Minimal genome-wide human CRISPR-Cas9 library

A benchmark of computational methods for correcting biases of established and unknown origin in CRISPR-Cas9 screening data

BACKGROUND

CRISPR-Cas9 dropout screens are formidable tools for investigating biology with unprecedented precision and scale. However, biases in data lead to potential confounding effects on interpretation and compromise overall quality. The activity of Cas9 is influenced by structural features of the target site, including copy number amplifications (CN bias). More worryingly, proximal targeted loci tend to generate similar gene-independent responses to CRISPR-Cas9 targeting (proximity bias), possibly due to Cas9-induced whole chromosome-arm truncations or other genomic structural features and different chromatin accessibility levels.

RESULTS

We benchmarked eight computational methods, rigorously evaluating their ability to reduce both CN and proximity bias in the two largest publicly available cell-line-based CRISPR-Cas9 screens to date. We also evaluated the capability of each method to preserve data quality and heterogeneity by assessing the extent to which the processed data allows accurate detection of true positive essential genes, established oncogenetic addictions, and known/novel biomarkers of cancer dependency. Our analysis sheds light on the ability of each method to correct biases under different scenarios. AC-Chronos outperforms other methods in correcting both CN and proximity biases when jointly processing multiple screens of models with available CN information, whereas CRISPRcleanR is the top performing method for individual screens or when CN information is not available. In addition, Chronos and AC-Chronos yield a final dataset better able to recapitulate known sets of essential and non-essential genes.

CONCLUSIONS

Overall, our investigation provides guidance for the selection of the most appropriate bias-correction method, based on its strengths, weaknesses and experimental settings.

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.

Efficient gene knockout and genetic interaction screening using the in4mer CRISPR/Cas12a multiplex knockout platform

Genetic interactions mediate the emergence of phenotype from genotype, but technologies for combinatorial genetic perturbation in mammalian cells are challenging to scale. Here, we identify background-independent paralog synthetic lethals from previous CRISPR genetic interaction screens, and find that the Cas12a platform provides superior sensitivity and assay replicability. We develop the in4mer Cas12a platform that uses arrays of four independent guide RNAs targeting the same or different genes. We construct a genome-scale library, Inzolia, that is ~30% smaller than a typical CRISPR/Cas9 library while also targeting ~4000 paralog pairs. Screens in cancer cells demonstrate discrimination of core and context-dependent essential genes similar to that of CRISPR/Cas9 libraries, as well as detection of synthetic lethal and masking/buffering genetic interactions between paralogs of various family sizes. Importantly, the in4mer platform offers a fivefold reduction in library size compared to other genetic interaction methods, substantially reducing the cost and effort required for these assays.

Uncovering the bookshelves of CRISPR-based libraries: Advances and applications in cancer studies

The advent of CRISPR/Cas9 technology has revolutionized the genome editing field. CRISPR-based libraries have become powerful tools for high-throughput functional genomics and genetic screening. CRISPR-based libraries can represent a powerful approach to uncovering genes related to chemoresistance and therapy efficacy and to studying cancer cells' fitness. In this review, we conducted an extensive literature search and summarized multiple studies that utilized these libraries in both in vitro and in vivo research, emphasizing their key findings. We provide an overview of the design, construction, and applications of CRISPR-based libraries in different cancer-focused studies and discuss the different types of CRISPR-based libraries. We finally point out the challenges associated with library design, including guide RNA selection, off-target effects, and library complexity. This review provides an overview of the work conducted with CRISPR libraries in the search for new targets that could potentially assist in cancer therapy by contributing to functional approaches.

High-throughput screening of genetic and cellular drivers of syncytium formation induced by the spike protein of SARS-CoV-2

Mapping mutations and discovering cellular determinants that cause the spike protein of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) to induce infected cells to form syncytia would facilitate the development of strategies for blocking the formation of such cell-cell fusion. Here we describe high-throughput screening methods based on droplet microfluidics and the size-exclusion selection of syncytia, coupled with large-scale mutagenesis and genome-wide knockout screening via clustered regularly interspaced short palindromic repeats (CRISPR), for the large-scale identification of determinants of cell-cell fusion. We used the methods to perform deep mutational scans in spike-presenting cells to pinpoint mutable syncytium-enhancing substitutions in two regions of the spike protein (the fusion peptide proximal region and the furin-cleavage site). We also used a genome-wide CRISPR screen in cells expressing the receptor angiotensin-converting enzyme 2 to identify inhibitors of clathrin-mediated endocytosis that impede syncytium formation, which we validated in hamsters infected with SARS-CoV-2. Finding genetic and cellular determinants of the formation of syncytia may reveal insights into the physiological and pathological consequences of cell-cell fusion.

