A benchmark of computational CRISPR-Cas9 guide design methods

CRISPRlnc: a machine learning method for lncRNA-specific single-guide RNA design of CRISPR/Cas9 system

CRISPR/Cas9 is a promising RNA-guided genome editing technology, which consists of a Cas9 nuclease and a single-guide RNA (sgRNA). So far, a number of sgRNA prediction softwares have been developed. However, they were usually designed for protein-coding genes without considering that long non-coding RNA (lncRNA) genes may have different characteristics. In this study, we first evaluated the performances of a series of known sgRNA-designing tools in the context of both coding and non-coding datasets. Meanwhile, we analyzed the underpinnings of their varied performances on the sgRNA's specificity for lncRNA including nucleic acid sequence, genome location and editing mechanism preference. Furthermore, we introduce a support vector machine-based machine learning algorithm named CRISPRlnc, which aims to model both CRISPR knock-out (CRISPRko) and CRISPR inhibition (CRISPRi) mechanisms to predict the on-target activity of targets. CRISPRlnc combined the paired-sgRNA design and off-target analysis to achieve one-stop design of CRISPR/Cas9 sgRNAs for non-coding genes. Performance comparison on multiple datasets showed that CRISPRlnc was far superior to existing methods for both CRISPRko and CRISPRi mechanisms during the lncRNA-specific sgRNA design. To maximize the availability of CRISPRlnc, we developed a web server (http://predict.crisprlnc.cc) and made it available for download on GitHub.

CRISPR-broad: combined design of multi-targeting gRNAs and broad, multiplex target finding

In CRISPR-Cas and related nuclease-mediated genome editing, target recognition is based on guide RNAs (gRNAs) that are complementary to selected DNA regions. While single site targeting is fundamental for localized genome editing, targeting to expanded and multiple chromosome elements is desirable for various biological applications such as genome mapping and epigenome editing that make use of different fusion proteins with enzymatically dead Cas9. The current gRNA design tools are not suitable for this task, as these are optimized for defining single gRNAs for unique loci. Here, we introduce CRISPR-broad, a standalone, open-source application that defines gRNAs with multiple but specific targets in large continuous or spread regions of the genome, as defined by the user. This ability to identify multi-targeting gRNAs and corresponding multiple targetable regions in genomes is based on a novel aggregate gRNA scoring derived from on-target windows and off-target sites. Applying the new tool to the genomes of two model species, C. elegans and H. sapiens, we verified its efficiency in determining multi-targeting gRNAs and ranking potential target regions optimized for broad targeting. Further, we demonstrated the general usability of CRISPR-broad by cellular mapping of a large human genome element using dCas9 fused to green fluorescent protein.

Comprehensive computational analysis of epigenetic descriptors affecting CRISPR-Cas9 off-target activity

BACKGROUND

A common issue in CRISPR-Cas9 genome editing is off-target activity, which prevents the widespread use of CRISPR-Cas9 in medical applications. Among other factors, primary chromatin structure and epigenetics may influence off-target activity.

METHODS

In this work, we utilize crisprSQL, an off-target database, to analyze the effect of 19 epigenetic descriptors on CRISPR-Cas9 off-target activity. Termed as 19 epigenetic features/scores, they consist of 6 experimental epigenetic and 13 computed nucleosome organization-related features. In terms of novel features, 15 of the epigenetic scores are newly considered. The 15 newly considered scores consist of 13 freshly computed nucleosome occupancy/positioning scores and 2 experimental features (MNase and DRIP). The other 4 existing scores are experimental features (CTCF, DNase I, H3K4me3, RRBS) commonly used in deep learning models for off-target activity prediction. For data curation, MNase was aggregated from existing experimental nucleosome occupancy data. Based on the sequence context information available in crisprSQL, we also computed nucleosome occupancy/positioning scores for off-target sites.

RESULTS

To investigate the relationship between the 19 epigenetic features and off-target activity, we first conducted Spearman and Pearson correlation analysis. Such analysis shows that some computed scores derived from training-based models and training-free algorithms outperform all experimental epigenetic features. Next, we evaluated the contribution of all epigenetic features in two successful machine/deep learning models which predict off-target activity. We found that some computed scores, unlike all 6 experimental features, significantly contribute to the predictions of both models. As a practical research contribution, we make the off-target dataset containing all 19 epigenetic features available to the research community.

