An integrative ENCODE resource for cancer genomics

Exploring the transcriptional cooperation between RUNX2 and its associated elncRNA RAIN

Recent insights into the mechanisms controlling gene expression identified enhancer-associated long non-coding RNAs (elncRNAs) as master players of transcription in cancers. RUNX2, a mammalian RUNT-related transcription factor, is increasingly recognized in cancer biology for its role in supporting survival and progression also in thyroid cancer (TC). We recently identified, within the RUNX2 locus, a novel elncRNA that we named RAIN (RUNX2 associated intergenic lncRNA). We showed that RAIN and RUNX2 expression correlate in TC, both in vitro and in vivo, and that RAIN promotes RUNX2 expression by interacting with and affecting the activity of the RUNX2 P2 promoter through two distinct mechanisms. Here, we took forward these observations to explore the genome-wide transcriptional function of RAIN and its contribution to the RUNX2-dependent gene expression program in TC. By combining multiple omics data, we demonstrated that RAIN functionally cooperates with RUNX2 to the regulation of a subset of functionally related genes involved in promoting matrix remodeling, migration, and loss of differentiation. We showed that RAIN interacts with RUNX2 and its expression is required for the efficient recruitment of this TF to its target regulatory regions. In addition, our data revealed that besides RUNX2, RAIN governs a hierarchically organized complex transcriptional program by controlling a core of cancer-associated TFs that, in turn, orchestrate the expression of downstream genes. This evidence indicates that the functional cooperation observed between RAIN and RUNX2 can be a diffuse work mechanism for this elncRNA.

Competition between two HUSH complexes orchestrates the immune response to retroelement invasion

The human silencing hub (HUSH) preserves genome integrity through the epigenetic repression of invasive genetic elements. However, despite our understanding of HUSH as an obligate complex of three subunits, only loss of MPP8 or Periphilin, but not TASOR, triggers interferon signaling following derepression of endogenous retroelements. Here, we resolve this paradox by characterizing a second HUSH complex that shares MPP8 and Periphilin but assembles around TASOR2, an uncharacterized paralog of TASOR. Whereas HUSH represses LINE-1 retroelements marked by the repressive histone modification H3K9me3, HUSH2 is recruited by the transcription factor IRF2 to repress interferon-stimulated genes. Mechanistically, HUSH-mediated retroelement silencing sequesters the limited pool of the shared subunits MPP8 and Periphilin, preventing TASOR2 from forming HUSH2 complexes and hence relieving the HUSH2-mediated repression of interferon-stimulated genes. Thus, competition between two HUSH complexes intertwines retroelement silencing with the induction of an immune response, coupling epigenetic and immune aspects of genome defense.

Replication timing alterations are associated with mutation acquisition during breast and lung cancer evolution

During each cell cycle, the process of DNA replication timing is tightly regulated to ensure the accurate duplication of the genome. The extent and significance of alterations in this process during malignant transformation have not been extensively explored. Here, we assess the impact of altered replication timing (ART) on cancer evolution by analysing replication-timing sequencing of cancer and normal cell lines and 952 whole-genome sequenced lung and breast tumours. We find that 6%-18% of the cancer genome exhibits ART, with regions with a change from early to late replication displaying an increased mutation rate and distinct mutational signatures. Whereas regions changing from late to early replication contain genes with increased expression and present a preponderance of APOBEC3-mediated mutation clusters and associated driver mutations. We demonstrate that ART occurs relatively early during cancer evolution and that ART may have a stronger correlation with mutation acquisition than alterations in chromatin structure.

Behaviors of nucleosomes with mutant histone H4s in euchromatic domains of living human cells

Since Robert Feulgen first stained DNA in the cell, visualizing genome chromatin has been a central issue in cell biology to uncover how chromatin is organized and behaves in the cell. To approach this issue, we have developed single-molecule imaging of nucleosomes, a basic unit of chromatin, to unveil local nucleosome behavior in living cells. In this study, we investigated behaviors of nucleosomes with various histone H4 mutants in living HeLa cells to address the role of H4 tail acetylation, including H4K16Ac and others, which are generally associated with more transcriptionally active chromatin regions. We ectopically expressed wild-type (wt) or mutated H4s (H4K16 point; H4K5,8,12,16 quadruple; and H4 tail deletion) fused with HaloTag in HeLa cells. Cells that expressed wtH4-Halo, H4K16-Halo mutants, and multiple H4-Halo mutants had euchromatin-concentrated distribution. Consistently, the genomic regions of the wtH4-Halo nucleosomes corresponded to Hi-C contact domains (or topologically associating domains, TADs) with active chromatin marks (A-compartment). Utilizing single-nucleosome imaging, we found that none of the H4 deacetylation or acetylation mimicked H4 mutants altered the overall local nucleosome motion. This finding suggests that H4 mutant nucleosomes embedded in the condensed euchromatic domains with excess endogenous H4 nucleosomes cannot cause an observable change in the local motion. Interestingly, H4 with four lysine-to-arginine mutations displayed a substantial freely diffusing fraction in the nucleoplasm, whereas H4 with a truncated N-terminal tail was incorporated in heterochromatic regions as well as euchromatin. Our study indicates the power of single-nucleosome imaging to understand individual histone/nucleosome behavior reflecting chromatin environments in living cells.

Machine learning on multiple epigenetic features reveals H3K27Ac as a driver of gene expression prediction across patients with glioblastoma

Cancer cells show remarkable plasticity and can switch lineages in response to the tumor microenvironment. Cellular plasticity drives invasiveness and metastasis and helps cancer cells to evade therapy by developing resistance to radiation and cytotoxic chemotherapy. Increased understanding of cell fate determination through epigenetic reprogramming is critical to discover how cancer cells achieve transcriptomic and phenotypic plasticity. Glioblastoma is a perfect example of cancer evolution where cells retain an inherent level of plasticity through activation or maintenance of progenitor developmental programs. However, the principles governing epigenetic drivers of cellular plasticity in glioblastoma remain poorly understood. Here, using machine learning (ML) we employ cross-patient prediction of transcript expression using a combination of epigenetic features (ATAC-seq, CTCF ChIP-seq, RNAPII ChIP-seq, H3K27Ac ChIP-seq, and RNA-seq) of glioblastoma stem cells (GSCs). We investigate different ML and deep learning (DL) models for this task and build our final pipeline using XGBoost. The model trained on one patient generalizes to another one suggesting that the epigenetic signals governing gene transcription are consistent across patients even if GSCs can be very different. We demonstrate that H3K27Ac is the epigenetic feature providing the most significant contribution to cross-patient prediction of gene expression. In addition, using H3K27Ac signals from patients-derived GSCs, we can predict gene expression of human neural crest stem cells suggesting a shared developmental epigenetic trajectory between subpopulations of these malignant and benign stem cells. Our cross-patient ML/DL models determine weighted patterns of influence of epigenetic marks on gene expression across patients with glioblastoma and between GSCs and neural crest stem cells. We propose that broader application of this analysis could reshape our view of glioblastoma tumor evolution and inform the design of new epigenetic targeting therapies.

Extensive long-range polycomb interactions and weak compartmentalization are hallmarks of human neuronal 3D genome

Chromatin architecture regulates gene expression and shapes cellular identity, particularly in neuronal cells. Specifically, polycomb group (PcG) proteins enable establishment and maintenance of neuronal cell type by reorganizing chromatin into repressive domains that limit the expression of fate-determining genes and sustain distinct gene expression patterns in neurons. Here, we map the 3D genome architecture in neuronal and non-neuronal cells isolated from the Wernicke's area of four human brains and comprehensively analyze neuron-specific aspects of chromatin organization. We find that genome segregation into active and inactive compartments is greatly reduced in neurons compared to other brain cells. Furthermore, neuronal Hi-C maps reveal strong long-range interactions, forming a specific network of PcG-mediated contacts in neurons that is nearly absent in other brain cells. These interacting loci contain developmental transcription factors with repressed expression in neurons and other mature brain cells. But only in neurons, they are rich in bivalent promoters occupied by H3K4me3 histone modification together with H3K27me3, which points to a possible functional role of PcG contacts in neurons. Importantly, other layers of chromatin organization also exhibit a distinct structure in neurons, characterized by an increase in short-range interactions and a decrease in long-range ones.

