Div-Seq: Single-nucleus RNA-Seq reveals dynamics of rare adult newborn neurons

scIMC: a platform for benchmarking comparison and visualization analysis of scRNA-seq data imputation methods

With the advent of single-cell RNA sequencing (scRNA-seq), one major challenging is the so-called 'dropout' events that distort gene expression and remarkably influence downstream analysis in single-cell transcriptome. To address this issue, much effort has been done and several scRNA-seq imputation methods were developed with two categories: model-based and deep learning-based. However, comprehensively and systematically comparing existing methods are still lacking. In this work, we use six simulated and two real scRNA-seq datasets to comprehensively evaluate and compare a total of 12 available imputation methods from the following four aspects: (i) gene expression recovering, (ii) cell clustering, (iii) gene differential expression, and (iv) cellular trajectory reconstruction. We demonstrate that deep learning-based approaches generally exhibit better overall performance than model-based approaches under major benchmarking comparison, indicating the power of deep learning for imputation. Importantly, we built scIMC (single-cell Imputation Methods Comparison platform), the first online platform that integrates all available state-of-the-art imputation methods for benchmarking comparison and visualization analysis, which is expected to be a convenient and useful tool for researchers of interest. It is now freely accessible via https://server.wei-group.net/scIMC/.

Identification of Ion Channel-Related Genes and miRNA-mRNA Networks in Mesial Temporal Lobe Epilepsy

Objective: It aimed to construct the miRNA-mRNA regulatory network related to ion channel genes in mesial temporal lobe epilepsy (mTLE), and further identify the vital node in the network.

Methods: Firstly, we identified ion channel-related differentially expressed genes (DEGs) in mTLE using the IUPHAR/BPS Guide to Pharmacology (GTP) database, neXtProt database, GeneCards database, and the high-throughput sequencing dataset. Then the STRING online database was used to construct a protein-protein interaction (PPI) network of DEGs, and the hub module in the PPI network was identified using the cytoHubba plug-in of Cytoscape software. In addition, the Single Cell Portal database was used to distinguish genes expression in different cell types. Based on the TarBase database, EpimiRBase database and the high-throughput sequencing dataset GSE99455, miRNA-mRNA regulatory network was constructed from selected miRNAs and their corresponding target genes from the identified DEGs. Finally, the rats were selected to construct chronic li-pilocarpine epilepsy model for the next stage experimental verification, and the miR-27a-3p mimic was used to regulate the miRNA expression level in PC12 cells. The relative expression of miR-27a-3p and its targeting mRNAs were determined by RT-qPCR.

Results: 80 mTLE ion channel-related DEGs had been screened. The functional enrichment analysis results of these genes were highly enriched in voltage-gated channel activation and ion transport across membranes. In addition, the hub module, consisting of the Top20 genes in the protein-protein interaction (PPI) network, was identified, which was mainly enriched in excitatory neurons in the CA3 region of the hippocampus. Besides, 14 miRNAs targeting hub module genes were screened, especially the miR-27a-3p deserving particular attention. miR-27a-3p was capable of regulating multiple mTLE ion channel-related DEGs. Moreover, in Li–pilocarpine-induced epilepsy models, the expression level of miR-27a-3p was increased and the mRNAs expression level of KCNB1, SCN1B and KCNQ2 was decreased significantly. The mRNAs expression level of KCNB1 and KCNQ2 was decreased significantly following PC12 cells transfection with miR-27a-3p mimics.

Conclusion: The hub ion channel-related DEGs in mTLE and the miRNA-mRNA regulatory networks had been identified. Moreover, the network of miR-27a-3p regulating ion channel genes will be of great value in mTLE.

New insights into Human Hematopoietic Stem and Progenitor Cells via Single-Cell Omics

Residing at the apex of the hematopoietic hierarchy, hematopoietic stem and progenitor cells (HSPCs) give rise to all mature blood cells. In the last decade, significant progress has been made in single-cell RNA sequencing as well as multi-omics technologies that have facilitated elucidation of the heterogeneity of previously defined human HSPCs. From the embryonic stage through the adult stage to aging, single-cell studies have enabled us to trace the origins of hematopoietic stem cells (HSCs), demonstrating different hematopoietic differentiation during development, as well as identifying novel cell populations. In both hematological benign diseases and malignancies, single-cell omics technologies have begun to reveal tissue heterogeneity and have permitted mapping of microenvironmental ecosystems and tracking of cell subclones, thereby greatly broadening our understanding of disease development. Furthermore, advances have also been made in elucidating the molecular mechanisms for relapse and identifying therapeutic targets of hematological disorders and other non-hematological diseases. Extensive exploration of hematopoiesis at the single-cell level may thus have great potential for broad clinical applications of HSPCs, as well as disease prognosis.

Fine-mapping of Parkinson's disease susceptibility loci identifies putative causal variants

Recent genome-wide association studies have identified 78 loci associated with Parkinson's disease susceptibility but the underlying mechanisms remain largely unclear. To identify likely causal variants for disease risk, we fine-mapped these Parkinson's-associated loci using four different fine-mapping methods. We then integrated multi-assay cell type-specific epigenomic profiles to pinpoint the likely mechanism of action of each variant, allowing us to identify Consensus single nucleotide polymorphism (SNPs) that disrupt LRRK2 and FCGR2A regulatory elements in microglia, an MBNL2 enhancer in oligodendrocytes, and a DYRK1A enhancer in neurons. This genome-wide functional fine-mapping investigation of Parkinson's disease substantially advances our understanding of the causal mechanisms underlying this complex disease while avoiding focus on spurious, non-causal mechanisms. Together, these results provide a robust, comprehensive list of the likely causal variants, genes and cell-types underlying Parkinson's disease risk as demonstrated by consistently greater enrichment of our fine-mapped SNPs relative to lead GWAS SNPs across independent functional impact annotations. In addition, our approach prioritized an average of 3/85 variants per locus as putatively causal, making downstream experimental studies both more tractable and more likely to yield disease-relevant, actionable results. Large-scale studies comparing individuals with Parkinson's disease to age-matched controls have identified many regions of the genome associated with the disease. However, there is widespread correlation between different parts of the genome, making it difficult to tell which genetic variants cause Parkinson's and which are simply co-inherited with causal variants. We therefore applied a suite of statistical models to identify the most likely causal genetic variants (i.e. fine-mapping). We then linked these genetic variants with epigenomic and gene expression signatures across a wide variety of tissues and cell types to identify how these variants cause disease. Therefore, this study provides a comprehensive and robust list of cellular and molecular mechanisms that may serve as targets in the development of more effective Parkinson's therapeutics.

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.

