dHICA: a deep transformer-based model enables accurate histone imputation from chromatin accessibility.

Histone modifications (HMs) are pivotal in various biological processes, including transcription, replication, and DNA repair, significantly impacting chromatin structure. These modifications underpin the molecular mechanisms of cell-type-specific gene expression and complex diseases. However, annotating HMs across different cell types solely using experimental approaches is impractical due to cost and time constraints. Herein, we present dHICA (deep histone imputation using chromatin accessibility), a novel deep learning framework that integrates DNA sequences and chromatin accessibility data to predict multiple HM tracks. Employing the transformer architecture alongside dilated convolutions, dHICA boasts an extensive receptive field and captures more cell-type-specific information. dHICA outperforms state-of-the-art baselines and achieves superior performance in cell-type-specific loci and gene elements, aligning with biological expectations. Furthermore, dHICA's imputations hold significant potential for downstream applications, including chromatin state segmentation and elucidating the functional implications of SNPs (Single Nucleotide Polymorphisms). In conclusion, dHICA serves as a valuable tool for advancing the understanding of chromatin dynamics, offering enhanced predictive capabilities and interpretability.

Using Functional Genomic Data in Monocytes/Macrophages and Genotyping to Nominate Disease-Driving Single Nucleotide Polymorphisms and Target Genes in Juvenile Idiopathic Arthritis.

Introduction: GWAS have identified multiple regions that confer risk for juvenile idiopathic arthritis (JIA). However, identifying the single nucleotide polymorphisms (SNPs) that drive disease risk is impeded by the SNPs' that identify risk loci being in linkage disequilibrium (LD) with hundreds of other SNPs. Since the causal SNPs remain unknown, it is difficult to identify target genes and use genetic information to inform patient care. We used genotyping and functional data in primary human monocytes/macrophages to nominate disease-driving SNPs on JIA risk haplotypes and identify their likely target genes. Methods: We identified JIA risk haplotypes using Immunochip data from Hinks et al (Nature Gen 2013) and the meta-analysis from McIntosh et al (Arthritis Rheum 2017). We used genotyping data from 3,939 children with JIA and 14,412 healthy controls to identify SNPs that: (1) were situated within open chromatin in multiple immune cell types and (2) were more common in children with JIA than the controls (p< 0.05). We intersected the chosen SNPs (n=846) with regions of bi-directional transcription initiation characteristic of non-coding regulatory regions detected using dREG to analyze GRO-seq data. Finally, we used MicroC data to identify gene promoters interacting with the regulatory regions harboring the candidate causal SNPs. Results: We identified 190 SNPs that overlap with dREG peaks in monocytes and126 SNPs that overlap with dREG peaks in macrophages. Of these SNPs, 101 were situated within dREG peaks in both monocytes and macrophages, suggesting that these SNPs exert their effects independent of the cellular activation state. MicroC data in monocytes identified 20 genes/transcripts whose promoters interact with the enhancers harboring the SNPs of interest. Conclusion: SNPs in JIA risk regions that are candidate causal variants can be further screened using functional data such as GRO-seq. This process identifies a finite number of candidate causal SNPs, the majority of which are likely to exert their biological effects independent of cellular activation state in monocytes. Three-dimensional chromatin data generated with MicroC identifies genes likely to be influenced by these SNPs. These studies demonstrate the importance of investigations into the role of innate immunity in JIA.

Dissection of core promoter syntax through single nucleotide resolution modeling of transcription initiation.

How the DNA sequence of cis -regulatory elements encode transcription initiation patterns remains poorly understood. Here we introduce CLIPNET, a deep learning model trained on population-scale PRO-cap data that predicts the position and quantity of transcription initiation with single nucleotide resolution from DNA sequence more accurately than existing approaches. Interpretation of CLIPNET revealed a complex regulatory syntax consisting of DNA-protein interactions in five major positions between - 200 and + 50 bp relative to the transcription start site, as well as more subtle positional preferences among transcriptional activators. Transcriptional activator and core promoter motifs work non-additively to encode distinct aspects of initiation, with the former driving initiation quantity and the latter initiation position. We identified core promoter motifs that explain initiation patterns in the majority of promoters and enhancers, including DPR motifs and AT-rich TBP binding sequences in TATA-less promoters. Our results provide insights into the sequence architecture governing transcription initiation.

