Higher-Order Inter-chromosomal Hubs Shape 3D Genome Organization in the Nucleus.

Eukaryotic genomes are packaged into a 3-dimensional structure in the nucleus. Current methods for studying genome-wide structure are based on proximity ligation. However, this approach can fail to detect known structures, such as interactions with nuclear bodies, because these DNA regions can be too far apart to directly ligate. Accordingly, our overall understanding of genome organization remains incomplete. Here, we develop split-pool recognition of interactions by tag extension (SPRITE), a method that enables genome-wide detection of higher-order interactions within the nucleus. Using SPRITE, we recapitulate known structures identified by proximity ligation and identify additional interactions occurring across larger distances, including two hubs of inter-chromosomal interactions that are arranged around the nucleolus and nuclear speckles. We show that a substantial fraction of the genome exhibits preferential organization relative to these nuclear bodies. Our results generate a global model whereby nuclear bodies act as inter-chromosomal hubs that shape the overall packaging of DNA in the nucleus.

HIV-1-induced cytokines deplete homeostatic innate lymphoid cells and expand TCF7-dependent memory NK cells.

Human immunodeficiency virus 1 (HIV-1) infection is associated with heightened inflammation and excess risk of cardiovascular disease, cancer and other complications. These pathologies persist despite antiretroviral therapy. In two independent cohorts, we found that innate lymphoid cells (ILCs) were depleted in the blood and gut of people with HIV-1, even with effective antiretroviral therapy. ILC depletion was associated with neutrophil infiltration of the gut lamina propria, type 1 interferon activation, increased microbial translocation and natural killer (NK) cell skewing towards an inflammatory state, with chromatin structure and phenotype typical of WNT transcription factor TCF7-dependent memory T cells. Cytokines that are elevated during acute HIV-1 infection reproduced the ILC and NK cell abnormalities ex vivo. These results show that inflammatory cytokines associated with HIV-1 infection irreversibly disrupt ILCs. This results in loss of gut epithelial integrity, microbial translocation and memory NK cells with heightened inflammatory potential, and explains the chronic inflammation in people with HIV-1.

Ebola Virus Glycoprotein with Increased Infectivity Dominated the 2013-2016 Epidemic.

The magnitude of the 2013-2016 Ebola virus disease (EVD) epidemic enabled an unprecedented number of viral mutations to occur over successive human-to-human transmission events, increasing the probability that adaptation to the human host occurred during the outbreak. We investigated one nonsynonymous mutation, Ebola virus (EBOV) glycoprotein (GP) mutant A82V, for its effect on viral infectivity. This mutation, located at the NPC1-binding site on EBOV GP, occurred early in the 2013-2016 outbreak and rose to high frequency. We found that GP-A82V had heightened ability to infect primate cells, including human dendritic cells. The increased infectivity was restricted to cells that have primate-specific NPC1 sequences at the EBOV interface, suggesting that this mutation was indeed an adaptation to the human host. GP-A82V was associated with increased mortality, consistent with the hypothesis that the heightened intrinsic infectivity of GP-A82V contributed to disease severity during the EVD epidemic.

Simultaneous profiling of multiple chromatin proteins in the same cells.

Methods derived from CUT&RUN and CUT&Tag enable genome-wide mapping of the localization of proteins on chromatin from as few as one cell. These and other mapping approaches focus on one protein at a time, preventing direct measurements of co-localization of different chromatin proteins in the same cells and requiring prioritization of targets where samples are limiting. Here, we describe multi-CUT&Tag, an adaptation of CUT&Tag that overcomes these hurdles by using antibody-specific barcodes to simultaneously map multiple proteins in the same cells. Highly specific multi-CUT&Tag maps of histone marks and RNA Polymerase II uncovered sites of co-localization in the same cells, active and repressed genes, and candidate cis-regulatory elements. Single-cell multi-CUT&Tag profiling facilitated identification of distinct cell types from a mixed population and characterization of cell-type-specific chromatin architecture. In sum, multi-CUT&Tag increases the information content per cell of epigenomic maps, facilitating direct analysis of the interplay of different chromatin proteins.

