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Programmable C•G-to-G•C base editors (CGBEs) have broad scientific and therapeutic potential, but their editing outcomes have proved difficult to predict and their editing efficiency and product purity are often low. We describe a suite of engineered CGBEs paired with machine learning models to enable efficient, high-purity C•G-to-G•C base editing. We performed a CRISPR interference (CRISPRi) screen targeting DNA repair genes to identify factors that affect C•G-to-G•C editing outcomes and used these insights to develop CGBEs with diverse editing profiles. We characterized ten promising CGBEs on a library of 10,638 genomically integrated target sites in mammalian cells and trained machine learning models that accurately predict the purity and yield of editing outcomes (R = 0.90) using these data. These CGBEs enable correction to the wild-type coding sequence of 546 disease-related transversion single-nucleotide variants (SNVs) with >90% precision (mean 96%) and up to 70% efficiency (mean 14%). Computational prediction of optimal CGBE-single-guide RNA pairs enables high-purity transversion base editing at over fourfold more target sites than achieved using any single CGBE variant.

Expanding the human proteome Using mass spectrometry, ribosome profiling, and several CRISPR-based screens, Chen et al. identified hundreds of previously uncharacterized functional micropeptides in the human genome (see the Perspective by Wei and Guo). Protein translation outside of annotated open reading frames (ORFs) in messenger RNAs and within ORFs in long noncoding RNAs is pervasive. A functional screen using CRISPR-Cas9 with single-cell transcriptomics suggested critical roles for hundreds of micropeptides. Micropeptides encoded by multiple short, upstream ORFs form stable protein complexes with the downstream canonical proteins encoded on the same messenger RNAs. Science , this issue p. 1140 ; see also p. 1074

SUMMARYCells repair DNA double-strand breaks (DSBs) through a complex set of pathways that are critical for maintaining genomic integrity. Here we present Repair-seq, a high-throughput screening approach that measures the effects of thousands of genetic perturbations on the distribution of mutations introduced at targeted DNA lesions. Using Repair-seq, we profiled DSB repair outcomes induced by two programmable nucleases (Cas9 and Cas12a) after knockdown of 476 genes involved in DSB repair or associated processes in the presence or absence of oligonucleotides for homology-directed repair (HDR). The resulting data enabled principled, data-driven inference of DSB end joining and HDR pathways and demonstrated that repair outcomes with superficially similar sequence architectures can have markedly different genetic dependencies. Systematic interrogation of these dependencies then uncovered unexpected relationships among DSB repair genes and isolated incompletely characterized repair mechanisms. This work provides a foundation for understanding the complex pathways of DSB repair and for optimizing genome editing across modalities.

Cells repair DNA double-strand breaks (DSBs) through a complex set of pathways critical for maintaining genomic integrity. To systematically map these pathways, we developed a high-throughput screening approach called Repair-seq that measures the effects of thousands of genetic perturbations on mutations introduced at targeted DNA lesions. Using Repair-seq, we profiled DSB repair products induced by two programmable nucleases (Cas9 and Cas12a) in the presence or absence of oligonucleotides for homology-directed repair (HDR) after knockdown of 476 genes involved in DSB repair or associated processes. The resulting data enabled principled, data-driven inference of DSB end joining and HDR pathways. Systematic interrogation of this data uncovered unexpected relationships among DSB repair genes and demonstrated that repair outcomes with superficially similar sequence architectures can have markedly different genetic dependencies. This work provides a foundation for mapping the complex pathways of DSB repair and for optimizing genome editing across diverse modalities.

Genome editing is a method for making targeted sequence changes to the genomes of living cells. Prime editing, recently reported by Anzalone et al. (2019), is a new technology that uses reverse transcription to "write" programmed sequence changes into genomic DNA and thus promises significant technical advances.

