Ancient genome duplications during the evolution of kiwifruit (Actinidia) and related Ericales
Bibliographic record
Abstract
BACKGROUND AND AIMS: To assess the number and phylogenetic distribution of large-scale genome duplications in the ancestry of Actinidia, publicly available expressed sequenced tags (ESTs) for members of the Actinidiaceae and related Ericales, including tea (Camellia sinensis), were analysed. METHODS: Synonymous divergences (K(s)) were calculated for all duplications within gene families and examined for evidence of large-scale duplication events. Phylogenetic comparisons for a selection of orthologues among several related species in Ericales and two outgroups permitted placement of duplication events in relation to lineage divergences. Gene ontology (GO) categories were analysed for each whole-genome duplication (WGD) and the whole transcriptome. KEY RESULTS: Evidence for three ancient WGDs in Actinidia was found. Analyses of paleologue GO categories indicated a different pattern of retained genes for each genome duplication, but a pattern consistent with the dosage-balance hypothesis among all retained paleologues. CONCLUSIONS: This study provides evidence for one independent WGD in the ancestry of Actinidia (Ad-alpha), a WGD shared by Actinidia and Camellia (Ad-beta), and the well-established At-gamma WGD that occurred prior to the divergence of all taxa examined. More ESTs in other taxa are needed to elucidate which groups in Ericales share the Ad-beta or Ad-alpha duplications and their impact on diversification.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.001 | 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".