UCSC Cell Browser: visualize your single-cell data

Single-cell transcriptome analysis of xenotransplanted human retinal organoids defines two migratory cell populations of nonretinal origin

Human retinal organoid transplantation could potentially be a treatment for degenerative retinal diseases. How the recipient retina regulates the survival, maturation, and proliferation of transplanted organoid cells is unknown. We transplanted human retinal organoid-derived cells into photoreceptor-deficient mice and conducted histology and single-cell RNA sequencing alongside time-matched cultured retinal organoids. Unexpectedly, we observed human cells that migrated into all recipient retinal layers and traveled long distances. Using an unbiased approach, we identified these cells as astrocytes and brain/spinal cord-like neural precursors that were absent or rare in stage-matched cultured organoids. In contrast, retinal progenitor-derived rods and cones remained in the subretinal space, maturing more rapidly than those in the cultured controls. These data suggest that recipient microenvironment promotes the maturation of transplanted photoreceptors while inducing or facilitating the survival of migratory cell populations that are not normally derived from retinal progenitors. These findings have important implications for potential cell-based treatments of retinal diseases.

Unexpected Distribution of Chitin and Chitin Synthase across Soft-Bodied Cnidarians

Cnidarians are commonly recognized as sea jellies, corals, or complex colonies such as the Portuguese man-of-war. While some cnidarians possess rigid internal calcareous skeletons (e.g., corals), many are soft-bodied. Intriguingly, genes coding for the chitin-biosynthetic enzyme, chitin synthase (CHS), were recently identified in the model anemone Nematostella vectensis, a species lacking hard structures. Here we report the prevalence and diversity of CHS across Cnidaria and show that cnidarian chitin synthase genes display diverse protein domain organizations. We found that CHS is expressed in cnidarian species and/or developmental stages with no reported chitinous or rigid morphological structures. Chitin affinity histochemistry indicates that chitin is present in soft tissues of some scyphozoan and hydrozoan medusae. To further elucidate the biology of chitin in cnidarian soft tissues, we focused on CHS expression in N. vectensis. Spatial expression data show that three CHS orthologs are differentially expressed in Nematostella embryos and larvae during development, suggesting that chitin has an integral role in the biology of this species. Understanding how a non-bilaterian lineage such as Cnidaria employs chitin may provide new insight into hitherto unknown functions of polysaccharides in animals, as well as their role in the evolution of biological novelty.

Targeting fatty acid oxidation via Acyl-CoA binding protein hinders glioblastoma invasion

The diffuse nature of Glioblastoma (GBM) tumors poses a challenge to current therapeutic options. We have previously shown that Acyl-CoA Binding Protein (ACBP, also known as DBI) regulates lipid metabolism in GBM cells, favoring fatty acid oxidation (FAO). Here we show that ACBP downregulation results in wide transcriptional changes affecting invasion-related genes. In vivo experiments using patient-derived xenografts combined with in vitro models demonstrated that ACBP sustains GBM invasion via binding to fatty acyl-CoAs. Blocking FAO mimics ACBP^KD-induced immobility, a cellular phenotype that can be rescued by increasing FAO rates. Further investigation into ACBP-downstream pathways served to identify Integrin beta-1, a gene downregulated upon inhibition of either ACBP expression or FAO rates, as a mediator for ACBP's role in GBM invasion. Altogether, our findings highlight a role for FAO in GBM invasion and reveal ACBP as a therapeutic vulnerability to stall FAO and subsequent cell invasion in GBM tumors.

Manual cell selection in single cell transcriptomics using scSELpy supports the analysis of immune cell subsets

Introduction

Single cell RNA sequencing plays an increasing and indispensable role in immunological research such as in the field of inflammatory bowel diseases (IBD). Professional pipelines are complex, but tools for the manual selection and further downstream analysis of single cell populations are missing so far.

Methods

We developed a tool called scSELpy, which can easily be integrated into Scanpy-based pipelines, allowing the manual selection of cells on single cell transcriptomic datasets by drawing polygons on various data representations. The tool further supports the downstream analysis of the selected cells and the plotting of results.

Results

Taking advantage of two previously published single cell RNA sequencing datasets we show that this tool is useful for the positive and negative selection of T cell subsets implicated in IBD beyond standard clustering. We further demonstrate the feasibility for subphenotyping T cell subsets and use scSELpy to corroborate earlier conclusions drawn from the dataset. Moreover, we also show its usefulness in the context of T cell receptor sequencing.

Discussion

Collectively, scSELpy is a promising additive tool fulfilling a so far unmet need in the field of single cell transcriptomic analysis that might support future immunological research.

TWEAK/Fn14 Signalling Regulates the Tissue Microenvironment in Chronic Pancreatitis

Chronic pancreatitis increases the risk of developing pancreatic cancer through the upregulation of pathways favouring proliferation, fibrosis, and sustained inflammation. We established in previous studies that the ligand tumour necrosis factor (TNF)-like weak inducer of apoptosis (TWEAK) signals through its cognate receptor fibroblast growth factor-inducible 14 (Fn14) to regulate these underlying cellular processes in the chronic liver injury niche. However, the role of the TWEAK/Fn14 signalling pathway in pancreatic disease is entirely unknown. An analysis of publicly available datasets demonstrated that the TWEAK receptor Fn14 is upregulated in pancreatitis and pancreatic adenocarcinoma, with single cell RNA sequencing revealing pancreatic ductal cells as the main Fn14 producers. We then used choline-deficient, ethionine-supplemented (CDE) diet feeding of wildtype C57BL/6J and Fn14 knockout littermates to (a) confirm CDE treatment as a suitable model of chronic pancreatitis and (b) to investigate the role of the TWEAK/Fn14 signalling pathway in pancreatic ductal proliferation, as well as fibrotic and inflammatory cell dynamics. Our time course data obtained at three days, three months, and six months of CDE treatment reveal that a lack of TWEAK/Fn14 signalling significantly inhibits the establishment and progression of the tissue microenvironment in CDE-induced chronic pancreatitis, thus proposing the TWEAK/Fn14 pathway as a novel therapeutic target.

Augmentation of a neuroprotective myeloid state by hematopoietic cell transplantation

Multiple sclerosis (MS) is an autoimmune disease associated with inflammatory demyelination in the central nervous system (CNS). Autologous hematopoietic cell transplantation (HCT) is under investigation as a promising therapy for treatment-refractory MS. Here we identify a reactive myeloid state in chronic experimental autoimmune encephalitis (EAE) mice and MS patients that is surprisingly associated with neuroprotection and immune suppression. HCT in EAE mice leads to an enhancement of this myeloid state, as well as clinical improvement, reduction of demyelinated lesions, suppression of cytotoxic T cells, and amelioration of reactive astrogliosis reflected in reduced expression of EAE-associated gene signatures in oligodendrocytes and astrocytes. Further enhancement of myeloid cell incorporation into the CNS following a modified HCT protocol results in an even more consistent therapeutic effect corroborated by additional amplification of HCT-induced transcriptional changes, underlining myeloid-derived beneficial effects in the chronic phase of EAE. Replacement or manipulation of CNS myeloid cells thus represents an intriguing therapeutic direction for inflammatory demyelinating disease.

