Guide RNAs containing universal bases enable Cas9/Cas12a recognition of polymorphic sequences
Bibliographic record
Abstract
CRISPR/Cas complexes enable precise gene editing in a wide variety of organisms. While the rigid identification of DNA sequences by these systems minimizes the potential for off-target effects, it consequently poses a problem for the recognition of sequences containing naturally occurring polymorphisms. The presence of genetic variance such as single nucleotide polymorphisms (SNPs) in a gene sequence can compromise the on-target activity of CRISPR systems. Thus, when attempting to target multiple variants of a human gene, or evolved variants of a pathogen gene using a single guide RNA, more flexibility is desirable. Here, we demonstrate that Cas9 can tolerate the inclusion of universal bases in individual guide RNAs, enabling simultaneous targeting of polymorphic sequences. Crucially, we find that specificity is selectively degenerate at the site of universal base incorporation, and remains otherwise preserved. We demonstrate the applicability of this technology to targeting multiple naturally occurring human SNPs with individual guide RNAs and to the design of Cas12a/Cpf1-based DETECTR probes capable of identifying multiple evolved variants of the HIV protease gene. Our findings extend the targeting capabilities of CRISPR/Cas systems beyond their canonical spacer sequences and highlight a use of natural and synthetic universal bases.
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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".