A TLR4/TRAF6-dependent signaling pathway mediates NCoR coactivator complex formation for inflammatory gene activation.

The nuclear receptor corepressor (NCoR) forms a complex with histone deacetylase 3 (HDAC3) that mediates repressive functions of unliganded nuclear receptors and other transcriptional repressors by deacetylation of histone substrates. Recent studies provide evidence that NCoR/HDAC3 complexes can also exert coactivator functions in brown adipocytes by deacetylating and activating PPARγ coactivator 1α (PGC1α) and that signaling via receptor activator of nuclear factor kappa-B (RANK) promotes the formation of a stable NCoR/HDAC3/PGC1ß complex that coactivates nuclear factor kappa-B (NFκB)- and activator protein 1 (AP-1)-dependent genes required for osteoclast differentiation. Here, we demonstrate that activation of Toll-like receptor (TLR) 4, but not TLR3, the interleukin 4 (IL4) receptor nor the Type I interferon receptor, also promotes assembly of an NCoR/HDAC3/PGC1ß coactivator complex. Receptor-specific utilization of TNF receptor-associated factor 6 (TRAF6) and downstream activation of extracellular signal-regulated kinase 1 (ERK1) and TANK-binding kinase 1 (TBK1) accounts for the common ability of RANK and TLR4 to drive assembly of an NCoR/HDAC3/PGC1ß complex in macrophages. ERK1, the p65 component of NFκB, and the p300 histone acetyltransferase (HAT) are also components of the induced complex and are associated with local histone acetylation and transcriptional activation of TLR4-dependent enhancers and promoters. These observations identify a TLR4/TRAF6-dependent signaling pathway that converts NCoR from a corepressor of nuclear receptors to a coactivator of NFκB and AP-1 that may be relevant to functions of NCoR in other developmental and homeostatic processes.

RANK ligand converts the NCoR/HDAC3 co-repressor to a PGC1ß- and RNA-dependent co-activator of osteoclast gene expression.

The nuclear receptor co-repressor (NCoR) complex mediates transcriptional repression dependent on histone deacetylation by histone deacetylase 3 (HDAC3) as a component of the complex. Unexpectedly, we found that signaling by the receptor activator of nuclear factor κB (RANK) converts the NCoR/HDAC3 co-repressor complex to a co-activator of AP-1 and NF-κB target genes that are required for mouse osteoclast differentiation. Accordingly, the dominant function of NCoR/HDAC3 complexes in response to RANK signaling is to activate, rather than repress, gene expression. Mechanistically, RANK signaling promotes RNA-dependent interaction of the transcriptional co-activator PGC1ß with the NCoR/HDAC3 complex, resulting in the activation of PGC1ß and inhibition of HDAC3 activity for acetylated histone H3. Non-coding RNAs Dancr and Rnu12, which are associated with altered human bone homeostasis, promote NCoR/HDAC3 complex assembly and are necessary for RANKL-induced osteoclast differentiation in vitro. These findings may be prototypic for signal-dependent functions of NCoR in other biological contexts.

scRNASequest: an ecosystem of scRNA-seq analysis, visualization, and publishing.

BACKGROUND: Single-cell RNA sequencing is a state-of-the-art technology to understand gene expression in complex tissues. With the growing amount of data being generated, the standardization and automation of data analysis are critical to generating hypotheses and discovering biological insights. RESULTS: Here, we present scRNASequest, a semi-automated single-cell RNA-seq (scRNA-seq) data analysis workflow which allows (1) preprocessing from raw UMI count data, (2) harmonization by one or multiple methods, (3) reference-dataset-based cell type label transfer and embedding projection, (4) multi-sample, multi-condition single-cell level differential gene expression analysis, and (5) seamless integration with cellxgene VIP for visualization and with CellDepot for data hosting and sharing by generating compatible h5ad files. CONCLUSIONS: We developed scRNASequest, an end-to-end pipeline for single-cell RNA-seq data analysis, visualization, and publishing. The source code under MIT open-source license is provided at https://github.com/interactivereport/scRNASequest . We also prepared a bookdown tutorial for the installation and detailed usage of the pipeline: https://interactivereport.github.io/scRNAsequest/tutorial/docs/ . Users have the option to run it on a local computer with a Linux/Unix system including MacOS, or interact with SGE/Slurm schedulers on high-performance computing (HPC) clusters.

RNASequest: An End-to-End Reproducible RNAseq Data Analysis and Publishing Framework.

