Mitigation of off-target toxicity in CRISPR-Cas9 screens for essential non-coding elements.

Pooled CRISPR-Cas9 screens are a powerful method for functionally characterizing regulatory elements in the non-coding genome, but off-target effects in these experiments have not been systematically evaluated. Here, we investigate Cas9, dCas9, and CRISPRi/a off-target activity in screens for essential regulatory elements. The sgRNAs with the largest effects in genome-scale screens for essential CTCF loop anchors in K562 cells were not single guide RNAs (sgRNAs) that disrupted gene expression near the on-target CTCF anchor. Rather, these sgRNAs had high off-target activity that, while only weakly correlated with absolute off-target site number, could be predicted by the recently developed GuideScan specificity score. Screens conducted in parallel with CRISPRi/a, which do not induce double-stranded DNA breaks, revealed that a distinct set of off-targets also cause strong confounding fitness effects with these epigenome-editing tools. Promisingly, filtering of CRISPRi libraries using GuideScan specificity scores removed these confounded sgRNAs and enabled identification of essential regulatory elements

BIASES AND BLIND-SPOTS IN GENOME-WIDE CRISPR-CAS9 KNOCKOUT SCREENS

Adaptation of the bacterial CRISPR-Cas9 system to mammalian cells revolutionized the field of functional genomics, enabling genome-scale genetic perturbations to study essential genes, whose loss of function results in a severe fitness defect. There are two types of essential genes in a cell. Core essential genes are absolutely required for growth and proliferation in every cell type. On the other hand, context-dependent essential genes become essential in an environmental or genetic context. The concept of context-dependent gene essentiality is particularly important in cancer, since killing cancer cells selectively without harming surrounding healthy tissue remains a major challenge. The toxicity of traditional cancer treatment protocols to the normal cells stresses the need for new strategies that can identify and address the weaknesses specific to cancer cells. Studies showed that CRISPR monogenic knockout screens can identify specific processes that cells rely on for growth and proliferation, which is a crucial step in identifying candidate cancer-specific therapeutic targets. While it is widely accepted that CRISPR screening is both more specific and more sensitive than previously established methods, the limitations of this technology have not been systematically investigated. In this dissertation, through several lines of integrated analysis of CRISPR screen data in cancer cell lines from the Cancer Dependency Map initiative, I will describe several computational approaches to demonstrate that CRISPR screens are not saturating. In fact, a typical screen has a ~20% false-negative rate, saturating coverage requires multiple repeats and false negatives are more prevalent among moderately expressed genes. I will then introduce a solution to the false negative problem and describe another method that provides a cleaner analysis of the data, rescuing the false negatives observed in these screens. Moreover, I will show that half of all constitutively expressed genes are never observed as essential in any CRISPR screen. Notably, these never-essentials are highly enriched for paralogs, suggesting that functional redundancy masks the detection of a substantial number of genes. Finally, I will describe our efforts to investigate functional buffering among approximately 400 candidate paralog pairs using CRISPR/enCas12a dual-gene knockout screening technology and discuss the paralog synthetic lethal interactions that we have identified, which have escaped detection in monogenic CRISPR-Cas9 knockout screens. Collectively, these observations reveal significant biases and blind-spots in the analysis of CRISPR-based functional genomics approaches and offer new opportunities for the discovery of novel candidate drug targets

A CRISPR-based screen for Hedgehog signaling provides insights into ciliary function and ciliopathies.

Primary cilia organize Hedgehog signaling and shape embryonic development, and their dysregulation is the unifying cause of ciliopathies. We conducted a functional genomic screen for Hedgehog signaling by engineering antibiotic-based selection of Hedgehog-responsive cells and applying genome-wide CRISPR-mediated gene disruption. The screen can robustly identify factors required for ciliary signaling with few false positives or false negatives. Characterization of hit genes uncovered novel components of several ciliary structures, including a protein complex that contains δ-tubulin and ε-tubulin and is required for centriole maintenance. The screen also provides an unbiased tool for classifying ciliopathies and showed that many congenital heart disorders are caused by loss of ciliary signaling. Collectively, our study enables a systematic analysis of ciliary function and of ciliopathies, and also defines a versatile platform for dissecting signaling pathways through CRISPR-based screening

Genome-scale analysis identifies paralog lethality as a vulnerability of chromosome 1p loss in cancer.

