Comparative functional characterization of the CSR-1 22G-RNA pathway in Caenorhabditis nematodes
Bibliographic record
Abstract
As a champion of small RNA research for two decades, Caenorhabditis elegans has revealed the essential Argonaute CSR-1 to play key nuclear roles in modulating chromatin, chromosome segregation and germline gene expression via 22G-small RNAs. Despite CSR-1 being preserved among diverse nematodes, the conservation and divergence in function of the targets of small RNA pathways remains poorly resolved. Here we apply comparative functional genomic analysis between C. elegans and Caenorhabditis briggsae to characterize the CSR-1 pathway, its targets and their evolution. C. briggsae CSR-1-associated small RNAs that we identified by immunoprecipitation-small RNA sequencing overlap with 22G-RNAs depleted in cbr-csr-1 RNAi-treated worms. By comparing 22G-RNAs and target genes between species, we defined a set of CSR-1 target genes with conserved germline expression, enrichment in operons and more slowly evolving coding sequences than other genes, along with a small group of evolutionarily labile targets. We demonstrate that the association of CSR-1 with chromatin is preserved, and show that depletion of cbr-csr-1 leads to chromosome segregation defects and embryonic lethality. This first comparative characterization of a small RNA pathway in Caenorhabditis establishes a conserved nuclear role for CSR-1 and highlights its key role in germline gene regulation across multiple animal 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 | 0.001 | 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".