Contribution of Functional Divergence Through Copy Number Variations to the Inter-Species and Intra-Species Diversity in Specialized Metabolites
Bibliographic record
Abstract
There is considerable diversity in the specialized metabolites within a single plant species (intra-species) and among different plant species (inter-species). The functional divergence associated with gene duplications largely contributes to the inter-species diversity in the specialized metabolites, whereas the intra-species diversity is due to gene dosage changes via gene duplications [i.e., copy number variants (CNVs)] at the intra-species level of evolution. This is because CNVs are thought to undergo associated with less functional divergence at the intra-species level of evolution. However, functional divergence caused by CNVs may induce specialized metabolite diversity at the intra-species and inter-species levels of evolution. We herein discuss the functional divergence of CNVs in metabolic quantitative trait genes (mQTGs). We focused on 5,654 previously identified mQTGs in 270 Arabidopsis thaliana accessions. The ratio of nonsynonymous to synonymous variations tends to be higher for mQTGs with CNVs than for mQTGs without CNVs within A. thaliana accessions, suggesting that CNVs are responsible for the functional divergence among mQTGs at the intra-species level of evolution. To evaluate the contribution of CNVs to inter-species diversity, we calculated the ratio of nonsynonymous to synonymous substitutions in the Arabidopsis lineage. The ratio tends to be higher for the mQTGs with CNVs than for the mQTGs without CNVs. Additionally, we determined that mQTGs with CNVs are subject to positive selection in the Arabidopsis lineage. Our data suggest that CNVs are closely related to functional divergence contributing to adaptations via the production of diverse specialized metabolites at the intra-species and inter-species levels of evolution.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| 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".