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Record W4403359691 · doi:10.1002/edn3.70022

<scp>V9</scp> Hypervariable Region Metabarcoding Primers for Euglenozoa and Metamonada

2024· article· en· W4403359691 on OpenAlexaff
Sebastian Cristian Treitli, Zoltán Füssy, Kristína Záhonová, Blanka Hamplová, Štěpánka Hrdá, Vladimı́r Hampl

Bibliographic record

VenueEnvironmental DNA · 2024
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicProtist diversity and phylogeny
Canadian institutionsUniversity of Alberta
FundersGrantová Agentura České Republiky
KeywordsHypervariable regionBiologyGeneticsGene

Abstract

fetched live from OpenAlex

ABSTRACT Short amplicon sequencing is a commonly used method to study the diversity of organisms in various habitats. The hypervariable regions of the small subunit rRNA gene (18S rDNA) are the most general barcodes for eukaryotes, which can provide detailed taxonomic information across a wide range of eukaryotic diversity. However, some organisms are often missed by universal primers, which have difficulty amplifying their barcodes. In this study, specific primers were designed for the amplification of the highly diverse 18S‐V9 region of the Euglenozoa and Metamonada groups. The performance of the newly designed primers—V9Eug and V9Meta—was compared with the universal V9 primer on cultured communities derived from a range of freshwater environments of the Soos Natural Reserve and the Slavkov Forest in the Czech Republic. The V9Eug primer was more specific with Euglenozoa representing 91.8% of reads and 57.0% of OTUs, while the V9Meta primer showed lower specificity with only 48.4% of reads and 19.7% of OTUs assigned to Metamonada. Both the Euglenozoa and Metamonada primer pairs significantly improved recovery of their target groups compared to the universal V9 primer pair, detecting 2.7 and 1.8 times more OTUs, respectively. These results provide a more sensitive protocol for studying the diversity of these eukaryotic taxa.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.492
Threshold uncertainty score0.493

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.010
GPT teacher head0.196
Teacher spread0.186 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations7
Published2024
Admission routes1
Has abstractyes

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