Prediction of prime editing insertion efficiencies using sequence features and DNA repair determinants

Machine learning prediction of prime editing efficiency across diverse chromatin contexts

The success of prime editing depends on the prime editing guide RNA (pegRNA) design and target locus. Here, we developed machine learning models that reliably predict prime editing efficiency. PRIDICT2.0 assesses the performance of pegRNAs for all edit types up to 15 bp in length in mismatch repair-deficient and mismatch repair-proficient cell lines and in vivo in primary cells. With ePRIDICT, we further developed a model that quantifies how local chromatin environments impact prime editing rates.

Development and testing of a versatile genome editing application reporter (V-GEAR) system

CRISPR-Cas9 and novel cas fusion proteins leveraging specific DNA targeting ability combined with deaminases or reverse transcriptases have revolutionized genome editing. However, their efficacy heavily relies upon protein variants, targeting single guide RNAs, and surrounding DNA sequence context within the targeted loci. This necessitates the need for efficient and rapid screening methods to evaluate these editing reagents and designs. Existing plasmid-based reporters lack flexibility, being fixed to specific DNA sequences, hindering direct comparisons between various editing approaches. To address this, we developed the versatile genome editing application reporter (V-GEAR) system. V-GEAR comprises genes detectable after desired editing via base editing, prime editing, or homology-directed repair within relevant genomic contexts. It employs a detectable synthetic cell surface protein (RQR8) followed by a customizable target sequence resembling genomic regions of interest. These genes allow for reliable identification of corrective editing and cell enrichment. We validated the V-GEAR system with base editors, prime editors, and Cas9-mediated homology-directed repair. Furthermore, the V-GEAR system offers versatility by allowing transient screening or stable integration at the AAVS1 safe harbor loci, rapidly achieved through immunomagnetic isolation. This innovative system enables direct comparisons among editing technologies, accelerating the development and testing of genome editing approaches.

Chromatin context-dependent regulation and epigenetic manipulation of prime editing

We set out to exhaustively characterize the impact of the cis-chromatin environment on prime editing, a precise genome engineering tool. Using a highly sensitive method for mapping the genomic locations of randomly integrated reporters, we discover massive position effects, exemplified by editing efficiencies ranging from ∼0% to 94% for an identical target site and edit. Position effects on prime editing efficiency are well predicted by chromatin marks, e.g., positively by H3K79me2 and negatively by H3K9me3. Next, we developed a multiplex perturbational framework to assess the interaction of trans-acting factors with the cis-chromatin environment on editing outcomes. Applying this framework to DNA repair factors, we identify HLTF as a context-dependent repressor of prime editing. Finally, several lines of evidence suggest that active transcriptional elongation enhances prime editing. Consistent with this, we show we can robustly decrease or increase the efficiency of prime editing by preceding it with CRISPR-mediated silencing or activation, respectively.

Genetic Tools for Cell Lineage Tracing and Profiling Developmental Trajectories in the Skin

The epidermis is the body's first line of protection against dehydration and pathogens, continually regenerating the outermost protective skin layers throughout life. During both embryonic development and wound healing, epidermal stem and progenitor cells must respond to external stimuli and insults to build, maintain, and repair the cutaneous barrier. Recent advances in CRISPR-based methods for cell lineage tracing have remarkably expanded the potential for experiments that track stem and progenitor cell proliferation and differentiation over the course of tissue and even organismal development. Additional tools for DNA-based recording of cellular signaling cues promise to deepen our understanding of the mechanisms driving normal skin morphogenesis and response to stressors as well as the dysregulation of cell proliferation and differentiation in skin diseases and cancer. In this review, we highlight cutting-edge methods for cell lineage tracing, including in organoids and model organisms, and explore how cutaneous biology researchers might leverage these techniques to elucidate the developmental programs that support the regenerative capacity and plasticity of the skin.

Recent advances in prime editing technologies and their promises for therapeutic applications

Prime editing (PE) is a groundbreaking genome editing technology offering unparalleled precision in targeted genome modifications and has great potential for therapeutic applications. This review delves into the core principles of PE and emphasizes its advancements, applications, and prospects. We begin with a brief introduction to PE principles, followed by a detailed examination of recent improvements in efficiency, precision, and the scale of feasible edits. These improvements have been made to the PE systems through guide RNA engineering, protein engineering, DNA repair pathway screening, chromosomal or epigenomic modification, and in silico design and optimization tools. Furthermore, we highlight in vivo studies showcasing the therapeutic potential of PE to model and treat genetic diseases. Moreover, we discuss PE's versatile applications in saturation genome editing and its applicability to nonhuman organisms. In conclusion, we address the challenges and opportunities linked with PE, emphasizing its profound impact on biological research and therapeutics.