HNF4A and HNF1A exhibit tissue specific target gene regulation in pancreatic beta cells and hepatocytes

HNF4A and HNF1A encode transcription factors that are important for the development and function of the pancreas and liver. Mutations in both genes have been directly linked to Maturity Onset Diabetes of the Young (MODY) and type 2 diabetes (T2D) risk. To better define the pleiotropic gene regulatory roles of HNF4A and HNF1A, we generated a comprehensive genome-wide map of their binding targets in pancreatic and hepatic cells using ChIP-Seq. HNF4A was found to bind and regulate known (ACY3, HAAO, HNF1A, MAP3K11) and previously unidentified (ABCD3, CDKN2AIP, USH1C, VIL1) loci in a tissue-dependent manner. Functional follow-up highlighted a potential role for HAAO and USH1C as regulators of beta cell function. Unlike the loss-of-function HNF4A/MODY1 variant I271fs, the T2D-associated HNF4A variant (rs1800961) was found to activate AKAP1, GAD2 and HOPX gene expression, potentially due to changes in DNA-binding affinity. We also found HNF1A to bind to and regulate GPR39 expression in beta cells. Overall, our studies provide a rich resource for uncovering downstream molecular targets of HNF4A and HNF1A that may contribute to beta cell or hepatic cell (dys)function, and set up a framework for gene discovery and functional validation.

bsgenova: an accurate, robust, and fast genotype caller for bisulfite-sequencing data

BACKGROUND

Bisulfite sequencing (BS-Seq) is a fundamental technique for characterizing DNA methylation profiles. Genotype calling from bisulfite-converted BS-Seq data allows allele-specific methylation analysis and the concurrent exploration of genetic and epigenetic profiles. Despite various methods have been proposed, single nucleotide polymorphisms (SNPs) calling from BS-Seq data, particularly for SNPs on chromosome X and in the presence of contaminative data, poses ongoing challenges.

RESULTS

We introduce bsgenova, a novel SNP caller tailored for bisulfite sequencing data, employing a Bayesian multinomial model. The performance of bsgenova is assessed by comparing SNPs called from real-world BS-Seq data with those from corresponding whole-genome sequencing (WGS) data across three human cell lines. bsgenova is both sensitive and precise, especially for chromosome X, compared with three existing methods. Moreover, in the presence of low-quality reads, bsgenova outperforms other methods notably. In addition, bsgenova is meticulously implemented, leveraging matrix imputation and multi-process parallelization. Compared to existing methods, bsgenova stands out for its speed and efficiency in memory and disk usage. Furthermore, bsgenova integrates bsextractor, a methylation extractor, enhancing its flexibility and expanding its utility.

CONCLUSIONS

We introduce bsgenova for SNP calling from bisulfite-sequencing data. The source code is available at https://github.com/hippo-yf/bsgenova under license GPL-3.0.

Single-cell long-read sequencing-based mapping reveals specialized splicing patterns in developing and adult mouse and human brain

RNA isoforms influence cell identity and function. However, a comprehensive brain isoform map was lacking. We analyze single-cell RNA isoforms across brain regions, cell subtypes, developmental time points and species. For 72% of genes, full-length isoform expression varies along one or more axes. Splicing, transcription start and polyadenylation sites vary strongly between cell types, influence protein architecture and associate with disease-linked variation. Additionally, neurotransmitter transport and synapse turnover genes harbor cell-type variability across anatomical regions. Regulation of cell-type-specific splicing is pronounced in the postnatal day 21-to-postnatal day 28 adolescent transition. Developmental isoform regulation is stronger than regional regulation for the same cell type. Cell-type-specific isoform regulation in mice is mostly maintained in the human hippocampus, allowing extrapolation to the human brain. Conversely, the human brain harbors additional cell-type specificity, suggesting gain-of-function isoforms. Together, this detailed single-cell atlas of full-length isoform regulation across development, anatomical regions and species reveals an unappreciated degree of isoform variability across multiple axes.

Interpretable deep learning reveals the role of an E-box motif in suppressing somatic hypermutation of AGCT motifs within human immunoglobulin variable regions

Introduction

Somatic hypermutation (SHM) of immunoglobulin variable (V) regions by activation induced deaminase (AID) is essential for robust, long-term humoral immunity against pathogen and vaccine antigens. AID mutates cytosines preferentially within WRCH motifs (where W=A or T, R=A or G and H=A, C or T). However, it has been consistently observed that the mutability of WRCH motifs varies substantially, with large variations in mutation frequency even between multiple occurrences of the same motif within a single V region. This has led to the notion that the immediate sequence context of WRCH motifs contributes to mutability. Recent studies have highlighted the potential role of local DNA sequence features in promoting mutagenesis of AGCT, a commonly mutated WRCH motif. Intriguingly, AGCT motifs closer to 5' ends of V regions, within the framework 1 (FW1) sub-region1, mutate less frequently, suggesting an SHM-suppressing sequence context.

Methods

Here, we systematically examined the basis of AGCT positional biases in human SHM datasets with DeepSHM, a machine-learning model designed to predict SHM patterns. This was combined with integrated gradients, an interpretability method, to interrogate the basis of DeepSHM predictions.

Results

DeepSHM predicted the observed positional differences in mutation frequencies at AGCT motifs with high accuracy. For the conserved, lowly mutating AGCT motifs in FW1, integrated gradients predicted a large negative contribution of 5'C and 3'G flanking residues, suggesting that a CAGCTG context in this location was suppressive for SHM. CAGCTG is the recognition motif for E-box transcription factors, including E2A, which has been implicated in SHM. Indeed, we found a strong, inverse relationship between E-box motif fidelity and mutation frequency. Moreover, E2A was found to associate with the V region locale in two human B cell lines. Finally, analysis of human SHM datasets revealed that naturally occurring mutations in the 3'G flanking residues, which effectively ablate the E-box motif, were associated with a significantly increased rate of AGCT mutation.

Discussion

Our results suggest an antagonistic relationship between mutation frequency and the binding of E-box factors like E2A at specific AGCT motif contexts and, therefore, highlight a new, suppressive mechanism regulating local SHM patterns in human V regions.

Dual-role transcription factors stabilize intermediate expression levels

Precise control of gene expression levels is essential for normal cell functions, yet how they are defined and tightly maintained, particularly at intermediate levels, remains elusive. Here, using a series of newly developed sequencing, imaging, and functional assays, we uncover a class of transcription factors with dual roles as activators and repressors, referred to as condensate-forming level-regulating dual-action transcription factors (TFs). They reduce high expression but increase low expression to achieve stable intermediate levels. Dual-action TFs directly exert activating and repressing functions via condensate-forming domains that compartmentalize core transcriptional unit selectively. Clinically relevant mutations in these domains, which are linked to a range of developmental disorders, impair condensate selectivity and dual-action TF activity. These results collectively address a fundamental question in expression regulation and demonstrate the potential of level-regulating dual-action TFs as powerful effectors for engineering controlled expression levels.

