Evidence map›Paper›PMID 35542310›Full record

ArticleVirus evolution2022

Sequencing SARS-CoV-2 genomes from saliva.

Tara Alpert, Chantal B F Vogels, Mallery I Breban, Mary E Petrone, Anne L Wyllie, Nathan D Grubaugh, Joseph R Fauver

Open access · goldAbstract read
In one paragraph

Article in Virus evolution, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
0.3field-weighted citation impact, top 38% 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

5 citing papers in PubMed, 7 citations in OpenAlex.

  1. Article
  2. Article
  3. Review
  4. Review
  5. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

7 authors at 1 institution in 1 country.

Tara AlpertDepartment of Epidemiology of Microbial Diseases, Yale School of Public Health, 60 College St, New Haven, CT 06510, USA.
Chantal B F VogelsDepartment of Epidemiology of Microbial Diseases, Yale School of Public Health, 60 College St, New Haven, CT 06510, USA.
Mallery I BrebanDepartment of Epidemiology of Microbial Diseases, Yale School of Public Health, 60 College St, New Haven, CT 06510, USA.
Mary E Petrone
Anne L WyllieDepartment of Epidemiology of Microbial Diseases, Yale School of Public Health, 60 College St, New Haven, CT 06510, USA.
Nathan D GrubaughDepartment of Epidemiology of Microbial Diseases, Yale School of Public Health, 60 College St, New Haven, CT 06510, USA.
Joseph R FauverDepartment of Epidemiology of Microbial Diseases, Yale School of Public Health, 60 College St, New Haven, CT 06510, USA.
Yale University · US

Funding

NRSA Training CoreTL1TR001864 · NCATS · YALE UNIVERSITY · PI CANTLEY, LLOYD G, EDELMAN, E. JENNIFER · 2016 to 2025
$9.9M
NCATS NIH HHS TL1 TR001864
6 · The paper itself

Abstract

Genomic sequencing is crucial to understanding the epidemiology and evolution of Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Often, genomic studies rely on remnant diagnostic material, typically nasopharyngeal (NP) swabs, as input into whole-genome SARS-CoV-2 next-generation sequencing pipelines. Saliva has proven to be a safe and stable specimen for the detection of SARS-CoV-2 RNA via traditional diagnostic assays; however, saliva is not commonly used for SARS-CoV-2 sequencing. Using the ARTIC Network amplicon-generation approach with sequencing on the Oxford Nanopore MinION, we demonstrate that sequencing SARS-CoV-2 from saliva produces genomes comparable to those from NP swabs, and that RNA extraction is necessary to generate complete genomes from saliva. In this study, we show that saliva is a useful specimen type for genomic studies of SARS-CoV-2.

Indexed as

genomic epidemiologynext generation sequencingoxford nanopore MinIONsalivadirectSARS-CoV-2; saliva

Identifiers

PMID35542310
PMCPMC9074962
OpenAlexW4205355349

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.