A rapid phylogeny-based method for accurate community profiling of large-scale metabarcoding datasets

Abstract
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Abstract

Environmental DNA (eDNA) is becoming an increasingly important tool in diverse scientific fields from ecological biomonitoring to wastewater surveillance of viruses. The fundamental challenge in eDNA analyses has been the bioinformatical assignment of reads to taxonomic groups. It has long been known that full probabilistic methods for phylogenetic assignment are preferable, but unfortunately, such methods are computationally intensive and are typically inapplicable to modern Next-Generation Sequencing data. We here present a fast approximate likelihood method for phylogenetic assignment of DNA sequences. Applying the new method to several mock communities and simulated datasets, we show that it identifies more reads at both high and low taxonomic levels more accurately than other leading methods. The advantage of the method is particularly apparent in the presence of polymorphisms and/or sequencing errors and when the true species is not represented in the reference database.

Data availability

The current manuscript is a computational study, so no data have been generated for this manuscript.

The following previously published data sets were used

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Lenore Pipes

University of California-Berkeley, Berkeley, United States

For correspondence
lpipes@berkeley.edu

Competing interests
The authors declare that no competing interests exist.

"This ORCID iD identifies the author of this article:" 0000-0003-0056-8045
Rasmus Nielsen

UC Berkeley, United States

Competing interests
The authors declare that no competing interests exist.

Funding

National Institute of General Medical Sciences (1R01GM138634-01)

Lenore Pipes
Rasmus Nielsen

National Institute of General Medical Sciences (1K99GM144747-01)

Lenore Pipes
Rasmus Nielsen

Advanced Cyberinfrastructure Coordination Ecosystem: Services & Support (BIO180028)

Lenore Pipes
Rasmus Nielsen

The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.

Copyright

This article is distributed under the terms of the Creative Commons Attribution License permitting unrestricted use and redistribution provided that the original author and source are credited.