Prognostic and immunotherapeutic predictive value of interleukin enhancer-binding factor 3 in hepatocellular carcinoma: Integrated bioinformatics and experimental analysis

Interleukin enhancer-binding factor 3 (ILF3) as an RNA-binding protein that plays a critical role in the process of cancer and antiviral responses. However, no researcher has focused on the pan-cancer analysis of ILF3, and the effect of ILF3 on tumor immunity is still largely unclear. This study synthetically analyzed the relationship between the expression of ILF3 across various cancers and prognosis, microsatellite instability (MSI), tumor mutational burden (TMB), tumor immune cell infiltration, and common immune checkpoint molecules by multiple bioinformatics databases. Experimentally, we detected the mRNA abundance of ILF3 and immune checkpoint molecules in liver hepatocellular carcinoma (LIHC) tissues. The functions of ILF3 on hepatocellular carcinoma (HCC) cells were verified by western blot assay and cytotoxicity assay. We found that ILF3 was aberrantly expressed and associated with the prognosis in several types of tumors. The ILF3 expression was significantly correlated with infiltrating levels of immune cells and immune molecules in certain cancers, particularly in LIHC. Detection of clinical liver cancer tissues confirmed the positive correlation between ILF3 and immune checkpoint molecules, including programmed cell death 1 (PD-1), programmed cell death ligand 1 (PD-L1), cytotoxic T lymphocyte-associated antigen 4 (CTLA4), lymphocyte-activation gene 3 (LAG3), and T cell immunoglobulin domain and mucin domain-3 (TIM3). Furthermore, reduced PD-L1 and increased sensitivity of HCC cells to T cells cytotoxicity were found in ILF3-knockdown cells. This work suggested ILF3 may be used as a prognostic marker for various tumors to predict the response to immunotherapy.

Systematic Guidelines for Effective Utilization of COVID-19 Databases in Genomic, Epidemiologic, and Clinical Research

The pandemic has led to the production and accumulation of various types of data related to coronavirus disease 2019 (COVID-19). To understand the features and characteristics of COVID-19 data, we summarized representative databases and determined the data types, purpose, and utilization details of each database. In addition, we categorized COVID-19 associated databases into epidemiological data, genome and protein data, and drug and target data. We found that the data present in each of these databases have nine separate purposes (clade/variant/lineage, genome browser, protein structure, epidemiological data, visualization, data analysis tool, treatment, literature, and immunity) according to the types of data. Utilizing the databases we investigated, we created four queries as integrative analysis methods that aimed to answer important scientific questions related to COVID-19. Our queries can make effective use of multiple databases to produce valuable results that can reveal novel findings through comprehensive analysis. This allows clinical researchers, epidemiologists, and clinicians to have easy access to COVID-19 data without requiring expert knowledge in computing or data science. We expect that users will be able to reference our examples to construct their own integrative analysis methods, which will act as a basis for further scientific inquiry and data searching.

Mendelian Randomization Study Using Dopaminergic Neuron-Specific eQTL Identifies Novel Risk Genes for Schizophrenia

Multiple integrative studies have been performed to identify the potential target genes of the non-coding schizophrenia (SCZ) risk variants. However, all the integrative studies used expression quantitative trait loci (eQTL) data from bulk tissues. Considering the cell type-specific regulatory effect of many genetic variants, it is important to conduct integrative studies using cell type-specific eQTL data. Here, we conduct a Mendelian randomization (MR) study by integrating genome-wide associations of SCZ (74,776 cases and 101,023 controls) and eQTL data (N = 215) from dopaminergic neurons, which were differentiated from human-induced pluripotent stem cell (iPSC) lines. For eQTL from young post-mitotic dopaminergic neurons (differentiation of iPSC for 30 days, D30), we identified 34 genes whose genetically regulated expression in dopaminergic neurons may have a causal role in SCZ. Among which, ARL3 showed the most significant associations with SCZ. For eQTL from more mature dopaminergic neurons (D52), we identified 37 potential SCZ causal genes, and ARL3 and GNL3 showed the most significant associations. Only 12 genes showed significant associations with SCZ in both D30 and D52 eQTL datasets, indicating the time point-specific genetic regulatory effects in young post-mitotic dopaminergic neurons and more mature dopaminergic neurons. Comparing the results from dopaminergic neurons with bulk brain tissues prioritized 2 high-confidence risk genes, including DDHD2 and GALNT10. Our study identifies multiple risk genes whose genetically regulated expression in dopaminergic neurons may have a causal role in SCZ. Further mechanistic investigation will provide pivotal insights into SCZ pathophysiology.

Toward Best Practices for Imaging Transcriptomics of the Human Brain

Modern brainwide transcriptional atlases provide unprecedented opportunities for investigating the molecular correlates of brain organization, as quantified using noninvasive neuroimaging. However, integrating neuroimaging data with transcriptomic measures is not straightforward, and careful consideration is required to make valid inferences. In this article, we review recent work exploring how various methodological choices affect 3 main phases of imaging transcriptomic analyses, including 1) processing of transcriptional atlas data; 2) relating transcriptional measures to independently derived neuroimaging phenotypes; and 3) evaluating the functional implications of identified associations through gene enrichment analyses. Our aim is to facilitate the development of standardized and reproducible approaches for this rapidly growing field. We identify sources of methodological variability, key choices that can affect findings, and considerations for mitigating false positive and/or spurious results. Finally, we provide an overview of freely available open-source toolboxes implementing current best-practice procedures across all 3 analysis phases.

The role of histone methyltransferases in neurocognitive disorders associated with brain size abnormalities

Brain size is controlled by several factors during neuronal development, including neural progenitor proliferation, neuronal arborization, gliogenesis, cell death, and synaptogenesis. Multiple neurodevelopmental disorders have co-morbid brain size abnormalities, such as microcephaly and macrocephaly. Mutations in histone methyltransferases that modify histone H3 on Lysine 36 and Lysine 4 (H3K36 and H3K4) have been identified in neurodevelopmental disorders involving both microcephaly and macrocephaly. H3K36 and H3K4 methylation are both associated with transcriptional activation and are proposed to sterically hinder the repressive activity of the Polycomb Repressor Complex 2 (PRC2). During neuronal development, tri-methylation of H3K27 (H3K27me3) by PRC2 leads to genome wide transcriptional repression of genes that regulate cell fate transitions and neuronal arborization. Here we provide a review of neurodevelopmental processes and disorders associated with H3K36 and H3K4 histone methyltransferases, with emphasis on processes that contribute to brain size abnormalities. Additionally, we discuss how the counteracting activities of H3K36 and H3K4 modifying enzymes vs. PRC2 could contribute to brain size abnormalities which is an underexplored mechanism in relation to brain size control.

Endothelial Indoleamine-2,3-Dioxygenase-1 is not Critically Involved in Regulating Antitumor Immunity in the Central Nervous System

The vascular niche of malignant gliomas is a key compartment that shapes the immunosuppressive brain tumor microenvironment (TME). The blood-brain-barrier (BBB) consisting of specialized endothelial cells (ECs) and perivascular cells forms a tight anatomical and functional barrier critically controlling transmigration and effector function of immune cells. During neuroinflammation and tumor progression, the metabolism of the essential amino acid tryptophan (Trp) to metabolites such as kynurenine has long been identified as an important metabolic pathway suppressing immune responses. Previous studies have demonstrated that indoleamine-2,3-dioxygenase-1 (IDO1), a key rate-limiting enzyme in tryptophan catabolism, is expressed within the TME of high-grade gliomas. Here, we investigate the role of endothelial IDO1 (eIDO1) expression for brain tumor immunity. Single-cell RNA sequencing data revealed that in human glioma tissue, IDO1 is predominantly expressed by activated ECs showing a JAK/STAT signaling pathway-related CXCL11⁺ gene expression signature. In a syngeneic experimental glioma model, eIDO1 is induced by low-dose tumor irradiation. However, cell type-specific ablation of eIDO1 in experimental gliomas did not alter frequency and phenotype of tumor-infiltrating T cells nor tumor growth. Taken together these data argue against a dominant role of eIDO1 for brain tumor immunity.