CONCLUSIONS

Our comprehensive computational analysis helps the CRISPR-Cas9 community better understand the relationship between epigenetic features and CRISPR-Cas9 off-target activity.

De novo assembly and annotation of the CHOZN® GS-/- genome supports high-throughput genome-scale screening

Chinese hamster ovary (CHO) cells have been used as the industry standard for the production of therapeutic monoclonal antibodies for several decades. Despite significant improvements in commercial-scale production processes and media, the CHO cell has remained largely unchanged. Due to the cost and complexity of whole-genome sequencing and gene-editing it has been difficult to obtain the tools necessary to improve the CHO cell line. With the advent of next-generation sequencing and the discovery of the CRISPR/Cas9 system it has become more cost effective to sequence and manipulate the CHO genome. Here, we provide a comprehensive de novo assembly and annotation of the CHO-K1 based CHOZN® GS-/- genome. Using this platform, we designed, built, and confirmed the functionality of a whole genome CRISPR guide RNA library that will allow the bioprocessing community to design a more robust CHO cell line leading to the production of life saving medications in a more cost-effective manner.

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.

CRISPR-Cas9 gRNA efficiency prediction: an overview of predictive tools and the role of deep learning

The clustered regularly interspaced short palindromic repeat (CRISPR)/CRISPR-associated protein 9 (Cas9) system has become a successful and promising technology for gene-editing. To facilitate its effective application, various computational tools have been developed. These tools can assist researchers in the guide RNA (gRNA) design process by predicting cleavage efficiency and specificity and excluding undesirable targets. However, while many tools are available, assessment of their application scenarios and performance benchmarks are limited. Moreover, new deep learning tools have been explored lately for gRNA efficiency prediction, but have not been systematically evaluated. Here, we discuss the approaches that pertain to the on-target activity problem, focusing mainly on the features and computational methods they utilize. Furthermore, we evaluate these tools on independent datasets and give some suggestions for their usage. We conclude with some challenges and perspectives about future directions for CRISPR-Cas9 guide design.

Hairy CRISPR: Genome Editing in Plants Using Hairy Root Transformation

CRISPR/Cas-mediated genome editing is a powerful tool of plant functional genomics. Hairy root transformation is a rapid and convenient approach for obtaining transgenic roots. When combined, these techniques represent a fast and effective means of studying gene function. In this review, we outline the current state of the art reached by the combination of these approaches over seven years. Additionally, we discuss the origins of different Agrobacterium rhizogenes strains that are widely used for hairy root transformation; the components of CRISPR/Cas vectors, such as the promoters that drive Cas or gRNA expression, the types of Cas nuclease, and selectable and screenable markers; and the application of CRISPR/Cas genome editing in hairy roots. The modification of the already known vector pKSE401 with the addition of the rice translational enhancer OsMac3 and the gene encoding the fluorescent protein DsRed1 is also described.

Construct design for CRISPR/Cas-based genome editing in plants

CRISPR construct design is a key step in the practice of genome editing, which includes identification of appropriate Cas proteins, design and selection of guide RNAs (gRNAs), and selection of regulatory elements to express gRNAs and Cas proteins. Here, we review the choices of CRISPR-based genome editors suited for different needs in plant genome editing applications. We consider the technical aspects of gRNA design and the associated computational tools. We also discuss strategies for the design of multiplex CRISPR constructs for high-throughput manipulation of complex biological processes or polygenic traits. We provide recommendations for different elements of CRISPR constructs and discuss the remaining challenges of CRISPR construct optimization in plant genome editing.