Prognostic and chemotherapeutic response prediction by proliferation essential gene signature: Investigating POLE2 in bladder cancer progression and cisplatin resistance

Background: Bladder cancer (BLCA) is the most common genitourinary malignancy. Proliferation essential genes (PEGs) are crucial to the survival of cancer cells. This study aimed to build a PEG signature to predict BLCA prognosis and treatment efficacy. Methods: BLCA PEGs and differentially expressed PEGs were identified using DepMap and TCGA-BLCA datasets, respectively. Based on the prognostic analysis of the differentially expressed PEGs, a PEG model was constructed. Subsequently, we analyzed the relationship between the PEG signature and prognosis of BLCA patients as well as their response to chemotherapy. Finally, we performed random forest analysis to target and functional experiments to validate the most significant PEG which is associated with BLCA progression. CCK-8, invasion, migration, and chemosensitivity assays were performed to assess effects of gene knockdown on BLCA cell proliferation, invasion and migration abilities, and cisplatin chemosensitivity. Results: We screened 10 prognostic PEGs from 201 differentially expressed PEGs and used them to construct a PEG signature model. Patients with high PEG signature score (PEGs-high) exhibited worse OS and lower sensitivity to chemotherapy than those with PEGs-low. We also found significant correlations between the PEG score and previously defined BLCA molecular subtypes. This suggests that the PEG score may effectively predict the molecular subtypes which have distinct clinical outcomes. Random forest analysis revealed that POLE2 (DNA polymerase epsilon subunit 2) was the most significant PEG differentiating BLCA tissue and normal tissue. Bioinformatic analysis and an immunohistochemistry staining assay confirmed that POLE2 was significantly up-regulated in tumor tissues and was associated with poor survival in BLCA patients. Moreover, POLE2 knockdown inhibited the ability of cell clone formation, proliferation, invasion, immigration and IC50 of cisplatin. Conclusion: The PEG signature acts as a potential predictor for prognosis and chemotherapy response in BLCA patients. POLE2 is a key PEG and plays a remarkable role in promoting the malignant progression and cisplatin resistance of BLCA.

Clonal dynamics limits detection of selection in tumour xenograft CRISPR/Cas9 screens

Transplantable in vivo CRISPR/Cas9 knockout screens, in which cells are edited in vitro and inoculated into mice to form tumours, allow evaluation of gene function in a cancer model that incorporates the multicellular interactions of the tumour microenvironment. To improve our understanding of the key parameters for success with this method, we investigated the choice of cell line, mouse host, tumour harvesting timepoint and guide RNA (gRNA) library size. We found that high gRNA (80-95%) representation was maintained in a HCT116 subline transduced with the GeCKOv2 whole-genome gRNA library and transplanted into NSG mice when tumours were harvested at early (14 d) but not late time points (38-43 d). The decreased representation in older tumours was accompanied by large increases in variance in gRNA read counts, with notable expansion of a small number of random clones in each sample. The variable clonal dynamics resulted in a high level of 'noise' that limited the detection of gRNA-based selection. Using simulated datasets derived from our experimental data, we show that considerable reductions in count variance would be achieved with smaller library sizes. Based on our findings, we suggest a pathway to rationally design adequately powered in vivo CRISPR screens for successful evaluation of gene function.