Precision run-on sequencing (PRO-seq) for microbiome transcriptomics.

Bacteria respond to environmental stimuli through precise regulation of transcription initiation and elongation. Bulk RNA sequencing primarily characterizes mature transcripts, so to identify actively transcribed loci we need to capture RNA polymerase (RNAP) complexed with nascent RNA. However, such capture methods have only previously been applied to culturable, genetically tractable organisms such as E. coli and B. subtilis. Here we apply precision run-on sequencing (PRO-seq) to profile nascent transcription in cultured E. coli and diverse uncultured bacteria. We demonstrate that PRO-seq can characterize the transcription of small, structured, or post-transcriptionally modified RNAs, which are often absent from bulk RNA-seq libraries. Applying PRO-seq to the human microbiome highlights taxon-specific RNAP pause motifs and pause-site distributions across non-coding RNA loci that reflect structure-coincident pausing. We also uncover concurrent transcription and cleavage of CRISPR guide RNAs and transfer RNAs. We demonstrate the utility of PRO-seq for exploring transcriptional dynamics in diverse microbial communities.

RNA polymerase II dynamics shape enhancer-promoter interactions.

How enhancers control target gene expression over long genomic distances remains an important unsolved problem. Here we investigated enhancer-promoter communication by integrating data from nucleosome-resolution genomic contact maps, nascent transcription and perturbations affecting either RNA polymerase II (Pol II) dynamics or the activity of thousands of candidate enhancers. Integration of new Micro-C experiments with published CRISPRi data demonstrated that enhancers spend more time in close proximity to their target promoters in functional enhancer-promoter pairs compared to nonfunctional pairs, which can be attributed in part to factors unrelated to genomic position. Manipulation of the transcription cycle demonstrated a key role for Pol II in enhancer-promoter interactions. Notably, promoter-proximal paused Pol II itself partially stabilized interactions. We propose an updated model in which elements of transcriptional dynamics shape the duration or frequency of interactions to facilitate enhancer-promoter communication.

A-MYB and BRDT-dependent RNA Polymerase II pause release orchestrates transcriptional regulation in mammalian meiosis.

During meiotic prophase I, spermatocytes must balance transcriptional activation with homologous recombination and chromosome synapsis, biological processes requiring extensive changes to chromatin state. We explored the interplay between chromatin accessibility and transcription through prophase I of mammalian meiosis by measuring genome-wide patterns of chromatin accessibility, nascent transcription, and processed mRNA. We find that Pol II is loaded on chromatin and maintained in a paused state early during prophase I. In later stages, paused Pol II is released in a coordinated transcriptional burst mediated by the transcription factors A-MYB and BRDT, resulting in ~3-fold increase in transcription. Transcriptional activity is temporally and spatially segregated from key steps of meiotic recombination: double strand breaks show evidence of chromatin accessibility earlier during prophase I and at distinct loci from those undergoing transcriptional activation, despite shared chromatin marks. Our findings reveal mechanisms underlying chromatin specialization in either transcription or recombination in meiotic cells.

Evolution of promoter-proximal pausing enabled a new layer of transcription control.

Promoter-proximal pausing of RNA polymerase II (Pol II) is a key regulatory step during transcription. Despite the central role of pausing in gene regulation, we do not understand the evolutionary processes that led to the emergence of Pol II pausing or its transition to a rate-limiting step actively controlled by transcription factors. Here we analyzed transcription in species across the tree of life. We found that unicellular eukaryotes display a slow acceleration of Pol II near transcription start sites. This proto-paused-like state transitioned to a longer, focused pause in derived metazoans which coincided with the evolution of new subunits in the NELF and 7SK complexes. Depletion of NELF reverts the mammalian focal pause to a proto-pause-like state and compromises transcriptional activation for a set of heat shock genes. Collectively, this work details the evolutionary history of Pol II pausing and sheds light on how new transcriptional regulatory mechanisms evolve.

GDNF-RET signaling and EGR1 form a positive feedback loop that promotes tamoxifen resistance via cyclin D1.

