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.

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.

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.

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.

Anti-apoptotic Protein BIRC5 Maintains Survival of HIV-1-Infected CD4+ T Cells.

HIV-1 infection of CD4+ T cells leads to cytopathic effects and cell demise, which is counter to the observation that certain HIV-1-infected cells possess a remarkable long-term stability and can persist lifelong in infected individuals treated with suppressive antiretroviral therapy (ART). Using quantitative mass spectrometry-based proteomics, we showed that HIV-1 infection activated cellular survival programs that were governed by BIRC5, a molecular inhibitor of cell apoptosis that is frequently overexpressed in malignant cells. BIRC5 and its upstream regulator OX40 were upregulated in productively and latently infected CD4+ T cells and were functionally involved in maintaining their viability. Moreover, OX40-expressing CD4+ T cells from ART-treated patients were enriched for clonally expanded HIV-1 sequences, and pharmacological inhibition of BIRC5 resulted in a selective decrease of HIV-1-infected cells in vitro. Together, these findings suggest that BIRC5 supports long-term survival of HIV-1-infected cells and may lead to clinical strategies to reduce persisting viral reservoirs.

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.

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.

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.

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.

Potent Cell-Intrinsic Immune Responses in Dendritic Cells Facilitate HIV-1-Specific T Cell Immunity in HIV-1 Elite Controllers.

The majority of HIV-1 elite controllers (EC) restrict HIV-1 replication through highly functional HIV-1-specific T cell responses, but mechanisms supporting the evolution of effective HIV-1-specific T cell immunity in these patients remain undefined. Cytosolic immune recognition of HIV-1 in conventional dendritic cells (cDC) can facilitate priming and expansion of HIV-1-specific T cells; however, HIV-1 seems to be able to avoid intracellular immune recognition in cDCs in most infected individuals. Here, we show that exposure of cDCs from EC to HIV-1 leads to a rapid and sustained production of type I interferons and upregulation of several interferon-stimulated effector genes. Emergence of these cell-intrinsic immune responses was associated with a reduced induction of SAMHD1 and LEDGF/p75, and an accumulation of viral reverse transcripts, but inhibited by pharmacological blockade of viral reverse transcription or siRNA-mediated silencing of the cytosolic DNA sensor cGAS. Importantly, improved cell-intrinsic immune recognition of HIV-1 in cDCs from elite controllers translated into stronger abilities to stimulate and expand HIV-1-specific CD8 T cell responses. These data suggest an important role of cell-intrinsic type I interferon secretion in dendritic cells for the induction of effective HIV-1-specific CD8 T cells, and may be helpful for eliciting functional T cell immunity against HIV-1 for preventative or therapeutic clinical purposes.

CbGRiTS: cerebellar gene regulation in time and space.

The mammalian CNS is one of the most complex biological systems to understand at the molecular level. The temporal information from time series transcriptome analysis can serve as a potent source of associative information between developmental processes and regulatory genes. Here, we introduce a new transcriptome database called, Cerebellar Gene Regulation in Time and Space (CbGRiTS). This dataset is populated with transcriptome data across embryonic and postnatal development from two standard mouse strains, C57BL/6J and DBA/2J, several recombinant inbred lines and cerebellar mutant strains. Users can evaluate expression profiles across cerebellar development in a deep time series with graphical interfaces for data exploration and link-out to anatomical expression databases. We present three analytical approaches that take advantage of specific aspects of the time series for transcriptome analysis. We demonstrate the use of CbGRiTS dataset as a community resource to explore patterns of gene expression and develop hypotheses concerning gene regulatory networks in brain development.

Prolonged Antiretroviral Therapy Preserves HIV-1-Specific CD8 T Cells with Stem Cell-Like Properties.

UNLABELLED: HIV-1-specific CD8 T cells can influence HIV-1 disease progression during untreated HIV-1 infection, but the functional and phenotypic properties of HIV-1-specific CD8 T cells in individuals treated with suppressive antiretroviral therapy remain less well understood. Here we show that a subgroup of HIV-1-specific CD8 T cells with stem cell-like properties, termed T memory stem cells (TSCM cells), is enriched in patients receiving suppressive antiretroviral therapy compared with their levels in untreated progressors or controllers. In addition, a prolonged duration of antiretroviral therapy was associated with a progressive increase in the relative proportions of these stem cell-like HIV-1-specific CD8 T cells. Interestingly, the proportions of HIV-1-specific CD8 TSCM cells and total HIV-1-specific CD8 TSCM cells were associated with the CD4 T cell counts during treatment with antiretroviral therapy but not with CD4 T cell counts, viral loads, or immune activation parameters in untreated patients, including controllers. HIV-1-specific CD8 TSCM cells had increased abilities to secrete interleukin-2 in response to viral antigen, while secretion of gamma interferon (IFN-γ) was more limited in comparison to alternative HIV-1-specific CD8 T cell subsets; however, only proportions of IFN-γ-secreting HIV-1-specific CD8 TSCM cells were associated with CD4 T cell counts during antiretroviral therapy. Together, these data suggest that HIV-1-specific CD8 TSCM cells represent a long-lasting component of the cellular immune response to HIV-1 that persists in an antigen-independent fashion during antiretroviral therapy but seems unable to survive and expand under conditions of ongoing viral replication during untreated infection. IMPORTANCE: Memory CD8 T cells that imitate the functional properties of stem cells to maintain lifelong cellular immunity have been hypothesized for many years, but only recently have such cells, termed T memory stem cells (TSCM cells), been physically identified and isolated in humans, mice, and nonhuman primates. Here, we investigated whether cellular immune responses against HIV-1 include such T memory stem cells. Our data show that HIV-1-specific CD8 T memory stem cells are detectable during all stages of HIV-1 infection but occur most visibly at times of prolonged viral antigen suppression by antiretroviral combination therapy. These cells may therefore be particularly relevant for designing antiviral immune defense strategies against the residual reservoir of HIV-1-infected cells that persists despite treatment and leads to viral rebound upon treatment discontinuation.

