Gene expression differentiation in the reproductive tissues of <i>Drosophila willistoni</i> subspecies and their hybrids
Bibliographic record
Abstract
Early lineage diversification is central to understand what mutational events drive species divergence. Particularly, gene misregulation in interspecific hybrids can inform about what genes and pathways underlie hybrid dysfunction. In Drosophila hybrids, how regulatory evolution impacts different reproductive tissues remains understudied. Here, we generate a new genome assembly and annotation in Drosophila willistoni and analyse the patterns of transcriptome divergence between two allopatrically evolved D. willistoni subspecies, their male sterile and female fertile hybrid progeny across testis, male accessory gland, and ovary. Patterns of transcriptome divergence and modes of regulatory evolution were tissue-specific. Despite no indication for cell-type differences in hybrid testis, this tissue exhibited the largest magnitude of expression differentiation between subspecies and between parentals and hybrids. No evidence for anomalous dosage compensation in hybrid male tissues was detected nor was a differential role for the neo- and the ancestral arms of the D. willistoni X chromosome. Compared to the autosomes, the X chromosome appeared enriched for transgressively expressed genes in testis despite being the least differentiated in expression between subspecies. Evidence for fine genome clustering of transgressively expressed genes suggests a role of chromatin structure on hybrid gene misregulation. Lastly, transgressively expressed genes in the testis of the sterile male progeny were enriched for GO terms not typically associated with sperm function, instead hinting at anomalous development of the reproductive tissue. Our thorough tissue-level portrait of transcriptome differentiation between recently diverged D. willistoni subspecies and their hybrids provides a more nuanced view of early regulatory changes during speciation.
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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 | 0.000 | 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) | 0.001 | 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".