ArticleNature biotechnology2024
Prediction of on-target and off-target activity of CRISPR-Cas13d guide RNAs using deep learning.
Article in Nature biotechnology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 75 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
75 citing papers in PubMed, 110 citations in OpenAlex.
- Nanocarrier-Based Gene Delivery Systems: Mechanisms, Clinical Translation, and Future Perspectives.Biotechnology and bioengineering · 2026Review
- Advanced gene editing technologies for oncology mechanisms, applications, and clinical implementation.Cancer gene therapy · 2026Review
- Craspase Protease Activation Is Sensitive to Oncogenic Single-Nucleotide RNA Mismatches.ACS chemical biology · 2026Article
- Structural basis for target discrimination and activation by Cas13d.Science advances · 2026Article
- Catfish Transgenesis and Gene Editing: Overview, Recent Advances, and Future Perspectives.Biology · 2026Review
- Essential lncRNAs in the human transcriptome.Cell genomics · 2026Article
- Thermodynamically programmed one-pot CRISPR platform for point-of-care SNP genotyping.Nature communications · 2026Article
- RNA-triggered cell killing with CRISPR-Cas12a2.Nature · 2026Article
- The Use of Deep Learning in RNA Therapeutic Development.ACS nano · 2026Review
- Machine Learning for CRISPR-Based Diagnostics.International journal of molecular sciences · 2026Review
- Harnessing Deep Learning Models for Guide RNA Optimization and Off-Target Prediction in CRISPR Systems.Biotechnology journal · 2026Review
- Applications of Gene-Editing Technologies in Enhancing Crop Stress Resistance with Emphasis on Rice.Plants (Basel, Switzerland) · 2026Review
- All-in-one, Cas13d-based cell-specific gene knockdown system for zebrafish.bioRxiv : the preprint server for biology · 2026Article
- Photoactivatable CRISPR/Cas13d via upconversion nanoparticles for deep tissue RNA engineering and orthopedic therapy.Nature communications · 2026Article
- A foundation model for nucleotide sequences.Nucleic acids research · 2026Article
- Artificial intelligence-enabled multi-scale virtual cell: perspective, challenges, and opportunities.Briefings in bioinformatics · 2026Review
- Harnessing artificial intelligence to advance CRISPR-based genome editing technologies.Nature reviews. Genetics · 2026Review
- AI-driven CRISPR screening: optimizing gene editing through automation and intelligent decision support.Journal of translational medicine · 2026Review
- Characterization of gRNA-dependent and gRNA-independent off-target binding sites of PspCas13b and RfxCas13d in mammalian cells.Nucleic acids research · 2026Article
- Toehold-VISTA: a machine learning approach to decipher programmable RNA sensor-target interactions.Nucleic acids research · 2026Article
15 more citing papers are in PubMed but not listed here.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors at 3 institutions in 1 country.
Funding
Abstract
Transcriptome engineering applications in living cells with RNA-targeting CRISPR effectors depend on accurate prediction of on-target activity and off-target avoidance. Here we design and test ~200,000 RfxCas13d guide RNAs targeting essential genes in human cells with systematically designed mismatches and insertions and deletions (indels). We find that mismatches and indels have a position- and context-dependent impact on Cas13d activity, and mismatches that result in G-U wobble pairings are better tolerated than other single-base mismatches. Using this large-scale dataset, we train a convolutional neural network that we term targeted inhibition of gene expression via gRNA design (TIGER) to predict efficacy from guide sequence and context. TIGER outperforms the existing models at predicting on-target and off-target activity on our dataset and published datasets. We show that TIGER scoring combined with specific mismatches yields the first general framework to modulate transcript expression, enabling the use of RNA-targeting CRISPRs to precisely control gene dosage.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.