Meta-Analysis of Human Cancer Single-Cell RNA-Seq Datasets Using the IMMUcan Database

The development of single-cell RNA sequencing (scRNA-seq) technologies has greatly contributed to deciphering the tumor microenvironment (TME). An enormous amount of independent scRNA-seq studies have been published representing a valuable resource that provides opportunities for meta-analysis studies. However, the massive amount of biological information, the marked heterogeneity and variability between studies, and the technical challenges in processing heterogeneous datasets create major bottlenecks for the full exploitation of scRNA-seq data. We have developed IMMUcan scDB (https://immucanscdb.vital-it.ch), a fully integrated scRNA-seq database exclusively dedicated to human cancer and accessible to nonspecialists. IMMUcan scDB encompasses 144 datasets on 56 different cancer types, annotated in 50 fields containing precise clinical, technological, and biological information. A data processing pipeline was developed and organized in four steps: (i) data collection; (ii) data processing (quality control and sample integration); (iii) supervised cell annotation with a cell ontology classifier of the TME; and (iv) interface to analyze TME in a cancer type-specific or global manner. This framework was used to explore datasets across tumor locations in a gene-centric (CXCL13) and cell-centric (B cells) manner as well as to conduct meta-analysis studies such as ranking immune cell types and genes correlated to malignant transformation. This integrated, freely accessible, and user-friendly resource represents an unprecedented level of detailed annotation, offering vast possibilities for downstream exploitation of human cancer scRNA-seq data for discovery and validation studies.

SIGNIFICANCE

The IMMUcan scDB database is an accessible supportive tool to analyze and decipher tumor-associated single-cell RNA sequencing data, allowing researchers to maximally use this data to provide new insights into cancer biology.

Differentiation and Maturation of Muscle and Fat Cells in Cultivated Seafood: Lessons from Developmental Biology

Cultivated meat, also known as cultured or cell-based meat, is meat produced directly from cultured animal cells rather than from a whole animal. Cultivated meat and seafood have been proposed as a means of mitigating the substantial harms associated with current production methods, including damage to the environment, antibiotic resistance, food security challenges, poor animal welfare, and-in the case of seafood-overfishing and ecological damage associated with fishing and aquaculture. Because biomedical tissue engineering research, from which cultivated meat draws a great deal of inspiration, has thus far been conducted almost exclusively in mammals, cultivated seafood suffers from a lack of established protocols for producing complex tissues in vitro. At the same time, fish such as the zebrafish Danio rerio have been widely used as model organisms in developmental biology. Therefore, many of the mechanisms and signaling pathways involved in the formation of muscle, fat, and other relevant tissue are relatively well understood for this species. The same processes are understood to a lesser degree in aquatic invertebrates. This review discusses the differentiation and maturation of meat-relevant cell types in aquatic species and makes recommendations for future research aimed at recapitulating these processes to produce cultivated fish and shellfish.

Molecular Actors of Inflammation and Their Signaling Pathways: Mechanistic Insights from Zebrafish

Inflammation is a hallmark of the physiological response to aggressions. It is orchestrated by a plethora of molecules that detect the danger, signal intracellularly, and activate immune mechanisms to fight the threat. Understanding these processes at a level that allows to modulate their fate in a pathological context strongly relies on in vivo studies, as these can capture the complexity of the whole process and integrate the intricate interplay between the cellular and molecular actors of inflammation. Over the years, zebrafish has proven to be a well-recognized model to study immune responses linked to human physiopathology. We here provide a systematic review of the molecular effectors of inflammation known in this vertebrate and recapitulate their modes of action, as inferred from sterile or infection-based inflammatory models. We present a comprehensive analysis of their sequence, expression, and tissue distribution and summarize the tools that have been developed to study their function. We further highlight how these tools helped gain insights into the mechanisms of immune cell activation, induction, or resolution of inflammation, by uncovering downstream receptors and signaling pathways. These progresses pave the way for more refined models of inflammation, mimicking human diseases and enabling drug development using zebrafish models.

Molecular imaging of chemokine-like receptor 1 (CMKLR1) in experimental acute lung injury

The lack of techniques for noninvasive imaging of inflammation has challenged precision medicine management of acute respiratory distress syndrome (ARDS). Here, we determined the potential of positron emission tomography (PET) of chemokine-like receptor-1 (CMKLR1) to monitor lung inflammation in a murine model of lipopolysaccharide-induced injury. Lung uptake of a CMKLR1-targeting radiotracer, [⁶⁴Cu]NODAGA-CG34, was significantly increased in lipopolysaccharide-induced injury, correlated with the expression of multiple inflammatory markers, and reduced by dexamethasone treatment. Monocyte-derived macrophages, followed by interstitial macrophages and monocytes were the major CMKLR1-expressing leukocytes contributing to the increased tracer uptake throughout the first week of lipopolysaccharide-induced injury. The clinical relevance of CMKLR1 as a biomarker of lung inflammation in ARDS was confirmed using single-nuclei RNA-sequencing datasets which showed significant increases in CMKLR1 expression among transcriptionally distinct subsets of lung monocytes and macrophages in COVID-19 patients vs. controls. CMKLR1-targeted PET is a promising strategy to monitor the dynamics of lung inflammation and response to anti-inflammatory treatment in ARDS.

SPEED: Single-cell Pan-species atlas in the light of Ecology and Evolution for Development and Diseases

It is a challenge to efficiently integrate and present the tremendous amounts of single-cell data generated from multiple tissues of various species. Here, we create a new database named SPEED for single-cell pan-species atlas in the light of ecology and evolution for development and diseases (freely accessible at http://8.142.154.29 or http://speedatlas.net). SPEED is an online platform with 4 data modules, 7 function modules and 2 display modules. The 'Pan' module is applied for the interactive analysis of single cell sequencing datasets from 127 species, and the 'Evo', 'Devo', and 'Diz' modules provide comprehensive analysis of single-cell atlases on 18 evolution datasets, 28 development datasets, and 85 disease datasets. The 'C2C', 'G2G' and 'S2S' modules explore intercellular communications, genetic regulatory networks, and cross-species molecular evolution. The 'sSearch', 'sMarker', 'sUp', and 'sDown' modules allow users to retrieve specific data information, obtain common marker genes for cell types, freely upload, and download single-cell datasets, respectively. Two display modules ('HOME' and 'HELP') offer easier access to the SPEED database with informative statistics and detailed guidelines. All in all, SPEED is an integrated platform for single-cell RNA sequencing (scRNA-seq) and single-cell whole-genome sequencing (scWGS) datasets to assist the deep-mining and understanding of heterogeneity among cells, tissues, and species at multi-levels, angles, and orientations, as well as provide new insights into molecular mechanisms of biological development and pathogenesis.

