Multicenter integrated analysis of noncoding CRISPRi screens.

The ENCODE Consortium's efforts to annotate noncoding cis-regulatory elements (CREs) have advanced our understanding of gene regulatory landscapes. Pooled, noncoding CRISPR screens offer a systematic approach to investigate cis-regulatory mechanisms. The ENCODE4 Functional Characterization Centers conducted 108 screens in human cell lines, comprising >540,000 perturbations across 24.85 megabases of the genome. Using 332 functionally confirmed CRE-gene links in K562 cells, we established guidelines for screening endogenous noncoding elements with CRISPR interference (CRISPRi), including accurate detection of CREs that exhibit variable, often low, transcriptional effects. Benchmarking five screen analysis tools, we find that CASA produces the most conservative CRE calls and is robust to artifacts of low-specificity single guide RNAs. We uncover a subtle DNA strand bias for CRISPRi in transcribed regions with implications for screen design and analysis. Together, we provide an accessible data resource, predesigned single guide RNAs for targeting 3,275,697 ENCODE SCREEN candidate CREs with CRISPRi and screening guidelines to accelerate functional characterization of the noncoding genome.

Transcriptional and epigenetic regulators of human CD8+ T cell function identified through orthogonal CRISPR screens.

Clinical response to adoptive T cell therapies is associated with the transcriptional and epigenetic state of the cell product. Thus, discovery of regulators of T cell gene networks and their corresponding phenotypes has potential to improve T cell therapies. Here we developed pooled, epigenetic CRISPR screening approaches to systematically profile the effects of activating or repressing 120 transcriptional and epigenetic regulators on human CD8+ T cell state. We found that BATF3 overexpression promoted specific features of memory T cells and attenuated gene programs associated with cytotoxicity, regulatory T cell function, and exhaustion. Upon chronic antigen stimulation, BATF3 overexpression countered phenotypic and epigenetic signatures of T cell exhaustion. Moreover, BATF3 enhanced the potency of CAR T cells in both in vitro and in vivo tumor models and programmed a transcriptional profile that correlates with positive clinical response to adoptive T cell therapy. Finally, we performed CRISPR knockout screens that defined cofactors and downstream mediators of the BATF3 gene network.

Integrin α3 promotes TH17 cell polarization and extravasation during autoimmune neuroinflammation.

Multiple sclerosis (MS) is an autoimmune disease of the central nervous system (CNS) caused by CNS-infiltrating leukocytes, including TH17 cells that are critical mediators of disease pathogenesis. Although targeting leukocyte trafficking is effective in treating autoimmunity, there are currently no therapeutic interventions that specifically block encephalitogenic TH17 cell migration. Here, we report integrin α3 as a TH17 cell-selective determinant of pathogenicity in experimental autoimmune encephalomyelitis. CNS-infiltrating TH17 cells express high integrin α3, and its deletion in CD4+ T cells or Il17a fate-mapped cells attenuated disease severity. Mechanistically, integrin α3 enhanced the immunological synapse formation to promote the polarization and proliferation of TH17 cells. Moreover, the transmigration of TH17 cells into the CNS was dependent on integrin α3, and integrin α3 deficiency enhanced the retention of CD4+ T cells in the perivascular space of the blood-brain barrier. Integrin α3-dependent interactions continuously maintain TH17 cell identity and effector function. The requirement of integrin α3 in TH17 cell pathogenicity suggests integrin α3 as a therapeutic target for MS treatment.

Cooperative regulation of coupled oncoprotein synthesis and stability in triple-negative breast cancer by EGFR and CDK12/13.

