CRISPR Screening Uncovers a Long-Range Enhancer for ONECUT1 in Pancreatic Differentiation and Links a Diabetes Risk Variant.

Functional enhancer annotation is a valuable first step for understanding tissue-specific transcriptional regulation and prioritizing disease-associated non-coding variants for investigation. However, unbiased enhancer discovery in physiologically relevant contexts remains a major challenge. To discover regulatory elements pertinent to diabetes, we conducted a CRISPR interference (CRISPRi) screen in the human pluripotent stem cell (hPSC) pancreatic differentiation system. Among the enhancers uncovered, we focused on a long-range enhancer ∼664 kb from the ONECUT1 promoter, as coding mutations in ONECUT1 cause pancreatic hypoplasia and neonatal diabetes. Homozygous enhancer deletion in hPSCs was associated with a near-complete loss of ONECUT1 gene expression and compromised pancreatic differentiation. This enhancer contains a confidently fine-mapped type 2 diabetes (T2D) associated variant (rs528350911) which disrupts a GATA motif. Introduction of the risk variant into hPSCs revealed substantially reduced binding of key pancreatic transcription factors (GATA4, GATA6 and FOXA2) on the edited allele, accompanied by a slight reduction of ONECUT1 transcription, supporting a causal role for this risk variant in metabolic disease. This work expands our knowledge about transcriptional regulation in pancreatic development through the characterization of a long-range enhancer and highlights the utility of enhancer discovery in disease-relevant settings for understanding monogenic and complex disease.

Scalable and unbiased sequence-informed embedding of single-cell ATAC-seq data with CellSpace.

Standard scATAC sequencing (scATAC-seq) analysis pipelines represent cells as sparse numeric vectors relative to an atlas of peaks or genomic tiles and consequently ignore genomic sequence information at accessible loci. Here we present CellSpace, an efficient and scalable sequence-informed embedding algorithm for scATAC-seq that learns a mapping of DNA k-mers and cells to the same space, to address this limitation. We show that CellSpace captures meaningful latent structure in scATAC-seq datasets, including cell subpopulations and developmental hierarchies, and can score transcription factor activities in single cells based on proximity to binding motifs embedded in the same space. Importantly, CellSpace implicitly mitigates batch effects arising from multiple samples, donors or assays, even when individual datasets are processed relative to different peak atlases. Thus, CellSpace provides a powerful tool for integrating and interpreting large-scale scATAC-seq compendia.

ERG activates a stem-like proliferation-differentiation program in prostate epithelial cells with mixed basal-luminal identity.

To gain insight into how ERG translocations cause prostate cancer, we performed single cell transcriptional profiling of an autochthonous mouse model at an early stage of disease initiation. Despite broad expression of ERG in all prostate epithelial cells, proliferation was enriched in a small, stem-like population with mixed-luminal basal identity (called intermediate cells). Through a series of lineage tracing and primary prostate tissue transplantation experiments, we find that tumor initiating activity resides in a subpopulation of basal cells that co-express the luminal genes Tmprss2 and Nkx3.1 (called BasalLum) but not in the larger population of classical Krt8+ luminal cells. Upon ERG activation, BasalLum cells give rise to the highly proliferative intermediate state, which subsequently transitions to the larger population of Krt8+ luminal cells characteristic of ERG-positive human cancers. Furthermore, this proliferative population is characterized by an ERG-specific chromatin state enriched for NFkB, AP-1, STAT and NFAT binding, with implications for TF cooperativity. The fact that the proliferative potential of ERG is enriched in a small stem-like population implicates the chromatin context of these cells as a critical variable for unmasking its oncogenic activity.

Single-cell multi-ome regression models identify functional and disease-associated enhancers and enable chromatin potential analysis.

