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Metabarcoding is an important tool for understanding fungal communities. The internal transcribed spacer (ITS) rDNA is the accepted fungal barcode but has known problems. The large subunit (LSU) rDNA has also been used to investigate fungal communities but available LSU metabarcoding primers were mostly designed to target Dikarya (Ascomycota + Basidiomycota) with little attention to early diverging fungi (EDF). However, evidence from multiple studies suggests that EDF comprise a large portion of unknown diversity in community sampling. Here, we investigate how DNA marker choice and methodological biases impact recovery of EDF from environmental samples. We focused on one EDF lineage, Zoopagomycota, as an example. We evaluated three primer sets (ITS1F/ITS2, LROR/LR3, and LR3 paired with new primer LR22F) to amplify and sequence a Zoopagomycota mock community and a set of 146 environmental samples with Illumina MiSeq. We compared two taxonomy assignment methods and created an LSU reference database compatible with AMPtk software. The two taxonomy assignment methods recovered strikingly different communities of fungi and EDF. Target fragment length variation exacerbated PCR amplification biases and influenced downstream taxonomic assignments, but this effect was greater for EDF than Dikarya. To improve identification of LSU amplicons we performed phylogenetic reconstruction and illustrate the advantages of this critical tool for investigating identified and unidentified sequences. Our results suggest much of the EDF community may be missed or misidentified with "standard" metabarcoding approaches and modified techniques are needed to understand the role of these taxa in a broader ecological context.

DNA metabarcoding can be a promising alternative to microscopy for analysing phytoplankton, a key ecological indicator for freshwater ecosystems. The aim of this study was to evaluate the performance of different barcodes and associated primer pairs to assess microalgal diversity with DNA metabarcoding using a single barcode targeting all microalgae. We investigated barcodes in 16S and 23S rRNA genes, encoding for prokaryotic ribosomal sub-units, that are present in Cyanobacteria as well as in chloroplasts. In silico PCR tests were carried out on eight 16S and five 23S primer pairs using the Phytool reference library. Two and three pairs were selected for 16S and 23S, respectively, to perform an in vitro metabarcoding test based on a mock community made of DNA extracts of 10 microalgae strains. The 23S pairs enabled to detect all species, whereas 16S ones failed in the detection of some of them. One pair was selected for each genetic marker, based on its efficiency and specificity towards microalgae (e.g. not heterotrophic bacteria). Another mock community covering a larger diversity (18 microalgae strains) was used to test the efficiency of the selected pairs and their ability to estimate relative abundances. The 23S pair performed better than the 16S one for detecting target species with also more accuracy to assess their relative abundances. We conclude that the 23S primer pair ECLA23S_F1/ECLA23S_R1 appears as a good candidate to decipher freshwater phytoplankton communities. As a next step, it will be necessary to confirm these results on a large diversity of natural communities. Microalgae taxa can be identified with short DNA barcodes. Eight primer pairs for 16S and five for 23S were tested in silico and with mock communities including cyanobacteria and eukaryotic microalgae. We conclude that the 23S primer pair ECLA23S_F1/ECLA23S_R1 was the best candidate to decipher freshwater phytoplankton communities. [ABSTRACT FROM AUTHOR]

Abstract High‐throughput sequencing has the potential to describe biological communities with high efficiency yet comprehensive assessment of diversity with species‐level resolution remains one of the most challenging aspects of metabarcoding studies. We investigated the utility of curated ribosomal and mitochondrial nematode reference sequence databases for determining phylum‐specific species‐level clustering thresholds. We compiled 438 ribosomal and 290 mitochondrial sequences which identified 99% and 94% as the species delineation clustering threshold, respectively. These thresholds were evaluated in HTS data from mock communities containing 39 nematode species as well as environmental samples from Vietnam. We compared the taxonomic description of the mocks generated by two read‐merging and two clustering algorithms and the cluster‐free Dada2 pipeline. Taxonomic assignment with the RDP classifier was assessed under different training sets. Our results showed that 36/39 mock nematode species were identified across the molecular markers (18S: 32, JB2: 19, JB3: 21) in UClust_ref OTUs at their respective clustering thresholds, outperforming UParse_denovo and the commonly used 97% similarity. Dada2 generated the most realistic number of ASVs (18S: 83, JB2: 75, JB3: 82), collectively identifying 30/39 mock species. The ribosomal marker outperformed the mitochondrial markers in terms of species and genus‐level detections for both OTUs and ASVs. The number of taxonomic assignments of OTUs/ASVs was highest when the smallest reference database containing only nematode sequences was used and when sequences were truncated to the respective amplicon length. Overall, OTUs generated more species‐level detections, which were, however, associated with higher error rates compared to ASVs. Genus‐level assignments using ASVs exhibited higher accuracy and lower error rates compared to species‐level assignments, suggesting that this is the most reliable pipeline for rapid assessment of alpha diversity from environmental samples.

