Genome Editing by CRISPR-Cas: A Game Change in the Genetic Manipulation of Chlamydomonas
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Microalgae are promising photosynthetic unicellular eukaryotes among the most abundant on the planet and are considered as alternative sustainable resources for various industrial applications. Chlamydomonas is an emerging model for microalgae to be manipulated by multiple biotechnological tools in order to produce high-value bioproducts such as biofuels, bioactive peptides, pigments, nutraceuticals, and medicines. Specifically, Chlamydomonas reinhardtii has become a subject of different genetic-editing techniques adapted to modulate the production of microalgal metabolites. The main nuclear genome-editing tools available today include zinc finger nucleases (ZFNs), transcriptional activator-like effector nucleases (TALENs), and more recently discovered the clustered regularly interspaced short palindromic repeats (CRISPR)-CRISPR associated protein (Cas) nuclease system. The latter, shown to have an interesting editing capacity, has become an essential tool for genome editing. In this review, we highlight the available literature on the methods and the applications of CRISPR-Cas for C. reinhardtii genetic engineering, including recent transformation methods, most used bioinformatic tools, best strategies for the expression of Cas protein and sgRNA, the CRISPR-Cas mediated gene knock-in/knock-out strategies, and finally the literature related to CRISPR expression and modification approaches.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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) | 0.000 | 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 it