Suv39h1 regulates memory stability by inhibiting the expression of Shank1 in hippocampal newborn neurons

Adult newborn neurons are involved in memory encoding and extinction, but the neural mechanism is unclear. We found the adult newborn neurons at 4 weeks are recruited by learning and subjected to epigenetic regulations, consequently reducing their ability to be re-recruited later. After removal of the epigenetic blockage, Suv39h1 KO mice showed an increased recruiting number of aged newborn neurons and enhanced flexibility in learning tasks. Besides NRXN1, we found SHANK1, the synaptic scaffold protein, is one of the major targets of Suv39h1, regulating memory stability. Expression of Shank1 is transiently engaged to enhance synaptogenesis during learning and is strongly suppressed by Suv39h1 from 5 hours after learning. Exogenously overexpression of Shank1 in dentate gyrus increased the density of mushroom spines and decreased the persistency of old memories. Our study indicated the activity-regulated epigenetic modification in newly matured newborn neurons in hippocampus insulates temporally distinct experiences and stabilizes old memories.

Comparative analysis of antibody- and lipid-based multiplexing methods for single-cell RNA-seq

BACKGROUND

Multiplexing of samples in single-cell RNA-seq studies allows a significant reduction of the experimental costs, straightforward identification of doublets, increased cell throughput, and reduction of sample-specific batch effects. Recently published multiplexing techniques using oligo-conjugated antibodies or -lipids allow barcoding sample-specific cells, a process called "hashing."

RESULTS

Here, we compare the hashing performance of TotalSeq-A and -C antibodies, custom synthesized lipids and MULTI-seq lipid hashes in four cell lines, both for single-cell RNA-seq and single-nucleus RNA-seq. We also compare TotalSeq-B antibodies with CellPlex reagents (10x Genomics) on human PBMCs and TotalSeq-B with different lipids on primary mouse tissues. Hashing efficiency was evaluated using the intrinsic genetic variation of the cell lines and mouse strains. Antibody hashing was further evaluated on clinical samples using PBMCs from healthy and SARS-CoV-2 infected patients, where we demonstrate a more affordable approach for large single-cell sequencing clinical studies, while simultaneously reducing batch effects.

CONCLUSIONS

Benchmarking of different hashing strategies and computational pipelines indicates that correct demultiplexing can be achieved with both lipid- and antibody-hashed human cells and nuclei, with MULTISeqDemux as the preferred demultiplexing function and antibody-based hashing as the most efficient protocol on cells. On nuclei datasets, lipid hashing delivers the best results. Lipid hashing also outperforms antibodies on cells isolated from mouse brain. However, antibodies demonstrate better results on tissues like spleen or lung.

SM-Omics is an automated platform for high-throughput spatial multi-omics

The spatial organization of cells and molecules plays a key role in tissue function in homeostasis and disease. Spatial transcriptomics has recently emerged as a key technique to capture and positionally barcode RNAs directly in tissues. Here, we advance the application of spatial transcriptomics at scale, by presenting Spatial Multi-Omics (SM-Omics) as a fully automated, high-throughput all-sequencing based platform for combined and spatially resolved transcriptomics and antibody-based protein measurements. SM-Omics uses DNA-barcoded antibodies, immunofluorescence or a combination thereof, to scale and combine spatial transcriptomics and spatial antibody-based multiplex protein detection. SM-Omics allows processing of up to 64 in situ spatial reactions or up to 96 sequencing-ready libraries, of high complexity, in a ~2 days process. We demonstrate SM-Omics in the mouse brain, spleen and colorectal cancer model, showing its broad utility as a high-throughput platform for spatial multi-omics.

Spatial proteogenomics reveals distinct and evolutionarily conserved hepatic macrophage niches

The liver is the largest solid organ in the body, yet it remains incompletely characterized. Here we present a spatial proteogenomic atlas of the healthy and obese human and murine liver combining single-cell CITE-seq, single-nuclei sequencing, spatial transcriptomics, and spatial proteomics. By integrating these multi-omic datasets, we provide validated strategies to reliably discriminate and localize all hepatic cells, including a population of lipid-associated macrophages (LAMs) at the bile ducts. We then align this atlas across seven species, revealing the conserved program of bona fide Kupffer cells and LAMs. We also uncover the respective spatially resolved cellular niches of these macrophages and the microenvironmental circuits driving their unique transcriptomic identities. We demonstrate that LAMs are induced by local lipid exposure, leading to their induction in steatotic regions of the murine and human liver, while Kupffer cell development crucially depends on their cross-talk with hepatic stellate cells via the evolutionarily conserved ALK1-BMP9/10 axis.

Olig2-astrocytes express neutral amino acid transporter SLC7A10 (Asc-1) in the adult brain

We have reported that the transcription factor Olig2 labels a subpopulation of astrocytes (Olig2-astrocytes), which show distribution patterns different from those of GFAP-expressing astrocytes (GFAP-astrocytes) in the adult brain. Here, to uncover the specific functions of Olig2-astrocytes, we first analyzed public single-cell RNA-seq databases of adult mouse brains. Unbiased classification of gene expression profiles and subsequent gene ontology analyses revealed that the majority of Olig2-astrocytes belonged to an astrocytic cluster that is enriched for transporter-related genes. SLC7A10 (also known as ASC-1) was one of the representative neutral amino acid transporter genes in the cluster. To complement the in silico data analyses, we differentially isolated Olig2- and GFAP-astrocytes from the same frozen section of the lateral globus pallidus using laser microdissection and compared their gene expression by quantitative reverse transcription PCR. We confirmed that Olig2 and GFAP mRNAs were preferentially expressed in the Olig2- and GFAP-astrocytes, respectively, indicating that the laser microdissection method yielded minimal cross-contamination between two types of cells. The Olig2-astrocytes expressed significantly higher levels of SLC7A10 mRNA than the GFAP-astrocytes, corroborating the in silico data. We next localized SLC7A10 protein by immunohistochemistry in the lateral globus pallidus, which was also genetically labeled for Olig2. SLC7A10 co-localized with Olig2-genetic labeling, especially on the fine processes of Olig2-astrocytes. These results are consistent with the recent discovery that SLC7A10 is expressed not only in neurons but also in a subset of astrocytes. Taken together, our findings suggest that SLC7A10 exerts specific functions in Olig2-astrocytes of the adult brain.

Immunohistochemical evidence for adult human neurogenesis in health and disease

Postnatal and adult neurogenesis in the subventricular zone and subgranular zone of animals such as rodents and non-human primates has been observed with many different technical approaches. Since most techniques used in animals cannot be used in humans, the majority of human neurogenesis studies rely on postmortem immunohistochemistry. This technique is difficult in human tissue, due to poor and variable preservation of antigens and samples. Nevertheless, a survey of the literature reveals that most published studies provide evidence for childhood and adult neurogenesis in the human brain stem cell niches. There are some conflicting results even when assessing the same markers and when using the same antibodies. Focusing on immunohistochemical studies on post-mortem human sections, we discuss the relative robustness of the literature on adult neurogenesis. We also discuss the response of the subventricular and subgranular zones to human disease, showing that the two niches can respond differently and that the stage of disease impacts neurogenesis levels. Thus, we highlight strong evidence for adult human neurogenesis, discuss other work that did not find it, describe obstacles in analysis, and offer other approaches to evaluate the neurogenic potential of the subventricular and subgranular zones of Homo sapiens. This article is categorized under: Neurological Diseases > Stem Cells and Development Reproductive System Diseases > Stem Cells and Development.

