Effects of operational taxonomic unit inference methods on soil microeukaryote community analysis using long-read metabarcoding.

Eshghi Sahraei S, Furneaux B, Kluting K, Zakieh M, Rydin H, Hytteborn H, Rosling A

Ecol Evol 12 (3) e8676 [2022-03-00; online 2022-03-08]

Long amplicon metabarcoding has opened the door for phylogenetic analysis of the largely unknown communities of microeukaryotes in soil. Here, we amplified and sequenced the ITS and LSU regions of the rDNA operon (around 1500 bp) from grassland soils using PacBio SMRT sequencing. We tested how three different methods for generation of operational taxonomic units (OTUs) effected estimated richness and identified taxa, and how well large-scale ecological patterns associated with shifting environmental conditions were recovered in data from the three methods. The field site at Kungsängen Nature Reserve has drawn frequent visitors since Linnaeus's time, and its species rich vegetation includes the largest population of Fritillaria meleagris in Sweden. To test the effect of different OTU generation methods, we sampled soils across an abrupt moisture transition that divides the meadow community into a Carex acuta dominated plant community with low species richness in the wetter part, which is visually distinct from the mesic-dry part that has a species rich grass-dominated plant community including a high frequency of F. meleagris. We used the moisture and plant community transition as a framework to investigate how detected belowground microeukaryotic community composition was influenced by OTU generation methods. Soil communities in both moisture regimes were dominated by protists, a large fraction of which were taxonomically assigned to Ciliophora (Alveolata) while 30%-40% of all reads were assigned to kingdom Fungi. Ecological patterns were consistently recovered irrespective of OTU generation method used. However, different methods strongly affect richness estimates and the taxonomic and phylogenetic resolution of the characterized community with implications for how well members of the microeukaryotic communities can be recognized in the data.

Bioinformatics Compute and Storage [Service]

Bioinformatics Support and Infrastructure [Service]

Bioinformatics Support, Infrastructure and Training [Service]

NGI Long read [Service]

NGI Uppsala (Uppsala Genome Center) [Service]

National Genomics Infrastructure [Service]

PubMed 35342585

DOI 10.1002/ece3.8676

Crossref 10.1002/ece3.8676

pmc: PMC8928899
pii: ECE38676


Publications 7.2.9