We present RNASequest, a customizable RNA sequencing (RNAseq) analysis, app management, and result publishing framework. Its three-in-one RNAseq data analysis ecosystem consists of (1) a reproducible, configurable expression analysis (EA) module, (2) multi-faceted result presentation in R Shiny, a Bookdown document and an online slide deck, and (3) a centralized data management system. In principle, following up our well-received omics data visualization tool Quickomics, RNASequest automates the differential gene expression analysis step, eases statistical model design by built-in covariates testing module, and further provides a web-based tool, ShinyOne, to manage apps powered by Quickomics and reports generated by running the pipeline on multiple projects in one place. Researchers can experience the functionalities by exploring demo data sets hosted at http://shinyone.bxgenomics.com or following the tutorial, https://interactivereport.github.io/RNASequest/tutorial/docs/introduction.html to set up the framework locally to process private RNAseq datasets. The source code released under MIT open-source license is provided at https://github.com/interactivereport/RNASequest.

Brain expression quantitative trait locus and network analyses reveal downstream effects and putative drivers for brain-related diseases.

Identification of therapeutic targets from genome-wide association studies (GWAS) requires insights into downstream functional consequences. We harmonized 8,613 RNA-sequencing samples from 14 brain datasets to create the MetaBrain resource and performed cis- and trans-expression quantitative trait locus (eQTL) meta-analyses in multiple brain region- and ancestry-specific datasets (n ≤ 2,759). Many of the 16,169 cortex cis-eQTLs were tissue-dependent when compared with blood cis-eQTLs. We inferred brain cell types for 3,549 cis-eQTLs by interaction analysis. We prioritized 186 cis-eQTLs for 31 brain-related traits using Mendelian randomization and co-localization including 40 cis-eQTLs with an inferred cell type, such as a neuron-specific cis-eQTL (CYP24A1) for multiple sclerosis. We further describe 737 trans-eQTLs for 526 unique variants and 108 unique genes. We used brain-specific gene-co-regulation networks to link GWAS loci and prioritize additional genes for five central nervous system diseases. This study represents a valuable resource for post-GWAS research on central nervous system diseases.

Cooperation between cGAS and RIG-I sensing pathways enables improved innate recognition of HIV-1 by myeloid dendritic cells in elite controllers.

Introduction: Spontaneous control of HIV-1 replication in the absence of anti-retroviral therapy (ART) naturally occurs in a small proportion of HIV-1-infected individuals known as elite controllers (EC), likely as a result of improved innate and adaptive immune mechanisms. Previous studies suggest that enhanced cytosolic immune recognition of HIV-1 reverse transcripts in conventional dendritic cells (mDC) from EC enables effective induction of antiviral effector T cell responses. However, the specific molecular circuits responsible for such improved innate recognition of HIV-1 in mDC from these individuals remain unknown. Results and methods: Here, we identified a subpopulation of EC whose mDC displayed higher baseline abilities to respond to intracellular HIV-1 dsDNA stimulation. A computational analysis of transcriptional signatures from such high responder EC, combined with functional studies, suggested cytosolic recognition of HIV-1 dsDNA by cGAS, combined with sensing of viral mRNA by RIG-I after polymerase III-mediated HIV-1 DNA transcription. Discussion: Together, our work identifies collaborative networks of innate sensing pathways that enhance cell-intrinsic abilities of mDC to induce antiviral innate responses against HIV-1; these observations might be useful for the therapeutic induction of effective antiviral immune responses.

Integrated single-cell transcriptomics of cerebrospinal fluid cells in treatment-naïve multiple sclerosis.

Multiple sclerosis (MS) is a chronic and often disabling autoimmune disease of the central nervous system (CNS). Cerebrospinal fluid (CSF) surrounds and protects the CNS. Analysis of CSF can aid the diagnosis of CNS diseases, help to identify the prognosis, and underlying mechanisms of diseases. Several recent studies have leveraged single-cell RNA-sequencing (scRNA-seq) to identify MS-associated changes in CSF cells that are considerably more altered than blood cells in MS. However, not all alterations were replicated across all studies. We therefore integrated multiple available scRNA-seq datasets of CSF cells from MS patients with early relapsing-remitting (RRMS) disease. We provide a searchable and interactive resource of this integrated analysis ( https://CSFinMS.bxgenomics.com ) facilitating diverse visualization and analysis methods without requiring computational skills. In the present joint analysis, we replicated the known expansion of B lineage and the recently described expansion of natural killer (NK) cells and some cytotoxic T cells and decrease of monocytes in the CSF in MS. The previous observation of the abundance of Th1-like Th17 effector memory cells in the CSF was not replicated. Expanded CSF B lineage cells resembled class-switched plasmablasts/-cells (e.g., SDC1/CD138, MZB1) as expected. Our integrative analysis thus validates increased cell type diversity and B cell maturation in the CSF in MS and improves accessibility of available data.

