Fifteen Years of Evolutionary Genomics in<i>Caenorhabditis elegans</i>
Bibliographic record
Abstract
Abstract The nematode worm Caenorhabditis elegans , introduced by Sydney Brenner for the genetic analysis of nervous system formation, is now a powerful model organism for studying nearly all aspects of biology, from development to diseases to evolution. Sequencing and analysis of the worm genome revealed intriguing nonrandom patterns of genome organisation and unusual features such as abundant operons. Surprising upon first discovery, worms and humans have a similar number of genes that are comprised of a similar proportion of transcription factors to regulate their genomes. However, differences in small ribonucleic acid content may contribute to differences in organismal complexity. In nature, the bacterivorous C. elegans is found primarily on rotting vegetation in temperate regions across the world. Natural selection, combined with the low effective recombination rate associated with selfing, strongly reduces nucleotide variation across the genome, yielding similarly low polymorphism to other selfing hermaphrodite species ofCaenorhabditis. The genusCaenorhabditisprovides a superb model system for ecological and evolutionary genetics, benefiting from C. elegans tools and information when applied to investigations of species with a higher polymorphism and better known ecological context. Key Concepts: The nematodeCaenorhabditis elegans, introduced by Sydney Brenner for the genetic analysis of nervous system development, was the first metazoan to have a complete sequenced genome and is now a model organism for nearly all fields of biology. Many genomic features are not randomly distributed along C. elegans chromosomes and are prevalent either in the chromosome arms or in its centre. An unusually large fraction of protein‐coding genes is organised in operons, possibly optimising transcriptional resources during recovery from developmental arrest. Gene duplication and alternative splicing contribute to extensive diversification of gene function, with 10.5% of protein‐coding genes having paralogs and 25% of genes being alternatively spliced. The ratio of transcription factors to protein‐coding genes is similar in worms and humans but the two species differ greatly in their microRNA content. The differences in chromatin states contribute to phenotypic variation and the transgenerational epigenetic inheritance suggests a role for epigenetic information in evolution. The rate of duplication is two orders of magnitude greater than the nucleotide mutation rate, highlighting the role of gene duplication in the evolution of the C. elegans genome. Caenorhabditisis not a soil nematode but instead proliferates and feeds on bacteria in rotting vegetation. Population genetic variation is strongly affected by the mating system ofCaenorhabditis, with very low polymorphism in selfing hermaphroditic species relative to outcrossing gonochoristic 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 | 0.005 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| 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".