Single-cell RNA sequencing and cell-cell communication analysis reveal tumor microenvironment associated with chemotherapy responsiveness in ovarian cancer.

BACKGROUND: To investigate the impact of the tumor microenvironment (TME) on the responsiveness to chemotherapy in ovarian cancer (OV). METHODS: We integrated single cell RNA-seq datasets of OV containing chemo-response information, and characterize their clusters based on different TME sections. We focus on analyzing cell-cell communication to elaborate on the mechanisms by which different components of the TME directly influence the chemo-response of tumor cells. RESULTS: scRNA-seq datasets were annotated according to specific markers for different cell types. Differential analysis of malignant epithelial cells revealed that chemoresistance was associated with the TME. Notably, distinct TME components exhibited varying effects on chemoresistance. Enriched SPP1+ tumor-associated macrophages in chemo-resistant patients could promote chemoresistance through SPP1 binding to CD44 on tumor cells. Additionally, the overexpression of THBS2 in stromal cells could promote chemoresistance through binding with CD47 on tumor cells. In contrast, GZMA in the lymphocytes could downregulate the expression of PARD3 through direct interaction with PARD3, thereby attenuating chemoresistance in tumor cells. CONCLUSION: Our study indicates that the non-tumor cell components of the TME (e.g. SPP1+ TAMs, stromal cells and lymphocytes) can directly impact the chemo-response of OV and targeting the TME was potentially crucial in chemotherapy of OV.

Unraveling the metastatic niche in breast cancer bone metastasis through single-cell RNA sequencing.

PURPOSE: Breast cancer (BRCA) is characterized by a unique metastatic pattern, often presenting with bone metastasis (BoM), posing significant clinical challenges. Through the study of the immune microenvironment in BRCA BoM offer perspectives for therapeutic interventions targeting this specific metastatic manifestation of BRCA. METHODS: This study employs single-cell RNA sequencing and TCGA data analysis to comprehensively compare primary tumors (PT), lymph node metastasis (LN), and BoM. RESULTS AND CONCLUSIONS: Our investigation identifies a metastatic niche in BoM marked by an increased abundance of cancer-associated fibroblasts (CAFs) and reduced immune cell presence. A distinct subtype (State 1) of BRCA BoM cells associated with adverse prognosis is identified. State 1, displaying heightened stemness traits, may represent an initiation phase for BoM in BRCA. Complex cell communications involving tumor, stromal, and immune cells are revealed. Interactions of FN1, SPP1, and MDK correlate with elevated immune cells in BoM. CD46, MDK, and PTN interactions drive myofibroblast activation and proliferation, contributing to tissue remodeling. Additionally, MDK, PTN, and FN1 interactions influence FAP+ CAF activation, impacting cell adhesion and migration in BoM. These insights deepen our understanding of the metastatic niche in breast cancer BoM.

Single-cell analysis of ovarian myeloid cells identifies aging associated changes in macrophages and signaling dynamics.

The aging of mammalian ovary is accompanied by an increase in tissue fibrosis and heightened inflammation. Myeloid cells, including macrophages, monocytes, dendritic cells, and neutrophils, play pivotal roles in shaping the ovarian tissue microenvironment and regulating inflammatory responses. However, a comprehensive understanding of the roles of these cells in the ovarian aging process is lacking. To bridge this knowledge gap, we utilized single-cell RNA sequencing (scRNAseq) and flow cytometry analysis to functionally characterize CD45+ CD11b+ myeloid cell populations in young (3 months old) and aged (14-17 months old) murine ovaries. Our dataset unveiled the presence of five ovarian macrophage subsets, including a Cx3cr1 low Cd81 hi subset unique to the aged murine ovary. Most notably, our data revealed significant alterations in ANNEXIN and TGFß signaling within aged ovarian myeloid cells, which suggest a novel mechanism contributing to the onset and progression of aging-associated inflammation and fibrosis in the ovarian tissue.

Molecular Changes Implicate Angiogenesis and Arterial Remodeling in Systemic Sclerosis-Associated and Idiopathic Pulmonary Hypertension.

