Towards Improved Reconstruction of Ancestral Gene Order in Angiosperm Phylogeny
Bibliographic record
Abstract
Whole genome doubling (WGD), a frequent occurrence during the evolution of the angiosperms, complicates ancestral gene order reconstruction due to the multiplicity of solutions to the genome halving process. Using the genome of a related species (the outgroup) to guide the halving of a WGD descendant attenuates this problem. We investigate a battery of techniques for further improvement, including an unbiased version of the guided genome halving algorithm, reference to two related genomes instead of only one to guide the reconstruction, use of draft genome sequences in contig form only, incorporation of incomplete sets of homology correspondences among the genomes, and addition of large numbers of "singleton" correspondences. We make use of genomic distance, breakpoint reuse rate, dispersion of sets of alternate solutions, and other means to evaluate these techniques, and employ the papaya (Carica papaya) and grapevine (Vitis vinifera) genomes to reconstruct the pre-WGD ancestor of poplar (Populus trichocarpa), as well as an early rosid ancestor. A significant result is that the papaya genome has rearranged at a greater rate from the rosid ancestor than phylogenetic relationships would predict.
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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 | 0.002 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| 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".