Evidence map›Paper›PMID 42715285›Full record

ArticlePloS one2026

Correlation assessment of SARS-CoV-2 variants and their subvariants present in clinical and wastewater samples in Oregon, USA (February 7, 2021 - February 26, 2022) using the Freyja bioinformatics approach.

Anirudh Bhatia, Justin Elser, Steven J Carrell, Brent Kronmiller, Melissa Sutton, Christine Kelly, Tyler S Radniecki

Abstract read
In one paragraph

Article in PloS one, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

What it found

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2 · The registry

The trial behind it

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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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

7 authors.

Anirudh BhatiaSchool of Chemical, Biological and Environmental Engineering, Oregon State University, Corvallis, Oregon, United States of America.ORCID https://orcid.org/0009-0009-8626-5651
Justin ElserCenter for Quantitative Life Sciences, Oregon State University, Corvallis, Oregon, United States of America.
Steven J CarrellCenter for Quantitative Life Sciences, Oregon State University, Corvallis, Oregon, United States of America.ORCID https://orcid.org/0000-0003-3243-2601
Brent KronmillerCenter for Quantitative Life Sciences, Oregon State University, Corvallis, Oregon, United States of America.
Melissa SuttonPublic Health Division, Oregon Health Authority, Portland, Oregon, United States of America.
Christine KellySchool of Chemical, Biological and Environmental Engineering, Oregon State University, Corvallis, Oregon, United States of America.
Tyler S RadnieckiSchool of Chemical, Biological and Environmental Engineering, Oregon State University, Corvallis, Oregon, United States of America.ORCID https://orcid.org/0000-0002-5295-3562

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundWastewater surveillance is a valuable tool for monitoring SARS-CoV-2 at the community level. As the virus diversified into many variants and subvariants that share overlapping mutations, resolving them accurately from wastewater becomes a key bioinformatic challenge. OBJECTIVES AND

aimsThis study evaluated two distinct bioinformatic approaches, multilocus sequence typing (MLST) and Freyja, for identifying SARS-CoV-2 variants and subvariants in Oregon wastewater samples collected from February 2021 to February 2022.

methodsThe MLST approach identified SARS-CoV-2 variants using unique mutations curated from clinical samples. In contrast, the Freyja approach resolved variant and subvariant abundances using genome wide mutation profiles weighted by sequencing depth. In this study, the variant and subvariants relative abundances produced by both approaches were compared against those observed in clinical surveillance data.

resultsBoth approaches identified SARS-CoV-2 variants at relative abundances that agreed closely with those observed in clinical surveillance data. However, only the Freyja approach identified over 200 Delta subvariants, divided into three clades (21A, 21I and 21J) and two levels (Level 1 and 2) based on Pango subvariants. Delta subvariants showed strong agreement at Level 1 subvariants (rs = 0.892-0.944), while agreement at Level 2 subvariants was inconsistent (rs = 0.324-0.903).

conclusionsThe Freyja approach provided enhanced resolution of SARS-CoV-2 variants and subvariants in wastewater, at abundances that agreed with clinical surveillance. This added resolution is a critical advantage for public health surveillance as SARS-CoV-2 continues to evolve and share mutations across variants and subvariants.

Indexed as

Computational BiologyCOVID-19SARS-CoV-2WastewaterGenome, ViralHumansMultilocus Sequence TypingMutationOregonWastewater

Identifiers

PMID42715285
PMCPMC13557366

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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.