The ENCODE Uniform Analysis Pipelines

Histone chaperones coupled to DNA replication and transcription control divergent chromatin elements to maintain cell fate

The manipulation of DNA replication and transcription can be harnessed to control cell fate. Central to the regulation of these DNA-templated processes are histone chaperones, which in turn are emerging as cell fate regulators. Histone chaperones are a group of proteins with diverse functions that are primarily involved in escorting histones to assemble nucleosomes and maintain the chromatin landscape. Whether distinct histone chaperone pathways control cell fate and whether they function using related mechanisms remain unclear. To address this, we performed a screen to assess the requirement of diverse histone chaperones in the self-renewal of hematopoietic stem and progenitor cells. Remarkably, all candidates were required to maintain cell fate to differing extents, with no clear correlation with their specific histone partners or DNA-templated process. Among all the histone chaperones, the loss of the transcription-coupled histone chaperone SPT6 most strongly promoted differentiation, even more than the major replication-coupled chromatin assembly factor complex CAF-1. To directly compare how DNA replication- and transcription-coupled histone chaperones maintain stem cell self-renewal, we generated an isogenic dual-inducible system to perturb each pathway individually. We found that SPT6 and CAF-1 perturbations required cell division to induce differentiation but had distinct effects on cell cycle progression, chromatin accessibility, and lineage choice. CAF-1 depletion led to S-phase accumulation, increased heterochromatic accessibility (particularly at H3K27me3 sites), and aberrant multilineage gene expression. In contrast, SPT6 loss triggered cell cycle arrest, altered accessibility at promoter elements, and drove lineage-specific differentiation, which is in part influenced by AP-1 transcription factors. Thus, CAF-1 and SPT6 histone chaperones maintain cell fate through distinct mechanisms, highlighting how different chromatin assembly pathways can be leveraged to alter cell fate.

Atlas of nascent RNA transcripts reveals tissue-specific enhancer to gene linkages

Gene transcription is controlled and modulated by regulatory regions, including enhancers and promoters. These regions are abundant in non-coding bidirectional transcription that results in generally unstable RNA. Using nascent RNA transcription data across hundreds of human samples, we identified over 800,000 regions containing bidirectional transcription. We then identify tissue specific, highly correlated transcription between bidirectional and gene regions. The identified correlated pairs, a bidirectional region and a gene, are enriched for disease associated SNPs and often supported by independent 3D data. We present these resources as a database called DBNascent ( https://nascent.colorado.edu/ ) which serves as a resource for future studies into gene regulation, enhancer associated RNAs, and transcription factors.

pC-SAC: A method for high-resolution 3D genome reconstruction from low-resolution Hi-C data

The three-dimensional (3D) organization of the genome is crucial for gene regulation, with disruptions linked to various diseases. High-throughput Chromosome Conformation Capture (Hi-C) and related technologies have advanced our understanding of 3D genome organization by mapping interactions between distal genomic regions. However, capturing enhancer-promoter interactions at high resolution remains challenging due to the high sequencing depth required. We introduce pC-SAC (probabilistically Constrained Self-Avoiding Chromatin), a novel computational method for producing accurate high-resolution Hi-C matrices from low-resolution data. pC-SAC uses adaptive importance sampling with sequential Monte Carlo to generate ensembles of 3D chromatin chains that satisfy physical constraints derived from low-resolution Hi-C data. Our method achieves over 95% accuracy in reconstructing high-resolution chromatin maps and identifies novel interactions enriched with candidate cis-regulatory elements (cCREs) and expression quantitative trait loci (eQTLs). Benchmarking against state-of-the-art deep learning models demonstrates pC-SAC's performance in both short- and long-range interaction reconstruction. pC-SAC offers a cost-effective solution for enhancing the resolution of Hi-C data, thus enabling deeper insights into 3D genome organization and its role in gene regulation and disease. Our tool can be found at https://github.com/G2Lab/pCSAC.

Chromatin structures from integrated AI and polymer physics model

The physical organization of the genome in three-dimensional space regulates many biological processes, including gene expression and cell differentiation. Three-dimensional characterization of genome structure is critical to understanding these biological processes. Direct experimental measurements of genome structure are challenging; computational models of chromatin structure are therefore necessary. We develop an approach that combines a particle-based chromatin polymer model, molecular simulation, and machine learning to efficiently and accurately estimate chromatin structure from indirect measures of genome structure. More specifically, we introduce a new approach where the interaction parameters of the polymer model are extracted from experimental Hi-C data using a graph neural network (GNN). We train the GNN on simulated data from the underlying polymer model, avoiding the need for large quantities of experimental data. The resulting approach accurately estimates chromatin structures across all chromosomes and across several experimental cell lines despite being trained almost exclusively on simulated data. The proposed approach can be viewed as a general framework for combining physical modeling with machine learning, and it could be extended to integrate additional biological data modalities. Ultimately, we achieve accurate and high-throughput estimations of chromatin structure from Hi-C data, which will be necessary as experimental methodologies, such as single-cell Hi-C, improve.