Multigene editing: current approaches and beyond

CRISPR/Cas9 multigene editing is an active and widely studied topic in the fields of biomedicine and biology. It involves a simultaneous participation of multiple single-guide RNAs (sgRNAs) to edit multiple target genes in a way that each gene is edited by one of these sgRNAs. There are possibly numerous sgRNA candidates capable of on-target editing on each of these genes with various efficiencies. Meanwhile, each of these sgRNA candidates may cause unwanted off-target editing at many other genes. Therefore, selection optimization of these multiple sgRNAs is demanded so as to minimize the number of sgRNAs and thus reduce the collective negative effects caused by the off-target editing. This survey reviews wet-laboratory approaches to the implementation of multigene editing and their needs of computational tools for better design. We found that though off-target editing is unavoidable during the gene editing, those disfavored cuttings by some target genes' sgRNAs can potentially become on-target editing sites for some other genes of interests. This off-to-on role conversion is beneficial to optimize the sgRNA selection in multigene editing. We present a preference cutting score to assess those beneficial off-target cutting sites, which have a few mismatches with their host genes' on-target editing sites. These potential sgRNAs can be prioritized for recommendation via ranking their on-target average cutting efficiency, the total off-target site number and their average preference cutting score. We also present case studies on cancer-associated genes to demonstrate tremendous usefulness of the new method.

TSA Promotes CRISPR/Cas9 Editing Efficiency and Expression of Cell Division-Related Genes from Plant Protoplasts

Trichostatin A (TSA) is a representative histone deacetylase (HDAC) inhibitor that modulates epigenetic gene expression by regulation of chromatin remodeling in cells. To investigate whether the regulation of chromatin de-condensation by TSA can affect the increase in the efficiency of Cas9 protein-gRNA ribonucleoprotein (RNP) indel formation from plant cells, genome editing efficiency using lettuce and tobacco protoplasts was examined after several concentrations of TSA treatments (0, 0.1, 1 and 10 μM). RNP delivery from protoplasts was conducted by conventional polyethylene glycol (PEG) transfection protocols. Interestingly, the indel frequency of the SOC1 gene from TSA treatments was about 3.3 to 3.8 times higher than DMSO treatment in lettuce protoplasts. The TSA-mediated increase of indel frequency of the SOC1 gene in lettuce protoplasts occurred in a concentration-dependent manner, although there was not much difference. Similar to lettuce, TSA also increased the indel frequency by 1.5 to 1.8 times in a concentration-dependent manner during PDS genome editing using tobacco protoplasts. The MNase test clearly showed that chromatin accessibility with TSA treatments was higher than that of DMSO treatment. Additionally, TSA treatment significantly increased the level of histone H3 and H4 acetylation from lettuce protoplasts. The qRT-PCR analysis showed that expression of cell division-related genes (LsCYCD1-1, LsCYCD3-2, LsCYCD6-1, and LsCYCU4-1) was increased by TSA treatment. These findings could contribute to increasing the efficiency of CRISPR/Cas9-mediated genome editing. Furthermore, this could be applied for the development of useful genome-edited crops using the CRISPR/Cas9 system with plant protoplasts.

Genome-wide detection and analysis of CRISPR-Cas off-targets

The clustered, regularly interspersed, short palindromic repeats (CRISPR) technology is revolutionizing biological studies and holds tremendous promise for treating human diseases. However, a significant limitation of this technology is that modifications can occur on off-target sites lacking perfect complementarity to the single guide RNA (sgRNA) or canonical protospacer-adjacent motif (PAM) sequence. Several in vivo and in vitro genome-wide off-target profiling approaches have been developed to inform on the fidelity of gene editing. Of these, GUIDE-seq has become one of the most widely adopted and reproducible methods. To allow users to easily analyze GUIDE-seq data generated on any sequencing platform, we developed an open-source pipeline, GS-Preprocess, that takes standard base-call output in bcl format and generate all required input data for off-target identification using bioconductor package GUIDEseq for off-target identification. Furthermore, we created a Docker image with GS-Proprocess, GUIDE-seq, and all its R and system dependencies already installed. The bundled pipeline will empower end users to streamline the analysis of GUIDE-seq data and motivate their use of higher throughput sequencing with increased multiplexing for GUIDE-seq experiments.