We present a gene-level regulatory model, single-cell ATAC + RNA linking (SCARlink), which predicts single-cell gene expression and links enhancers to target genes using multi-ome (scRNA-seq and scATAC-seq co-assay) sequencing data. The approach uses regularized Poisson regression on tile-level accessibility data to jointly model all regulatory effects at a gene locus, avoiding the limitations of pairwise gene-peak correlations and dependence on peak calling. SCARlink outperformed existing gene scoring methods for imputing gene expression from chromatin accessibility across high-coverage multi-ome datasets while giving comparable to improved performance on low-coverage datasets. Shapley value analysis on trained models identified cell-type-specific gene enhancers that are validated by promoter capture Hi-C and are 11× to 15× and 5× to 12× enriched in fine-mapped eQTLs and fine-mapped genome-wide association study (GWAS) variants, respectively. We further show that SCARlink-predicted and observed gene expression vectors provide a robust way to compute a chromatin potential vector field to enable developmental trajectory analysis.

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.

An epigenetic barrier sets the timing of human neuronal maturation.

The pace of human brain development is highly protracted compared with most other species1-7. The maturation of cortical neurons is particularly slow, taking months to years to develop adult functions3-5. Remarkably, such protracted timing is retained in cortical neurons derived from human pluripotent stem cells (hPSCs) during in vitro differentiation or upon transplantation into the mouse brain4,8,9. Those findings suggest the presence of a cell-intrinsic clock setting the pace of neuronal maturation, although the molecular nature of this clock remains unknown. Here we identify an epigenetic developmental programme that sets the timing of human neuronal maturation. First, we developed a hPSC-based approach to synchronize the birth of cortical neurons in vitro which enabled us to define an atlas of morphological, functional and molecular maturation. We observed a slow unfolding of maturation programmes, limited by the retention of specific epigenetic factors. Loss of function of several of those factors in cortical neurons enables precocious maturation. Transient inhibition of EZH2, EHMT1 and EHMT2 or DOT1L, at progenitor stage primes newly born neurons to rapidly acquire mature properties upon differentiation. Thus our findings reveal that the rate at which human neurons mature is set well before neurogenesis through the establishment of an epigenetic barrier in progenitor cells. Mechanistically, this barrier holds transcriptional maturation programmes in a poised state that is gradually released to ensure the prolonged timeline of human cortical neuron maturation.

Reprogramming tumor-associated macrophages to outcompete endovascular endothelial progenitor cells and suppress tumor neoangiogenesis.

Tumors develop by invoking a supportive environment characterized by aberrant angiogenesis and infiltration of tumor-associated macrophages (TAMs). In a transgenic model of breast cancer, we found that TAMs localized to the tumor parenchyma and were smaller than mammary tissue macrophages. TAMs had low activity of the metabolic regulator mammalian/mechanistic target of rapamycin complex 1 (mTORC1), and depletion of negative regulator of mTORC1 signaling, tuberous sclerosis complex 1 (TSC1), in TAMs inhibited tumor growth in a manner independent of adaptive lymphocytes. Whereas wild-type TAMs exhibited inflammatory and angiogenic gene expression profiles, TSC1-deficient TAMs had a pro-resolving phenotype. TSC1-deficient TAMs relocated to a perivascular niche, depleted protein C receptor (PROCR)-expressing endovascular endothelial progenitor cells, and rectified the hyperpermeable blood vasculature, causing tumor tissue hypoxia and cancer cell death. TSC1-deficient TAMs were metabolically active and effectively eliminated PROCR-expressing endothelial cells in cell competition experiments. Thus, TAMs exhibit a TSC1-dependent mTORC1-low state, and increasing mTORC1 signaling promotes a pro-resolving state that suppresses tumor growth, defining an innate immune tumor suppression pathway that may be exploited for cancer immunotherapy.

An encyclopedia of enhancer-gene regulatory interactions in the human genome.