Evidence has long suggested that epidermal growth factor receptor (EGFR) may play a prominent role in triple-negative breast cancer (TNBC) pathogenesis, but clinical trials of EGFR inhibitors have yielded disappointing results. Using a candidate drug screen, we identified that inhibition of cyclin-dependent kinases 12 and 13 (CDK12/13) dramatically sensitizes diverse models of TNBC to EGFR blockade. This combination therapy drives cell death through the 4E-BP1-dependent suppression of the translation and translation-linked turnover of driver oncoproteins, including MYC. A genome-wide CRISPR/Cas9 screen identified the CCR4-NOT complex as a major determinant of sensitivity to the combination therapy whose loss renders 4E-BP1 unresponsive to drug-induced dephosphorylation, thereby rescuing MYC translational suppression and promoting MYC stability. The central roles of CCR4-NOT and 4E-BP1 in response to the combination therapy were further underscored by the observation of CNOT1 loss and rescue of 4E-BP1 phosphorylation in TNBC cells that naturally evolved therapy resistance. Thus, pharmacological inhibition of CDK12/13 reveals a long-proposed EGFR dependence in TNBC that functions through the cooperative regulation of translation-coupled oncoprotein stability.

Orthogonal CRISPR screens to identify transcriptional and epigenetic regulators of human CD8 T cell function.

The clinical response to adoptive T cell therapies is strongly associated with transcriptional and epigenetic state. Thus, technologies to discover regulators of T cell gene networks and their corresponding phenotypes have great potential to improve the efficacy of T cell therapies. We developed pooled CRISPR screening approaches with compact epigenome editors to systematically profile the effects of activation and repression of 120 transcription factors and epigenetic modifiers on human CD8+ T cell state. These screens nominated known and novel regulators of T cell phenotypes with BATF3 emerging as a high confidence gene in both screens. We found that BATF3 overexpression promoted specific features of memory T cells such as increased IL7R expression and glycolytic capacity, while attenuating gene programs associated with cytotoxicity, regulatory T cell function, and T cell exhaustion. In the context of chronic antigen stimulation, BATF3 overexpression countered phenotypic and epigenetic signatures of T cell exhaustion. CAR T cells overexpressing BATF3 significantly outperformed control CAR T cells in both in vitro and in vivo tumor models. Moreover, we found that BATF3 programmed a transcriptional profile that correlated with positive clinical response to adoptive T cell therapy. Finally, we performed CRISPR knockout screens with and without BATF3 overexpression to define co-factors and downstream factors of BATF3, as well as other therapeutic targets. These screens pointed to a model where BATF3 interacts with JUNB and IRF4 to regulate gene expression and illuminated several other novel targets for further investigation.

Adaptive sequence divergence forged new neurodevelopmental enhancers in humans.

Searches for the genetic underpinnings of uniquely human traits have focused on human-specific divergence in conserved genomic regions, which reflects adaptive modifications of existing functional elements. However, the study of conserved regions excludes functional elements that descended from previously neutral regions. Here, we demonstrate that the fastest-evolved regions of the human genome, which we term "human ancestor quickly evolved regions" (HAQERs), rapidly diverged in an episodic burst of directional positive selection prior to the human-Neanderthal split, before transitioning to constraint within hominins. HAQERs are enriched for bivalent chromatin states, particularly in gastrointestinal and neurodevelopmental tissues, and genetic variants linked to neurodevelopmental disease. We developed a multiplex, single-cell in vivo enhancer assay to discover that rapid sequence divergence in HAQERs generated hominin-unique enhancers in the developing cerebral cortex. We propose that a lack of pleiotropic constraints and elevated mutation rates poised HAQERs for rapid adaptation and subsequent susceptibility to disease.

ZBTB7A promotes virus-host homeostasis during human coronavirus 229E infection.

The cellular fate after infection with human coronaviruses (HCoVs) is typically death. Previous data suggest, however, that the transcriptional state of an individual cell may sometimes allow additional outcomes of infection. Here, to probe the range of interactions a permissive cell type can have with a HCoV, we perform a CRISPR activation screen with HCoV-229E. The screen identified the transcription factor ZBTB7A, which strongly promotes cell survival after infection. Rather than suppressing viral infection, ZBTB7A upregulation allows the virus to induce a persistent infection and homeostatic state with the cell. We also find that control of oxidative stress is a primary driver of cellular survival during HCoV-229E infection. These data illustrate that, in addition to the nature of the infecting virus and the type of cell that it encounters, the cellular gene expression profile prior to infection can affect the eventual fate.

