Direct RNA nanopore sequencing of full-length coronavirus genomes provides novel insights into structural variants and enables modification analysis.


Journal

Genome research
ISSN: 1549-5469
Titre abrégé: Genome Res
Pays: United States
ID NLM: 9518021

Informations de publication

Date de publication:
09 2019
Historique:
received: 10 12 2018
accepted: 05 08 2019
pubmed: 24 8 2019
medline: 25 2 2020
entrez: 24 8 2019
Statut: ppublish

Résumé

Sequence analyses of RNA virus genomes remain challenging owing to the exceptional genetic plasticity of these viruses. Because of high mutation and recombination rates, genome replication by viral RNA-dependent RNA polymerases leads to populations of closely related viruses, so-called "quasispecies." Standard (short-read) sequencing technologies are ill-suited to reconstruct large numbers of full-length haplotypes of (1) RNA virus genomes and (2) subgenome-length (sg) RNAs composed of noncontiguous genome regions. Here, we used a full-length, direct RNA sequencing (DRS) approach based on nanopores to characterize viral RNAs produced in cells infected with a human coronavirus. By using DRS, we were able to map the longest (∼26-kb) contiguous read to the viral reference genome. By combining Illumina and Oxford Nanopore sequencing, we reconstructed a highly accurate consensus sequence of the human coronavirus (HCoV)-229E genome (27.3 kb). Furthermore, by using long reads that did not require an assembly step, we were able to identify, in infected cells, diverse and novel HCoV-229E sg RNAs that remain to be characterized. Also, the DRS approach, which circumvents reverse transcription and amplification of RNA, allowed us to detect methylation sites in viral RNAs. Our work paves the way for haplotype-based analyses of viral quasispecies by showing the feasibility of intra-sample haplotype separation. Even though several technical challenges remain to be addressed to exploit the potential of the nanopore technology fully, our work illustrates that DRS may significantly advance genomic studies of complex virus populations, including predictions on long-range interactions in individual full-length viral RNA haplotypes.

Identifiants

pubmed: 31439691
pii: gr.247064.118
doi: 10.1101/gr.247064.118
pmc: PMC6724671
doi:

Types de publication

Journal Article Research Support, Non-U.S. Gov't

Langues

eng

Sous-ensembles de citation

IM

Pagination

1545-1554

Informations de copyright

© 2019 Viehweger et al.; Published by Cold Spring Harbor Laboratory Press.

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Auteurs

Adrian Viehweger (A)

RNA Bioinformatics and High-Throughput Analysis, Friedrich Schiller University Jena, 07743 Jena, Germany.
European Virus Bioinformatics Center, Friedrich Schiller University Jena, 07743 Jena, Germany.

Sebastian Krautwurst (S)

RNA Bioinformatics and High-Throughput Analysis, Friedrich Schiller University Jena, 07743 Jena, Germany.
European Virus Bioinformatics Center, Friedrich Schiller University Jena, 07743 Jena, Germany.

Kevin Lamkiewicz (K)

RNA Bioinformatics and High-Throughput Analysis, Friedrich Schiller University Jena, 07743 Jena, Germany.
European Virus Bioinformatics Center, Friedrich Schiller University Jena, 07743 Jena, Germany.

Ramakanth Madhugiri (R)

Institute of Medical Virology, Justus Liebig University Gießen, 35390 Gießen, Germany.

John Ziebuhr (J)

European Virus Bioinformatics Center, Friedrich Schiller University Jena, 07743 Jena, Germany.
Institute of Medical Virology, Justus Liebig University Gießen, 35390 Gießen, Germany.

Martin Hölzer (M)

RNA Bioinformatics and High-Throughput Analysis, Friedrich Schiller University Jena, 07743 Jena, Germany.
European Virus Bioinformatics Center, Friedrich Schiller University Jena, 07743 Jena, Germany.

Manja Marz (M)

RNA Bioinformatics and High-Throughput Analysis, Friedrich Schiller University Jena, 07743 Jena, Germany.
European Virus Bioinformatics Center, Friedrich Schiller University Jena, 07743 Jena, Germany.
Leibniz Institute on Aging-Fritz Lipmann Institute, 07743 Jena, Germany.

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