Copy number normalization distinguishes differential signals driven by copy number differences in ATAC-seq and ChIP-seq

A common objective across ATAC-seq and ChIP-seq analyses is to identify differential signals across contrasted conditions. However, in differential analyses, the impact of copy number variation is often overlooked. Here, we demonstrated copy number differences among samples could drive, if not dominate, differential signals. To address this, we propose a pipeline featuring copy number normalization. By comparing the averaged signal per gene copy, it effectively segregates differential signals driven by copy number from other factors. Further applying it to Down syndrome unveiled distinct dosage-dependent and -independent changes on chromosome 21. Thus, we recommend copy number normalization as a general approach.

Characterization of diverse Cas9 orthologs for genome and epigenome editing

CRISPR-Cas9 systems have revolutionized biotechnology, creating diverse new opportunities for biomedical research and therapeutic genome and epigenome editing. Despite the abundance of bacterial CRISPR-Cas9 systems, relatively few are effective in human cells, limiting the overall potential of CRISPR technology. To expand the CRISPR-Cas toolbox, we characterized a set of type II CRISPR-Cas9 systems from select bacterial genera and species encoding diverse Cas9s. Four systems demonstrated robust and specific gene repression in human cells when used as nuclease-null dCas9s fused with a KRAB domain and were also highly active nucleases in human cells. These systems have distinct protospacer adjacent motifs (PAMs), including AT-rich motifs and sgRNA features orthogonal to the commonly used Staphylococcus aureus and Streptococcus pyogenes Cas9s. Additionally, we assessed gene activation when fused with the p300 catalytic domain. Notably, S. uberis Cas9 performed competitively against benchmarks with promising repression, activation, nuclease, and base editing activity. This study expands the CRISPR-Cas9 repertoire, enabling effective genome and epigenome editing for diverse applications.

Functional analysis of cancer-associated germline risk variants

Single-nucleotide variants (SNVs) in regulatory DNA are linked to inherited cancer risk. Massively parallel reporter assays of 4,041 SNVs linked to 13 neoplasms comprising >90% of human malignancies were performed in pertinent primary human cell types and then integrated with matching chromatin accessibility, DNA looping and expression quantitative trait loci data to nominate 380 potentially regulatory SNVs and their putative target genes. The latter highlighted specific protein networks in lifetime cancer risk, including mitochondrial translation, DNA damage repair and Rho GTPase activity. A CRISPR knockout screen demonstrated that a subset of germline putative risk genes also enables the growth of established cancers. Editing one SNV, rs10411210 , showed that its risk allele increases rhophilin RHPN2 expression and stimulus-responsive RhoA activation, indicating that individual SNVs may upregulate cancer-linked pathways. These functional data are a resource for variant prioritization efforts and further interrogation of the mechanisms underlying inherited risk for cancer.

Cooperation between the Hippo and MAPK pathway activation drives acquired resistance to TEAD inhibition

TEAD (transcriptional enhanced associate domain) transcription factors (TEAD1-4) serve as the primary effectors of the Hippo signaling pathway in various cancers. Targeted therapy leads to the emergence of resistance and the underlying mechanism of resistance to TEAD inhibition in cancers is less characterized. We uncover that upregulation of the AP-1 (activator protein-1) transcription factors, along with restored YAP (yes-associated protein) and TEAD activity, drives resistance to GNE-7883, a pan-TEAD inhibitor. Acute GNE-7883 treatment abrogates YAP-TEAD binding and attenuates FOSL1 (FOS like 1) activity. TEAD inhibitor resistant cells restore YAP and TEAD chromatin occupancy, acquire additional FOSL1 binding and exhibit increased MAPK (mitogen-activated protein kinase) pathway activity. FOSL1 is required for the chromatin binding of YAP and TEAD. This study describes a clinically relevant interplay between the Hippo and MAPK pathway and highlights the key role of MAPK pathway inhibitors in mitigating resistance to TEAD inhibition in Hippo pathway dependent cancers.