The immune niche of the liver

The liver is an essential organ that is critical for the removal of toxins, the production of proteins, and the maintenance of metabolic homeostasis. Behind each liver functional unit, termed lobules, hides a heterogeneous, complex, and well-orchestrated system. Despite parenchymal cells being most commonly associated with the liver's primary functionality, it has become clear that it is the immune niche of the liver that plays a central role in maintaining both local and systemic homeostasis by propagating hepatic inflammation and orchestrating its resolution. As such, the immunological processes that are at play in healthy and diseased livers are being investigated thoroughly in order to understand the underpinnings of inflammation and the potential avenues for restoring homeostasis. This review highlights recent advances in our understanding of the immune niche of the liver and provides perspectives for how the implementation of new transcriptomic, multimodal, and spatial technologies can uncover the heterogeneity, plasticity, and location of hepatic immune populations. Findings from these technologies will further our understanding of liver biology and create a new framework for the identification of therapeutic targets.

Single-Cell Analysis Using Machine Learning Techniques and Its Application to Medical Research

In recent years, the diversity of cancer cells in tumor tissues as a result of intratumor heterogeneity has attracted attention. In particular, the development of single-cell analysis technology has made a significant contribution to the field; technologies that are centered on single-cell RNA sequencing (scRNA-seq) have been reported to analyze cancer constituent cells, identify cell groups responsible for therapeutic resistance, and analyze gene signatures of resistant cell groups. However, although single-cell analysis is a powerful tool, various issues have been reported, including batch effects and transcriptional noise due to gene expression variation and mRNA degradation. To overcome these issues, machine learning techniques are currently being introduced for single-cell analysis, and promising results are being reported. In addition, machine learning has also been used in various ways for single-cell analysis, such as single-cell assay of transposase accessible chromatin sequencing (ATAC-seq), chromatin immunoprecipitation sequencing (ChIP-seq) analysis, and multi-omics analysis; thus, it contributes to a deeper understanding of the characteristics of human diseases, especially cancer, and supports clinical applications. In this review, we present a comprehensive introduction to the implementation of machine learning techniques in medical research for single-cell analysis, and discuss their usefulness and future potential.

Single-nucleus transcriptome analysis reveals cell-type-specific molecular signatures across reward circuitry in the human brain

Single-cell gene expression technologies are powerful tools to study cell types in the human brain, but efforts have largely focused on cortical brain regions. We therefore created a single-nucleus RNA-sequencing resource of 70,615 high-quality nuclei to generate a molecular taxonomy of cell types across five human brain regions that serve as key nodes of the human brain reward circuitry: nucleus accumbens, amygdala, subgenual anterior cingulate cortex, hippocampus, and dorsolateral prefrontal cortex. We first identified novel subpopulations of interneurons and medium spiny neurons (MSNs) in the nucleus accumbens and further characterized robust GABAergic inhibitory cell populations in the amygdala. Joint analyses across the 107 reported cell classes revealed cell-type substructure and unique patterns of transcriptomic dynamics. We identified discrete subpopulations of D1- and D2-expressing MSNs in the nucleus accumbens to which we mapped cell-type-specific enrichment for genetic risk associated with both psychiatric disease and addiction.

DNA methylation atlas of the mouse brain at single-cell resolution

Mammalian brain cells show remarkable diversity in gene expression, anatomy and function, yet the regulatory DNA landscape underlying this extensive heterogeneity is poorly understood. Here we carry out a comprehensive assessment of the epigenomes of mouse brain cell types by applying single-nucleus DNA methylation sequencing1,2 to profile 103,982 nuclei (including 95,815 neurons and 8,167 non-neuronal cells) from 45 regions of the mouse cortex, hippocampus, striatum, pallidum and olfactory areas. We identified 161 cell clusters with distinct spatial locations and projection targets. We constructed taxonomies of these epigenetic types, annotated with signature genes, regulatory elements and transcription factors. These features indicate the potential regulatory landscape supporting the assignment of putative cell types and reveal repetitive usage of regulators in excitatory and inhibitory cells for determining subtypes. The DNA methylation landscape of excitatory neurons in the cortex and hippocampus varied continuously along spatial gradients. Using this deep dataset, we constructed an artificial neural network model that precisely predicts single neuron cell-type identity and brain area spatial location. Integration of high-resolution DNA methylomes with single-nucleus chromatin accessibility data3 enabled prediction of high-confidence enhancer-gene interactions for all identified cell types, which were subsequently validated by cell-type-specific chromatin conformation capture experiments4. By combining multi-omic datasets (DNA methylation, chromatin contacts, and open chromatin) from single nuclei and annotating the regulatory genome of hundreds of cell types in the mouse brain, our DNA methylation atlas establishes the epigenetic basis for neuronal diversity and spatial organization throughout the mouse cerebrum.

Joint single-cell measurements of nuclear proteins and RNA in vivo

Identifying gene-regulatory targets of nuclear proteins in tissues is a challenge. Here we describe intranuclear cellular indexing of transcriptomes and epitopes (inCITE-seq), a scalable method that measures multiplexed intranuclear protein levels and the transcriptome in parallel across thousands of nuclei, enabling joint analysis of transcription factor (TF) levels and gene expression in vivo. We apply inCITE-seq to characterize cell state-related changes upon pharmacological induction of neuronal activity in the mouse brain. Modeling gene expression as a linear combination of quantitative protein levels revealed genome-wide associations of each TF and recovered known gene targets. TF-associated genes were coexpressed as distinct modules that each reflected positive or negative TF levels, showing that our approach can disentangle relative putative contributions of TFs to gene expression and add interpretability to inferred gene networks. inCITE-seq can illuminate how combinations of nuclear proteins shape gene expression in native tissue contexts, with direct applications to solid or frozen tissues and clinical specimens.

Single-Nucleus RNA-Seq Is Not Suitable for Detection of Microglial Activation Genes in Humans

Single-nucleus RNA sequencing (snRNA-seq) is used as an alternative to single-cell RNA-seq, as it allows transcriptomic profiling of frozen tissue. However, it is unclear whether snRNA-seq is able to detect cellular state in human tissue. Indeed, snRNA-seq analyses of human brain samples have failed to detect a consistent microglial activation signature in Alzheimer’s disease. Our comparison of microglia from single cells and single nuclei of four human subjects reveals that, although most genes show similar relative abundances in cells and nuclei, a small population of genes (∼1%) is depleted in nuclei compared to whole cells. This population is enriched for genes previously implicated in microglial activation, including APOE, CST3, SPP1, and CD74, comprising 18% of previously identified microglial-disease-associated genes. Given the low sensitivity of snRNA-seq to detect many activation genes, we conclude that snRNA-seq is not suited for detecting cellular activation in microglia in human disease.