Gene expression is circular: factors for mRNA degradation also foster mRNA synthesis.

Maintaining proper mRNA levels is a key aspect in the regulation of gene expression. The balance between mRNA synthesis and decay determines these levels. We demonstrate that most yeast mRNAs are degraded by the cytoplasmic 5'-to-3' pathway (the "decaysome"), as proposed previously. Unexpectedly, the level of these mRNAs is highly robust to perturbations in this major pathway because defects in various decaysome components lead to transcription downregulation. Moreover, these components shuttle between the cytoplasm and the nucleus, in a manner dependent on proper mRNA degradation. In the nucleus, they associate with chromatin-preferentially ∼30 bp upstream of transcription start-sites-and directly stimulate transcription initiation and elongation. The nuclear role of the decaysome in transcription is linked to its cytoplasmic role in mRNA decay; linkage, in turn, seems to depend on proper shuttling of its components. The gene expression process is therefore circular, whereby the hitherto first and last stages are interconnected.

High-Resolution Mapping of Multiway Enhancer-Promoter Interactions Regulating Pathogen Detection.

Eukaryotic gene expression regulation involves thousands of distal regulatory elements. Understanding the quantitative contribution of individual enhancers to gene expression is critical for assessing the role of disease-associated genetic risk variants. Yet, we lack the ability to accurately link genes with their distal regulatory elements. To address this, we used 3D enhancer-promoter (E-P) associations identified using split-pool recognition of interactions by tag extension (SPRITE) to build a predictive model of gene expression. Our model dramatically outperforms models using genomic proximity and can be used to determine the quantitative impact of enhancer loss on gene expression in different genetic backgrounds. We show that genes that form stable E-P hubs have less cell-to-cell variability in gene expression. Finally, we identified transcription factors that regulate stimulation-dependent E-P interactions. Together, our results provide a framework for understanding quantitative contributions of E-P interactions and associated genetic variants to gene expression.

Systematic discovery of TLR signaling components delineates viral-sensing circuits.

Deciphering the signaling networks that underlie normal and disease processes remains a major challenge. Here, we report the discovery of signaling components involved in the Toll-like receptor (TLR) response of immune dendritic cells (DCs), including a previously unkown pathway shared across mammalian antiviral responses. By combining transcriptional profiling, genetic and small-molecule perturbations, and phosphoproteomics, we uncover 35 signaling regulators, including 16 known regulators, involved in TLR signaling. In particular, we find that Polo-like kinases (Plk) 2 and 4 are essential components of antiviral pathways in vitro and in vivo and activate a signaling branch involving a dozen proteins, among which is Tnfaip2, a gene associated with autoimmune diseases but whose role was unknown. Our study illustrates the power of combining systematic measurements and perturbations to elucidate complex signaling circuits and discover potential therapeutic targets.

A large intergenic noncoding RNA induced by p53 mediates global gene repression in the p53 response.

Recently, more than 1000 large intergenic noncoding RNAs (lincRNAs) have been reported. These RNAs are evolutionarily conserved in mammalian genomes and thus presumably function in diverse biological processes. Here, we report the identification of lincRNAs that are regulated by p53. One of these lincRNAs (lincRNA-p21) serves as a repressor in p53-dependent transcriptional responses. Inhibition of lincRNA-p21 affects the expression of hundreds of gene targets enriched for genes normally repressed by p53. The observed transcriptional repression by lincRNA-p21 is mediated through the physical association with hnRNP-K. This interaction is required for proper genomic localization of hnRNP-K at repressed genes and regulation of p53 mediates apoptosis. We propose a model whereby transcription factors activate lincRNAs that serve as key repressors by physically associating with repressive complexes and modulate their localization to sets of previously active genes.

Transcriptome-wide Analysis of Roles for tRNA Modifications in Translational Regulation.

