Enhanced functional divergence of duplicate genes several million years after gene duplication in the <i>Arabidopsis</i> lineage
Bibliographic record
Abstract
Abstract Lineage-specifically duplicated genes likely contribute to the phenotypic divergence in closely related species. However, neither the frequency of duplication events nor the degree of selective pressures immediately after gene duplication is clear in the speciation process. Plants have substantially higher gene duplication rates than most other eukaryotes. Here, using Illumina short reads from Arabidopsis halleri , which has highly qualified plant genomes in close species ( Brassica rapa, A. thaliana and A. lyrata ), we succeeded in generating orthologous gene groups among B. rapa, A. thaliana, A. lyrata and A. halleri . The frequency of duplication events in the Arabidopsis lineage was approximately 10 times higher than the frequency inferred by comparative genomics of Arabidopsis , poplar, rice and moss. Of the currently retained genes in A. halleri , 11–24% had undergone gene duplication in the Arabidopsis lineage. To examine the degree of selective pressure for duplicated genes, we calculated the ratios of nonsynonymous to synonymous substitution rates ( K A / K S ) in the A. halleri-lyrata and A. halleri lineages. Using a maximum-likelihood framework, we examined positive ( K A / K S > 1) and purifying selection ( K A / K S < 1) at a significant level (P < 0.01). Duplicate genes tended to have a higher proportion of positive selection compared with non-duplicated genes. More interestingly, we found that functional divergence of duplicated genes was accelerated several million years after gene duplication at a higher proportion than immediately after gene duplication.
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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 | 0.000 |
| 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) | 0.001 | 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".