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.

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 disease 1-6 . 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 large-scale genetic perturbations generated by the ENCODE Consortium 7 . We first create a systematic benchmarking pipeline to compare predictive models, assembling a dataset of 10,411 element-gene 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 enhancer-promoter 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.

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.

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.

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-1β 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.

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.

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.

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.

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 na√Øve 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.

TP53 mutations and RNA-binding protein MUSASHI-2 drive resistance to PRMT5-targeted therapy in B-cell lymphoma

To identify drivers of sensitivity and resistance to Protein Arginine Methyltransferase 5 (PRMT5) inhibition, we perform a genome-wide CRISPR/Cas9 screen. We identify TP53 and RNA-binding protein MUSASHI2 (MSI2) as the top-ranked sensitizer and driver of resistance to specific PRMT5i, GSK-591, respectively. TP53 deletion and TP53^R248W mutation are biomarkers of resistance to GSK-591. PRMT5 expression correlates with MSI2 expression in lymphoma patients. MSI2 depletion and pharmacological inhibition using Ro 08-2750 (Ro) both synergize with GSK-591 to reduce cell growth. Ro reduces MSI2 binding to its global targets and dual treatment of Ro and PRMT5 inhibitors result in synergistic gene expression changes including cell cycle, P53 and MYC signatures. Dual MSI2 and PRMT5 inhibition further blocks c-MYC and BCL-2 translation. BCL-2 depletion or inhibition with venetoclax synergizes with a PRMT5 inhibitor by inducing reduced cell growth and apoptosis. Thus, we propose a therapeutic strategy in lymphoma that combines PRMT5 with MSI2 or BCL-2 inhibition.

Inhibition of the protein arginine methyltransferase PRMT5 has been suggested as a promising therapy for lymphoma. Here, the authors show that TP53 loss of function and MUSASHI-2 (MSI2) expression are biomarkers of resistance to PRMT5-targeted therapy in B-cell lymphoma. Moreover, combining PRMT5 inhibition with MSI2 or BCL-2 inhibitors blocks the translation of key drivers of lymphoma, c-MYC and BCL-2, inhibiting cell growth.

CRISPR screening uncovers a central requirement for HHEX in pancreatic lineage commitment and plasticity restriction

The pancreas and liver arise from a common pool of progenitors. However, the underlying mechanisms that drive their lineage diversification from the foregut endoderm are not fully understood. To tackle this question, we undertook a multifactorial approach that integrated human pluripotent-stem-cell-guided differentiation, genome-scale CRISPR-Cas9 screening, single-cell analysis, genomics and proteomics. We discovered that HHEX, a transcription factor (TF) widely recognized as a key regulator of liver development, acts as a gatekeeper of pancreatic lineage specification. HHEX deletion impaired pancreatic commitment and unleashed an unexpected degree of cellular plasticity towards the liver and duodenum fates. Mechanistically, HHEX cooperates with the pioneer TFs FOXA1, FOXA2 and GATA4, shared by both pancreas and liver differentiation programmes, to promote pancreas commitment, and this cooperation restrains the shared TFs from activating alternative lineages. These findings provide a generalizable model for how gatekeeper TFs like HHEX orchestrate lineage commitment and plasticity restriction in broad developmental contexts.

Base editing sensor libraries for high-throughput engineering and functional analysis of cancer-associated single nucleotide variants

Base editing can be applied to characterize single nucleotide variants of unknown function, yet defining effective combinations of single guide RNAs (sgRNAs) and base editors remains challenging. Here, we describe modular base-editing-activity 'sensors' that link sgRNAs and cognate target sites in cis and use them to systematically measure the editing efficiency and precision of thousands of sgRNAs paired with functionally distinct base editors. By quantifying sensor editing across >200,000 editor-sgRNA combinations, we provide a comprehensive resource of sgRNAs for introducing and interrogating cancer-associated single nucleotide variants in multiple model systems. We demonstrate that sensor-validated tools streamline production of in vivo cancer models and that integrating sensor modules in pooled sgRNA libraries can aid interpretation of high-throughput base editing screens. Using this approach, we identify several previously uncharacterized mutant TP53 alleles as drivers of cancer cell proliferation and in vivo tumor development. We anticipate that the framework described here will facilitate the functional interrogation of cancer variants in cell and animal models.

Globin vector regulatory elements are active in early hematopoietic progenitor cells

The globin genes are archetypal tissue-specific genes that are silent in most tissues but for late-stage erythroblasts upon terminal erythroid differentiation. The transcriptional activation of the β-globin gene is under the control of proximal and distal regulatory elements located on chromosome 11p15.4, including the β-globin locus control region (LCR). The incorporation of selected LCR elements in lentiviral vectors encoding β and β-like globin genes has enabled successful genetic treatment of the β-thalassemias and sickle cell disease. However, recent occurrences of benign clonal expansions in thalassemic patients and myelodysplastic syndrome in patients with sickle cell disease call attention to the non-erythroid functions of these powerful vectors. Here we demonstrate that lentivirally encoded LCR elements, in particular HS1 and HS2, can be activated in early hematopoietic cells including hematopoietic stem cells and myeloid progenitors. This activity is position-dependent and results in the transcriptional activation of a nearby reporter gene in these progenitor cell populations. We further show that flanking a globin vector with an insulator can effectively restrain this non-erythroid activity without impairing therapeutic globin expression. Globin lentiviral vectors harboring powerful LCR HS elements may thus expose to the risk of trans-activating cancer-related genes, which can be mitigated by a suitable insulator.