Covalent nucleotide modifications in noncoding RNAs affect a plethora of biological processes, and new functions continue to be discovered even for well-known modifying enzymes. To systematically compare the functions of a large set of noncoding RNA modifications in gene regulation, we carried out ribosome profiling in budding yeast to characterize 57 nonessential genes involved in tRNA modification. Deletion mutants exhibited a range of translational phenotypes, with enzymes known to modify anticodons, or non-tRNA substrates such as rRNA, exhibiting the most dramatic translational perturbations. Our data build on prior reports documenting translational upregulation of the nutrient-responsive transcription factor Gcn4 in response to numerous tRNA perturbations, and identify many additional translationally regulated mRNAs throughout the yeast genome. Our data also uncover unexpected roles for tRNA-modifying enzymes in regulation of TY retroelements, and in rRNA 2'-O-methylation. This dataset should provide a rich resource for discovery of additional links between tRNA modifications and gene regulation.

Single cell transcriptomics reveals dysregulated cellular and molecular networks in a fragile X syndrome model.

Despite advances in understanding the pathophysiology of Fragile X syndrome (FXS), its molecular basis is still poorly understood. Whole brain tissue expression profiles have proved surprisingly uninformative, therefore we applied single cell RNA sequencing to profile an FMRP deficient mouse model with higher resolution. We found that the absence of FMRP results in highly cell type specific gene expression changes that are strongest among specific neuronal types, where FMRP-bound mRNAs were prominently downregulated. Metabolic pathways including translation and respiration are significantly upregulated across most cell types with the notable exception of excitatory neurons. These effects point to a potential difference in the activity of mTOR pathways, and together with other dysregulated pathways, suggest an excitatory-inhibitory imbalance in the Fmr1-knock out cortex that is exacerbated by astrocytes. Our data demonstrate that FMRP loss affects abundance of key cellular communication genes that potentially affect neuronal synapses and provide a resource for interrogating the biological basis of this disorder.

Intratracheally administered LNA gapmer antisense oligonucleotides induce robust gene silencing in mouse lung fibroblasts.

The lung is a complex organ with various cell types having distinct roles. Antisense oligonucleotides (ASOs) have been studied in the lung, but it has been challenging to determine their effectiveness in each cell type due to the lack of appropriate analytical methods. We employed three distinct approaches to study silencing efficacy within different cell types. First, we used lineage markers to identify cell types in flow cytometry, and simultaneously measured ASO-induced silencing of cell-surface proteins CD47 or CD98. Second, we applied single-cell RNA sequencing (scRNA-seq) to measure silencing efficacy in distinct cell types; to the best of our knowledge, this is the first time scRNA-seq has been applied to measure the efficacy of oligonucleotide therapeutics. In both approaches, fibroblasts were the most susceptible to locally delivered ASOs, with significant silencing also in endothelial cells. Third, we confirmed that the robust silencing in fibroblasts is broadly applicable by silencing two targets expressed mainly in fibroblasts, Mfap4 and Adam33. Across independent approaches, we demonstrate that intratracheally administered LNA gapmer ASOs robustly induce gene silencing in lung fibroblasts. ASO-induced gene silencing in fibroblasts was durable, lasting 4-8 weeks after a single dose. Thus, lung fibroblasts are well aligned with ASOs as therapeutics.

Hierarchy of signaling thresholds downstream of the T cell receptor and the Tec kinase ITK.

The strength of peptide:MHC interactions with the T cell receptor (TCR) is correlated with the time to first cell division, the relative scale of the effector cell response, and the graded expression of activation-associated proteins like IRF4. To regulate T cell activation programming, the TCR and the TCR proximal interleukin-2-inducible T cell kinase (ITK) simultaneously trigger many biochemically separate signaling cascades. T cells lacking ITK exhibit selective impairments in effector T cell responses after activation, but under the strongest signaling conditions, ITK activity is dispensable. To gain insight into whether TCR signal strength and ITK activity tune observed graded gene expression through the unequal activation of distinct signaling pathways, we examined Erk1/2 phosphorylation or nuclear factor of activated T cells (NFAT) and nuclear factor (NF)-κB translocation in naïve OT-I CD8+ cell nuclei. We observed the consistent digital activation of NFAT1 and Erk1/2, but NF-κB displayed dynamic, graded activation in response to variation in TCR signal strength, tunable by treatment with an ITK inhibitor. Inhibitor-treated cells showed the dampened induction of AP-1 factors Fos and Fosb, NF-κB response gene transcripts, and survival factor Il2 transcripts. ATAC sequencing analysis also revealed that genomic regions most sensitive to ITK inhibition were enriched for NF-κB and AP-1 motifs. Specific inhibition of NF-κB during peptide stimulation tuned the expression of early gene products like c-Fos. Together, these data indicate a key role for ITK in orchestrating the optimal activation of separate TCR downstream pathways, specifically aiding NF-κB activation. More broadly, we revealed a mechanism by which variations in TCR signal strength can produce patterns of graded gene expression in activated T cells.

