Pacesa, M., Pelea, O. & Jinek, M. Past, present, and future of crispr genome editing technologies. Cell 187, 1076–1100 (2024).
Nijkamp, E., Ruffolo, J. A., Weinstein, E. N., Naik, N. & Madani, A. Progen2: exploring the boundaries of protein language models. Cell Syst. 14, 968–978 (2023).
Wu, Z. et al. Programmed genome editing by a miniature CRISPR–Cas12f nuclease. Nat. Chem. Biol. 17, 1132–1138 (2021).
Chen, K. et al. Lung and liver editing by lipid nanoparticle delivery of a stable CRISPR–Cas9 ribonucleoprotein. Nat. Biotechnol. https://doi.org/10.1038/s41587-024-02437-3 (2024).
Eggers, A. R. et al. Rapid DNA unwinding accelerates genome editing by engineered CRISPR–Cas9. Cell 187, 3249–3261 (2024).
Nguyen, L. T. et al. Engineering highly thermostable Cas12b via de novo structural analyses for one-pot detection of nucleic acids. Cell Rep. Med.4, 101037 (2023).
Gasiunas, G. et al. A catalogue of biochemically diverse CRISPR–Cas9 orthologs. Nat. Commun. 11, 5512 (2020).
Casini, A. et al. A highly specific spCas9 variant is identified by in vivo screening in yeast. Nat. Biotechnol. 36, 265–271 (2018).
Hu, J. H. et al. Evolved Cas9 variants with broad pam compatibility and high DNA specificity. Nature 556, 57–63 (2018).
Lee, J. K. et al. Directed evolution of CRISPR–Cas9 to increase its specificity. Nat. Commun. 9, 3048 (2018).
Vakulskas, C. A. et al. A high-fidelity Cas9 mutant delivered as a ribonucleoprotein complex enables efficient gene editing in human hematopoietic stem and progenitor cells. Nat. Med. 24, 1216–1224 (2018).
Chen, J. S. et al. Enhanced proofreading governs CRISPR–Cas9 targeting accuracy. Nature 550, 407–410 (2017).
Kleinstiver, B. P. et al. High-fidelity CRISPR–Cas9 nucleases with no detectable genome-wide off-target effects. Nature 529, 490–495 (2016).
Slaymaker, I. M. et al. Rationally engineered Cas9 nucleases with improved specificity. Science 351, 84–88 (2016).
Walton, R. T., Christie, K. A., Whittaker, M. N. & Kleinstiver, B. P. Unconstrained genome targeting with near-PAMless engineered CRISPR–Cas9 variants. Science 368, 290–296 (2020).
Dauparas, J. et al. Robust deep learning–based protein sequence design using ProteinMPNN. Science 378, 49–56 (2022).
Dauparas, J. et al. Atomic context-conditioned protein sequence design using ligandmpnn. Nat. Methods 22, 717–723 (2025).
Ruffolo, J. A. & Madani, A. Designing proteins with language models. Nat. Biotechnol. 42, 200–202 (2024).
Lin, Z. et al. Evolutionary-scale prediction of atomic-level protein structure with a language model. Science 379, 1123–1130 (2023).
Madani, A. et al. Large language models generate functional protein sequences across diverse families. Nat. Biotechnol. 41, 1099–1106 (2023).
Subramanian, A. M. & Thomson, M. Unexplored regions of the protein sequence-structure map revealed at scale by a library of foldtuned language models. Preprint at bioRxiv https://doi.org/10.1101/2023.12.22.573145 (2023).
Hopf, T. A. et al. The EVcouplings Python framework for coevolutionary sequence analysis. Bioinformatics 35, 1582–1584 (2019).
Russ, W. P. et al. An evolution-based model for designing chorismate mutase enzymes. Science 369, 440–445 (2020).
Trinquier, J., Uguzzoni, G., Pagnani, A., Zamponi, F. & Weigt, M. Efficient generative modeling of protein sequences using simple autoregressive models. Nat. Commun. 12, 5800 (2021).
Ferruz, N., Schmidt, S. & Höcker, B. ProtGPT2 is a deep unsupervised language model for protein design. Nat. Commun. 13, 1–10 (2022).
Johnson, S. R. et al. Computational scoring and experimental evaluation of enzymes generated by neural networks. Nat. Biotechnol. 43, 396–405 (2024).
Zetsche, B. et al. Cpf1 is a single RNA-guided endonuclease of a class 2 CRISPR–Cas9 system. Cell 163, 759–771 (2015).
Cox, D. B. T. et al. RNA editing with CRISPR–Cas13. Science 358, 1019–1027 (2017).
Anzalone, A. V., Koblan, L. W. & Liu, D. R. Genome editing with CRISPR–Cas nucleases, base editors, transposases and prime editors. Nat. Biotechnol. 38, 824–844 (2020).
Jumper, J. et al. Highly accurate protein structure prediction with alphafold. Nature 596, 583–589 (2021).
Chandonia, J.-M., Fox, N. K. & Brenner, S. E. Scope: classification of large macromolecular structures in the structural classification of proteins—extended database. Nucleic Acids Res. 47, D475–D481 (2019).