Th1/17 Polarization of CD4 T Cells Supports HIV-1 Persistence during Antiretroviral Therapy.

UNLABELLED: The ability to persist long term in latently infected CD4 T cells represents a characteristic feature of HIV-1 infection and the predominant barrier to efforts aiming at viral eradication and cure. Yet, increasing evidence suggests that only small subsets of CD4 T cells with specific developmental and maturational profiles are able to effectively support HIV-1 long-term persistence. Here, we analyzed how the functional polarization of CD4 T cells shapes and structures the reservoirs of HIV-1-infected cells. We found that CD4 T cells enriched for a Th1/17 polarization had elevated susceptibilities to HIV-1 infection in ex vivo assays, harbored high levels of HIV-1 DNA in persons treated with antiretroviral therapy, and made a disproportionately increased contribution to the viral reservoir relative to their contribution to the CD4 T memory cell pool. Moreover, HIV-1 DNA levels in Th1/17 cells remained stable over many years of antiretroviral therapy, resulting in a progressively increasing contribution of these cells to the viral reservoir, and phylogenetic studies suggested preferential long-term persistence of identical viral sequences during prolonged antiretroviral treatment in this cell compartment. Together, these data suggest that Th1/17 CD4 T cells represent a preferred site for HIV-1 DNA long-term persistence in patients receiving antiretroviral therapy. IMPORTANCE: Current antiretroviral therapy is very effective in suppressing active HIV-1 replication but does not fully eliminate virally infected cells. The ability of HIV-1 to persist long term despite suppressive antiretroviral combination therapy represents a perplexing aspect of HIV-1 disease pathogenesis, since most HIV-1 target cells are activated, short-lived CD4 T cells. This study suggests that CD4 T helper cells with Th1/17 polarization have a preferential role as a long-term reservoir for HIV-1 infection during antiretroviral therapy, possibly because these cells may imitate some of the functional properties traditionally attributed to stem cells, such as the ability to persist for extremely long periods of time and to repopulate their own pool size through homeostatic self-renewal. These observations support the hypothesis that HIV-1 persistence is driven by small subsets of long-lasting stem cell-like CD4 T cells that may represent particularly promising targets for clinical strategies aiming at HIV-1 eradication and cure.

Innate Immune Activity Correlates with CD4 T Cell-Associated HIV-1 DNA Decline during Latency-Reversing Treatment with Panobinostat.

UNLABELLED: The pharmaceutical reactivation of dormant HIV-1 proviruses by histone deacetylase inhibitors (HDACi) represents a possible strategy to reduce the reservoir of HIV-1-infected cells in individuals treated with suppressive combination antiretroviral therapy (cART). However, the effects of such latency-reversing agents on the viral reservoir size are likely to be influenced by host immune responses. Here, we analyzed the immune factors associated with changes in proviral HIV-1 DNA levels during treatment with the potent HDACi panobinostat in a human clinical trial involving 15 cART-treated HIV-1-infected patients. We observed that the magnitude, breadth, and cytokine secretion profile of HIV-1-specific CD8 T cell responses were unrelated to changes in HIV-1 DNA levels in CD4 T cells during panobinostat treatment. In contrast, the proportions of CD3(-) CD56(+) total NK cells and CD16(+) CD56(dim) NK cells were inversely correlated with HIV-1 DNA levels throughout the study, and changes in HIV-1 DNA levels during panobinostat treatment were negatively associated with the corresponding changes in CD69(+) NK cells. Decreasing levels of HIV-1 DNA during latency-reversing treatment were also related to the proportions of plasmacytoid dendritic cells, to distinct expression patterns of interferon-stimulated genes, and to the expression of the IL28B CC genotype. Together, these data suggest that innate immune activity can critically modulate the effects of latency-reversing agents on the viral reservoir and may represent a target for future immunotherapeutic interventions in HIV-1 eradication studies. IMPORTANCE: Currently available antiretroviral drugs are highly effective in suppressing HIV-1 replication, but the virus persists, despite treatment, in a latent form that does not actively express HIV-1 gene products. One approach to eliminate these cells, colloquially termed the "shock-and-kill" strategy, focuses on the use of latency-reversing agents that induce active viral gene expression in latently infected cells, followed by immune-mediated killing. Panobinostat, a histone deacetylase inhibitor, demonstrated potent activities in reversing HIV-1 latency in a recent pilot clinical trial and reduced HIV-1 DNA levels in a subset of patients. Interestingly, we found that innate immune factors, such as natural killer cells, plasmacytoid dendritic cells, and the expression patterns of interferon-stimulated genes, were most closely linked to a decline in the HIV-1 DNA level during treatment with panobinostat. These data suggest that innate immune activity may play an important role in reducing the residual reservoir of HIV-1-infected cells.