BACKGROUND: Rearranged during transfection (RET) tyrosine kinase signaling has been previously implicated in endocrine resistant breast cancer, however the mechanism by which this signaling cascade promotes resistance is currently not well described. We recently reported that glial cell-derived neurotrophic factor (GDNF)-RET signaling appears to promote a positive feedback loop with the transcription factor early growth response 1 (EGR1). Here we investigate the mechanism behind this feedback loop and test the hypothesis that GDNF-RET signaling forms a regulatory loop with EGR1 to upregulate cyclin D1 (CCND1) transcription, leading to cell cycle progression and tamoxifen resistance. METHODS: To gain a better understanding of the GDNF-RET-EGR1 resistance mechanism, we studied the GDNF-EGR1 positive feedback loop and the role of GDNF and EGR1 in endocrine resistance by modulating their transcription levels using CRISPR-dCAS9 in tamoxifen sensitive (TamS) and tamoxifen resistant (TamR) MCF-7 cells. Additionally, we performed kinetic studies using recombinant GDNF (rGDNF) treatment of TamS cells. Finally, we performed cell proliferation assays using rGDNF, tamoxifen (TAM), and Palbociclib treatments in TamS cells. Statistical significance for qPCR and chromatin immunoprecipitation (ChIP)-qPCR experiments were determined using a student's paired t-test and statistical significance for the cell viability assay was a one-way ANOVA. RESULTS: GDNF-RET signaling formed a positive feedback loop with EGR1 and also downregulated estrogen receptor 1 (ESR1) transcription. Upregulation of GDNF and EGR1 promoted tamoxifen resistance in TamS cells and downregulation of GDNF promoted tamoxifen sensitivity in TamR cells. Additionally, we show that rGDNF treatment activated GDNF-RET signaling in TamS cells, leading to recruitment of phospho-ELK-1 to the EGR1 promoter, upregulation of EGR1 mRNA and protein, binding of EGR1 to the GDNF and CCND1 promoters, increased GDNF protein expression, and subsequent upregulation of CCND1 mRNA levels. We also show that inhibition of cyclin D1 with Palbociclib, in the presence of rGDNF, decreases cell proliferation and resensitizes cells to TAM. CONCLUSION: Outcomes from these studies support the hypotheses that GDNF-RET signaling forms a positive feedback loop with the transcription factor EGR1, and that GDNF-RET-EGR1 signaling promotes endocrine resistance via signaling to cyclin D1. Inhibition of components of this signaling pathway could lead to therapeutic insights into the treatment of endocrine resistant breast cancer.

Mapping Transcription Regulation with Run-on and Sequencing Data Using the Web-Based tfTarget Gateway.

Run-on and sequencing assays like GRO-seq, PRO-seq, and ChRO-seq allow for joint profiling of transcription activity of transcriptional regulatory elements (TREs), i.e., promoters and active enhancers, and target genes. Variation in biological conditions, such as treated vs. control, results in changes in the activity of transcription factors (TFs), which induces concerted changes in TREs and target genes. By modeling the differences between two biological conditions, we developed the computational pipeline known as tfTarget that predicts a set of putative TREs and target genes responding to each TF under the biological condition of interest. In this chapter, we demonstrate the use of the new web-based tfTarget in mapping transcription regulation using run-on sequencing data.

Comprehensive microRNA analysis across genome-edited colorectal cancer organoid models reveals miR-24 as a candidate regulator of cell survival.

Somatic mutations drive colorectal cancer (CRC) by disrupting gene regulatory mechanisms. Distinct combinations of mutations can result in unique changes to regulatory mechanisms leading to variability in the efficacy of therapeutics. MicroRNAs are important regulators of gene expression, and their activity can be altered by oncogenic mutations. However, it is unknown how distinct combinations of CRC-risk mutations differentially affect microRNAs. Here, using genetically-modified mouse intestinal organoid (enteroid) models, we identify 12 different modules of microRNA expression patterns across different combinations of mutations common in CRC. We also show that miR-24-3p is aberrantly upregulated in genetically-modified mouse enteroids irrespective of mutational context. Furthermore, we identify an enrichment of miR-24-3p predicted targets in downregulated gene lists from various mutational contexts compared to WT. In follow-up experiments, we demonstrate that miR-24-3p promotes CRC cell survival in multiple cell contexts. Our novel characterization of genotype-specific patterns of miRNA expression offer insight into the mechanisms that drive inter-tumor heterogeneity and highlight candidate microRNA therapeutic targets for the advancement of precision medicine for CRC.

