DNA hypomethylation silences anti-tumor immune genes in early prostate cancer and CTCs.

Cancer is characterized by hypomethylation-associated silencing of large chromatin domains, whose contribution to tumorigenesis is uncertain. Through high-resolution genome-wide single-cell DNA methylation sequencing, we identify 40 core domains that are uniformly hypomethylated from the earliest detectable stages of prostate malignancy through metastatic circulating tumor cells (CTCs). Nested among these repressive domains are smaller loci with preserved methylation that escape silencing and are enriched for cell proliferation genes. Transcriptionally silenced genes within the core hypomethylated domains are enriched for immune-related genes; prominent among these is a single gene cluster harboring all five CD1 genes that present lipid antigens to NKT cells and four IFI16-related interferon-inducible genes implicated in innate immunity. The re-expression of CD1 or IFI16 murine orthologs in immuno-competent mice abrogates tumorigenesis, accompanied by the activation of anti-tumor immunity. Thus, early epigenetic changes may shape tumorigenesis, targeting co-located genes within defined chromosomal loci. Hypomethylation domains are detectable in blood specimens enriched for CTCs.

Human lung cancer harbors spatially organized stem-immunity hubs associated with response to immunotherapy.

The organization of immune cells in human tumors is not well understood. Immunogenic tumors harbor spatially localized multicellular 'immunity hubs' defined by expression of the T cell-attracting chemokines CXCL10/CXCL11 and abundant T cells. Here, we examined immunity hubs in human pre-immunotherapy lung cancer specimens and found an association with beneficial response to PD-1 blockade. Critically, we discovered the stem-immunity hub, a subtype of immunity hub strongly associated with favorable PD-1-blockade outcome. This hub is distinct from mature tertiary lymphoid structures and is enriched for stem-like TCF7+PD-1+CD8+ T cells, activated CCR7+LAMP3+ dendritic cells and CCL19+ fibroblasts as well as chemokines that organize these cells. Within the stem-immunity hub, we find preferential interactions between CXCL10+ macrophages and TCF7-CD8+ T cells as well as between mature regulatory dendritic cells and TCF7+CD4+ and regulatory T cells. These results provide a picture of the spatial organization of the human intratumoral immune response and its relevance to patient immunotherapy outcomes.

Large-Scale Topological Changes Restrain Malignant Progression in Colorectal Cancer.

Widespread changes to DNA methylation and chromatin are well documented in cancer, but the fate of higher-order chromosomal structure remains obscure. Here we integrated topological maps for colon tumors and normal colons with epigenetic, transcriptional, and imaging data to characterize alterations to chromatin loops, topologically associated domains, and large-scale compartments. We found that spatial partitioning of the open and closed genome compartments is profoundly compromised in tumors. This reorganization is accompanied by compartment-specific hypomethylation and chromatin changes. Additionally, we identify a compartment at the interface between the canonical A and B compartments that is reorganized in tumors. Remarkably, similar shifts were evident in non-malignant cells that have accumulated excess divisions. Our analyses suggest that these topological changes repress stemness and invasion programs while inducing anti-tumor immunity genes and may therefore restrain malignant progression. Our findings call into question the conventional view that tumor-associated epigenomic alterations are primarily oncogenic.

Lineage Tracing in Humans Enabled by Mitochondrial Mutations and Single-Cell Genomics.

Lineage tracing provides key insights into the fate of individual cells in complex organisms. Although effective genetic labeling approaches are available in model systems, in humans, most approaches require detection of nuclear somatic mutations, which have high error rates, limited scale, and do not capture cell state information. Here, we show that somatic mutations in mtDNA can be tracked by single-cell RNA or assay for transposase accessible chromatin (ATAC) sequencing. We leverage somatic mtDNA mutations as natural genetic barcodes and demonstrate their utility as highly accurate clonal markers to infer cellular relationships. We track native human cells both in vitro and in vivo and relate clonal dynamics to gene expression and chromatin accessibility. Our approach should allow clonal tracking at a 1,000-fold greater scale than with nuclear genome sequencing, with simultaneous information on cell state, opening the way to chart cellular dynamics in human health and disease.

Stromal Microenvironment Shapes the Intratumoral Architecture of Pancreatic Cancer.