Cytotoxic granzyme C-expressing ILC1s contribute to antitumor immunity and neonatal autoimmunity

Innate lymphocytes are integral components of the cellular immune system that can coordinate host defense against a multitude of challenges and trigger immunopathology when dysregulated. Natural killer (NK) cells and innate lymphoid cells (ILCs) are innate immune effectors postulated to functionally mirror conventional cytotoxic T lymphocytes and helper T cells, respectively. Here, we showed that the cytolytic molecule granzyme C was expressed in cells with the phenotype of type 1 ILCs (ILC1s) in mouse liver and salivary gland. Cell fate-mapping and transfer studies revealed that granzyme C-expressing innate lymphocytes could be derived from ILC progenitors and did not interconvert with NK cells, ILC2s, or ILC3s. Granzyme C defined a maturation state of ILC1s. These granzyme C-expressing ILC1s required the transcription factors T-bet and, to a lesser extent, Eomes and support from transforming growth factor-β (TGF-β) signaling for their maintenance in the salivary gland. In a transgenic mouse breast cancer model, depleting ILC1s caused accelerated tumor growth. ILC1s gained granzyme C expression following interleukin-15 (IL-15) stimulation, which enabled perforin-mediated cytotoxicity. Constitutive activation of STAT5, a transcription factor regulated by IL-15, in granzyme C-expressing ILC1s triggered lethal perforin-dependent autoimmunity in neonatal mice. Thus, granzyme C marks a cytotoxic effector state of ILC1s, broadening their function beyond "helper-like" lymphocytes.

Chromatin interaction aware gene regulatory modeling with graph attention networks

Linking distal enhancers to genes and modeling their impact on target gene expression are longstanding unresolved problems in regulatory genomics and critical for interpreting noncoding genetic variation. Here we present a new deep learning approach called GraphReg that exploits 3D interactions from chromosome conformation capture assays in order to predict gene expression from 1D epigenomic data or genomic DNA sequence. By using graph attention networks to exploit the connectivity of distal elements up to 2Mb away in the genome, GraphReg more faithfully models gene regulation and more accurately predicts gene expression levels than state-of-the-art deep learning methods for this task. Feature attribution used with GraphReg accurately identifies functional enhancers of genes, as validated by CRISPRi-FlowFISH and TAP-seq assays, outperforming both CNNs and the recently proposed Activity-by-Contact model. Sequence-based GraphReg also accurately predicts direct transcription factor (TF) targets as validated by CRISPRi TF knockout experiments via in silico ablation of TF binding motifs. GraphReg therefore represents an important advance in modeling the regulatory impact of epigenomic and sequence elements.

Single-Cell Transcriptional Profiling Reveals Signatures of Helper, Effector, and Regulatory MAIT Cells during Homeostasis and Activation

Mucosal-associated invariant T (MAIT) cells are innate-like lymphocytes that recognize microbial vitamin B metabolites and have emerging roles in infectious disease, autoimmunity, and cancer. Although MAIT cells are identified by a semi-invariant TCR, their phenotypic and functional heterogeneity is not well understood. Here we present an integrated single cell transcriptomic analysis of over 76,000 human MAIT cells during early and prolonged Ag-specific activation with the MR1 ligand 5-OP-RU and nonspecific TCR stimulation. We show that MAIT cells span a broad range of homeostatic, effector, helper, tissue-infiltrating, regulatory, and exhausted phenotypes, with distinct gene expression programs associated with CD4⁺ or CD8⁺ coexpression. During early activation, MAIT cells rapidly adopt a cytotoxic phenotype characterized by high expression of GZMB, IFNG and TNF In contrast, prolonged stimulation induces heterogeneous states defined by proliferation, cytotoxicity, immune modulation, and exhaustion. We further demonstrate a FOXP3 expressing MAIT cell subset that phenotypically resembles conventional regulatory T cells. Moreover, scRNAseq-defined MAIT cell subpopulations were also detected in individuals recently exposed to Mycobacterium tuberculosis, confirming their presence during human infection. To our knowledge, our study provides the first comprehensive atlas of human MAIT cells in activation conditions and defines substantial functional heterogeneity, suggesting complex roles in health and disease.