Unraveling noncoding DNA variants and epimutations: a paradigm shift in hereditary cancer research

Exhaustive efforts have been dedicated to uncovering genomic aberrations linked to cancer susceptibility. Noncoding sequence variants and epigenetic alterations significantly influence gene regulation and could contribute to cancer development. However, exploring noncoding regions in hereditary cancer susceptibility demands cutting-edge methodologies for functionally characterizing genomic discoveries. Additionally, comprehending the impact on cancer development of variants in noncoding DNA and the epigenome necessitates integrating diverse data through bioinformatic analyses. As novel technologies and analytical methods continue to advance, this realm of research is rapidly gaining traction. Within this mini-review, we delve into future research domains concerning aberrations in noncoding DNA regions, such as pseudoexons, promoter variants and cis-epimutations.

Exhaustive identification of genome-wide binding events of transcriptional regulators

Genome-wide binding assays aspire to map the complete binding pattern of gene regulators. Common practice relies on replication-duplicates or triplicates-and high stringency statistics to favor false negatives over false positives. Here we show that duplicates and triplicates of CUT&RUN are not sufficient to discover the entire activity of transcriptional regulators. We introduce ICEBERG (Increased Capture of Enrichment By Exhaustive Replicate aGgregation), a pipeline that harnesses large numbers of CUT&RUN replicates to discover the full set of binding events and chart the line between false positives and false negatives. We employed ICEBERG to map the full set of H3K4me3-marked regions, the targets of the co-factor β-catenin, and those of the transcription factor TBX3, in human colorectal cancer cells. The ICEBERG datasets allow benchmarking of individual replicates, comparing the performance of peak calling and replication approaches, and expose the arbitrary nature of strategies to identify reproducible peaks. Instead of a static view of genomic targets, ICEBERG establishes a spectrum of detection probabilities across the genome for a given factor, underlying the intrinsic dynamicity of its mechanism of action, and permitting to distinguish frequent from rare regulation events. Finally, ICEBERG discovered instances, undetectable with other approaches, that underlie novel mechanisms of colorectal cancer progression.

Polycomb-mediated silencing of miR-8 is required for maintenance of intestinal stemness in Drosophila melanogaster

Balancing maintenance of self-renewal and differentiation is a key property of adult stem cells. The epigenetic mechanisms controlling this balance remain largely unknown. Herein, we report that the Polycomb Repressive Complex 2 (PRC2) is required for maintenance of the intestinal stem cell (ISC) pool in the adult female Drosophila melanogaster. We show that loss of PRC2 activity in ISCs by RNAi-mediated knockdown or genetic ablation of the enzymatic subunit Enhancer of zeste, E(z), results in loss of stemness and precocious differentiation of enteroblasts to enterocytes. Mechanistically, we have identified the microRNA miR-8 as a critical target of E(z)/PRC2-mediated tri-methylation of histone H3 at Lys27 (H3K27me3) and uncovered a dynamic relationship between E(z), miR-8 and Notch signaling in controlling stemness versus differentiation of ISCs. Collectively, these findings uncover a hitherto unrecognized epigenetic layer in the regulation of stem cell specification that safeguards intestinal homeostasis.

Cis-regulatory control of transcriptional timing and noise in response to estrogen

Cis-regulatory elements control transcription levels, temporal dynamics, and cell-cell variation or transcriptional noise. However, the combination of regulatory features that control these different attributes is not fully understood. Here, we used single cell RNA-seq during an estrogen treatment time course and machine learning to identify predictors of expression timing and noise. We find that genes with multiple active enhancers exhibit faster temporal responses. We verified this finding by showing that manipulation of enhancer activity changes the temporal response of estrogen target genes. Analysis of transcriptional noise uncovered a relationship between promoter and enhancer activity, with active promoters associated with low noise and active enhancers linked to high noise. Finally, we observed that co-expression across single cells is an emergent property associated with chromatin looping, timing, and noise. Overall, our results indicate a fundamental tradeoff between a gene's ability to quickly respond to incoming signals and maintain low variation across cells.

Pycallingcards: an integrated environment for visualizing, analyzing, and interpreting Calling Cards data

MOTIVATION

Unraveling the transcriptional programs that control how cells divide, differentiate, and respond to their environments requires a precise understanding of transcription factors' (TFs) DNA-binding activities. Calling cards (CC) technology uses transposons to capture transient TF binding events at one instant in time and then read them out at a later time. This methodology can also be used to simultaneously measure TF binding and mRNA expression from single-cell CC and to record and integrate TF binding events across time in any cell type of interest without the need for purification. Despite these advantages, there has been a lack of dedicated bioinformatics tools for the detailed analysis of CC data.

RESULTS

We introduce Pycallingcards, a comprehensive Python module specifically designed for the analysis of single-cell and bulk CC data across multiple species. Pycallingcards introduces two innovative peak callers, CCcaller and MACCs, enhancing the accuracy and speed of pinpointing TF binding sites from CC data. Pycallingcards offers a fully integrated environment for data visualization, motif finding, and comparative analysis with RNA-seq and ChIP-seq datasets. To illustrate its practical application, we have reanalyzed previously published mouse cortex and glioblastoma datasets. This analysis revealed novel cell-type-specific binding sites and potential sex-linked TF regulators, furthering our understanding of TF binding and gene expression relationships. Thus, Pycallingcards, with its user-friendly design and seamless interface with the Python data science ecosystem, stands as a critical tool for advancing the analysis of TF functions via CC data.

AVAILABILITY AND IMPLEMENTATION

Pycallingcards can be accessed on the GitHub repository: https://github.com/The-Mitra-Lab/pycallingcards.

Dynamic IL-6R/STAT3 signaling leads to heterogeneity of metabolic phenotype in pancreatic ductal adenocarcinoma cells

Malignancy is enabled by pro-growth mutations and adequate energy provision. However, global metabolic activation would be self-terminating if it depleted tumor resources. Cancer cells could avoid this by rationing resources, e.g., dynamically switching between "baseline" and "activated" metabolic states. Using single-cell metabolic phenotyping of pancreatic ductal adenocarcinoma cells, we identify MIA-PaCa-2 as having broad heterogeneity of fermentative metabolism. Sorting by a readout of lactic acid permeability separates cells by fermentative and respiratory rates. Contrasting phenotypes persist for 4 days and are unrelated to cell cycling or glycolytic/respiratory gene expression; however, transcriptomics links metabolically active cells with interleukin-6 receptor (IL-6R)-STAT3 signaling. We verify this by IL-6R/STAT3 knockdowns and sorting by IL-6R status. IL-6R/STAT3 activates fermentation and transcription of its inhibitor, SOCS3, resulting in delayed negative feedback that underpins transitions between metabolic states. Among cells manifesting wide metabolic heterogeneity, dynamic IL-6R/STAT3 signaling may allow cell cohorts to take turns in progressing energy-intense processes without depleting shared resources.

Locus-Specific and Stable DNA Demethylation at the H19/IGF2 ICR1 by Epigenome Editing Using a dCas9-SunTag System and the Catalytic Domain of TET1

DNA methylation is critically involved in the regulation of chromatin states and cell-type-specific gene expression. The exclusive expression of imprinted genes from either the maternal or the paternal allele is regulated by allele-specific DNA methylation at imprinting control regions (ICRs). Aberrant DNA hyper- or hypomethylation at the ICR1 of the H19/IGF2 imprinting locus is characteristic for the imprinting disorders Beckwith-Wiedemann syndrome (BWS) and Silver-Russell syndrome (SRS), respectively. In this paper, we performed epigenome editing to induce targeted DNA demethylation at ICR1 in HEK293 cells using dCas9-SunTag and the catalytic domain of TET1. 5-methylcytosine (5mC) levels at the target locus were reduced up to 90% and, 27 days after transient transfection, >60% demethylation was still observed. Consistent with the stable demethylation of CTCF-binding sites within the ICR1, the occupancy of the DNA methylation-sensitive insulator CTCF protein increased by >2-fold throughout the 27 days. Additionally, the H19 expression was increased by 2-fold stably, while IGF2 was repressed though only transiently. Our data illustrate the ability of epigenome editing to implement long-term changes in DNA methylation at imprinting control regions after a single transient treatment, potentially paving the way for therapeutic epigenome editing approaches in the treatment of imprinting disorders.