Single-cell technologies have described heterogeneity across tissues, but the spatial distribution and forces that drive single-cell phenotypes have not been well defined. Combining single-cell RNA and protein analytics in studying the role of stromal cancer-associated fibroblasts (CAFs) in modulating heterogeneity in pancreatic cancer (pancreatic ductal adenocarcinoma [PDAC]) model systems, we have identified significant single-cell population shifts toward invasive epithelial-to-mesenchymal transition (EMT) and proliferative (PRO) phenotypes linked with mitogen-activated protein kinase (MAPK) and signal transducer and activator of transcription 3 (STAT3) signaling. Using high-content digital imaging of RNA in situ hybridization in 195 PDAC tumors, we quantified these EMT and PRO subpopulations in 319,626 individual cancer cells that can be classified within the context of distinct tumor gland "units." Tumor gland typing provided an additional layer of intratumoral heterogeneity that was associated with differences in stromal abundance and clinical outcomes. This demonstrates the impact of the stroma in shaping tumor architecture by altering inherent patterns of tumor glands in human PDAC.

A CTCF-binding site in the Mdm1-Il22-Ifng locus shapes cytokine expression profiles and plays a critical role in early Th1 cell fate specification.

Cytokine expression during T cell differentiation is a highly regulated process that involves long-range promoter-enhancer and CTCF-CTCF contacts at cytokine loci. Here, we investigated the impact of dynamic chromatin loop formation within the topologically associating domain (TAD) in regulating the expression of interferon gamma (IFN-γ) and interleukin-22 (IL-22); these cytokine loci are closely located in the genome and are associated with complex enhancer landscapes, which are selectively active in type 1 and type 3 lymphocytes. In situ Hi-C analyses revealed inducible TADs that insulated Ifng and Il22 enhancers during Th1 cell differentiation. Targeted deletion of a 17 bp boundary motif of these TADs imbalanced Th1- and Th17-associated immunity, both in vitro and in vivo, upon Toxoplasma gondii infection. In contrast, this boundary element was dispensable for cytokine regulation in natural killer cells. Our findings suggest that precise cytokine regulation relies on lineage- and developmental stage-specific interactions of 3D chromatin architectures and enhancer landscapes.

Integrated Single-Cell Analysis Maps the Continuous Regulatory Landscape of Human Hematopoietic Differentiation.

Human hematopoiesis involves cellular differentiation of multipotent cells into progressively more lineage-restricted states. While the chromatin accessibility landscape of this process has been explored in defined populations, single-cell regulatory variation has been hidden by ensemble averaging. We collected single-cell chromatin accessibility profiles across 10 populations of immunophenotypically defined human hematopoietic cell types and constructed a chromatin accessibility landscape of human hematopoiesis to characterize differentiation trajectories. We find variation consistent with lineage bias toward different developmental branches in multipotent cell types. We observe heterogeneity within common myeloid progenitors (CMPs) and granulocyte-macrophage progenitors (GMPs) and develop a strategy to partition GMPs along their differentiation trajectory. Furthermore, we integrated single-cell RNA sequencing (scRNA-seq) data to associate transcription factors to chromatin accessibility changes and regulatory elements to target genes through correlations of expression and regulatory element accessibility. Overall, this work provides a framework for integrative exploration of complex regulatory dynamics in a primary human tissue at single-cell resolution.

Spatial transcriptomics reveals distinct tissue niches linked with steroid responsiveness in acute gastrointestinal GVHD.

Severe acute graft-versus-host disease (aGVHD) is associated with significant mortality and morbidity, especially in steroid-resistant (SR) cases. Spatial transcriptomic technology can elucidate tissue-based interactions in vivo and possibly identify predictors of treatment response. Tissue sections from 32 treatment-naïve patients with biopsy-confirmed lower gastrointestinal (GI) aGVHD were obtained. The GeoMx digital spatial profiler was used to capture transcriptome profiles of >18 000 genes from different foci of immune infiltrates, colonic epithelium, and vascular endothelium. Each tissue compartment sampled showed 2 distinct clusters that were analyzed for differential expression and spatially resolved correlation of gene signatures. Classic cell-mediated immunity signatures, normal differentiated epithelial cells, and inflamed vasculature dominated foci sampled from steroid-sensitive cases. In contrast, a neutrophil predominant noncanonical inflammation with regenerative epithelial cells and some indication of angiogenic endothelial response was overrepresented in areas from SR cases. Evaluation of potential prognostic biomarkers identified ubiquitin specific peptidase 17-like (USP17L) family of genes as being differentially expressed in immune cells from patients with worsened survival. In summary, we demonstrate distinct tissue niches with unique gene expression signatures within lower GI tissue from patients with aGVHD and provide evidence of a potential prognostic biomarker.

Transcriptome-wide off-target RNA editing induced by CRISPR-guided DNA base editors.