Characterizing the composition of iPSC derived cells from bulk transcriptomics data with CellMap.

Induced pluripotent stem cell (iPSC) derived cell types are increasingly employed as in vitro model systems for drug discovery. For these studies to be meaningful, it is important to understand the reproducibility of the iPSC-derived cultures and their similarity to equivalent endogenous cell types. Single-cell and single-nucleus RNA sequencing (RNA-seq) are useful to gain such understanding, but they are expensive and time consuming, while bulk RNA-seq data can be generated quicker and at lower cost. In silico cell type decomposition is an efficient, inexpensive, and convenient alternative that can leverage bulk RNA-seq to derive more fine-grained information about these cultures. We developed CellMap, a computational tool that derives cell type profiles from publicly available single-cell and single-nucleus datasets to infer cell types in bulk RNA-seq data from iPSC-derived cell lines.

Recommendations of scRNA-seq Differential Gene Expression Analysis Based on Comprehensive Benchmarking.

To guide analysts to select the right tool and parameters in differential gene expression analyses of single-cell RNA sequencing (scRNA-seq) data, we developed a novel simulator that recapitulates the data characteristics of real scRNA-seq datasets while accounting for all the relevant sources of variation in a multi-subject, multi-condition scRNA-seq experiment: the cell-to-cell variation within a subject, the variation across subjects, the variability across cell types, the mean/variance relationship of gene expression across genes, library size effects, group effects, and covariate effects. By applying it to benchmark 12 differential gene expression analysis methods (including cell-level and pseudo-bulk methods) on simulated multi-condition, multi-subject data of the 10x Genomics platform, we demonstrated that methods originating from the negative binomial mixed model such as glmmTMB and NEBULA-HL outperformed other methods. Utilizing NEBULA-HL in a statistical analysis pipeline for single-cell analysis will enable scientists to better understand the cell-type-specific transcriptomic response to disease or treatment effects and to discover new drug targets. Further, application to two real datasets showed the outperformance of our differential expression (DE) pipeline, with unified findings of differentially expressed genes (DEG) and a pseudo-time trajectory transcriptomic result. In the end, we made recommendations for filtering strategies of cells and genes based on simulation results to achieve optimal experimental goals.

Systemic Influences of Mammary Cancer on Monocytes in Mice.

There is a growing body of evidence that cancer causes systemic changes. These influences are most evident in the bone marrow and the blood, particularly in the myeloid compartment. Here, we show that there is an increase in the number of bone marrow, circulating and splenic monocytes by using mouse models of breast cancer caused by the mammary epithelial expression of the polyoma middle T antigen. Cancer does not affect ratios of classical to non-classical populations of monocytes in the circulation nor does it affect their half-lives. Single cell RNA sequencing also indicates that cancer does not induce any new monocyte populations. Cancer does not change the monocytic progenitor number in the bone marrow, but the proliferation rate of monocytes is higher, thus providing an explanation for the expansion of the circulating numbers. Deep RNA sequencing of these monocytic populations reveals that cancer causes changes in the classical monocyte compartment, with changes evident in bone marrow monocytes and even more so in the blood, suggesting influences in both compartments, with the down-regulation of interferon type 1 signaling and antigen presentation being the most prominent of these. Consistent with this analysis, down-regulated genes are enriched with STAT1/STAT2 binding sites in their promoter, which are transcription factors required for type 1 interferon signaling. However, these transcriptome changes in mice did not replicate those found in patients with breast cancer. Consequently, this mouse model of breast cancer may be insufficient to study the systemic influences of human cancer.

CellDepot: A Unified Repository for scRNA-seq Data and Visual Exploration.

CellDepot containing over 270 datasets from 8 species and many tissues serves as an integrated web application to empower scientists in exploring single-cell RNA-seq (scRNA-seq) datasets and comparing the datasets among various studies through a user-friendly interface with advanced visualization and analytical capabilities. To begin with, it provides an efficient data management system that users can upload single cell datasets and query the database by multiple attributes such as species and cell types. In addition, the graphical multi-logic, multi-condition query builder and convenient filtering tool backed by MySQL database system, allows users to quickly find the datasets of interest and compare the expression of gene(s) across these. Moreover, by embedding the cellxgene VIP tool, CellDepot enables fast exploration of individual dataset in the manner of interactivity and scalability to gain more refined insights such as cell composition, gene expression profiles, and differentially expressed genes among cell types by leveraging more than 20 frequently applied plotting functions and high-level analysis methods in single cell research. In summary, the web portal available at http://celldepot.bxgenomics.com, prompts large scale single cell data sharing, facilitates meta-analysis and visualization, and encourages scientists to contribute to the single-cell community in a tractable and collaborative way. Finally, CellDepot is released as open-source software under MIT license to motivate crowd contribution, broad adoption, and local deployment for private datasets.