Leveraging Tissue-Specific Enhancer-Target Gene Regulatory Networks Identifies Enhancer Somatic Mutations That Functionally Impact Lung Cancer

Enhancers are noncoding regulatory DNA regions that modulate the transcription of target genes, often over large distances along with the genomic sequence. Enhancer alterations have been associated with various pathological conditions, including cancer. However, the identification and characterization of somatic mutations in noncoding regulatory regions with a functional effect on tumorigenesis and prognosis remain a major challenge. Here, we present a strategy for detecting and characterizing enhancer mutations in a genome-wide analysis of patient cohorts, across three lung cancer subtypes. Lung tissue-specific enhancers were defined by integrating experimental data and public epigenomic profiles, and the genome-wide enhancer-target gene regulatory network of lung cells was constructed by integrating chromatin three-dimensional architecture data. Lung cancers possessed a similar mutation burden at tissue-specific enhancers and exons but with differences in their mutation signatures. Functionally relevant alterations were prioritized on the basis of the pathway-level integration of the effect of a mutation and the frequency of mutations on individual enhancers. The genes enriched for mutated enhancers converged on the regulation of key biological processes and pathways relevant to tumor biology. Recurrent mutations in individual enhancers also affected the expression of target genes, with potential relevance for patient prognosis. Together, these findings show that noncoding regulatory mutations have a potential relevance for cancer pathogenesis and can be exploited for patient classification.

SIGNIFICANCE

Mapping enhancer-target gene regulatory interactions and analyzing enhancer mutations at the level of their target genes and pathways reveal convergence of recurrent enhancer mutations on biological processes involved in tumorigenesis and prognosis.

EZH2 inhibitors promote β-like cell regeneration in young and adult type 1 diabetes donors

β-cells are a type of endocrine cell found in pancreatic islets that synthesize, store and release insulin. In type 1 diabetes (T1D), T-cells of the immune system selectively destroy the insulin-producing β-cells. Destruction of these cells leads to a lifelong dependence on exogenous insulin administration for survival. Consequently, there is an urgent need to identify novel therapies that stimulate β-cell growth and induce β-cell function. We and others have shown that pancreatic ductal progenitor cells are a promising source for regenerating β-cells for T1D owing to their inherent differentiation capacity. Default transcriptional suppression is refractory to exocrine reaction and tightly controls the regenerative potential by the EZH2 methyltransferase. In the present study, we show that transient stimulation of exocrine cells, derived from juvenile and adult T1D donors to the FDA-approved EZH2 inhibitors GSK126 and Tazemetostat (Taz) influence a phenotypic shift towards a β-like cell identity. The transition from repressed to permissive chromatin states are dependent on bivalent H3K27me3 and H3K4me3 chromatin modification. Targeting EZH2 is fundamental to β-cell regenerative potential. Reprogrammed pancreatic ductal cells exhibit insulin production and secretion in response to a physiological glucose challenge ex vivo. These pre-clinical studies underscore the potential of small molecule inhibitors as novel modulators of ductal progenitor differentiation and a promising new approach for the restoration of β-like cell function.

Somatic structural variation signatures in pediatric brain tumors

Brain cancer is the leading cause of cancer-related death in children. Somatic structural variations (SVs), large-scale alterations in DNA, remain poorly understood in pediatric brain tumors. Here, we detect a total of 13,199 high-confidence somatic SVs in 744 whole-genome sequences of pediatric brain tumors from the Pediatric Brain Tumor Atlas. The somatic SV occurrences have tremendous diversity among the cohort and across different tumor types. We decompose mutational signatures of clustered complex SVs, non-clustered complex SVs, and simple SVs separately to infer their mutational mechanisms. Our finding of many tumor types carrying unique sets of SV signatures suggests that distinct molecular mechanisms shape genome instability in different tumor types. The patterns of somatic SV signatures in pediatric brain tumors are substantially different from those in adult cancers. The convergence of multiple SV signatures on several major cancer driver genes implies vital roles of somatic SVs in disease progression.

iHerd: an integrative hierarchical graph representation learning framework to quantify network changes and prioritize risk genes in disease

Different genes form complex networks within cells to carry out critical cellular functions, while network alterations in this process can potentially introduce downstream transcriptome perturbations and phenotypic variations. Therefore, developing efficient and interpretable methods to quantify network changes and pinpoint driver genes across conditions is crucial. We propose a hierarchical graph representation learning method, called iHerd. Given a set of networks, iHerd first hierarchically generates a series of coarsened sub-graphs in a data-driven manner, representing network modules at different resolutions (e.g., the level of signaling pathways). Then, it sequentially learns low-dimensional node representations at all hierarchical levels via efficient graph embedding. Lastly, iHerd projects separate gene embeddings onto the same latent space in its graph alignment module to calculate a rewiring index for driver gene prioritization. To demonstrate its effectiveness, we applied iHerd on a tumor-to-normal GRN rewiring analysis and cell-type-specific GCN analysis using single-cell multiome data of the brain. We showed that iHerd can effectively pinpoint novel and well-known risk genes in different diseases. Distinct from existing models, iHerd's graph coarsening for hierarchical learning allows us to successfully classify network driver genes into early and late divergent genes (EDGs and LDGs), emphasizing genes with extensive network changes across and within signaling pathway levels. This unique approach for driver gene classification can provide us with deeper molecular insights. The code is freely available at https://github.com/aicb-ZhangLabs/iHerd. All other relevant data are within the manuscript and supporting information files.

Keratin 19 binds and regulates cytoplasmic HNRNPK mRNA targets in triple-negative breast cancer

BACKGROUND

Heterogeneous nuclear ribonucleoprotein K (HNRNPK) regulates pre-mRNA processing and long non-coding RNA localization in the nucleus. It was previously shown that shuttling of HNRNPK to the cytoplasm promotes cell proliferation and cancer metastasis. However, the mechanism of HNRNPK cytoplasmic localization, its cytoplasmic RNA ligands, and impact on post-transcriptional gene regulation remain uncharacterized.

RESULTS

Here we show that the intermediate filament protein Keratin 19 (K19) directly interacts with HNRNPK and sequesters it in the cytoplasm. Correspondingly, in K19 knockout breast cancer cells, HNRNPK does not localize in the cytoplasm, resulting in reduced cell proliferation. We comprehensively mapped HNRNPK binding sites on mRNAs and showed that, in the cytoplasm, K19-mediated HNRNPK-retention increases the abundance of target mRNAs bound to the 3' untranslated region (3'UTR) at the expected cytidine-rich (C-rich) sequence elements. Furthermore, these mRNAs protected by HNRNPK in the cytoplasm are typically involved in cancer progression and include the p53 signaling pathway that is dysregulated upon HNRNPK knockdown (HNRNPK KD) or K19 knockout (KRT19 KO).

CONCLUSIONS

This study identifies how a cytoskeletal protein can directly regulate gene expression by controlling the subcellular localization of RNA-binding proteins to support pathways involved in cancer progression.

Machine-guided design of synthetic cell type-specific cis-regulatory elements

Cis-regulatory elements (CREs) control gene expression, orchestrating tissue identity, developmental timing, and stimulus responses, which collectively define the thousands of unique cell types in the body. While there is great potential for strategically incorporating CREs in therapeutic or biotechnology applications that require tissue specificity, there is no guarantee that an optimal CRE for an intended purpose has arisen naturally through evolution. Here, we present a platform to engineer and validate synthetic CREs capable of driving gene expression with programmed cell type specificity. We leverage innovations in deep neural network modeling of CRE activity across three cell types, efficient in silico optimization, and massively parallel reporter assays (MPRAs) to design and empirically test thousands of CREs. Through in vitro and in vivo validation, we show that synthetic sequences outperform natural sequences from the human genome in driving cell type-specific expression. Synthetic sequences leverage unique sequence syntax to promote activity in the on-target cell type and simultaneously reduce activity in off-target cells. Together, we provide a generalizable framework to prospectively engineer CREs and demonstrate the required literacy to write regulatory code that is fit-for-purpose in vivo across vertebrates.