•

A small set of genes is depleted in microglial nuclei relative to single cells

•

This set is enriched for microglial activation genes, including APOE and SPP1

•

This depletion is confirmed in publicly available datasets

•

Single-nucleus sequencing is not suited for the detection of human microglial activation

GDF11 expressed in the adult brain negatively regulates hippocampal neurogenesis

Growth differentiation factor 11 (GDF11) is a transforming factor-β superfamily member that functions as a negative regulator of neurogenesis during embryonic development. However, when recombinant GDF11 (rGDF11) is administered systemically in aged mice, it promotes neurogenesis, the opposite of its role during development. The goal of the present study was to reconcile this apparent discrepancy by performing the first detailed investigation into the expression of endogenous GDF11 in the adult brain and its effects on neurogenesis. Using quantitative histological analysis, we observed that Gdf11 is most highly expressed in adult neurogenic niches and non-neurogenic regions within the hippocampus, choroid plexus, thalamus, habenula, and cerebellum. To investigate the role of endogenous GDF11 during adult hippocampal neurogenesis, we generated a tamoxifen inducible mouse that allowed us to reduce GDF11 levels. Depletion of Gdf11 during adulthood increased proliferation of neural progenitors and decreased the number of newborn neurons in the hippocampus, suggesting that endogenous GDF11 remains a negative regulator of hippocampal neurogenesis in adult mice. These findings further support the idea that circulating systemic GDF11 and endogenously expressed GDF11 in the adult brain have different target cells or mechanisms of action. Our data describe a role for GDF11-dependent signaling in adult neurogenesis that has implications for how GDF11 may be used to treat CNS disease.

Single-cell RNA sequencing in Drosophila: Technologies and applications

Single-cell RNA sequencing (scRNA-seq) has emerged as a powerful tool for investigating cell states and functions at the single-cell level. It has greatly revolutionized transcriptomic studies in many life science research fields, such as neurobiology, immunology, and developmental biology. With the fast development of both experimental platforms and bioinformatics approaches over the past decade, scRNA-seq is becoming economically feasible and experimentally practical for many biomedical laboratories. Drosophila has served as an excellent model organism for dissecting cellular and molecular mechanisms that underlie tissue development, adult cell function, disease, and aging. The recent application of scRNA-seq methods to Drosophila tissues has led to a number of exciting discoveries. In this review, I will provide a summary of recent scRNA-seq studies in Drosophila, focusing on technical approaches and biological applications. I will also discuss current challenges and future opportunities of making new discoveries using scRNA-seq in Drosophila. This article is categorized under:   Technologies > Analysis of the Transcriptome.

Single-nucleus transcriptomic landscape of primate hippocampal aging

The hippocampus plays a crucial role in learning and memory, and its progressive deterioration with age is functionally linked to a variety of human neurodegenerative diseases. Yet a systematic profiling of the aging effects on various hippocampal cell types in primates is still missing. Here, we reported a variety of new aging-associated phenotypic changes of the primate hippocampus. These include, in particular, increased DNA damage and heterochromatin erosion with time, alongside loss of proteostasis and elevated inflammation. To understand their cellular and molecular causes, we established the first single-nucleus transcriptomic atlas of primate hippocampal aging. Among the 12 identified cell types, neural transiently amplifying progenitor cell (TAPC) and microglia were most affected by aging. In-depth dissection of gene-expression dynamics revealed impaired TAPC division and compromised neuronal function along the neurogenesis trajectory; additionally elevated pro-inflammatory responses in the aged microglia and oligodendrocyte, as well as dysregulated coagulation pathways in the aged endothelial cells may contribute to a hostile microenvironment for neurogenesis. This rich resource for understanding primate hippocampal aging may provide potential diagnostic biomarkers and therapeutic interventions against age-related neurodegenerative diseases.

An early proinflammatory transcriptional response to tau pathology is age-specific and foreshadows reduced tau burden

Age is one of the strongest risk factors for the development of neurodegenerative diseases, the majority of which involve misfolded protein aggregates in the brain. These protein aggregates are thought to drive pathology and are attractive targets for the development of new therapies. However, it is unclear how age influences the onset of pathology and the accompanying molecular response. To address this knowledge gap, we used a model of seeded tau pathology to profile the transcriptomic changes in 3 and 12 month old mice in response to developing tau hyperphosphorylation and aggregation. First, we found the burden of hyperphosphorylated tau pathology in mice injected at 12 months of age was moderately reduced compared to animals injected at 3 months. On a molecular level, we found an inflammation-related subset of genes, including C3 and the disease-associated microglia genes Ctsd, Cst7, and Clec7a, were more expressed early in disease in 12 but not 3 month old mice. These findings provide evidence of an early, age-specific response to tau pathology, which could serve as a marker for the severity of downstream pathology.

Using single-nucleus RNA-sequencing to interrogate transcriptomic profiles of archived human pancreatic islets

Background

Human pancreatic islets are a central focus of research in metabolic studies. Transcriptomics is frequently used to interrogate alterations in cultured human islet cells using single-cell RNA-sequencing (scRNA-seq). We introduce single-nucleus RNA-sequencing (snRNA-seq) as an alternative approach for investigating transplanted human islets.

Methods

The Nuclei EZ protocol was used to obtain nuclear preparations from fresh and frozen human islet cells. Such preparations were first used to generate snRNA-seq datasets and compared to scRNA-seq output obtained from cells from the same donor. Finally, we employed snRNA-seq to obtain the transcriptomic profile of archived human islets engrafted in immunodeficient animals.

Results

We observed virtually complete concordance in identifying cell types and gene proportions as well as a strong association of global and islet cell type gene signatures between scRNA-seq and snRNA-seq applied to fresh and frozen cultured or transplanted human islet samples.

Conclusions

We propose snRNA-seq as a reliable strategy to probe transcriptomic profiles of freshly harvested or frozen sources of transplanted human islet cells especially when scRNA-seq is not ideal.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13073-021-00941-8.

NovoSpaRc: flexible spatial reconstruction of single-cell gene expression with optimal transport

Single-cell RNA-sequencing (scRNA-seq) technologies have revolutionized modern biomedical sciences. A fundamental challenge is to incorporate spatial information to study tissue organization and spatial gene expression patterns. Here, we describe a detailed protocol for using novoSpaRc, a computational framework that probabilistically assigns cells to tissue locations. At the core of this framework lies a structural correspondence hypothesis, that cells in physical proximity share similar gene expression profiles. Given scRNA-seq data, novoSpaRc spatially reconstructs tissues based on this hypothesis, and optionally, by including a reference atlas of marker genes to improve reconstruction. We describe the novoSpaRc algorithm, and its implementation in an open-source Python package ( https://pypi.org/project/novosparc ). NovoSpaRc maps a scRNA-seq dataset of 10,000 cells onto 1,000 locations in <5 min. We describe results obtained using novoSpaRc to reconstruct the mouse organ of Corti de novo based on the structural correspondence assumption and human osteosarcoma cultured cells based on marker gene information, and provide a step-by-step guide to Drosophila embryo reconstruction in the Procedure to demonstrate how these two strategies can be combined.

