Genome Editing in <i>Caenorhabditis briggsae</i> using the CRISPR/Cas9 System
Bibliographic record
Abstract
Author Summary The CRISPR/Cas9 system has recently emerged as a powerful tool to engineer the genome of an organism. The system is adopted from bacteria where it confers immunity against invading foreign DNA. This work reports the first successful use of the CRISPR/Cas9 system in C. briggsae , a cousin of the well-known nematode C. elegans . We used two plasmids, one expressing Cas9 endonuclease and the other an engineered CRISPR RNA corresponding to the DNA sequence to be cleaved. Our approach allows for the generation of loss-of-function mutations in C. briggsae genes thereby facilitating a comparative study of gene function between nematodes. Abstract The CRISPR/Cas9 system is an efficient technique for generating targeted alterations in an organism’s genome. Here we describe a methodology for using the CRISPR/Cas9 system to generate mutations via non-homologous end joining in the nematode Caenorhabditis briggsae, a sister species of C. elegans . Evidence for somatic mutations and off-target mutations are also reported. The use of the CRISPR/Cas9 system in C. briggsae will greatly facilitate comparative studies to C. elegans.
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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 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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".