Improving prime editing with an endogenous small RNA-binding protein

Prime editing enables the precise modification of genomes through reverse transcription of template sequences appended to the 3' ends of CRISPR-Cas guide RNAs1. To identify cellular determinants of prime editing, we developed scalable prime editing reporters and performed genome-scale CRISPR-interference screens. From these screens, a single factor emerged as the strongest mediator of prime editing: the small RNA-binding exonuclease protection factor La. Further investigation revealed that La promotes prime editing across approaches (PE2, PE3, PE4 and PE5), edit types (substitutions, insertions and deletions), endogenous loci and cell types but has no consistent effect on genome-editing approaches that rely on standard, unextended guide RNAs. Previous work has shown that La binds polyuridine tracts at the 3' ends of RNA polymerase III transcripts2. We found that La functionally interacts with the 3' ends of polyuridylated prime editing guide RNAs (pegRNAs). Guided by these results, we developed a prime editor protein (PE7) fused to the RNA-binding, N-terminal domain of La. This editor improved prime editing with expressed pegRNAs and engineered pegRNAs (epegRNAs), as well as with synthetic pegRNAs optimized for La binding. Together, our results provide key insights into how prime editing components interact with the cellular environment and suggest general strategies for stabilizing exogenous small RNAs therein.

High-throughput evaluation of genetic variants with prime editing sensor libraries

Tumor genomes often harbor a complex spectrum of single nucleotide alterations and chromosomal rearrangements that can perturb protein function. Prime editing has been applied to install and evaluate genetic variants, but previous approaches have been limited by the variable efficiency of prime editing guide RNAs. Here we present a high-throughput prime editing sensor strategy that couples prime editing guide RNAs with synthetic versions of their cognate target sites to quantitatively assess the functional impact of endogenous genetic variants. We screen over 1,000 endogenous cancer-associated variants of TP53-the most frequently mutated gene in cancer-to identify alleles that impact p53 function in mechanistically diverse ways. We find that certain endogenous TP53 variants, particularly those in the p53 oligomerization domain, display opposite phenotypes in exogenous overexpression systems. Our results emphasize the physiological importance of gene dosage in shaping native protein stoichiometry and protein-protein interactions, and establish a framework for studying genetic variants in their endogenous sequence context at scale.

Exonuclease-enhanced prime editors

Prime editing (PE) is a powerful gene-editing technique based on targeted gRNA-templated reverse transcription and integration of the de novo synthesized single-stranded DNA. To circumvent one of the main bottlenecks of the method, the competition of the reverse-transcribed 3' flap with the original 5' flap DNA, we generated an enhanced fluorescence-activated cell sorting reporter cell line to develop an exonuclease-enhanced PE strategy ('Exo-PE') composed of an improved PE complex and an aptamer-recruited DNA-exonuclease to remove the 5' original DNA flap. Exo-PE achieved better overall editing efficacy than the reference PE2 strategy for insertions ≥30 base pairs in several endogenous loci and cell lines while maintaining the high editing precision of PE2. By enabling the precise incorporation of larger insertions, Exo-PE complements the growing palette of different PE tools and spurs additional refinements of the PE machinery.

Efficient prime editing in two-cell mouse embryos using PEmbryo

Using transient inhibition of DNA mismatch repair during a permissive stage of development, we demonstrate highly efficient prime editing of mouse embryos with few unwanted, local byproducts (average 58% precise edit frequency, 0.5% on-target error frequency across 13 substitution edits at 8 sites), enabling same-generation phenotyping of founders. Whole-genome sequencing reveals that mismatch repair inhibition increases off-target indels at low-complexity regions in the genome without any obvious phenotype in mice.

Advancing genome editing with artificial intelligence: opportunities, challenges, and future directions

Clustered regularly interspaced short palindromic repeat (CRISPR)-based genome editing (GED) technologies have unlocked exciting possibilities for understanding genes and improving medical treatments. On the other hand, Artificial intelligence (AI) helps genome editing achieve more precision, efficiency, and affordability in tackling various diseases, like Sickle cell anemia or Thalassemia. AI models have been in use for designing guide RNAs (gRNAs) for CRISPR-Cas systems. Tools like DeepCRISPR, CRISTA, and DeepHF have the capability to predict optimal guide RNAs (gRNAs) for a specified target sequence. These predictions take into account multiple factors, including genomic context, Cas protein type, desired mutation type, on-target/off-target scores, potential off-target sites, and the potential impacts of genome editing on gene function and cell phenotype. These models aid in optimizing different genome editing technologies, such as base, prime, and epigenome editing, which are advanced techniques to introduce precise and programmable changes to DNA sequences without relying on the homology-directed repair pathway or donor DNA templates. Furthermore, AI, in collaboration with genome editing and precision medicine, enables personalized treatments based on genetic profiles. AI analyzes patients' genomic data to identify mutations, variations, and biomarkers associated with different diseases like Cancer, Diabetes, Alzheimer's, etc. However, several challenges persist, including high costs, off-target editing, suitable delivery methods for CRISPR cargoes, improving editing efficiency, and ensuring safety in clinical applications. This review explores AI's contribution to improving CRISPR-based genome editing technologies and addresses existing challenges. It also discusses potential areas for future research in AI-driven CRISPR-based genome editing technologies. The integration of AI and genome editing opens up new possibilities for genetics, biomedicine, and healthcare, with significant implications for human health.

