Evidence map›Paper›PMID 34937774›Full record

ArticleRNA (New York, N.Y.)2022

sgDI-tector: defective interfering viral genome bioinformatics for detection of coronavirus subgenomic RNAs.

Andrea Di Gioacchino, Rachel Legendre, Yannis Rahou, Valérie Najburg, Pierre Charneau, Benjamin D Greenbaum, Frédéric Tangy, Sylvie van der Werf, Simona Cocco, Anastassia V Komarova

Open access · bronzeAbstract read
In one paragraph

Article in RNA (New York, N.Y.), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
0.6field-weighted citation impact, top 34% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

6 citing papers in PubMed, 9 citations in OpenAlex.

  1. Article
  2. Article
  3. Article
  4. Article
  5. sgRNAs: A SARS-CoV-2 emerging issue.Aspects of molecular medicine · 2023
    Review
  6. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

10 authors at 3 institutions in 3 countries.

Andrea Di GioacchinoSorbonne Université, Université de Paris, Laboratoire de Physique de l'Ecole Normale Supérieure, PSL & CNRS UMR8063, 75005, Paris, France.ORCID 0000-0002-6085-7589
Rachel LegendreInstitut Pasteur, Université de Paris, Hub de Bioinformatique et Biostatistique - Département Biologie Computationnelle, 75015, Paris, France.ORCID 0000-0002-5196-9431
Yannis RahouInstitut Pasteur, Université de Paris, CNRS UMR3569, Génétique Moléculaire des Virus à ARN, F-75015 Paris, France.
Valérie NajburgInstitut Pasteur, Université de Paris, Laboratory of Innovative Vaccines, 75015, Paris, France.
Pierre CharneauInstitut Pasteur, Pasteur-TheraVectys joined unit, 75015, Paris, France.
Benjamin D GreenbaumComputational Oncology, Department of Epidemiology and Biostatistics, Memorial Sloan Kettering Cancer Center, New York 10065, USA.
Frédéric TangyInstitut Pasteur, Université de Paris, Laboratory of Innovative Vaccines, 75015, Paris, France.ORCID 0000-0002-5937-5654
Sylvie van der WerfInstitut Pasteur, Université de Paris, CNRS UMR3569, Génétique Moléculaire des Virus à ARN, F-75015 Paris, France.ORCID 0000-0002-1148-4456
Simona CoccoSorbonne Université, Université de Paris, Laboratoire de Physique de l'Ecole Normale Supérieure, PSL & CNRS UMR8063, 75005, Paris, France.ORCID 0000-0002-1852-7789
Anastassia V KomarovaInstitut Pasteur, Université de Paris, CNRS UMR3569, Génétique Moléculaire des Virus à ARN, F-75015 Paris, France.
Centre National de la Recherche Scientifique · FRInstitut Pasteur · FRMemorial Sloan Kettering Cancer Center · US

Funding

X-RAY CRYSTALLOGRAPHYP30CA008748 · NCI · SLOAN-KETTERING INSTITUTE FOR CANCER RES · PI Hongbiao Carl Lekaye · 1985 to 2026
$347.4M
NCI NIH HHS P30 CA008748
6 · The paper itself

Abstract

Coronavirus RNA-dependent RNA polymerases produce subgenomic RNAs (sgRNAs) that encode viral structural and accessory proteins. User-friendly bioinformatic tools to detect and quantify sgRNA production are urgently needed to study the growing number of next-generation sequencing (NGS) data of SARS-CoV-2. We introduced sgDI-tector to identify and quantify sgRNA in SARS-CoV-2 NGS data. sgDI-tector allowed detection of sgRNA without initial knowledge of the transcription-regulatory sequences. We produced NGS data and successfully detected the nested set of sgRNAs with the ranking M > ORF3a > N>ORF6 > ORF7a > ORF8 > S > E>ORF7b. We also compared the level of sgRNA production with other types of viral RNA products such as defective interfering viral genomes.

Indexed as

Genome, ViralComputational BiologyHigh-Throughput Nucleotide SequencingOpen Reading FramesRNA, ViralSARS-CoV-2RNA, Viraldefective viral genomesSARS-CoV-2subgenomic RNAuser-friendly bioinformatics

Identifiers

PMID34937774
PMCPMC8848934
OpenAlexW4220660345

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.