Summary: Recent studies have questioned the use of high‐throughput sequencing of the nuclear ribosomal internal transcribed spacer (ITS) region to derive a semi‐quantitative representation of fungal community composition. However, comprehensive studies that quantify biases occurring during PCR and sequencing of ITS amplicons are still lacking.We used artificially assembled communities consisting of 10 ITS‐like fragments of varying lengths and guanine‐cytosine (GC) contents to evaluate and quantify biases during PCR and sequencing with Illumina MiSeq, PacBio RS II and PacBio Sequel I technologies.Fragment length variation was the main source of bias in observed community composition relative to the template, with longer fragments generally being under‐represented for all sequencing platforms. This bias was three times higher for Illumina MiSeq than for PacBio RS II and Sequel I. All 10 fragments in the artificial community were recovered when sequenced with PacBio technologies, whereas the three longest fragments (> 447 bases) were lost when sequenced with Illumina MiSeq. Fragment length bias also increased linearly with increasing number of PCR cycles but could be mitigated by optimization of the PCR setup. No significant biases related to GC content were observed.Despite lower sequencing output, PacBio sequencing was better able to reflect the community composition of the template than Illumina MiSeq sequencing. [ABSTRACT FROM AUTHOR]

Oomycetes are eukaryotic plant pathogens that require health monitoring. High-throughput sequencing (HTS) methods replace progressively cultivation-based approaches in soil surveys of Oomycetes, but very little control has been done from synthetic communities. Indeed, several potential biases do exist and need to be assessed for Oomycetes communities. We created a mock community by mixing DNA from 24 Phytophthora species. We amplified two barcode regions with Oomycete-specific primers before HTS. With this aim, we used three primer sets in nested PCR amplification, targeting the ITS-1 region or the RAS gene region. The three nested PCR strategies proved to be a reliable qualitative approach, identifying approximately 95% of the species after Illumina Miseq sequencing and bioinformatic analysis. However, quantitative proportions of each species showed distortions compared to the original mixture of the mock. In addition, we compared the two ITS primer sets on soil environmental DNA sampled from temperate forests. The 'oom18S-ITS7/18ph2f-5.8S-1R' primer set, more specific to Phytophthora, was able to detect seven Phytophthora species, confirming what was expected for temperate forests. Using the 'DC6-ITS7/oom18S-ITS7' primer set that covers the broader Peronosporaceans, we detected only one Phytophthora species among the dominance of Pythium and Phytopythium species. We concluded that 'oom18S-ITS7/18ph2f-5.8S-1R' primer set is a reliable tool for the qualitative description of environmental Phytophthora communities. [ABSTRACT FROM AUTHOR]

High‐throughput sequencing has the potential to describe biological communities with high efficiency yet comprehensive assessment of diversity with species‐level resolution remains one of the most challenging aspects of metabarcoding studies. We investigated the utility of curated ribosomal and mitochondrial nematode reference sequence databases for determining phylum‐specific species‐level clustering thresholds. We compiled 438 ribosomal and 290 mitochondrial sequences which identified 99% and 94% as the species delineation clustering threshold, respectively. These thresholds were evaluated in HTS data from mock communities containing 39 nematode species as well as environmental samples from Vietnam. We compared the taxonomic description of the mocks generated by two read‐merging and two clustering algorithms and the cluster‐free Dada2 pipeline. Taxonomic assignment with the RDP classifier was assessed under different training sets. Our results showed that 36/39 mock nematode species were identified across the molecular markers (18S: 32, JB2: 19, JB3: 21) in UClust_ref OTUs at their respective clustering thresholds, outperforming UParse_denovo and the commonly used 97% similarity. Dada2 generated the most realistic number of ASVs (18S: 83, JB2: 75, JB3: 82), collectively identifying 30/39 mock species. The ribosomal marker outperformed the mitochondrial markers in terms of species and genus‐level detections for both OTUs and ASVs. The number of taxonomic assignments of OTUs/ASVs was highest when the smallest reference database containing only nematode sequences was used and when sequences were truncated to the respective amplicon length. Overall, OTUs generated more species‐level detections, which were, however, associated with higher error rates compared to ASVs. Genus‐level assignments using ASVs exhibited higher accuracy and lower error rates compared to species‐level assignments, suggesting that this is the most reliable pipeline for rapid assessment of alpha diversity from environmental samples. Curated DNA barcode data were used to delineate nematode‐specific inter‐specific operational taxonomic unit (OTUs) clustering thresholds, which were subsequently tested on a artificial nematode community and environmental samples. Open‐reference clustering (UClust_ref) at these empirically derived thresholds outperformed denovo (UParse) as well as cluster‐free approaches (DADA2), resulting in the most accurate description of the nematode community. [ABSTRACT FROM AUTHOR]

