Comparative genomics of two closely related Acropora coral species with different spawning seasons reveals genomic regions possibly associated with gametogenesis
Bibliographic record
Abstract
Marine invertebrates release their gametes at an optimal time to produce the next generation. In reef-building scleractinian corals, synchronous spawning is essential for reproductive success. Molecular mechanisms of scleractinian gametogenesis have been studied; however, the mechanism by which coral gametes mature at specific times has yet to be discovered. The present study focused on two Acropora species with different spawning seasons. In Okinawa, Japan, Acropora digitifera spawns from May to June, whereas Acropora sp. 1 spawns in August. Comparative genomic analyses revealed that 60 genes are located in the diverged genomic regions between the two species, suggesting a possible association with timing of gametogenesis. Among candidate genes, we identified an Acropora sp. 1-specific amino acid change in gene WDR59, one of the components of a mTORC1 activator, GATOR2. Since regulation of gametogenesis by mTORC1 is widely conserved among eukaryotes, the difference in timing of gamete maturation observed in the two Acropora species may be caused by a substitution in WDR59 that slightly affects timing of mTORC1 activation via GATOR2. In addition, this substitution may lead to reproductive isolation between the two species, due to different spawning periods. Thus, we propose that A. digitifera and Acropora sp. 1 species pair is an effective model for studying coral speciation and understanding the molecular mechanisms that control coral spawning timing.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".