Profiling the quantitative occupancy of myriad transcription factors across conditions by modeling chromatin accessibility data.

Over a thousand different transcription factors (TFs) bind with varying occupancy across the human genome. Chromatin immunoprecipitation (ChIP) can assay occupancy genome-wide, but only one TF at a time, limiting our ability to comprehensively observe the TF occupancy landscape, let alone quantify how it changes across conditions. We developed TF occupancy profiler (TOP), a Bayesian hierarchical regression framework, to profile genome-wide quantitative occupancy of numerous TFs using data from a single chromatin accessibility experiment (DNase- or ATAC-seq). TOP is supervised, and its hierarchical structure allows it to predict the occupancy of any sequence-specific TF, even those never assayed with ChIP. We used TOP to profile the quantitative occupancy of hundreds of sequence-specific TFs at sites throughout the genome and examined how their occupancies changed in multiple contexts: in approximately 200 human cell types, through 12 h of exposure to different hormones, and across the genetic backgrounds of 70 individuals. TOP enables cost-effective exploration of quantitative changes in the landscape of TF binding.

Epigenome editing of the CFTR-locus for treatment of cystic fibrosis.

BACKGROUND: Mechanisms governing the diversity of CFTR gene expression throughout the body are complex. Multiple intronic and distal regulatory elements are responsible for regulating differential CFTR expression across tissues. METHODS: Drawing on published data, 18 high-priority genomic regions were identified and interrogated for CFTR-enhancer function using CRISPR/dCas9-based epigenome editing tools. Each region was evaluated by dCas9p300 and dCas9KRAB for its ability to enhance or repress CFTR expression, respectively. RESULTS: Multiple genomic regions were tested for enhancer activity using CRISPR/dCas9 epigenome editing. dCas9p300 mediates a significant increase in CFTR mRNA levels when targeted to the promoter and a region 44 kb upstream of the transcriptional start site in a CFTR-low expressing cell line. Multiple gRNAs targeting the promoter induced a robust increase in CFTR protein levels. In contrast, dCas9KRAB-mediated repression is much more robust with 10 of the 18 evaluated genomic regions inducing CFTR protein knockdown. To evaluate the therapeutic efficacy of modulating CFTR gene regulation, dCas9p300 was used to induce elevated levels of CFTR from the endogenous locus in ΔF508/ΔF508 human bronchial epithelial cells. Ussing chamber studies demonstrated a synergistic increase in ion transport in response to CRISPR-induced expression of ΔF508 CFTR mRNA along with VX809 treatment. CONCLUSIONS: CRISPR/dCas9-based epigenome-editing provides a previously unexplored tool for interrogating CFTR enhancer function. Here, we demonstrate that therapeutic interventions that increase the expression of CFTR may improve the efficacy of CFTR modulators. A better understanding CFTR regulatory mechanisms could uncover novel therapeutic interventions for the development of cystic fibrosis therapies.

Transgenic mice for in vivo epigenome editing with CRISPR-based systems.

CRISPR-Cas9 technologies have dramatically increased the ease of targeting DNA sequences in the genomes of living systems. The fusion of chromatin-modifying domains to nuclease-deactivated Cas9 (dCas9) has enabled targeted epigenome editing in both cultured cells and animal models. However, delivering large dCas9 fusion proteins to target cells and tissues is an obstacle to the widespread adoption of these tools for in vivo studies. Here, we describe the generation and characterization of two conditional transgenic mouse lines for epigenome editing, Rosa26:LSL-dCas9-p300 for gene activation and Rosa26:LSL-dCas9-KRAB for gene repression. By targeting the guide RNAs to transcriptional start sites or distal enhancer elements, we demonstrate regulation of target genes and corresponding changes to epigenetic states and downstream phenotypes in the brain and liver in vivo, and in T cells and fibroblasts ex vivo. These mouse lines are convenient and valuable tools for facile, temporally controlled, and tissue-restricted epigenome editing and manipulation of gene expression in vivo.