Modeling and designing enhancers by introducing and harnessing transcription factor binding units

Enhancers serve as pivotal regulators of gene expression throughout various biological processes by interacting with transcription factors (TFs). While transcription factor binding sites (TFBSs) are widely acknowledged as key determinants of TF binding and enhancer activity, the significant role of their surrounding context sequences remains to be quantitatively characterized. Here we propose the concept of transcription factor binding unit (TFBU) to modularly model enhancers by quantifying the impact of context sequences surrounding TFBSs using deep learning models. Based on this concept, we develop DeepTFBU, a comprehensive toolkit for enhancer design. We demonstrate that designing TFBS context sequences can significantly modulate enhancer activities and produce cell type-specific responses. DeepTFBU is also highly efficient in the de novo design of enhancers containing multiple TFBSs. Furthermore, DeepTFBU enables flexible decoupling and optimization of generalized enhancers. We prove that TFBU is a crucial concept, and DeepTFBU is highly effective for rational enhancer design.

PIK3CA mutation fortifies molecular determinants for immune signaling in vascular cancers

Angiosarcomas are a group of vascular cancers that form malignant blood vessels. These malignancies are seemingly inflamed primarily due to their pathognomonic nature, which consists of irregular endothelium and tortuous blood channels. PIK3CA mutations are oncogenic and disrupt the PI3K pathway. In this study, we aimed to define the molecular and functional consequences of oncogenic PIK3CA mutations in angiosarcoma. We first generated two isogenic hemangiosarcoma cell lines harboring the H1047R hotspot mutations in PIK3CA gene using CRISPR/Cas9. We found PIK3CA-mutant cells established distinct molecular signatures in global gene expression and chromatin accessibility, which were associated with enrichment of immune cytokine signaling, including IL-6, IL-8, and MCP-1. These molecular processes were disrupted by the PI3K-α specific inhibitor, alpelisib. We also observed that the molecular distinctions in PIK3CA-mutant cells were linked to metabolic reprogramming in glycolytic activity and mitochondrial respiration. Our multi-omics analysis revealed that activating PIK3CA mutations regulate molecular machinery that contributes to phenotypic alterations and resistance to alpelisib. Furthermore, we identified potential therapeutic vulnerabilities of PIK3CA mutations in response to PI3K-α inhibition mediated by MAPK signaling. In summary, we demonstrate that PIK3CA mutations perpetuate PI3K activation and reinforce immune enrichment to promote drug resistance in vascular cancers.

scATAC-seq generates more accurate and complete regulatory maps than bulk ATAC-seq

Bulk ATAC-seq assays have been used to map and profile the chromatin accessibility of regulatory elements such as enhancers, promoters, and insulators. This has provided great insight into the regulation of gene expression in many cell types in a variety of organisms. To date, ATAC-seq has most often been used to provide an average evaluation of chromatin accessibility in populations of cells. The development of a single cell approach (scATAC-seq) assay enables researchers to evaluate chromatin accessibility in individual cells and identify sub-groups in mixed populations of cells. To investigate the full potential of single-cell epigenomic data, we have comprehensively compared the information derived from bulk ATAC-seq and scATAC-seq in populations of cells. We found that the chromatin architecture signal is the same using bulk ATAC-seq and scATAC-seq to analyse aliquots of the same cell population. However, scATAC-seq provides substantially higher data quality compared to bulk ATAC-seq improving the sensitivity to detect relatively weak, but functionally important ATAC-seq signals. Furthermore, we found that scATAC-seq identified differences in what was previously assumed to be a homogenous population of cells. Finally, we determined the number of cells required to generate aggregated open chromatin profiles from single cells and to identify biologically meaningful clusters after pseudo-bulking of data. This study illustrates the added value of using scATAC-seq rather than bulk ATAC-seq in evaluating both homogeneous and heterogeneous populations of cells. This paper provides a comprehensive guide on the benefits of using scATAC-seq data to study gene regulation.

ChromatinHD connects single-cell DNA accessibility and conformation to gene expression through scale-adaptive machine learning

Gene regulation is inherently multiscale, but scale-adaptive machine learning methods that fully exploit this property in single-nucleus accessibility data are still lacking. Here, we develop ChromatinHD, a pair of scale-adaptive models that uses the raw accessibility data, without peak-calling or windows, to link regions to gene expression and determine differentially accessible chromatin. We show how ChromatinHD consistently outperforms existing peak and window-based approaches and find that this is due to a large number of uniquely captured, functional accessibility changes within and outside of putative cis-regulatory regions. Furthermore, ChromatinHD can delineate collaborating regulatory regions, including their preferential genomic conformations, that drive gene expression. Finally, our models also use changes in ATAC-seq fragment lengths to identify dense binding of transcription factors, a feature not captured by footprinting methods. Altogether, ChromatinHD, available at https://chromatinhd.org , is a suite of computational tools that enables a data-driven understanding of chromatin accessibility at various scales and how it relates to gene expression.

