CRISPRitz: rapid, high-throughput and variant-aware in silico off-target site identification for CRISPR genome editing

Variant-aware Cas-OFFinder: web-based in silico variant-aware potential off-target site identification for genome editing applications

Genome editing based on CRISPR systems has been widely used in the vast areas of biomedical and agricultural applications. However, identifying the potential off-target sites remains challenging, particularly in individuals with diverse genetic variations. Several in silico tools have been developed to predict potential off-target sites, but they have limitations on their performance and scalability. In this paper, we present "Variant-aware Cas-OFFinder," a novel pipeline based on Cas-OFFinder for identifying potential off-target sites by accounting for individual genetic variants. We benchmarked the pipeline's improved scalability and performance with the human genome and pepper cultivars, having unique potential off-target sites on each allele at the haplotype level. The web tool is open to all users without a login requirement and is freely available online at https://rgetoolkit.com/var-cas-offinder.

Current trends in gene therapy to treat inherited disorders of the brain

Gene therapy development, re-engineering, and application to patients hold promise to revolutionize medicine, including therapies for disorders of the brain. Advances in delivery modalities, expression regulation, and improving safety profiles are of critical importance. Additionally, each inherited disorder has its own unique characteristics as to regions and cell types impacted and the temporal dynamics of that impact that are essential for the design of therapeutic design strategies. Here, we review the current state of the art in gene therapies for inherited brain disorders, summarizing key considerations for vector delivery, gene addition, gene silencing, gene editing, and epigenetic editing. We provide examples from animal models, human cell lines, and, where possible, clinical trials. This review also highlights the various tools available to researchers for basic research questions and discusses our views on the current limitations in the field.

Genome-wide CRISPR guide RNA design and specificity analysis with GuideScan2

We present GuideScan2 for memory-efficient, parallelizable construction of high-specificity CRISPR guide RNA (gRNA) databases and user-friendly design and analysis of individual gRNAs and gRNA libraries for targeting coding and non-coding regions in custom genomes. GuideScan2 analysis identifies widespread confounding effects of low-specificity gRNAs in published CRISPR screens and enables construction of a gRNA library that reduces off-target effects in a gene essentiality screen. GuideScan2 also enables the design and experimental validation of allele-specific gRNAs in a hybrid mouse genome. GuideScan2 will facilitate CRISPR experiments across a wide range of applications.

CRIBAR: a fast and flexible sgRNA design tool for CRISPR imaging

Motivation

CRISPR imaging enables the real-time tracking of nucleic acids. Using guide RNAs (gRNAs) to direct fluorescent tags to target regions allows for precise nucleic acid monitoring via microscopy. The design of gRNAs largely affects the efficacy of CRISPR imaging. Currently, available gRNA design tools are developed primarily for gene editing, often producing individual gRNAs that target genes or regulatory elements.

Results

In this study, we introduce CRIBAR, a computational tool developed to systematically design single-guide RNAs (sgRNAs) for CRISPR imaging applications. CRIBAR first generates sgRNA sets optimized to maximize the number of on-target binding sites and then evaluates the potential off-target effect. The results of the in silico experiment show that CRIBAR enables CRISPR imaging in non-repetitive regions.

Availability and implementation

CRIBAR is available as a software package at https://github.com/ucfcbb/CRIBAR and as a web server at http://genome.ucf.edu/CRIBAR.

Combining Off-flow, a Nextflow-coded program, and whole genome sequencing reveals unintended genetic variation in CRISPR/Cas-edited iPSCs

Clustered Regularly Interspaced Short Palindromic Repeats (CRISPR)-Cas nucleases and human induced pluripotent stem cell (iPSC) technology can reveal deep insight into the genetic and molecular bases of human biology and disease. Undesired editing outcomes, both on-target (at the edited locus) and off-target (at other genomic loci) hinder the application of CRISPR-Cas nucleases. We developed Off-flow, a Nextflow-coded bioinformatic workflow that takes a specific guide sequence and Cas protein input to call four separate off-target prediction programs (CHOPCHOP, Cas-Offinder, CRISPRitz, CRISPR-Offinder) to output a comprehensive list of predicted off-target sites. We applied it to whole genome sequencing (WGS) data to investigate the occurrence of unintended effects in human iPSCs that underwent repair or insertion of disease-related variants by homology-directed repair. Off-flow identified a 3-base-pair-substitution and a mono-allelic genomic deletion at the target loci, KCNQ2, in 2 clones. Unbiased WGS analysis further identified off-target missense variants and a mono-allelic genomic deletion at the targeted locus, GNAQ, in 10 clones. On-target substitution and deletions had escaped standard PCR and Sanger sequencing analysis, while missense variants at other genomic loci were not detected by Off-flow. We used these results to filter out iPSC clones for subsequent functional experiments. Off-flow, which we make publicly available, works for human and mouse genomes currently and can be adapted for other genomes. Off-flow and WGS analysis can improve the integrity of studies using CRISPR/Cas-edited cells and animal models.