Targeted long-read sequencing identifies missing disease-causing variation.

Despite widespread clinical genetic testing, many individuals with suspected genetic conditions lack a precise diagnosis, limiting their opportunity to take advantage of state-of-the-art treatments. In some cases, testing reveals difficult-to-evaluate structural differences, candidate variants that do not fully explain the phenotype, single pathogenic variants in recessive disorders, or no variants in genes of interest. Thus, there is a need for better tools to identify a precise genetic diagnosis in individuals when conventional testing approaches have been exhausted. We performed targeted long-read sequencing (T-LRS) using adaptive sampling on the Oxford Nanopore platform on 40 individuals, 10 of whom lacked a complete molecular diagnosis. We computationally targeted up to 151 Mbp of sequence per individual and searched for pathogenic substitutions, structural variants, and methylation differences using a single data source. We detected all genomic aberrations-including single-nucleotide variants, copy number changes, repeat expansions, and methylation differences-identified by prior clinical testing. In 8/8 individuals with complex structural rearrangements, T-LRS enabled more precise resolution of the mutation, leading to changes in clinical management in one case. In ten individuals with suspected Mendelian conditions lacking a precise genetic diagnosis, T-LRS identified pathogenic or likely pathogenic variants in six and variants of uncertain significance in two others. T-LRS accurately identifies pathogenic structural variants, resolves complex rearrangements, and identifies Mendelian variants not detected by other technologies. T-LRS represents an efficient and cost-effective strategy to evaluate high-priority genes and regions or complex clinical testing results.

AP-1 subunits converge promiscuously at enhancers to potentiate transcription.

The AP-1 transcription factor (TF) dimer contributes to many biological processes and environmental responses. AP-1 can be composed of many interchangeable subunits. Unambiguously determining the binding locations of these subunits in the human genome is challenging because of variable antibody specificity and affinity. Here, we definitively establish the genome-wide binding patterns of five AP-1 subunits by using CRISPR to introduce a common antibody tag on each subunit. We find limited evidence for strong dimerization preferences between subunits at steady state and find that, under a stimulus, dimerization patterns reflect changes in the transcriptome. Further, our analysis suggests that canonical AP-1 motifs indiscriminately recruit all AP-1 subunits to genomic sites, which we term AP-1 hotspots. We find that AP-1 hotspots are predictive of cell type-specific gene expression and of genomic responses to glucocorticoid signaling (more so than super-enhancers) and are significantly enriched in disease-associated genetic variants. Together, these results support a model where promiscuous binding of many AP-1 subunits to the same genomic location play a key role in regulating cell type-specific gene expression and environmental responses.

Correcting signal biases and detecting regulatory elements in STARR-seq data.

High-throughput reporter assays such as self-transcribing active regulatory region sequencing (STARR-seq) have made it possible to measure regulatory element activity across the entire human genome at once. The resulting data, however, present substantial analytical challenges. Here, we identify technical biases that explain most of the variance in STARR-seq data. We then develop a statistical model to correct those biases and to improve detection of regulatory elements. This approach substantially improves precision and recall over current methods, improves detection of both activating and repressive regulatory elements, and controls for false discoveries despite strong local correlations in signal.

Causal network inference from gene transcriptional time-series response to glucocorticoids.