Summary While prime editing enables precise sequence changes in DNA, cellular determinants of prime editing remain poorly understood. Using pooled CRISPRi screens, we discovered that DNA mismatch repair (MMR) impedes prime editing and promotes undesired indel byproducts. We developed PE4 and PE5 prime editing systems in which transient expression of an engineered MMR-inhibiting protein enhances the efficiency of substitution, small insertion, and small deletion prime edits by an average 7.7-fold and 2.0-fold compared to PE2 and PE3 systems, respectively, while improving edit/indel ratios by 3.4-fold in MMR-proficient cell types. Strategic installation of silent mutations near the intended edit can enhance prime editing outcomes by evading MMR. Prime editor protein optimization resulted in a PEmax architecture that enhances editing efficacy by 2.8-fold on average in HeLa cells. These findings enrich our understanding of prime editing and establish prime editing systems that show substantial improvement across 191 edits in seven mammalian cell types., Graphical abstract, Highlights • Pooled CRISPRi screens reveal that MMR inhibits prime editing efficiency and precision • PE4 and PE5 enhance editing outcomes through co-expression of dominant negative MLH1 • Programming additional silent mutations can enhance prime editing by evading MMR • PEmax editor improves prime editing efficacy in synergy with PE4, PE5, and epegRNAs, PE4 and PE5 are efficient and precise prime editing systems developed by leveraging insights into the way DNA repair pathways impact genome editing outcomes

Ontogeny describes the emergence of complex multicellular organisms from single totipotent cells. This field is particularly challenging in mammals, owing to the indeterminate relationship between self-renewal and differentiation, variation in progenitor field sizes, and internal gestation in these animals. Here we present a flexible, high-information, multi-channel molecular recorder with a single-cell readout and apply it as an evolving lineage tracer to assemble mouse cell-fate maps from fertilization through gastrulation. By combining lineage information with single-cell RNA sequencing profiles, we recapitulate canonical developmental relationships between different tissue types and reveal the nearly complete transcriptional convergence of endodermal cells of extra-embryonic and embryonic origins. Finally, we apply our cell-fate maps to estimate the number of embryonic progenitor cells and their degree of asymmetric partitioning during specification. Our approach enables massively parallel, high-resolution recording of lineage and other information in mammalian systems, which will facilitate the construction of a quantitative framework for understanding developmental processes.

Pairing CRISPR-based genetic screens with single-cell transcriptional phenotypes (Perturb-seq) has advanced efforts to explore the function of mammalian genes and genetic networks. We present strategies for Perturb-seq that enable direct capture of CRISPR sgRNAs within 3’ or 5’ single-cell RNA-sequencing libraries using the 10x Genomics platform. This technology greatly expands the accessibility, scalability, and flexibility of Perturb-seq, specifically enabling use with programmed combinatorial perturbations and multiplexing with multi-omic measurements.

Single-cell CRISPR screens enable the exploration of mammalian gene function and genetic regulatory networks. However, use of this technology has been limited by reliance on indirect indexing of single-guide RNAs (sgRNAs). Here we present direct-capture Perturb-seq, a versatile screening approach in which expressed sgRNAs are sequenced alongside single-cell transcriptomes. Direct-capture Perturb-seq enables detection of multiple distinct sgRNA sequences from individual cells and thus allows pooled single-cell CRISPR screens to be easily paired with combinatorial perturbation libraries that contain dual-guide expression vectors. We demonstrate the utility of this approach for high-throughput investigations of genetic interactions and, leveraging this ability, dissect epistatic interactions between cholesterol biogenesis and DNA repair. Using direct capture Perturb-seq, we also show that targeting individual genes with multiple sgRNAs per cell improves the efficacy of CRISPR interference and activation, facilitating the use of compact, highly active CRISPR libraries for single-cell screens. Last, we show that hybridization-based target enrichment permits sensitive, specific sequencing of informative transcripts from single-cell RNA-seq experiments.

