Divergence in expression of a singing-related neuroplasticity gene in the brains of 2 <i>Ficedula</i> flycatchers and their hybrids
Bibliographic record
Abstract
Species-specific sexual traits facilitate species-assortative mating by reducing mating across species and reducing hybrid sexual attractiveness. For learned sexual traits, such as song in oscine birds, species distinctiveness can be eroded when species co-occur. Transcriptional regulatory divergence in brain regions involved in sensory learning is hypothesized to maintain species distinctiveness, but relatively few studies have compared gene expression in relevant brain regions between closely related species. Species differences in song are an important premating reproductive barrier between the collared (Ficedula albicollis) and pied flycatcher (F. hypoleuca). Here, we compare brain gene expression in adult males from each species and their naturally occurring F1 hybrids. We report overall conserved expression across species in a portion of the brain containing regions and nuclei known to be involved in song responses and learning. Further, among those genes that were differentially expressed between species, we find largely intermediate expression in hybrids. A single gene, SYT4 (synaptotagmin 4), known to be singing-associated, both was differentially expressed and has a putative upstream transcriptional regulatory factor containing fixed differences between the 2 species. Although a finer-scale investigation limited to song-specific regions may reveal further species differences, our findings provide insight into regulatory divergence in the brain between closely related species.
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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".