Chromatin alternates between A and B compartments at kilobase scale for subgenic organization

Nuclear compartments are prominent features of 3D chromatin organization, but sequencing depth limitations have impeded investigation at ultra fine-scale. CTCF loops are generally studied at a finer scale, but the impact of looping on proximal interactions remains enigmatic. Here, we critically examine nuclear compartments and CTCF loop-proximal interactions using a combination of in situ Hi-C at unparalleled depth, algorithm development, and biophysical modeling. Producing a large Hi-C map with 33 billion contacts in conjunction with an algorithm for performing principal component analysis on sparse, super massive matrices (POSSUMM), we resolve compartments to 500 bp. Our results demonstrate that essentially all active promoters and distal enhancers localize in the A compartment, even when flanking sequences do not. Furthermore, we find that the TSS and TTS of paused genes are often segregated into separate compartments. We then identify diffuse interactions that radiate from CTCF loop anchors, which correlate with strong enhancer-promoter interactions and proximal transcription. We also find that these diffuse interactions depend on CTCF's RNA binding domains. In this work, we demonstrate features of fine-scale chromatin organization consistent with a revised model in which compartments are more precise than commonly thought while CTCF loops are more protracted.

Analyses of Genes Critical to Tumor Survival Reveal Potential 'Supertargets': Focus on Transcription

The identification of mechanisms that underlie the biology of individual tumors is aimed at the development of personalized treatment strategies. Herein, we performed a comprehensive search of genes (termed Supertargets) vital for tumors of particular tissue origin. In so doing, we used the DepMap database portal that encompasses a broad panel of cell lines with individual genes knocked out by CRISPR/Cas9 technology. For each of the 27 tumor types, we revealed the top five genes whose deletion was lethal in the particular case, indicating both known and unknown Supertargets. Most importantly, the majority of Supertargets (41%) were represented by DNA-binding transcription factors. RNAseq data analysis demonstrated that a subset of Supertargets was deregulated in clinical tumor samples but not in the respective non-malignant tissues. These results point to transcriptional mechanisms as key regulators of cell survival in specific tumors. Targeted inactivation of these factors emerges as a straightforward approach to optimize therapeutic regimens.

Mapping Multi-factor-mediated Chromatin Interactions to Assess Dysregulation of Lung Cancer-related Genes

Studies on the lung cancer genome are indispensable for developing a cure for lung cancer. Whole-genome resequencing, genome-wide association studies, and transcriptome sequencing have greatly improved our understanding of the cancer genome. However, dysregulation of long-range chromatin interactions in lung cancer remains poorly described. To better understand the three-dimensional (3D) genomic interaction features of the lung cancer genome, we used the A549 cell line as a model system and generated high-resolution chromatin interactions associated with RNA polymerase II (RNAPII), CCCTC-binding factor (CTCF), enhancer of zeste homolog 2 (EZH2), and histone 3 lysine 27 trimethylation (H3K27me3) using long-read chromatin interaction analysis by paired-end tag sequencing (ChIA-PET). Analysis showed that EZH2/H3K27me3-mediated interactions further repressed target genes, either through loops or domains, and their distributions along the genome were distinct from and complementary to those associated with RNAPII. Cancer-related genes were highly enriched with chromatin interactions, and chromatin interactions specific to the A549 cell line were associated with oncogenes and tumor suppressor genes, such as additional repressive interactions on FOXO4 and promoter-promoter interactions between NF1 and RNF135. Knockout of an anchor associated with chromatin interactions reversed the dysregulation of cancer-related genes, suggesting that chromatin interactions are essential for proper expression of lung cancer-related genes. These findings demonstrate the 3D landscape and gene regulatory relationships of the lung cancer genome.

Somatic structural variation signatures in pediatric brain tumors

Brain cancer is the leading cause of cancer-related death in children. Somatic structural variations (SVs), large scale alterations in DNA, remain poorly understood in pediatric brain tumors. Here, we detect a total of 13,199 high confidence somatic SVs in 744 whole-genome-sequenced pediatric brain tumors from Pediatric Brain Tumor Atlas. The somatic SV occurrences have tremendous diversity among the cohort and across different tumor types. We decompose mutational signatures of clustered complex SVs, non-clustered complex SVs, and simple SVs separately to infer the mutational mechanisms of SV formation. Our finding of many tumor types carrying unique sets of SV signatures suggests that distinct molecular mechanisms are active in different tumor types to shape genome instability. The patterns of somatic SV signatures in pediatric brain tumors are substantially different from those in adult cancers. The convergence of multiple signatures to alter several major cancer driver genes suggesting the functional importance of somatic SVs in disease progression.

Condensed but liquid-like domain organization of active chromatin regions in living human cells

In eukaryotes, higher-order chromatin organization is spatiotemporally regulated as domains, for various cellular functions. However, their physical nature in living cells remains unclear (e.g., condensed domains or extended fiber loops; liquid-like or solid-like). Using novel approaches combining genomics, single-nucleosome imaging, and computational modeling, we investigated the physical organization and behavior of early DNA replicated regions in human cells, which correspond to Hi-C contact domains with active chromatin marks. Motion correlation analysis of two neighbor nucleosomes shows that nucleosomes form physically condensed domains with ~150-nm diameters, even in active chromatin regions. The mean-square displacement analysis between two neighbor nucleosomes demonstrates that nucleosomes behave like a liquid in the condensed domain on the ~150 nm/~0.5 s spatiotemporal scale, which facilitates chromatin accessibility. Beyond the micrometers/minutes scale, chromatin seems solid-like, which may contribute to maintaining genome integrity. Our study reveals the viscoelastic principle of the chromatin polymer; chromatin is locally dynamic and reactive but globally stable.

Discovery of novel predisposing coding and noncoding variants in familial Hodgkin lymphoma

Familial aggregation of Hodgkin lymphoma (HL) has been demonstrated in large population studies, pointing to genetic predisposition to this hematological malignancy. To understand the genetic variants associated with the development of HL, we performed whole genome sequencing on 234 individuals with and without HL from 36 pedigrees that had 2 or more first-degree relatives with HL. Our pedigree selection criteria also required at least 1 affected individual aged <21 years, with the median age at diagnosis of 21.98 years (3-55 years). Family-based segregation analysis was performed for the identification of coding and noncoding variants using linkage and filtering approaches. Using our tiered variant prioritization algorithm, we identified 44 HL-risk variants in 28 pedigrees, of which 33 are coding and 11 are noncoding. The top 4 recurrent risk variants are a coding variant in KDR (rs56302315), a 5' untranslated region variant in KLHDC8B (rs387906223), a noncoding variant in an intron of PAX5 (rs147081110), and another noncoding variant in an intron of GATA3 (rs3824666). A newly identified splice variant in KDR (c.3849-2A>C) was observed for 1 pedigree, and high-confidence stop-gain variants affecting IRF7 (p.W238∗) and EEF2KMT (p.K116∗) were also observed. Multiple truncating variants in POLR1E were found in 3 independent pedigrees as well. Whereas KDR and KLHDC8B have previously been reported, PAX5, GATA3, IRF7, EEF2KMT, and POLR1E represent novel observations. Although there may be environmental factors influencing lymphomagenesis, we observed segregation of candidate germline variants likely to predispose HL in most of the pedigrees studied.