CRISPR-GPT: An LLM Agent for Automated Design of Gene-Editing Experiments

The introduction of genome engineering technology has transformed biomedical research, making it possible to make precise changes to genetic information. However, creating an efficient gene-editing system requires a deep understanding of CRISPR technology, and the complex experimental systems under investigation. While Large Language Models (LLMs) have shown promise in various tasks, they often lack specific knowledge and struggle to accurately solve biological design problems. In this work, we introduce CRISPR-GPT, an LLM agent augmented with domain knowledge and external tools to automate and enhance the design process of CRISPR-based gene-editing experiments. CRISPR-GPT leverages the reasoning ability of LLMs to facilitate the process of selecting CRISPR systems, designing guide RNAs, recommending cellular delivery methods, drafting protocols, and designing validation experiments to confirm editing outcomes. We showcase the potential of CRISPR-GPT for assisting non-expert researchers with gene-editing experiments from scratch and validate the agent's effectiveness in a real-world use case. Furthermore, we explore the ethical and regulatory considerations associated with automated gene-editing design, highlighting the need for responsible and transparent use of these tools. Our work aims to bridge the gap between biological researchers across various fields with CRISPR genome engineering technology and demonstrate the potential of LLM agents in facilitating complex biological discovery tasks.

CRISPR-Cas9n-mediated ELANE promoter editing for gene therapy of severe congenital neutropenia

Severe congenital neutropenia (CN) is an inherited pre-leukemia bone marrow failure syndrome commonly caused by autosomal-dominant ELANE mutations (ELANE-CN). ELANE-CN patients are treated with daily injections of recombinant human granulocyte colony-stimulating factor (rhG-CSF). However, some patients do not respond to rhG-CSF, and approximately 15% of ELANE-CN patients develop myelodysplasia or acute myeloid leukemia. Here, we report the development of a curative therapy for ELANE-CN through inhibition of ELANE mRNA expression by introducing two single-strand DNA breaks at the opposing DNA strands of the ELANE promoter TATA box using CRISPR-Cas9D10A nickases-termed MILESTONE. This editing effectively restored defective neutrophil differentiation of ELANE-CN CD34+ hematopoietic stem and progenitor cells (HSPCs) in vitro and in vivo, without affecting the functions of the edited neutrophils. CRISPResso analysis of the edited ELANE-CN CD34+ HSPCs revealed on-target efficiencies of over 90%. Simultaneously, GUIDE-seq, CAST-Seq, and rhAmpSeq indicated a safe off-target profile with no off-target sites or chromosomal translocations. Taken together, ex vivo gene editing of ELANE-CN HSPCs using MILESTONE in the setting of autologous stem cell transplantation could be a universal, safe, and efficient gene therapy approach for ELANE-CN patients.

Ensemble Detection of DNA Engineering Signatures

Synthetic biology is creating genetically engineered organisms at an increasing rate for many potentially valuable applications, but this potential comes with the risk of misuse or accidental release. To begin to address this issue, we have developed a system called GUARDIAN that can automatically detect signatures of engineering in DNA sequencing data, and we have conducted a blinded test of this system using a curated Test and Evaluation (T&E) data set. GUARDIAN uses an ensemble approach based on the guiding principle that no single approach is likely to be able to detect engineering with perfect accuracy. Critically, ensembling enables GUARDIAN to detect sequence inserts in 13 target organisms with a high degree of specificity that requires no subject matter expert (SME) review.

Massively parallel screen uncovers many rare 3' UTR variants regulating mRNA abundance of cancer driver genes

Understanding the function of rare non-coding variants represents a significant challenge. Using MapUTR, a screening method, we studied the function of rare 3' UTR variants affecting mRNA abundance post-transcriptionally. Among 17,301 rare gnomAD variants, an average of 24.5% were functional, with 70% in cancer-related genes, many in critical cancer pathways. This observation motivated an interrogation of 11,929 somatic mutations, uncovering 3928 (33%) functional mutations in 155 cancer driver genes. Functional MapUTR variants were enriched in microRNA- or protein-binding sites and may underlie outlier gene expression in tumors. Further, we introduce untranslated tumor mutational burden (uTMB), a metric reflecting the amount of somatic functional MapUTR variants of a tumor and show its potential in predicting patient survival. Through prime editing, we characterized three variants in cancer-relevant genes (MFN2, FOSL2, and IRAK1), demonstrating their cancer-driving potential. Our study elucidates the function of tens of thousands of non-coding variants, nominates non-coding cancer driver mutations, and demonstrates their potential contributions to cancer.

SWOffinder: Efficient and versatile search of CRISPR off-targets with bulges by Smith-Waterman alignment

CRISPR/Cas9 technology is revolutionizing the field of gene editing. While this technology enables the targeting of any gene, it may also target unplanned loci, termed off-target sites (OTS), which are a few mismatches, insertions, and deletions from the target. While existing methods for finding OTS up to a given mismatch threshold are efficient, other methods considering insertions and deletions are limited by long runtimes, incomplete OTS lists, and partial support of versatile thresholds. Here, we developed SWOffinder, an efficient method based on Smith-Waterman alignment to find all OTS up to some edit distance. We implemented an original trace-back approach to find OTS under versatile criteria, such as separate limits on the number of insertions, deletions, and mismatches. Compared to state-of-the-art methods, only SWOffinder finds all OTS in the genome in just a few minutes. SWOffinder enables accurate and efficient genomic search of OTS, which will lead to safer gene editing.

