Efficient genome editing using tRNA promoter-driven CRISPR/Cas9 gRNA in Aspergillus niger
Bibliographic record
Abstract
As a powerful tool for fast and precise genome editing, the CRISPR/Cas9 system has been applied in filamentous fungi to improve the efficiency of genome alteration. However, the method of delivering guide RNA (gRNA) remains a bottleneck in performing CRISPR mutagenesis in Aspergillus species. Here we report a gRNA transcription driven by endogenous tRNA promoters which include a tRNA gene plus 100 base pairs of upstream sequence. Co-transformation of a cas9-expressing plasmid with a linear DNA coding for gRNA demonstrated that 36 of the 37 tRNA promoters tested were able to generate the intended mutation in A. niger. When gRNA and cas9 were expressed in a single extra-chromosomal plasmid, the efficiency of gene mutation was as high as 97%. Co-transformation with DNA template for homologous recombination, the CRISPR/Cas9 system resulted ~42% efficiency of gene replacement in a strain with a functioning non-homologous end joining machinery (kusA+), and an efficiency of >90% gene replacement in a kusA- background. Our results demonstrate that tRNA promoter-mediated gRNA expressions are reliable and efficient in genome editing in A. niger.
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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 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".