Successful Correction by Prime Editing of a Mutation in the RYR1 Gene Responsible for a Myopathy

We report the first correction from prime editing a mutation in the RYR1 gene, paving the way to gene therapies for RYR1-related myopathies. The RYR1 gene codes for a calcium channel named Ryanodine receptor 1, which is expressed in skeletal muscle fibers. The failure of this channel causes muscle weakness in patients, which leads to motor disabilities. Currently, there are no effective treatments for these diseases, which are mainly caused by point mutations. Prime editing allows for the modification of precise nucleotides in the DNA. Our results showed a 59% correction rate of the T4709M mutation in the RYR1 gene in human myoblasts by RNA delivery of the prime editing components. It is to be noted that T4709M is recessive and, thus, persons having a heterozygous mutation are healthy. These results are the first demonstration that correcting mutations in the RYR1 gene is possible.

Rewriting regulatory DNA to dissect and reprogram gene expression

Regulatory DNA sequences within enhancers and promoters bind transcription factors to encode cell type-specific patterns of gene expression. However, the regulatory effects and programmability of such DNA sequences remain difficult to map or predict because we have lacked scalable methods to precisely edit regulatory DNA and quantify the effects in an endogenous genomic context. Here we present an approach to measure the quantitative effects of hundreds of designed DNA sequence variants on gene expression, by combining pooled CRISPR prime editing with RNA fluorescence in situ hybridization and cell sorting (Variant-FlowFISH). We apply this method to mutagenize and rewrite regulatory DNA sequences in an enhancer and the promoter of PPIF in two immune cell lines. Of 672 variant-cell type pairs, we identify 497 that affect PPIF expression. These variants appear to act through a variety of mechanisms including disruption or optimization of existing transcription factor binding sites, as well as creation of de novo sites. Disrupting a single endogenous transcription factor binding site often led to large changes in expression (up to -40% in the enhancer, and -50% in the promoter). The same variant often had different effects across cell types and states, demonstrating a highly tunable regulatory landscape. We use these data to benchmark performance of sequence-based predictive models of gene regulation, and find that certain types of variants are not accurately predicted by existing models. Finally, we computationally design 185 small sequence variants (≤10 bp) and optimize them for specific effects on expression in silico. 84% of these rationally designed edits showed the intended direction of effect, and some had dramatic effects on expression (-100% to +202%). Variant-FlowFISH thus provides a powerful tool to map the effects of variants and transcription factor binding sites on gene expression, test and improve computational models of gene regulation, and reprogram regulatory DNA.

The Development, Optimization and Future of Prime Editing

Prime editing is a rapidly developing method of CRISPR/Cas-based genome editing. The increasing number of novel PE applications and improved versions demands constant analysis and evaluation. The present review covers the mechanism of prime editing, the optimization of the method and the possible next step in the evolution of CRISPR/Cas9-associated genome editing. The basic components of a prime editing system are a prime editor fusion protein, consisting of nickase and reverse transcriptase, and prime editing guide RNA, consisting of a protospacer, scaffold, primer binding site and reverse transcription template. Some prime editing systems include other parts, such as additional RNA molecules. All of these components were optimized to achieve better efficiency for different target organisms and/or compactization for viral delivery. Insights into prime editing mechanisms allowed us to increase the efficiency by recruiting mismatch repair inhibitors. However, the next step in prime editing evolution requires the incorporation of new mechanisms. Prime editors combined with integrases allow us to combine the precision of prime editing with the target insertion of large, several-kilobase-long DNA fragments.