BACKGROUND: Pulmonary hypertension (PH) is a common complication of systemic sclerosis (SSc) and a leading cause of mortality among patients with this disease. PH can also occur as an idiopathic condition (idiopathic pulmonary arterial hypertension). Investigation of transcriptomic alterations in vascular populations is critical to elucidating cellular mechanisms underlying pathobiology of SSc-associated and idiopathic PH. METHODS: We analyzed single-cell RNA sequencing profiles of endothelial and perivascular mesenchymal populations from explanted lung tissue of patients with SSc-associated PH (n=16), idiopathic pulmonary arterial hypertension (n=3), and healthy controls (n=15). Findings were validated by immunofluorescence staining of explanted human lung tissue. RESULTS: Three disease-associated endothelial populations emerged. Two angiogenic endothelial cell (EC) subtypes markedly expanded in SSc-associated PH lungs: tip ECs expressing canonical tip markers PGF and APLN and phalanx ECs expressing genes associated with vascular development, endothelial barrier integrity, and Notch signaling. Gene regulatory network analysis suggested enrichment of Smad1 (SMAD family member 1) and PPAR-γ (peroxisome proliferator-activated receptor-γ) regulon activities in these 2 populations, respectively. Mapping of potential ligand-receptor interactions highlighted Notch, apelin-APJ (apelin receptor), and angiopoietin-Tie (tyrosine kinase with immunoglobulin-like and EGF-like domains 1) signaling pathways between angiogenic ECs and perivascular cells. Transitional cells, expressing both endothelial and pericyte/smooth muscle cell markers, provided evidence for the presence of endothelial-to-mesenchymal transition. Transcriptional programs associated with arterial endothelial dysfunction implicated VEGF-A (vascular endothelial growth factor-A), TGF-ß1 (transforming growth factor beta-1), angiotensin, and TNFSF12 (tumor necrosis factor ligand superfamily member 12)/TWEAK (TNF-related weak inducer of apoptosis) in the injury/remodeling phenotype of PH arterial ECs. CONCLUSIONS: These data provide high-resolution insights into the complexity and plasticity of the pulmonary endothelium in SSc-associated PH and idiopathic pulmonary arterial hypertension and provide direct molecular insights into soluble mediators and transcription factors driving PH vasculopathy.

Unveiling the Dynamics behind Glioblastoma Multiforme Single-Cell Data Heterogeneity.

Glioblastoma Multiforme is a brain tumor distinguished by its aggressiveness. We suggested that this aggressiveness leads single-cell RNA-sequence data (scRNA-seq) to span a representative portion of the cancer attractors domain. This conjecture allowed us to interpret the scRNA-seq heterogeneity as reflecting a representative trajectory within the attractor's domain. We considered factors such as genomic instability to characterize the cancer dynamics through stochastic fixed points. The fixed points were derived from centroids obtained through various clustering methods to verify our method sensitivity. This methodological foundation is based upon sample and time average equivalence, assigning an interpretative value to the data cluster centroids and supporting parameters estimation. We used stochastic simulations to reproduce the dynamics, and our results showed an alignment between experimental and simulated dataset centroids. We also computed the Waddington landscape, which provided a visual framework for validating the centroids and standard deviations as characterizations of cancer attractors. Additionally, we examined the stability and transitions between attractors and revealed a potential interplay between subtypes. These transitions might be related to cancer recurrence and progression, connecting the molecular mechanisms of cancer heterogeneity with statistical properties of gene expression dynamics. Our work advances the modeling of gene expression dynamics and paves the way for personalized therapeutic interventions.

Prognostic model based on B cell marker genes for NSCLC patients under neoadjuvant immunotherapy by integrated analysis of single-cell and bulk RNA-sequencing data.

BACKGROUND: Neoadjuvant immunotherapy has evolved as an effective option to treat non-small cell lung cancer (NSCLC). B cells play essential roles in the immune system as well as cancer progression. However, the repertoire of B cells and its association with clinical outcomes remains unclear in NSCLC patients receiving neoadjuvant immunotherapy. METHODS: Single-cell RNA sequencing (scRNA-seq) and bulk RNA sequencing data for LUAD samples were accessed from the TCGA and GEO databases. LUAD-related B cell marker genes were confirmed based on comprehensive analysis of scRNA-seq data. We then constructed the B cell marker gene signature (BCMGS) and validated it. In addition, we evaluated the association of BCGMS with tumor immune microenvironment (TIME) characteristics. Furthermore, we validated the efficacy of BCGMS in a cohort of NSCLC patients receiving neoadjuvant immunotherapy. RESULTS: A BCMGS was constructed based on the TCGA cohort and further validated in three independent GSE cohorts. In addition, the BCMGS was proven to be significantly associated with TIME characteristics. Moreover, a relatively higher risk score indicated poor clinical outcomes and a worse immune response among NSCLC patients receiving neoadjuvant immunotherapy. CONCLUSIONS: We constructed an 18-gene prognostic signature derived from B cell marker genes based on scRNA-seq data, which had the potential to predict the prognosis and immune response of NSCLC patients receiving neoadjuvant immunotherapy.