CRISPR-Cas base-editor technology enables targeted nucleotide alterations, and is being increasingly used for research and potential therapeutic applications1,2. The most widely used cytosine base editors (CBEs) induce deamination of DNA cytosines using the rat APOBEC1 enzyme, which is targeted by a linked Cas protein-guide RNA complex3,4. Previous studies of the specificity of CBEs have identified off-target DNA edits in mammalian cells5,6. Here we show that a CBE with rat APOBEC1 can cause extensive transcriptome-wide deamination of RNA cytosines in human cells, inducing tens of thousands of C-to-U edits with frequencies ranging from 0.07% to 100% in 38-58% of expressed genes. CBE-induced RNA edits occur in both protein-coding and non-protein-coding sequences and generate missense, nonsense, splice site, and 5' and 3' untranslated region mutations. We engineered two CBE variants bearing mutations in rat APOBEC1 that substantially decreased the number of RNA edits (by more than 390-fold and more than 3,800-fold) in human cells. These variants also showed more precise on-target DNA editing than the wild-type CBE and, for most guide RNAs tested, no substantial reduction in editing efficiency. Finally, we show that an adenine base editor7 can also induce transcriptome-wide RNA edits. These results have implications for the use of base editors in both research and clinical settings, illustrate the feasibility of engineering improved variants with reduced RNA editing activities, and suggest the need to more fully define and characterize the RNA off-target effects of deaminase enzymes in base editor platforms.

Epigenetic evolution and lineage histories of chronic lymphocytic leukaemia.

Genetic and epigenetic intra-tumoral heterogeneity cooperate to shape the evolutionary course of cancer1. Chronic lymphocytic leukaemia (CLL) is a highly informative model for cancer evolution as it undergoes substantial genetic diversification and evolution after therapy2,3. The CLL epigenome is also an important disease-defining feature4,5, and growing populations of cells in CLL diversify by stochastic changes in DNA methylation known as epimutations6. However, previous studies using bulk sequencing methods to analyse the patterns of DNA methylation were unable to determine whether epimutations affect CLL populations homogeneously. Here, to measure the epimutation rate at single-cell resolution, we applied multiplexed single-cell reduced-representation bisulfite sequencing to B cells from healthy donors and patients with CLL. We observed that the common clonal origin of CLL results in a consistently increased epimutation rate, with low variability in the cell-to-cell epimutation rate. By contrast, variable epimutation rates across healthy B cells reflect diverse evolutionary ages across the trajectory of B cell differentiation, consistent with epimutations serving as a molecular clock. Heritable epimutation information allowed us to reconstruct lineages at high-resolution with single-cell data, and to apply this directly to patient samples. The CLL lineage tree shape revealed earlier branching and longer branch lengths than in normal B cells, reflecting rapid drift after the initial malignant transformation and a greater proliferative history. Integration of single-cell bisulfite sequencing analysis with single-cell transcriptomes and genotyping confirmed that genetic subclones mapped to distinct clades, as inferred solely on the basis of epimutation information. Finally, to examine potential lineage biases during therapy, we profiled serial samples during ibrutinib-associated lymphocytosis, and identified clades of cells that were preferentially expelled from the lymph node after treatment, marked by distinct transcriptional profiles. The single-cell integration of genetic, epigenetic and transcriptional information thus charts the lineage history of CLL and its evolution with therapy.

Augmenting and directing long-range CRISPR-mediated activation in human cells.

Epigenetic editing is an emerging technology that uses artificial transcription factors (aTFs) to regulate expression of a target gene. Although human genes can be robustly upregulated by targeting aTFs to promoters, the activation induced by directing aTFs to distal transcriptional enhancers is substantially less robust and consistent. Here we show that long-range activation using CRISPR-based aTFs in human cells can be made more efficient and reliable by concurrently targeting an aTF to the target gene promoter. We used this strategy to direct target gene choice for enhancers capable of regulating more than one promoter and to achieve allele-selective activation of human genes by targeting aTFs to single-nucleotide polymorphisms embedded in distally located sequences. Our results broaden the potential applications of the epigenetic editing toolbox for research and therapeutics.

Congenital anemia reveals distinct targeting mechanisms for master transcription factor GATA1.