Next-generation sequencing has yielded unprecedented insights into the mutational landscapes of cancer cells. The next challenge is to decipher the functional relevance of these mutations for cancer proliferation, metastasis and response to therapy. To tackle these questions, we have developed a versatile functional-genomics platform that overcomes issues that have plagued traditional approaches. Most recently, we have established two novel screening technologies based on the bacterial CRISPR/Cas9 system. In our CRISPRi approach, a catalytically dead version of Cas9 (dCas9) fused to a KRAB transcriptional repressor domain is targeted to specific DNA loci close to the transcription start site of endogenous genes to block transcription. Importantly, and in contrast to RNAi-based approaches, CRISPRi is highly specific and virtually lacks off-target effects. This specificity enabled us to construct more condensed genome-wide libraries. Importantly, CRISPRi proved to be non-toxic and reversible. We also developed an approach for targeted activation of endogenous genes, termed CRISPRa, in which dCas9 recruits an array of transcriptional activators to a transcription start site of interest. CRISPRi-based loss-of-function screens and CRISPRa-based gain-of-function screens yield rich, complementary insights into cellular pathways. In particular, drug resistance in cancer cells is commonly driven by gain-of-function events, which we can model using CRISPRa. In a pilot application, we identify genes whose expression levels control growth and survival of human leukemia cells. While primary genetic screens generate a list of hit genes, it commonly is challenging to elucidate the functional connections between these genes. Systematic, high-density mapping of genetic interactions is a powerful approach to elucidate functional pathways and reveal synthetic lethal / synthetic sick gene pairs, and has successfully been applied in microorganisms. We have developed a functional genomics platform that enables the parallel measurement of 100,000s of double-mutant phenotypes in mammalian cells for the construction of high-density genetic interaction maps. This platform reveals novel biological pathways in cancer cells and points to synthetic-lethal / synthetic-sick gene pairs, which can be exploited therapeutically. It also makes it possible to systematically uncover the accessible escape routes to targeted therapies, paving the way for rational design of combination therapies that pre-empt cancer drug resistance. Systematic comparison of genetic interactions between different growth conditions and genetic backgrounds can reveal context-specific rewiring of functional networks. We present the application of our platforms to identify adaptations and vulnerabilities in the stress response network of leukemia and multiple myeloma cells. Stress response pathways play important roles in cancer cell survival, drug resistance and tumor progression, and cancer cells are particularly dependent on such pathways. A prominent example of such non-oncogene addiction is the hypersensitivity of multiple myeloma cells to proteasome inhibition. We are applying our functional genomics platforms to understand the rewiring of genetic networks in myeloma cells that underlies this non-oncogene addiction and systematically characterize synthetic-lethal vulnerabilities that are potential new targets for combination therapies. Citation Format: Martin Kampmann, Diego Acosta-Alvear, Luke A. Gilbert, Max A. Horlbeck, Min Y. Cho, Britt Adamson, Jacqueline Villalta, Yuwen Chen, Peter Walter, Jonathan S. Weissman. Cancer-specific synthetic lethality and network rewiring elucidated by genetic interaction maps and CRISPR-based gain- and loss-of-function screens. [abstract]. In: Proceedings of the AACR Special Conference on Translation of the Cancer Genome; Feb 7-9, 2015; San Francisco, CA. Philadelphia (PA): AACR; Cancer Res 2015;75(22 Suppl 1):Abstract nr A2-56.

Understanding the emergence of complex multicellular organisms from single totipotent cells, or ontogenesis, represents a foundational question in biology. The study of mammalian development is particularly challenging due to the difficulty of monitoring embryosin utero, the variability of progenitor field sizes, and the indeterminate relationship between the generation of uncommitted progenitors and their progression to subsequent stages. Here, we present a flexible, high information, multi-channel molecular recorder with a single cell (sc) readout and apply it as an evolving lineage tracer to define a mouse cell fate map from fertilization through gastrulation. By combining lineage information with scRNA-seq profiles, we recapitulate canonical developmental relationships between different tissue types and reveal an unexpected transcriptional convergence of endodermal cells from extra-embryonic and embryonic origins, illustrating how lineage information complements scRNA-seq to define cell types. Finally, we apply our cell fate map to estimate the number of embryonic progenitor cells and the degree of asymmetric partitioning within the pluripotent epiblast during specification. Our approach enables massively parallel, high-resolution recording of lineage and other information in mammalian systems to facilitate a quantitative framework for describing developmental processes.