Upregulated PPP1R14B is connected to cancer progression and immune infiltration in kidney renal clear cell carcinoma.

BACKGROUND: Protein phosphatase 1 regulatory subunit 14B (PPP1R14B) is an oncogenic gene found in a variety of tumors, but its role in the prognosis and development of kidney renal clear cell carcinoma (KIRC) remains unknown. Our study aimed to determine whether PPP1R14B could be a prognostic biomarker for KIRC and its role in the development of KIRC. METHODS: In this work, we used The Cancer Genome Atlas (TCGA) database to explore the expression of PPP1R14B in tumor tissues, its relationship with the prognosis of tumor patients, and its role in tumor occurrence and development. We validated our findings using the International Cancer Genome Consortium (ICGC) cohort, our clinical samples, and in vitro experiments. RESULTS: PPP1R14B was upregulated in KIRC compared to adjacent normal tissue. Moreover, multivariate analysis revealed that upregulated PPP1R14B expression was an independent risk factor for KIRC progression. High-PPP1R14B groups had shorter overall survival (OS) and disease-free survival (DFS) in TCGA and ICGC cohorts. We used Cell Counting Kit-8 (CCK8) and scratch wound healing assay to explore the proliferation and migration of KIRC cells following PPP1R14B knockdown. Our results indicated that PPP1R14B knockdown significantly reduced the proliferation and migration of KIRC cells in vitro. We also explored the possible cellular mechanisms of PPP1R14B through the Kyoto Encyclopedia of Genes and Genomes (KEGG), Gene ontology (GO) analysis, and TISIDB analysis. The function enrich analysis revealed that PPP1R14B-related genes were mainly enriched in purine metabolism and the macromolecule catabolic process. PPP1R14B expression was associated with tumor-infiltrating immune cells (TIICs) in the TCGA cohort, and the results of single-cell RNA-seq (scRNA) further demonstrated that PPP1R14B expression was associated with the enhanced infiltration of CD8 + T lymphocytes. CONCLUSION: PPP1R14B may serve as a prognostic biomarker in KIRC, affect purine metabolism, activate immune infiltration, and promote KIRC cell migration.

Gene Regulatory Networks: Improving Inferences with Transfer Learning.

Deep transfer learning improves the inference of gene regulatory networks in human cells, reveals disease-associated genes, and identifies network-based druggable targets in human heart disease.

Single-Cell RNA Sequencing and Its Applications in the Study of Psychiatric Disorders.

Neuroscience is currently one of the most challenging research fields owing to the enormous complexity of the mammalian nervous system. We are yet to understand precise transcriptional programs that govern cell fate during neurodevelopment, resolve the connectome of the mammalian brain, and determine the etiology of various neurodegenerative and psychiatric disorders. Technological advances in the past decade, notably single-cell RNA sequencing, have enabled huge progress in our understanding of such features. Our current knowledge of the transcriptome is largely derived from bulk RNA sequencing, which reveals only the average gene expression of millions of cells, potentially missing out on minor transcriptome differences between cells detectable only at single-cell resolution. Since 2009, several single-cell RNA sequencing techniques have emerged that enable the accurate classification of neuronal and glial cell subtypes beyond classical molecular markers and electrophysiological features and allow the identification of previously unknown cell types. Furthermore, it enables the interrogation of molecular and disease-relevant mechanisms and offers further possibilities for the discovery of new drug targets and disease biomarkers. This review intends to familiarize the reader with the main single-cell RNA sequencing techniques developed throughout the past decade and discusses their application in the fields of brain cell taxonomy, neurodevelopment, and psychiatric disorders.

Single-cell RNA sequencing reveals the lineage of malignant epithelial cells and upregulation of TAGLN2 promotes peritoneal metastasis in gastric cancer.