Analysis of histone antibody specificity directly in sequencing data using siQ-ChIP

We previously developed sans spike-in quantitative chromatin immunoprecipitation sequencing (siQ-ChIP), a technique that introduces an absolute quantitative scale to ChIP-seq data without reliance on spike-in normalization approaches. The physical model of siQ-ChIP predicted that the IP step of ChIP would produce a classical binding isotherm when antibody or epitope was titrated. Here, we define experimental conditions in which this titration is observable for antibodies that recognize modified states of histone proteins. We show that minimally sequenced points along an isotherm can reveal differential binding specificities that are associated with on- and off-target epitope interactions. This work demonstrates that the interpretation of histone post-translational modification distribution from ChIP-seq data has a dependence on antibody concentration. Collectively, these studies introduce a simplified and reproducible experimental method to generate quantitative ChIP-seq data without spike-in normalization and demonstrate that histone antibody specificity can be analyzed directly in ChIP-seq experiments.

Conformational analysis of chromosome structures reveals vital role of chromosome morphology in gene function

The 3D conformations of chromosomes are highly variant and stochastic between single cells. Recent progress in multiplexed 3D FISH imaging, single cell Hi-C and genome structure modeling allows a closer analysis of the structural variations of chromosomes between cells to infer the functional implications of structural heterogeneity. Here, we introduce a two-step dimensionality reduction method to classify a population of single cell 3D chromosome structures, either from simulation or imaging experiment, into dominant conformational clusters with distinct chromosome morphologies. We found that almost half of all structures for each chromosome can be described by 5-10 dominant chromosome morphologies, which play a fundamental role in establishing conformational variation of chromosomes. These morphologies are conserved in different cell types, but vary in their relative proportion of structures. Chromosome morphologies are distinguished by the presence or absence of characteristic chromosome territory domains, which expose some chromosomal regions to varying nuclear environments in different morphologies, such as nuclear positions and associations to nuclear speckles, lamina, and nucleoli. These observations point to distinct functional variations for the same chromosomal region in different chromosome morphologies. We validated chromosome conformational clusters and their associated subnuclear locations with data from DNA-MERFISH imaging and single cell sci-HiC data. Our method provides an important approach to assess the variation of chromosome structures between cells and link differences in conformational states with distinct gene functions.

Targeting Menin disrupts the KMT2A/B and polycomb balance to paradoxically activate bivalent genes

Precise control of activating H3K4me3 and repressive H3K27me3 histone modifications at bivalent promoters is essential for normal development and frequently corrupted in cancer. By coupling a cell surface readout of bivalent MHC class I gene expression with whole-genome CRISPR-Cas9 screens, we identify specific roles for MTF2-PRC2.1, PCGF1-PRC1.1 and Menin-KMT2A/B complexes in maintaining bivalency. Genetic loss or pharmacological inhibition of Menin unexpectedly phenocopies the effects of polycomb disruption, resulting in derepression of bivalent genes in both cancer cells and pluripotent stem cells. While Menin and KMT2A/B contribute to H3K4me3 at active genes, a separate Menin-independent function of KMT2A/B maintains H3K4me3 and opposes polycomb-mediated repression at bivalent genes. Release of KMT2A from active genes following Menin targeting alters the balance of polycomb and KMT2A at bivalent genes, facilitating gene activation. This functional partitioning of Menin-KMT2A/B complex components reveals therapeutic opportunities that can be leveraged through inhibition of Menin.

Regulation of Ferroptosis by Transcription Factor E2F1 and RB

Tumor suppressor RB binds to E2F family proteins and modulates cell cycle progression. Cyclin dependent kinases (CDK) regulate the interaction of RB/E2F by phosphorylating RB. Previously, we have revealed that CDK2, RB and E2F inhibit ferroptosis. Ferroptosis is a non-apoptotic, iron-dependent form of cell death characterized by toxic lipid peroxidation. Here we provide evidence that CDK2 suppresses ferroptosis through phosphorylation of RB. We approach this question by overexpressing WT-RB or a mutant RB that cannot be phosphorylated by CDKs (RBΔCDK) along with CDK2/cyclinE followed by analysis of ferroptosis. We also observed that E2F1 regulates of both pro and anti-ferroptotic proteins including ALOX5, MYC SLC7A11, ATF4, and GPX4 and finally renders a net inhibitory role in ferroptosis. Interestingly, we also found a cell type dependent compensatory effect of E2F3 upon E2F1 depletion. This compensatory effect resulted in no change of ferroptotic target genes after E2F1 knock down in an osteosarcoma cell line. Taken together, our study reveals that cancer cells protect themselves from ferroptosis through cell cycle regulatory proteins.

MINE is a method for detecting spatial density of regulatory chromatin interactions based on a multi-modal network

Chromatin interactions play essential roles in chromatin conformation and gene expression. However, few tools exist to analyze the spatial density of regulatory chromatin interactions (SD-RCI). Here, we present the multi-modal network (MINE) toolkit, including MINE-Loop, MINE-Density, and MINE-Viewer. The MINE-Loop network aims to enhance the detection of RCIs, MINE-Density quantifies the SD--RCI, and MINE-Viewer facilitates 3D visualization of the density of chromatin interactions and participating regulatory factors (e.g., transcription factors). We applied MINE to investigate the relationship between the SD-RCI and chromatin volume change in HeLa cells before and after liquid-liquid phase separation. Changes in SD-RCI before and after treating the HeLa cells with 1,6-hexanediol suggest that changes in chromatin organization was related to the degree of activation or repression of genes. Together, the MINE toolkit enables quantitative studies on different aspects of chromatin conformation and regulatory activity.

Single-cell RNA binding protein regulatory network analyses reveal oncogenic HNRNPK-MYC signalling pathway in cancer

RNA-binding proteins (RBPs) are key players of gene expression and perturbations of RBP-RNA regulatory network have been observed in various cancer types. Here, we propose a computational method, RBPreg, to identify the RBP regulators by integration of single cell RNA-Seq (N = 233,591) and RBP binding data. Pan-cancer analyses suggest that RBP regulators exhibit cancer and cell specificity and perturbations of RBP regulatory network are involved in cancer hallmark-related functions. We prioritize an oncogenic RBP-HNRNPK, which is highly expressed in tumors and associated with poor prognosis of patients. Functional assays performed in cancer cells reveal that HNRNPK promotes cancer cell proliferation, migration, and invasion in vitro and in vivo. Mechanistic investigations further demonstrate that HNRNPK promotes tumorigenesis and progression by directly binding to MYC and perturbed the MYC targets pathway in lung cancer. Our results provide a valuable resource for characterizing RBP regulatory networks in cancer, yielding potential biomarkers for precision medicine.

The homeodomain of Oct4 is a dimeric binder of methylated CpG elements

Oct4 is essential to maintain pluripotency and has a pivotal role in establishing the germline. Its DNA-binding POU domain was recently found to bind motifs with methylated CpG elements normally associated with epigenetic silencing. However, the mode of binding and the consequences of this capability has remained unclear. Here, we show that Oct4 binds to a compact palindromic DNA element with a methylated CpG core (CpGpal) in alternative states of pluripotency and during cellular reprogramming towards induced pluripotent stem cells (iPSCs). During cellular reprogramming, typical Oct4 bound enhancers are uniformly demethylated, with the prominent exception of the CpGpal sites where DNA methylation is often maintained. We demonstrate that Oct4 cooperatively binds the CpGpal element as a homodimer, which contrasts with the ectoderm-expressed POU factor Brn2. Indeed, binding to CpGpal is Oct4-specific as other POU factors expressed in somatic cells avoid this element. Binding assays combined with structural analyses and molecular dynamic simulations show that dimeric Oct4-binding to CpGpal is driven by the POU-homeodomain whilst the POU-specific domain is detached from DNA. Collectively, we report that Oct4 exerts parts of its regulatory function in the context of methylated DNA through a DNA recognition mechanism that solely relies on its homeodomain.

