A customized nuclear target enrichment approach for developing a phylogenomic baseline for <i>Dioscorea</i> yams (Dioscoreaceae)
Bibliographic record
Abstract
Premise We developed a target enrichment panel for phylogenomic studies of Dioscorea, an economically important genus with incompletely resolved relationships. Methods Our bait panel comprises 260 low‐ to single‐copy nuclear genes targeted to work in Dioscorea, assessed here using a preliminary taxon sampling that includes both distantly and closely related taxa, including several yam crops and potential crop wild relatives. We applied coalescent‐based and maximum likelihood phylogenomic inference approaches to the pilot taxon set, incorporating new and published transcriptome data from additional species. Results The custom panel retrieved ~94% of targets and >80% of full gene length from 88% and 68% of samples, respectively. It has minimal gene overlap with existing panels designed for angiosperm‐wide studies and generally recovers longer and more variable targets. Pilot phylogenomic analyses consistently resolve most deep and recent relationships with strong support across analyses and point to revised relationships between the crop species D. alata and candidate crop wild relatives. Discussion Our customized panel reliably retrieves targeted loci from Dioscorea, is informative for resolving relationships in denser samplings, and is suitable for refining our understanding of the independent origins of cultivated yam species; the panel likely has broader promise for phylogenomic studies across Dioscoreales.
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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".