Conserved Gene Expression Plasticity in Development Is More Pervasive Than Expression Divergence Between Species of <i>Caenorhabditis</i> Nematodes
Bibliographic record
Abstract
Diverse regulatory mechanisms enable precise spatio-temporal control of gene expression across developmental stages, tissues, and sexes, contributing to the proper development of the organism. Evolutionary divergence leads to species-specific gene expression patterns, even in preserved developmental structures, due to regulatory changes that can disproportionately influence subsets of developmental genetic networks. Here, we quantify the evolution of sex-biased and tissue-biased transcriptomes from two tissue types (gonad and soma) for each of two sexes (male and female) from two of the closest known sister species of Caenorhabditis nematodes (C. remanei and C. latens). Differential gene expression and co-expression network analyses identify gene sets with distinct transcriptomic profiles, revealing widespread divergence between these morphologically and developmentally cryptic sister species. The transcriptomic divergence occurs despite most genes showing conserved expression across tissues and sexes. These observations implicate shared selection pressures related to tissue and sex differences as outweighing species-specific selection and developmental system drift in shaping overall transcriptome profiles. Although developmentally plastic tissue-biased expression profiles are mostly conserved between species, we find that sex-biased genes, particularly male-biased genes, contribute disproportionately to species-differences in gene expression, consistent with a disproportionate role for male-biased selection driving gene expression divergence.
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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".