Hierarchical regulation of the resting and activated T cell epigenome by major transcription factor families

T cell activation, a key early event in the adaptive immune response, is subject to elaborate transcriptional control. Here, we examined how the activities of eight major transcription factor (TF) families are integrated to shape the epigenome of naïve and activated CD4 and CD8 T cells. By leveraging extensive polymorphisms in evolutionarily divergent mice, we identified the “heavy lifters” positively influencing chromatin accessibility. Members of Ets, Runx, and TCF/Lef TF families occupied the vast majority of accessible chromatin regions, acting as “housekeepers”, “universal amplifiers”, and “placeholders”, respectively, at sites that maintained or gained accessibility upon T cell activation. Additionally, a small subset of strongly induced immune response genes displayed a non-canonical TF recruitment pattern. Our study provides a key resource and foundation for the understanding of transcriptional and epigenetic regulation in T cells and offers a new perspective on the hierarchical interactions between critical TFs.

HiC-DC+ enables systematic 3D interaction calls and differential analysis for Hi-C and HiChIP

Recent genome-wide chromosome conformation capture assays such as Hi-C and HiChIP have vastly expanded the resolution and throughput with which we can study 3D genomic architecture and function. Here, we present HiC-DC+, a software tool for Hi-C/HiChIP interaction calling and differential analysis using an efficient implementation of the HiC-DC statistical framework. HiC-DC+ integrates with popular preprocessing and visualization tools and includes topologically associating domain (TAD) and A/B compartment callers. We found that HiC-DC+ can more accurately identify enhancer-promoter interactions in H3K27ac HiChIP, as validated by CRISPRi-FlowFISH experiments, compared to existing methods. Differential HiC-DC+ analyses of published HiChIP and Hi-C data sets in settings of cellular differentiation and cohesin perturbation systematically and quantitatively recovers biological findings, including enhancer hubs, TAD aggregation, and the relationship between promoter-enhancer loop dynamics and gene expression changes. HiC-DC+ therefore provides a principled statistical analysis tool to empower genome-wide studies of 3D chromatin architecture and function.

The genome-wide investigation of chromatin organization enables insights into global gene expression control. Here, the authors present a computationally efficient method for the analysis of chromatin organization data and use it to recover principles of 3D organization across conditions.

A unified atlas of CD8 T cell dysfunctional states in cancer and infection

CD8 T cells play an essential role in defense against viral and bacterial infections and in tumor immunity. Deciphering T cell loss of functionality is complicated by the conspicuous heterogeneity of CD8 T cell states described across experimental and clinical settings. By carrying out a unified analysis of over 300 assay for transposase-accessible chromatin sequencing (ATAC-seq) and RNA sequencing (RNA-seq) experiments from 12 studies of CD8 T cells in cancer and infection, we defined a shared differentiation trajectory toward dysfunction and its underlying transcriptional drivers and revealed a universal early bifurcation of functional and dysfunctional T cell states across models. Experimental dissection of acute and chronic viral infection using single-cell ATAC (scATAC)-seq and allele-specific single-cell RNA (scRNA)-seq identified state-specific drivers and captured the emergence of similar TCF1+ progenitor-like populations at an early branch point, at which functional and dysfunctional T cells diverge. Our atlas of CD8 T cell states will facilitate mechanistic studies of T cell immunity and translational efforts.

Pancreatic cancer prognosis is predicted by an ATAC-array technology for assessing chromatin accessibility

Unlike other malignancies, therapeutic options in pancreatic ductal adenocarcinoma (PDAC) are largely limited to cytotoxic chemotherapy without the benefit of molecular markers predicting response. Here we report tumor-cell-intrinsic chromatin accessibility patterns of treatment-naïve surgically resected PDAC tumors that were subsequently treated with (Gem)/Abraxane adjuvant chemotherapy. By ATAC-seq analyses of EpCAM+ PDAC malignant epithelial cells sorted from 54 freshly resected human tumors, we show here the discovery of a signature of 1092 chromatin loci displaying differential accessibility between patients with disease free survival (DFS) < 1 year and patients with DFS > 1 year. Analyzing transcription factor (TF) binding motifs within these loci, we identify two TFs (ZKSCAN1 and HNF1b) displaying differential nuclear localization between patients with short vs. long DFS. We further develop a chromatin accessibility microarray methodology termed "ATAC-array", an easy-to-use platform obviating the time and cost of next generation sequencing. Applying this methodology to the original ATAC-seq libraries as well as independent libraries generated from patient-derived organoids, we validate ATAC-array technology in both the original ATAC-seq cohort as well as in an independent validation cohort. We conclude that PDAC prognosis can be predicted by ATAC-array, which represents a low-cost, clinically feasible technology for assessing chromatin accessibility profiles.

Single-cell sequencing links multiregional immune landscapes and tissue-resident T cells in ccRCC to tumor topology and therapy efficacy

Clear cell renal cell carcinomas (ccRCCs) are highly immune infiltrated, but the effect of immune heterogeneity on clinical outcome in ccRCC has not been fully characterized. Here we perform paired single-cell RNA (scRNA) and T cell receptor (TCR) sequencing of 167,283 cells from multiple tumor regions, lymph node, normal kidney, and peripheral blood of two immune checkpoint blockade (ICB)-naïve and four ICB-treated patients to map the ccRCC immune landscape. We detect extensive heterogeneity within and between patients, with enrichment of CD8A+ tissue-resident T cells in a patient responsive to ICB and tumor-associated macrophages (TAMs) in a resistant patient. A TCR trajectory framework suggests distinct T cell differentiation pathways between patients responding and resistant to ICB. Finally, scRNA-derived signatures of tissue-resident T cells and TAMs are associated with response to ICB and targeted therapies across multiple independent cohorts. Our study establishes a multimodal interrogation of the cellular programs underlying therapeutic efficacy in ccRCC.