Functional classification of DDOST variants of uncertain clinical significance in congenital disorders of glycosylation

Congenital disorders of glycosylation (CDG) are rare genetic disorders with a spectrum of clinical manifestations caused by abnormal N-glycosylation of secreted and cell surface proteins. Over 130 genes are implicated and next generation sequencing further identifies potential disease drivers in affected individuals. However, functional testing of these variants is challenging, making it difficult to distinguish pathogenic from non-pathogenic events. Using proximity labelling, we identified OST48 as a protein that transiently interacts with lysyl oxidase (LOX), a secreted enzyme that cross-links the fibrous extracellular matrix. OST48 is a non-catalytic component of the oligosaccharyltransferase (OST) complex, which transfers glycans to substrate proteins. OST48 is encoded by DDOST, and 43 variants of DDOST are described in CDG patients, of which 34 are classified as variants of uncertain clinical significance (VUS). We developed an assay based on LOX N-glycosylation that confirmed two previously characterised DDOST variants as pathogenic. Notably, 39 of the 41 remaining variants did not have impaired activity, but we demonstrated that p.S243F and p.E286del were functionally impaired, consistent with a role in driving CDG in those patients. Thus, we describe a rapid assay for functional testing of clinically relevant CDG variants to complement genome sequencing and support clinical diagnosis of affected individuals.

Analysis and therapeutic targeting of the IL-1R pathway in anaplastic large cell lymphoma

Anaplastic large cell lymphoma (ALCL), a subgroup of mature T-cell neoplasms with an aggressive clinical course, is characterized by elevated expression of CD30 and anaplastic cytology. To achieve a comprehensive understanding of the molecular characteristics of ALCL pathology and to identify therapeutic vulnerabilities, we applied genome-wide CRISPR library screenings to both anaplastic lymphoma kinase positive (ALK+) and primary cutaneous (pC) ALK- ALCLs and identified an unexpected role of the interleukin-1R (IL-1R) inflammatory pathway in supporting the viability of pC ALK- ALCL. Importantly, this pathway is activated by IL-1α in an autocrine manner, which is essential for the induction and maintenance of protumorigenic inflammatory responses in pC-ALCL cell lines and primary cases. Hyperactivation of the IL-1R pathway is promoted by the A20 loss-of-function mutation in the pC-ALCL lines we analyze and is regulated by the nonproteolytic protein ubiquitination network. Furthermore, the IL-1R pathway promotes JAK-STAT3 signaling activation in ALCLs lacking STAT3 gain-of-function mutation or ALK translocation and enhances the sensitivity of JAK inhibitors in these tumors in vitro and in vivo. Finally, the JAK2/IRAK1 dual inhibitor, pacritinib, exhibited strong activities against pC ALK- ALCL, where the IL-1R pathway is hyperactivated in the cell line and xenograft mouse model. Thus, our studies revealed critical insights into the essential roles of the IL-1R pathway in pC-ALCL and provided opportunities for developing novel therapeutic strategies.

Efficient gene knockout and genetic interactions: the IN4MER CRISPR/Cas12a multiplex knockout platform

Genetic interactions mediate the emergence of phenotype from genotype, but initial technologies for combinatorial genetic perturbation in mammalian cells suffer from inefficiency and are challenging to scale. Recent focus on paralog synthetic lethality in cancer cells offers an opportunity to evaluate different approaches and improve on the state of the art. Here we report a meta-analysis of CRISPR genetic interactions screens, identifying a candidate set of background-independent paralog synthetic lethals, and find that the Cas12a platform provides superior sensitivity and assay replicability. We demonstrate that Cas12a can independently target up to four genes from a single guide array, and we build on this knowledge by constructing a genome-scale library that expresses arrays of four guides per clone, a platform we call 'in4mer'. Our genome-scale human library, with only 49k clones, is substantially smaller than a typical CRISPR/Cas9 monogenic library while also targeting more than four thousand paralog pairs, triples, and quads. Proof of concept screens in four cell lines demonstrate discrimination of core and context-dependent essential genes similar to that of state-of-the-art CRISPR/Cas9 libraries, as well as detection of synthetic lethal and masking/buffering genetic interactions between paralogs of various family sizes, a capability not offered by any extant library. Importantly, the in4mer platform offers a fivefold reduction in the number of clones required to assay genetic interactions, dramatically improving the cost and effort required for these studies.