Prime editing: current advances and therapeutic opportunities in human diseases

Gene editing ushers in a new era of disease treatment since many genetic diseases are caused by base-pair mutations in genomic DNA. With the rapid development of genome editing technology, novel editing tools such as base editing and prime editing (PE) have attracted public attention, heralding a great leap forward in this field. PE, in particular, is characterized by no need for double-strand breaks (DSBs) or homology sequence templates with variable application scenarios, including point mutations as well as insertions or deletions. With higher editing efficiency and fewer byproducts than traditional editing tools, PE holds great promise as a therapeutic strategy for human diseases. Subsequently, a growing demand for the standard construction of PE system has spawned numerous easy-to-access internet resources and tools for personalized prime editing guide RNA (pegRNA) design and off-target site prediction. In this review, we mainly introduce the innovation and evolutionary strategy of PE systems and the auxiliary tools for PE design and analysis. Additionally, its application and future potential in the clinical field have been summarized and envisaged.

Functional interrogation of twenty type 2 diabetes-associated genes using isogenic human embryonic stem cell-derived β-like cells

Genetic studies have identified numerous loci associated with type 2 diabetes (T2D), but the functional roles of many loci remain unexplored. Here, we engineered isogenic knockout human embryonic stem cell lines for 20 genes associated with T2D risk. We examined the impacts of each knockout on β cell differentiation, functions, and survival. We generated gene expression and chromatin accessibility profiles on β cells derived from each knockout line. Analyses of T2D-association signals overlapping HNF4A-dependent ATAC peaks identified a likely causal variant at the FAIM2 T2D-association signal. Additionally, the integrative association analyses identified four genes (CP, RNASE1, PCSK1N, and GSTA2) associated with insulin production, and two genes (TAGLN3 and DHRS2) associated with β cell sensitivity to lipotoxicity. Finally, we leveraged deep ATAC-seq read coverage to assess allele-specific imbalance at variants heterozygous in the parental line and identified a single likely functional variant at each of 23 T2D-association signals.

Endogenous CRISPR-Cas mediated in situ genome editing: State-of-the-art and the road ahead for engineering prokaryotes

The CRISPR-Cas systems have shown tremendous promise as heterologous tools for genome editing in various prokaryotes. However, the perturbation of DNA homeostasis and the inherent toxicity of Cas9/12a proteins could easily lead to cell death, which led to the development of endogenous CRISPR-Cas systems. Programming the widespread endogenous CRISPR-Cas systems for in situ genome editing represents a promising tool in prokaryotes, especially in genetically intractable species. Here, this review briefly summarizes the advances of endogenous CRISPR-Cas-mediated genome editing, covering aspects of establishing and optimizing the genetic tools. In particular, this review presents the application of different types of endogenous CRISPR-Cas tools for strain engineering, including genome editing and genetic regulation. Notably, this review also provides a detailed discussion of the transposon-associated CRISPR-Cas systems, and the programmable RNA-guided transposition using endogenous CRISPR-Cas systems to enable editing of microbial communities for understanding and control. Therefore, they will be a powerful tool for targeted genetic manipulation. Overall, this review will not only facilitate the development of standard genetic manipulation tools for non-model prokaryotes but will also enable more non-model prokaryotes to be genetically tractable.

Guide-specific loss of efficiency and off-target reduction with Cas9 variants

High-fidelity clustered regularly interspaced palindromic repeats (CRISPR)-associated protein 9 (Cas9) variants have been developed to reduce the off-target effects of CRISPR systems at a cost of efficiency loss. To systematically evaluate the efficiency and off-target tolerance of Cas9 variants in complex with different single guide RNAs (sgRNAs), we applied high-throughput viability screens and a synthetic paired sgRNA-target system to assess thousands of sgRNAs in combination with two high-fidelity Cas9 variants HiFi and LZ3. Comparing these variants against wild-type SpCas9, we found that ∼20% of sgRNAs are associated with a significant loss of efficiency when complexed with either HiFi or LZ3. The loss of efficiency is dependent on the sequence context in the seed region of sgRNAs, as well as at positions 15-18 in the non-seed region that interacts with the REC3 domain of Cas9, suggesting that the variant-specific mutations in the REC3 domain account for the loss of efficiency. We also observed various degrees of sequence-dependent off-target reduction when different sgRNAs are used in combination with the variants. Given these observations, we developed GuideVar, a transfer learning-based computational framework for the prediction of on-target efficiency and off-target effects with high-fidelity variants. GuideVar facilitates the prioritization of sgRNAs in the applications with HiFi and LZ3, as demonstrated by the improvement of signal-to-noise ratios in high-throughput viability screens using these high-fidelity variants.