FXR mediates T cell-intrinsic responses to reduced feeding during infection

Reduced nutrient intake is a widely conserved manifestation of sickness behavior with poorly characterized effects on adaptive immune responses. During infectious challenges, naive T cells encountering their cognate antigen become activated and differentiate into highly proliferative effector T cells. Despite their evident metabolic shift upon activation, it remains unclear how effector T cells respond to changes in nutrient availability in vivo. Here, we show that spontaneous or imposed feeding reduction during infection decreases the numbers of splenic lymphocytes. Effector T cells showed cell-intrinsic responses dependent on the nuclear receptor Farnesoid X Receptor (FXR). Deletion of FXR in T cells prevented starvation-induced loss of lymphocytes and increased effector T cell fitness in nutrient-limiting conditions, but imparted greater weight loss to the host. FXR deficiency increased the contribution of glutamine and fatty acids toward respiration and enhanced cell survival under low-glucose conditions. Provision of glucose during anorexia of infection rescued effector T cells, suggesting that this sugar is a limiting nutrient for activated lymphocytes and that alternative fuel usage may affect cell survival in starved animals. Altogether, we identified a mechanism by which the host scales immune responses according to food intake, featuring FXR as a T cell-intrinsic sensor.

The Transcription Factor Foxp3 Shapes Regulatory T Cell Identity by Tuning the Activity of trans-Acting Intermediaries

Regulatory T (Treg) cell identity is defined by the lineage-specifying transcription factor (TF) Foxp3. Here we examined mechanisms of Foxp3 function by leveraging naturally occurring genetic variation in wild-derived inbred mice, which enables the identification of DNA sequence motifs driving epigenetic features. Chromatin accessibility, TF binding, and gene expression patterns in resting and activated subsets of Treg cells, conventional CD4 T cells, and cells expressing a Foxp3 reporter null allele revealed that the majority of Foxp3-dependent changes occurred at sites not bound by Foxp3. Chromatin accessibility of these indirect Foxp3 targets depended on the presence of DNA binding motifs for other TFs, including TCF1. Foxp3 expression correlated with decreased TCF1 and reduced accessibility of TCF1-bound chromatin regions. Deleting one copy of the Tcf7 gene recapitulated Foxp3-dependent negative regulation of chromatin accessibility. Thus, Foxp3 defines Treg cell identity in a largely indirect manner by fine-tuning the activity of other major chromatin remodeling TFs such as TCF1.

Author Correction: FOXA1 mutations alter pioneering activity, differentiation and prostate cancer phenotypes

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

High-Resolution In Vivo Identification of miRNA Targets by Halo-Enhanced Ago2 Pull-Down

The identification of microRNA (miRNA) targets by Ago2 crosslinking-immunoprecipitation (CLIP) methods has provided major insights into the biology of this important class of non-coding RNAs. However, these methods are technically challenging and not easily applicable to an in vivo setting. To overcome these limitations and facilitate the investigation of miRNA functions in vivo, we have developed a method based on a genetically engineered mouse harboring a conditional Halo-Ago2 allele expressed from the endogenous Ago2 locus. By using a resin conjugated to the HaloTag ligand, Ago2-miRNA-mRNA complexes can be purified from cells and tissues expressing the endogenous Halo-Ago2 allele. We demonstrate the reproducibility and sensitivity of this method in mouse embryonic stem cells, developing embryos, adult tissues, and autochthonous mouse models of human brain and lung cancers. This method and the datasets we have generated will facilitate the characterization of miRNA-mRNA networks in vivo under physiological and pathological conditions.

PI3K Inhibition Activates SGK1 via a Feedback Loop to Promote Chromatin-Based Regulation of ER-Dependent Gene Expression

The PI3K pathway integrates extracellular stimuli to phosphorylate effectors such as AKT and serum-and-glucocorticoid-regulated kinase (SGK1). We have previously reported that the PI3K pathway regulates estrogen receptor (ER)-dependent transcription in breast cancer through the phosphorylation of the lysine methyltransferase KMT2D by AKT. Here, we show that PI3Kα inhibition, via a negative-feedback loop, activates SGK1 to promote chromatin-based regulation of ER-dependent transcription. PI3K/AKT inhibitors activate ER, which promotes SGK1 transcription through direct binding to its promoter. Elevated SGK1, in turn, phosphorylates KMT2D, suppressing its function, leading to a loss of methylation of lysine 4 on histone H3 (H3K4) and a repressive chromatin state at ER loci to attenuate ER activity. Thus, SGK1 regulates the chromatin landscape and ER-dependent transcription via the direct phosphorylation of KMT2D. These findings reveal an ER-SGK1-KMT2D signaling circuit aimed to attenuate ER response through a role for SGK1 to program chromatin and ER transcriptional output.