Master regulators, such as the hematopoietic transcription factor (TF) GATA1, play an essential role in orchestrating lineage commitment and differentiation. However, the precise mechanisms by which such TFs regulate transcription through interactions with specific cis-regulatory elements remain incompletely understood. Here, we describe a form of congenital hemolytic anemia caused by missense mutations in an intrinsically disordered region of GATA1, with a poorly understood role in transcriptional regulation. Through integrative functional approaches, we demonstrate that these mutations perturb GATA1 transcriptional activity by partially impairing nuclear localization and selectively altering precise chromatin occupancy by GATA1. These alterations in chromatin occupancy and concordant chromatin accessibility changes alter faithful gene expression, with failure to both effectively silence and activate select genes necessary for effective terminal red cell production. We demonstrate how disease-causing mutations can reveal regulatory mechanisms that enable the faithful genomic targeting of master TFs during cellular differentiation.

In vivo CRISPR editing with no detectable genome-wide off-target mutations.

CRISPR-Cas genome-editing nucleases hold substantial promise for developing human therapeutic applications1-6 but identifying unwanted off-target mutations is important for clinical translation7. A well-validated method that can reliably identify off-targets in vivo has not been described to date, which means it is currently unclear whether and how frequently these mutations occur. Here we describe 'verification of in vivo off-targets' (VIVO), a highly sensitive strategy that can robustly identify the genome-wide off-target effects of CRISPR-Cas nucleases in vivo. We use VIVO and a guide RNA deliberately designed to be promiscuous to show that CRISPR-Cas nucleases can induce substantial off-target mutations in mouse livers in vivo. More importantly, we also use VIVO to show that appropriately designed guide RNAs can direct efficient in vivo editing in mouse livers with no detectable off-target mutations. VIVO provides a general strategy for defining and quantifying the off-target effects of gene-editing nucleases in whole organisms, thereby providing a blueprint to foster the development of therapeutic strategies that use in vivo gene editing.

Survival in Quiescence Requires the Euchromatic Deployment of Clr4/SUV39H by Argonaute-Associated Small RNAs.

Quiescence (G0) is a ubiquitous stress response through which cells enter reversible dormancy, acquiring distinct properties including reduced metabolism, resistance to stress, and long life. G0 entry involves dramatic changes to chromatin and transcription of cells, but the mechanisms coordinating these processes remain poorly understood. Using the fission yeast, here, we track G0-associated chromatin and transcriptional changes temporally and show that as cells enter G0, their survival and global gene expression programs become increasingly dependent on Clr4/SUV39H, the sole histone H3 lysine 9 (H3K9) methyltransferase, and RNAi proteins. Notably, G0 entry results in RNAi-dependent H3K9 methylation of several euchromatic pockets, prior to which Argonaute1-associated small RNAs from these regions emerge. Overall, our data reveal another function for constitutive heterochromatin proteins (the establishment of the global G0 transcriptional program) and suggest that stress-induced alterations in Argonaute-associated sRNAs can target the deployment of transcriptional regulatory proteins to specific sequences.

Screening human lung cancer with predictive models of serum magnetic resonance spectroscopy metabolomics.

The current high mortality of human lung cancer stems largely from the lack of feasible, early disease detection tools. An effective test with serum metabolomics predictive models able to suggest patients harboring disease could expedite triage patient to specialized imaging assessment. Here, using a training-validation-testing-cohort design, we establish our high-resolution magic angle spinning (HRMAS) magnetic resonance spectroscopy (MRS)-based metabolomics predictive models to indicate lung cancer presence and patient survival using serum samples collected prior to their disease diagnoses. Studied serum samples were collected from 79 patients before (within 5.0 y) and at lung cancer diagnosis. Disease predictive models were established by comparing serum metabolomic patterns between our training cohorts: patients with lung cancer at time of diagnosis, and matched healthy controls. These predictive models were then applied to evaluate serum samples of our validation and testing cohorts, all collected from patients before their lung cancer diagnosis. Our study found that the predictive model yielded values for prior-to-detection serum samples to be intermediate between values for patients at time of diagnosis and for healthy controls; these intermediate values significantly differed from both groups, with an F1 score = 0.628 for cancer prediction. Furthermore, values from metabolomics predictive model measured from prior-to-diagnosis sera could significantly predict 5-y survival for patients with localized disease.

Engineered CRISPR-Cas9 nucleases with altered PAM specificities.