Optimized minimal genome-wide human sgRNA library

Genome-wide clustered regularly interspaced short palindromic repeats (CRISPR)-based knockout screening is revolting the genetic analysis of a cellular or molecular phenotype in question but is challenged by the large size of single-guide RNA (sgRNA) library. Here we designed a minimal genome-wide human sgRNA library, H-mLib, which is composed of 21,159 sgRNA pairs assembled based on a dedicated selection strategy from all potential SpCas9/sgRNAs in the human genome. These sgRNA pairs were cloned into a dual-gRNA vector each targeting one gene, resulting in a compact library size nearly identical to the number of human protein-coding genes. The performance of the H-mLib was benchmarked to other CRISPR libraries in a proliferation screening conducted in K562 cells. We also identified groups of core essential genes and cell-type specific essential genes by comparing the screening results from the K562 and Jurkat cells. Together, the H-mLib exemplified high specificity and sensitivity in identifying essential genes while containing minimal library complexity, emphasizing its advantages and applications in CRISPR screening with limited cell numbers.

Efficient prioritization of CRISPR screen hits by accounting for targeting efficiency of guide RNA

BACKGROUND

CRISPR-based screens are revolutionizing drug discovery as tools to identify genes whose ablation induces a phenotype of interest. For instance, CRISPR-Cas9 screening has been successfully used to identify novel therapeutic targets in cancer where disruption of genes leads to decreased viability of malignant cells. However, low-activity guide RNAs may give rise to variable changes in phenotype, preventing easy identification of hits and leading to false negative results. Therefore, correcting the effects of bias due to differences in guide RNA efficiency in CRISPR screening data can improve the efficiency of prioritizing hits for further validation. Here, we developed an approach to identify hits from negative CRISPR screens by correcting the fold changes (FC) in gRNA frequency by the actual, observed frequency of indel mutations generated by gRNA.

RESULTS

Each gRNA was coupled with the "reporter sequence" that can be targeted by the same gRNA so that the frequency of mutations in the reporter sequence can be used as a proxy for the endogenous target gene. The measured gRNA activity was used to correct the FC. We identified indel generation efficiency as the dominant factor contributing significant bias to screening results, and our method significantly removed such bias and was better at identifying essential genes when compared to conventional fold change analysis. We successfully applied our gRNA activity data to previously published gRNA screening data, and identified novel genes whose ablation could synergize with vemurafenib in the A375 melanoma cell line. Our method identified nicotinamide N-methyltransferase, lactate dehydrogenase B, and polypyrimidine tract-binding protein 1 as synergistic targets whose ablation sensitized A375 cells to vemurafenib.

CONCLUSIONS

We identified the variations in target cleavage efficiency, even in optimized sgRNA libraries, that pose a strong bias in phenotype and developed an analysis method that corrects phenotype score by the measured differences in the targeting efficiency among sgRNAs. Collectively, we expect that our new analysis method will more accurately identify genes that confer the phenotype of interest.

Optimization of Genomewide CRISPR Screens Using AsCas12a and Multi-Guide Arrays

Genomewide loss-of-function (LOF) screening using clustered regularly interspaced short palindromic repeats (CRISPR) has facilitated the discovery of novel gene functions across diverse physiological and pathophysiological systems. A challenge with conventional genomewide CRISPR-Cas9 libraries is the unwieldy size (60,000-120,000 constructs), which is resource intensive and prohibitive in some experimental contexts. One solution to streamlining CRISPR screening is by multiplexing two or more guides per gene on a single construct, which enables functional redundancy to compensate for suboptimal gene knockout by individual guides. In this regard, AsCas12a (Cpf1) and its derivatives, for example, enhanced AsCas12a (enAsCas12a), have enabled multiplexed guide arrays to be specifically and efficiently processed for genome editing. Prior studies have established that multiplexed CRISPR-Cas12a libraries perform comparably to the larger equivalent CRISPR-Cas9 libraries, yet the most efficient CRISPR-Cas12a library design remains unresolved. In this study, we demonstrate that CRISPR-Cas12a genomewide LOF screening performed optimally with three guides arrayed per gene construct and could be adapted to robotic cell culture without noticeable differences in screen performance. Thus, the conclusions from this study provide novel insight to streamlining genomewide LOF screening using CRISPR-Cas12a and robotic cell culture.