Identifying transcriptional enhancers and their target genes is essential for understanding gene regulation and the impact of human genetic variation on disease1-6. Here we create and evaluate a resource of >13 million enhancer-gene regulatory interactions across 352 cell types and tissues, by integrating predictive models, measurements of chromatin state and 3D contacts, and largescale genetic perturbations generated by the ENCODE Consortium7. We first create a systematic benchmarking pipeline to compare predictive models, assembling a dataset of 10,411 elementgene pairs measured in CRISPR perturbation experiments, >30,000 fine-mapped eQTLs, and 569 fine-mapped GWAS variants linked to a likely causal gene. Using this framework, we develop a new predictive model, ENCODE-rE2G, that achieves state-of-the-art performance across multiple prediction tasks, demonstrating a strategy involving iterative perturbations and supervised machine learning to build increasingly accurate predictive models of enhancer regulation. Using the ENCODE-rE2G model, we build an encyclopedia of enhancer-gene regulatory interactions in the human genome, which reveals global properties of enhancer networks, identifies differences in the functions of genes that have more or less complex regulatory landscapes, and improves analyses to link noncoding variants to target genes and cell types for common, complex diseases. By interpreting the model, we find evidence that, beyond enhancer activity and 3D enhancer-promoter contacts, additional features guide enhancerpromoter communication including promoter class and enhancer-enhancer synergy. Altogether, these genome-wide maps of enhancer-gene regulatory interactions, benchmarking software, predictive models, and insights about enhancer function provide a valuable resource for future studies of gene regulation and human genetics.

Chronic Interferon Stimulated Gene Transcription Promotes Oncogene Induced Breast Cancer.

The Mre11 complex (comprising Mre11, Rad50, Nbs1) is integral to the maintenance of genome stability. We previously showed that a hypomorphic Mre11 mutant mouse strain ( Mre11 ATLD1/ATLD1 ) was highly susceptible to oncogene induced breast cancer. Here we used a mammary organoid system to examine which Mre11 dependent responses are tumor suppressive. We found that Mre11 ATLD1/ATLD1 organoids exhibited an elevated interferon stimulated gene (ISG) signature and sustained changes in chromatin accessibility. This Mre11 ATLD1/ATLD1 phenotype depended on DNA binding of a nuclear innate immune sensor, IFI205. Ablation of Ifi205 in Mre11 ATLD1/ATLD1 organoids restored baseline and oncogene-induced chromatin accessibility patterns to those observed in WT . Implantation of Mre11 ATLD1/ATLD1 organoids and activation of oncogene led to aggressive metastatic breast cancer. This outcome was reversed in implanted Ifi205 -/- Mre11 ATLD1/ATLD1 organoids. These data reveal a connection between innate immune signaling and tumor suppression in mammary epithelium. Given the abundance of aberrant DNA structures that arise in the context of genome instability syndromes, the data further suggest that cancer predisposition in those contexts may be partially attributable to tonic innate immune transcriptional programs.

ChromaFold predicts the 3D contact map from single-cell chromatin accessibility.

The identification of cell-type-specific 3D chromatin interactions between regulatory elements can help to decipher gene regulation and to interpret the function of disease-associated non-coding variants. However, current chromosome conformation capture (3C) technologies are unable to resolve interactions at this resolution when only small numbers of cells are available as input. We therefore present ChromaFold, a deep learning model that predicts 3D contact maps and regulatory interactions from single-cell ATAC sequencing (scATAC-seq) data alone. ChromaFold uses pseudobulk chromatin accessibility, co-accessibility profiles across metacells, and predicted CTCF motif tracks as input features and employs a lightweight architecture to enable training on standard GPUs. Once trained on paired scATAC-seq and Hi-C data in human cell lines and tissues, ChromaFold can accurately predict both the 3D contact map and peak-level interactions across diverse human and mouse test cell types. In benchmarking against a recent deep learning method that uses bulk ATAC-seq, DNA sequence, and CTCF ChIP-seq to make cell-type-specific predictions, ChromaFold yields superior prediction performance when including CTCF ChIP-seq data as an input and comparable performance without. Finally, fine-tuning ChromaFold on paired scATAC-seq and Hi-C in a complex tissue enables deconvolution of chromatin interactions across cell subpopulations. ChromaFold thus achieves state-of-the-art prediction of 3D contact maps and regulatory interactions using scATAC-seq alone as input data, enabling accurate inference of cell-type-specific interactions in settings where 3C-based assays are infeasible.

