Escaping introns in <scp>COI</scp> through <scp>cDNA</scp> barcoding of mushrooms: <i>Pleurotus</i> as a test case
Bibliographic record
Abstract
Abstract DNA barcoding involves the use of one or more short, standardized DNA fragments for the rapid identification of species. A 648‐bp segment near the 5′ terminus of the mitochondrial cytochrome c oxidase subunit I (COI) gene has been adopted as the universal DNA barcode for members of the animal kingdom, but its utility in mushrooms is complicated by the frequent occurrence of large introns. As a consequence, ITS has been adopted as the standard DNA barcode marker for mushrooms despite several shortcomings. This study employed newly designed primers coupled with cDNA analysis to examine COI sequence diversity in six species of Pleurotus and compared these results with those for ITS. The ability of the COI gene to discriminate six species of Pleurotus, the commonly cultivated oyster mushroom, was examined by analysis of cDNA. The amplification success, sequence variation within and among species, and the ability to design effective primers was tested. We compared ITS sequences to their COI cDNA counterparts for all isolates. ITS discriminated between all six species, but some sequence results were uninterpretable, because of length variation among ITS copies. By comparison, a complete COI sequences were recovered from all but three individuals of Pleurotus giganteus where only the 5′ region was obtained. The COI sequences permitted the resolution of all species when partial data was excluded for P. giganteus. Our results suggest that COI can be a useful barcode marker for mushrooms when cDNA analysis is adopted, permitting identifications in cases where ITS cannot be recovered or where it offers higher resolution when fresh tissue is. The suitability of this approach remains to be confirmed for other mushrooms.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
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".