An interactive web application for processing, correcting, and visualizing genome-wide pooled CRISPR-Cas9 screens

A limitation of pooled CRISPR-Cas9 screens is the high false-positive rate in detecting essential genes arising from copy-number-amplified genomics regions. To solve this issue, we previously developed CRISPRcleanR: a computational method implemented as R/python package and in a dockerized version. CRISPRcleanR detects and corrects biased responses to CRISPR-Cas9 targeting in an unsupervised fashion, accurately reducing false-positive signals while maintaining sensitivity in identifying relevant genetic dependencies. Here, we present CRISPRcleanR WebApp , a web application enabling access to CRISPRcleanR through an intuitive interface. CRISPRcleanR WebApp removes the complexity of R/python language user interactions; provides user-friendly access to a complete analytical pipeline, not requiring any data pre-processing and generating gene-level summaries of essentiality with associated statistical scores; and offers a range of interactively explorable plots while supporting a more comprehensive range of CRISPR guide RNAs' libraries than the original package. CRISPRcleanR WebApp is available at https://crisprcleanr-webapp.fht.org/.

A modular CRISPR screen identifies individual and combination pathways contributing to HIV-1 latency

Transcriptional silencing of latent HIV-1 proviruses entails complex and overlapping mechanisms that pose a major barrier to in vivo elimination of HIV-1. We developed a new latency CRISPR screening strategy, called Latency HIV-CRISPR which uses the packaging of guideRNA-encoding lentiviral vector genomes into the supernatant of budding virions as a direct readout of factors involved in the maintenance of HIV-1 latency. We developed a custom guideRNA library targeting epigenetic regulatory genes and paired the screen with and without a latency reversal agent-AZD5582, an activator of the non-canonical NFκB pathway-to examine a combination of mechanisms controlling HIV-1 latency. A component of the Nucleosome Acetyltransferase of H4 histone acetylation (NuA4 HAT) complex, ING3, acts in concert with AZD5582 to activate proviruses in J-Lat cell lines and in a primary CD4+ T cell model of HIV-1 latency. We found that the knockout of ING3 reduces acetylation of the H4 histone tail and BRD4 occupancy on the HIV-1 LTR. However, the combination of ING3 knockout accompanied with the activation of the non-canonical NFκB pathway via AZD5582 resulted in a dramatic increase in initiation and elongation of RNA Polymerase II on the HIV-1 provirus in a manner that is nearly unique among all cellular promoters.

CEDA: integrating gene expression data with CRISPR-pooled screen data identifies essential genes with higher expression

MOTIVATION

Clustered regularly interspaced short palindromic repeats (CRISPR)-based genetic perturbation screen is a powerful tool to probe gene function. However, experimental noises, especially for the lowly expressed genes, need to be accounted for to maintain proper control of false positive rate.

METHODS

We develop a statistical method, named CRISPR screen with Expression Data Analysis (CEDA), to integrate gene expression profiles and CRISPR screen data for identifying essential genes. CEDA stratifies genes based on expression level and adopts a three-component mixture model for the log-fold change of single-guide RNAs (sgRNAs). Empirical Bayesian prior and expectation-maximization algorithm are used for parameter estimation and false discovery rate inference.

RESULTS

Taking advantage of gene expression data, CEDA identifies essential genes with higher expression. Compared to existing methods, CEDA shows comparable reliability but higher sensitivity in detecting essential genes with moderate sgRNA fold change. Therefore, using the same CRISPR data, CEDA generates an additional hit gene list.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Reduced gene templates for supervised analysis of scale-limited CRISPR-Cas9 fitness screens

Pooled genome-wide CRISPR-Cas9 screens are furthering our mechanistic understanding of human biology and have allowed us to identify new oncology therapeutic targets. Scale-limited CRISPR-Cas9 screens-typically employing guide RNA libraries targeting subsets of functionally related genes, biological pathways, or portions of the druggable genome-constitute an optimal setting for investigating narrow hypotheses and are easier to execute on complex models, such as organoids and in vivo models. Different supervised methods are used for computational analysis of genome-wide CRISPR-Cas9 screens; most are not well suited for scale-limited screens, as they require large sets of positive/negative control genes (gene templates) to be included among the screened ones. Here, we develop a computational framework identifying optimal subsets of known essential and nonessential genes (at different subsampling percentages) that can be used as templates for supervised analyses of scale-limited CRISPR-Cas9 screens, while having a reduced impact on the size of the employed library.