Discovery of Competent Chromatin Regions in Human Embryonic Stem Cells.

The mechanisms underlying the ability of embryonic stem cells (ESCs) to rapidly activate lineage-specific genes during differentiation remain largely unknown. Through multiple CRISPR-activation screens, we discovered human ESCs have pre-established transcriptionally competent chromatin regions (CCRs) that support lineage-specific gene expression at levels comparable to differentiated cells. CCRs reside in the same topological domains as their target genes. They lack typical enhancer-associated histone modifications but show enriched occupancy of pluripotent transcription factors, DNA demethylation factors, and histone deacetylases. TET1 and QSER1 protect CCRs from excessive DNA methylation, while HDAC1 family members prevent premature activation. This "push and pull" feature resembles bivalent domains at developmental gene promoters but involves distinct molecular mechanisms. Our study provides new insights into pluripotency regulation and cellular plasticity in development and disease. One sentence summary: We report a class of distal regulatory regions distinct from enhancers that confer human embryonic stem cells with the competence to rapidly activate the expression of lineage-specific genes.

Spatial and temporal organization of the genome: Current state and future aims of the 4D nucleome project.

The four-dimensional nucleome (4DN) consortium studies the architecture of the genome and the nucleus in space and time. We summarize progress by the consortium and highlight the development of technologies for (1) mapping genome folding and identifying roles of nuclear components and bodies, proteins, and RNA, (2) characterizing nuclear organization with time or single-cell resolution, and (3) imaging of nuclear organization. With these tools, the consortium has provided over 2,000 public datasets. Integrative computational models based on these data are starting to reveal connections between genome structure and function. We then present a forward-looking perspective and outline current aims to (1) delineate dynamics of nuclear architecture at different timescales, from minutes to weeks as cells differentiate, in populations and in single cells, (2) characterize cis-determinants and trans-modulators of genome organization, (3) test functional consequences of changes in cis- and trans-regulators, and (4) develop predictive models of genome structure and function.

Epiphany: predicting Hi-C contact maps from 1D epigenomic signals.

Recent deep learning models that predict the Hi-C contact map from DNA sequence achieve promising accuracy but cannot generalize to new cell types and or even capture differences among training cell types. We propose Epiphany, a neural network to predict cell-type-specific Hi-C contact maps from widely available epigenomic tracks. Epiphany uses bidirectional long short-term memory layers to capture long-range dependencies and optionally a generative adversarial network architecture to encourage contact map realism. Epiphany shows excellent generalization to held-out chromosomes within and across cell types, yields accurate TAD and interaction calls, and predicts structural changes caused by perturbations of epigenomic signals.

Drivers of heterogeneity in synovial fibroblasts in rheumatoid arthritis.

Inflammation of non-barrier immunologically quiescent tissues is associated with a massive influx of blood-borne innate and adaptive immune cells. Cues from the latter are likely to alter and expand activated states of the resident cells. However, local communications between immigrant and resident cell types in human inflammatory disease remain poorly understood. Here, we explored drivers of fibroblast-like synoviocyte (FLS) heterogeneity in inflamed joints of patients with rheumatoid arthritis using paired single-cell RNA and ATAC sequencing, multiplexed imaging and spatial transcriptomics along with in vitro modeling of cell-extrinsic factor signaling. These analyses suggest that local exposures to myeloid and T cell-derived cytokines, TNF, IFN-γ, IL-1ß or lack thereof, drive four distinct FLS states some of which closely resemble fibroblast states in other disease-affected tissues including skin and colon. Our results highlight a role for concurrent, spatially distributed cytokine signaling within the inflamed synovium.

RNA binding protein SYNCRIP maintains proteostasis and self-renewal of hematopoietic stem and progenitor cells.