MAGGIE: leveraging genetic variation to identify DNA sequence motifs mediating transcription factor binding and function.

MOTIVATION: Genetic variation in regulatory elements can alter transcription factor (TF) binding by mutating a TF binding motif, which in turn may affect the activity of the regulatory elements. However, it is unclear which motifs are prone to impact transcriptional regulation if mutated. Current motif analysis tools either prioritize TFs based on motif enrichment without linking to a function or are limited in their applications due to the assumption of linearity between motifs and their functional effects. RESULTS: We present MAGGIE (Motif Alteration Genome-wide to Globally Investigate Elements), a novel method for identifying motifs mediating TF binding and function. By leveraging measurements from diverse genotypes, MAGGIE uses a statistical approach to link mutations of a motif to changes of an epigenomic feature without assuming a linear relationship. We benchmark MAGGIE across various applications using both simulated and biological datasets and demonstrate its improvement in sensitivity and specificity compared with the state-of-the-art motif analysis approaches. We use MAGGIE to gain novel insights into the divergent functions of distinct NF-κB factors in pro-inflammatory macrophages, revealing the association of p65-p50 co-binding with transcriptional activation and the association of p50 binding lacking p65 with transcriptional repression. AVAILABILITY AND IMPLEMENTATION: The Python package for MAGGIE is freely available at https://github.com/zeyang-shen/maggie. The accession number for the NF-κB ChIP-seq data generated for this study is Gene Expression Omnibus: GSE144070. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Immune-profiling of ZIKV-infected patients identifies a distinct function of plasmacytoid dendritic cells for immune cross-regulation.

Zika virus (ZIKV) is a mosquito-borne pathogen with increasing public health significance. To characterize immune responses to ZIKV, here we examine transcriptional signatures of CD4 T, CD8 T, B, and NK cells, monocytes, myeloid dendritic cells (mDCs), and plasmacytoid dendritic cells (pDCs) from three individuals with ZIKV infection. While gene expression patterns from most cell subsets display signs of impaired antiviral immune activity, pDCs from infected host have distinct transcriptional response associated with activation of innate immune recognition and type I interferon signaling pathways, but downregulation of key host factors known to support ZIKV replication steps; meanwhile, pDCs exhibit a unique expression pattern of gene modules that are correlated with alternative cell populations, suggesting collaborative interactions between pDCs and other immune cells, particularly B cells. Together, these results point towards a discrete but integrative function of pDCs in the human immune responses to ZIKV infection.

Niche-Specific Reprogramming of Epigenetic Landscapes Drives Myeloid Cell Diversity in Nonalcoholic Steatohepatitis.

Tissue-resident and recruited macrophages contribute to both host defense and pathology. Multiple macrophage phenotypes are represented in diseased tissues, but we lack deep understanding of mechanisms controlling diversification. Here, we investigate origins and epigenetic trajectories of hepatic macrophages during diet-induced non-alcoholic steatohepatitis (NASH). The NASH diet induced significant changes in Kupffer cell enhancers and gene expression, resulting in partial loss of Kupffer cell identity, induction of Trem2 and Cd9 expression, and cell death. Kupffer cell loss was compensated by gain of adjacent monocyte-derived macrophages that exhibited convergent epigenomes, transcriptomes, and functions. NASH-induced changes in Kupffer cell enhancers were driven by AP-1 and EGR that reprogrammed LXR functions required for Kupffer cell identity and survival to instead drive a scar-associated macrophage phenotype. These findings reveal mechanisms by which disease-associated environmental signals instruct resident and recruited macrophages to acquire distinct gene expression programs and corresponding functions.

Chronic Peripheral Inflammation Causes a Region-Specific Myeloid Response in the Central Nervous System.

Systemic immune dysregulation contributes to the development of neuropsychiatric and neurodegenerative diseases. The precise effect of chronic peripheral immune stimulation on myeloid cells across anatomical brain regions is unclear. Here, we demonstrate brain-region-specific differences in myeloid responses induced by chronic peripheral inflammation. This shift in the myeloid compartment is associated with the appearance of an inflammatory myeloid subpopulation in the cortex, striatum, and thalamus accompanied by regional transcriptomic fingerprints that include induction of chemokines, complement factors, and endothelial adhesion molecules. In contrast, myeloid immune responses within the hippocampus and cerebellum are subtle or absent. Treatment with the anti-tumor necrosis factor α (anti-TNF-α) antibody infliximab ablates the region-specific inflammatory response. A region-specific myeloid cell response to chronic peripheral inflammation is observed in postmortem brains from individuals with rheumatoid arthritis. Our data suggest that chronic peripheral inflammation has heterogeneous effects on the brain, as evidenced by the spectrum of myeloid cell responses observed across brain regions.