Plasticity of the Injured Spinal Cord

Complete spinal cord injury (SCI) leads to permanent motor, sensitive and sensory deficits. In humans, there is currently no therapy to promote recovery and the only available treatments include surgical intervention to prevent further damage and symptomatic relief of pain and infections in the acute and chronic phases, respectively. Basically, the spinal cord is classically viewed as a nonregenerative tissue with limited plasticity. Thereby the establishment of the “glial” scar which appears within the SCI is mainly described as a hermetic barrier for axon regeneration. However, recent discoveries have shed new light on the intrinsic functional plasticity and endogenous recovery potential of the spinal cord. In this review, we will address the different aspects that the spinal cord plasticity can take on. Indeed, different experimental paradigms have demonstrated that axonal regrowth can occur even after complete SCI. Moreover, recent articles have demonstrated too that the “glial” scar is in fact composed of several cellular populations and that each of them exerts specific roles after SCI. These recent discoveries underline the underestimation of the plasticity of the spinal cord at cellular and molecular levels. Finally, we will address the modulation of this endogenous spinal cord plasticity and the perspectives of future therapeutic opportunities which can be offered by modulating the injured spinal cord microenvironment.

Refining the Molecular Framework for Pancreatic Cancer with Single-cell and Spatial Technologies

Pancreatic ductal adenocarcinoma (PDAC) is a treatment-refractory malignancy in urgent need of a molecular framework for guiding therapeutic strategies. Bulk transcriptomic efforts over the past decade have yielded two broad consensus subtypes: classical pancreatic/epithelial versus basal-like/squamous/quasi-mesenchymal. Although this binary classification enables prognostic stratification, it does not currently inform the administration of treatments uniquely sensitive to either subtype. Furthermore, bulk mRNA studies are challenged by distinguishing contributions from the neoplastic compartment versus other cell types in the microenvironment, which is accentuated in PDAC given that neoplastic cellularity can be low. The application of single-cell transcriptomics to pancreatic tumors has generally lagged behind other cancer types due in part to the difficulty of extracting high-quality RNA from enzymatically degradative tissue, but emerging studies have and will continue to shed light on intratumoral heterogeneity, malignant-stromal interactions, and subtle transcriptional programs previously obscured at the bulk level. In conjunction with insights provided by single-cell/nucleus dissociative techniques, spatially resolved technologies should also facilitate the contextualization of gene programs and inferred cell-cell interactions within the tumor architecture. Finally, given that patients often receive neoadjuvant chemotherapy and/or chemoradiotherapy even in resectable disease, deciphering the gene programs enriched in or induced by cytotoxic therapy will be crucial for developing insights into complementary treatments aimed at eradicating residual cancer cells. Taken together, single-cell and spatial technologies provide an unprecedented opportunity to refine the foundations laid by prior bulk molecular studies and significantly augment precision oncology efforts in pancreatic cancer.

Single-nucleus RNA-seq2 reveals functional crosstalk between liver zonation and ploidy

Single-cell RNA-seq reveals the role of pathogenic cell populations in development and progression of chronic diseases. In order to expand our knowledge on cellular heterogeneity, we have developed a single-nucleus RNA-seq2 method tailored for the comprehensive analysis of the nuclear transcriptome from frozen tissues, allowing the dissection of all cell types present in the liver, regardless of cell size or cellular fragility. We use this approach to characterize the transcriptional profile of individual hepatocytes with different levels of ploidy, and have discovered that ploidy states are associated with different metabolic potential, and gene expression in tetraploid mononucleated hepatocytes is conditioned by their position within the hepatic lobule. Our work reveals a remarkable crosstalk between gene dosage and spatial distribution of hepatocytes.

Highly selective brain-to-gut communication via genetically defined vagus neurons

The vagus nerve innervates many organs, and most, if not all, of its motor fibers are cholinergic. However, no one knows its organizing principles-whether or not there are dedicated neurons with restricted targets that act as "labeled lines" to perform certain functions, including two opposing ones (gastric contraction versus relaxation). By performing unbiased transcriptional profiling of DMV cholinergic neurons, we discovered seven molecularly distinct subtypes of motor neurons. Then, by using subtype-specific Cre driver mice, we show that two of these subtypes exclusively innervate the glandular domain of the stomach where, remarkably, they contact different enteric neurons releasing functionally opposing neurotransmitters (acetylcholine versus nitric oxide). Thus, the vagus motor nerve communicates via genetically defined labeled lines to control functionally unique enteric neurons within discrete subregions of the gastrointestinal tract. This discovery reveals that the parasympathetic nervous system utilizes a striking division of labor to control autonomic function.

Resolving cellular and molecular diversity along the hippocampal anterior-to-posterior axis in humans

The hippocampus supports many facets of cognition, including learning, memory, and emotional processing. Anatomically, the hippocampus runs along a longitudinal axis, posterior to anterior in primates. The structure, function, and connectivity of the hippocampus vary along this axis. In human hippocampus, longitudinal functional heterogeneity remains an active area of investigation, and structural heterogeneity has not been described. To understand the cellular and molecular diversity along the hippocampal long axis in human brain and define molecular signatures corresponding to functional domains, we performed single-nuclei RNA sequencing on surgically resected human anterior and posterior hippocampus from epilepsy patients, identifying differentially expressed genes at cellular resolution. We further identify axis- and cell-type-specific gene expression signatures that differentially intersect with human genetic signals, identifying cell-type-specific genes in the posterior hippocampus for cognitive function and the anterior hippocampus for mood and affect. These data are accessible as a public resource through an interactive website.

Generating and Using Transcriptomically Based Retinal Cell Atlases

It has been known for over a century that the basic organization of the retina is conserved across vertebrates. It has been equally clear that retinal cells can be classified into numerous types, but only recently have methods been devised to explore this diversity in unbiased, scalable, and comprehensive ways. Advances in high-throughput single-cell RNA-sequencing (scRNA-seq) have played a pivotal role in this effort. In this article, we outline the experimental and computational components of scRNA-seq and review studies that have used them to generate retinal atlases of cell types in several vertebrate species. These atlases have enabled studies of retinal development, responses of retinal cells to injury, expression patterns of genes implicated in retinal disease, and the evolution of cell types. Recently, the inquiry has expanded to include the entire eye and visual centers in the brain. These studies have enhanced our understanding of retinal function and dysfunction and provided tools and insights for exploring neural diversity throughout the brain. Expected final online publication date for the Annual Review of Vision Science, Volume 7 is September 2021. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.

Gene expression variation in Arabidopsis embryos at single-nucleus resolution

Soon after fertilization of egg and sperm, plant genomes become transcriptionally activated and drive a series of coordinated cell divisions to form the basic body plan during embryogenesis. Early embryonic cells rapidly diversify from each other, and investigation of the corresponding gene expression dynamics can help elucidate underlying cellular differentiation programs. However, current plant embryonic transcriptome datasets either lack cell-specific information or have RNA contamination from surrounding non-embryonic tissues. We have coupled fluorescence-activated nuclei sorting together with single-nucleus mRNA-sequencing to construct a gene expression atlas of Arabidopsis thaliana early embryos at single-cell resolution. In addition to characterizing cell-specific transcriptomes, we found evidence that distinct epigenetic and transcriptional regulatory mechanisms operate across emerging embryonic cell types. These datasets and analyses, as well as the approach we devised, are expected to facilitate the discovery of molecular mechanisms underlying pattern formation in plant embryos. This article has an associated 'The people behind the papers' interview.