RNA Pol II pausing facilitates phased pluripotency transitions by buffering transcription.

Promoter-proximal RNA Pol II pausing is a critical step in transcriptional control. Pol II pausing has been predominantly studied in tissue culture systems. While Pol II pausing has been shown to be required for mammalian development, the phenotypic and mechanistic details of this requirement are unknown. Here, we found that loss of Pol II pausing stalls pluripotent state transitions within the epiblast of the early mouse embryo. Using Nelfb -/- mice and a NELFB degron mouse pluripotent stem cell model, we show that embryonic stem cells (ESCs) representing the naïve state of pluripotency successfully initiate a transition program but fail to balance levels of induced and repressed genes and enhancers in the absence of NELF. We found an increase in chromatin-associated NELF during transition from the naïve to later pluripotent states. Overall, our work defines the acute and long-term molecular consequences of NELF loss and reveals a role for Pol II pausing in the pluripotency continuum as a modulator of cell state transitions.

Genetic dissection of the RNA polymerase II transcription cycle.

How DNA sequence affects the dynamics and position of RNA Polymerase II (Pol II) during transcription remains poorly understood. Here, we used naturally occurring genetic variation in F1 hybrid mice to explore how DNA sequence differences affect the genome-wide distribution of Pol II. We measured the position and orientation of Pol II in eight organs collected from heterozygous F1 hybrid mice using ChRO-seq. Our data revealed a strong genetic basis for the precise coordinates of transcription initiation and promoter proximal pause, allowing us to redefine molecular models of core transcriptional processes. Our results implicate DNA sequence, including both known and novel DNA sequence motifs, as key determinants of the position of Pol II initiation and pause. We report evidence that initiation site selection follows a stochastic process similar to Brownian motion along the DNA template. We found widespread differences in the position of transcription termination, which impact the primary structure and stability of mature mRNA. Finally, we report evidence that allelic changes in transcription often affect mRNA and ncRNA expression across broad genomic domains. Collectively, we reveal how DNA sequences shape core transcriptional processes at single nucleotide resolution in mammals.

Cell type and gene expression deconvolution with BayesPrism enables Bayesian integrative analysis across bulk and single-cell RNA sequencing in oncology.

Inferring single-cell compositions and their contributions to global gene expression changes from bulk RNA sequencing (RNA-seq) datasets is a major challenge in oncology. Here we develop Bayesian cell proportion reconstruction inferred using statistical marginalization (BayesPrism), a Bayesian method to predict cellular composition and gene expression in individual cell types from bulk RNA-seq, using patient-derived, scRNA-seq as prior information. We conduct integrative analyses in primary glioblastoma, head and neck squamous cell carcinoma and skin cutaneous melanoma to correlate cell type composition with clinical outcomes across tumor types, and explore spatial heterogeneity in malignant and nonmalignant cell states. We refine current cancer subtypes using gene expression annotation after exclusion of confounding nonmalignant cells. Finally, we identify genes whose expression in malignant cells correlates with macrophage infiltration, T cells, fibroblasts and endothelial cells across multiple tumor types. Our work introduces a new lens to accurately infer cellular composition and expression in large cohorts of bulk RNA-seq data.

SETD2 Haploinsufficiency Enhances Germinal Center-Associated AICDA Somatic Hypermutation to Drive B-cell Lymphomagenesis.