A histone code for inducible transcription in immune responses

Complex organisms have been subjected to intense selective pressure by host-pathogen coevolution to adapt robust immune responses to pathogen sensing. These responses occur by inducing specific genes within the context of large genomes condensed into chromatin. Despite general description of the chromatin changes that occur across inducible genes, little is known of how specific chromatin features, including histone post-translational modifications (PTM), functionally contribute to transcriptional output of responsive genes.

We have described two “signaling-to-chromatin” pathways leading to phosphorylation of histone H3 at residues S28 and S31 that are “read out” by chromatin regulatory factors to augment transcription. H3S28 phosphorylation drives early chromatin activation preceding transcription. This modification delineates expansive chromatin architectural domains containing responsive genes. We are pursuing the hypothesis that H3S28 phosphorylation increases chromatin interaction dynamics within the compartment to favor specific enhancer-promoter interactions and concentrate transcription factors. H3.3S31 is co-transcriptionally phosphorylated along the bodies of induced genes, and coordinately stimulates co-activators and ejects repressors to augment transcription.

We hypothesize that these stimulation-dependent histone phosphorylations act synergistically as a dedicated histone code selectively employed at stimulation responsive genes in macrophages and B cells, with potential for involvement in diverse cell types.

Our data suggest that co-option of these signaling pathways may contribute to lymphomagenesis, and their disruption could represent novel therapeutic strategies.

HyperTRIBE uncovers increased MUSASHI-2 RNA binding activity and differential regulation in leukemic stem cells

The cell-context dependency for RNA binding proteins (RBPs) mediated control of stem cell fate remains to be defined. Here we adapt the HyperTRIBE method using an RBP fused to a Drosophila RNA editing enzyme (ADAR) to globally map the mRNA targets of the RBP MSI2 in mammalian adult normal and malignant stem cells. We reveal a unique MUSASHI-2 (MSI2) mRNA binding network in hematopoietic stem cells that changes during transition to multipotent progenitors. Additionally, we discover a significant increase in RNA binding activity of MSI2 in leukemic stem cells compared with normal hematopoietic stem and progenitor cells, resulting in selective regulation of MSI2's oncogenic targets. This provides a basis for MSI2 increased dependency in leukemia cells compared to normal cells. Moreover, our study provides a way to measure RBP function in rare cells and suggests that RBPs can achieve differential binding activity during cell state transition independent of gene expression.

Non-redundant ISGF3 Components Promote NK Cell Survival in an Auto-regulatory Manner during Viral Infection

Natural killer (NK) cells are innate lymphocytes that possess adaptive features, including antigen-specific clonal expansion and long-lived memory responses. Although previous work demonstrated that type I interferon (IFN) signaling is crucial for NK cell expansion and memory cell formation following mouse cytomegalovirus (MCMV) infection, the global transcriptional mechanisms underlying type I IFN-mediated responses remained to be determined. Here, we demonstrate that among the suite of transcripts induced in activated NK cells, IFN-α is necessary and sufficient to promote expression of its downstream transcription factors STAT1, STAT2, and IRF9, via an auto-regulatory, feedforward loop. Similar to STAT1 deficiency, we show that STAT2- or IRF9-deficient NK cells are defective in their ability to expand following MCMV infection, in part because of diminished survival rather than an inability to proliferate. Thus, our findings demonstrate that individual ISGF3 components are crucial cell-autonomous and non-redundant regulators of the NK cell response to viral infection.

Using RNA-seq and ChIP-seq, Geary et al. investigate the impacts of type I interferon on NK cells during MCMV infection and demonstrate crucial and non-redundant roles for STAT1, STAT2, and IRF9 in promoting cytotoxicity and survival of antiviral NK cells.

Chromatin-informed inference of transcriptional programs in gynecologic and basal breast cancers

Chromatin accessibility data can elucidate the developmental origin of cancer cells and reveal the enhancer landscape of key oncogenic transcriptional regulators. We develop a computational strategy called PSIONIC (patient-specific inference of networks informed by chromatin) to combine chromatin accessibility data with large tumor expression data and model the effect of enhancers on transcriptional programs in multiple cancers. We generate a new ATAC-seq data profiling chromatin accessibility in gynecologic and basal breast cancer cell lines and apply PSIONIC to 723 patient and 96 cell line RNA-seq profiles from ovarian, uterine, and basal breast cancers. Our computational framework enables us to share information across tumors to learn patient-specific TF activities, revealing regulatory differences between and within tumor types. PSIONIC-predicted activity for MTF1 in cell line models correlates with sensitivity to MTF1 inhibition, showing the potential of our approach for personalized therapy. Many identified TFs are significantly associated with survival outcome. To validate PSIONIC-derived prognostic TFs, we perform immunohistochemical analyses in 31 uterine serous tumors for ETV6 and 45 basal breast tumors for MITF and confirm that the corresponding protein expression patterns are also significantly associated with prognosis.