Genetic screening for hypertension and COVID-19 reveals functional variation of SPEG potentially associated with severe COVID-19 in women

The coronavirus disease 2019 (COVID-19) pandemic, caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has led to more than 6.4 million deaths worldwide. The prevalent comorbidity between hypertension and severe COVID-19 suggests common genetic factors may affect the outcome of both diseases. As both hypertension and severe COVID-19 demonstrate sex-biased prevalence, common genetic factors between the two diseases may display sex-biased differential associations. By evaluating COVID-19 association signals of 172-candidate hypertension single nucleotide polymorphisms (SNPs) derived from more than 1 million European individuals in two sex-stratified severe COVID-19 genome-wide association studies from UK BioBank with European ancestry, we revealed one functional cis expression quantitative trait locus of SPEG (rs12474050) showing sex-biased association with severe COVID-19 in women. The risk allele rs12474050*T associates with higher blood pressure. In our study, we found it is significantly correlated with lower SPEG expression in muscle-skeletal but with higher expression in both brain cerebellum and cerebellar hemisphere. Additionally, nominal significances were detected for the association between rs12474050*T and lower SPEG expression in both heart left ventricle and atrial appendage; among these tissues, the SPEG expression is nominally significantly higher in females than in males. Further analysis revealed SPEG is mainly expressed in cardiomyocytes in heart and is upregulated upon SARS-CoV-2 infection, with significantly higher upregulation of SPEG only observed in female but not in male COVID-19 patients compared to both normal female and male individuals, suggesting upregulation of SPEG is a female-specific protective mechanism against COVID-19 induced heart damage. Taken together, our analyses suggest the involvement of SPEG in both hypertension and severe COVID-19 in women, which provides new insights for sex-biased effect of severe COVID-19 in women.

Polyphony: an Interactive Transfer Learning Framework for Single-Cell Data Analysis

Reference-based cell-type annotation can significantly reduce time and effort in single-cell analysis by transferring labels from a previously-annotated dataset to a new dataset. However, label transfer by end-to-end computational methods is challenging due to the entanglement of technical (e.g., from different sequencing batches or techniques) and biological (e.g., from different cellular microenvironments) variations, only the first of which must be removed. To address this issue, we propose Polyphony, an interactive transfer learning (ITL) framework, to complement biologists' knowledge with advanced computational methods. Polyphony is motivated and guided by domain experts' needs for a controllable, interactive, and algorithm-assisted annotation process, identified through interviews with seven biologists. We introduce anchors, i.e., analogous cell populations across datasets, as a paradigm to explain the computational process and collect user feedback for model improvement. We further design a set of visualizations and interactions to empower users to add, delete, or modify anchors, resulting in refined cell type annotations. The effectiveness of this approach is demonstrated through quantitative experiments, two hypothetical use cases, and interviews with two biologists. The results show that our anchor-based ITL method takes advantage of both human and machine intelligence in annotating massive single-cell datasets.

Web-based gene expression analysis-paving the way to decode healthy and diseased ocular tissue

BACKGROUND

Gene expression analysis using RNA sequencing has helped to improve the understanding of many diseases. Databases, such as the Gene Expression Omnibus database of the National Center for Biotechnology Information provide RNA sequencing raw data from various diseased tissue types but their analysis requires advanced bioinformatics skills. Therefore, specific ocular databases provide the transcriptional profiles of different ocular tissues and in addition enable intuitive web-based data analysis.

OBJECTIVE

The aim of this narrative review is to provide an overview of ocular transcriptome databases and to compare them with the Human Eye Transcriptome Atlas newly established in Freiburg.

METHODS

PubMed literature search.

RESULTS

A total of nine ocular transcriptome databases focusing on different aspects were identified. The iSyTE and Express platforms specialize in gene expression during lens and retinal development in mice, whereas retina.tigem.it, Eye in a Disk, and Spectacle focus on selected ocular tissues such as the retina. Spectacle, UCSC Cell Browser and Single Cell Portal allow intuitive exploration of single cell RNA sequencing data derived from retinal, choroid, cornea, iris, trabecular meshwork and sclera specimens. The microarray profiles of a variety of healthy ocular tissues are included in the Ocular Tissue Database. The Human Eye Transcriptome Atlas provides the largest collection of different ocular tissue types, contains the highest number of ocular diseases and is characterized by a high level of quality achieved by methodological consistency.

CONCLUSION

Ocular transcriptome databases provide comprehensive and intuitive insights into the transcriptional profiles of a variety of healthy and diseased ocular tissues. Thus, they improve our understanding of the underlying molecular mediators, support hypothesis generation and help in the search for new diagnostic and therapeutic targets for various ocular diseases.

A theoretical framework of immune cell phenotypic classification and discovery

Immune cells are highly heterogeneous and show diverse phenotypes, but the underlying mechanism remains to be elucidated. In this study, we proposed a theoretical framework for immune cell phenotypic classification based on gene plasticity, which herein refers to expressional change or variability in response to conditions. The system contains two core points. One is that the functional subsets of immune cells can be further divided into subdivisions based on their highly plastic genes, and the other is that loss of phenotype accompanies gain of phenotype during phenotypic conversion. The first point suggests phenotypic stratification or layerability according to gene plasticity, while the second point reveals expressional compatibility and mutual exclusion during the change in gene plasticity states. Abundant transcriptome data analysis in this study from both microarray and RNA sequencing in human CD4 and CD8 single-positive T cells, B cells, natural killer cells and monocytes supports the logical rationality and generality, as well as expansibility, across immune cells. A collection of thousands of known immunophenotypes reported in the literature further supports that highly plastic genes play an important role in maintaining immune cell phenotypes and reveals that the current classification model is compatible with the traditionally defined functional subsets. The system provides a new perspective to understand the characteristics of dynamic, diversified immune cell phenotypes and intrinsic regulation in the immune system. Moreover, the current substantial results based on plasticitomics analysis of bulk and single-cell sequencing data provide a useful resource for big-data-driven experimental studies and knowledge discoveries.

Integrated Analysis of Bulk RNA-Seq and Single-Cell RNA-Seq Unravels the Influences of SARS-CoV-2 Infections to Cancer Patients

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is a highly contagious and pathogenic coronavirus that emerged in late 2019 and caused a pandemic of respiratory illness termed as coronavirus disease 2019 (COVID-19). Cancer patients are more susceptible to SARS-CoV-2 infection. The treatment of cancer patients infected with SARS-CoV-2 is more complicated, and the patients are at risk of poor prognosis compared to other populations. Patients infected with SARS-CoV-2 are prone to rapid development of acute respiratory distress syndrome (ARDS) of which pulmonary fibrosis (PF) is considered a sequelae. Both ARDS and PF are factors that contribute to poor prognosis in COVID-19 patients. However, the molecular mechanisms among COVID-19, ARDS and PF in COVID-19 patients with cancer are not well-understood. In this study, the common differentially expressed genes (DEGs) between COVID-19 patients with and without cancer were identified. Based on the common DEGs, a series of analyses were performed, including Gene Ontology (GO) and pathway analysis, protein-protein interaction (PPI) network construction and hub gene extraction, transcription factor (TF)-DEG regulatory network construction, TF-DEG-miRNA coregulatory network construction and drug molecule identification. The candidate drug molecules (e.g., Tamibarotene CTD 00002527) obtained by this study might be helpful for effective therapeutic targets in COVID-19 patients with cancer. In addition, the common DEGs among ARDS, PF and COVID-19 patients with and without cancer are TNFSF10 and IFITM2. These two genes may serve as potential therapeutic targets in the treatment of COVID-19 patients with cancer. Changes in the expression levels of TNFSF10 and IFITM2 in CD14+/CD16+ monocytes may affect the immune response of COVID-19 patients. Specifically, changes in the expression level of TNFSF10 in monocytes can be considered as an immune signature in COVID-19 patients with hematologic cancer. Targeting N6-methyladenosine (m6A) pathways (e.g., METTL3/SERPINA1 axis) to restrict SARS-CoV-2 reproduction has therapeutic potential for COVID-19 patients.

