, Stanford, CA 94304, USA.

István Prazsák (I)

Department of Medical Biology, Faculty of Medicine, University of Szeged, 6720 Szeged, Hungary.

Gábor Torma (G)

Department of Medical Biology, Faculty of Medicine, University of Szeged, 6720 Szeged, Hungary.

Zsolt Csabai (Z)

Department of Medical Biology, Faculty of Medicine, University of Szeged, 6720 Szeged, Hungary.

Zsolt Balázs (Z)

Department of Medical Biology, Faculty of Medicine, University of Szeged, 6720 Szeged, Hungary.

Norbert Moldován (N)

Department of Medical Biology, Faculty of Medicine, University of Szeged, 6720 Szeged, Hungary.

Béla Dénes (B)

Veterinary Diagnostic Directorate, National Food Chain Safety Office, 1143 Budapest, Hungary.

Michael Snyder (M)

Department of Genetics, School of Medicine, Stanford University, Stanford, CA 94304, USA.

Zsolt Boldogkői (Z)

Department of Medical Biology, Faculty of Medicine, University of Szeged, 6720 Szeged, Hungary.

Classifications MeSH