OffRisk: a docker image for annotating CRISPR off-target sites in the human genome

Summary

The CRISPR-Cas9 system has been adapted to achieve targeted genome editing as well as transcriptional control by customizing 20-nt guide RNA (gRNA) molecules for desired regions in the target genome. Designing gRNAs must consider nonspecific and unintended binding, known as off-targets, since these may have potentially harmful effects. To assist in gRNA design, we have developed OffRisk. This Docker-based tool annotates off-target sites in the human genome and assigns them a potential risk label by incorporating functional and regulatory information at different molecular levels.

Availability and implementation

OffRisk is available at https://github.com/IsanaVekslerLublinsky/OffRisk and https://github.com/IsanaVekslerLublinsky/OffRisk-ui (including code, user guide, docker installation guide, and running examples).All processed datasets are available at https://zenodo.org/record/8289271.

Prediction of base editor off-targets by deep learning

Due to the tolerance of mismatches between gRNA and targeting sequence, base editors frequently induce unwanted Cas9-dependent off-target mutations. Here, to develop models to predict such off-targets, we design gRNA-off- target pairs for adenine base editors (ABEs) and cytosine base editors (CBEs) and stably integrate them into the human cells. After five days of editing, we obtain valid efficiency datasets of 54,663 and 55,727 off-targets for ABEs and CBEs, respectively. We use the datasets to train deep learning models, resulting in ABEdeepoff and CBEdeepoff, which can predict off-target sites. We use these tools to predict off-targets for a panel of endogenous loci and achieve Spearman correlation values varying from 0.710 to 0.859. Finally, we develop an integrated tool that is freely accessible via an online web server http://www.deephf.com/#/bedeep/bedeepoff . These tools could facilitate minimizing the off-target effects of base editing.

Application of CRISPR-Cas system in the diagnosis and therapy of ESKAPE infections

Antimicrobial-resistant ESKAPE (Enterococcus faecium, Staphylococcus aureus, Klebsiella pneumoniae, Acinetobacter baumannii, Pseudomonas aeruginosa, and Enterobacter species) pathogens represent a global threat to human health. ESKAPE pathogens are the most common opportunistic pathogens in nosocomial infections, and a considerable number of their clinical isolates are not susceptible to conventional antimicrobial therapy. Therefore, innovative therapeutic strategies that can effectively deal with ESKAPE pathogens will bring huge social and economic benefits and ease the suffering of tens of thousands of patients. Among these strategies, CRISPR (clustered regularly interspaced short palindromic repeats) system has received extra attention due to its high specificity. Regrettably, there is currently no direct CRISPR-system-based anti-infective treatment. This paper reviews the applications of CRISPR-Cas system in the study of ESKAPE pathogens, aiming to provide directions for the research of ideal new drugs and provide a reference for solving a series of problems caused by multidrug-resistant bacteria (MDR) in the post-antibiotic era. However, most research is still far from clinical application.

Massively parallel CRISPR off-target detection enables rapid off-target prediction model building

BACKGROUND

CRISPR (clustered regularly interspaced short palindromic repeats) genome editing holds tremendous potential in clinical translation. However, the off-target effect has always been a major concern.

METHODS

Here, we have developed a novel sensitive and specific off-target detection method, AID-seq (adaptor-mediated off-target identification by sequencing), that can comprehensively and faithfully detect the low-frequency off targets generated by different CRISPR nucleases (including Cas9 and Cas12a).

FINDINGS

Based on AID-seq, we developed a pooled strategy to simultaneously identify the on/off targets of multiple gRNAs, as well as using mixed human and human papillomavirus (HPV) genomes to screen the most efficient and safe targets from 416 HPV gRNA candidates for antiviral therapy. Moreover, we used the pooled strategy with 2,069 single-guide RNAs (sgRNAs) at a pool size of about 500 to profile the properties of our newly discovered CRISPR, FrCas9. Importantly, we successfully built an off-target detection model using these off-target data via the CRISPR-Net deep learning method (area under the receiver operating characteristic curve [AUROC] = 0.97, area under the precision recall curve [AUPRC] = 0.29).

CONCLUSIONS

To our knowledge, AID-seq is the most sensitive and specific in vitro off-target detection method to date. And the pooled AID-seq strategy can be used as a rapid and high-throughput platform to select the best sgRNAs and characterize the properties of new CRISPRs.

FUNDING

This work was supported by The National Natural Science Foundation of China (grant nos. 32171465 and 82102392), the General Program of Natural Science Foundation of Guangdong Province of China (grant no. 2021A1515012438), Guangdong Basic and Applied Basic Research Foundation (grant no. 2020A1515110170), and the National Ten Thousand Plan-Young Top Talents of China (grant no. 80000-41180002).