Van der Maaten, L. & Hinton, G. Visualizing data using t-SNE. J. Mach. Learn. Res. 9, 2579–2605 (2008).
Conant, D. et al. Inference of CRISPR edits from sanger trace data. CRISPR J. 5, 123–130 (2022).
Tsai, S. Q. et al. Guide-seq enables genome-wide profiling of off-target cleavage by CRISPR–Cas nucleases. Nat. Biotechnol. 33, 187–197 (2015).
Cameron, P. et al. Mapping the genomic landscape of CRISPR–Cas9 cleavage. Nat. Methods 14, 600–606 (2017).
Eddy, S. R. Accelerated profile HMM searches. PLoS Comput. Biol. 7, e1002195 (2011).
Schmid-Burgk, J. L. et al. Highly parallel profiling of Cas9 variant specificity. Mol. Cell 78, 794–800 (2020).
Alonso-Lerma, B. et al. Evolution of CRISPR-associated endonucleases as inferred from resurrected proteins. Nat. Microbiol. 8, 77–90 (2023).
Ferdosi, S. R. et al. Multifunctional CRISPR–Cas9 with engineered immunosilenced human T cell epitopes. Nat. Commun. 10, 1842 (2019).
Pacesa, M. et al. R-loop formation and conformational activation mechanisms of Cas9. Nature 609, 191–196 (2022).
Zhao, L. et al. Pam-flexible genome editing with an engineered chimeric Cas9. Nat. Commun. 14, 6175 (2023).
van Overbeek, M. et al. DNA repair profiling reveals nonrandom outcomes at Cas9-mediated breaks. Mol. Cell 63, 633–646 (2016).
Gaudelli, N. M. et al. Directed evolution of adenine base editors with increased activity and therapeutic application. Nat. Biotechnol. 38, 892–900 (2020).
Boutet, E. et al. in Plant Bioinformatics: Methods and Protocols (ed. Edwards, D.) Ch. 2 (Springer Nature, 2016).
Gaudelli, N. M. et al. Programmable base editing of A•T to G•C in genomic DNA without DNA cleavage. Nature 551, 464–471 (2017).
Nguyen, E. et al. Sequence modeling and design from molecular to genome scale with Evo. Science 386, eado9336 (2024).
Donohoue, P. D. et al. Conformational control of Cas9 by crispr hybrid RNA-DNA guides mitigates off-target activity in T cells. Mol. Cell 81, 3637–3649 (2021).
Huang, P.-S., Boyken, S. E. & Baker, D. The coming of age of de novo protein design. Nature 537, 320–327 (2016).
Chu, A. E., Lu, T. & Huang, P.-S. Sparks of function by de novo protein design. Nat. Biotechnol. 42, 203–215 (2024).
Watson, J. L. et al. De novo design of protein structure and function with RFdiffusion. Nature 620, 1089–1100 (2023).
Ruffolo, J. Fine-tuned language models for CRISPR–Cas and Cas9 protein generation. Zenodo https://doi.org/10.5281/zenodo.15128064 (2025).
Ruffolo, J. Modeling code for design and prediction of Cas9-like proteins. Zenodo https://doi.org/10.5281/zenodo.15231637 (2025).
Ciciani, M. et al. Automated identification of sequence-tailored Cas9 proteins using massive metagenomic data. Nat. Commun. 13, 6474 (2022).
Tang, Z. et al. CasPDB: an integrated and annotated database for Cas proteins from bacteria and archaea. Database 2019, baz093 (2019).
Coudert, E. et al. Annotation of biologically relevant ligands in UniProtKB using ChEBI. Bioinformatics 39, btac793 (2023).
Pourcel, C. et al. CRISPRCasdb a successor of CRISPRdb containing CRISPR arrays and cas genes from complete genome sequences, and tools to download and query lists of repeats and spacers. Nucleic Acids Res. 48, D535–D544 (2020).
Makarova, K. S. et al. Evolutionary classification of CRISPR-Cas systems: a burst of class 2 and derived variants. Nat. Rev. Microbiol. 18, 67–83 (2020).
Price, M. N., Dehal, P. S. & Arkin, A. P. Fasttree 2—approximately maximum-likelihood trees for large alignments. PLoS ONE 5, e9490 (2010).
Letunic, I. & Bork, P. Interactive Tree Of Life (iTOL) v5: an online tool for phylogenetic tree display and annotation. Nucleic Acids Res. 49, W293–W296 (2021).
Steinegger, M. & Söding, J. MMseqs2 enables sensitive protein sequence searching for the analysis of massive data sets. Nat. Biotechnol. 35, 1026–1028 (2017).
Mirdita, M. et al. ColabFold: making protein folding accessible to all. Nat. Methods 19, 679–682 (2022).
Van Kempen, M. et al. Fast and accurate protein structure search with foldseek. Nat. Biotechnol. 42, 243–246 (2024).
Fonfara, I. et al. Phylogeny of Cas9 determines functional exchangeability of Dual-RNA and Cas9 among orthologous type II CRISPR-Cas9 systems. Nucleic Acids Res. 42, 2577–2590 (2014).