Targeting cancer epigenetics with CRISPR-dCAS9: Principles and prospects

Cancer therapeutics is an ever-evolving field due to incessant demands for effective and precise treatment options. Over the last few decades, cancer treatment strategies have shifted somewhat from surgery to targeted precision medicine. CRISPR-dCas9 is an emerging version of precision cancer therapy that has been adapted from the prokaryotic CRISPR-Cas system. Once ligated to epigenetic effectors (EE), CRISPR-dCas9 can function as an epigenetic editing tool and CRISPR-dCas9-EE complexes could be exploited to alter cancerous epigenetic features associated with different cancer hallmarks. In this article, we discuss the rationale of epigenetic editing as a therapeutic strategy against cancer. We also outline how sgRNA-dCas9 was derived from the CRISPR-Cas system. In addition, the current status of sgRNA-dCas9 use (in vivo and in vitro) in cancer is updated with a molecular illustration of CRISPR-dCas9-mediated epigenetic and transcriptional modulation. As sgRNA-dCas9 is still at the developmental phase, challenges are inherent to its use. We evaluate major challenges in targeting cancer with sgRNA-dCas9 such as off-target effects, lack of sgRNA designing rubrics, target site selection dilemmas and deficient sgRNA-dCas9 delivery systems. Finally, we appraise the sgRNA-dCas9 as a prospective cancer therapeutic by summarizing ongoing improvements of sgRNA-dCas9 methodology.

Trends in CRISPR-Cas9 technology application in cancer

The evolution of the CRISPR-Cas9 technology in cancer research has tremendous potential to shape the future of oncology. Although this gene-editing tool's pre-clinical progress is into its nascent stage, there are many unanswered questions regarding health benefits and therapy precision using CRISPR. The application of CRISPR is highly specific, economically sustainable, and is a high throughput technique, but on the other hand, its application involves measured risk of countering the toxic immune response of Cas protein, off-target effects, limitation of delivering the edited cells back into cancer patients. The current chapter highlights the possibilities and perils of the present-day CRISPR engineering in cancer that should highlight CRISPR translation to therapy.

Gene Editing in Dimorphic Fungi Using CRISPR/Cas9

Dimorphic fungi in the genera Blastomyces, Histoplasma, Coccidioides, and Paracoccidioides are important human pathogens that affect human health in many countries throughout the world. Understanding the biology of these fungi is important for the development of effective treatments and vaccines. Gene editing is a critically important tool for research into these organisms. In recent years, gene targeting approaches employing RNA-guided DNA nucleases, such as clustered regularly interspaced short palindromic repeats (CRISPR)/CRISPR-associated nuclease 9 (Cas9), have exploded in popularity. Here, we provide a detailed description of the steps involved in applying CRISPR/Cas9 technology to dimorphic fungi, with Blastomyces dermatitidis in particular as our model fungal pathogen. We discuss the design and construction of single guide RNA and Cas9-expressing targeting vectors (including multiplexed vectors) as well as introduction of these plasmids into Blastomyces using Agrobacterium-mediated transformation. Finally, we cover the outcomes that may be expected in terms of gene-editing efficiency and types of gene alterations produced. © 2020 Wiley Periodicals LLC. Basic Protocol 1: Construction of CRISPR/Cas9 targeting vectors Support Protocol 1: Choosing protospacers in the target gene Basic Protocol 2: Agrobacterium-mediated transformation of Blastomyces Support Protocol 2: Preparation of electrocompetent Agrobacterium Support Protocol 3: Preparation and recovery of Blastomyces frozen stocks.

Systematic in vitro profiling of off-target affinity, cleavage and efficiency for CRISPR enzymes

CRISPR RNA-guided endonucleases (RGEs) cut or direct activities to specific genomic loci, yet each has off-target activities that are often unpredictable. We developed a pair of simple in vitro assays to systematically measure the DNA-binding specificity (Spec-seq), catalytic activity specificity (SEAM-seq) and cleavage efficiency of RGEs. By separately quantifying binding and cleavage specificity, Spec/SEAM-seq provides detailed mechanistic insight into off-target activity. Feature-based models generated from Spec/SEAM-seq data for SpCas9 were consistent with previous reports of its in vitro and in vivo specificity, validating the approach. Spec/SEAM-seq is also useful for profiling less-well characterized RGEs. Application to an engineered SpCas9, HiFi-SpCas9, indicated that its enhanced target discrimination can be attributed to cleavage rather than binding specificity. The ortholog ScCas9, on the other hand, derives specificity from binding to an extended PAM. The decreased off-target activity of AsCas12a (Cpf1) appears to be primarily driven by DNA-binding specificity. Finally, we performed the first characterization of CasX specificity, revealing an all-or-nothing mechanism where mismatches can be bound, but not cleaved. Together, these applications establish Spec/SEAM-seq as an accessible method to rapidly and reliably evaluate the specificity of RGEs, Cas::gRNA pairs, and gain insight into the mechanism and thermodynamics of target discrimination.