Tissue homeostasis is maintained after stress by engaging and activating the hematopoietic stem and progenitor compartments in the blood. Hematopoietic stem cells (HSCs) are essential for long-term repopulation after secondary transplantation. Here, using a conditional knockout mouse model, we revealed that the RNA-binding protein SYNCRIP is required for maintenance of blood homeostasis especially after regenerative stress due to defects in HSCs and progenitors. Mechanistically, we find that SYNCRIP loss results in a failure to maintain proteome homeostasis that is essential for HSC maintenance. SYNCRIP depletion results in increased protein synthesis, a dysregulated epichaperome, an accumulation of misfolded proteins and induces endoplasmic reticulum stress. Additionally, we find that SYNCRIP is required for translation of CDC42 RHO-GTPase, and loss of SYNCRIP results in defects in polarity, asymmetric segregation, and dilution of unfolded proteins. Forced expression of CDC42 recovers polarity and in vitro replating activities of HSCs. Taken together, we uncovered a post-transcriptional regulatory program that safeguards HSC self-renewal capacity and blood homeostasis.

Microenvironment-Driven Dynamic Chromatin Changes in Glioblastoma Recapitulate Early Neural Development at Single-Cell Resolution.

The tumor microenvironment is necessary for recapitulating the intratumoral heterogeneity and cell state plasticity found in human primary glioblastoma (GBM). Conventional models do not accurately recapitulate the spectrum of GBM cellular states, hindering elucidation of the underlying transcriptional regulation of these states. Using our glioblastoma cerebral organoid model, we profiled the chromatin accessibility of 28,040 single cells in five patient-derived glioma stem cell lines. Integration of paired epigenomes and transcriptomes within the context of tumor-normal host cell interactions was used to probe the gene-regulatory networks underlying individual GBM cellular states in a way not readily possible in other in vitro models. These analyses identified the epigenetic underpinnings of GBM cellular states and characterized dynamic chromatin changes reminiscent of early neural development that underlie GBM cell state transitions. Despite large differences between tumors, a shared cellular compartment made up of neural progenitor-like cells and outer radial glia-like cells was observed. Together, these results shed light on the transcriptional regulation program in GBM and offer novel therapeutic targets across a broad range of genetically heterogenous GBMs. SIGNIFICANCE: Single-cell analyses elucidate the chromatin landscape and transcriptional regulation of glioblastoma cellular states and identify a radial glia-like population, providing potential targets to disrupt cell states and improve therapeutic efficacy.

Novel extragenic genomic safe harbors for precise therapeutic T-cell engineering.

Cell therapies that rely on engineered immune cells can be enhanced by achieving uniform and controlled transgene expression in order to maximize T-cell function and achieve predictable patient responses. Although they are effective, current genetic engineering strategies that use γ-retroviral, lentiviral, and transposon-based vectors to integrate transgenes, unavoidably produce variegated transgene expression in addition to posing a risk of insertional mutagenesis. In the setting of chimeric antigen receptor (CAR) therapy, inconsistent and random CAR expression may result in tonic signaling, T-cell exhaustion, and variable T-cell persistence. Here, we report and validate an algorithm for the identification of extragenic genomic safe harbors (GSH) that can be efficiently targeted for DNA integration and can support sustained and predictable CAR expression in human peripheral blood T cells. The algorithm is based on 7 criteria established to minimize genotoxicity by directing transgene integration away from functionally important genomic elements, maximize efficient CRISPR/Cas9-mediated targeting, and avert transgene silencing over time. T cells engineered to express a CD19 CAR at GSH6, which meets all 7 criteria, are curative at low cell dose in a mouse model of acute lymphoblastic leukemia, matching the potency of CAR T cells engineered at the TRAC locus and effectively resisting tumor rechallenge 100 days after their infusion. The identification of functional extragenic GSHs thus expands the human genome available for therapeutic precision engineering.

SETD2 regulates chromatin accessibility and transcription to suppress lung tumorigenesis.

