Pruning the Tree: Comparing OTUs and ASVs in High‐Throughput Sequencing of 5S‐IGS Nuclear Ribosomal DNA in Phylogenetic Studies

Amplicon sequencing of the nuclear ribosomal 5S RNA gene arrays is highly promising for genotaxonomy, to delineate genetic resources of species and trace their evolution. However, the huge amount of data retrieved with this approach is difficult to manage and prone to redundancy, error, and computational difficulties. Reducing the amount of data per sample without losing molecular‐phylogenetic signal is therefore a crucial step for downstream analyses. In this work, we compared operational taxonomic units (OTUs, 100% identity) and amplicon sequence variants (ASVs) from 5S intergenic spacer (5S‐IGS) amplicons of seven beech species ( Fagus spp.) obtained with two widely used and competing bioinformatics tools, MOTHUR and DADA2. We assessed quantitative (total number of sequences retrieved, proportion of sequences unique or shared across the different data sets) and qualitative (sample diversity, data ruggedness and congruence of the obtained phylogenies) differences among sample data profiles obtained with the two methods, and the capacity of the inferred phylogenies to capture diagnostic 5S‐IGS variant types. Over 70% of processed reads were shared between OTUs and ASVs. Despite a strong reduction (> 80%) of the representative sequences, DADA2‐ASVs identified all main 5S‐IGS variants known for Fagus , reflecting the phylogenetic, taxonomic and diversity patterns expected for each sample. In contrast, MOTHUR generated large proportions of rare OTUs and ASVs that complicated the obtained phylogenies and were inference‐wise redundant. We conclude that differences in the sequence variation detected by the two pipelines are minimal and do not result in different phylogenetic information. The more effective and computationally more efficient DADA2 ASVs may thus replace OTUs in future 5S‐IGS studies dealing with complex bioecological phenomena such as hybridisation, polyploidisation, drift and inferring evolutionary pathways of species systems, especially when using increasingly large sample sets.