Impact of Genetic Variation on CRISPR-Cas Targeting

Germline variation contributes to false negatives in CRISPR-based experiments with varying burden across ancestries

Reducing disparities is vital for equitable access to precision treatments in cancer. Socioenvironmental factors are a major driver of disparities, but differences in genetic variation likely also contribute. The impact of genetic ancestry on prioritization of cancer targets in drug discovery pipelines has not been systematically explored due to the absence of pre-clinical data at the appropriate scale. Here, we analyze data from 611 genome-scale CRISPR/Cas9 viability experiments in human cell line models to identify ancestry-associated genetic dependencies essential for cell survival. Surprisingly, we find that most putative associations between ancestry and dependency arise from artifacts related to germline variants. Our analysis suggests that for 1.2-2.5% of guides, germline variants in sgRNA targeting sequences reduce cutting by the CRISPR/Cas9 nuclease, disproportionately affecting cell models derived from individuals of recent African descent. We propose three approaches to mitigate this experimental bias, enabling the scientific community to address these disparities.

The dawn of a cure for sickle cell disease through CRISPR-based treatment: A critical test of equity in public health genomics

Equity in access to genomic technologies, resources, and products remains a great challenge. This was evident especially during the coronavirus disease 2019 (COVID-19) pandemic when the majority of lower middle-income countries were unable to achieve at least 10% population vaccination coverage during initial COVID-19 vaccine rollouts, despite the rapid development of those vaccines. Sickle cell disease (SCD) is an inherited monogenic red blood cell disorder that affects hemoglobin, the protein that carries oxygen through the body. Globally, the African continent carries the highest burden of SCD with at least 240,000 children born each year with the disease. SCD has evolved from a treatable to a curable disease. Recently, the UK medical regulator approved its cure through clustered regularly interspaced short palindromic repeat (CRISPR)-based treatment, whereas the US Food and Drug Administration has equally approved two SCD gene therapies. This presents a remarkable opportunity to demonstrate equity in public health genomics. This CRISPR-based treatment is expensive and therefore, a need for an ambitious action to ensure that they are affordable and accessible where they are needed most and stand to save millions of lives.

Deciphering the recent trends in pesticide bioremediation using genome editing and multi-omics approaches: a review

Pesticide pollution in recent times has emerged as a grave environmental problem contaminating both aquatic and terrestrial ecosystems owing to their widespread use. Bioremediation using gene editing and system biology could be developed as an eco-friendly and proficient tool to remediate pesticide-contaminated sites due to its advantages and greater public acceptance over the physical and chemical methods. However, it is indispensable to understand the different aspects associated with microbial metabolism and their physiology for efficient pesticide remediation. Therefore, this review paper analyses the different gene editing tools and multi-omics methods in microbes to produce relevant evidence regarding genes, proteins and metabolites associated with pesticide remediation and the approaches to contend against pesticide-induced stress. We systematically discussed and analyzed the recent reports (2015-2022) on multi-omics methods for pesticide degradation to elucidate the mechanisms and the recent advances associated with the behaviour of microbes under diverse environmental conditions. This study envisages that CRISPR-Cas, ZFN and TALEN as gene editing tools utilizing Pseudomonas, Escherichia coli and Achromobacter sp. can be employed for remediation of chlorpyrifos, parathion-methyl, carbaryl, triphenyltin and triazophos by creating gRNA for expressing specific genes for the bioremediation. Similarly, systems biology accompanying multi-omics tactics revealed that microbial strains from Paenibacillus, Pseudomonas putida, Burkholderia cenocepacia, Rhodococcus sp. and Pencillium oxalicum are capable of degrading deltamethrin, p-nitrophenol, chlorimuron-ethyl and nicosulfuron. This review lends notable insights into the research gaps and provides potential solutions for pesticide remediation by using different microbe-assisted technologies. The inferences drawn from the current study will help researchers, ecologists, and decision-makers gain comprehensive knowledge of value and application of systems biology and gene editing in bioremediation assessments.

