Are We Overestimating Protistan Diversity in Nature?

Caron, David A.; Hu, Sarah K.

doi:10.1016/j.tim.2018.10.009

Cited by 84 publications

(68 citation statements)

References 79 publications

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“…This is the case for many parasitic protists ( Weber & Pawlowski, 2014). This can artificially increase diversity estimates as single taxa can then be 177 treated as different species or, if intraspecific sequence diversity is high, as different taxonomic groups 178 (Caron & Hu, 2019). 179…”

Section: Introduction 41mentioning

confidence: 99%

A user guide to environmental protistology: primers, metabarcoding, sequencing, and analyses

Geisen¹,

Vaulot

Mahé

et al. 2019

Preprint

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23Protists -all eukaryotes besides fungi, animals, and plants -represent a major part of the taxonomic 24 and functional diversity of eukaryotic life on the planet and drive many ecosystem processes. However, 25 knowledge of protist communities and their diversity lags behind that of most other groups of 26 organisms, largely due to methodological constraints. While protist communities differ markedly 27 between habitats and biomes, they can be studied in very similar ways. Here we provide a guide to 28 current molecular approaches used for studying protist diversity, with a particular focus on amplicon-29 based high-throughput sequencing (metabarcoding). We highlight that the choice of suitable primers 30 artificially alters community profiles observed in metabarcoding studies. While there are no true 31 'universal' primers to target all protist taxa as a whole, we identify some primer combinations with a 32 wide taxonomic coverage and provide detailed information on their properties. Although 33 environmental protistan ecological research will probably shift towards PCR-free metagenomics 34 or/and transcriptomic approaches in a near future, metabarcoding will remain the method of choice 35 for in-depth community analyses and taxon inventories in biodiversity surveys and ecological studies, 36 due its great cost-efficiency, sensitivity, and throughput. In this paper we provide a guide for scientists 37 from a broad range of disciplines to implement protists in their ecological analyses. 38

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Section: Introduction 41mentioning

confidence: 99%

A user guide to environmental protistology: primers, metabarcoding, sequencing, and analyses

Geisen¹,

Vaulot

Mahé

et al. 2019

Preprint

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show abstract

“…Tools used to estimate protist diversity, including advances in microscopical and molecular techniques, have evolved rapidly since the 1950s (Pawlowski et al. , Caron and Hu ). Morphology has always been and remains the central criterion for delineating protist species.…”

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confidence: 99%

Comparing Morphological and Molecular Estimates of Species Diversity in the Freshwater Genus Synura (Stramenopiles): A Model for Understanding Diversity of Eukaryotic Microorganisms

Škaloud

Škaloudová

Jadrná

et al. 2020

Journal of Phycology

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We performed a comparison of molecular and morphological diversity in a freshwater colonial genus Synura (Chrysophyceae, Stramenopiles), using the island of Newfoundland (Canada) as a case study. We examined the morphological species diversity in collections from 79 localities, and compared these findings to diversity based on molecular characters for 150 strains isolated from the same sites. Of 27 species or species‐level lineages identified, only one third was recorded by both molecular and morphological techniques, showing both approaches are complementary in estimating species diversity within this genus. Eight taxa, each representing young evolutionary lineages, were recovered only by sequencing of isolated colonies, whereas ten species were recovered only microscopically. Our complex investigation, involving both morphological and molecular examinations, indicates that our knowledge of Synura diversity is still poor, limited only to a few well‐studied areas. We revealed considerable cryptic diversity within the core S. petersenii and S. leptorrhabda lineages. We further resolved the phylogenetic position of two previously described taxa, S. kristiansenii and S. petersenii f. praefracta, propose species‐level status for S. petersenii f. praefracta, and describe three new species, S. vinlandica, S. fluviatilis, and S. cornuta. Our findings add to the growing body of literature detailing distribution patterns observed in the genus, ranging from cosmopolitan species, to highly restricted taxa, to species such as S. hibernica found along coastal regions on multiple continents. Finally, our study illustrates the usefulness of combining detailed morphological information with gene sequence data to examine species diversity within chrysophyte algae.

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“…This assumption, which is made by most metabarcoding studies (Bik et al, 2012;Blaxter et al, 2005;Taberlet, Bonin, Zinger, & Coissac, 2018), allowed us to infer relative occurrences of each protist taxonomic unit among all samples of each datasets and allowed to infer the co-occurrence and co-exclusion networks. However, all clustering programs used to construct OTUs make assumptions about the best ways to handle the environmental sequencing data (Callahan et al, 2016;Caron & Hu, 2018;Mahé et al, 2015;Nebel, Pfabel, Stock, Dunthorn, & Stoeck, 2011;Rognes, Flouri, Nichols, Quince, & Mahé, 2016;Zhang, Kapli, Pavlidis, & Stamatakis, 2013) and these assumptions, along with the choice of molecular markers, may or may not lead to under-or over-estimations of species diversity. Here the reads were clustered into OTU with the program Swarm Mahé, Rognes, Quince, Vargas, & Dunthorn, 2014), which uses local clustering thresholds and a breaking phase to construct the OTUs.…”

Section: Discussionmentioning

confidence: 99%

Relating network analyses to phylogenetic relatedness to infer protistan co-occurrences and co-exclusions in marine and terrestrial environments

Lentendu

Dunthorn

2020

Preprint

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We used two large-scale metabarcoding datasets to evaluate phylogenetic signals at global marine and regional terrestrial scales using co-occurrence and co-exclusion networks. Phylogenetic relatedness was estimated using either global pairwise sequence distance or phylogenetic distance and the significance of observed patterns relating networks and phylogenies were evaluated against two null models. In all datasets, we found that phylogenetically close OTUs significantly cooccurred more often, and OTUs with intermediate phylogenetic relatedness co-occurred less often, than expected by chance. Phylogenetically close OTUs co-excluded less often than expected by chance in the marine datasets only. Simultaneous excess of co-occurrences and co-exclusions were observed in the inversion zone between close and intermediate phylogenetic distance classes in marine surface. Similar patterns were observed by using either pairwise sequence or phylogenetic distances, and by using both null models. These results suggest that environmental filtering and dispersal limitation are the preponderant forces driving co-occurrence of protists in both environments, while signal of competitive exclusion was only detected in the marine surface environment. The discrepancy in the co-exclusion pattern is potentially linked to the individual 1 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 environments: water bodies are more homogeneous while tropical forest soils contain a myriad of nutrient rich micro-environment reducing the strength of mutual exclusion.

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Are We Overestimating Protistan Diversity in Nature?

Cited by 84 publications

References 79 publications

A user guide to environmental protistology: primers, metabarcoding, sequencing, and analyses

A user guide to environmental protistology: primers, metabarcoding, sequencing, and analyses

Comparing Morphological and Molecular Estimates of Species Diversity in the Freshwater Genus Synura (Stramenopiles): A Model for Understanding Diversity of Eukaryotic Microorganisms

Relating network analyses to phylogenetic relatedness to infer protistan co-occurrences and co-exclusions in marine and terrestrial environments

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