Elucidating the cellular dynamics of the brain with single-cell RNA sequencing

Single-cell RNA-sequencing (scRNA-seq) has emerged in recent years as a breakthrough technology to understand RNA metabolism at cellular resolution. In addition to allowing new cell types and states to be identified, scRNA-seq can permit cell-type specific differential gene expression changes, pre-mRNA processing events, gene regulatory networks and single-cell developmental trajectories to be uncovered. More recently, a new wave of multi-omic adaptations and complementary spatial transcriptomics workflows have been developed that facilitate the collection of even more holistic information from individual cells. These developments have unprecedented potential to provide penetrating new insights into the basic neural cell dynamics and molecular mechanisms relevant to the nervous system in both health and disease. In this review we discuss this maturation of single-cell RNA-sequencing over the past decade, and review the different adaptations of the technology that can now be applied both at different scales and for different purposes. We conclude by highlighting how these methods have already led to many exciting discoveries across neuroscience that have furthered our cellular understanding of the neurological disease.

Neurogenesis after Spinal Cord Injury: State of the Art

Neurogenesis in the adult state is the process of new neuron formation. This relatively infrequent phenomenon comprises four stages: cell proliferation, cell migration, differentiation, and the integration of these cells into an existing circuit. Recent reports suggest that neurogenesis can be found in different regions of the Central Nervous System (CNS), including the spinal cord (SC). This process can be observed in physiological settings; however, it is more evident in pathological conditions. After spinal cord injury (SCI), the activation of microglial cells and certain cytokines have shown to exert different modulatory effects depending on the presence of inflammation and on the specific region of the injury site. In these conditions, microglial cells and cytokines are considered to play an important role in the regulation of neurogenesis after SCI. The purpose of this article is to present an overview on neural progenitor cells and neurogenic and non-neurogenic zones as well as the cellular and molecular regulation of neurogenesis. Additionally, we will briefly describe the recent advances in the knowledge of neurogenesis after SCI.

Cholinergic Modulation of Dendritic Signaling in Hippocampal GABAergic Inhibitory Interneurons

Dendrites represent the "reception hub" of the neuron as they collect thousands of different inputs and send a coherent response to the cell body. A considerable portion of these signals, especially in vivo, arises from neuromodulatory sources, which affect dendritic computations and cellular activity. In this context, acetylcholine (ACh) exerts a coordinating role of different brain structures, contributing to goal-driven behaviors and sleep-wake cycles. Specifically, cholinergic neurons from the medial septum-diagonal band of Broca complex send numerous projections to glutamatergic principal cells and GABAergic inhibitory neurons in the hippocampus, differentially entraining them during network oscillations. Interneurons display abundant expression of cholinergic receptors and marked responses to stimulation by ACh. Nonetheless, the precise localization of ACh inputs is largely unknown, and evidence for cholinergic modulation of interneuronal dendritic signaling remains elusive. In this article, we review evidence that suggests modulatory effects of ACh on dendritic computations in three hippocampal interneuron subtypes: fast-spiking parvalbumin-positive (PV⁺) cells, somatostatin-expressing (SOM⁺) oriens lacunosum moleculare cells and vasoactive intestinal polypeptide-expressing (VIP⁺) interneuron-selective interneurons. We consider the distribution of cholinergic receptors on these interneurons, including information about their specific somatodendritic location, and discuss how the action of these receptors can modulate dendritic Ca²⁺ signaling and activity of interneurons. The implications of ACh-dependent Ca²⁺ signaling for dendritic plasticity are also discussed. We propose that cholinergic modulation can shape the dendritic integration and plasticity in interneurons in a cell type-specific manner, and the elucidation of these mechanisms will be required to understand the contribution of each cell type to large-scale network activity.

Progress towards a cellularly resolved mouse mesoconnectome is empowered by data fusion and new neuroanatomy techniques

Over the past decade there has been a rapid improvement in techniques for obtaining large-scale cellular level data related to the mouse brain connectome. However, a detailed mapping of cell-type-specific projection patterns is lacking, which would, for instance, allow us to study the role of circuit motifs in cognitive processes. In this work, we review advanced neuroanatomical and data fusion techniques within the context of a proposed Multimodal Connectomic Integration Framework for augmenting the cellularly resolved mouse mesoconnectome. First, we emphasize the importance of registering data modalities to a common reference atlas. We then review a number of novel experimental techniques that can provide data for characterizing cell-types in the mouse brain. Furthermore, we examine a number of data integration strategies, which involve fine-grained cell-type classification, spatial inference of cell densities, latent variable models for the mesoconnectome and multi-modal factorisation. Finally, we discuss a number of use cases which depend on connectome augmentation techniques, such as model simulations of functional connectivity and generating mechanistic hypotheses for animal disease models.

Applications of single-cell sequencing in cancer research: progress and perspectives

Single-cell sequencing, including genomics, transcriptomics, epigenomics, proteomics and metabolomics sequencing, is a powerful tool to decipher the cellular and molecular landscape at a single-cell resolution, unlike bulk sequencing, which provides averaged data. The use of single-cell sequencing in cancer research has revolutionized our understanding of the biological characteristics and dynamics within cancer lesions. In this review, we summarize emerging single-cell sequencing technologies and recent cancer research progress obtained by single-cell sequencing, including information related to the landscapes of malignant cells and immune cells, tumor heterogeneity, circulating tumor cells and the underlying mechanisms of tumor biological behaviors. Overall, the prospects of single-cell sequencing in facilitating diagnosis, targeted therapy and prognostic prediction among a spectrum of tumors are bright. In the near future, advances in single-cell sequencing will undoubtedly improve our understanding of the biological characteristics of tumors and highlight potential precise therapeutic targets for patients.

Sublayer- and cell-type-specific neurodegenerative transcriptional trajectories in hippocampal sclerosis

Hippocampal sclerosis, the major neuropathological hallmark of temporal lobe epilepsy, is characterized by different patterns of neuronal loss. The mechanisms of cell-type-specific vulnerability and their progression and histopathological classification remain controversial. Using single-cell electrophysiology in vivo and immediate-early gene expression, we reveal that superficial CA1 pyramidal neurons are overactive in epileptic rodents. Bulk tissue and single-nucleus expression profiling disclose sublayer-specific transcriptomic signatures and robust microglial pro-inflammatory responses. Transcripts regulating neuronal processes such as voltage channels, synaptic signaling, and cell adhesion are deregulated differently by epilepsy across sublayers, whereas neurodegenerative signatures primarily involve superficial cells. Pseudotime analysis of gene expression in single nuclei and in situ validation reveal separated trajectories from health to epilepsy across cell types and identify a subset of superficial cells undergoing a later stage in neurodegeneration. Our findings indicate that sublayer- and cell-type-specific changes associated with selective CA1 neuronal damage contribute to progression of hippocampal sclerosis.