Guide-specific loss of efficiency and off-target reduction with Cas9 variants

High-fidelity Cas9 variants have been developed to reduce the off-target effects of CRISPR systems at a cost of efficiency loss. To systematically evaluate the efficiency and off-target tolerance of Cas9 variants in complex with different single guide RNAs (sgRNAs), we applied high-throughput viability screens and a synthetic paired sgRNA-target system to assess thousands of sgRNAs in combination with two high-fidelity Cas9 variants HiFi and LZ3. Comparing these variants against WT SpCas9, we found that ~20% of sgRNAs are associated with a significant loss of efficiency when complexed with either HiFi or LZ3. The loss of efficiency is dependent on the sequence context in the seed region of sgRNAs, as well as at positions 15-18 in the non-seed region that interacts with the REC3 domain of Cas9, suggesting that the variant-specific mutations in REC3 domain account for the loss of efficiency. We also observed various degrees of sequencedependent off-target reduction when different sgRNAs are used in combination with the variants. Given these observations, we developed GuideVar, a transfer-learning-based computational framework for the prediction of on-target efficiency and off-target effect with high-fidelity variants. GuideVar facilitates the prioritization of sgRNAs in the applications with HiFi and LZ3, as demonstrated by the improvement of signal-to-noise ratios in high-throughput viability screens using these high-fidelity variants.

CRISPR genome editing using computational approaches: A survey

Clustered regularly interspaced short palindromic repeats (CRISPR)-based gene editing has been widely used in various cell types and organisms. To make genome editing with Clustered regularly interspaced short palindromic repeats far more precise and practical, we must concentrate on the design of optimal gRNA and the selection of appropriate Cas enzymes. Numerous computational tools have been created in recent years to help researchers design the best gRNA for Clustered regularly interspaced short palindromic repeats researches. There are two approaches for designing an appropriate gRNA sequence (which targets our desired sites with high precision): experimental and predicting-based approaches. It is essential to reduce off-target sites when designing an optimal gRNA. Here we review both traditional and machine learning-based approaches for designing an appropriate gRNA sequence and predicting off-target sites. In this review, we summarize the key characteristics of all available tools (as far as possible) and compare them together. Machine learning-based tools and web servers are believed to become the most effective and reliable methods for predicting on-target and off-target activities of Clustered regularly interspaced short palindromic repeats in the future. However, these predictions are not so precise now and the performance of these algorithms -especially deep learning one's-depends on the amount of data used during training phase. So, as more features are discovered and incorporated into these models, predictions become more in line with experimental observations. We must concentrate on the creation of ideal gRNA and the choice of suitable Cas enzymes in order to make genome editing with Clustered regularly interspaced short palindromic repeats far more accurate and feasible.

Human genetic diversity alters off-target outcomes of therapeutic gene editing

CRISPR gene editing holds great promise to modify DNA sequences in somatic cells to treat disease. However, standard computational and biochemical methods to predict off-target potential focus on reference genomes. We developed an efficient tool called CRISPRme that considers single-nucleotide polymorphism (SNP) and indel genetic variants to nominate and prioritize off-target sites. We tested the software with a BCL11A enhancer targeting guide RNA (gRNA) showing promise in clinical trials for sickle cell disease and β-thalassemia and found that the top candidate off-target is produced by an allele common in African-ancestry populations (MAF 4.5%) that introduces a protospacer adjacent motif (PAM) sequence. We validated that SpCas9 generates strictly allele-specific indels and pericentric inversions in CD34+ hematopoietic stem and progenitor cells (HSPCs), although high-fidelity Cas9 mitigates this off-target. This report illustrates how genetic variants should be considered as modifiers of gene editing outcomes. We expect that variant-aware off-target assessment will become integral to therapeutic genome editing evaluation and provide a powerful approach for comprehensive off-target nomination.

CRISPR-Cas system: from diagnostic tool to potential antiviral treatment

This mini review focuses on the diagnosis and treatment of virus diseases using Crisper-Cas technology. The present paper describes various strategies involved in diagnosing diseases using Crispr-Cas-based assays. Additionally, CRISPR-Cas systems offer great potential as new therapeutic tools for treating viral infections including HIV, Influenza, and SARS-CoV-2. There are several major challenges to be overcome before this technology can be applied routinely in clinical settings, such as finding a suitable delivery tool, toxicity, and immunogenicity, as well as off-target effects. This review also discusses ways to deal with the challenges associated with Crisper-Cas technology. KEY POINTS: • Crisper technology is being applied to diagnose infectious and non-infectious diseases. • A new generation of CRISPR-Cas-based assays has been developed which detect pathogens within minutes, providing rapid diagnosis of diseases. • Crispr-Cas tools can be used to combat viral infections, specifically HIV, influenza, and SARS-CoV-2.

JACKIE: Fast Enumeration of Genome-Wide Single- and Multicopy CRISPR Target Sites and Their Off-Target Numbers

Zinc finger protein-, transcription activator like effector-, and CRISPR-based methods for genome and epigenome editing and imaging have provided powerful tools to investigate functions of genomes. Targeting sequence design is vital to the success of these experiments. Although existing design software mainly focus on designing target sequence for specific elements, we report here the implementation of Jackie and Albert's Comprehensive K-mer Instances Enumerator (JACKIE), a suite of software for enumerating all single- and multicopy sites in the genome that can be incorporated for genome-scale designs as well as loaded onto genome browsers alongside other tracks for convenient web-based graphic-user-interface-enabled design. We also implement fast algorithms to identify sequence neighborhoods or off-target counts of targeting sequences so that designs with low probability of off-target can be identified among millions of design sequences in reasonable time. We demonstrate the application of JACKIE-designed CRISPR site clusters for genome imaging.

