ASV vs OTUs clustering: Effects on alpha, beta, and gamma diversities in microbiome metabarcoding studies

Area of Science:

• Microbial ecology and bioinformatics
• Molecular ecology and biodiversity assessment

Background:

• Traditional microbial community analysis relies on Operational Taxonomic Units (OTUs) clustering, typically at 97% sequence identity.
• Advances in bioinformatics allow for Amplicon Sequence Variants (ASV) analysis, which resolves sequences to single-nucleotide differences, minimizing technical errors.

Purpose of the Study:

• To compare the impact of OTU clustering (at 97% and 99% identity) versus ASV analysis on ecological indicators.
• To evaluate the performance of these methods using a 16S rRNA gene amplicon dataset from a diverse environmental transect.

Main Methods:

• A 16S rRNA gene metabarcoding dataset from 17 adjacent habitats along a 700m transect was analyzed.
• Two OTU clustering levels (97% and 99%) and ASV analysis were applied to the same dataset.
• Alpha, beta, and gamma diversity, dominance, evenness, and multivariate ordination analyses were performed for comparison.

Main Results:

• OTU clustering significantly underestimated ecological indicator values for species diversity.
• OTU methods distorted dominance and evenness index behavior compared to ASV analysis.
• Multivariate ordination analyses showed sensitivity to clustering methods, impacting tree topology and coherence.

Conclusions:

• Reference-based OTU clustering introduces biases, potentially missing novel taxa and misrepresenting community structure.
• ASV analysis offers significant advantages for prokaryotic community studies, providing more accurate ecological insights.
• ASV analysis is recommended over OTU clustering for environmental studies, especially those with uncharacterized species.