Emergence of CRISPR/Cas9-mediated bioimaging: A new dawn of in-situ detection

In-situ detection provides deep insights into the function of genes and their relationship with diseases by directly visualizing their spatiotemporal behavior. As an emerging in-situ imaging tool, clustered regularly interspaced short palindromic repeats (CRISPR)-mediated bioimaging can localize targets in living and fixed cells. CRISPR-mediated bioimaging has inherent advantages over the gold standard of fluorescent in-situ hybridization (FISH), including fast imaging, cost-effectiveness, and ease of preparation. Existing reviews have provided a detailed classification and overview of the principles of CRISPR-mediated bioimaging. However, the exploitation of potential clinical applicability of this bioimaging technique is still limited. Therefore, analyzing the potential value of CRISPR-mediated in-situ imaging is of great significance to the development of bioimaging. In this review, we initially discuss the available CRISPR-mediated imaging systems from the following aspects: summary of imaging substances, the design and optimization of bioimaging strategies, and factors influencing CRISPR-mediated in-situ detection. Subsequently, we highlight the potential of CRISPR-mediated bioimaging for application in biomedical research and clinical practice. Furthermore, we outline the current bottlenecks and future perspectives of CRISPR-based bioimaging. We believe that this review will facilitate the potential integration of bioimaging-related research with current clinical workflow.

Current Bioinformatics Tools to Optimize CRISPR/Cas9 Experiments to Reduce Off-Target Effects

The CRISPR-Cas system has evolved into a cutting-edge technology that has transformed the field of biological sciences through precise genetic manipulation. CRISPR/Cas9 nuclease is evolving into a revolutionizing method to edit any gene of any species with desirable outcomes. The swift advancement of CRISPR-Cas technology is reflected in an ever-expanding ecosystem of bioinformatics tools designed to make CRISPR/Cas9 experiments easier. To assist researchers with efficient guide RNA designs with fewer off-target effects, nuclease target site selection, and experimental validation, bioinformaticians have built and developed a comprehensive set of tools. In this article, we will review the various computational tools available for the assessment of off-target effects, as well as the quantification of nuclease activity and specificity, including web-based search tools and experimental methods, and we will describe how these tools can be optimized for gene knock-out (KO) and gene knock-in (KI) for model organisms. We also discuss future directions in precision genome editing and its applications, as well as challenges in target selection, particularly in predicting off-target effects.

Bioremediation of Endocrine Disrupting Chemicals- Advancements and Challenges

Endocrine Disrupting Chemicals (EDCs), major group of recalcitrant compounds, poses a serious threat to the health and future of millions of human beings, and other flora and fauna for years to come. A close analysis of various xenobiotics undermines the fact that EDC is structurally diverse chemical compounds generated as a part of anthropogenic advancements as well as part of their degradation. Regardless of such structural diversity, EDC is common in their ultimate drastic effect of impeding the proper functioning of the endocrinal system, basic physiologic systems, resulting in deregulated growth, malformations, and cancerous outcomes in animals as well as humans. The current review outlines an overview of various EDCs, their toxic effects on the ecosystem and its inhabitants. Conventional remediation methods such as physico-chemical methods and enzymatic approaches have been put into action as some form of mitigation measures. However, the last decade has seen the hunt for newer technologies and methodologies at an accelerated pace. Genetically engineered microbial degradation, gene editing strategies, metabolic and protein engineering, and in-silico predictive approaches - modern day's additions to our armamentarium in combating the EDCs are addressed. These additions have greater acceptance socially with lesser dissonance owing to reduced toxic by-products, lower health trepidations, better degradation, and ultimately the prevention of bioaccumulation. The positive impact of such new approaches on controlling the menace of EDCs has been outlaid. This review will shed light on sources of EDCs, their impact, significance, and the different remediation and bioremediation approaches, with a special emphasis on the recent trends and perspectives in using sustainable approaches for bioremediation of EDCs. Strict regulations to prevent the release of estrogenic chemicals to the ecosystem, adoption of combinatorial methods to remove EDC and prevalent use of bioremediation techniques should be followed in all future endeavors to combat EDC pollution. Moreover, the proper development, growth and functioning of future living forms relies on their non-exposure to EDCs, thus remediation of such chemicals present even in nano-concentrations should be addressed gravely.

