New Primers for Discovering Fungal Diversity Using Nuclear Large Ribosomal DNA
Bibliographic record
Abstract
Metabarcoding has become an important tool in the discovery of biodiversity, including fungi, which are the second most speciose group of eukaryotes, with diverse and important ecological roles in terrestrial ecosystems. We have designed and tested new PCR primers that target the D1 variable region of nuclear large subunit (LSU) ribosomal DNA; one set that targets the phylum Ascomycota and another that recovers all other fungal phyla. The primers yield amplicons compatible with the Illumina MiSeq platform, which is cost-effective and has a lower error rate than other high throughput sequencing platforms. The new primer set LSU200A-F/LSU476A-R (Ascomycota) yielded 95-98% of reads of target taxa from environmental samples, and primers LSU200-F/LSU481-R (all other fungi) yielded 72-80% of target reads. Both primer sets have fairly low rates of data loss, and together they cover a wide variety of fungal taxa. We compared our results with these primers by amplifying and sequencing a subset of samples using the previously described ITS3_KYO2/ITS4_KYO3 primers, which amplify the internal transcribed spacer 2 (ITS2) of Ascomycota and Basidiomycota. With approximately equivalent read depth, our LSU primers recovered a greater number and phylogenetic diversity of sequences than the ITS2 primers. For instance, ITS3_KYO2/ITS4_KYO3 primers failed to pick up any members of Eurotiales, Mytilinidiales, Pezizales, Saccharomycetales, or Venturiales within Ascomycota, or members of Exobasidiomycetes, Microbotryomycetes, Pucciniomycetes, or Tremellomycetes within Basidiomycota, which were retrieved in good numbers from the same samples by our LSU primers. Among the OTUs recovered using the LSU primers were 127 genera and 28 species that were not obtained using the ITS2 primers, although the ITS2 primers recovered 10 unique genera and 16 species that were not obtained using either of the LSU primers These features identify the new primer sets developed in this study as useful complements to other universal primers for the study of fungal diversity and community composition.
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 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 | 0.004 | 0.007 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 0.004 |
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".