Magnipore: Prediction of differential single nucleotide changes in the Oxford Nanopore Technologies sequencing signal of SARS-CoV-2 samples.

Oxford Nanopore Technologies SARS-CoV-2 comparative analysis differential RNA modifications raw ONT sequencing signal

Journal

bioRxiv : the preprint server for biology
Titre abrégé: bioRxiv
Pays: United States
ID NLM: 101680187

Informations de publication

Date de publication:
17 Mar 2023
Historique:
pubmed: 31 3 2023
medline: 31 3 2023
entrez: 30 3 2023
Statut: epublish

Résumé

Oxford Nanopore Technologies (ONT) allows direct sequencing of ribonucleic acids (RNA) and, in addition, detection of possible RNA modifications due to deviations from the expected ONT signal. The software available so far for this purpose can only detect a small number of modifications. Alternatively, two samples can be compared for different RNA modifications. We present Magnipore, a novel tool to search for significant signal shifts between samples of Oxford Nanopore data from similar or related species. Magnipore classifies them into mutations and potential modifications. We use Magnipore to compare SARS-CoV-2 samples. Included were representatives of the early 2020s Pango lineages (n=6), samples from Pango lineages B.1.1.7 (n=2, Alpha), B.1.617.2 (n=1, Delta), and B.1.529 (n=7, Omicron). Magnipore utilizes position-wise Gaussian distribution models and a comprehensible significance threshold to find differential signals. In the case of Alpha and Delta, Magnipore identifies 55 detected mutations and 15 sites that hint at differential modifications. We predicted potential virus-variant and variant-group-specific differential modifications. Magnipore contributes to advancing RNA modification analysis in the context of viruses and virus variants.

Identifiants

pubmed: 36993667
doi: 10.1101/2023.03.17.533105
pmc: PMC10055291
pii:
doi:

Types de publication

Preprint

Langues

eng

Auteurs

Jannes Spangenberg (J)

RNA Bioinformatics and High-Throughput Analysis, Friedrich Schiller University Jena, Leutragraben 1, 07743 Jena, Germany.

Christian Höner Zu Siederdissen (CH)

RNA Bioinformatics and High-Throughput Analysis, Friedrich Schiller University Jena, Leutragraben 1, 07743 Jena, Germany.

Milena Žarković (M)

RNA Bioinformatics and High-Throughput Analysis, Friedrich Schiller University Jena, Leutragraben 1, 07743 Jena, Germany.

Sandra Triebel (S)

RNA Bioinformatics and High-Throughput Analysis, Friedrich Schiller University Jena, Leutragraben 1, 07743 Jena, Germany.

Ruben Rose (R)

Institute for Infection Medicine, Christian-Albrechts-Universität zu Kiel and University Medical Center Schleswig-Holstein, Campus Kiel, Brunswiker Straße 4, 24105 Kiel, Germany.

Christina Martínez Christophersen (CM)

Labor Dr. Krause und Kollegen MVZ GmbH, Steenbeker Weg 23, 24106 Kiel, Germany.

Lea Paltzow (L)

Labor Dr. Krause und Kollegen MVZ GmbH, Steenbeker Weg 23, 24106 Kiel, Germany.

Mohsen M Hegab (MM)

Labor Dr. Krause und Kollegen MVZ GmbH, Steenbeker Weg 23, 24106 Kiel, Germany.

Anna Wansorra (A)

Labor Dr. Krause und Kollegen MVZ GmbH, Steenbeker Weg 23, 24106 Kiel, Germany.

Akash Srivastava (A)

RNA Bioinformatics and High-Throughput Analysis, Friedrich Schiller University Jena, Leutragraben 1, 07743 Jena, Germany.

Andi Krumbholz (A)

Institute for Infection Medicine, Christian-Albrechts-Universität zu Kiel and University Medical Center Schleswig-Holstein, Campus Kiel, Brunswiker Straße 4, 24105 Kiel, Germany.
Labor Dr. Krause und Kollegen MVZ GmbH, Steenbeker Weg 23, 24106 Kiel, Germany.

Manja Marz (M)

RNA Bioinformatics and High-Throughput Analysis, Friedrich Schiller University Jena, Leutragraben 1, 07743 Jena, Germany.
European Virus Bioinformatics Center 2, Leutragraben 1, 07743 Jena, Germany.
FLI Leibniz Institute for Age Research, Beutenbergstraße 11, 07745 Jena, Germany.

Classifications MeSH