BACKGROUND: Peritoneal metastasis (PM) is an important factor contributing to poor prognosis in patients with gastric cancer (GC). Transcriptomic sequencing has been used to explore the molecular changes in metastatic cancers, but comparing the bulk RNA-sequencing data between primary tumors and metastases in PM studies is unreasonable due to the small proportion of tumor cells in PM tissues. METHODS: We performed single-cell RNA-sequencing analysis on four gastric adenocarcinoma specimens, including one primary tumor sample (PT), one adjacent nontumoral sample (PN), one peritoneal metastatic sample (MT) and one normal peritoneum sample (MN), from the same patient. Pseudotime trajectory analysis was used to display the process by which nonmalignant epithelial cells transform into tumor cells and then metastasize to the peritoneum. Finally, in vitro and in vivo assays were used to validate one of the selected genes that promote peritoneal metastasis. RESULTS: Single-cell RNA sequencing showed that a development curve was found from normal mucosa to tumor tissues and then into metastatic sites on peritoneum. TAGLN2 was found to trigger this metastasis process. The migration and invasion capability of GC cells were changed by downregulating and upregulating TAGLN2 expression. Mechanistically, TAGLN2 might modulate tumor metastasis via alterations in cell morphology and several signaling pathways, thus promoting epithelial-mesenchymal transition (EMT). CONCLUSIONS: In summary, we identified and validated TAGLN2 as a novel gene involved in GC peritoneal metastasis. This study provided valuable insight into the mechanisms of GC metastasis and developed a potential therapeutic target to prevent GC cell dissemination.

Necroptosis activation is associated with greater methylene blue-photodynamic therapy-induced cytotoxicity in human pancreatic ductal adenocarcinoma cells.

Pancreatic ductal adenocarcinomas (PDAC) are the fourth leading cause of death due to neoplasms. In view of the urgent need of effective treatments for PDAC, photodynamic therapy (PDT) appears as a promising alternative. However, its efficacy against PDAC and the mechanisms involved in cell death induction remain unclear. In this study, we set out to evaluate PDT's cytotoxicity using methylene blue (MB) as a photosensitizer (PS) (MB-PDT) and to evaluate the contribution of necroptosis in its effect in human PDAC cells. Our results demonstrated that MB-PDT induced significant death of different human PDAC models presenting two different susceptibility profiles. This effect was independent of MB uptake or its subcellular localization. We found that the ability of triggering necroptosis was determinant to increase the treatment efficiency. Analysis of single cell RNA-seq data from normal and neoplastic human pancreatic tissues showed that specific necroptosis proteins RIPK1, RIPK3 and MLKL presented significant higher expression levels in cells displaying a transformed phenotype providing further support to the use of approaches that activate necroptosis, like MB-PDT, as useful adjunct to surgery of PDAC to tackle the problem of microscopic residual disease as well as to minimize the chance of local and metastatic recurrence.

Analysis of Tumor-Infiltrating T-Cell Transcriptomes Reveal a Unique Genetic Signature across Different Types of Cancer.

CD8+ and CD4+ T-cells play a key role in cellular immune responses against cancer by cytotoxic responses and effector lineages differentiation, respectively. These subsets have been found in different types of cancer; however, it is unclear whether tumor-infiltrating T-cell subsets exhibit similar transcriptome profiling across different types of cancer in comparison with healthy tissue-resident T-cells. Thus, we analyzed the single cell transcriptome of five tumor-infiltrating CD4-T, CD8-T and Treg cells obtained from different types of cancer to identify specific pathways for each subset in malignant environments. An in silico analysis was performed from single-cell RNA-sequencing data available in public repositories (Gene Expression Omnibus) including breast cancer, melanoma, colorectal cancer, lung cancer and head and neck cancer. After dimensionality reduction, clustering and selection of the different subpopulations from malignant and nonmalignant datasets, common genes across different types of cancer were identified and compared to nonmalignant genes for each T-cell subset to identify specific pathways. Exclusive pathways in CD4+ cells, CD8+ cells and Tregs, and common pathways for the tumor-infiltrating T-cell subsets were identified. Finally, the identified pathways were compared with RNAseq and proteomic data obtained from T-cell subsets cultured under malignant environments and we observed that cytokine signaling, especially Th2-type cytokine, was the top overrepresented pathway in Tregs from malignant samples.

Contribution of Transcriptome to Elucidate the Biology of Plasmodium spp.

The present review discusses some of the new technologies that have been applied to elucidate how Plasmodium spp escape from the immune system and subvert the host physiology to orchestrate the regulation of its biological pathways. Our manuscript describes how techniques such as microarray approaches, RNA-Seq, and single-cell RNA sequencing have contributed to the discovery of transcripts and changed the concept of gene expression regulation in closely related malaria parasite species. Moreover, the text highlights the contributions of high-throughput RNA sequencing for the current knowledge of malaria parasite biology, physiology, vaccine target, and the revelation of new players in parasite signaling.

Heterogeneity in the Response of Different Subtypes of Drosophila melanogaster Midgut Cells to Viral Infections.

