A New Oomycete Metabarcoding Method Using the <i>rps10</i> Gene
Bibliographic record
Abstract
Oomycetes are a group of eukaryotes related to brown algae and diatoms, many of which cause plant and animal diseases. Improved methods are needed for rapid and accurate characterization of oomycete communities using DNA metabarcoding. We have evaluated the mitochondrial 40S ribosomal protein S10 ( rps10) gene as a locus for oomycete metabarcoding and provide primers predicted to amplify this region from all oomycetes based on a wide range of available reference sequences. We evaluated its utility relative to the internal transcribed spacer 1 (ITS1), by sequencing environmental samples and a mock community using Illumina MiSeq. Amplified sequence variants (ASVs) and operational taxonomic units (OTUs) were identified per community. Observed sequences and predicted taxonomy of ASVs and OTUs were compared with the known composition of the mock community. Both rps10 and ITS yielded ASVs with sequences matching 21 of the 24 species in the mock community and matching all 24 when allowing for a 1-bp difference. Taxonomic classifications of ASVs included 23 members of the mock community for rps10 and 17 for ITS1. Sequencing results for the environmental samples suggest that the rps10 locus results in substantially less amplification of nontarget organisms than the ITS1 method. The amplified rps10 region also has higher taxonomic resolution than ITS1, allowing for greater discrimination of closely related species. We present a new website with a searchable rps10 reference database for species identification and all protocols needed for oomycete metabarcoding. The rps10 barcode and methods described herein provide an effective tool for metabarcoding oomycetes using short-read sequencing.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.006 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".