Computational estimation of quality and clinical relevance of cancer cell lines

Immortal cancer cell lines (CCLs) are the most widely used system for investigating cancer biology and for the preclinical development of oncology therapies. Pharmacogenomic and genome‐wide editing screenings have facilitated the discovery of clinically relevant gene–drug interactions and novel therapeutic targets via large panels of extensively characterised CCLs. However, tailoring pharmacological strategies in a precision medicine context requires bridging the existing gaps between tumours and in vitro models. Indeed, intrinsic limitations of CCLs such as misidentification, the absence of tumour microenvironment and genetic drift have highlighted the need to identify the most faithful CCLs for each primary tumour while addressing their heterogeneity, with the development of new models where necessary. Here, we discuss the most significant limitations of CCLs in representing patient features, and we review computational methods aiming at systematically evaluating the suitability of CCLs as tumour proxies and identifying the best patient representative in vitro models. Additionally, we provide an overview of the applications of these methods to more complex models and discuss future machine‐learning‐based directions that could resolve some of the arising discrepancies.

CRISPR screening in cancer stem cells

Cancer stem cells (CSCs) are a subpopulation of tumor cells with self-renewal ability. Increasing evidence points to the critical roles of CSCs in tumorigenesis, metastasis, therapy resistance, and cancer relapse. As such, the elimination of CSCs improves cancer treatment outcomes. However, challenges remain due to limited understanding of the molecular mechanisms governing self-renewal and survival of CSCs. Clustered regularly interspaced short palindromic repeats (CRISPR)/Cas9 screening has been increasingly used to identify genetic determinants in cancers. In this primer, we discuss the progress made and emerging opportunities of coupling advanced CRISPR screening systems with CSC models to reveal the understudied vulnerabilities of CSCs.

Comparative optimization of combinatorial CRISPR screens

Combinatorial CRISPR technologies have emerged as a transformative approach to systematically probe genetic interactions and dependencies of redundant gene pairs. However, the performance of different functional genomic tools for multiplexing sgRNAs vary widely. Here, we generate and benchmark ten distinct pooled combinatorial CRISPR libraries targeting paralog pairs to optimize digenic knockout screens. Libraries composed of dual Streptococcus pyogenes Cas9 (spCas9), orthogonal spCas9 and Staphylococcus aureus (saCas9), and enhanced Cas12a from Acidaminococcus were evaluated. We demonstrate a combination of alternative tracrRNA sequences from spCas9 consistently show superior effect size and positional balance between the sgRNAs as a robust combinatorial approach to profile genetic interactions of multiple genes.

Validating Small Molecule Chemical Probes for Biological Discovery

Small molecule chemical probes are valuable tools for interrogating protein biological functions and relevance as a therapeutic target. Rigorous validation of chemical probe parameters such as cellular potency and selectivity is critical to unequivocally linking biological and phenotypic data resulting from treatment with a chemical probe to the function of a specific target protein. A variety of modern technologies are available to evaluate cellular potency and selectivity, target engagement, and functional response biomarkers of chemical probe compounds. Here, we review these technologies and the rationales behind using them for the characterization and validation of chemical probes. In addition, large-scale phenotypic characterization of chemical probes through chemical genetic screening is increasingly leading to a wealth of information on the cellular pharmacology and disease involvement of potential therapeutic targets. Extensive compound validation approaches and integration of phenotypic information will lay foundations for further use of chemical probes in biological discovery. Expected final online publication date for the Annual Review of Biochemistry, Volume 91 is June 2022. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.

High-content CRISPR screening

CRISPR screens are a powerful source of biological discovery, enabling the unbiased interrogation of gene function in a wide range of applications and species. In pooled CRISPR screens, various genetically encoded perturbations are introduced into pools of cells. The targeted cells proliferate under a biological challenge such as cell competition, drug treatment or viral infection. Subsequently, the perturbation-induced effects are evaluated by sequencing-based counting of the guide RNAs that specify each perturbation. The typical results of such screens are ranked lists of genes that confer sensitivity or resistance to the biological challenge of interest. Contributing to the broad utility of CRISPR screens, adaptations of the core CRISPR technology make it possible to activate, silence or otherwise manipulate the target genes. Moreover, high-content read-outs such as single-cell RNA sequencing and spatial imaging help characterize screened cells with unprecedented detail. Dedicated software tools facilitate bioinformatic analysis and enhance reproducibility. CRISPR screening has unravelled various molecular mechanisms in basic biology, medical genetics, cancer research, immunology, infectious diseases, microbiology and other fields. This Primer describes the basic and advanced concepts of CRISPR screening and its application as a flexible and reliable method for biological discovery, biomedical research and drug development - with a special emphasis on high-content methods that make it possible to obtain detailed biological insights directly as part of the screen.