A negative feedback loop of transcription factors specifies alternative dendritic cell chromatin States.

During hematopoiesis, cells originating from the same stem cell reservoir differentiate into distinct cell types. The mechanisms enabling common progenitors to differentiate into alternative cell fates are not fully understood. Here, we identify cell-fate-determining transcription factors (TFs) governing dendritic cell (DC) development by annotating the enhancer landscapes of the DC lineage. Combining these analyses with detailed overexpression, knockdown, and ChIP-Seq studies, we show that Irf8 functions as a plasmacytoid DC epigenetic and fate-determining TF, regulating massive, cell-specific chromatin changes in thousands of pDC enhancers. Importantly, Irf8 forms a negative feedback loop with Cebpb, a monocyte-derived DC epigenetic fate-determining TF. We show that using this circuit logic, a pulse of TF expression can stably define epigenetic and transcriptional states, regardless of the microenvironment. More broadly, our study proposes a general paradigm that allows closely related cells with a similar set of signal-dependent factors to generate differential and persistent enhancer landscapes.

Diverse repertoire of human adipocyte subtypes develops from transcriptionally distinct mesenchymal progenitor cells.

Single-cell sequencing technologies have revealed an unexpectedly broad repertoire of cells required to mediate complex functions in multicellular organisms. Despite the multiple roles of adipose tissue in maintaining systemic metabolic homeostasis, adipocytes are thought to be largely homogenous with only 2 major subtypes recognized in humans so far. Here we report the existence and characteristics of 4 distinct human adipocyte subtypes, and of their respective mesenchymal progenitors. The phenotypes of these distinct adipocyte subtypes are differentially associated with key adipose tissue functions, including thermogenesis, lipid storage, and adipokine secretion. The transcriptomic signature of "brite/beige" thermogenic adipocytes reveals mechanisms for iron accumulation and protection from oxidative stress, necessary for mitochondrial biogenesis and respiration upon activation. Importantly, this signature is enriched in human supraclavicular adipose tissue, confirming that these cells comprise thermogenic depots in vivo, and explain previous findings of a rate-limiting role of iron in adipose tissue browning. The mesenchymal progenitors that give rise to beige/brite adipocytes express a unique set of cytokines and transcriptional regulators involved in immune cell modulation of adipose tissue browning. Unexpectedly, we also find adipocyte subtypes specialized for high-level expression of the adipokines adiponectin or leptin, associated with distinct transcription factors previously implicated in adipocyte differentiation. The finding of a broad adipocyte repertoire derived from a distinct set of mesenchymal progenitors, and of the transcriptional regulators that can control their development, provides a framework for understanding human adipose tissue function and role in metabolic disease.

Recovery of viable endocrine-specific cells and transcriptomes from human pancreatic islet-engrafted mice.

