Elucidating the cellular architecture of the human cerebral cortex is central to understanding our cognitive abilities and susceptibility to disease. Here we applied single nucleus RNA-sequencing to perform a comprehensive analysis of cell types in the middle temporal gyrus of human cortex. We identified a highly diverse set of excitatory and inhibitory neuronal types that are mostly sparse, with excitatory types being less layer-restricted than expected. Comparison to similar mouse cortex single cell RNA-sequencing datasets revealed a surprisingly well-conserved cellular architecture that enables matching of homologous types and predictions of human cell type properties. Despite this general conservation, we also find extensive differences between homologous human and mouse cell types, including dramatic alterations in proportions, laminar distributions, gene expression, and morphology. These species-specific features emphasize the importance of directly studying human brain.

ARS-CoV-2 is the causal agent for COVID-19, and the World Health Organization classifies this virus as an airborne pathogen transmitted by asymptomatic, pre-symptomatic and symptomatic individuals through close contact via exposure to infected droplets and aerosols 1,2 . Although SARS-CoV-2 transmission can occur by activities involving the oral cavity, such as speaking, breathing, coughing, sneezing and even singing [3][4][5] , most attention has focused on the nasal-lung axis of infection 6 . Oral manifestations, such as taste loss, dry mouth and oral lesions, are evident in about half of COVID-19 cases [7][8][9] , although it remains unknown whether SARS-CoV-2 can directly infect and replicate in oral tissues, such as the salivary glands (SGs) or mucosa. This is critical because, if these are sites of early infection, they could play an important role in transmitting the virus to the lungs or the gastrointestinal tract via saliva, as has been suggested for other microbial-associated diseases, such as pneumonia 10 and inflammatory bowel diseases 11,12 (Extended Data Fig. 1a).SARS-CoV-2 uses host entry factors, such as ACE2 and TMPRSS family members (TMPRSS2 and TMPRSS4) 13,14 , and understanding the cell types that harbor these receptors is important for determining infection susceptibilities throughout the body [15][16][17] . ACE2 and TMPRSS2 expression has been reported in oral tissues 18,19 ; however, there are no comprehensive descriptions of viral entry factor expression nor direct confirmation of SARS-CoV-2 infection in oral tissues. We hypothesized that SGs and barrier epithelia of the oral cavity and oropharynx can be infected by SARS-CoV-2 and contribute to the transmission of SARS-CoV-2. To test this, we generated two human oral single-cell RNA sequencing (scRNA-seq) atlases to predict cell-specific susceptibilities to SARS-CoV-2 infection. We confirmed ACE2 and TMPRSS expression in SGs and oral mucosa epithelia. SARS-CoV-2 infection was confirmed using autopsy and outpatient samples. Saliva from asymptomatic individuals with COVID-19 demonstrated the potential for viral transmission. In a prospective clinical cohort, we found a positive correlation between salivary viral load and taste loss; we also demonstrated persistent salivary antibody responses to SARS-CoV-2 nucleocapsid and spike proteins. ResultsOral tissue atlases reveal resident immune cells and niche-specific epithelial diversity. The SGs and the barrier mucosa of the oral cavity and oropharynx are likely gateways for viral infection, replication SARS-CoV-2 infection of the oral cavity and saliva

The primary motor cortex (M1) is essential for voluntary fine-motor control and is functionally conserved across mammals1. Here, using high-throughput transcriptomic and epigenomic profiling of more than 450,000 single nuclei in humans, marmoset monkeys and mice, we demonstrate a broadly conserved cellular makeup of this region, with similarities that mirror evolutionary distance and are consistent between the transcriptome and epigenome. The core conserved molecular identities of neuronal and non-neuronal cell types allow us to generate a cross-species consensus classification of cell types, and to infer conserved properties of cell types across species. Despite the overall conservation, however, many species-dependent specializations are apparent, including differences in cell-type proportions, gene expression, DNA methylation and chromatin state. Few cell-type marker genes are conserved across species, revealing a short list of candidate genes and regulatory mechanisms that are responsible for conserved features of homologous cell types, such as the GABAergic chandelier cells. This consensus transcriptomic classification allows us to use patch–seq (a combination of whole-cell patch-clamp recordings, RNA sequencing and morphological characterization) to identify corticospinal Betz cells from layer 5 in non-human primates and humans, and to characterize their highly specialized physiology and anatomy. These findings highlight the robust molecular underpinnings of cell-type diversity in M1 across mammals, and point to the genes and regulatory pathways responsible for the functional identity of cell types and their species-specific adaptations.