Transcriptomic and epigenetic mechanisms underlying myeloid diversity in the lung.

The lung is inhabited by resident alveolar and interstitial macrophages as well as monocytic cells that survey lung tissues. Each cell type plays distinct functional roles under homeostatic and inflammatory conditions, but mechanisms establishing their molecular identities and functional potential remain poorly understood. In the present study, systematic evaluation of transcriptomes and open chromatin of alveolar macrophages (AMs), interstitial macrophages (IMs) and lung monocytes from two mouse strains enabled inference of common and cell-specific transcriptional regulators. We provide evidence that these factors drive selection of regulatory landscapes that specify distinct phenotypes of AMs and IMs and entrain qualitatively different responses to toll-like receptor 4 signaling in vivo. These studies reveal a striking divergence in a fundamental innate immune response pathway in AMs and establish a framework for further understanding macrophage diversity in the lung.

Immunological Fingerprints of Controllers Developing Neutralizing HIV-1 Antibodies.

The induction of broadly neutralizing antibodies (bnAbs) is highly desired for an effective vaccine against HIV-1. Typically, bnAbs develop in patients with high viremia, but they can also evolve in some untreated HIV-1 controllers with low viral loads. Here, we identify a subgroup of neutralizer-controllers characterized by myeloid DCs (mDCs) with a distinct inflammatory signature and a superior ability to prime T follicular helper (Tfh)-like cells in an STAT4-dependent fashion. This distinct immune profile is associated with a higher frequency of Tfh-like cells in peripheral blood (pTfh) and an enrichment for Tfh-defining genes in circulating CD4+ T cells. Correspondingly, monocytes from this neutralizer controller subgroup upregulate genes encoding for chemotaxis and inflammation, and they secrete high levels of IL-12 in response to TLR stimulation. Our results suggest the existence of multi-compartment immune networks between mDCs, Tfh, and monocytes that may facilitate the development of bnAbs in a subgroup of HIV-1 controllers.

Cx3cr1-deficient microglia exhibit a premature aging transcriptome.

CX3CR1, one of the highest expressed genes in microglia in mice and humans, is implicated in numerous microglial functions. However, the molecular mechanisms underlying Cx3cr1 signaling are not well understood. Here, we analyzed transcriptomes of Cx3cr1-deficient microglia under varying conditions by RNA-sequencing (RNA-seq). In 2-mo-old mice, Cx3cr1 deletion resulted in the down-regulation of a subset of immune-related genes, without substantial epigenetic changes in markers of active chromatin. Surprisingly, Cx3cr1-deficient microglia from young mice exhibited a transcriptome consistent with that of aged Cx3cr1-sufficient animals, suggesting a premature aging transcriptomic signature. Immunohistochemical analysis of microglia in young and aged mice revealed that loss of Cx3cr1 modulates microglial morphology in a comparable fashion. Our results suggest that CX3CR1 may regulate microglial function in part by modulating the expression levels of a subset of inflammatory genes during chronological aging, making Cx3cr1-deficient mice useful for studying aged microglia.

Liver-Derived Signals Sequentially Reprogram Myeloid Enhancers to Initiate and Maintain Kupffer Cell Identity.

Tissue environment plays a powerful role in establishing and maintaining the distinct phenotypes of resident macrophages, but the underlying molecular mechanisms remain poorly understood. Here, we characterized transcriptomic and epigenetic changes in repopulating liver macrophages following acute Kupffer cell depletion as a means to infer signaling pathways and transcription factors that promote Kupffer cell differentiation. We obtained evidence that combinatorial interactions of the Notch ligand DLL4 and transforming growth factor-b (TGF-ß) family ligands produced by sinusoidal endothelial cells and endogenous LXR ligands were required for the induction and maintenance of Kupffer cell identity. DLL4 regulation of the Notch transcriptional effector RBPJ activated poised enhancers to rapidly induce LXRα and other Kupffer cell lineage-determining factors. These factors in turn reprogrammed the repopulating liver macrophage enhancer landscape to converge on that of the original resident Kupffer cells. Collectively, these findings provide a framework for understanding how macrophage progenitor cells acquire tissue-specific phenotypes.