BindSpace decodes transcription factor binding signals by large-scale sequence embedding

Decoding transcription factor (TF) binding signals in genomic DNA is a fundamental problem. Here we present a prediction model called BindSpace that learns to embed DNA sequences and TF class/family labels into the same space. By training on binding data for hundreds of TFs and embedding over 1M DNA sequences, BindSpace achieves state-of-the-art multiclass binding prediction performance, in vitro and in vivo, and can distinguish signals of closely related TFs.

Natural Genetic Variation Reveals Key Features of Epigenetic and Transcriptional Memory in Virus-Specific CD8 T Cells

Stable changes in chromatin states and gene expression in cells of the immune system form the basis for memory of infections and other challenges. Here, we used naturally occurring cis-regulatory variation in wild-derived inbred mouse strains to explore the mechanisms underlying long-lasting versus transient gene regulation in CD8 T cells responding to acute viral infection. Stably responsive DNA elements were characterized by dramatic and congruent chromatin remodeling events affecting multiple neighboring sites and required distinct transcription factor (TF) binding motifs for their accessibility. Specifically, we found that cooperative recruitment of T-box and Runx family transcription factors to shared targets mediated stable chromatin remodeling upon T cell activation. Our observations provide insights into the molecular mechanisms driving virus-specific CD8 T cell responses and suggest a general mechanism for the formation of transcriptional and epigenetic memory applicable to other immune and non-immune cells.

Transcription factor Foxp1 regulates Foxp3 chromatin binding and coordinates regulatory T cell function

Regulatory T cells (T_reg cells), whose differentiation and function are controlled by transcription factor Foxp3, express the closely related family member Foxp1. Here we explored Foxp1 function in T_reg cells. We found that a large number of Foxp3-bound genomic sites in T_reg cells were occupied by Foxp1 in both T_reg cells and conventional T cells (T_conv cells). In T_reg cells, Foxp1 markedly increased Foxp3 binding to these sites. Foxp1 deficiency in T_reg cells resulted in their impaired function and competitive fitness, associated with markedly reduced CD25 expression and interleukin-2 (IL-2) responsiveness, diminished CTLA-4 expression and increased SATB1 expression. The characteristic expression patterns of CD25, Foxp3 and CTLA-4 in T_reg cells were fully or partially rescued by strong IL-2 signaling. Our studies suggest that Foxp1 serves an essential non-redundant function in T_reg cells by enforcing Foxp3-mediated regulation of gene expression and enabling efficient IL-2 signaling in these cells.

Widespread intronic polyadenylation inactivates tumour suppressor genes in leukaemia

DNA mutations are known cancer drivers. Here we investigated whether mRNA events that are upregulated in cancer can functionally mimic the outcome of genetic alterations. RNA sequencing or 3'-end sequencing techniques were applied to normal and malignant B cells from 59 patients with chronic lymphocytic leukaemia (CLL)^1-3. We discovered widespread upregulation of truncated mRNAs and proteins in primary CLL cells that were not generated by genetic alterations but instead occurred by intronic polyadenylation. Truncated mRNAs caused by intronic polyadenylation were recurrent (n = 330) and predominantly affected genes with tumour-suppressive functions. The truncated proteins generated by intronic polyadenylation often lack the tumour-suppressive functions of the corresponding full-length proteins (such as DICER and FOXN3), and several even acted in an oncogenic manner (such as CARD11, MGA and CHST11). In CLL, the inactivation of tumour-suppressor genes by aberrant mRNA processing is substantially more prevalent than the functional loss of such genes through genetic events. We further identified new candidate tumour-suppressor genes that are inactivated by intronic polyadenylation in leukaemia and by truncating DNA mutations in solid tumours^4,5. These genes are understudied in cancer, as their overall mutation rates are lower than those of well-known tumour-suppressor genes. Our findings show the need to go beyond genomic analyses in cancer diagnostics, as mRNA events that are silent at the DNA level are widespread contributors to cancer pathogenesis through the inactivation of tumour-suppressor genes.

Abstract LB-A04: Transcriptional regulatory programs in gynecological cancers

Cancer cells acquire genetic and epigenetic alterations that often lead to dysregulation of oncogenic signal transduction pathways, which in turn alter downstream transcriptional programs. The Cancer Genome Atlas (TCGA) has studied several of the most common and aggressive gynecologic tumors including high-grade serous ovarian carcinomas (HGSOC), uterine carcinosarcoma (UCS), and the serous-like subset of endometrial cancer (UCEC), together with basal breast cancer, which shares many genomic features with serous ovarian tumors. These tumors all lack accurate predictors of response and resistance and share an unmet need for adequate treatment of recurrent disease. We developed a multitask learning framework for integrating regulatory sequence from ATAC-mapped promoters and enhancers with RNA-seq data from patient tumors in order to infer transcription factor (TF) regulatory activities and explore similarities and differences between endometrial, ovarian, and basal breast tumors. We showed that our multitask learning framework enables us to selectively share the information across tumors and strongly improves the accuracy of gene expression prediction models for gynecological and basal breast tumors. Our analysis identified histologic type specific and common TF regulators of gene expression as well as predicted distinct dysregulated transcriptional regulators downstream of somatic alterations in these different cancers. Moreover, many of the identified TF regulators were significantly associated with survival outcome within the histological subtype. Computationally dissecting the role of TFs in these cancers may ultimately lead to new therapeutics tailored to subtype or individual.