The UCSC Genome Browser database: 2023 update

The UCSC Genome Browser (https://genome.ucsc.edu) is an omics data consolidator, graphical viewer, and general bioinformatics resource that continues to serve the community as it enters its 23rd year. This year has seen an emphasis in clinical data, with new tracks and an expanded Recommended Track Sets feature on hg38 as well as the addition of a single cell track group. SARS-CoV-2 continues to remain a focus, with regular annotation updates to the browser and continued curation of our phylogenetic sequence placing tool, hgPhyloPlace, whose tree has now reached over 12M sequences. Our GenArk resource has also grown, offering over 2500 hubs and a system for users to request any absent assemblies. We have expanded our bigBarChart display type and created new ways to visualize data via bigRmsk and dynseq display. Displaying custom annotations is now easier due to our chromAlias system which eliminates the requirement for renaming sequence names to the UCSC standard. Users involved in data generation may also be interested in our new tools and trackDb settings which facilitate the creation and display of their custom annotations.

Leveraging global multi-ancestry meta-analysis in the study of idiopathic pulmonary fibrosis genetics

The research of rare and devastating orphan diseases, such as idiopathic pulmonary fibrosis (IPF) has been limited by the rarity of the disease itself. The prognosis is poor-the prevalence of IPF is only approximately four times the incidence, limiting the recruitment of patients to trials and studies of the underlying biology. Global biobanking efforts can dramatically alter the future of IPF research. We describe a large-scale meta-analysis of IPF, with 8,492 patients and 1,355,819 population controls from 13 biobanks around the globe. Finally, we combine this meta-analysis with the largest available meta-analysis of IPF, reaching 11,160 patients and 1,364,410 population controls. We identify seven novel genome-wide significant loci, only one of which would have been identified if the analysis had been limited to European ancestry individuals. We observe notable pleiotropy across IPF susceptibility and severe COVID-19 infection and note an unexplained sex-heterogeneity effect at the strongest IPF locus MUC5B.

FaceBase: A Community-Driven Hub for Data-Intensive Research

The FaceBase Consortium, funded by the National Institute of Dental and Craniofacial Research of the National Institutes of Health, was established in 2009 with the recognition that dental and craniofacial research are increasingly data-intensive disciplines. Data sharing is critical for the validation and reproducibility of results as well as to enable reuse of data. In service of these goals, data ought to be FAIR: Findable, Accessible, Interoperable, and Reusable. The FaceBase data repository and educational resources exemplify the FAIR principles and support a broad user community including researchers in craniofacial development, molecular genetics, and genomics. FaceBase demonstrates that a model in which researchers "self-curate" their data can be successful and scalable. We present the results of the first 2.5 y of FaceBase's operations as an open community and summarize the data sets published during this period. We then describe a research highlight from work on the identification of regulatory networks and noncoding RNAs involved in cleft lip with/without cleft palate that both used and in turn contributed new findings to publicly available FaceBase resources. Collectively, FaceBase serves as a dynamic and continuously evolving resource to facilitate data-intensive research, enhance data reproducibility, and perform deep phenotyping across multiple species in dental and craniofacial research.

Cerebral Organoids as an Experimental Platform for Human Neurogenomics

The cerebral cortex forms early in development according to a series of heritable neurodevelopmental instructions. Despite deep evolutionary conservation of the cerebral cortex and its foundational six-layered architecture, significant variations in cortical size and folding can be found across mammals, including a disproportionate expansion of the prefrontal cortex in humans. Yet our mechanistic understanding of neurodevelopmental processes is derived overwhelmingly from rodent models, which fail to capture many human-enriched features of cortical development. With the advent of pluripotent stem cells and technologies for differentiating three-dimensional cultures of neural tissue in vitro, cerebral organoids have emerged as an experimental platform that recapitulates several hallmarks of human brain development. In this review, we discuss the merits and limitations of cerebral organoids as experimental models of the developing human brain. We highlight innovations in technology development that seek to increase its fidelity to brain development in vivo and discuss recent efforts to use cerebral organoids to study regeneration and brain evolution as well as to develop neurological and neuropsychiatric disease models.

Single-cell analyses reveal early thymic progenitors and pre-B cells in zebrafish

The zebrafish has proven to be a valuable model organism for studying hematopoiesis, but relatively little is known about zebrafish immune cell development and functional diversity. Elucidating key aspects of zebrafish lymphocyte development and exploring the breadth of effector functions would provide valuable insight into the evolution of adaptive immunity. We performed single-cell RNA sequencing on ∼70,000 cells from the zebrafish marrow and thymus to establish a gene expression map of zebrafish immune cell development. We uncovered rich cellular diversity in the juvenile and adult zebrafish thymus, elucidated B- and T-cell developmental trajectories, and transcriptionally characterized subsets of hematopoietic stem and progenitor cells and early thymic progenitors. Our analysis permitted the identification of two dendritic-like cell populations and provided evidence in support of the existence of a pre-B cell state. Our results provide critical insights into the landscape of zebrafish immunology and offer a foundation for cellular and genetic studies.

dock8 deficiency attenuates microglia colonization in early zebrafish larvae

Microglia are tissue-resident macrophages that carry out immune functions in the brain. The deficiency or dysfunction of microglia has been implicated in many neurodegenerative disorders. DOCK8, a member of the DOCK family, functions as a guanine nucleotide exchange factor and plays key roles in immune regulation and neurological diseases. The functions of DOCK8 in microglia development are not fully understood. Here, we generated zebrafish dock8 mutants by CRISPR/Cas9 genome editing and showed that dock8 mutations attenuate microglia colonization in the zebrafish midbrain at early larvae stages. In vivo time-lapse imaging revealed that the motility of macrophages was reduced in the dock8 mutant. We further found that cdc42/cdc42l, which encode the small GTPase activated by Dock8, also regulate microglia colonization in zebrafish. Collectively, our study suggests that the Dock8-Cdc42 pathway is required for microglia colonization in zebrafish larvae.

Single cell spatial analysis reveals the topology of immunomodulatory purinergic signaling in glioblastoma

How the glioma immune microenvironment fosters tumorigenesis remains incompletely defined. Here, we use single-cell RNA-sequencing and multiplexed tissue-imaging to characterize the composition, spatial organization, and clinical significance of extracellular purinergic signaling in glioma. We show that microglia are the predominant source of CD39, while tumor cells principally express CD73. In glioblastoma, CD73 is associated with EGFR amplification, astrocyte-like differentiation, and increased adenosine, and is linked to hypoxia. Glioblastomas enriched for CD73 exhibit inflammatory microenvironments, suggesting that purinergic signaling regulates immune adaptation. Spatially-resolved single-cell analyses demonstrate a strong spatial correlation between tumor-CD73 and microglial-CD39, with proximity associated with poor outcomes. Similar spatial organization is present in pediatric high-grade gliomas including H3K27M-mutant diffuse midline glioma. These data reveal that purinergic signaling in gliomas is shaped by genotype, lineage, and functional state, and that core enzymes expressed by tumor and myeloid cells are organized to promote adenosine-rich microenvironments potentially amenable to therapeutic targeting.