GWAS-Informed data integration and non-coding CRISPRi screen illuminate genetic etiology of bone mineral density

Over 1,100 independent signals have been identified with genome-wide association studies (GWAS) for bone mineral density (BMD), a key risk factor for mortality-increasing fragility fractures; however, the effector gene(s) for most remain unknown. Informed by a variant-to-gene mapping strategy implicating 89 non-coding elements predicted to regulate osteoblast gene expression at BMD GWAS loci, we executed a single-cell CRISPRi screen in human fetal osteoblasts (hFOBs). The BMD relevance of hFOBs was supported by heritability enrichment from stratified LD-score regression involving 98 cell types grouped into 15 tissues. 23 genes showed perturbation in the screen, with four (ARID5B, CC2D1B, EIF4G2, and NCOA3) exhibiting consistent effects upon siRNA knockdown on three measures of osteoblast maturation and mineralization. Lastly, additional heritability enrichments, genetic correlations, and multi-trait fine-mapping revealed unexpectedly that many BMD GWAS signals are pleiotropic and likely mediate their effects via non-bone tissues. Extending our CRISPRi screening approach to these tissues could play a key role in fully elucidating the etiology of BMD.

Direct and indirect effects of spliceosome disruption compromise gene regulation by Nonsense-Mediated mRNA Decay

Pre-mRNA splicing, carried out in the nucleus by a large ribonucleoprotein machine known as the spliceosome, is functionally and physically coupled to the mRNA surveillance pathway in the cytoplasm called nonsense mediated mRNA decay (NMD). The NMD pathway monitors for premature translation termination signals, which can result from alternative splicing, by relying on the exon junction complex (EJC) deposited on exon-exon junctions by the spliceosome. Recently, multiple genetic screens in human cell lines have identified numerous spliceosome components as putative NMD factors. Using publicly available RNA-seq datasets from K562 and HepG2 cells depleted of 18 different spliceosome components, we find that natural NMD targeted mRNA isoforms are upregulated when members of the catalytic spliceosome are reduced. While some of this increase could be due to widespread pleiotropic effects of spliceosome dysfunction (e.g., reduced expression of NMD factors due to mis-splicing of their mRNAs), we identify that AQR, SF3B1, SF3B4 and CDC40 may have a more direct role in NMD. We also test the hypothesis that increased production of novel NMD substrates may overwhelm the pathway to find a direct correlation between the amount of novel NMD substrates detected and the degree of NMD inhibition observed. Finally, similar transcriptome alterations and NMD substrate upregulation are also observed in cells treated with spliceosome inhibitors and in cells derived from retinitis pigmentosa patients with mutations in PRPF8 and PRPF31. Overall, our results show that regardless of the cause, spliceosome disruption upregulates a broad set of NMD targets, which could contribute to cellular dysfunction in spliceosomopathies.

Angiotensin receptor blockers modulate the lupus CD4+ T cell epigenome characterized by TNF family-linked signaling

In systemic lupus erythematosus (lupus), environmental effects acting within a permissive genetic background lead to autoimmune dysregulation. Dysfunction of CD4+ T cells contributes to pathology by providing help to autoreactive B and T cells, and CD4+ T cell dysfunction coincides with altered DNA methylation and histone modifications of select gene loci. However, chromatin accessibility states of distinct T cell subsets and mechanisms driving heterogeneous chromatin states across patients remain poorly understood. We defined the transcriptome and epigenome of multiple CD4+ T cell populations from patients with lupus and healthy individuals. Most patients with lupus, regardless of disease activity, had enhanced chromatin accessibility bearing hallmarks of inflammatory cytokine signals. Single-cell approaches revealed that chromatin changes extended to naive CD4+ T cells, uniformly affecting naive subpopulations. Transcriptional data and cellular and protein analyses suggested that the TNF family members, TNF-α, LIGHT, and TWEAK, were linked to observed molecular changes and the altered lupus chromatin state. However, we identified a patient subgroup prescribed angiotensin receptor blockers (ARBs), which lacked TNF-linked lupus chromatin accessibility features. These data raise questions about the role of lupus-associated chromatin changes in naive CD4+ T cell activation and differentiation and implicate ARBs in the regulation of disease-driven epigenetic states.

A novel human protein-coding locus identified using a targeted RNA enrichment technique

BACKGROUND

Accurate and comprehensive genomic annotation, including the full list of protein-coding genes, is vital for understanding the molecular mechanisms of human biology. We have previously shown that the genome contains a multitude of yet hidden functional exons and transcripts, some of which might represent novel mRNAs. These results resonate with those from other groups and strongly argue that two decades after the completion of the first draft of the human genome sequence, the current annotation of human genes and transcripts remains far from being complete.