Single-cell RNA sequencing (scRNA-seq) offers the possibility to monitor both host and pathogens transcriptomes at the cellular level. Here, public scRNA-seq datasets from Drosophila melanogaster midgut cells were used to compare the differences in replication strategy and cellular responses between two fly picorna-like viruses, Thika virus (TV) and D. melanogaster Nora virus (DMelNV). TV exhibited lower levels of viral RNA accumulation but infected a higher number of cells compared to DMelNV. In both cases, viral RNA accumulation varied according to cell subtype. The cellular heat shock response to TV and DMelNV infection was cell-subtype- and virus-specific. Disruption of bottleneck genes at later stages of infection in the systemic response, as well as of translation-related genes in the cellular response to DMelNV in two cell subtypes, may affect the virus replication.

In silico Analyses of Immune System Protein Interactome Network, Single-Cell RNA Sequencing of Human Tissues, and Artificial Neural Networks Reveal Potential Therapeutic Targets for Drug Repurposing Against COVID-19.

Background: There is pressing urgency to identify therapeutic targets and drugs that allow treating COVID-19 patients effectively. Methods: We performed in silico analyses of immune system protein interactome network, single-cell RNA sequencing of human tissues, and artificial neural networks to reveal potential therapeutic targets for drug repurposing against COVID-19. Results: We screened 1,584 high-confidence immune system proteins in ACE2 and TMPRSS2 co-expressing cells, finding 25 potential therapeutic targets significantly overexpressed in nasal goblet secretory cells, lung type II pneumocytes, and ileal absorptive enterocytes of patients with several immunopathologies. Then, we performed fully connected deep neural networks to find the best multitask classification model to predict the activity of 10,672 drugs, obtaining several approved drugs, compounds under investigation, and experimental compounds with the highest area under the receiver operating characteristics. Conclusion: After being effectively analyzed in clinical trials, these drugs can be considered for treatment of severe COVID-19 patients. Scripts can be downloaded at https://github.com/muntisa/immuno-drug-repurposing-COVID-19.

Pulmonary Mesenchymal Stem Cells in Mild Cases of COVID-19 Are Dedicated to Proliferation; In Severe Cases, They Control Inflammation, Make Cell Dispersion, and Tissue Regeneration.

Mesenchymal stem cells (MSCs) are multipotent adult stem cells present in virtually all tissues; they have potent self-renewal capacity and differentiate into multiple cell types. For many reasons, these cells are a promising therapeutic alternative to treat patients with severe COVID-19 and pulmonary post-COVID sequelae. These cells are not only essential for tissue regeneration; they can also alter the pulmonary environment through the paracrine secretion of several mediators. They can control or promote inflammation, induce other stem cells differentiation, restrain the virus load, and much more. In this work, we performed single-cell RNA-seq data analysis of MSCs in bronchoalveolar lavage samples from control individuals and COVID-19 patients with mild and severe clinical conditions. When we compared samples from mild cases with control individuals, most genes transcriptionally upregulated in COVID-19 were involved in cell proliferation. However, a new set of genes with distinct biological functions was upregulated when we compared severely affected with mild COVID-19 patients. In this analysis, the cells upregulated genes related to cell dispersion/migration and induced the γ-activated sequence (GAS) genes, probably triggered by IFNGR1 and IFNGR2. Then, IRF-1 was upregulated, one of the GAS target genes, leading to the interferon-stimulated response (ISR) and the overexpression of many signature target genes. The MSCs also upregulated genes involved in the mesenchymal-epithelial transition, virus control, cell chemotaxis, and used the cytoplasmic RNA danger sensors RIG-1, MDA5, and PKR. In a non-comparative analysis, we observed that MSCs from severe cases do not express many NF-κB upstream receptors, such as Toll-like (TLRs) TLR-3, -7, and -8; tumor necrosis factor (TNFR1 or TNFR2), RANK, CD40, and IL-1R1. Indeed, many NF-κB inhibitors were upregulated, including PPP2CB, OPTN, NFKBIA, and FHL2, suggesting that MSCs do not play a role in the "cytokine storm" observed. Therefore, lung MSCs in COVID-19 sense immune danger and act protectively in concert with the pulmonary environment, confirming their therapeutic potential in cell-based therapy for COVID-19. The transcription of MSCs senescence markers is discussed.

MYC Promotes Bone Marrow Stem Cell Dysfunction in Fanconi Anemia.

