Comparative Transcriptomics of Alternative Developmental Phenotypes in a Marine Gastropod
Bibliographic record
Abstract
Alternative phenotypes are discrete phenotypic differences that develop in response to both genetic and environmental cues. Nutritive embryos, which arrest their development to serve as nutrition for their viable siblings, are an example of an alternative developmental phenotype found in many animal groups. Females of the marine snail, Crepidula navicella, produce broods that consist mainly of nutritive embryos and a small number of viable embryos. In order to better understand the genetic mechanisms that lead to the development of alternative phenotypes in this species, we compared the transcriptomes of viable and nutritive embryos at the earliest stage that we were able to distinguish visually between the two. Using high-throughput Illumina sequencing, we assembled and annotated a de novo transcriptome and compared transcript levels in viable and nutritive embryos. Viable embryos express high levels of transcripts associated with known developmental events, while nutritive embryos express high levels of apoptosis-related transcripts. Gene Ontology term enrichment with GOSeq found that these are associated with the negative regulation of apoptotic processes. This enrichment, combined with morphological evidence, suggests that apoptosis is important in the formation of gastrula-like nutritive embryos. Apoptosis has been implicated in the development of alternative phenotypes in other animal groups, raising the possibility that this mechanism's role in alternative phenotypes is conserved in gastropod development. We suggest possible alternative mechanisms of nutritive embryo development. Most importantly, we contribute further evidence to the hypothesis that nutritive embryos are an alternative developmental phenotype.
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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 | 0.000 |
| 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".