RESULTS

Using a targeted RNA enrichment technique, we showed that one of the novel functional exons previously discovered by us and currently annotated as part of a long non-coding RNA, is actually a part of a novel protein-coding gene, InSETG-4, which encodes a novel human protein with no known homologs or motifs. We found that InSETG-4 is induced by various DNA-damaging agents across multiple cell types and therefore might represent a novel component of DNA damage response. Despite its low abundance in bulk cell populations, InSETG-4 exhibited expression restricted to a small fraction of cells, as demonstrated by the amplification-based single-molecule fluorescence in situ hybridization (asmFISH) analysis.

CONCLUSIONS

This study argues that yet undiscovered human protein-coding genes exist and provides an example of how targeted RNA enrichment techniques can help to fill this major gap in our knowledge of the information encoded in the human genome.

MicroRNA-mediated network redundancy is constrained by purifying selection and contributes to expression robustness in Drosophila melanogaster

MicroRNAs (miRNAs) are post-transcriptional, non-coding regulatory RNAs that function coordinately with transcription factors (TFs) in gene regulatory networks. TFs and their targets are often co-regulated by miRNAs, forming composite feedforward circuits (cFFCs) with varying degrees of redundancy, primarily mediated by miRNAs. However, the maintenance of miRNA-mediated regulatory redundancy and its impact on gene expression evolution remain elusive. By integrating ChIP-seq data from ENCODE and miRNA targeting from TargetScanFly, we quantified miRNA-mediated cFFC redundancy in Drosophila melanogaster embryos and larvae, revealing more than three quarters of miRNA targets are involved in redundant cFFCs. Higher cFFC redundancy, where more miRNAs target the same gene within a cFFC, is correlated with stronger purifying selection, reduced expression divergence between species, and increased expression stability under heat shock stress. Redundant cFFCs primarily regulate older or broadly expressed young genes. These findings highlight the role of miRNA-mediated cFFC redundancy in enhancing gene expression robustness through natural selection.

Systematic perturbation screens identify regulators of inflammatory macrophage states and a role for TNF mRNA m6A modification

Macrophages exhibit remarkable functional plasticity, a requirement for their central role in tissue homeostasis. During chronic inflammation, macrophages acquire sustained inflammatory 'states' that contribute to disease, but there is limited understanding of the regulatory mechanisms that drive their generation. Here we describe a systematic functional genomics approach that combines genome-wide phenotypic screening in primary murine macrophages with transcriptional and cytokine profiling of genetic perturbations in primary human macrophages to uncover regulatory circuits of inflammatory states. This process identifies regulators of five distinct states associated with key features of macrophage function. Among these regulators, loss of the N6-methyladenosine (m6A) writer components abolishes m6A modification of TNF transcripts, thereby enhancing mRNA stability and TNF production associated with multiple inflammatory pathologies. Thus, phenotypic characterization of primary murine and human macrophages describes the regulatory circuits underlying distinct inflammatory states, revealing post-transcriptional control of TNF mRNA stability as an immunosuppressive mechanism in innate immunity.

Comprehensive analysis of computational approaches in plant transcription factors binding regions discovery

Transcription factors (TFs) are regulatory proteins which bind to a specific DNA region known as the transcription factor binding regions (TFBRs) to regulate the rate of transcription process. The identification of TFBRs has been made possible by a number of experimental and computational techniques established during the past few years. The process of TFBR identification involves peak identification in the binding data, followed by the identification of motif characteristics. Using the same binding data attempts have been made to raise computational models to identify such binding regions which could save time and resources spent for binding experiments. These computational approaches depend a lot on what way they learn and how. These existing computational approaches are skewed heavily around human TFBRs discovery, while plants have drastically different genomic setup for regulation which these approaches have grossly ignored. Here, we provide a comprehensive study of the current state of the matters in plant specific TF discovery algorithms. While doing so, we encountered several software tools' issues rendering the tools not useable to researches. We fixed them and have also provided the corrected scripts for such tools. We expect this study to serve as a guide for better understanding of software tools' approaches for plant specific TFBRs discovery and the care to be taken while applying them, especially during cross-species applications. The corrected scripts of these software tools are made available at https://github.com/SCBB-LAB/Comparative-analysis-of-plant-TFBS-software.

Machine-guided design of cell-type-targeting 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 body1-3. 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 these intended purposes has arisen naturally. Here we present a platform to engineer and validate synthetic CREs capable of driving gene expression with programmed cell-type specificity. We take advantage of innovations in deep neural network modelling of CRE activity across three cell types, efficient in silico optimization and massively parallel reporter assays to design and empirically test thousands of CREs4-8. Through large-scale in vitro validation, we show that synthetic sequences are more effective at driving cell-type-specific expression in three cell lines compared with natural sequences from the human genome and achieve specificity in analogous tissues when tested in vivo. Synthetic sequences exhibit distinct motif vocabulary associated with activity in the on-target cell type and a simultaneous reduction in the activity of off-target cells. Together, we provide a generalizable framework to prospectively engineer CREs from massively parallel reporter assay models and demonstrate the required literacy to write fit-for-purpose regulatory code.

