Evidence map›Paper›PMID 33875001›Full record

ArticleGenome medicine2021

Profiling SARS-CoV-2 mutation fingerprints that range from the viral pangenome to individual infection quasispecies.

Billy T Lau, Dmitri Pavlichin, Anna C Hooker, Alison Almeda, Giwon Shin, Jiamin Chen, Malaya K Sahoo, Chun Hong Huang, Benjamin A Pinsky, Ho Joon Lee and 1 more

Open access · goldAbstract read
In one paragraph

Article in Genome medicine, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers.

0numbers the graph read from it
0cells of the map it votes in
19citing papers in PubMed
1.6field-weighted citation impact, top 14% 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

19 citing papers in PubMed, 29 citations in OpenAlex.

  1. Article
  2. SARS-CoV-2 mutant spectrum complexity is an epidemiologically evolvable trait.Proceedings of the National Academy of Sciences of the United States of America · 2025
    Article
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  7. Article
  8. Zebrafish models of COVID-19.FEMS microbiology reviews · 2023
    Review
  9. Article
  10. Article
  11. Article
  12. Article
  13. Article
  14. Article
  15. Article
  16. Jumping a Moving Train: SARS-CoV-2 Evolution in Real Time.Journal of the Pediatric Infectious Diseases Society · 2021
    Review
  17. Article
  18. Review
  19. Review
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

11 authors at 2 institutions in 1 country.

Billy T Lau *Division of Oncology, Department of Medicine, Stanford University School of Medicine, 269 Campus Drive, CCSR 1120, Stanford, CA, 94305-5151, USA.
Dmitri Pavlichin *Division of Oncology, Department of Medicine, Stanford University School of Medicine, 269 Campus Drive, CCSR 1120, Stanford, CA, 94305-5151, USA.
Anna C Hooker *Division of Oncology, Department of Medicine, Stanford University School of Medicine, 269 Campus Drive, CCSR 1120, Stanford, CA, 94305-5151, USA.
Alison AlmedaDivision of Oncology, Department of Medicine, Stanford University School of Medicine, 269 Campus Drive, CCSR 1120, Stanford, CA, 94305-5151, USA.
Giwon ShinDivision of Oncology, Department of Medicine, Stanford University School of Medicine, 269 Campus Drive, CCSR 1120, Stanford, CA, 94305-5151, USA.
Jiamin ChenDivision of Oncology, Department of Medicine, Stanford University School of Medicine, 269 Campus Drive, CCSR 1120, Stanford, CA, 94305-5151, USA.
Malaya K SahooDepartment of Pathology, Stanford University School of Medicine, Stanford, CA, 94305, USA.
Chun Hong HuangDepartment of Pathology, Stanford University School of Medicine, Stanford, CA, 94305, USA.
Benjamin A PinskyDepartment of Pathology, Stanford University School of Medicine, Stanford, CA, 94305, USA.
Ho Joon LeeDivision of Oncology, Department of Medicine, Stanford University School of Medicine, 269 Campus Drive, CCSR 1120, Stanford, CA, 94305-5151, USA. hojoon@stanford.edu.
Hanlee P JiDivision of Oncology, Department of Medicine, Stanford University School of Medicine, 269 Campus Drive, CCSR 1120, Stanford, CA, 94305-5151, USA. genomics_ji@stanford.edu.ORCID 0000-0003-3772-3424
Stanford University · USStanford Medicine · US

Funding

Statistical Models for Genome Sequencing and AssociationR01HG006137 · NHGRI · UNIVERSITY OF PENNSYLVANIA · PI JI, HANLEE P, ZHANG, NANCY R · 2011 to 2022
$4.3M
Omics information maximization in single-cell sequencing with hybrid molecular and computational approachesR35HG011292 · NHGRI · STANFORD UNIVERSITY · PI LAU, BILLY TSZ CHEONG · 2020 to 2024
$2.3M
K-mer indexing for pan-genome reference annotationU01HG010963 · NHGRI · STANFORD UNIVERSITY · PI JI, HANLEE P, WEISSMAN, TSACHY · 2020 to 2023
$1.3M
National Institutes of Health (US) R35HG011292NHGRI NIH HHS R01 HG006137NHGRI NIH HHS R35 HG011292NHGRI NIH HHS U01 HG010963NHGRI NIH HHS U01HG010963NIH HHS 2R01HG006137-04
6 · The paper itself

Abstract

backgroundThe genome of SARS-CoV-2 is susceptible to mutations during viral replication due to the errors generated by RNA-dependent RNA polymerases. These mutations enable the SARS-CoV-2 to evolve into new strains. Viral quasispecies emerge from de novo mutations that occur in individual patients. In combination, these sets of viral mutations provide distinct genetic fingerprints that reveal the patterns of transmission and have utility in contact tracing.

methodsLeveraging thousands of sequenced SARS-CoV-2 genomes, we performed a viral pangenome analysis to identify conserved genomic sequences. We used a rapid and highly efficient computational approach that relies on k-mers, short tracts of sequence, instead of conventional sequence alignment. Using this method, we annotated viral mutation signatures that were associated with specific strains. Based on these highly conserved viral sequences, we developed a rapid and highly scalable targeted sequencing assay to identify mutations, detect quasispecies variants, and identify mutation signatures from patients. These results were compared to the pangenome genetic fingerprints.

resultsWe built a k-mer index for thousands of SARS-CoV-2 genomes and identified conserved genomics regions and landscape of mutations across thousands of virus genomes. We delineated mutation profiles spanning common genetic fingerprints (the combination of mutations in a viral assembly) and a combination of mutations that appear in only a small number of patients. We developed a targeted sequencing assay by selecting primers from the conserved viral genome regions to flank frequent mutations. Using a cohort of 100 SARS-CoV-2 clinical samples, we identified genetic fingerprints consisting of strain-specific mutations seen across populations and de novo quasispecies mutations localized to individual infections. We compared the mutation profiles of viral samples undergoing analysis with the features of the pangenome.

conclusionsWe conducted an analysis for viral mutation profiles that provide the basis of genetic fingerprints. Our study linked pangenome analysis with targeted deep sequenced SARS-CoV-2 clinical samples. We identified quasispecies mutations occurring within individual patients and determined their general prevalence when compared to over 70,000 other strains. Analysis of these genetic fingerprints may provide a way of conducting molecular contact tracing.

Indexed as

Genome, ViralMutationBase SequenceConserved SequenceCOVID-19DNA FingerprintingHumansRNA, ViralSARS-CoV-2Sequence Analysis, RNARNA, ViralCOVID-19Genetic fingerprintsPandemicQuasispeciesSARS-CoV-2SequencingViral mutations

Identifiers

PMID33875001
PMCPMC8054698
OpenAlexW3155780538

What OpenQuestion holds

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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.