Rapid Whole-Genome Identification of High Quality CRISPR Guide RNAs with the Crackling Method

The design of CRISPR-Cas9 guide RNAs is not trivial and is a computationally demanding task. Design tools need to identify target sequences that will maximize the likelihood of obtaining the desired cut, while minimizing off-target risk. There is a need for a tool that can meet both objectives while remaining practical to use on large genomes. In this study, we present Crackling, a new method that is more suitable for meeting these objectives. We test its performance on 12 genomes and on data from validation studies. Crackling maximizes guide efficiency by combining multiple scoring approaches. On experimental data, the guides it selects are better than those selected by others. It also incorporates Inverted Signature Slice Lists (ISSL) for faster off-target scoring. ISSL provides a gain of an order of magnitude in speed compared with other popular tools, such as Cas-OFFinder, Crisflash, and FlashFry, while preserving the same level of accuracy. Overall, this makes Crackling a faster and better method to design guide RNAs at scale. Crackling is available at https://github.com/bmds-lab/Crackling under the Berkeley Software Distribution (BSD) 3-Clause license.

High-throughput methods for genome editing: the more the better

During the last decade, targeted genome-editing technologies, especially clustered regularly interspaced short palindromic repeat (CRISPR)/CRISPR-associated protein (Cas) technologies, have permitted efficient targeting of genomes, thereby modifying these genomes to offer tremendous opportunities for deciphering gene function and engineering beneficial traits in many biological systems. As a powerful genome-editing tool, the CRISPR/Cas systems, combined with the development of next-generation sequencing and many other high-throughput techniques, have thus been quickly developed into a high-throughput engineering strategy in animals and plants. Therefore, here, we review recent advances in using high-throughput genome-editing technologies in animals and plants, such as the high-throughput design of targeted guide RNA (gRNA), construction of large-scale pooled gRNA, and high-throughput genome-editing libraries, high-throughput detection of editing events, and high-throughput supervision of genome-editing products. Moreover, we outline perspectives for future applications, ranging from medication using gene therapy to crop improvement using high-throughput genome-editing technologies.

CRISPR/ Cas9 Off-targets: Computational Analysis of Causes, Prediction, Detection, and Overcoming Strategies

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CRISPR/Cas9 technology is a highly flexible RNA-guided endonuclease (RGEN) based gene-editing tool that has transformed the field of genomics, gene therapy, and genome/ epigenome imaging. Its wide range of applications provides immense scope for understanding as well as manipulating genetic/epigenetic elements. However, the RGEN is prone to off-target mutagenesis that leads to deleterious effects. This review details the molecular and cellular mechanisms underlying the off-target activity, various available detection tools and prediction methodology ranging from sequencing to machine learning approaches, and the strategies to overcome/minimise off-targets. A coherent and concise method increasing target precision would prove indispensable to concrete manipulation and interpretation of genome editing results that can revolutionise therapeutics, including clarity in genome regulatory mechanisms during development.

Systematic decomposition of sequence determinants governing CRISPR/Cas9 specificity

The specificity of CRISPR/Cas9 genome editing is largely determined by the sequences of guide RNA (gRNA) and the targeted DNA, yet the sequence-dependent rules underlying off-target effects are not fully understood. To systematically explore the sequence determinants governing CRISPR/Cas9 specificity, here we describe a dual-target system to measure the relative cleavage rate between off- and on-target sequences (off-on ratios) of 1902 gRNAs on 13,314 synthetic target sequences, and reveal a set of sequence rules involving 2 factors in off-targeting: 1) a guide-intrinsic mismatch tolerance (GMT) independent of the mismatch context; 2) an "epistasis-like" combinatorial effect of multiple mismatches, which are associated with the free-energy landscape in R-loop formation and are explainable by a multi-state kinetic model. These sequence rules lead to the development of MOFF, a model-based predictor of Cas9-mediated off-target effects. Moreover, the "epistasis-like" combinatorial effect suggests a strategy of allele-specific genome editing using mismatched guides. With the aid of MOFF prediction, this strategy significantly improves the selectivity and expands the application domain of Cas9-based allele-specific editing, as tested in a high-throughput allele-editing screen on 18 cancer hotspot mutations.

Cleavage-free human genome editing

Most gene editing technologies introduce breaks or nicks into DNA, leading to the generation of mutagenic insertions and deletions by non-homologous end-joining repair. Here, we report a new, cleavage-free gene editing approach based on replication interrupted template-driven DNA modification (RITDM). The RITDM system makes use of sequence-specific DLR fusion molecules that are specifically designed to enable localized, temporary blockage of DNA replication fork progression, thereby exposing single-stranded DNA that can be bound by DNA sequence modification templates for precise editing. We evaluate the use of zinc-finger arrays for sequence recognition. We demonstrate that RITDM can be used for gene editing at endogenous genomic loci in human cells and highlight its safety profile of low indel frequencies and undetectable off-target side effects in RITDM-edited clones and pools of cells.

