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.
| Original language | English |
|---|---|
| Article number | 242110 |
| Number of pages | 17 |
| Journal | Royal Society Open Science |
| Volume | 12 |
| Issue number | 4 |
| DOIs | |
| Publication status | Published - 23 Apr 2025 |
Bibliographical note
Publisher Copyright:© 2025 The Author(s).
Research Groups and Themes
- Bristol BioDesign Institute
Keywords
- nanopore sequencing
- Cas9
- targeted enrichment
- metabarcoding
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Cas9-based enrichment for targeted long-read metabarcoding
Nikolaeva-Reynolds, L. (Creator), Cammies, C. (Creator), Crichton, R. (Creator) & Gorochowski, T. (Creator), Zenodo, 2025
DOI: 10.5281/zenodo.14250758, https://zenodo.org/records/14250758
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