CRISPR approach in environmental chemical screening focusing on population variability

A significant barrier to include population variability in risk assessment is our incomplete understanding of inter-individual variability and the differential susceptibility to environmental exposures induced adverse outcomes. By combining genome editing tools with the population diversity model, this article intended to highlight a potential strategy to identify and characterize the inter-individual variability factors, the determinant gene anchoring to a particular phenotype. The goal could be achieved by integrating the perturbed CRISPR-based unbiased functional genomics screening, genome-wide or a focused subset of genes, in a population-based in vitro model system (such as the lymphoblastoid cell lines, LCL, available from HapMap and 1000 Genomes project). Then data can be translated to genetic variability and individual (or subpopulation) susceptibility by incorporating ethnicity and corresponding genome-wide association studies (GWAS) with functional genomics screening results. This approach can provide complementary data for next-generation risk assessment, in particular, for environmental stressors. The current paper outlined the previous work conducted with a population-based in vitro model system, perturbed CRISPR-based functional toxicogenomic screening of environmental chemicals, and finally, the potential strategies to combine these two platforms with their opportunities and challenges to achieve a mechanistic understanding of population variability.

Paving the way towards precise and safe CRISPR genome editing

As the possibilities of CRISPR-Cas9 technology have been revealed, we have entered a new era of research aimed at increasing its specificity and safety. This stage of technology development is necessary not only for its wider application in the clinic but also in basic research to better control the process of genome editing. Research during the past eight years has identified some factors influencing editing outcomes and led to the development of highly specific endonucleases, modified guide RNAs and computational tools supporting experiments. More recently, large-scale experiments revealed a previously overlooked feature: Cas9 can generate reproducible mutation patterns. As a result, it has become apparent that Cas9-induced double-strand break (DSB) repair is nonrandom and can be predicted to some extent. Here, we review the present state of knowledge regarding the specificity and safety of CRISPR-Cas9 technology to define gRNA, protein and target-related problems and solutions. These issues include sequence-specific off-target effects, immune responses, genetic variation and chromatin accessibility. We present new insights into the role of DNA repair in genome editing and define factors influencing editing outcomes. In addition, we propose practical guidelines for increasing the specificity of editing and discuss novel perspectives in improvement of this technology.

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.

Challenges and Strategies in Ascribing Functions to Long Noncoding RNAs

Long noncoding RNAs (lncRNAs) are involved in many physiological and pathological processes, such as development, aging, immunity, and cancer. Mechanistically, lncRNAs exert their functions through interaction with proteins, genomic DNA, and other RNA, leading to transcriptional and post-transcriptional regulation of gene expression, either in cis or in trans; it is often difficult to distinguish between these two regulatory mechanisms. A variety of approaches, including RNA interference, antisense oligonucleotides, CRISPR-based methods, and genetically engineered mouse models, have yielded abundant information about lncRNA functions and underlying mechanisms, albeit with many discrepancies. In this review, we elaborate on the challenges in ascribing functions to lncRNAs based on the features of lncRNAs, including the genomic location, copy number, domain structure, subcellular localization, stability, evolution, and expression pattern. We also describe a framework for the investigation of lncRNA functions and mechanisms of action. Rigorous characterization of cancer-implicated lncRNAs is critical for the identification of bona fide anticancer targets.

Computational Tools and Resources Supporting CRISPR-Cas Experiments

The CRISPR-Cas system has become a cutting-edge technology that revolutionized genome engineering. The use of Cas9 nuclease is currently the method of choice in most tasks requiring a specific DNA modification. The rapid development in the field of CRISPR-Cas is reflected by the constantly expanding ecosystem of computational tools aimed at facilitating experimental design and result analysis. The first group of CRISPR-Cas-related tools that we review is dedicated to aid in guide RNA design by prediction of their efficiency and specificity. The second, relatively new group of tools exploits the observed biases in repair outcomes to predict the results of CRISPR-Cas edits. The third class of tools is developed to assist in the evaluation of the editing outcomes by analysis of the sequencing data. These utilities are accompanied by relevant repositories and databases. Here we present a comprehensive and updated overview of the currently available CRISPR-Cas-related tools, from the perspective of a user who needs a convenient and reliable means to facilitate genome editing experiments at every step, from the guide RNA design to analysis of editing outcomes. Moreover, we discuss the current limitations and challenges that the field must overcome for further improvement in the CRISPR-Cas endeavor.