Seminal yeast studies have established the value of comprehensively mapping genetic interactions (GIs) for inferring gene function. Efforts in human cells using focused gene sets underscore the utility of this approach, but the feasibility of generating large-scale, diverse human GI maps remains unresolved. We developed a CRISPR interference platform for large-scale quantitative mapping of human GIs. We systematically perturbed 222,784 gene pairs in two cancer cell lines. The resultant maps cluster functionally related genes, assigning function to poorly characterized genes, including TMEM261, a new electron transport chain component. Individual GIs pinpoint unexpected relationships between pathways, exemplified by a specific cholesterol biosynthesis intermediate whose accumulation induces deoxynucleotide depletion, causing replicative DNA damage and a synthetic-lethal interaction with the ATR/9-1-1 DNA repair pathway. Our map provides a broad resource, establishes GI maps as a high-resolution tool for dissecting gene function, and serves as a blueprint for mapping the genetic landscape of human cells.

Perturb-seq is a platform for single-cell gene expression profiling of pooled CRISPR screens. Like many functional genomics platforms, Perturb-seq relies on lentiviral transduction to introduce perturbation libraries to cells. On this platform, these are barcoded sgRNA libraries. A critical consideration for performing Perturb-seq experiments is uncoupling of barcodes from linked sgRNA expression cassettes, which can occur during lentiviral transduction of co-packaged libraries due to reverse transcriptase-mediated template switching. This problem is common to lentiviral libraries designed with linked variable regions. Here, we demonstrate that recombination between Perturb-seq vectors scrambles linked variable regions separated by 2 kb. This predicts information loss in Perturb-seq screens performed with co-packaged libraries. We also demonstrate ways to address this problem and discuss best practices for single-cell screens with transcriptional readouts.

SummaryWhile the catalog of mammalian transcripts and their expression levels in different cell types and disease states is rapidly expanding, our understanding of transcript function lags behind. We present a robust technology enabling systematic investigation of the cellular consequences of repressing or inducing individual transcripts. We identify rules for specific targeting of transcriptional repressors (CRISPRi), typically achieving 90%–99% knockdown with minimal off-target effects, and activators (CRISPRa) to endogenous genes via endonuclease-deficient Cas9. Together they enable modulation of gene expression over a ∼1,000-fold range. Using these rules, we construct genome-scale CRISPRi and CRISPRa libraries, each of which we validate with two pooled screens. Growth-based screens identify essential genes, tumor suppressors, and regulators of differentiation. Screens for sensitivity to a cholera-diphtheria toxin provide broad insights into the mechanisms of pathogen entry, retrotranslocation and toxicity. Our results establish CRISPRi and CRISPRa as powerful tools that provide rich and complementary information for mapping complex pathways.

Genetic screens help infer gene function in mammalian cells, but it has remained difficult to assay complex phenotypes—such as transcriptional profiles—at scale. Here, we develop Perturb-seq, combining single-cell RNA sequencing (RNA-seq) and clustered regularly interspaced short palindromic repeats (CRISPR)-based perturbations to perform many such assays in a pool. We demonstrate Perturb-seq by analyzing 200,000 cells in immune cells and cell lines, focusing on transcription factors regulating the response of dendritic cells to lipopolysaccharide (LPS). Perturb-seq accurately identifies individual gene targets, gene signatures, and cell states affected by individual perturbations and their genetic interactions. We posit new functions for regulators of differentiation, the anti-viral response, and mitochondrial function during immune activation. By decomposing many high content measurements into the effects of perturbations, their interactions, and diverse cell metadata, Perturb-seq dramatically increases the scope of pooled genomic assays. Keywords: single-cell RNA-seq; pooled screen; CRISPR; epistasis; genetic interactions

Functional genomics efforts face tradeoffs between number of perturbations examined and complexity of phenotypes measured. We bridge this gap with Perturb-seq, which combines droplet-based single-cell RNA-seq with a strategy for barcoding CRISPR-mediated perturbations, allowing many perturbations to be profiled in pooled format. We applied Perturb-seq to dissect the mammalian unfolded protein response (UPR) using single and combinatorial CRISPR perturbations. Two genome-scale CRISPR interference (CRISPRi) screens identified genes whose repression perturbs ER homeostasis. Subjecting ∼100 hits to Perturb-seq enabled high-precision functional clustering of genes. Single-cell analyses decoupled the three UPR branches, revealed bifurcated UPR branch activation among cells subject to the same perturbation, and uncovered differential activation of the branches across hits, including an isolated feedback loop between the translocon and IRE1α. These studies provide insight into how the three sensors of ER homeostasis monitor distinct types of stress and highlight the ability of Perturb-seq to dissect complex cellular responses., National Human Genome Research Institute (U.S.) (Grant P50HG006193)