Functional redundancy shared by paralog genes may afford protection against genetic perturbations, but it can also result in genetic vulnerabilities due to mutual interdependency1-5. Here, we surveyed genome-scale short hairpin RNA and CRISPR screening data on hundreds of cancer cell lines and identified MAGOH and MAGOHB, core members of the splicing-dependent exon junction complex, as top-ranked paralog dependencies6-8. MAGOHB is the top gene dependency in cells with hemizygous MAGOH deletion, a pervasive genetic event that frequently occurs due to chromosome 1p loss. Inhibition of MAGOHB in a MAGOH-deleted context compromises viability by globally perturbing alternative splicing and RNA surveillance. Dependency on IPO13, an importin-β receptor that mediates nuclear import of the MAGOH/B-Y14 heterodimer9, is highly correlated with dependency on both MAGOH and MAGOHB. Both MAGOHB and IPO13 represent dependencies in murine xenografts with hemizygous MAGOH deletion. Our results identify MAGOH and MAGOHB as reciprocal paralog dependencies across cancer types and suggest a rationale for targeting the MAGOHB-IPO13 axis in cancers with chromosome 1p deletion

Agreement between two large pan-cancer CRISPR-Cas9 gene dependency data sets.

Genome-scale CRISPR-Cas9 viability screens performed in cancer cell lines provide a systematic approach to identify cancer dependencies and new therapeutic targets. As multiple large-scale screens become available, a formal assessment of the reproducibility of these experiments becomes necessary. We analyze data from recently published pan-cancer CRISPR-Cas9 screens performed at the Broad and Sanger Institutes. Despite significant differences in experimental protocols and reagents, we find that the screen results are highly concordant across multiple metrics with both common and specific dependencies jointly identified across the two studies. Furthermore, robust biomarkers of gene dependency found in one data set are recovered in the other. Through further analysis and replication experiments at each institute, we show that batch effects are driven principally by two key experimental parameters: the reagent library and the assay length. These results indicate that the Broad and Sanger CRISPR-Cas9 viability screens yield robust and reproducible findings

Application of CRISPR/Cas9 screening to study cancer drivers and to identify novel cancer vulnerabilities

The development of targeted therapies has had a significant impact on cancer survival rates. However, targeting cancers that are driven by loss of tumour suppressor genes remains a major challenge. One promising approach to treat these cancers is the exploitation of synthetic lethal interactions. Synthetic lethality describes an interaction between two genes, where loss of one gene alone does not affect viability but loss of both genes induces cell death. Inhibiting the synthetic lethal partner of a tumour suppressor gene should specifically kill tumour cells, and so these represent potential therapeutic targets. However, very few synthetic lethal interactions have been well-established. The aim of this project was to systematically screen for synthetic lethal partners of known tumour suppressor genes. To do so, isogenic human induced pluripotent stem cell lines were generated, each carrying a loss-of-function mutation in a single tumour suppressor gene. These cells have a normal genetic background, thus making it simpler to accurately identify interactions. CRISPR/Cas9 technology was applied as it allows for large-scale, unbiased screening of genetic interactions. A genome-wide guide RNA library was prepared and implemented for knockout screening in the isogenic cell line panel. Analysis was performed to identify genes that were specifically essential for cell fitness/survival in the mutant lines. Particular focus was placed on four tumour suppressor genes that encode subunits of the PBAF/BAF complexes. Approximately 20% of human cancers harbour mutations in subunits of these complexes, so identifying dependencies associated with these could have broad therapeutic potential. Candidate synthetic lethal interactions with these genes were investigated using low-throughput assays in the stem cells and in a cancer cell line. The data obtained suggests that screening in stem cells produces highly variable results. Although potential vulnerabilities associated with all of the tumour suppressor genes were identified, further work is required to validate these and to assess the quality of the results. In addition to genome editing, CRISPR/Cas9 has been adapted as a tool for controlling gene regulation. In collaboration with Dr Louise van der Weyden, I applied this technology to address another challenging area of cancer biology. Metastasis is the main cause of cancer mortality, yet we still have a poor understanding of the genes that control this process. Considering this, an in vivo CRISPR activation screen was performed to identify novel drivers of metastatic colonisation. A mouse melanoma cell line was transduced in vitro with a library designed to up-regulate expression of membrane proteins, which represent ideal drug targets. These cells were then used in an in vivo experimental metastasis assay. Enrichment of guide RNAs in the lungs was assessed to identify genes that increased pulmonary metastatic colonisation when activated. Candidate genes were selected using three analysis strategies, and hits from each were tested. Several genes were successfully validated using the experimental metastasis assay. The most robust hit was studied further to explore its potential as a therapeutic target. Collectively, the work described in this thesis demonstrates how CRISPR/Cas9 screening can be applied in different model systems to study genes that drive cancer and to explore novel therapeutic strategies.I was funded by the Wellcome Sanger Institute and the MRC