Common computational tools for analyzing CRISPR screens

CRISPR–Cas technology offers a versatile toolbox for genome editing, with applications in various cancer-related fields such as functional genomics, immunotherapy, synthetic lethality and drug resistance, metastasis, genome regulation, chromatic accessibility and RNA-targeting. The variety of screening platforms and questions in which they are used have caused the development of a wide array of analytical methods for CRISPR analysis. In this review, we focus on the algorithms and frameworks used in the computational analysis of pooled CRISPR knockout (KO) screens and highlight some of the most significant target discoveries made using these methods. Lastly, we offer perspectives on the design and analysis of state-of-art multiplex screening for genetic interactions.

CoRe: a robustly benchmarked R package for identifying core-fitness genes in genome-wide pooled CRISPR-Cas9 screens

BACKGROUND

CRISPR-Cas9 genome-wide screens are being increasingly performed, allowing systematic explorations of cancer dependencies at unprecedented accuracy and scale. One of the major computational challenges when analysing data derived from such screens is to identify genes that are essential for cell survival invariantly across tissues, conditions, and genomic-contexts (core-fitness genes), and to distinguish them from context-specific essential genes. This is of paramount importance to assess the safety profile of candidate therapeutic targets and for elucidating mechanisms involved in tissue-specific genetic diseases.

RESULTS

We have developed CoRe: an R package implementing existing and novel methods for the identification of core-fitness genes (at two different level of stringency) from joint analyses of multiple CRISPR-Cas9 screens. We demonstrate, through a fully reproducible benchmarking pipeline, that CoRe outperforms state-of-the-art tools, yielding more reliable and biologically relevant sets of core-fitness genes.

CONCLUSIONS

CoRe offers a flexible pipeline, compatible with many pre-processing methods for the analysis of CRISPR data, which can be tailored onto different use-cases. The CoRe package can be used for the identification of high-confidence novel core-fitness genes, as well as a means to filter out potentially cytotoxic hits while analysing cancer dependency datasets for identifying and prioritising novel selective therapeutic targets.

To Discover the Efficient and Novel Drug Targets in Human Cancers Using CRISPR/Cas Screening and Databases

CRISPR/Cas has emerged as an excelle nt gene-editing technology and is used worldwide for research. The CRISPR library is an ideal tool for identifying essential genes and synthetic lethality targeted for cancer therapies in human cancers. Synthetic lethality is defined as multiple genetic abnormalities that, when present individually, do not affect function or survival, but when present together, are lethal. Recently, many CRISPR libraries are available, and the latest libraries are more accurate and can be applied to few cells. However, it is easier to efficiently search for cancer targets with their own screenings by effectively using databases of CRISPR screenings, such as Depmap portal, PICKLES (Pooled In-Vitro CRISPR Knockout Library Essentiality Screens), iCSDB, Project Score database, and CRISP-view. This review will suggest recent optimal CRISPR libraries and effective databases for Novel Approaches in the Discovery and Design of Targeted Therapies.

Strategies for genetic manipulation of adult stem cell-derived organoids

Organoid technology allows the expansion of primary epithelial cells from normal and diseased tissues, providing a unique model for human (patho)biology. In a three-dimensional environment, adult stem cells self-organize and differentiate to gain tissue-specific features. Accessibility to genetic manipulation enables the investigation of the molecular mechanisms underlying cell fate regulation, cell differentiation and cell interactions. In recent years, powerful methodologies using lentiviral transgenesis, CRISPR/Cas9 gene editing, and single-cell readouts have been developed to study gene function and carry out genetic screens in organoids. However, the multicellularity and dynamic nature of stem cell-derived organoids also present challenges for genetic experimentation. In this review, we focus on adult gastrointestinal organoids and summarize the state-of-the-art protocols for successful transgenesis. We provide an outlook on emerging genetic techniques that could further increase the applicability of organoids and enhance the potential of organoid-based techniques to deepen our understanding of gene function in tissue biology.