DNA metabarcoding is widely used to study prokaryotic and eukaryotic microbial diversity. Technological constraints limit most studies to marker lengths below 600 base pairs (bp). Longer sequencing reads of several thousand bp are now possible with third‐generation sequencing. Increased marker lengths provide greater taxonomic resolution and allow for phylogenetic methods of classification, but longer reads may be subject to higher rates of sequencing error and chimera formation. In addition, most bioinformatics tools for DNA metabarcoding were designed for short reads and are therefore unsuitable. Here, we used Pacific Biosciences circular consensus sequencing (CCS) to DNA‐metabarcode environmental samples using a ca. 4,500 bp marker that included most of the eukaryote SSU and LSU rRNA genes and the complete ITS region. We developed an analysis pipeline that reduced error rates to levels comparable to short‐read platforms. Validation using a mock community indicated that our pipeline detected 98% of chimeras de novo. We recovered 947 OTUs from water and sediment samples from a natural lake, 848 of which could be classified to phylum, 397 to genus and 330 to species. By allowing for the simultaneous use of three databases (Unite, SILVA and RDP LSU), long‐read DNA metabarcoding provided better taxonomic resolution than any single marker. We foresee the use of long reads enabling the cross‐validation of reference sequences and the synthesis of ribosomal rRNA gene databases. The universal nature of the rRNA operon and our recovery of >100 nonfungal OTUs indicate that long‐read DNA metabarcoding holds promise for studies of eukaryotic diversity more broadly. [ABSTRACT FROM AUTHOR]

Abstract: Microbial ecology has been profoundly advanced by the ability to profile complex microbial communities by sequencing of marker genes amplified from environmental samples. However, inclusion of appropriate controls is vital to revealing the limitations and biases of this technique. “Mock community” samples, in which the composition and relative abundances of community members are known, are particularly valuable for guiding library preparation and data processing decisions. I generated a set of three mock communities using 19 different fungal taxa and demonstrate their utility by contrasting amplicon sequencing data obtained for the same communities under modifications to PCR conditions during library preparation. Increasing the number of PCR cycles elevated rates of chimera formation, and of errors in the final data set. Extension time during PCR had little impact on chimera formation, error rate or observed community structure. Polymerase fidelity impacted error rates significantly. Despite a high error rate, a master mix optimized to minimize amplification bias yielded profiles that were most similar to the true community structure. Bias against particular taxa differed among ITS1 vs. ITS2 loci. Preclustering nearly identical reads substantially reduced error rates, but did not improve similarity to the expected community structure. Inaccuracies in amplicon sequence‐based estimates of fungal community structure were associated with amplification bias and size selection processes, as well as variable culling rates among reads from different taxa. In some cases, the numerically dominant taxon was completely absent from final data sets, highlighting the need for further methodological improvements to avoid biased observations of community profiles. [ABSTRACT FROM AUTHOR]

DNA metabarcoding is a promising method for describing communities and estimating biodiversity. This approach uses high-throughput sequencing of targeted markers to identify species in a complex sample. By convention, sequences are clustered at a predefined sequence divergence threshold (often 3%) into operational taxonomic units ( OTUs) that serve as a proxy for species. However, variable levels of interspecific marker variation across taxonomic groups make clustering sequences from a phylogenetically diverse dataset into OTUs at a uniform threshold problematic. In this study, we use mock zooplankton communities to evaluate the accuracy of species richness estimates when following conventional protocols to cluster hypervariable sequences of the V4 region of the small subunit ribosomal RNA gene (18S) into OTUs. By including individually tagged single specimens and 'populations' of various species in our communities, we examine the impact of intra- and interspecific diversity on OTU clustering. Communities consisting of single individuals per species generated a correspondence of 59-84% between OTU number and species richness at a 3% divergence threshold. However, when multiple individuals per species were included, the correspondence between OTU number and species richness dropped to 31-63%. Our results suggest that intraspecific variation in this marker can often exceed 3%, such that a single species does not always correspond to one OTU. We advocate the need to apply group-specific divergence thresholds when analyzing complex and taxonomically diverse communities, but also encourage the development of additional filtering steps that allow identification of artifactual rRNA gene sequences or pseudogenes that may generate spurious OTUs. [ABSTRACT FROM AUTHOR]