SETD2 is the sole histone methyltransferase responsible for H3K36me3, with roles in splicing, transcription initiation, and DNA damage response. Homozygous disruption of SETD2 yields a tumor suppressor effect in various cancers. However, SETD2 mutation is typically heterozygous in diffuse large B-cell lymphomas. Here we show that heterozygous Setd2 deficiency results in germinal center (GC) hyperplasia and increased competitive fitness, with reduced DNA damage checkpoint activity and apoptosis, resulting in accelerated lymphomagenesis. Impaired DNA damage sensing in Setd2-haploinsufficient germinal center B (GCB) and lymphoma cells associated with increased AICDA-induced somatic hypermutation, complex structural variants, and increased translocations including those activating MYC. DNA damage was selectively increased on the nontemplate strand, and H3K36me3 loss was associated with greater RNAPII processivity and mutational burden, suggesting that SETD2-mediated H3K36me3 is required for proper sensing of cytosine deamination. Hence, Setd2 haploinsufficiency delineates a novel GCB context-specific oncogenic pathway involving defective epigenetic surveillance of AICDA-mediated effects on transcribed genes. SIGNIFICANCE: Our findings define a B cell-specific oncogenic effect of SETD2 heterozygous mutation, which unleashes AICDA mutagenesis of nontemplate strand DNA in the GC reaction, resulting in lymphomas with heavy mutational burden. GC-derived lymphomas did not tolerate SETD2 homozygous deletion, pointing to a novel context-specific therapeutic vulnerability. This article is highlighted in the In This Issue feature, p. 1599.

Prediction of histone post-translational modification patterns based on nascent transcription data.

The role of histone modifications in transcription remains incompletely understood. Here, we examine the relationship between histone modifications and transcription using experimental perturbations combined with sensitive machine-learning tools. Transcription predicted the variation in active histone marks and complex chromatin states, like bivalent promoters, down to single-nucleosome resolution and at an accuracy that rivaled the correspondence between independent ChIP-seq experiments. Blocking transcription rapidly removed two punctate marks, H3K4me3 and H3K27ac, from chromatin indicating that transcription is required for active histone modifications. Transcription was also required for maintenance of H3K27me3, consistent with a role for RNA in recruiting PRC2. A subset of DNase-I-hypersensitive sites were refractory to prediction, precluding models where transcription initiates pervasively at any open chromatin. Our results, in combination with past literature, support a model in which active histone modifications serve a supportive, rather than an essential regulatory, role in transcription.

E-Protein Inhibition in ILC2 Development Shapes the Function of Mature ILC2s during Allergic Airway Inflammation.

E-protein transcription factors limit group 2 innate lymphoid cell (ILC2) development while promoting T cell differentiation from common lymphoid progenitors. Inhibitors of DNA binding (ID) proteins block E-protein DNA binding in common lymphoid progenitors to allow ILC2 development. However, whether E-proteins influence ILC2 function upon maturity and activation remains unclear. Mice that overexpress ID1 under control of the thymus-restricted proximal Lck promoter (ID1tg/WT) have a large pool of primarily thymus-derived ILC2s in the periphery that develop in the absence of E-protein activity. We used these mice to investigate how the absence of E-protein activity affects ILC2 function and the genomic landscape in response to house dust mite (HDM) allergens. ID1tg/WT mice had increased KLRG1- ILC2s in the lung compared with wild-type (WT; ID1WT/WT) mice in response to HDM, but ID1tg/WT ILC2s had an impaired capacity to produce type 2 cytokines. Analysis of WT ILC2 accessible chromatin suggested that AP-1 and C/EBP transcription factors but not E-proteins were associated with ILC2 inflammatory gene programs. Instead, E-protein binding sites were enriched at functional genes in ILC2s during development that were later dynamically regulated in allergic lung inflammation, including genes that control ILC2 response to cytokines and interactions with T cells. Finally, ILC2s from ID1tg/WT compared with WT mice had fewer regions of open chromatin near functional genes that were enriched for AP-1 factor binding sites following HDM treatment. These data show that E-proteins shape the chromatin landscape during ILC2 development to dictate the functional capacity of mature ILC2s during allergic inflammation in the lung.

Darwinian genomics and diversity in the tree of life.

