Targeted loss of heterozygosity in <i>Candida albicans</i> using CRISPR-Cas9 reveals the functional impact of allelic variation
Bibliographic record
Abstract
The diploid genome of the fungal pathogen Candida albicans is highly heterozygous, with most allele pairs diverging at either the coding or regulatory level. When faced with selection pressure like antifungal exposure, this hidden genetic diversity can provide a reservoir of adaptive mutations through loss of heterozygosity (LOH) events. Validating the potential phenotypic impact of LOH events observed in clinical or experimentally evolved strains can be difficult due to the challenge of precisely targeting one allele over the other. Here, we show that a CRISPR-Cas9 system can be used to overcome this challenge. By designing allele-specific guide RNA sequences, we can induce targeted, directed LOH events, which we validate by whole-genome long-read sequencing. Using this approach, we efficiently recapitulate a recently described LOH event that increases resistance to the antifungal fluconazole. Additionally, we find that the recombination tracts of these induced LOH events have similar lengths to those observed naturally. To facilitate future use of this method, we provide a database of allele-specific sgRNA sequences for Cas9 that provide near genome-wide coverage of heterozygous sites through either direct or indirect targeting. This approach will be useful in probing the adaptive role of LOH events in this important human pathogen.
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How this classification was reachedexpand
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) | 0.000 | 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 | 0.000 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".