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

MOTIVATION

Clustered regularly interspaced short palindromic repeats (CRISPR) technologies allow for facile genomic modification in a site-specific manner. A key step in this process is the in silico design of single guide RNAs to efficiently and specifically target a site of interest. To this end, it is necessary to enumerate all potential off-target sites within a given genome that could be inadvertently altered by nuclease-mediated cleavage. Currently available software for this task is limited by computational efficiency, variant support or annotation, and assessment of the functional impact of potential off-target effects.

RESULTS

To overcome these limitations, we have developed CRISPRitz, a suite of software tools to support the design and analysis of CRISPR/CRISPR-associated (Cas) experiments. Using efficient data structures combined with parallel computation, we offer a rapid, reliable, and exhaustive search mechanism to enumerate a comprehensive list of putative off-target sites. As proof-of-principle, we performed a head-to-head comparison with other available tools on several datasets. This analysis highlighted the unique features and superior computational performance of CRISPRitz including support for genomic searching with DNA/RNA bulges and mismatches of arbitrary size as specified by the user as well as consideration of genetic variants (variant-aware). In addition, graphical reports are offered for coding and non-coding regions that annotate the potential impact of putative off-target sites that lie within regions of functional genomic annotation (e.g. insulator and chromatin accessible sites from the ENCyclopedia Of DNA Elements [ENCODE] project).

AVAILABILITY AND IMPLEMENTATION

The software is freely available at: https://github.com/pinellolab/CRISPRitzhttps://github.com/InfOmics/CRISPRitz.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

VARSCOT: variant-aware detection and scoring enables sensitive and personalized off-target detection for CRISPR-Cas9

Background

Natural variations in a genome can drastically alter the CRISPR-Cas9 off-target landscape by creating or removing sites. Despite the resulting potential side-effects from such unaccounted for sites, current off-target detection pipelines are not equipped to include variant information. To address this, we developed VARiant-aware detection and SCoring of Off-Targets (VARSCOT).

Results

VARSCOT identifies only 0.6% of off-targets to be common between 4 individual genomes and the reference, with an average of 82% of off-targets unique to an individual. VARSCOT is the most sensitive detection method for off-targets, finding 40 to 70% more experimentally verified off-targets compared to other popular software tools and its machine learning model allows for CRISPR-Cas9 concentration aware off-target activity scoring.

Conclusions

VARSCOT allows researchers to take genomic variation into account when designing individual or population-wide targeting strategies. VARSCOT is available from https://github.com/BauerLab/VARSCOT.

Electronic supplementary material

The online version of this article (10.1186/s12896-019-0535-5) contains supplementary material, which is available to authorized users.

Gene Editing and Systems Biology Tools for Pesticide Bioremediation: A Review

Bioremediation is the degradation potential of microorganisms to dissimilate the complex chemical compounds from the surrounding environment. The genetics and biochemistry of biodegradation processes in datasets opened the way of systems biology. Systemic biology aid the study of interacting parts involved in the system. The significant keys of system biology are biodegradation network, computational biology, and omics approaches. Biodegradation network consists of all the databases and datasets which aid in assisting the degradation and deterioration potential of microorganisms for bioremediation processes. This review deciphers the bio-degradation network, i.e., the databases and datasets (UM-BBD, PAN, PTID, etc.) aiding in assisting the degradation and deterioration potential of microorganisms for bioremediation processes, computational biology and multi omics approaches like metagenomics, genomics, transcriptomics, proteomics, and metabolomics for the efficient functional gene mining and their validation for bioremediation experiments. Besides, the present review also describes the gene editing tools like CRISPR Cas, TALEN, and ZFNs which can possibly make design microbe with functional gene of interest for degradation of particular recalcitrant for improved bioremediation.

The Current State and Future of CRISPR-Cas9 gRNA Design Tools

Recent years have seen the development of computational tools to assist researchers in performing CRISPR-Cas9 experiment optimally. More specifically, these tools aim to maximize on-target activity (guide efficiency) while also minimizing potential off-target effects (guide specificity) by analyzing the features of the target site. Nonetheless, currently available tools cannot robustly predict experimental success as prediction accuracy depends on the approximations of the underlying model and how closely the experimental setup matches the data the model was trained on. Here, we present an overview of the available computational tools, their current limitations and future considerations. We discuss new trends around personalized health by taking genomic variants into account when predicting target sites as well as discussing other governing factors that can improve prediction accuracy.