High-throughput optimized prime editing mediated endogenous protein tagging for pooled imaging of protein localization

The subcellular organization of proteins carries important information on cellular state and gene function, yet currently there are no technologies that enable accurate measurement of subcellular protein localizations at scale. Here we develop an approach for pooled endogenous protein tagging using prime editing, which coupled with an optical readout and sequencing, provides a snapshot of proteome organization in a manner akin to perturbation-based CRISPR screens. We constructed a pooled library of 17,280 pegRNAs designed to exhaustively tag 60 endogenous proteins spanning diverse localization patterns and explore a large space of genomic and pegRNA design parameters. Pooled measurements of tagging efficiency uncovered both genomic and pegRNA features associated with increased efficiency, including epigenetic states and interactions with transcription. We integrate pegRNA features into a computational model with predictive value for tagging efficiency to constrain the design space of pegRNAs for large-scale peptide knock-in. Lastly, we show that combining in-situ pegRNA sequencing with high-throughput deep learning image analysis, enables exploration of subcellular protein localization patterns for many proteins in parallel following a single pooled lentiviral transduction, setting the stage for scalable studies of proteome dynamics across cell types and environmental perturbations.

A TrkB and TrkC partial agonist restores deficits in synaptic function and promotes activity-dependent synaptic and microglial transcriptomic changes in a late-stage Alzheimer's mouse model

INTRODUCTION

Tropomyosin related kinase B (TrkB) and C (TrkC) receptor signaling promotes synaptic plasticity and interacts with pathways affected by amyloid beta (Aβ) toxicity. Upregulating TrkB/C signaling could reduce Alzheimer's disease (AD)-related degenerative signaling, memory loss, and synaptic dysfunction.

METHODS

PTX-BD10-2 (BD10-2), a small molecule TrkB/C receptor partial agonist, was orally administered to aged London/Swedish-APP mutant mice (APPL/S) and wild-type controls. Effects on memory and hippocampal long-term potentiation (LTP) were assessed using electrophysiology, behavioral studies, immunoblotting, immunofluorescence staining, and RNA sequencing.

RESULTS

In APPL/S mice, BD10-2 treatment improved memory and LTP deficits. This was accompanied by normalized phosphorylation of protein kinase B (Akt), calcium-calmodulin-dependent kinase II (CaMKII), and AMPA-type glutamate receptors containing the subunit GluA1; enhanced activity-dependent recruitment of synaptic proteins; and increased excitatory synapse number. BD10-2 also had potentially favorable effects on LTP-dependent complement pathway and synaptic gene transcription.

DISCUSSION

BD10-2 prevented APPL/S/Aβ-associated memory and LTP deficits, reduced abnormalities in synapse-related signaling and activity-dependent transcription of synaptic genes, and bolstered transcriptional changes associated with microglial immune response.

HIGHLIGHTS

Small molecule modulation of tropomyosin related kinase B (TrkB) and C (TrkC) restores long-term potentiation (LTP) and behavior in an Alzheimer's disease (AD) model. Modulation of TrkB and TrkC regulates synaptic activity-dependent transcription. TrkB and TrkC receptors are candidate targets for translational therapeutics. Electrophysiology combined with transcriptomics elucidates synaptic restoration. LTP identifies neuron and microglia AD-relevant human-mouse co-expression modules.

Physical modeling of nucleosome clustering in euchromatin resulting from interactions between epigenetic reader proteins

Euchromatin is an accessible phase of genetic material containing genes that encode proteins with increased expression levels. The structure of euchromatin in vitro has been described as a 30-nm fiber formed from ordered nucleosome arrays. However, recent advances in microscopy have revealed an in vivo euchromatin architecture that is much more disordered, characterized by variable-length linker DNA and sporadic nucleosome clusters. In this work, we develop a theoretical model to elucidate factors contributing to the disordered in vivo architecture of euchromatin. We begin by developing a 1D model of nucleosome positioning that captures the interactions between bound epigenetic reader proteins to predict the distribution of DNA linker lengths between adjacent nucleosomes. We then use the predicted linker lengths to construct 3D chromatin configurations consistent with the physical properties of DNA within the nucleosome array, and we evaluate the distribution of nucleosome cluster sizes in those configurations. Our model reproduces experimental cluster-size distributions, which are dramatically influenced by the local pattern of epigenetic marks and the concentration of reader proteins. Based on our model, we attribute the disordered arrangement of euchromatin to the heterogeneous binding of reader proteins and subsequent short-range interactions between bound reader proteins on adjacent nucleosomes. By replicating experimental results with our physics-based model, we propose a mechanism for euchromatin organization in the nucleus that impacts gene regulation and the maintenance of epigenetic marks.

