Evidence map›Paper›PMID 40271134›Full record

ArticleRoyal Society open science2025

Cas9-based enrichment for targeted long-read metabarcoding.

Lucia Nikolaeva-Reynolds, Christopher Cammies, Rosemary Crichton, Thomas E Gorochowski

Abstract read
In one paragraph

Article in Royal Society open science, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Review
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

4 authors.

Lucia Nikolaeva-ReynoldsSchool of Biological Sciences, University of Bristol, 24 Tyndall Avenue, Bristol BS8 1TQ, UK.
Christopher CammiesSchool of Biological Sciences, University of Bristol, 24 Tyndall Avenue, Bristol BS8 1TQ, UK.
Rosemary CrichtonSchool of Biological Sciences, University of Bristol, 24 Tyndall Avenue, Bristol BS8 1TQ, UK.
Thomas E GorochowskiSchool of Biological Sciences, University of Bristol, 24 Tyndall Avenue, Bristol BS8 1TQ, UK.ORCID https://orcid.org/0000-0003-1702-786X

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Metabarcoding is a valuable tool for characterizing the communities that underpin the functioning of ecosystems. However, current methods often rely on polymerase chain reaction (PCR) amplification for enrichment of marker genes. PCR can introduce significant biases that affect quantification and is typically restricted to one target loci at a time, limiting the diversity that can be captured in a single reaction. Here, we address these issues by using Cas9 to enrich marker genes for long-read nanopore sequencing directly from a DNA sample, removing the need for PCR. We show that this approach can effectively isolate a 4.5 kb region covering partial 18S and 28S rRNA genes and the ITS region in a mixed nematode community, and further adapt our approach for characterizing a diverse microbial community. We demonstrate the ability for Cas9-based enrichment to support multiplexed targeting of several different DNA regions simultaneously, enabling optimal marker gene selection for different clades of interest within a sample. We also find a strong correlation between input DNA concentrations and output read proportions for mixed-species samples, demonstrating the ability for quantification of relative species abundance. This study lays a foundation for targeted long-read sequencing to more fully capture the diversity of organisms present in complex environments.

Indexed as

Cas9metabarcodingnanopore sequencingtargeted enrichment

Identifiers

PMID40271134
PMCPMC12014237

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.