Effective use of sequence information to predict CRISPR-Cas9 off-target

The CRISPR/Cas9 gene-editing system is the third-generation gene-editing technology that has been widely used in biomedical applications. However, off-target effects occurring CRISPR/Cas9 system has been a challenging problem it faces in practical applications. Although many predictive models have been developed to predict off-target activities, current models do not effectively use sequence pair information. There is still room for improved accuracy. This study aims to effectively use sequence pair information to improve the model's performance for predicting off-target activities. We propose a new coding scheme for coding sequence pairs and design a new model called CRISPR-IP for predicting off-target activity. Our coding scheme distinguishes regions with different functions in the sequence pairs through the function channel. Moreover, it distinguishes between bases and base pairs using type channels, effectively representing the sequence pair information. The CRISPR-IP model is based on CNN, BiLSTM, and the attention layer to learn features of sequence pairs. We performed performance verification on two data sets and found that our coding scheme can represent sequence pair information effectively, and the CRISPR-IP model performance is better than others. Data and source codes are available at https://github.com/BioinfoVirgo/CRISPR-IP.

Evaluation of two in vitro assays for tumorigenicity assessment of CRISPR-Cas9 genome-edited cells

Off-target editing is one of the main safety concerns for the use of CRISPR-Cas9 genome editing in gene therapy. These unwanted modifications could lead to malignant transformation, which renders tumorigenicity assessment of gene therapy products indispensable. In this study, we established two in vitro transformation assays, the soft agar colony-forming assay (SACF) and the growth in low attachment assay (GILA) as alternative methods for tumorigenicity evaluation of genome-edited cells. Using a CRISPR-Cas9-based approach to transform immortalized MCF10A cells, we identified PTPN12, a known tumor suppressor, as a valid positive control in GILA and SACF. Next, we measured the limit of detection for both assays and proved that SACF is more sensitive than GILA (0.8% versus 3.1% transformed cells). We further validated SACF and GILA by identifying a set of positive and negative controls and by testing the suitability of another cell line (THLE-2). Moreover, in contrast to SACF and GILA, an in vivo tumorigenicity study failed to detect the known tumorigenic potential of PTPN12 deletion, demonstrating the relevance of GILA and SACF in tumorigenicity testing. In conclusion, SACF and GILA are both attractive and valuable additions to preclinical safety assessment of gene therapy products.

CRISPR-derived genome editing therapies: Progress from bench to bedside

The development of CRISPR-derived genome editing technologies has enabled the precise manipulation of DNA sequences within the human genome. In this review, we discuss the initial development and cellular mechanism of action of CRISPR nucleases and DNA base editors. We then describe factors that must be taken into consideration when developing these tools into therapeutic agents, including the potential for unintended and off-target edits when using these genome editing tools, and methods to characterize these types of edits. We finish by considering specific challenges associated with bringing a CRISPR-based therapy to the clinic, including manufacturing, regulatory oversight, and considerations for clinical trials that involve genome editing agents.

CALITAS: A CRISPR-Cas-aware ALigner for In silico off-TArget Search

We describe CALITAS, a CRISPR-Cas-aware aligner and integrated off-target search algorithm. CALITAS uses a modified and CRISPR-tuned version of the Needleman-Wunsch algorithm. It supports an unlimited number of mismatches and gaps and allows protospacer adjacent motif (PAM) mismatches or PAMless searches. CALITAS also includes an exhaustive search routine to scan genomes and genome variants provided with a standard Variant Call Format file. By default, CALITAS returns a single best alignment for a given off-target site, which is a significant improvement compared to other off-target algorithms, and it enables off-targets to be referenced directly using alignment coordinates. We validate and compare CALITAS using a selected set of target sites, as well as experimentally derived specificity data sets. In summary, CALITAS is a new tool for precise and relevant alignments and identification of candidate off-target sites across a genome. We believe it is the state of the art for CRISPR-Cas specificity assessments.

CRISPR-SE: a brute force search engine for CRISPR design

CRISPR is a revolutionary genome-editing tool that has been broadly used and integrated within novel biotechnologies. A major component of existing CRISPR design tools is the search engines that find the off-targets up to a predefined number of mismatches. Many CRISPR design tools adapted sequence alignment tools as the search engines to speed up the process. These commonly used alignment tools include BLAST, BLAT, Bowtie, Bowtie2 and BWA. Alignment tools use heuristic algorithm to align large amount of sequences with high performance. However, due to the seed-and-extend algorithms implemented in the sequence alignment tools, these methods are likely to provide incomplete off-targets information for ultra-short sequences, such as 20-bp guide RNAs (gRNA). An incomplete list of off-targets sites may lead to erroneous CRISPR design. To address this problem, we derived four sets of gRNAs to evaluate the accuracy of existing search engines; further, we introduce a search engine, namely CRISPR-SE. CRISPR-SE is an accurate and fast search engine using a brute force approach. In CRISPR-SE, all gRNAs are virtually compared with query gRNA, therefore, the accuracies are guaranteed. We performed the accuracy benchmark with multiple search engines. The results show that as expected, alignment tools reported an incomplete and varied list of off-target sites. CRISPR-SE performs well in both accuracy and speed. CRISPR-SE will improve the quality of CRISPR design as an accurate high-performance search engine.