Csf1rb regulates definitive hematopoiesis in zebrafish

In vertebrates, hematopoietic stem and progenitor cells (HSPCs) are capable of self-renewal and continuously replenishing all mature blood lineages throughout life. However, the molecular signaling regulating the maintenance and expansion of HSPCs remains incompletely understood. Colony-stimulating factor 1 receptor (CSF1R) is believed to be the primary regulator for the myeloid lineage but not HSPC development. Here, we show a surprising role of Csf1rb, a zebrafish homolog of mammalian CSF1R, in preserving the HSPC pool by maintaining the proliferation of HSPCs. Deficiency of csf1rb leads to a reduction in both HSPCs and their differentiated progenies, including myeloid, lymphoid and erythroid cells at early developmental stages. Likewise, the absence of csf1rb conferred similar defects upon HSPCs and leukocytes in adulthood. Furthermore, adult hematopoietic cells from csf1rb mutants failed to repopulate immunodeficient zebrafish. Interestingly, loss-of-function and gain-of-function assays suggested that the canonical ligands for Csf1r in zebrafish, including Csf1a, Csf1b and Il34, were unlikely to be ligands of Csf1rb. Thus, our data indicate a previously unappreciated role of Csf1r in maintaining HSPCs, independently of known ligands.

Redox regulation by TXNRD3 during epididymal maturation underlies capacitation-associated mitochondrial activity and sperm motility in mice

During epididymal transit, redox remodeling protects mammalian spermatozoa, preparing them for survival in the subsequent journey to fertilization. However, molecular mechanisms of redox regulation in sperm development and maturation remain largely elusive. In this study, we report that thioredoxin-glutathione reductase (TXNRD3), a thioredoxin reductase family member particularly abundant in elongating spermatids at the site of mitochondrial sheath formation, regulates redox homeostasis to support male fertility. Using Txnrd3-/- mice, our biochemical, ultrastructural, and live cell imaging analyses revealed impairments in sperm morphology and motility under conditions of TXNRD3 deficiency. We find that mitochondria develop more defined cristae during capacitation in wildtype sperm. Furthermore, we show that absence of TXNRD3 alters thiol redox status in both the head and tail during sperm maturation and capacitation, resulting in defective mitochondrial ultrastructure and activity under capacitating conditions. These findings provide insights into molecular mechanisms of redox homeostasis and bioenergetics during sperm maturation, capacitation, and fertilization.

Emerging pathogenic mechanisms in human brain arteriovenous malformations: a contemporary review in the multiomics era

A variety of pathogenic mechanisms have been described in the formation, maturation, and rupture of brain arteriovenous malformations (bAVMs). While the understanding of bAVMs has largely been formulated based on animal models of rare hereditary diseases in which AVMs form, a new era of “omics” has permitted large-scale examinations of contributory genetic variations in human sporadic bAVMs. New findings regarding the pathogenesis of bAVMs implicate changes to endothelial and mural cells that result in increased angiogenesis, proinflammatory recruitment, and breakdown of vascular barrier properties that may result in hemorrhage; a greater diversity of cell populations that compose the bAVM microenvironment may also be implicated and complicate traditional models. Genomic sequencing of human bAVMs has uncovered inherited, de novo, and somatic activating mutations, such as KRAS, which contribute to the pathogenesis of bAVMs. New droplet-based, single-cell sequencing technologies have generated atlases of cell-specific molecular derangements. Herein, the authors review emerging genomic and transcriptomic findings underlying pathologic cell transformations in bAVMs derived from human tissues. The application of multiple sequencing modalities to bAVM tissues is a natural next step for researchers, although the potential therapeutic benefits or clinical applications remain unknown.

SingleCAnalyzer: Interactive Analysis of Single Cell RNA-Seq Data on the Cloud

Single-cell RNA sequencing (scRNA-Seq) enables researchers to quantify the transcriptomes of individual cells. The capacity of researchers to perform this type of analysis has allowed researchers to undertake new scientific goals. The usefulness of scRNA-Seq has depended on the development of new computational biology methods, which have been designed to meeting challenges associated with scRNA-Seq analysis. However, the proper application of these computational methods requires extensive bioinformatics expertise. Otherwise, it is often difficult to obtain reliable and reproducible results. We have developed SingleCAnalyzer, a cloud platform that provides a means to perform full scRNA-Seq analysis from FASTQ within an easy-to-use and self-exploratory web interface. Its analysis pipeline includes the demultiplexing and alignment of FASTQ files, read trimming, sample quality control, feature selection, empty droplets detection, dimensional reduction, cellular type prediction, unsupervised clustering of cells, pseudotime/trajectory analysis, expression comparisons between groups, functional enrichment of differentially expressed genes and gene set expression analysis. Results are presented with interactive graphs, which provide exploratory and analytical features. SingleCAnalyzer is freely available at https://singleCAnalyzer.eu.

Developmental landscape of human forebrain at a single-cell level identifies early waves of oligodendrogenesis

Oligodendrogenesis in the human central nervous system has been observed mainly at the second trimester of gestation, a much later developmental stage compared to oligodendrogenesis in mice. Here, we characterize the transcriptomic neural diversity in the human forebrain at post-conception weeks (PCW) 8-10. Using single-cell RNA sequencing, we find evidence of the emergence of a first wave of oligodendrocyte lineage cells as early as PCW 8, which we also confirm at the epigenomic level through the use of single-cell ATAC-seq. Using regulatory network inference, we predict key transcriptional events leading to the specification of oligodendrocyte precursor cells (OPCs). Moreover, by profiling the spatial expression of 50 key genes through the use of in situ sequencing (ISS), we identify regions in the human ventral fetal forebrain where oligodendrogenesis first occurs. Our results indicate evolutionary conservation of the first wave of oligodendrogenesis between mice and humans and describe regulatory mechanisms involved in human OPC specification.

Regulatory variants at 2q33.1 confer schizophrenia risk by modulating distal gene TYW5 expression

Genome-wide association studies have shown that genetic variants at 2q33.1 are strongly associated with schizophrenia. However, potential causal variants in this locus and their roles in schizophrenia remain unknown. Here, we identified two functional variants (rs796364 and rs281759) that disrupt CTCF, RAD21 and FOXP2 binding at 2q33.1. We systematically investigated the regulatory mechanisms of these two variants with serial experiments, including reporter gene assays and electrophoretic mobility shift assay. Intriguingly, these two single nucleotide polymorphisms physically interacted with TYW5 and showed the most significant associations with TYW5 expression in human brain. Consistently, CRISPR-Cas9-mediated genome editing confirmed the regulatory effect of the two single nucleotide polymorphisms on TYW5 expression. Additionally, expression analysis indicated that TYW5 was significantly upregulated in brains of schizophrenia cases compared with controls, suggesting that rs796364 and rs281759 might confer schizophrenia risk by modulating TYW5 expression. We over-expressed TYW5 in mouse neural stem cells and rat primary neurons to mimic its upregulation in schizophrenia and found significant alterations in the proliferation and differentiation of neural stem cells, as well as dendritic spine density following TYW5 overexpression, indicating its important roles in neurodevelopment and spine morphogenesis. Furthermore, we independently confirmed the association between rs796364 and schizophrenia in a Chinese cohort of 8202 subjects. Finally, transcriptome analysis revealed that TYW5 affected schizophrenia-associated pathways. These lines of evidence consistently revealed that rs796364 and rs281759 might contribute to schizophrenia risk by regulating the expression of TYW5, a gene whose expression dysregulation affects two important schizophrenia pathophysiological processes (i.e. neurodevelopment and dendritic spine formation).