Gene regulatory network inference is essential to uncover complex relationships among gene pathways and inform downstream experiments, ultimately enabling regulatory network re-engineering. Network inference from transcriptional time-series data requires accurate, interpretable, and efficient determination of causal relationships among thousands of genes. Here, we develop Bootstrap Elastic net regression from Time Series (BETS), a statistical framework based on Granger causality for the recovery of a directed gene network from transcriptional time-series data. BETS uses elastic net regression and stability selection from bootstrapped samples to infer causal relationships among genes. BETS is highly parallelized, enabling efficient analysis of large transcriptional data sets. We show competitive accuracy on a community benchmark, the DREAM4 100-gene network inference challenge, where BETS is one of the fastest among methods of similar performance and additionally infers whether causal effects are activating or inhibitory. We apply BETS to transcriptional time-series data of differentially-expressed genes from A549 cells exposed to glucocorticoids over a period of 12 hours. We identify a network of 2768 genes and 31,945 directed edges (FDR ≤ 0.2). We validate inferred causal network edges using two external data sources: Overexpression experiments on the same glucocorticoid system, and genetic variants associated with inferred edges in primary lung tissue in the Genotype-Tissue Expression (GTEx) v6 project. BETS is available as an open source software package at https://github.com/lujonathanh/BETS.

Master Regulators and Cofactors of Human Neuronal Cell Fate Specification Identified by CRISPR Gene Activation Screens.

Technologies to reprogram cell-type specification have revolutionized the fields of regenerative medicine and disease modeling. Currently, the selection of fate-determining factors for cell reprogramming applications is typically a laborious and low-throughput process. Therefore, we use high-throughput pooled CRISPR activation (CRISPRa) screens to systematically map human neuronal cell fate regulators. We utilize deactivated Cas9 (dCas9)-based gene activation to target 1,496 putative transcription factors (TFs) in the human genome. Using a reporter of neuronal commitment, we profile the neurogenic activity of these factors in human pluripotent stem cells (PSCs), leading to a curated set of pro-neuronal factors. Activation of pairs of TFs reveals neuronal cofactors, including E2F7, RUNX3, and LHX8, that improve conversion efficiency, subtype specificity, and maturation of neuronal cell types. Finally, using multiplexed gene regulation with orthogonal CRISPR systems, we demonstrate improved neuronal differentiation with concurrent activation and repression of target genes, underscoring the power of CRISPR-based gene regulation for programming complex cellular phenotypes.

Transcriptome and regulatory maps of decidua-derived stromal cells inform gene discovery in preterm birth.

While a genetic component of preterm birth (PTB) has long been recognized and recently mapped by genome-wide association studies (GWASs), the molecular determinants underlying PTB remain elusive. This stems in part from an incomplete availability of functional genomic annotations in human cell types relevant to pregnancy and PTB. We generated transcriptome (RNA-seq), epigenome (ChIP-seq of H3K27ac, H3K4me1, and H3K4me3 histone modifications), open chromatin (ATAC-seq), and chromatin interaction (promoter capture Hi-C) annotations of cultured primary decidua-derived mesenchymal stromal/stem cells and in vitro differentiated decidual stromal cells and developed a computational framework to integrate these functional annotations with results from a GWAS of gestational duration in 56,384 women. Using these resources, we uncovered additional loci associated with gestational duration and target genes of associated loci. Our strategy illustrates how functional annotations in pregnancy-relevant cell types aid in the experimental follow-up of GWAS for PTB and, likely, other pregnancy-related conditions.

Functional Genomics of Healthy and Pathological Fetal Membranes.

Premature preterm rupture of membranes (PPROM), rupture of fetal membranes before 37 weeks of gestation, is the leading identifiable cause of spontaneous preterm births. Often there is no obvious cause that is identified in a patient who presents with PPROM. Identifying the upstream molecular events that lead to fetal membrane weakening presents potentially actionable mechanisms which could lead to the identification of at-risk patients and to the development of new therapeutic interventions. Functional genomic studies have transformed understanding of the role of gene regulation in diverse cells and tissues involved health and disease. Here, we review the results of those studies in the context of fetal membranes. We will highlight relevant results from major coordinated functional genomics efforts and from targeted studies focused on individual cell or tissue models. Studies comparing gene expression and DNA methylation between healthy and pathological fetal membranes have found differential regulation between labor and quiescent tissue as well as in preterm births, preeclampsia, and recurrent pregnancy loss. Whole genome and exome sequencing studies have identified common and rare fetal variants associated with preterm births. However, few fetal membrane tissue studies have modeled the response to stimuli relevant to pregnancy. Fetal membranes are readily adaptable to cell culture and relevant cellular phenotypes are readily observable. For these reasons, this is now an unrealized opportunity for genomic studies isolating the effect of cell signaling cascades and mapping the fetal membrane responses that lead to PPROM and other pregnancy complications.

c-Maf regulates the plasticity of group 3 innate lymphoid cells by restraining the type 1 program.