Human pancreatic islets engrafted into immunodeficient mice serve as an important model for in vivo human diabetes studies. Following engraftment, islet function can be monitored in vivo by measuring circulating glucose and human insulin; however, it will be important to recover viable cells for more complex graft analyses. Moreover, RNA analyses of dissected grafts have not distinguished which hormone-specific cell types contribute to gene expression. We developed a method for recovering live cells suitable for fluorescence-activated cell sorting from human islets engrafted in mice. Although yields of recovered islet cells were relatively low, the ratios of bulk-sorted ß, α, and δ cells and their respective hormone-specific RNA-Seq transcriptomes are comparable pretransplant and posttransplant, suggesting that the cellular characteristics of islet grafts posttransplant closely mirror the original donor islets. Single-cell RNA-Seq transcriptome analysis confirms the presence of appropriate ß, α, and δ cell subsets. In addition, ex vivo perifusion of recovered human islet grafts demonstrated glucose-stimulated insulin secretion. Viable cells suitable for patch-clamp analysis were recovered from transplanted human embryonic stem cell-derived ß cells. Together, our functional and hormone-specific transcriptome analyses document the broad applicability of this system for longitudinal examination of human islet cells undergoing developmental/metabolic/pharmacogenetic manipulation in vivo and may facilitate the discovery of treatments for diabetes.

Frequent Loss of IRF2 in Cancers Leads to Immune Evasion through Decreased MHC Class I Antigen Presentation and Increased PD-L1 Expression.

To arise and progress, cancers need to evade immune elimination. Consequently, progressing tumors are often MHC class I (MHC-I) low and express immune inhibitory molecules, such as PD-L1, which allows them to avoid the main antitumor host defense, CD8+ T cells. The molecular mechanisms that led to these alterations were incompletely understood. In this study, we identify loss of the transcription factor IRF2 as a frequent underlying mechanism that leads to a tumor immune evasion phenotype in both humans and mice. We identified IRF2 in a CRISPR-based forward genetic screen for genes that controlled MHC-I Ag presentation in HeLa cells. We then found that many primary human cancers, including lung, colon, breast, prostate, and others, frequently downregulated IRF2. Although IRF2 is generally known as a transcriptional repressor, we found that it was a transcriptional activator of many key components of the MHC-I pathway, including immunoproteasomes, TAP, and ERAP1, whose transcriptional control was previously poorly understood. Upon loss of IRF2, cytosol-to-endoplasmic reticulum peptide transport and N-terminal peptide trimming become rate limiting for Ag presentation. In addition, we found that IRF2 is a repressor of PD-L1. Thus, by downregulating a single nonessential gene, tumors become harder to see (reduced Ag presentation), more inhibitory (increased checkpoint inhibitor), and less susceptible to being killed by CD8+ T cells. Importantly, we found that the loss of Ag presentation caused by IRF2 downregulation could be reversed by IFN-stimulated induction of the transcription factor IRF1. The implication of these findings for tumor progression and immunotherapy are discussed.

DolphinNext: a distributed data processing platform for high throughput genomics.

BACKGROUND: The emergence of high throughput technologies that produce vast amounts of genomic data, such as next-generation sequencing (NGS) is transforming biological research. The dramatic increase in the volume of data, the variety and continuous change of data processing tools, algorithms and databases make analysis the main bottleneck for scientific discovery. The processing of high throughput datasets typically involves many different computational programs, each of which performs a specific step in a pipeline. Given the wide range of applications and organizational infrastructures, there is a great need for highly parallel, flexible, portable, and reproducible data processing frameworks. Several platforms currently exist for the design and execution of complex pipelines. Unfortunately, current platforms lack the necessary combination of parallelism, portability, flexibility and/or reproducibility that are required by the current research environment. To address these shortcomings, workflow frameworks that provide a platform to develop and share portable pipelines have recently arisen. We complement these new platforms by providing a graphical user interface to create, maintain, and execute complex pipelines. Such a platform will simplify robust and reproducible workflow creation for non-technical users as well as provide a robust platform to maintain pipelines for large organizations. RESULTS: To simplify development, maintenance, and execution of complex pipelines we created DolphinNext. DolphinNext facilitates building and deployment of complex pipelines using a modular approach implemented in a graphical interface that relies on the powerful Nextflow workflow framework by providing 1. A drag and drop user interface that visualizes pipelines and allows users to create pipelines without familiarity in underlying programming languages. 2. Modules to execute and monitor pipelines in distributed computing environments such as high-performance clusters and/or cloud 3. Reproducible pipelines with version tracking and stand-alone versions that can be run independently. 4. Modular process design with process revisioning support to increase reusability and pipeline development efficiency. 5. Pipeline sharing with GitHub and automated testing 6. Extensive reports with R-markdown and shiny support for interactive data visualization and analysis. CONCLUSION: DolphinNext is a flexible, intuitive, web-based data processing and analysis platform that enables creating, deploying, sharing, and executing complex Nextflow pipelines with extensive revisioning and interactive reporting to enhance reproducible results.