Citation Format: Hatice U. Osmanbeyoglu, Petar Jelinic, Douglas Levine, Christina S. Leslie. Transcriptional regulatory programs in gynecological cancers [abstract]. In: Proceedings of the AACR-NCI-EORTC International Conference: Molecular Targets and Cancer Therapeutics; 2017 Oct 26-30; Philadelphia, PA. Philadelphia (PA): AACR; Mol Cancer Ther 2018;17(1 Suppl):Abstract nr LB-A04.

The SWI/SNF Protein PBRM1 Restrains VHL-Loss-Driven Clear Cell Renal Cell Carcinoma

PBRM1 is the second most commonly mutated gene after VHL in clear cell renal cell carcinoma (ccRCC). However, the biological consequences of PBRM1 mutations for kidney tumorigenesis are unknown. Here, we find that kidney-specific deletion of Vhl and Pbrm1, but not either gene alone, results in bilateral, multifocal, transplantable clear cell kidney cancers. PBRM1 loss amplified the transcriptional outputs of HIF1 and STAT3 incurred by Vhl deficiency. Analysis of mouse and human ccRCC revealed convergence on mTOR activation, representing the third driver event after genetic inactivation of VHL and PBRM1. Our study reports a physiological preclinical ccRCC mouse model that recapitulates somatic mutations in human ccRCC and provides mechanistic and therapeutic insights into PBRM1 mutated subtypes of human ccRCC.

Ets transcription factor GABP controls T cell homeostasis and immunity

Peripheral T cells are maintained in the absence of vigorous stimuli, and respond to antigenic stimulation by initiating cell cycle progression and functional differentiation. Here we show that depletion of the Ets family transcription factor GA-binding protein (GABP) in T cells impairs T-cell homeostasis. In addition, GABP is critically required for antigen-stimulated T-cell responses in vitro and in vivo. Transcriptome and genome-wide GABP-binding site analyses identify GABP direct targets encoding proteins involved in cellular redox balance and DNA replication, including the Mcm replicative helicases. These findings show that GABP has a nonredundant role in the control of T-cell homeostasis and immunity.

T cells need to undergo rapid proliferation in response to antigenic stimulation. Here the authors show that the Ets family transcription factor GABP is required for T-cell homeostasis and response to infection by inducing Mcm3 and Mcm5 expression and enabling S-phase entry.

ILC1 Confer Early Host Protection at Initial Sites of Viral Infection

Infection is restrained by the concerted activation of tissue-resident and circulating immune cells. Whether tissue-resident lymphocytes confer early antiviral immunity at local sites of primary infection prior to the initiation of circulating responses is not well understood. Furthermore, the kinetics of initial antiviral responses at sites of infection remain unclear. Here, we show that tissue-resident type 1 innate lymphoid cells (ILC1) serve an essential early role in host immunity through rapid production of interferon (IFN)-γ following viral infection. Ablation of Zfp683-dependent liver ILC1 lead to increased viral load in the presence of intact adaptive and innate immune cells critical for mouse cytomegalovirus (MCMV) clearance. Swift production of interleukin (IL)-12 by tissue-resident XCR1⁺ conventional dendritic cells (cDC1) promoted ILC1 production of IFN-γ in a STAT4-dependent manner to limit early viral burden. Thus, ILC1 contribute an essential role in viral immunosurveillance at sites of initial infection in response to local cDC1-derived proinflammatory cytokines.

Abstract LB-271: SplashRNA, a sequential classification algorithm for ultra-potent RNAi

We present SplashRNA, a sequential classifier - analogous to face detection algorithms - to predict ultra-potent microRNA-based short hairpin RNAs (shRNAs) for virtually any gene. Trained on existing and novel large-scale datasets, SplashRNA outperforms previous algorithms and reliably predicts the most efficient shRNAs for a given gene. Combined with the optimized miR-E backbone, &gt;90% of high-scoring SplashRNA predictions trigger &gt;85% protein knockdown when expressed from a single genomic integration. SplashRNA can significantly improve the accuracy of loss-of-function genetics studies and facilitates the generation of compact shRNA libraries. The open source SplashRNA platform completes the RNAi toolkit to harness microRNA-based shRNAs for robust single-gene and multiplexed inducible and reversible target inhibition.