Although CRISPR-Cas9 nucleases are widely used for genome editing, the range of sequences that Cas9 can recognize is constrained by the need for a specific protospacer adjacent motif (PAM). As a result, it can often be difficult to target double-stranded breaks (DSBs) with the precision that is necessary for various genome-editing applications. The ability to engineer Cas9 derivatives with purposefully altered PAM specificities would address this limitation. Here we show that the commonly used Streptococcus pyogenes Cas9 (SpCas9) can be modified to recognize alternative PAM sequences using structural information, bacterial selection-based directed evolution, and combinatorial design. These altered PAM specificity variants enable robust editing of endogenous gene sites in zebrafish and human cells not currently targetable by wild-type SpCas9, and their genome-wide specificities are comparable to wild-type SpCas9 as judged by GUIDE-seq analysis. In addition, we identify and characterize another SpCas9 variant that exhibits improved specificity in human cells, possessing better discrimination against off-target sites with non-canonical NAG and NGA PAMs and/or mismatched spacers. We also find that two smaller-size Cas9 orthologues, Streptococcus thermophilus Cas9 (St1Cas9) and Staphylococcus aureus Cas9 (SaCas9), function efficiently in the bacterial selection systems and in human cells, suggesting that our engineering strategies could be extended to Cas9s from other species. Our findings provide broadly useful SpCas9 variants and, more importantly, establish the feasibility of engineering a wide range of Cas9s with altered and improved PAM specificities.

Data-Driven Polymer Model for Mechanistic Exploration of Diploid Genome Organization.

Chromosomes are positioned nonrandomly inside the nucleus to coordinate with their transcriptional activity. The molecular mechanisms that dictate the global genome organization and the nuclear localization of individual chromosomes are not fully understood. We introduce a polymer model to study the organization of the diploid human genome. It is data-driven because all parameters can be derived from Hi-C data; it is also a mechanistic model because the energy function is explicitly written out based on a few biologically motivated hypotheses. These two features distinguish the model from existing approaches and make it useful both for reconstructing genome structures and for exploring the principles of genome organization. We carried out extensive validations to show that simulated genome structures reproduce a wide variety of experimental measurements, including chromosome radial positions and spatial distances between homologous pairs. Detailed mechanistic investigations support the importance of both specific interchromosomal interactions and centromere clustering for chromosome positioning. We anticipate the polymer model, when combined with Hi-C experiments, to be a powerful tool for investigating large-scale rearrangements in genome structure upon cell differentiation and tumor progression.

CIRCLE-seq: a highly sensitive in vitro screen for genome-wide CRISPR-Cas9 nuclease off-targets.

Sensitive detection of off-target effects is important for translating CRISPR-Cas9 nucleases into human therapeutics. In vitro biochemical methods for finding off-targets offer the potential advantages of greater reproducibility and scalability while avoiding limitations associated with strategies that require the culture and manipulation of living cells. Here we describe circularization for in vitro reporting of cleavage effects by sequencing (CIRCLE-seq), a highly sensitive, sequencing-efficient in vitro screening strategy that outperforms existing cell-based or biochemical approaches for identifying CRISPR-Cas9 genome-wide off-target mutations. In contrast to previously described in vitro methods, we show that CIRCLE-seq can be practiced using widely accessible next-generation sequencing technology and does not require reference genome sequences. Importantly, CIRCLE-seq can be used to identify off-target mutations associated with cell-type-specific single-nucleotide polymorphisms, demonstrating the feasibility and importance of generating personalized specificity profiles. CIRCLE-seq provides an accessible, rapid, and comprehensive method for identifying genome-wide off-target mutations of CRISPR-Cas9.

A (fire)cloud-based DNA methylation data preprocessing and quality control platform.

BACKGROUND: Bisulfite sequencing allows base-pair resolution profiling of DNA methylation and has recently been adapted for use in single-cells. Analyzing these data, including making comparisons with existing data, remains challenging due to the scale of the data and differences in preprocessing methods between published datasets. RESULTS: We present a set of preprocessing pipelines for bisulfite sequencing DNA methylation data that include a new R/Bioconductor package, scmeth, for a series of efficient QC analyses of large datasets. The pipelines go from raw data to CpG-level methylation estimates and can be run, with identical results, either on a single computer, in an HPC cluster or on Google Cloud Compute resources. These pipelines are designed to allow users to 1) ensure reproducibility of analyses, 2) achieve scalability to large whole genome datasets with 100 GB+ of raw data per sample and to single-cell datasets with thousands of cells, 3) enable integration and comparison between user-provided data and publicly available data, as all samples can be processed through the same pipeline, and 4) access to best-practice analysis pipelines. Pipelines are provided for whole genome bisulfite sequencing (WGBS), reduced representation bisulfite sequencing (RRBS) and hybrid selection (capture) bisulfite sequencing (HSBS). CONCLUSIONS: The workflows produce data quality metrics, visualization tracks, and aggregated output for further downstream analysis. Optional use of cloud computing resources facilitates analysis of large datasets, and integration with existing methylome profiles. The workflow design principles are applicable to other genomic data types.