Integrative analysis of young genes, positively selected genes and lncRNAs in the development of Drosophila melanogaster
Bibliographic record
Abstract
BACKGROUND: Young genes and genes under positive selection commonly contribute to adaptive phenotypic evolution. Early developmental stages are very important for establishing phenotypes, which might be helpful for studying the evolutionary patterns of these rapidly evolving genes. RESULTS: Here, we performed a weighted gene co-expression network analysis to identify modules of co-expressed genes at different stages of Drosophila melanogaster development. We found that young genes, including duplicated, orphan, and young lncRNA genes, are significantly enriched among modules associated with specific developmental stages. In addition, genes undergoing rapid amino acid sequence evolution driven by positive selection showed a similar proportion of essentiality with other genes, and enrichment in modules for specific developmental stages. CONCLUSIONS: Our integrative analysis revealed important roles for the origin of new genes and rapid amino acid sequence evolution in development that may account for specific phenotype evolution in Drosophila melanogaster.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.000 | 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 teacher head, 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".