The development and evolution of inhibitory neurons in primate cerebrum

Neuroanatomists have long speculated that expanded primate brains contain an increased morphological diversity of inhibitory neurons (INs)1, and recent studies have identified primate-specific neuronal populations at the molecular level2. However, we know little about the developmental mechanisms that specify evolutionarily novel cell types in the brain. Here, we reconstruct gene expression trajectories specifying INs generated throughout the neurogenic period in macaques and mice by analysing the transcriptomes of 250,181 cells. We find that the initial classes of INs generated prenatally are largely conserved among mammals. Nonetheless, we identify two contrasting developmental mechanisms for specifying evolutionarily novel cell types during prenatal development. First, we show that recently identified primate-specific TAC3 striatal INs are specified by a unique transcriptional programme in progenitors followed by induction of a distinct suite of neuropeptides and neurotransmitter receptors in new-born neurons. Second, we find that multiple classes of transcriptionally conserved olfactory bulb (OB)-bound precursors are redirected to expanded primate white matter and striatum. These classes include a novel peristriatal class of striatum laureatum neurons that resemble dopaminergic periglomerular cells of the OB. We propose an evolutionary model in which conserved initial classes of neurons supplying the smaller primate OB are reused in the enlarged striatum and cortex. Together, our results provide a unified developmental taxonomy of initial classes of mammalian INs and reveal multiple developmental mechanisms for neural cell type evolution.

[Web-based gene expression analysis-paving the way to decode healthy and diseased ocular tissue]

BACKGROUND

Gene expression analysis using RNA sequencing has helped to improve the understanding of many diseases. Databases, such as the Gene Expression Omnibus database of the National Center for Biotechnology Information provide RNA sequencing raw data from various diseased tissue types but their analysis requires advanced bioinformatics skills. Therefore, specific ocular databases provide the transcriptional profiles of different ocular tissues and in addition enable intuitive web-based data analysis.

OBJECTIVE

The aim of this narrative review is to provide an overview of ocular transcriptome databases and to compare them with the Human Eye Transcriptome Atlas newly established in Freiburg.

METHODS

PubMed literature search.

RESULTS

A total of nine ocular transcriptome databases focusing on different aspects were identified. The iSyTE and Express platforms specialize in gene expression during lens and retinal development in mice, whereas retina.tigem.it, Eye in a Disk, and Spectacle focus on selected ocular tissues such as the retina. Spectacle, UCSC Cell Browser and Single Cell Portal allow intuitive exploration of single cell RNA sequencing data derived from retinal, choroid, cornea, iris, trabecular meshwork and sclera specimens. The microarray profiles of a variety of healthy ocular tissues are included in the Ocular Tissue Database. The Human Eye Transcriptome Atlas provides the largest collection of different ocular tissue types, contains the highest number of ocular diseases and is characterized by a high level of quality achieved by methodological consistency.

CONCLUSION

Ocular transcriptome databases provide comprehensive and intuitive insights into the transcriptional profiles of a variety of healthy and diseased ocular tissues. Thus, they improve our understanding of the underlying molecular mediators, support hypothesis generation and help in the search for new diagnostic and therapeutic targets for various ocular diseases.

Methods to Improve Molecular Diagnosis in Genomic Cold Cases in Pediatric Neurology

During the last decade, genetic testing has emerged as an important etiological diagnostic tool for Mendelian diseases, including pediatric neurological conditions. A genetic diagnosis has a considerable impact on disease management and treatment; however, many cases remain undiagnosed after applying standard diagnostic sequencing techniques. This review discusses various methods to improve the molecular diagnostic rates in these genomic cold cases. We discuss extended analysis methods to consider, non-Mendelian inheritance models, mosaicism, dual/multiple diagnoses, periodic re-analysis, artificial intelligence tools, and deep phenotyping, in addition to integrating various omics methods to improve variant prioritization. Last, novel genomic technologies, including long-read sequencing, artificial long-read sequencing, and optical genome mapping are discussed. In conclusion, a more comprehensive molecular analysis and a timely re-analysis of unsolved cases are imperative to improve diagnostic rates. In addition, our current understanding of the human genome is still limited due to restrictions in technologies. Novel technologies are now available that improve upon some of these limitations and can capture all human genomic variation more accurately. Last, we recommend a more routine implementation of high molecular weight DNA extraction methods that is coherent with the ability to use and/or optimally benefit from these novel genomic methods.

The UCSC Genome Browser database: 2022 update

The UCSC Genome Browser, https://genome.ucsc.edu, is a graphical viewer for exploring genome annotations. The website provides integrated tools for visualizing, comparing, analyzing, and sharing both publicly available and user-generated genomic datasets. Data highlights this year include a collection of easily accessible public hub assemblies on new organisms, now featuring BLAT alignment and PCR capabilities, and new and updated clinical tracks (gnomAD, DECIPHER, CADD, REVEL). We introduced a new Track Sets feature and enhanced variant displays to aid in the interpretation of clinical data. We also added a tool to rapidly place new SARS-CoV-2 genomes in a global phylogenetic tree enabling researchers to view the context of emerging mutations in our SARS-CoV-2 Genome Browser. Other new software focuses on usability features, including more informative mouseover displays and new fonts.

Generating colorblind-friendly scatter plots for single-cell data

Reduced-dimension or spatial in situ scatter plots are widely employed in bioinformatics papers analyzing single-cell data to present phenomena or cell-conditions of interest in cell groups. When displaying these cell groups, color is frequently the only graphical cue used to differentiate them. However, as the complexity of the information presented in these visualizations increases, the usefulness of color as the only visual cue declines, especially for the sizable readership with color-vision deficiencies (CVDs). In this paper, we present scatterHatch, an R package that creates easily interpretable scatter plots by redundant coding of cell groups using colors as well as patterns. We give examples to demonstrate how the scatterHatch plots are more accessible than simple scatter plots when simulated for various types of CVDs.

Individual human cortical progenitors can produce excitatory and inhibitory neurons

The cerebral cortex is a cellularly complex structure comprising a rich diversity of neuronal and glial cell types. Cortical neurons can be broadly categorized into two classes-excitatory neurons that use the neurotransmitter glutamate, and inhibitory interneurons that use γ-aminobutyric acid (GABA). Previous developmental studies in rodents have led to a prevailing model in which excitatory neurons are born from progenitors located in the cortex, whereas cortical interneurons are born from a separate population of progenitors located outside the developing cortex in the ganglionic eminences^1-5. However, the developmental potential of human cortical progenitors has not been thoroughly explored. Here we show that, in addition to excitatory neurons and glia, human cortical progenitors are also capable of producing GABAergic neurons with the transcriptional characteristics and morphologies of cortical interneurons. By developing a cellular barcoding tool called 'single-cell-RNA-sequencing-compatible tracer for identifying clonal relationships' (STICR), we were able to carry out clonal lineage tracing of 1,912 primary human cortical progenitors from six specimens, and to capture both the transcriptional identities and the clonal relationships of their progeny. A subpopulation of cortically born GABAergic neurons was transcriptionally similar to cortical interneurons born from the caudal ganglionic eminence, and these cells were frequently related to excitatory neurons and glia. Our results show that individual human cortical progenitors can generate both excitatory neurons and cortical interneurons, providing a new framework for understanding the origins of neuronal diversity in the human cortex.

