Understanding the spectacular failure of <scp>DNA</scp> barcoding in willows (<i>Salix</i>): Does this result from a trans‐specific selective sweep?
Bibliographic record
Abstract
Willows (Salix: Salicaceae) form a major ecological component of Holarctic floras and consequently are an obvious target for a DNA-based identification system. We surveyed two to seven plastid genome regions (~3.8 kb; ~3% of the genome) from 71 Salix species across all five subgenera, to assess their performance as DNA barcode markers. Although Salix has a relatively high level of interspecific hybridization, this may not sufficiently explain the near complete failure of barcoding that we observed: only one species had a unique barcode. We recovered 39 unique haplotypes, from more than 500 specimens, that could be partitioned into six major haplotype groups. A unique variant of group I (haplotype 1*) was shared by 53 species in three of five Salix subgenera. This unusual pattern of haplotype sharing across infrageneric taxa is suggestive of either a massive nonrandom coalescence failure (incomplete lineage sorting), or of repeated plastid capture events, possibly including a historical selective sweep of haplotype 1* across taxonomic sections. The former is unlikely as molecular dating indicates that haplotype 1* originated recently and is nested in the oldest major haplotype group in the genus. Further, we detected significant non-neutrality in the frequency spectrum of mutations in group I, but not outside group I, and demonstrated a striking absence of geographical (isolation by distance) effects in the haplotype distributions of this group. The most likely explanation for the patterns we observed involves recent repeated plastid capture events, aided by widespread hybridization and long-range seed dispersal, but primarily propelled by one or more trans-species selective sweeps.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".