CRISPR screens in the era of microbiomes

Recent advances in genomics have uncovered the tremendous diversity and richness of microbial ecosystems. New functional genomics methods are now needed to probe gene function in high-throughput and provide mechanistic insights. Here, we review how the CRISPR toolbox can be used to inactivate, repress or overexpress genes in a sequence-specific manner and how this offers diverse attractive solutions to identify gene function in high-throughput. Developed both in eukaryotes and prokaryotes, CRISPR screening technologies have already provided meaningful insights in microbiology and host-pathogen interactions. In the era of microbiomes, the versatility and the functional diversity of CRISPR-derived tools has the potential to significantly improve our understanding of microbial communities and their interaction with the host.

Management of cutaneous neurofibroma: current therapy and future directions

Neurofibromatosis type 1 (NF1) is a life-long neurocutaneous disorder characterized by a predisposition to tumor development, including cutaneous neurofibroma (cNF), the hallmark of the disease. cNF is a histologically benign, multicellular tumor formed in virtually most individuals with NF1. It is considered the most burdensome feature of the disorder due to their physical discomfort, cosmetically disfiguring appearance, and psychosocial burden. Management of cNF remains a challenge in the medical field. Effective medicinal treatment for cNF does not exist at this time. Trials aimed at targeting individual components of the neoplasm such as mast cells with Ketotifen have not shown much success. Physical removal or destruction has been the mainstay of therapy. Surgical removal gives excellent cosmetic results, but risk in general anesthesia may require trained specialists. Destructive laser such as CO2 laser is effective in treating hundreds of tumors at one time but has high risk of scarring hypopigmentation or hyperpigmentation that alter cosmetic outcomes. A robust, low-risk surgical technique has been developed, which may be performed in clinic using traditional biopsy tools that may be more accessible to NF1 patients worldwide than contemporary techniques including Er:YAG or Nd:YAG laser. In this review, specific recommendations for management of cNFs are made based on symptoms, clinical expertise, and available resources. Additionally, antiproliferative agents aimed at stimulating cellular quiescence are explored.

crispRdesignR: A Versatile Guide RNA Design Package in R for CRISPR/Cas9 Applications

The success of CRISPR/Cas9 gene editing applications relies on the efficiency of the single guide RNA (sgRNA) used in conjunction with the Cas9 protein. Current sgRNA design software vary in the details they provide on sgRNA sequence efficiency and usually limit organism choice to a list of developer-selected species. The crispRdesignR package aims to address these limitations by providing comprehensive sequence features of the generated sgRNAs in a single program, which allows users to predict sgRNA efficiency and design sgRNA sequences for systems that currently do not have optimized efficiency scoring methods. crispRdesignR reports extensive information on all designed sgRNA sequences with robust off-target calling and annotation and can be run in a user-friendly graphical interface. The crispRdesignR package is implemented in R and has fully editable code for specialized purposes including sgRNA design in user-provided genomes. The package is platform independent and extendable, with its source code and documentation freely available at https://github.com/dylanbeeber/crispRdesignR.

Improving CRISPR guide design with consensus approaches

Background

CRISPR-based systems are playing an important role in modern genome engineering. A large number of computational methods have been developed to assist in the identification of suitable guides. However, there is only limited overlap between the guides that each tool identifies. This can motivate further development, but also raises the question of whether it is possible to combine existing tools to improve guide design.

Results

We considered nine leading guide design tools, and their output when tested using two sets of guides for which experimental validation data is available. We found that consensus approaches were able to outperform individual tools. The best performance (with a precision of up to 0.912) was obtained when combining four of the tools and accepting all guides selected by at least three of them.

Conclusions

These results can be used to improve CRISPR-based studies, but also to guide further tool development. However, they only provide a short-term solution as the time and computational resources required to run four tools may be impractical in certain applications.