Plasticity and heterogeneity of thermogenic adipose tissue

The perception of adipose tissue, both in the scientific community and in the general population, has changed dramatically in the past 20 years. While adipose tissue was thought for a long time to be a rather simple lipid storage entity, it is now recognized as a highly heterogeneous organ and a critical regulator of systemic metabolism, composed of many different subtypes of cells, with important endocrine functions. Additionally, adipose tissue is nowadays recognized to contribute to energy turnover, due to the presence of specialized thermogenic adipocytes, which can be found in many adipose depots. This review discusses the unprecedented insights that we have gained into the heterogeneity of thermogenic adipocytes and their respective precursors due to the technical developments in single-cell and nucleus technologies. These methodological advances have increased our understanding of how adipose tissue catabolic function is influenced by developmental and intercellular communication events.

Stress relief: emerging methods to mitigate dissociation-induced artefacts

The rapid progress of single-cell RNA-sequencing (scRNA-seq) at large scales has led to what seemed impossible until recently: the generation of comprehensive transcriptional maps of nearly all cells in multicellular tissues. We pinpoint three key elements as being critical to the production of these maps: scalability, spatial information, and accuracy of the transcriptome of the individual cells. Here, we discuss the ramifications of traditional cell-isolation protocols when capturing the transcriptional signature of cells as they exist in their native tissue context, the methods that have been developed to avoid these distortions, and the biological processes that have unraveled on account of these upgraded methodological approaches.

Single-cell RNA sequencing reveals Nestin+ active neural stem cells outside the central canal after spinal cord injury

Neural stem cells (NSCs) in the spinal cord hold great potential for repair after spinal cord injury (SCI). The ependyma in the central canal (CC) region has been considered as the NSCs source in the spinal cord. However, the ependyma function as NSCs after SCI is still under debate. We used Nestin as a marker to isolate potential NSCs and their immediate progeny, and characterized the cells before and after SCI by single-cell RNA-sequencing (scRNA-seq). We identified two subgroups of NSCs: the subgroup located within the CC cannot prime to active NSCs after SCI, while the subgroup located outside the CC were activated and exhibited the active NSCs properties after SCI. We demonstrated the comprehensive dynamic transcriptome of NSCs from quiescent to active NSCs after SCI. This study reveals that Nestin⁺ cells outside CC were NSCs that activated upon SCI and may thus serve as endogenous NSCs for regenerative treatment of SCI in the future.

Unraveling Root Development Through Single-Cell Omics and Reconstruction of Gene Regulatory Networks

Over the last decades, research on postembryonic root development has been facilitated by "omics" technologies. Among these technologies, microarrays first, and RNA sequencing (RNA-seq) later, have provided transcriptional information on the underlying molecular processes establishing the basis of System Biology studies in roots. Cell fate specification and development have been widely studied in the primary root, which involved the identification of many cell type transcriptomes and the reconstruction of gene regulatory networks (GRN). The study of lateral root (LR) development has not been an exception. However, the molecular mechanisms regulating cell fate specification during LR formation remain largely unexplored. Recently, single-cell RNA-seq (scRNA-seq) studies have addressed the specification of tissues from stem cells in the primary root. scRNA-seq studies are anticipated to be a useful approach to decipher cell fate specification and patterning during LR formation. In this review, we address the different scRNA-seq strategies used both in plants and animals and how we could take advantage of scRNA-seq to unravel new regulatory mechanisms and reconstruct GRN. In addition, we discuss how to integrate scRNA-seq results with previous RNA-seq datasets and GRN. We also address relevant findings obtained through single-cell based studies and how LR developmental studies could be facilitated by scRNA-seq approaches and subsequent GRN inference. The use of single-cell approaches to investigate LR formation could help to decipher fundamental biological mechanisms such as cell memory, synchronization, polarization, or pluripotency.

RGS6 Mediates Effects of Voluntary Running on Adult Hippocampal Neurogenesis

Voluntary running enhances adult hippocampal neurogenesis, with consequences for hippocampal-dependent learning ability and mood regulation. However, the underlying mechanism remains unclear. Here, we show that voluntary running induces unique and dynamic gene expression changes specifically within the adult-born hippocampal neurons, with significant impact on genes involved in neuronal maturation and human diseases. We identify the regulator of G protein signaling 6 (RGS6) as a key factor that mediates running impact on adult-born neurons. RGS6 overexpression mimics the positive effects of voluntary running on morphological and physiological maturation of adult new neurons and reduced sensitivity of adult-born neurons to the inhibitory effect of GABA_B (γ-Aminobutyric acid B) receptor activation. Knocking down RGS6 abolishes running-enhanced neuronal maturation and hippocampal neurogenesis-dependent learning and anxiolytic effect. Our study provides a data resource showing genome-wide intrinsic molecular changes in adult-born hippocampal neurons that contribute to voluntary running-induced neurogenesis.

Preclinical models and technologies to advance nanovaccine development

The remarkable success of targeted immunotherapies is revolutionizing cancer treatment. However, tumor heterogeneity and low immunogenicity, in addition to several tumor-associated immunosuppression mechanisms are among the major factors that have precluded the success of cancer vaccines as targeted cancer immunotherapies. The exciting outcomes obtained in patients upon the injection of tumor-specific antigens and adjuvants intratumorally, reinvigorated interest in the use of nanotechnology to foster the delivery of vaccines to address cancer unmet needs. Thus, bridging nano-based vaccine platform development and predicted clinical outcomes the selection of the proper preclinical model will be fundamental. Preclinical models have revealed promising outcomes for cancer vaccines. However, only few cases were associated with clinical responses. This review addresses the major challenges related to the translation of cancer nano-based vaccines to the clinic, discussing the requirements for ex vivo and in vivo models of cancer to ensure the translation of preclinical success to patients.

Novel Tools and Investigative Approaches for the Study of Oligodendrocyte Precursor Cells (NG2-Glia) in CNS Development and Disease

Oligodendrocyte progenitor cells (OPCs), also referred to as NG2-glia, are the most proliferative cell type in the adult central nervous system. While the primary role of OPCs is to serve as progenitors for oligodendrocytes, in recent years, it has become increasingly clear that OPCs fulfil a number of other functions. Indeed, independent of their role as stem cells, it is evident that OPCs can regulate the metabolic environment, directly interact with and modulate neuronal function, maintain the blood brain barrier (BBB) and regulate inflammation. In this review article, we discuss the state-of-the-art tools and investigative approaches being used to characterize the biology and function of OPCs. From functional genetic investigation to single cell sequencing and from lineage tracing to functional imaging, we discuss the important discoveries uncovered by these techniques, such as functional and spatial OPC heterogeneity, novel OPC marker genes, the interaction of OPCs with other cells types, and how OPCs integrate and respond to signals from neighboring cells. Finally, we review the use of in vitro assay to assess OPC functions. These methodologies promise to lead to ever greater understanding of this enigmatic cell type, which in turn will shed light on the pathogenesis and potential treatment strategies for a number of diseases, such as multiple sclerosis (MS) and gliomas.