External signals regulate continuous transcriptional states in hematopoietic stem cells

Hematopoietic stem cells (HSCs) must ensure adequate blood cell production following distinct external stressors. A comprehensive understanding of in vivo heterogeneity and specificity of HSC responses to external stimuli is currently lacking. We performed single-cell RNA sequencing (scRNA-Seq) on functionally validated mouse HSCs and LSK (Lin-, c-Kit+, Sca1+) progenitors after in vivo pharmacological perturbation of niche signals interferon, granulocyte colony-stimulating factor (G-CSF), and prostaglandin. We identified six HSC states that are characterized by enrichment but not exclusive expression of marker genes. External signals induced rapid transitions between HSC states but transcriptional response varied both between external stimulants and within the HSC population for a given perturbation. In contrast to LSK progenitors, HSCs were characterized by a greater link between molecular signatures at baseline and in response to external stressors. Chromatin analysis of unperturbed HSCs and LSKs by scATAC-Seq suggested some HSC-specific, cell intrinsic predispositions to niche signals. We compiled a comprehensive resource of HSC- and LSK progenitor-specific chromatin and transcriptional features that represent determinants of signal receptiveness and regenerative potential during stress hematopoiesis.

Preparation of mouse pancreatic tumor for single-cell RNA sequencing and analysis of the data

Preparation of single-cell suspension from primary tumor tissue can provide a valuable resource for functional, genetic, proteomic, and tumor microenvironment studies. Here, we describe an effective protocol for mouse pancreatic tumor dissociation with further processing of tumor suspension for single-cell RNA sequencing analysis of cellular populations. We further provide an outline of the bioinformatics processing of the data and clustering of heterogeneous cellular populations comprising pancreatic tumors using Common Workflow Language (CWL) pipelines within user-friendly Scientific Data Analysis Platform (https://SciDAP.com).

For complete details on the use and execution of this protocol, please refer to Gabitova-Cornell et al. (2020).

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Isolation of single-cell suspension from pancreatic tumor

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Step-by-step guidance to the generation of quality single-cell RNA libraries

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An online informatics pipeline SciDAP for downstream processes

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SciDAP uses open source pipelines to obtain reproducible results

Characterization, isolation, and in vitro culture of leptomeningeal fibroblasts

Meninges, or the membranous coverings of the brain and spinal cord, play host to dozens of morbid pathologies. In this study we provide a method to isolate the leptomeningeal cell layer, identify leptomeninges in histologic slides, and maintain leptomeningeal fibroblasts in in vitro culture. Using an array of transcriptomic, histological, and cytometric analyses, we identified ICAM1 and SLC38A2 as two novel markers of leptomeningeal cells in vivo and in vitro. Our results confirm the fibroblastoid nature of leptomeningeal cells and their ability to form a sheet-like layer that covers the brain and spine parenchyma. These findings will enable researchers in central nervous system barriers to describe leptomeningeal cell functions in health and disease.

DAPL1 is a novel regulator of testosterone production in Leydig cells of mouse testis

Leydig cells in the testes produce testosterone in the presence of gonadotropins. Therefore, male testosterone levels must oscillate within a healthy spectrum, given that elevated testosterone levels augment the risk of cardiovascular disorders. We observed that the expression of death-associated protein-like 1 (DAPL1), which is involved in the early stages of epithelial differentiation and apoptosis, is considerably higher in the testes of sexually mature mice than in other tissues. Accordingly, Dapl1-null mice were constructed to evaluate this variation. Notably, in these mice, the testicular levels of steroidogenic acute regulatory protein (StAR) and serum testosterone levels were significantly elevated on postnatal day 49. The findings were confirmed in vitro using I-10 mouse testis-derived tumor cells. The in vivo and in vitro data revealed the DAPL1-regulated the expression of StAR involving altered transcription of critical proteins in the protein kinase A and CREB/CREM pathways in Leydig cells. The collective findings implicate DAPL1 as an important factor for steroidogenesis regulation, and DAPL1 deregulation may be related to high endogenous levels of testosterone.

Activity-dependent modulation of synapse-regulating genes in astrocytes

Astrocytes regulate the formation and function of neuronal synapses via multiple signals; however, what controls regional and temporal expression of these signals during development is unknown. We determined the expression profile of astrocyte synapse-regulating genes in the developing mouse visual cortex, identifying astrocyte signals that show differential temporal and layer-enriched expression. These patterns are not intrinsic to astrocytes, but regulated by visually evoked neuronal activity, as they are absent in mice lacking glutamate release from thalamocortical terminals. Consequently, synapses remain immature. Expression of synapse-regulating genes and synaptic development is also altered when astrocyte signaling is blunted by diminishing calcium release from astrocyte stores. Single-nucleus RNA sequencing identified groups of astrocytic genes regulated by neuronal and astrocyte activity, and a cassette of genes that show layer-specific enrichment. Thus, the development of cortical circuits requires coordinated signaling between astrocytes and neurons, highlighting astrocytes as a target to manipulate in neurodevelopmental disorders.

Single-cell analysis of cell fate bifurcation in the chordate Ciona

BACKGROUND

Inductive signaling interactions between different cell types are a major mechanism for the further diversification of embryonic cell fates. Most blastomeres in the model chordate Ciona robusta become restricted to a single predominant fate between the 64-cell and mid-gastrula stages. The deeply stereotyped and well-characterized Ciona embryonic cell lineages allow the transcriptomic analysis of newly established cell types very early in their divergence from sibling cell states without the pseudotime inference needed in the analysis of less synchronized cell populations. This is the first ascidian study to use droplet scRNAseq with large numbers of analyzed cells as early as the 64-cell stage when major lineages such as primary notochord first become fate restricted.

RESULTS AND CONCLUSIONS

We identify 59 distinct cell states, including new subregions of the b-line neural lineage and the early induction of the tail tip epidermis. We find that 34 of these cell states are directly or indirectly dependent on MAPK-mediated signaling critical to early Ciona patterning. Most of the MAPK-dependent bifurcations are canalized with the signal-induced cell fate lost upon MAPK inhibition, but the posterior endoderm is unique in being transformed into a novel state expressing some but not all markers of both endoderm and muscle. Divergent gene expression between newly bifurcated sibling cell types is dominated by upregulation in the induced cell type. The Ets family transcription factor Elk1/3/4 is uniquely upregulated in nearly all the putatively direct inductions. Elk1/3/4 upregulation together with Ets transcription factor binding site enrichment analysis enables inferences about which bifurcations are directly versus indirectly controlled by MAPK signaling. We examine notochord induction in detail and find that the transition between a Zic/Ets-mediated regulatory state and a Brachyury/FoxA-mediated regulatory state is unexpectedly late. This supports a "broad-hourglass" model of cell fate specification in which many early tissue-specific genes are induced in parallel to key tissue-specific transcriptional regulators via the same set of transcriptional inputs.

Mammary cell gene expression atlas links epithelial cell remodeling events to breast carcinogenesis

The female mammary epithelium undergoes reorganization during development, pregnancy, and menopause, linking higher risk with breast cancer development. To characterize these periods of complex remodeling, here we report integrated 50 K mouse and 24 K human mammary epithelial cell atlases obtained by single-cell RNA sequencing, which covers most lifetime stages. Our results indicate a putative trajectory that originates from embryonic mammary stem cells which differentiates into three epithelial lineages (basal, luminal hormone-sensing, and luminal alveolar), presumably arising from unipotent progenitors in postnatal glands. The lineage-specific genes infer cells of origin of breast cancer using The Cancer Genome Atlas data and single-cell RNA sequencing of human breast cancer, as well as the association of gland reorganization to different breast cancer subtypes. This comprehensive mammary cell gene expression atlas ( https://mouse-mammary-epithelium-integrated.cells.ucsc.edu ) presents insights into the impact of the internal and external stimuli on the mammary epithelium at an advanced resolution.