Completion of DNA replication after replication stress depends on PCNA, which undergoes monoubiquitination to stimulate direct bypass of DNA lesions by specialized DNA polymerases or is polyubiquitinated to promote recombination-dependent DNA synthesis across DNA lesions by template switching mechanisms. Here we report that the ZRANB3 translocase, a SNF2 family member related to the SIOD disorder SMARCAL1 protein, is recruited by polyubiquitinated PCNA to promote fork restart following replication arrest. ZRANB3 depletion in mammalian cells results in an increased frequency of sister chromatid exchange and DNA damage sensitivity after treatment with agents that cause replication stress. Using in vitro biochemical assays, we show that recombinant ZRANB3 remodels DNA structures mimicking stalled replication forks and disassembles recombination intermediates. We therefore propose that ZRANB3 maintains genomic stability at stalled or collapsed replication forks by facilitating fork restart and limiting inappropriate recombination that could occur during template switching events.

Drug resistance remains a pressing problem in cancer therapy. One major mode of resistance involves altered gene expression in the cancer cell. Knowing which genes can promote resistance or sensitivity to a specific cancer drug could pave the way for the development of new treatment strategies that minimize cancer drug resistance. Genome-scale loss-of-function and gain-of-function screens can be used to discover novel gene-drug interactions in cancer. RNAi and cDNA/ORF overexpression libraries have previously been used to conduct such screens, but both have drawbacks. RNAi has off-target effects, which can lead to false-positive results. cDNAs/ORFs are usually kilobases long and can be challenging to clone, verify and maintain in an overexpression library. Our recently developed CRISPR-based screening methods address these shortcomings. The technology combines different catalytically inactive Cas9 (dCas9) fusion proteins and uniquely designed short guide RNAs (sgRNA) allowing us to repress (CRISPRi) or activate (CRISPRa) the transcription of specific genes. CRISPRi uses KRAB, a repressive chromatin modifier domain, fused to dCas9. CRISPRa uses the sunCas9 system where a peptide epitope chain is fused to dCas9 and recruits multiple copies of VP64, a transcriptional activator, attached to an intracellular single-chain antibody directed against the epitope. The gene-specific region of sgRNAs is at most 25 bases, so with the help of massively parallel oligonucleotide synthesis and next-generation sequencing, we cloned and verified genome-scaled sgRNA libraries targeting 15,977 human protein-coding genes. When used for screening, we showed that CRISPRi has minimal off-target effects, one reason being that repression is highly sensitive to mismatches between sequences of the target DNA and the sgRNA. Citation Format: Luke A. Gilbert, Marvin E. Tanenbaum, Max A. Horlbeck, Britt Adamson, Jacqueline E. Villalta, Ronald D. Vale, Martin Kampmann, Jonathan S. Weissman. Using genome-scale CRISPR-mediated loss-of-function and gain-of-function screens to analyze gene-drug interactions in cancer. [abstract]. In: Proceedings of the AACR Special Conference on Translation of the Cancer Genome; Feb 7-9, 2015; San Francisco, CA. Philadelphia (PA): AACR; Cancer Res 2015;75(22 Suppl 1):Abstract nr PR05.

Repair of DNA double-strand breaks is critical to genomic stability and the prevention of developmental disorders and cancer. A central pathway for this repair is homologous recombination (HR). Most knowledge of HR is derived from work in prokaryotic and eukaryotic model organisms. We carried out a genome-wide siRNA-based screen in human cells. Among positive regulators of HR we identified networks of DNA-damage-response and pre-mRNA-processing proteins, and among negative regulators we identified a phosphatase network. Three candidate proteins localized to DNA lesions, including RBMX, a heterogeneous nuclear ribonucleoprotein that has a role in alternative splicing. RBMX accumulated at DNA lesions through multiple domains in a poly(ADP-ribose) polymerase 1-dependent manner and promoted HR by facilitating proper BRCA2 expression. Our screen also revealed that off-target depletion of RAD51 is a common source of RNAi false positives, raising a cautionary note for siRNA screens and RNAi-based studies of HR.