Conserved Genes in Highly Regenerative Metazoans Are Associated with Planarian Regeneration
Bibliographic record
Abstract
Metazoan species depict a wide spectrum of regeneration ability which calls into question the evolutionary origins of the underlying processes. Since species with high regeneration ability are widely distributed throughout metazoans, there is a possibility that the metazoan ancestor had an underlying common molecular mechanism. Early metazoans like sponges possess high regenerative ability, but, due to the large differences they have with Cnidaria and Bilateria regarding symmetry and neuronal systems, it can be inferred that this regenerative ability is different. We hypothesized that the last common ancestor of Cnidaria and Bilateria possessed remarkable regenerative ability which was lost during evolution. We separated Cnidaria and Bilateria into three classes possessing whole-body regenerating, high regenerative ability, and low regenerative ability. Using a multiway BLAST and gene phylogeny approach, we identified genes conserved in whole-body regenerating species and lost in low regenerative ability species and labeled them Cnidaria and Bilaterian regeneration genes. Through transcription factor analysis, we identified that Cnidaria and Bilaterian regeneration genes were associated with an overabundance of homeodomain regulatory elements. RNA interference of Cnidaria and Bilaterian regeneration genes resulted in loss of regeneration phenotype for HRJDa, HRJDb, DUF21, DISP3, and ARMR genes. We observed that DUF21 knockdown was highly lethal in the early stages of regeneration indicating a potential role in wound response. Also, HRJDa, HRJDb, DISP3, and ARMR knockdown showed loss of regeneration phenotype after second amputation. The results strongly correlate with their respective RNA-seq profiles. We propose that Cnidaria and Bilaterian regeneration genes play a major role in regeneration across highly regenerative Cnidaria and Bilateria.
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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".