Transcriptomic profiling of complex tissues by single-nucleus RNA-sequencing (snRNA-seq) affords some advantages over single-cell RNA-sequencing (scRNA-seq). snRNA-seq provides less biased cellular coverage, does not appear to suffer cell isolation-based transcriptional artifacts, and can be applied to archived frozen specimens. We used well-matched snRNA-seq and scRNA-seq datasets from mouse visual cortex to compare cell type detection. Although more transcripts are detected in individual whole cells (~11,000 genes) than nuclei (~7,000 genes), we demonstrate that closely related neuronal cell types can be similarly discriminated with both methods if intronic sequences are included in snRNA-seq analysis. We estimate that the nuclear proportion of total cellular mRNA varies from 20% to over 50% for large and small pyramidal neurons, respectively. Together, these results illustrate the high information content of nuclear RNA for characterization of cellular diversity in brain tissues.

A protocol is described for sequencing the transcriptome of a cell nucleus. Nuclei are isolated from specimens and sorted by FACS, cDNA libraries are constructed and RNA-seq is performed, followed by data analysis. Some steps follow published methods (Smart-seq2 for cDNA synthesis and Nextera XT barcoded library preparation) and are not described in detail here. Previous single-cell approaches for RNA-seq from tissues include cell dissociation using protease treatment at 30 °C, which is known to alter the transcriptome. We isolate nuclei at 4 °C from tissue homogenates, which cause minimal damage. Nuclear transcriptomes can be obtained from postmortem human brain tissue stored at −80 °C, making brain archives accessible for RNA-seq from individual neurons. The method also allows investigation of biological features unique to nuclei, such as enrichment of certain transcripts and precursors of some noncoding RNAs. By following this procedure, it takes about 4 d to construct cDNA libraries that are ready for sequencing.

We describe convergent evidence from transcriptomics, morphology and physiology for a specialized GABAergic neuron subtype in human cortex. Using unbiased single nucleus RNA sequencing, we identify ten GABAergic interneuron subtypes with combinatorial gene signatures in human cortical layer 1 and characterize a novel group of human interneurons with anatomical features never described in rodents having large, “rosehip”-like axonal boutons and compact arborization. These rosehip cells show an immunohistochemical profile (GAD1/CCK-positive, CNR1/SST/CALB2/PVALB-negative) matching a single transcriptomically-defined cell type whose specific molecular marker signature is not seen in mouse cortex. Rosehip cells in layer 1 make homotypic gap junctions, predominantly target apical dendritic shafts of layer 3 pyramidal neurons and inhibit backpropagating pyramidal action potentials in microdomains of the dendritic tuft. These cells are therefore positioned for potent local control of distal dendritic computation in cortical pyramidal neurons.

The Influenza Research Database (IRD) is a U.S. National Institute of Allergy and Infectious Diseases (NIAID)-sponsored Bioinformatics Resource Center dedicated to providing bioinformatics support for influenza virus research. IRD facilitates the research and development of vaccines, diagnostics and therapeutics against influenza virus by providing a comprehensive collection of influenza-related data integrated from various sources, a growing suite of analysis and visualization tools for data mining and hypothesis generation, personal workbench spaces for data storage and sharing, and active user community support. Here, we describe the recent improvements in IRD including the use of cloud and high performance computing resources, analysis and visualization of user-provided sequence data with associated metadata, predictions of novel variant proteins, annotations of phenotype-associated sequence markers and their predicted phenotypic effects, hemagglutinin (HA) clade classifications, an automated tool for HA subtype numbering conversion, linkouts to disease event data and the addition of host factor and antiviral drug components. All data and tools are freely available without restriction from the IRD website at https://www.fludb.org.

The small heat shock proteins (sHSPs) are a diverse family of molecular chaperones. It is well established that these proteins are crucial components of the plant heat shock response. They also have important roles in other stress responses and in normal development. We have conducted a comparative sequence analysis of the sHSPs in three complete angiosperms genomes: Arabidopsis thaliana, Populus trichocarpa, and Oryza sativa. Our phylogenetic analysis has identified four additional plant sHSP subfamilies and thus has increased the number of plant sHSP subfamilies from 7 to 11. We have also identified a number of novel sHSP genes in each genome that lack close homologs in other genomes. Using publicly available gene expression data and predicted secondary structures, we have determined that the sHSPs in plants are far more diverse in sequence, expression profile, and in structure than had been previously known. Some of the newly identified subfamilies are not stress regulated, may not possess the highly conserved large oligomer structure, and may not even function as molecular chaperones. We found no consistent evolutionary patterns across the three species studied. For example, gene conversion was found among the sHSPs in O. sativa but not in A. thaliana or P. trichocarpa. Among the three species, P. trichocarpa had the most sHSPs. This was due to an expansion of the cytosolic I sHSPs that was not seen in the other two species. Our analysis indicates that the sHSPs are a dynamic protein family in angiosperms with unexpected levels of diversity.