Genomics encompasses the entire tree of life, both extinct and extant, and the evolutionary processes that shape this diversity. To date, genomic research has focused on humans, a small number of agricultural species, and established laboratory models. Fewer than 18,000 of ∼2,000,000 eukaryotic species (<1%) have a representative genome sequence in GenBank, and only a fraction of these have ancillary information on genome structure, genetic variation, gene expression, epigenetic modifications, and population diversity. This imbalance reflects a perception that human studies are paramount in disease research. Yet understanding how genomes work, and how genetic variation shapes phenotypes, requires a broad view that embraces the vast diversity of life. We have the technology to collect massive and exquisitely detailed datasets about the world, but expertise is siloed into distinct fields. A new approach, integrating comparative genomics with cell and evolutionary biology, ecology, archaeology, anthropology, and conservation biology, is essential for understanding and protecting ourselves and our world. Here, we describe potential for scientific discovery when comparative genomics works in close collaboration with a broad range of fields as well as the technical, scientific, and social constraints that must be addressed.

Multiple stages of evolutionary change in anthrax toxin receptor expression in humans.

The advent of animal husbandry and hunting increased human exposure to zoonotic pathogens. To understand how a zoonotic disease may have influenced human evolution, we study changes in human expression of anthrax toxin receptor 2 (ANTXR2), which encodes a cell surface protein necessary for Bacillus anthracis virulence toxins to cause anthrax disease. In immune cells, ANTXR2 is 8-fold down-regulated in all available human samples compared to non-human primates, indicating regulatory changes early in the evolution of modern humans. We also observe multiple genetic signatures consistent with recent positive selection driving a European-specific decrease in ANTXR2 expression in multiple tissues affected by anthrax toxins. Our observations fit a model in which humans adapted to anthrax disease following early ecological changes associated with hunting and scavenging, as well as a second period of adaptation after the rise of modern agriculture.

Identification and prediction of developmental enhancers in sea urchin embryos.

BACKGROUND: The transcription of developmental regulatory genes is often controlled by multiple cis-regulatory elements. The identification and functional characterization of distal regulatory elements remains challenging, even in tractable model organisms like sea urchins. RESULTS: We evaluate the use of chromatin accessibility, transcription and RNA Polymerase II for their ability to predict enhancer activity of genomic regions in sea urchin embryos. ATAC-seq, PRO-seq, and Pol II ChIP-seq from early and late blastula embryos are manually contrasted with experimental cis-regulatory analyses available in sea urchin embryos, with particular attention to common developmental regulatory elements known to have enhancer and silencer functions differentially deployed among embryonic territories. Using the three functional genomic data types, machine learning models are trained and tested to classify and quantitatively predict the enhancer activity of several hundred genomic regions previously validated with reporter constructs in vivo. CONCLUSIONS: Overall, chromatin accessibility and transcription have substantial power for predicting enhancer activity. For promoter-overlapping cis-regulatory elements in particular, the distribution of Pol II is the best predictor of enhancer activity in blastula embryos. Furthermore, ATAC- and PRO-seq predictive value is stage dependent for the promoter-overlapping subset. This suggests that the sequence of regulatory mechanisms leading to transcriptional activation have distinct relevance at different levels of the developmental gene regulatory hierarchy deployed during embryogenesis.

Deconvolution of expression for nascent RNA-sequencing data (DENR) highlights pre-RNA isoform diversity in human cells.

MOTIVATION: Quantification of isoform abundance has been extensively studied at the mature RNA level using RNA-seq but not at the level of precursor RNAs using nascent RNA sequencing. RESULTS: We address this problem with a new computational method called Deconvolution of Expression for Nascent RNA-sequencing data (DENR), which models nascent RNA-sequencing read-counts as a mixture of user-provided isoforms. The baseline algorithm is enhanced by machine-learning predictions of active transcription start sites and an adjustment for the typical 'shape profile' of read-counts along a transcription unit. We show that DENR outperforms simple read-count-based methods for estimating gene and isoform abundances, and that transcription of multiple pre-RNA isoforms per gene is widespread, with frequent differences between cell types. In addition, we provide evidence that a majority of human isoform diversity derives from primary transcription rather than from post-transcriptional processes. AVAILABILITY AND IMPLEMENTATION: DENR and nascentRNASim are freely available at https://github.com/CshlSiepelLab/DENR (version v1.0.0) and https://github.com/CshlSiepelLab/nascentRNASim (version v0.3.0). SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.