Citation Format: Raphael Pelossof, Lauren Fairchild, Christina S. Leslie, Christof Fellmann. SplashRNA, a sequential classification algorithm for ultra-potent RNAi [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2017; 2017 Apr 1-5; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2017;77(13 Suppl):Abstract nr LB-271. doi:10.1158/1538-7445.AM2017-LB-271

Chromatin states define tumour-specific T cell dysfunction and reprogramming

Tumour-specific CD8 T cells in solid tumours are dysfunctional, allowing tumours to progress. The epigenetic regulation of T cell dysfunction and therapeutic reprogrammability (for example, to immune checkpoint blockade) is not well understood. Here we show that T cells in mouse tumours differentiate through two discrete chromatin states: a plastic dysfunctional state from which T cells can be rescued, and a fixed dysfunctional state in which the cells are resistant to reprogramming. We identified surface markers associated with each chromatin state that distinguished reprogrammable from non-reprogrammable PD1^hi dysfunctional T cells within heterogeneous T cell populations from tumours in mice; these surface markers were also expressed on human PD1^hi tumour-infiltrating CD8 T cells. Our study has important implications for cancer immunotherapy as we define key transcription factors and epigenetic programs underlying T cell dysfunction and surface markers that predict therapeutic reprogrammability.

An integrated model for detecting significant chromatin interactions from high-resolution Hi-C data

Here we present HiC-DC, a principled method to estimate the statistical significance (P values) of chromatin interactions from Hi-C experiments. HiC-DC uses hurdle negative binomial regression account for systematic sources of variation in Hi-C read counts—for example, distance-dependent random polymer ligation and GC content and mappability bias—and model zero inflation and overdispersion. Applied to high-resolution Hi-C data in a lymphoblastoid cell line, HiC-DC detects significant interactions at the sub-topologically associating domain level, identifying potential structural and regulatory interactions supported by CTCF binding sites, DNase accessibility, and/or active histone marks. CTCF-associated interactions are most strongly enriched in the middle genomic distance range (∼700 kb–1.5 Mb), while interactions involving actively marked DNase accessible elements are enriched both at short (<500 kb) and longer (>1.5 Mb) genomic distances. There is a striking enrichment of longer-range interactions connecting replication-dependent histone genes on chromosome 6, potentially representing the chromatin architecture at the histone locus body.

Genome-wide chromosome conformation capture has helped us identify features of genome topology influencing biology but requires careful statistical analysis. Here the authors present HiC-DC, a bioinformatics method that can detect statistically significant regulatory interactions.

GuideScan software for improved single and paired CRISPR guide RNA design

We present GuideScan software for the design of CRISPR guide RNA libraries that can be used to edit coding and noncoding genomic regions. GuideScan produces high-density sets of guide RNAs (gRNAs) for single- and paired-gRNA genome-wide screens. We also show that the trie data structure of GuideScan enables the design of gRNAs that are more specific than those designed by existing tools.

PI3K pathway regulates ER-dependent transcription in breast cancer through the epigenetic regulator KMT2D

Activating mutations in PIK3CA, the gene encoding phosphoinositide-(3)-kinase α (PI3Kα), are frequently found in estrogen receptor (ER)-positive breast cancer. PI3Kα inhibitors, now in late-stage clinical development, elicit a robust compensatory increase in ER-dependent transcription that limits therapeutic efficacy. We investigated the chromatin-based mechanisms leading to the activation of ER upon PI3Kα inhibition. We found that PI3Kα inhibition mediates an open chromatin state at the ER target loci in breast cancer models and clinical samples. KMT2D, a histone H3 lysine 4 methyltransferase, is required for FOXA1, PBX1, and ER recruitment and activation. AKT binds and phosphorylates KMT2D, attenuating methyltransferase activity and ER function, whereas PI3Kα inhibition enhances KMT2D activity. These findings uncover a mechanism that controls the activation of ER by the posttranslational modification of epigenetic regulators, providing a rationale for epigenetic therapy in ER-positive breast cancer.

Prediction of potent shRNAs with a sequential classification algorithm

We present SplashRNA, a sequential classifier to predict potent microRNA-based short hairpin RNAs (shRNAs). Trained on published and novel datasets, SplashRNA outperforms previous algorithms and reliably predicts the most efficient shRNAs for a given gene. Combined with an optimized miR-E backbone, >90% of high-scoring SplashRNA predictions trigger >85% protein knockdown when expressed from a single genomic integration. SplashRNA can significantly improve the accuracy of loss-of-function genetics studies and facilitates the generation of compact shRNA libraries.

Stage-Specific Human Induced Pluripotent Stem Cells Map the Progression of Myeloid Transformation to Transplantable Leukemia

Myeloid malignancy is increasingly viewed as a disease spectrum, comprising hematopoietic disorders that extend across a phenotypic continuum ranging from clonal hematopoiesis to myelodysplastic syndrome (MDS) and acute myeloid leukemia (AML). In this study, we derived a collection of induced pluripotent stem cell (iPSC) lines capturing a range of disease stages encompassing preleukemia, low-risk MDS, high-risk MDS, and secondary AML. Upon their differentiation, we found hematopoietic phenotypes of graded severity and/or stage specificity that together delineate a phenotypic roadmap of disease progression culminating in serially transplantable leukemia. We also show that disease stage transitions, both reversal and progression, can be modeled in this system using genetic correction or introduction of mutations via CRISPR/Cas9 and that this iPSC-based approach can be used to uncover disease-stage-specific responses to drugs. Our study therefore provides insight into the cellular events demarcating the initiation and progression of myeloid transformation and a new platform for testing genetic and pharmacological interventions.