O-GlcNAcylation controls pro-fibrotic transcriptional regulatory signaling in myofibroblasts

Tissue injury causes activation of mesenchymal lineage cells into wound-repairing myofibroblasts (MFs), whose uncontrolled activity ultimately leads to fibrosis. Although this process is triggered by deep metabolic and transcriptional reprogramming, functional links between these two key events are not yet understood. Here, we report that the metabolic sensor post-translational modification O-linked β-D-N-acetylglucosaminylation (O-GlcNAcylation) is increased and required for myofibroblastic activation. Inhibition of protein O-GlcNAcylation impairs archetypal myofibloblast cellular activities including extracellular matrix gene expression and collagen secretion/deposition as defined in vitro and using ex vivo and in vivo murine liver injury models. Mechanistically, a multi-omics approach combining proteomic, epigenomic, and transcriptomic data mining revealed that O-GlcNAcylation controls the MF transcriptional program by targeting the transcription factors Basonuclin 2 (BNC2) and TEA domain transcription factor 4 (TEAD4) together with the Yes-associated protein 1 (YAP1) co-activator. Indeed, inhibition of protein O-GlcNAcylation impedes their stability leading to decreased functionality of the BNC2/TEAD4/YAP1 complex towards promoting activation of the MF transcriptional regulatory landscape. We found that this involves O-GlcNAcylation of BNC2 at Thr455 and Ser490 and of TEAD4 at Ser69 and Ser99. Altogether, this study unravels protein O-GlcNAcylation as a key determinant of myofibroblastic activation and identifies its inhibition as an avenue to intervene with fibrogenic processes.

RNA polymerases reshape chromatin and coordinate transcription on individual fibers

During eukaryotic transcription, RNA polymerases must initiate and pause within a crowded, complex environment, surrounded by nucleosomes and other transcriptional activity. This environment creates a spatial arrangement along individual chromatin fibers ripe for both competition and coordination, yet these relationships remain largely unknown owing to the inherent limitations of traditional structural and sequencing methodologies. To address these limitations, we employed long-read chromatin fiber sequencing (Fiber-seq) to visualize RNA polymerases within their native chromatin context at single-molecule and near single-nucleotide resolution along up to 30 kb fibers. We demonstrate that Fiber-seq enables the identification of single-molecule RNA Polymerase (Pol) II and III transcription associated footprints, which, in aggregate, mirror bulk short-read sequencing-based measurements of transcription. We show that Pol II pausing destabilizes downstream nucleosomes, with frequently paused genes maintaining a short-term memory of these destabilized nucleosomes. Furthermore, we demonstrate pervasive direct coordination and anti-coordination between nearby Pol II genes, Pol III genes, transcribed enhancers, and insulator elements. This coordination is largely limited to spatially organized elements within 5 kb of each other, implicating short-range chromatin environments as a predominant determinant of coordinated polymerase initiation. Overall, transcription initiation reshapes surrounding nucleosome architecture and coordinates nearby transcriptional machinery along individual chromatin fibers.

MESIA: multi-epigenome sample integration approach for precise peak calling

The assay for transposase-accessible chromatin with sequencing (ATAC-seq) is the most widely used method for measuring chromatin accessibility. Researchers have included multi-sample replication in ATAC-seq experimental designs. In epigenomic analysis, researchers should measure subtle changes in the peak by considering the read depth of individual samples. It is important to determine whether the peaks of each replication have an integrative meaning for the region of interest observed during multi-sample integration. We developed multi-epigenome sample integration approach for precise peak calling (MESIA), which integrates replication with high representativeness and reproducibility in multi-sample replication and determines the optimal peak. After identifying the reproducibility between all replications, our method integrated multiple samples determined as representative replicates. MESIA detected 6.06 times more peaks, and the value of the peaks was 1.32 times higher than the previously used method. MESIA is a shell-script-based open-source code that provides researchers involved in the epigenome with comprehensive insights.

Seq2science: an end-to-end workflow for functional genomics analysis

Sequencing databases contain enormous amounts of functional genomics data, making them an extensive resource for genome-scale analysis. Reanalyzing publicly available data, and integrating it with new, project-specific data sets, can be invaluable. With current technologies, genomic experiments have become feasible for virtually any species of interest. However, using and integrating this data comes with its challenges, such as standardized and reproducible analysis. Seq2science is a multi-purpose workflow that covers preprocessing, quality control, visualization, and analysis of functional genomics sequencing data. It facilitates the downloading of sequencing data from all major databases, including NCBI SRA, EBI ENA, DDBJ, GSA, and ENCODE. Furthermore, it automates the retrieval of any genome assembly available from Ensembl, NCBI, and UCSC. It has been tested on a variety of species, and includes diverse workflows such as ATAC-, RNA-, and ChIP-seq. It consists of both generic as well as advanced steps, such as differential gene expression or peak accessibility analysis and differential motif analysis. Seq2science is built on the Snakemake workflow language and thus can be run on a range of computing infrastructures. It is available at https://github.com/vanheeringen-lab/seq2science.