The human pre-replication complex is an open complex

In eukaryotes, DNA replication initiation requires assembly and activation of the minichromosome maintenance (MCM) 2-7 double hexamer (DH) to melt origin DNA strands. However, the mechanism for this initial melting is unknown. Here, we report a 2.59-Å cryo-electron microscopy structure of the human MCM-DH (hMCM-DH), also known as the pre-replication complex. In this structure, the hMCM-DH with a constricted central channel untwists and stretches the DNA strands such that almost a half turn of the bound duplex DNA is distorted with 1 base pair completely separated, generating an initial open structure (IOS) at the hexamer junction. Disturbing the IOS inhibits DH formation and replication initiation. Mapping of hMCM-DH footprints indicates that IOSs are distributed across the genome in large clusters aligning well with initiation zones designed for stochastic origin firing. This work unravels an intrinsic mechanism that couples DH formation with initial DNA melting to license replication initiation in human cells.

Active enhancers strengthen insulation by RNA-mediated CTCF binding at chromatin domain boundaries

Vertebrate genomes are partitioned into chromatin domains or topologically associating domains (TADs), which are typically bound by head-to-head pairs of CTCF binding sites. Transcription at domain boundaries correlates with better insulation; however, it is not known whether the boundary transcripts themselves contribute to boundary function. Here we characterize boundary-associated RNAs genome-wide, focusing on the disease-relevant INK4a/ARF and MYC TAD. Using CTCF site deletions and boundary-associated RNA knockdowns, we observe that boundary-associated RNAs facilitate recruitment and clustering of CTCF at TAD borders. The resulting CTCF enrichment enhances TAD insulation, enhancer-promoter interactions, and TAD gene expression. Importantly, knockdown of boundary-associated RNAs results in loss of boundary insulation function. Using enhancer deletions and CRISPRi of promoters, we show that active TAD enhancers, but not promoters, induce boundary-associated RNA transcription, thus defining a novel class of regulatory enhancer RNAs.

Network-based approaches for modeling disease regulation and progression

Molecular interaction networks lay the foundation for studying how biological functions are controlled by the complex interplay of genes and proteins. Investigating perturbed processes using biological networks has been instrumental in uncovering mechanisms that underlie complex disease phenotypes. Rapid advances in omics technologies have prompted the generation of high-throughput datasets, enabling large-scale, network-based analyses. Consequently, various modeling techniques, including network enrichment, differential network extraction, and network inference, have proven to be useful for gaining new mechanistic insights. We provide an overview of recent network-based methods and their core ideas to facilitate the discovery of disease modules or candidate mechanisms. Knowledge generated from these computational efforts will benefit biomedical research, especially drug development and precision medicine. We further discuss current challenges and provide perspectives in the field, highlighting the need for more integrative and dynamic network approaches to model disease development and progression.

Interplay Between the Histone Variant H2A.Z and the Epigenome in Pancreatic Cancer

BACKGROUND

The oncogenic process is orchestrated by a complex network of chromatin remodeling elements that shape the cancer epigenome. Histone variant H2A.Z regulates DNA control elements such as promoters and enhancers in different types of cancer; however, the interplay between H2A.Z and the pancreatic cancer epigenome is unknown.

OBJECTIVE

This study analyzed the role of H2A.Z in different DNA regulatory elements.

METHODS

We performed Chromatin Immunoprecipitation Sequencing assays (ChiP-seq) with total H2A.Z and acetylated H2A.Z (acH2A.Z) antibodies and analyzed published data from ChIP-seq, RNA-seq, bromouridine labeling-UV and sequencing (BruUV-seq), Hi-C and ATAC-seq (Assay for Transposase-Accessible Chromatin using sequencing) in the pancreatic cancer cell line PANC-1.

RESULTS

The results indicate that total H2A.Z facilitates the recruitment of RNA polymerase II and transcription factors at promoters and enhancers allowing the expression of pro-oncogenic genes. Interestingly, we demonstrated that H2A.Z is enriched in super-enhancers (SEs) contributing to the transcriptional activation of key genes implicated in tumor development. Importantly, we established that H2A.Z contributes to the three-dimensional (3D) genome organization of pancreatic cancer and that it is a component of the Topological Associated Domains (TADs) boundaries in PANC-1 and that total H2A.Z and acH2A.Z are associated with A and B compartments, respectively.

CONCLUSIONS

H2A.Z participates in the biology and development of pancreatic cancer by generating a pro-oncogenic transcriptome through its posttranslational modifications, interactions with different partners, and regulatory elements, contributing to the oncogenic 3D genome organization. These data allow us to understand the molecular mechanisms that promote an oncogenic transcriptome in pancreatic cancer mediated by H2A.Z.

Regulome analysis in B-acute lymphoblastic leukemia exposes Core Binding Factor addiction as a therapeutic vulnerability

The ETV6-RUNX1 onco-fusion arises in utero, initiating a clinically silent pre-leukemic state associated with the development of pediatric B-acute lymphoblastic leukemia (B-ALL). We characterize the ETV6-RUNX1 regulome by integrating chromatin immunoprecipitation- and RNA-sequencing and show that ETV6-RUNX1 functions primarily through competition for RUNX1 binding sites and transcriptional repression. In pre-leukemia, this results in ETV6-RUNX1 antagonization of cell cycle regulation by RUNX1 as evidenced by mass cytometry analysis of B-lineage cells derived from ETV6-RUNX1 knock-in human pluripotent stem cells. In frank leukemia, knockdown of RUNX1 or its co-factor CBFβ results in cell death suggesting sustained requirement for RUNX1 activity which is recapitulated by chemical perturbation using an allosteric CBFβ-inhibitor. Strikingly, we show that RUNX1 addiction extends to other genetic subtypes of pediatric B-ALL and also adult disease. Importantly, inhibition of RUNX1 activity spares normal hematopoiesis. Our results suggest that chemical intervention in the RUNX1 program may provide a therapeutic opportunity in ALL.

Discovery of a MUC3B gene reconstructs the membrane mucin gene cluster on human chromosome 7

Human tissue surfaces are coated with mucins, a family of macromolecular sugar-laden proteins serving diverse functions from lubrication to the formation of selective biochemical barriers against harmful microorganisms and molecules. Membrane mucins are a distinct group of mucins that are attached to epithelial cell surfaces where they create a dense glycocalyx facing the extracellular environment. All mucin proteins carry long stretches of tandemly repeated sequences that undergo extensive O-linked glycosylation to form linear mucin domains. However, the repetitive nature of mucin domains makes them prone to recombination and renders their genetic sequences particularly difficult to read with standard sequencing technologies. As a result, human mucin genes suffer from significant sequence gaps that have hampered the investigation of gene function in health and disease. Here we leveraged a recent human genome assembly to characterize a previously unmapped MUC3B gene located at the q22 locus on chromosome 7, within a cluster of four structurally related membrane mucin genes that we name the MUC3 cluster. We found that MUC3B shares high sequence identity with the known MUC3A gene and that the two genes are governed by evolutionarily conserved regulatory elements. Furthermore, we show that MUC3A, MUC3B, MUC12, and MUC17 in the human MUC3 cluster are expressed in intestinal epithelial cells (IECs). Our results complete existing genetic gaps in the MUC3 cluster which is a conserved genetic unit in vertebrates. We anticipate our results to be the starting point for the detection of disease-associated polymorphisms in the human MUC3 cluster. Moreover, our study provides the basis for the exploration of intestinal mucin gene function in widely used experimental models such as human intestinal organoids and genetic mouse models.

A quantitative metric of pioneer activity reveals that HNF4A has stronger in vivo pioneer activity than FOXA1

BACKGROUND

We and others have suggested that pioneer activity - a transcription factor's (TF's) ability to bind and open inaccessible loci - is not a qualitative trait limited to a select class of pioneer TFs. We hypothesize that most TFs display pioneering activity that depends on the TF concentration and the motif content at their target loci.