SETD2, a H3K36 trimethyltransferase, is the most frequently mutated epigenetic modifier in lung adenocarcinoma, with a mutation frequency of approximately 9%. However, how SETD2 loss of function promotes tumorigenesis remains unclear. Using conditional Setd2-KO mice, we demonstrated that Setd2 deficiency accelerated the initiation of KrasG12D-driven lung tumorigenesis, increased tumor burden, and significantly reduced mouse survival. An integrated chromatin accessibility and transcriptome analysis revealed a potentially novel tumor suppressor model of SETD2 in which SETD2 loss activates intronic enhancers to drive oncogenic transcriptional output, including the KRAS transcriptional signature and PRC2-repressed targets, through regulation of chromatin accessibility and histone chaperone recruitment. Importantly, SETD2 loss sensitized KRAS-mutant lung cancer to inhibition of histone chaperones, the FACT complex, or transcriptional elongation both in vitro and in vivo. Overall, our studies not only provide insight into how SETD2 loss shapes the epigenetic and transcriptional landscape to promote tumorigenesis, but they also identify potential therapeutic strategies for SETD2 mutant cancers.

3D Chromatin Dynamics during Innate and Adaptive Immune Memory Acquisition.

Immune cells responding to pathogens undergo molecular changes that are intimately linked to genome organization. Recent work has demonstrated that natural killer (NK) and CD8 + T cells experience substantial transcriptomic and epigenetic rewiring during their differentiation from naïve to effector to memory cells. Whether these molecular adaptations are accompanied by changes in three-dimensional (3D) chromatin architecture is unknown. In this study, we combine histone profiling, ATAC-seq, RNA-seq and high-throughput chromatin capture (HiC) assay to investigate the dynamics of one-dimensional (1D) and 3D chromatin during the differentiation of innate and adaptive lymphocytes. To this end, we discovered a coordinated 1D and 3D epigenetic remodeling during innate immune memory differentiation, and demonstrate that effector CD8 + T cells adopt an NK-like architectural program that is maintained in memory cells. Altogether, our study reveals the dynamic nature of the 1D and 3D genome during the formation of innate and adaptive immunological memory.

Novel antigen-presenting cell imparts Treg-dependent tolerance to gut microbiota.

Establishing and maintaining tolerance to self-antigens or innocuous foreign antigens is vital for the preservation of organismal health. Within the thymus, medullary thymic epithelial cells (mTECs) expressing autoimmune regulator (AIRE) have a critical role in self-tolerance through deletion of autoreactive T cells and promotion of thymic regulatory T (Treg) cell development1-4. Within weeks of birth, a separate wave of Treg cell differentiation occurs in the periphery upon exposure to antigens derived from the diet and commensal microbiota5-8, yet the cell types responsible for the generation of peripheral Treg (pTreg) cells have not been identified. Here we describe the identification of a class of RORγt+ antigen-presenting cells called Thetis cells, with transcriptional features of both mTECs and dendritic cells, comprising four major sub-groups (TC I-TC IV). We uncover a developmental wave of Thetis cells within intestinal lymph nodes during a critical window in early life, coinciding with the wave of pTreg cell differentiation. Whereas TC I and TC III expressed the signature mTEC nuclear factor AIRE, TC IV lacked AIRE expression and was enriched for molecules required for pTreg generation, including the TGF-ß-activating integrin αvß8. Loss of either major histocompatibility complex class II (MHCII) or ITGB8 by Thetis cells led to a profound impairment in intestinal pTreg differentiation, with ensuing colitis. By contrast, MHCII expression by RORγt+ group 3 innate lymphoid cells (ILC3) and classical dendritic cells was neither sufficient nor required for pTreg generation, further implicating TC IV as the tolerogenic RORγt+ antigen-presenting cell with an essential function in early life. Our studies reveal parallel pathways for the establishment of tolerance to self and foreign antigens in the thymus and periphery, respectively, marked by the involvement of shared cellular and transcriptional programmes.