Long-term antiretroviral treatment initiated at primary HIV-1 infection affects the size, composition, and decay kinetics of the reservoir of HIV-1-infected CD4 T cells.

UNLABELLED: Initiation of antiretroviral therapy during the earliest stages of HIV-1 infection may limit the seeding of a long-lasting viral reservoir, but long-term effects of early antiretroviral treatment initiation remain unknown. Here, we analyzed immunological and virological characteristics of nine patients who started antiretroviral therapy at primary HIV-1 infection and remained on suppressive treatment for >10 years; patients with similar treatment duration but initiation of suppressive therapy during chronic HIV-1 infection served as controls. We observed that independently of the timing of treatment initiation, HIV-1 DNA in CD4 T cells decayed primarily during the initial 3 to 4 years of treatment. However, in patients who started antiretroviral therapy in early infection, this decay occurred faster and was more pronounced, leading to substantially lower levels of cell-associated HIV-1 DNA after long-term treatment. Despite this smaller size, the viral CD4 T cell reservoir in persons with early treatment initiation consisted more dominantly of the long-lasting central-memory and T memory stem cells. HIV-1-specific T cell responses remained continuously detectable during antiretroviral therapy, independently of the timing of treatment initiation. Together, these data suggest that early HIV-1 treatment initiation, even when continued for >10 years, is unlikely to lead to viral eradication, but the presence of low viral reservoirs and durable HIV-1 T cell responses may make such patients good candidates for future interventional studies aiming at HIV-1 eradication and cure. IMPORTANCE: Antiretroviral therapy can effectively suppress HIV-1 replication to undetectable levels; however, HIV-1 can persist despite treatment, and viral replication rapidly rebounds when treatment is discontinued. This is mainly due to the presence of latently infected CD4 T cells, which are not susceptible to antiretroviral drugs. Starting treatment in the earliest stages of HIV-1 infection can limit the number of these latently infected cells, raising the possibility that these viral reservoirs are naturally eliminated if suppressive antiretroviral treatment is continued for extremely long periods of time. Here, we analyzed nine patients who started on antiretroviral therapy within the earliest weeks of the disease and continued treatment for more than 10 years. Our data show that early treatment accelerated the decay of infected CD4 T cells and led to very low residual levels of detectable HIV-1 after long-term therapy, levels that were otherwise detectable in patients who are able to maintain a spontaneous, drug-free control of HIV-1 replication. Thus, long-term antiretroviral treatment started during early infection cannot eliminate HIV-1, but the reduced reservoirs of HIV-1 infected cells in such patients may increase their chances to respond to clinical interventions aiming at inducing a drug-free remission of HIV-1 infection.

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.

Conserved and differential gene interactions in dynamical biological systems.

MOTIVATION: While biological systems operated from a common genome can be conserved in various ways, they can also manifest highly diverse dynamics and functions. This is because the same set of genes can interact differentially across specific molecular contexts. For example, differential gene interactions give rise to various stages of morphogenesis during cerebellar development. However, after over a decade of efforts toward reverse engineering biological networks from high-throughput omic data, gene networks of most organisms remain sketchy. This hindrance has motivated us to develop comparative modeling to highlight conserved and differential gene interactions across experimental conditions, without reconstructing complete gene networks first. RESULTS: We established a comparative dynamical system modeling (CDSM) approach to identify conserved and differential interactions across molecular contexts. In CDSM, interactions are represented by ordinary differential equations and compared across conditions through statistical heterogeneity and homogeneity tests. CDSM demonstrated a consistent superiority over differential correlation and reconstruct-then-compare in simulation studies. We exploited CDSM to elucidate gene interactions important for cellular processes poorly understood during mouse cerebellar development. We generated hypotheses on 66 differential genetic interactions involved in expansion of the external granule layer. These interactions are implicated in cell cycle, differentiation, apoptosis and morphogenesis. Additional 1639 differential interactions among gene clusters were also identified when we compared gene interactions during the presence of Rhombic lip versus the presence of distinct internal granule layer. Moreover, compared with differential correlation and reconstruct-then-compare, CDSM makes fewer assumptions on data and thus is applicable to a wider range of biological assays. AVAILABILITY: Source code in C++ and R is available for non-commercial organizations upon request from the corresponding author. The cerebellum gene expression dataset used in this article is available upon request from the Goldowitz lab (dang@cmmt.ubc.ca, http://grits.dglab.org/). CONTACT: joemsong@cs.nmsu.edu SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

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.

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.