Evidence map›Paper›PMID 35242361›Full record

ArticleVirus evolution2022

Limited genomic reconstruction of SARS-CoV-2 transmission history within local epidemiological clusters.

Pilar Gallego-García, Nair Varela, Nuria Estévez-Gómez, Loretta De Chiara, Iria Fernández-Silva, Diana Valverde, Nicolae Sapoval, Todd J Treangen, Benito Regueiro, Jorge Julio Cabrera-Alvargonzález and 3 more

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 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed
1.3field-weighted citation impact, top 19% 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

8 citing papers in PubMed, 14 citations in OpenAlex.

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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 at 5 institutions in 2 countries.

Pilar Gallego-GarcíaCINBIO, Universidade de Vigo, Vigo 36310, Spain.
Nair VarelaCINBIO, Universidade de Vigo, Vigo 36310, Spain.
Nuria Estévez-GómezCINBIO, Universidade de Vigo, Vigo 36310, Spain.
Loretta De ChiaraCINBIO, Universidade de Vigo, Vigo 36310, Spain.
Iria Fernández-SilvaDepartment of Biochemistry, Genetics, and Immunology, Universidade de Vigo, Vigo 36310, Spain.
Diana ValverdeCINBIO, Universidade de Vigo, Vigo 36310, Spain.
Todd J TreangenDepartment of Computer Science, Rice University, Houston, TX 77005, USA.ORCID https://orcid.org/0000-0002-3760-564X
Benito RegueiroGalicia Sur Health Research Institute (IIS Galicia Sur), SERGAS-UVIGO.
Jorge Julio Cabrera-AlvargonzálezGalicia Sur Health Research Institute (IIS Galicia Sur), SERGAS-UVIGO.
Víctor Del CampoGalicia Sur Health Research Institute (IIS Galicia Sur), SERGAS-UVIGO.
Sonia PérezGalicia Sur Health Research Institute (IIS Galicia Sur), SERGAS-UVIGO.ORCID https://orcid.org/0000-0003-1734-1904
David PosadaCINBIO, Universidade de Vigo, Vigo 36310, Spain.ORCID https://orcid.org/0000-0003-1407-3406
Galicia Sur Biomedical Foundation · ESUniversity Hospital Complex Of Vigo · ESRice University · USUniversidade de Vigo · ESUniversidade de Santiago de Compostela · ES

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

A detailed understanding of how and when severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) transmission occurs is crucial for designing effective prevention measures. Other than contact tracing, genome sequencing provides information to help infer who infected whom. However, the effectiveness of the genomic approach in this context depends on both (high enough) mutation and (low enough) transmission rates. Today, the level of resolution that we can obtain when describing SARS-CoV-2 outbreaks using just genomic information alone remains unclear. In order to answer this question, we sequenced forty-nine SARS-CoV-2 patient samples from ten local clusters in NW Spain for which partial epidemiological information was available and inferred transmission history using genomic variants. Importantly, we obtained high-quality genomic data, sequencing each sample twice and using unique barcodes to exclude cross-sample contamination. Phylogenetic and cluster analyses showed that consensus genomes were generally sufficient to discriminate among independent transmission clusters. However, levels of intrahost variation were low, which prevented in most cases the unambiguous identification of direct transmission events. After filtering out recurrent variants across clusters, the genomic data were generally compatible with the epidemiological information but did not support specific transmission events over possible alternatives. We estimated the effective transmission bottleneck size to be one to two viral particles for sample pairs whose donor-recipient relationship was likely. Our analyses suggest that intrahost genomic variation in SARS-CoV-2 might be generally limited and that homoplasy and recurrent errors complicate identifying shared intrahost variants. Reliable reconstruction of direct SARS-CoV-2 transmission based solely on genomic data seems hindered by a slow mutation rate, potential convergent events, and technical artifacts. Detailed contact tracing seems essential in most cases to study SARS-CoV-2 transmission at high resolution.

Indexed as

contact traceintrahost variantslocal outbreakshared variantstransmission bottleneckviral contagion

Identifiers

PMID35242361
PMCPMC8889950
OpenAlexW4210766426

What OpenQuestion holds

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LicenceCC BY-NC
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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.