Harnessing the power of artificial intelligence to advance cell therapy

Cell therapies are powerful technologies in which human cells are reprogrammed for therapeutic applications such as killing cancer cells or replacing defective cells. The technologies underlying cell therapies are increasing in effectiveness and complexity, making rational engineering of cell therapies more difficult. Creating the next generation of cell therapies will require improved experimental approaches and predictive models. Artificial intelligence (AI) and machine learning (ML) methods have revolutionized several fields in biology including genome annotation, protein structure prediction, and enzyme design. In this review, we discuss the potential of combining experimental library screens and AI to build predictive models for the development of modular cell therapy technologies. Advances in DNA synthesis and high-throughput screening techniques enable the construction and screening of libraries of modular cell therapy constructs. AI and ML models trained on this screening data can accelerate the development of cell therapies by generating predictive models, design rules, and improved designs.

Phage-assisted evolution and protein engineering yield compact, efficient prime editors

Prime editing enables a wide variety of precise genome edits in living cells. Here we use protein evolution and engineering to generate prime editors with reduced size and improved efficiency. Using phage-assisted evolution, we improved editing efficiencies of compact reverse transcriptases by up to 22-fold and generated prime editors that are 516-810 base pairs smaller than the current-generation editor PEmax. We discovered that different reverse transcriptases specialize in different types of edits and used this insight to generate reverse transcriptases that outperform PEmax and PEmaxΔRNaseH, the truncated editor used in dual-AAV delivery systems. Finally, we generated Cas9 domains that improve prime editing. These resulting editors (PE6a-g) enhance therapeutically relevant editing in patient-derived fibroblasts and primary human T-cells. PE6 variants also enable longer insertions to be installed in vivo following dual-AAV delivery, achieving 40% loxP insertion in the cortex of the murine brain, a 24-fold improvement compared to previous state-of-the-art prime editors.

Predicting Mutations Generated by Cas9, Base Editing, and Prime Editing in Mammalian Cells

The first fruits of the CRISPR-Cas revolution are starting to enter the clinic, with gene editing therapies offering solutions to previously incurable genetic diseases. The success of such applications hinges on control over the mutations that are generated, which are known to vary depending on the targeted locus. In this review, we present the current state of understanding and predicting CRISPR-Cas cutting, base editing, and prime editing outcomes in mammalian cells. We first provide an introduction to the basics of DNA repair and machine learning that the models rely on. We then overview the datasets and methods created for characterizing edits at scale, as well as the insights that have been derived from them. The predictions generated from these models serve as a foundation for designing efficient experiments across the broad contexts where these tools are applied.

Position-dependent sequence motif preferences of SpCas9 are largely determined by scaffold-complementary spacer motifs

Streptococcus pyogenes Cas9 (SpCas9) nuclease exhibits considerable position-dependent sequence preferences. The reason behind these preferences is not well understood and is difficult to rationalise, since the protein establishes interactions with the target-spacer duplex in a sequence-independent manner. We revealed here that intramolecular interactions within the single guide RNA (sgRNA), between the spacer and the scaffold, cause most of these preferences. By using in cellulo and in vitro SpCas9 activity assays with systematically designed spacer and scaffold sequences and by analysing activity data from a large SpCas9 sequence library, we show that some long (>8 nucleotides) spacer motifs, that are complementary to the RAR unit of the scaffold, interfere with sgRNA loading, and that some motifs of more than 4 nucleotides, that are complementary to the SL1 unit, inhibit DNA binding and cleavage. Furthermore, we show that intramolecular interactions are present in the majority of the inactive sgRNA sequences of the library, suggesting that they are the most important intrinsic determinants of the activity of the SpCas9 ribonucleoprotein complex. We also found that in pegRNAs, sequences at the 3' extension of the sgRNA that are complementary to the SL2 unit are also inhibitory to prime editing, but not to the nuclease activity of SpCas9.

Chromatin context-dependent regulation and epigenetic manipulation of prime editing

Prime editing is a powerful means of introducing precise changes to specific locations in mammalian genomes. However, the widely varying efficiency of prime editing across target sites of interest has limited its adoption in the context of both basic research and clinical settings. Here, we set out to exhaustively characterize the impact of the cis- chromatin environment on prime editing efficiency. Using a newly developed and highly sensitive method for mapping the genomic locations of a randomly integrated "sensor", we identify specific epigenetic features that strongly correlate with the highly variable efficiency of prime editing across different genomic locations. Next, to assess the interaction of trans -acting factors with the cis -chromatin environment, we develop and apply a pooled genetic screening approach with which the impact of knocking down various DNA repair factors on prime editing efficiency can be stratified by cis -chromatin context. Finally, we demonstrate that we can dramatically modulate the efficiency of prime editing through epigenome editing, i.e. altering chromatin state in a locus-specific manner in order to increase or decrease the efficiency of prime editing at a target site. Looking forward, we envision that the insights and tools described here will broaden the range of both basic research and therapeutic contexts in which prime editing is useful.