A high-throughput chromatin immunoprecipitation approach reveals principles of dynamic gene regulation in mammals.

Understanding the principles governing mammalian gene regulation has been hampered by the difficulty in measuring in vivo binding dynamics of large numbers of transcription factors (TF) to DNA. Here, we develop a high-throughput Chromatin ImmunoPrecipitation (HT-ChIP) method to systematically map protein-DNA interactions. HT-ChIP was applied to define the dynamics of DNA binding by 25 TFs and 4 chromatin marks at 4 time-points following pathogen stimulus of dendritic cells. Analyzing over 180,000 TF-DNA interactions we find that TFs vary substantially in their temporal binding landscapes. This data suggests a model for transcription regulation whereby TF networks are hierarchically organized into cell differentiation factors, factors that bind targets prior to stimulus to prime them for induction, and factors that regulate specific gene programs. Overlaying HT-ChIP data on gene-expression dynamics shows that many TF-DNA interactions are established prior to the stimuli, predominantly at immediate-early genes, and identified specific TF ensembles that coordinately regulate gene-induction.

DEBrowser: interactive differential expression analysis and visualization tool for count data.

BACKGROUND: Sequencing data has become a standard measure of diverse cellular activities. For example, gene expression is accurately measured by RNA sequencing (RNA-Seq) libraries, protein-DNA interactions are captured by chromatin immunoprecipitation sequencing (ChIP-Seq), protein-RNA interactions by crosslinking immunoprecipitation sequencing (CLIP-Seq) or RNA immunoprecipitation (RIP-Seq) sequencing, DNA accessibility by assay for transposase-accessible chromatin (ATAC-Seq), DNase or MNase sequencing libraries. The processing of these sequencing techniques involves library-specific approaches. However, in all cases, once the sequencing libraries are processed, the result is a count table specifying the estimated number of reads originating from each genomic locus. Differential analysis to determine which loci have different cellular activity under different conditions starts with the count table and iterates through a cycle of data assessment, preparation and analysis. Such complex analysis often relies on multiple programs and is therefore a challenge for those without programming skills. RESULTS: We developed DEBrowser as an R bioconductor project to interactively visualize every step of the differential analysis, without programming. The application provides a rich and interactive web based graphical user interface built on R's shiny infrastructure. DEBrowser allows users to visualize data with various types of graphs that can be explored further by selecting and re-plotting any desired subset of data. Using the visualization approaches provided, users can determine and correct technical variations such as batch effects and sequencing depth that affect differential analysis. We show DEBrowser's ease of use by reproducing the analysis of two previously published data sets. CONCLUSIONS: DEBrowser is a flexible, intuitive, web-based analysis platform that enables an iterative and interactive analysis of count data without any requirement of programming knowledge.

End Sequence Analysis Toolkit (ESAT) expands the extractable information from single-cell RNA-seq data.

RNA-seq protocols that focus on transcript termini are well suited for applications in which template quantity is limiting. Here we show that, when applied to end-sequencing data, analytical methods designed for global RNA-seq produce computational artifacts. To remedy this, we created the End Sequence Analysis Toolkit (ESAT). As a test, we first compared end-sequencing and bulk RNA-seq using RNA from dendritic cells stimulated with lipopolysaccharide (LPS). As predicted by the telescripting model for transcriptional bursts, ESAT detected an LPS-stimulated shift to shorter 3'-isoforms that was not evident by conventional computational methods. Then, droplet-based microfluidics was used to generate 1000 cDNA libraries, each from an individual pancreatic islet cell. ESAT identified nine distinct cell types, three distinct ß-cell types, and a complex interplay between hormone secretion and vascularization. ESAT, then, offers a much-needed and generally applicable computational pipeline for either bulk or single-cell RNA end-sequencing.