RESULTS

Here, we present a quantitative in vivo measure of pioneer activity that captures the relative difference in a TF's ability to bind accessible versus inaccessible DNA. The metric is based on experiments that use CUT&Tag to measure the binding of doxycycline-inducible TFs. For each location across the genome, we determine the concentration of doxycycline required for a TF to reach half-maximal occupancy; lower concentrations reflect higher affinity. We propose that the relative difference in a TF's affinity between ATAC-seq labeled accessible and inaccessible binding sites is a measure of its pioneer activity. We estimate binding affinities at tens of thousands of genomic loci for the endodermal TFs FOXA1 and HNF4A and show that HNF4A has stronger pioneer activity than FOXA1. We show that both FOXA1 and HNF4A display higher binding affinity at inaccessible sites with more copies of their respective motifs. The quantitative analysis of binding suggests different modes of binding for FOXA1, including an anti-cooperative mode of binding at certain accessible loci.

CONCLUSIONS

Our results suggest that relative binding affinities are reasonable measures of pioneer activity and support the model wherein most TFs have some degree of context-dependent pioneer activity.

iDNA-ABF: multi-scale deep biological language learning model for the interpretable prediction of DNA methylations

In this study, we propose iDNA-ABF, a multi-scale deep biological language learning model that enables the interpretable prediction of DNA methylations based on genomic sequences only. Benchmarking comparisons show that our iDNA-ABF outperforms state-of-the-art methods for different methylation predictions. Importantly, we show the power of deep language learning in capturing both sequential and functional semantics information from background genomes. Moreover, by integrating the interpretable analysis mechanism, we well explain what the model learns, helping us build the mapping from the discovery of important sequential determinants to the in-depth analysis of their biological functions.

Single-cell transcriptome analyses reveal distinct gene expression signatures of severe COVID-19 in the presence of clonal hematopoiesis

Clonal hematopoiesis of indeterminate potential (CHIP), a common aging-related process that predisposes individuals to various inflammatory responses, has been reported to be associated with COVID-19 severity. However, the immunological signature and the exact gene expression program by which the presence of CHIP exerts its clinical impact on COVID-19 remain to be elucidated. In this study, we generated a single-cell transcriptome landscape of severe COVID-19 according to the presence of CHIP using peripheral blood mononuclear cells. Patients with CHIP exhibited a potent IFN-γ response in exacerbating inflammation, particularly in classical monocytes, compared to patients without CHIP. To dissect the regulatory mechanism of CHIP (+)-specific IFN-γ response gene expression in severe COVID-19, we identified DNMT3A CHIP mutation-dependent differentially methylated regions (DMRs) and annotated their putative target genes based on long-range chromatin interactions. We revealed that CHIP mutant-driven hypo-DMRs at poised cis-regulatory elements appear to facilitate the CHIP (+)-specific IFN-γ-mediated inflammatory immune response. Our results highlight that the presence of CHIP may increase the susceptibility to hyperinflammation through the reorganization of chromatin architecture, establishing a novel subgroup of severe COVID-19 patients.

Inhibition of pancreatic EZH2 restores progenitor insulin in T1D donor

Type 1 diabetes (T1D) is an autoimmune disease that selectively destroys insulin-producing β-cells in the pancreas. An unmet need in diabetes management, current therapy is focussed on transplantation. While the reprogramming of progenitor cells into functional insulin-producing β-cells has also been proposed this remains controversial and poorly understood. The challenge is determining why default transcriptional suppression is refractory to exocrine reactivation. After the death of a 13-year-old girl with established insulin-dependent T1D, pancreatic cells were harvested in an effort to restore and understand exocrine competence. The pancreas showed classic silencing of β-cell progenitor genes with barely detectable insulin (Ins) transcript. GSK126, a highly selective inhibitor of EZH2 methyltransferase activity influenced H3K27me3 chromatin content and transcriptional control resulting in the expression of core β-cell markers and ductal progenitor genes. GSK126 also reinstated Ins gene expression despite absolute β-cell destruction. These studies show the refractory nature of chromatin characterises exocrine suppression influencing β-cell plasticity. Additional regeneration studies are warranted to determine if the approach of this n-of-1 study generalises to a broader T1D population.

Integrated bioinformatics analysis reveals that EZH2-rich domains promote transcriptional repression in cervical cancer

Cervical cancer is the third female cancer most common worldwide. The carcinogenic process involves an alteration of the mechanisms associated with transcription. Several studies have reported an oncogenic role of the polycomb complex subunit, EZH2. However, the role of EZH2 in cervical cancer is unknown. Hence, the objective of this study was to determine the role of EZH2 in transcriptional regulation in cervical cancer. The EZH2 expression and the methylation status of its promoter were analyzed in The Cancer Genome Atlas. The EZH2 enrichment profile was analyzed using chromatin immunoprecipitation with massively parallel DNA sequencing data provided by ENCODE project. The chromatin compartments were identified in the 4D Nucleome Data Portal. The functional annotation was examined in Enrichr. We report that EZH2 expression is increased in cervical cancer which is associated with hypomethylation of its promoter. EZH2 is enriched at promoter and distal intergenic regions. We identified that EZH2 defines chromatin domains enriched with H3K27me3 within repressive compartments in the HeLa-S3 cell line. Additionally, high EZH2 expression is associated with the repression of the senescent phenotype in cervical cancer patients. Our results suggest the participation of EZH2 in the generation of domains with a silencer function in cervical cancer, which regulate the expression of genes associated with cellular senescence.

DIRECT-NET: An efficient method to discover cis-regulatory elements and construct regulatory networks from single-cell multiomics data

The emergence of single-cell multiomics data provides unprecedented opportunities to scrutinize the transcriptional regulatory mechanisms controlling cell identity. However, how to use those datasets to dissect the cis-regulatory element (CRE)-to-gene relationships at a single-cell level remains a major challenge. Here, we present DIRECT-NET, a machine-learning method based on gradient boosting, to identify genome-wide CREs and their relationship to target genes, either from parallel single-cell gene expression and chromatin accessibility data or from single-cell chromatin accessibility data alone. By extensively evaluating and characterizing DIRECT-NET's predicted CREs using independent functional genomics data, we find that DIRECT-NET substantially improves the accuracy of inferring CRE-to-gene relationships in comparison to existing methods. DIRECT-NET is also capable of revealing cell subpopulation-specific and dynamic regulatory linkages. Overall, DIRECT-NET provides an efficient tool for predicting transcriptional regulation codes from single-cell multiomics data.

PHF13 epigenetically activates TGFβ driven epithelial to mesenchymal transition

Epigenetic alteration is a pivotal factor in tumor metastasis. PHD finger protein 13 (PHF13) is a recently identified epigenetic reader of H3K4me2/3 that functions as a transcriptional co-regulator. In this study, we demonstrate that PHF13 is required for pancreatic-cancer-cell growth and metastasis. Integrative analysis of transcriptome and epigenetic profiles provide further mechanistic insights into the epigenetic regulation of genes associated with cell metastasis during the epithelial-to-mesenchymal transition (EMT) induced by transforming growth factor β (TGFβ). Our data suggest PHF13 depletion impairs activation of TGFβ stimulated genes and correlates with a loss of active epigenetic marks (H3K4me3 and H3K27ac) at these genomic regions. These observations argue for a dependency of TGFβ target activation on PHF13. Furthermore, PHF13-dependent chromatin regions are enriched in broad H3K4me3 domains and super-enhancers, which control genes critical to cancer-cell migration and invasion, such as SNAI1 and SOX9. Overall, our data indicate a functional and mechanistic correlation between PHF13 and EMT.