CCR6- group 3 innate lymphoid cells (ILC3s) are mediators of intestinal immunity and barrier function that possess the capacity to acquire type 1 effector features and fully convert into ILC1s. The molecular mechanisms governing such plasticity are undefined. Here, we identified c-Maf as an essential regulator of ILC3 homeostasis and plasticity that limits physiological ILC1 conversion. Phenotypic analysis of effector status in Maf-deficient CCR6- ILC3s, coupled with evaluation of global changes in transcriptome, chromatin accessibility, and transcription factor motif enrichment, revealed that c-Maf enforces ILC3 identity. c-Maf promoted ILC3 accessibility and supported RORγt activity and expression of type 3 effector genes. Conversely, c-Maf antagonized type 1 programming, largely through restraint of T-bet expression and function. Mapping of the dynamic changes in chromatin landscape accompanying CCR6- ILC3 development and ILC1 conversion solidified c-Maf as a gatekeeper of type 1 regulatory transformation and a controller of ILC3 fate.

Bayesian estimation of genetic regulatory effects in high-throughput reporter assays.

MOTIVATION: High-throughput reporter assays dramatically improve our ability to assign function to noncoding genetic variants, by measuring allelic effects on gene expression in the controlled setting of a reporter gene. Unlike genetic association tests, such assays are not confounded by linkage disequilibrium when loci are independently assayed. These methods can thus improve the identification of causal disease mutations. While work continues on improving experimental aspects of these assays, less effort has gone into developing methods for assessing the statistical significance of assay results, particularly in the case of rare variants captured from patient DNA. RESULTS: We describe a Bayesian hierarchical model, called Bayesian Inference of Regulatory Differences, which integrates prior information and explicitly accounts for variability between experimental replicates. The model produces substantially more accurate predictions than existing methods when allele frequencies are low, which is of clear advantage in the search for disease-causing variants in DNA captured from patient cohorts. Using the model, we demonstrate a clear tradeoff between variant sequencing coverage and numbers of biological replicates, and we show that the use of additional biological replicates decreases variance in estimates of effect size, due to the properties of the Poisson-binomial distribution. We also provide a power and sample size calculator, which facilitates decision making in experimental design parameters. AVAILABILITY AND IMPLEMENTATION: The software is freely available from www.geneprediction.org/bird. The experimental design web tool can be accessed at http://67.159.92.22:8080. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Targeted transcriptional modulation with type I CRISPR-Cas systems in human cells.

Class 2 CRISPR-Cas systems, such as Cas9 and Cas12, have been widely used to target DNA sequences in eukaryotic genomes. However, class 1 CRISPR-Cas systems, which represent about 90% of all CRISPR systems in nature, remain largely unexplored for genome engineering applications. Here, we show that class 1 CRISPR-Cas systems can be expressed in mammalian cells and used for DNA targeting and transcriptional control. We repurpose type I variants of class 1 CRISPR-Cas systems from Escherichia coli and Listeria monocytogenes, which target DNA via a multi-component RNA-guided complex termed Cascade. We validate Cascade expression, complex formation and nuclear localization in human cells, and demonstrate programmable CRISPR RNA (crRNA)-mediated targeting of specific loci in the human genome. By tethering activation and repression domains to Cascade, we modulate the expression of targeted endogenous genes in human cells. This study demonstrates the use of Cascade as a CRISPR-based technology for targeted eukaryotic gene regulation, highlighting class 1 CRISPR-Cas systems for further exploration.