Bibliographic record
Abstract
Although introns were first discovered almost 30 years ago, their evolutionary origin remains elusive. In this work, we used multispecies whole-genome alignments to map Drosophila melanogaster introns onto 10 other fully sequenced Drosophila genomes. We were able to find 1,944 sites where an intron was missing in one or more species. We show that for most (>80%) of these cases, there is no leftover intronic sequence or any missing exonic sequence, indicating exact intron loss or gain events. We used parsimony to classify these differences as 1,754 intron loss events and 213 gain events. We show that lost and gained introns are significantly shorter than average and flanked by longer than average exons. They also display quite distinct phase distributions and show greater than average similarity between the 5' splice site and its 3' partner splice site. Introns that have been lost in one or more species evolve faster than other introns, occur in slowly evolving genes, and are found adjacent to each other more often than would be expected for independent single losses. Our results support the cDNA recombination mechanism of intron loss, suggest that selective pressures affect site-specific loss rates, and show conclusively that intron gain has occurred within the Drosophila lineage, solidifying the "introns-middle" hypothesis and providing some hints about the gain mechanism.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.000 | 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 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".