Pyrosequencing for Mini-Barcoding of Fresh and Old Museum Specimens
Bibliographic record
Abstract
DNA barcoding is an effective approach for species identification and for discovery of new and/or cryptic species. Sanger sequencing technology is the method of choice for obtaining standard 650 bp cytochrome c oxidase subunit I (COI) barcodes. However, DNA degradation/fragmentation makes it difficult to obtain a full-length barcode from old specimens. Mini-barcodes of 130 bp from the standard barcode region have been shown to be effective for accurate identification in many animal groups and may be readily obtained from museum samples. Here we demonstrate the application of an alternative sequencing technology, the four-enzymes single-specimen pyrosequencing, in rapid, cost-effective mini-barcode analysis. We were able to generate sequences of up to 100 bp from mini-barcode fragments of COI in 135 fresh and 50 old Lepidoptera specimens (ranging from 53-97 year-old). The sequences obtained using pyrosequencing were of high quality and we were able to robustly match all the tested pyro-sequenced samples to their respective Sanger-sequenced standard barcode sequences, where available. Simplicity of the protocol and instrumentation coupled with higher speed and lower cost per sequence than Sanger sequencing makes this approach potentially useful in efforts to link standard barcode sequences from unidentified specimens to known museum specimens with only short DNA fragments.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| 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 teacher head, 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".