Algorithms meet sequencing technologies - 10th edition of the RECOMB-Seq workshop

DNA and RNA sequencing is a core technology in biological and medical research. The high throughput of these technologies and the consistent development of new experimental assays and biotechnologies demand the continuous development of methods to analyze the resulting data. The RECOMB Satellite Workshop on Massively Parallel Sequencing brings together leading researchers in computational genomics to discuss emerging frontiers in algorithm development for massively parallel sequencing data. The 10th meeting in this series, RECOMB-Seq 2020, was scheduled to be held in Padua, Italy, but due to the ongoing COVID-19 pandemic, the meeting was carried out virtually instead. The online workshop featured keynote talks by Paola Bonizzoni and Zamin Iqbal, two highlight talks, ten regular talks, and three short talks. Seven of the works presented in the workshop are featured in this edition of iScience, and many of the talks are available online in the RECOMB-Seq 2020 YouTube channel.

Tools for experimental and computational analyses of off-target editing by programmable nucleases

Genome editing using programmable nucleases is revolutionizing life science and medicine. Off-target editing by these nucleases remains a considerable concern, especially in therapeutic applications. Here we review tools developed for identifying potential off-target editing sites and compare the ability of these tools to properly analyze off-target effects. Recent advances in both in silico and experimental tools for off-target analysis have generated remarkably concordant results for sites with high off-target editing activity. However, no single tool is able to accurately predict low-frequency off-target editing, presenting a bottleneck in therapeutic genome editing, because even a small number of cells with off-target editing can be detrimental. Therefore, we recommend that at least one in silico tool and one experimental tool should be used together to identify potential off-target sites, and amplicon-based next-generation sequencing (NGS) should be used as the gold standard assay for assessing the true off-target effects at these candidate sites. Future work to improve off-target analysis includes expanding the true off-target editing dataset to evaluate new experimental techniques and to train machine learning algorithms; performing analysis using the particular genome of the cells in question rather than the reference genome; and applying novel NGS techniques to improve the sensitivity of amplicon-based off-target editing quantification.

Therapeutic gene editing strategies using CRISPR-Cas9 for the β-hemoglobinopathies

With advancements in gene editing technologies, our ability to make precise and efficient modifications to the genome is increasing at a remarkable rate, paving the way for scientists and clinicians to uniquely treat a multitude of previously irremediable diseases. CRISPR-Cas9, short for clustered regularly interspaced short palindromic repeats and CRISPR-associated protein 9, is a gene editing platform with the ability to alter the nucleotide sequence of the genome in living cells. This technology is increasing the number and pace at which new gene editing treatments for genetic disorders are moving toward the clinic. The β-hemoglobinopathies are a group of monogenic diseases, which despite their high prevalence and chronic debilitating nature, continue to have few therapeutic options available. In this review, we will discuss our existing comprehension of the genetics and current state of treatment for β-hemoglobinopathies, consider potential genome editing therapeutic strategies, and provide an overview of the current state of clinical trials using CRISPR-Cas9 gene editing.

Delivery Approaches for Therapeutic Genome Editing and Challenges

Impressive therapeutic advances have been possible through the advent of zinc-finger nucleases and transcription activator-like effector nucleases. However, discovery of the more efficient and highly tailorable clustered regularly interspaced short palindromic repeats (CRISPR) and associated proteins (Cas9) has provided unprecedented gene-editing capabilities for treatment of various inherited and acquired diseases. Despite recent clinical trials, a major barrier for therapeutic gene editing is the absence of safe and effective methods for local and systemic delivery of gene-editing reagents. In this review, we elaborate on the challenges and provide practical considerations for improving gene editing. Specifically, we highlight issues associated with delivery of gene-editing tools into clinically relevant cells.

Technologies and Computational Analysis Strategies for CRISPR Applications

The CRISPR-Cas system offers a programmable platform for eukaryotic genome and epigenome editing. The ability to perform targeted genetic and epigenetic perturbations enables researchers to perform a variety of tasks, ranging from investigating questions in basic biology to potentially developing novel therapeutics for the treatment of disease. While CRISPR systems have been engineered to target DNA and RNA with increased precision, efficiency, and flexibility, assays to identify off-target editing are becoming more comprehensive and sensitive. Furthermore, techniques to perform high-throughput genome and epigenome editing can be paired with a variety of readouts and are uncovering important cellular functions and mechanisms. These technological advances drive and are driven by accompanying computational approaches. Here, we briefly present available CRISPR technologies and review key computational advances and considerations for various CRISPR applications. In particular, we focus on the analysis of on- and off-target editing and CRISPR pooled screen data.