A new era in functional genomics screens

The past 25 years of genomics research first revealed which genes are encoded by the human genome and then a detailed catalogue of human genome variation associated with many diseases. Despite this, the function of many genes and gene regulatory elements remains poorly characterized, which limits our ability to apply these insights to human disease. The advent of new CRISPR functional genomics tools allows for scalable and multiplexable characterization of genes and gene regulatory elements encoded by the human genome. These approaches promise to reveal mechanisms of gene function and regulation, and to enable exploration of how genes work together to modulate complex phenotypes.

CRISPR/Cas9: Principle, Applications, and Delivery through Extracellular Vesicles

The establishment of CRISPR/Cas9 (clustered regularly interspaced short palindromic repeats/CRISPR-associated protein 9) technology for eukaryotic gene editing opened up new avenues not only for the analysis of gene function but also for therapeutic interventions. While the original methodology allowed for targeted gene disruption, recent technological advancements yielded a rich assortment of tools to modify genes and gene expression in various ways. Currently, clinical applications of this technology fell short of expectations mainly due to problems with the efficient and safe delivery of CRISPR/Cas9 components to living organisms. The targeted in vivo delivery of therapeutic nucleic acids and proteins remain technically challenging and further limitations emerge, for instance, by unwanted off-target effects, immune reactions, toxicity, or rapid degradation of the transfer vehicles. One approach that might overcome many of these limitations employs extracellular vesicles as intercellular delivery devices. In this review, we first introduce the CRISPR/Cas9 system and its latest advancements, outline major applications, and summarize the current state of the art technology using exosomes or microvesicles for transporting CRISPR/Cas9 constituents into eukaryotic cells.

Minimized combinatorial CRISPR screens identify genetic interactions in autophagy

Combinatorial CRISPR-Cas screens have advanced the mapping of genetic interactions, but their experimental scale limits the number of targetable gene combinations. Here, we describe 3Cs multiplexing, a rapid and scalable method to generate highly diverse and uniformly distributed combinatorial CRISPR libraries. We demonstrate that the library distribution skew is the critical determinant of its required screening coverage. By circumventing iterative cloning of PCR-amplified oligonucleotides, 3Cs multiplexing facilitates the generation of combinatorial CRISPR libraries with low distribution skews. We show that combinatorial 3Cs libraries can be screened with minimal coverages, reducing associated efforts and costs at least 10-fold. We apply a 3Cs multiplexing library targeting 12,736 autophagy gene combinations with 247,032 paired gRNAs in viability and reporter-based enrichment screens. In the viability screen, we identify, among others, the synthetic lethal WDR45B-PIK3R4 and the proliferation-enhancing ATG7-KEAP1 genetic interactions. In the reporter-based screen, we identify over 1,570 essential genetic interactions for autophagy flux, including interactions among paralogous genes, namely ATG2A-ATG2B, GABARAP-MAP1LC3B and GABARAP-GABARAPL2. However, we only observe few genetic interactions within paralogous gene families of more than two members, indicating functional compensation between them. This work establishes 3Cs multiplexing as a platform for genetic interaction screens at scale.

Integrated cross-study datasets of genetic dependencies in cancer

CRISPR-Cas9 viability screens are increasingly performed at a genome-wide scale across large panels of cell lines to identify new therapeutic targets for precision cancer therapy. Integrating the datasets resulting from these studies is necessary to adequately represent the heterogeneity of human cancers and to assemble a comprehensive map of cancer genetic vulnerabilities. Here, we integrated the two largest public independent CRISPR-Cas9 screens performed to date (at the Broad and Sanger institutes) by assessing, comparing, and selecting methods for correcting biases due to heterogeneous single-guide RNA efficiency, gene-independent responses to CRISPR-Cas9 targeting originated from copy number alterations, and experimental batch effects. Our integrated datasets recapitulate findings from the individual datasets, provide greater statistical power to cancer- and subtype-specific analyses, unveil additional biomarkers of gene dependency, and improve the detection of common essential genes. We provide the largest integrated resources of CRISPR-Cas9 screens to date and the basis for harmonizing existing and future functional genetics datasets.