Neuronal deletion of Wwox, associated with WOREE syndrome, causes epilepsy and myelin defects

WOREE syndrome caused by human germline biallelic mutations in WWOX is a neurodevelopmental disorder characterized by intractable epilepsy, severe developmental delay, ataxia and premature death at the age of 2-4 years. The underlying mechanisms of WWOX actions are poorly understood. In the current study, we show that specific neuronal deletion of murine Wwox produces phenotypes typical of the Wwox-null mutation leading to brain hyperexcitability, intractable epilepsy, ataxia and postnatal lethality. A significant decrease in transcript levels of genes involved in myelination was observed in mouse cortex and hippocampus. Wwox-mutant mice exhibited reduced maturation of oligodendrocytes, reduced myelinated axons and impaired axonal conductivity. Brain hyperexcitability and hypomyelination were also revealed in human brain organoids with a WWOX deletion. These findings provide cellular and molecular evidence for myelination defects and hyperexcitability in the WOREE syndrome linked to neuronal function of WWOX.

Neuronal and Glial Distribution of Tau Protein in the Adult Rat and Monkey

Tau is a microtubule-associated protein for which the physiological functions remain a topic of vigorous investigation. Additionally, tau is a central player in the pathogenesis of several diseases such as Alzheimer's disease and several frontotemporal dementias. A critical variable to understanding tau in physiological and disease contexts is its normal localization within cells of the adult CNS. Tau is often described as an axon-specific (or enriched) and neuron-specific protein with little to no expression in glial cells, all of which are untrue. Understanding normal tau distribution also impacts interpretation of experimental results and hypotheses regarding its role in disease. Thus, we set out to help clarify the normal localization of tau in the adult CNS of middle-aged rats and rhesus macaque using the hippocampus as a representative brain structure. The physiological concentration of tau in the rat hippocampus was 6.6 μM and in white matter was 3.6 μM as determined by quantitative sandwich ELISAs. We evaluated the cellular localization of tau using multiple tau-specific antibodies with epitopes to different regions, including Tau1, Tau5, Tau7, R1, and two novel primate-specific antibodies NT9 and NT15. In the rat and monkey, tau was localized within the somatodendritic and axonal compartments, as well as a subset of neuronal nuclei. Semi-quantitative fluorescence intensity measurements revealed that depending on the specific reagent used the somatodendritic tau is relatively equal to, higher than, or lower than axonal tau, highlighting differential labeling of tau with various antibodies despite its distribution throughout the neuron. Tau was strongly expressed in mature oligodendrocytes and displayed little to no expression in oligodendrocyte precursor cells, astrocytes or microglia. Collectively, the data indicate tau is ∼3 - 7 μM under physiological conditions, is not specifically enriched in axons, and is normally found in both neurons and mature oligodendrocytes in the adult CNS. The full landscape of tau distribution is not revealed by all antibodies suggesting availability of the epitopes is different within specific neuronal compartments. These findings set the stage for better understanding normal tau distributions and interpreting data regarding the presence of tau in different compartments or cell types within disease conditions.

A flexible microfluidic system for single-cell transcriptome profiling elucidates phased transcriptional regulators of cell cycle

Single cell transcriptome profiling has emerged as a breakthrough technology for the high-resolution understanding of complex cellular systems. Here we report a flexible, cost-effective and user-friendly droplet-based microfluidics system, called the Nadia Instrument, that can allow 3' mRNA capture of ~ 50,000 single cells or individual nuclei in a single run. The precise pressure-based system demonstrates highly reproducible droplet size, low doublet rates and high mRNA capture efficiencies that compare favorably in the field. Moreover, when combined with the Nadia Innovate, the system can be transformed into an adaptable setup that enables use of different buffers and barcoded bead configurations to facilitate diverse applications. Finally, by 3' mRNA profiling asynchronous human and mouse cells at different phases of the cell cycle, we demonstrate the system's ability to readily distinguish distinct cell populations and infer underlying transcriptional regulatory networks. Notably this provided supportive evidence for multiple transcription factors that had little or no known link to the cell cycle (e.g. DRAP1, ZKSCAN1 and CEBPZ). In summary, the Nadia platform represents a promising and flexible technology for future transcriptomic studies, and other related applications, at cell resolution.

A new era for plant science: spatial single-cell transcriptomics

To achieve a complete understanding of how organisms function, there is a need to study their fundamental unit, the cell, in its spatial context. In recent years, we have seen fast-paced technological progress to study the transcriptional content of single cells and their spatial relationships. This review highlights modern advancements in single-cell RNA-sequencing, provides an overview of the technologies that led the plant field toward spatial transcriptomics, and describes the available spatial transcriptomics approaches providing examples of their application to plant tissues. In addition, it discusses the integration of these methods to study plant tissues. Taken together, we propose a central role of spatial transcriptomics approaches in plant science.

Formation and integration of new neurons in the adult hippocampus

Neural stem cells (NSCs) generate new neurons throughout life in the mammalian brain. Adult-born neurons shape brain function, and endogenous NSCs could potentially be harnessed for brain repair. In this Review, focused on hippocampal neurogenesis in rodents, we highlight recent advances in the field based on novel technologies (including single-cell RNA sequencing, intravital imaging and functional observation of newborn cells in behaving mice) and characterize the distinct developmental steps from stem cell activation to the integration of newborn neurons into pre-existing circuits. Further, we review current knowledge of how levels of neurogenesis are regulated, discuss findings regarding survival and maturation of adult-born cells and describe how newborn neurons affect brain function. The evidence arguing for (and against) lifelong neurogenesis in the human hippocampus is briefly summarized. Finally, we provide an outlook of what is needed to improve our understanding of the mechanisms and functional consequences of adult neurogenesis and how the field may move towards more translational relevance in the context of acute and chronic neural injury and stem cell-based brain repair.

Diapause vs. reproductive programs: transcriptional phenotypes in a keystone copepod

Many arthropods undergo a seasonal dormancy termed "diapause" to optimize timing of reproduction in highly seasonal environments. In the North Atlantic, the copepod Calanus finmarchicus completes one to three generations annually with some individuals maturing into adults, while others interrupt their development to enter diapause. It is unknown which, why and when individuals enter the diapause program. Transcriptomic data from copepods on known programs were analyzed using dimensionality reduction of gene expression and functional analyses to identify program-specific genes and biological processes. These analyses elucidated physiological differences and established protocols that distinguish between programs. Differences in gene expression were associated with maturation of individuals on the reproductive program, while those on the diapause program showed little change over time. Only two of six filters effectively separated copepods by developmental program. The first one included all genes annotated to RNA metabolism and this was confirmed using differential gene expression analysis. The second filter identified 54 differentially expressed genes that were consistently up-regulated in individuals on the diapause program in comparison with those on the reproductive program. Annotated to oogenesis, RNA metabolism and fatty acid biosynthesis, these genes are both indicators for diapause preparation and good candidates for functional studies.