Genome-Scale CRISPR Screens Identify Human Pluripotency-Specific Genes

Human pluripotent stem cells (hPSCs) generate a variety of disease-relevant cells that can be used to improve the translation of preclinical research. Despite the potential of hPSCs, their use for genetic screening has been limited by technical challenges. We developed a scalable and renewable Cas9 and sgRNA-hPSC library in which loss-of-function mutations can be induced at will. Our inducible mutant hPSC library can be used for multiple genome-wide CRISPR screens in a variety of hPSC-induced cell types. As proof of concept, we performed three screens for regulators of properties fundamental to hPSCs: their ability to self-renew and/or survive (fitness), their inability to survive as single-cell clones, and their capacity to differentiate. We identified the majority of known genes and pathways involved in these processes, as well as a plethora of genes with unidentified roles. This resource will increase the understanding of human development and genetics. This approach will be a powerful tool to identify disease-modifying genes and pathways

A novel bioinformatic approach for comprehensive genome scale analysis identifies key regulators of macrophage activation.

The initiation of inflammatory cytokine transcription by bacterial ligands is a central mechanism by which the immune system activates its first line of defense. Macrophage activation by the Toll-like Receptor 4 (TLR4) pathway is initiated with receptor binding of lipopolysaccharides (LPS) and culminates in a large-scale transcriptional response of the inflammatory gene program. Advancements in genome-wide screening technologies have made it possible to interrogate the regulatory landscape of signaling pathways such as those activated by TLR4. Utilizing these high-throughput methods for the comprehensive characterization of pathway components, particularly for regulators that are involved in critical cellular processes such as transcription and translation, however, requires an approach that goes beyond the top scoring and previously characterized hits of genome-scale studies. To address this challenge, I developed the Throughput Ranking by Iterative Analysis of Genomic Enrichment (TRIAGE) method, a bioinformatic analysis model that facilitates the comprehensive identification of likely regulators by iterative sampling of pathway and network databases. I validated the TRIAGE approach by analyzing three previously published genome-wide studies of regulators of early HIV infection and viral transcription. Analysis by TRIAGE showed significantly increased overlap and identified shared novel targets across the three studies. I further developed the TRIAGE analysis method as a globally accessible web-based resource. Applying TRIAGE analysis to three genome-scale studies of LPS treatment in macrophages of mouse and human cell lines, I identified an enrichment for regulators relating to alternative splicing and protein degradation. Using short read and long read RNA-seq of ligand-stimulated macrophages I further characterized the broad transcriptional variation induced by the LPS response and the novel and known transcript variants that define different macrophage activation states. These findings define an approach for comprehensive unbiased discovery of signaling pathway regulators from genome-scale datasets and suggest a model of macrophage activation involving proteasomal removal of negative regulators and remodeling of the macrophage state via a transcriptional shift in splice variant dynamics

Identification and functional characterisation of gene fusions in human cancer cell lines

Advances in next-generation sequencing have accelerated the rate at which novel gene fusions are discovered. The discovery of gene fusions such as EML4-ALK in lung cancer and BCR-ABL1 in chronic myeloid leukaemia have already led to changes in clinical care. However, important questions remain about the role of gene fusions in promoting oncogenic phenotypes and their relevance in drug response. In this study, I combine RNA sequencing, CRISPR/Cas9 screens and high-throughput drug sensitivity data in a panel of 1,011 human cancer cell lines across 42 tissue types to examine the occurrence and functional relevance of gene fusions in cancer. Fusions were called using three algorithms and filtered to reveal 8,354 fusion events with a validation rate of 70%. Cell lines exhibit known fusions in their corresponding tissue types as well as a large number of putative passenger events and fusion recurrence across tissue types correlates with that found in patient samples. The panel of 1,011 cell lines has previously undergone high-throughput drug screening of 409 drug compounds. I implemented a systematic analysis to identify associations between fusion occurrence and drug response. It reliably recapitulates known associations (e.g. BCR-ABL1 and sensitivity to ABL inhibitors). However, the number of novel findings is low, likely due to the low numbers of recurrent fusions, a lack of prior knowledge of novel gene fusions as well as a narrow range of drug targets. Next, I developed a computational approach using whole-genome CRISPR/Cas9 screening data for 339 cell lines. It utilises CRISPR/Cas9 data on a guide-level to systematically evaluate essentiality of novel gene fusions. My analysis predicts essentiality of known gene fusions with high accuracy and provides evidence for the oncogenic relevance of novel gene fusions. A gene fusions in YAP1-MAML2 represents a particularly interesting finding showing functionality across multiple distinct cancer types. Altogether, in my thesis, I demonstrate that innovative computational approaches leveraging new datasets can enable us to elucidate the functionality of rare gene fusions in human cancer. These types of discoveries may aid in the development of targeted therapies and supports the use of clinical basket trials to capture cancer events across multiple tissue types.Full funding provided jointly by Wellcome Trust and MR