Bone marrow failure (BMF) in Fanconi anemia (FA) patients results from dysfunctional hematopoietic stem and progenitor cells (HSPCs). To identify determinants of BMF, we performed single-cell transcriptome profiling of primary HSPCs from FA patients. In addition to overexpression of p53 and TGF-ß pathway genes, we identified high levels of MYC expression. We correspondingly observed coexistence of distinct HSPC subpopulations expressing high levels of TP53 or MYC in FA bone marrow (BM). Inhibiting MYC expression with the BET bromodomain inhibitor (+)-JQ1 reduced the clonogenic potential of FA patient HSPCs but rescued physiological and genotoxic stress in HSPCs from FA mice, showing that MYC promotes proliferation while increasing DNA damage. MYC-high HSPCs showed significant downregulation of cell adhesion genes, consistent with enhanced egress of FA HSPCs from bone marrow to peripheral blood. We speculate that MYC overexpression impairs HSPC function in FA patients and contributes to exhaustion in FA bone marrow.

Immune cell infiltration features and related marker genes in lung cancer based on single-cell RNA-seq.

PURPOSE: Immune cells in the immune microenvironment of lung cancer have a great impact on the development of lung cancer. Our purpose was to analyze the immune cell infiltration features and related marker genes for lung cancer. METHODS: Single cell RNA sequencing data of 11,485 lung cancer cells were retrieved from the Gene Expression Omnibus. After quality control and data normalization, cell clustering was performed using the Seurat package. Based on the marker genes of each cell type from the CellMarker database, each cell was divided into G1, G2M, and S phases. Then, differential expression and functional enrichment analyses were performed. CIBERSORT was used to reconstruct immune cell types. RESULTS: Following cell filtering, highly variable genes were identified for all cells. 14 cell types were clustered. Among them, CD4 + T cell, B cell, plasma cell, natural killer cell and cancer stem cell were the top five cell types. Up-regulated genes were mainly enriched in immune-related biological processes and pathways. Using CIBERSORT, we identified the significantly higher fractions of naïve B cell, memory CD4 + T cell, T follicular helper cell, T regulatory helper cell and M1 macrophage in lung cancer tissues compared to normal tissues. Furthermore, the fractions of resting NK cell, monocyte, M0 macrophage, resting mast cell, eosinophil and neutrophil were significantly lower in tumor tissues than normal tissues. CONCLUSION: Our findings dissected the immune cell infiltration features and related marker genes for lung cancer, which might provide novel insights for the immunotherapy of lung cancer.

Epithelial Vegfa Specifies a Distinct Endothelial Population in the Mouse Lung.

The lung microvasculature is essential for gas exchange and commonly considered homogeneous. We show that VEGFA from the epithelium is required for a distinct endothelial cell (EC) population in the mouse lung. Vegfa is predominantly expressed by alveolar type 1 (AT1) cells and locally required to specify a subset of ECs. Single-cell RNA sequencing (scRNA-seq) reveals that ∼15% of lung ECs are transcriptionally distinct-marked by Carbonic anhydrase 4 (Car4)-and arise from bulk ECs, as suggested by trajectory analysis. Car4 ECs have extensive cellular projections and are separated from AT1 cells by a limited basement membrane without intervening pericytes. Car4 ECs are specifically lost upon epithelial Vegfa deletion; without Car4 ECs, the alveolar space is aberrantly enlarged despite the normal appearance of myofibroblasts. Lung Car4 ECs and retina tip ECs have common and distinct features. These findings support a signaling role of AT1 cells and shed light on alveologenesis.

Multimodal Analysis of Cell Types in a Hypothalamic Node Controlling Social Behavior.

The ventrolateral subdivision of the ventromedial hypothalamus (VMHvl) contains ∼4,000 neurons that project to multiple targets and control innate social behaviors including aggression and mounting. However, the number of cell types in VMHvl and their relationship to connectivity and behavioral function are unknown. We performed single-cell RNA sequencing using two independent platforms-SMART-seq (∼4,500 neurons) and 10x (∼78,000 neurons)-and investigated correspondence between transcriptomic identity and axonal projections or behavioral activation, respectively. Canonical correlation analysis (CCA) identified 17 transcriptomic types (T-types), including several sexually dimorphic clusters, the majority of which were validated by seqFISH. Immediate early gene analysis identified T-types exhibiting preferential responses to intruder males versus females but only rare examples of behavior-specific activation. Unexpectedly, many VMHvl T-types comprise a mixed population of neurons with different projection target preferences. Overall our analysis revealed that, surprisingly, few VMHvl T-types exhibit a clear correspondence with behavior-specific activation and connectivity.