Identification of essential genes in <i>Caenorhabditis elegans</i> through whole-genome sequencing of legacy mutant collections
Bibliographic record
Abstract
It has been estimated that 15%-30% of the ∼20,000 genes in C. elegans are essential, yet many of these genes remain to be identified or characterized. With the goal of identifying unknown essential genes, we performed whole-genome sequencing on complementation pairs from legacy collections of maternal-effect lethal and sterile mutants. This approach uncovered maternal genes required for embryonic development and genes with apparent sperm-specific functions. In total, 58 putative essential genes were identified on chromosomes III-V, of which 52 genes are represented by novel alleles in this collection. Of these 52 genes, 19 (40 alleles) were selected for further functional characterization. The terminal phenotypes of embryos were examined, revealing defects in cell division, morphogenesis, and osmotic integrity of the eggshell. Mating assays with wild-type males revealed previously unknown male-expressed genes required for fertilization and embryonic development. The result of this study is a catalog of mutant alleles in essential genes that will serve as a resource to guide further study toward a more complete understanding of this important model organism. As many genes and developmental pathways in C. elegans are conserved and essential genes are often linked to human disease, uncovering the function of these genes may also provide insight to further our understanding of human biology.
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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".