Evidence map›Paper›PMID 37748810›Full record

ArticleLife science alliance2023

Comparative analysis of bioinformatics tools to characterize SARS-CoV-2 subgenomic RNAs.

Denise Lavezzari, Antonio Mori, Elena Pomari, Michela Deiana, Antonio Fadda, Luca Bertoli, Alessandro Sinigaglia, Silvia Riccetti, Luisa Barzon, Chiara Piubelli and 3 more

Abstract read
In one paragraph

Article in Life science alliance, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
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

2 citing papers in PubMed.

  1. Article
  2. 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

13 authors.

Denise LavezzariDepartment of Infectious and Tropical Diseases and Microbiology, IRCCS Sacro Cuore Don Calabria Hospital, Verona, Italy.ORCID 0000-0003-2859-5424
Antonio MoriDepartment of Infectious and Tropical Diseases and Microbiology, IRCCS Sacro Cuore Don Calabria Hospital, Verona, Italy.ORCID 0000-0003-2845-5931
Elena PomariDepartment of Infectious and Tropical Diseases and Microbiology, IRCCS Sacro Cuore Don Calabria Hospital, Verona, Italy elena.pomari@sacrocuore.it.ORCID 0000-0002-5182-0231
Michela DeianaDepartment of Infectious and Tropical Diseases and Microbiology, IRCCS Sacro Cuore Don Calabria Hospital, Verona, Italy.
Antonio FaddaDepartment of Biotechnology, University of Verona, Verona, Italy.
Luca BertoliDepartment of Biotechnology, University of Verona, Verona, Italy.ORCID 0009-0005-8052-1694
Alessandro SinigagliaDepartment of Molecular Medicine, University of Padova, Padova, Italy.
Silvia RiccettiDepartment of Molecular Medicine, University of Padova, Padova, Italy.
Luisa BarzonDepartment of Molecular Medicine, University of Padova, Padova, Italy.
Chiara PiubelliDepartment of Infectious and Tropical Diseases and Microbiology, IRCCS Sacro Cuore Don Calabria Hospital, Verona, Italy.
Massimo DelledonneDepartment of Biotechnology, University of Verona, Verona, Italy.
Maria Rosaria CapobianchiDepartment of Infectious and Tropical Diseases and Microbiology, IRCCS Sacro Cuore Don Calabria Hospital, Verona, Italy.
Concetta CastillettiDepartment of Infectious and Tropical Diseases and Microbiology, IRCCS Sacro Cuore Don Calabria Hospital, Verona, Italy.ORCID 0000-0001-9819-236X

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

During the replication of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), positive-sense genomic RNA and subgenomic RNAs (sgRNAs) are synthesized by a discontinuous process of transcription characterized by a template switch, regulated by transcription-regulating sequences (TRS). Although poorly known about makeup and dynamics of sgRNAs population and function of its constituents, next-generation sequencing approaches with the help of bioinformatics tools have made a significant contribution to expand the knowledge of sgRNAs in SARS-CoV-2. For this scope to date, Periscope, LeTRS, sgDI-tector, and CORONATATOR have been developed. However, limited number of studies are available to compare the performance of such tools. To this purpose, we compared Periscope, LeTRS, and sgDI-tector in the identification of canonical (c-) and noncanonical (nc-) sgRNA species in the data obtained with the Illumina ARTIC sequencing protocol applied to SARS-CoV-2-infected Caco-2 cells, sampled at different time points. The three software showed a high concordance rate in the identification and in the quantification of c-sgRNA, whereas more differences were observed in nc-sgRNA. Overall, LeTRS and sgDI-tector result to be adequate alternatives to Periscope to analyze Fastq data from sequencing platforms other than Nanopore.

Indexed as

COVID-19SARS-CoV-2Caco-2 CellsComputational BiologyHumansRNASubgenomic RNARNASubgenomic RNA

Identifiers

PMID37748810
PMCPMC10520259

What OpenQuestion holds

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Registered trials

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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.