The 3D chromatin landscape of rhabdomyosarcoma

Rhabdomyosarcoma (RMS) is a pediatric soft tissue cancer with a lack of precision therapy options for patients. We hypothesized that with a general paucity of known mutations in RMS, chromatin structural driving mechanisms are essential for tumor proliferation. Thus, we carried out high-depth in situ Hi-C in representative cell lines and patient-derived xenografts (PDXs) to define chromatin architecture in each major RMS subtype. We report a comprehensive 3D chromatin structural analysis and characterization of fusion-positive (FP-RMS) and fusion-negative RMS (FN-RMS). We have generated spike-in in situ Hi-C chromatin interaction maps for the most common FP-RMS and FN-RMS cell lines and compared our data with PDX models. In our studies, we uncover common and distinct structural elements in large Mb-scale chromatin compartments, tumor-essential genes within variable topologically associating domains and unique patterns of structural variation. Our high-depth chromatin interactivity maps and comprehensive analyses provide context for gene regulatory events and reveal functional chromatin domains in RMS.

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.

Genome-wide chromatin accessibility landscape and dynamics of transcription factor networks during ovule and fiber development in cotton

BACKGROUND

The development of cotton fiber is regulated by the orchestrated binding of regulatory proteins to cis-regulatory elements associated with developmental genes. The cis-trans regulatory dynamics occurred throughout the course of cotton fiber development are elusive. Here we generated genome-wide high-resolution DNase I hypersensitive sites (DHSs) maps to understand the regulatory mechanisms of cotton ovule and fiber development.

RESULTS

We generated DNase I hypersensitive site (DHS) profiles from cotton ovules at 0 and 3 days post anthesis (DPA) and fibers at 8, 12, 15, and 18 DPA. We obtained a total of 1185 million reads and identified a total of 199,351 DHSs through ~ 30% unique mapping reads. It should be noted that more than half of DNase-seq reads mapped multiple genome locations and were not analyzed in order to achieve a high specificity of peak profile and to avoid bias from repetitive genomic regions. Distinct chromatin accessibilities were observed in the ovules (0 and 3 DPA) compared to the fiber elongation stages (8, 12, 15, and 18 DPA). Besides, the chromatin accessibility during ovules was particularly elevated in genomic regions enriched with transposable elements (TEs) and genes in TE-enriched regions were involved in ovule cell division. We analyzed cis-regulatory modules and revealed the influence of hormones on fiber development from the regulatory divergence of transcription factor (TF) motifs. Finally, we constructed a reliable regulatory network of TFs related to ovule and fiber development based on chromatin accessibility and gene co-expression network. From this network, we discovered a novel TF, WRKY46, which may shape fiber development by regulating the lignin content.

CONCLUSIONS

Our results not only reveal the contribution of TEs in fiber development, but also predict and validate the TFs related to fiber development, which will benefit the research of cotton fiber molecular breeding.

Gene editing without ex vivo culture evades genotoxicity in human hematopoietic stem cells

Gene editing the BCL11A erythroid enhancer is a validated approach to fetal hemoglobin (HbF) induction for β-hemoglobinopathy therapy, though heterogeneity in edit allele distribution and HbF response may impact its safety and efficacy. Here we compared combined CRISPR-Cas9 endonuclease editing of the BCL11A +58 and +55 enhancers with leading gene modification approaches under clinical investigation. We found that combined targeting of the BCL11A +58 and +55 enhancers with 3xNLS-SpCas9 and two sgRNAs resulted in superior HbF induction, including in engrafting erythroid cells from sickle cell disease (SCD) patient xenografts, attributable to simultaneous disruption of core half E-box/GATA motifs at both enhancers. We corroborated prior observations that double strand breaks (DSBs) could produce unintended on- target outcomes in hematopoietic stem and progenitor cells (HSPCs) such as long deletions and centromere-distal chromosome fragment loss. We show these unintended outcomes are a byproduct of cellular proliferation stimulated by ex vivo culture. Editing HSPCs without cytokine culture bypassed long deletion and micronuclei formation while preserving efficient on-target editing and engraftment function. These results indicate that nuclease editing of quiescent hematopoietic stem cells (HSCs) limits DSB genotoxicity while maintaining therapeutic potency and encourages efforts for in vivo delivery of nucleases to HSCs.