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Background JUNO and IZUMO1 are the first receptor-ligand protein pairs discovered to be essential for sperm-oocyte fusion; their interaction is indispensable for fertilization. Methods PCR was used to clone the full-length DNA sequence of the Juno gene in sheep. The single nucleotide polymorphism (SNP) loci of Juno were genotyped by Sequenom MassARRAY®. PCR combined with rapid amplification of cDNA Ends were used to clone the full-length cDNA sequence of Juno and Izumo1. Reverse transcriptase-PCR (RT-PCR) and real time-quantitative-PCR (RT-qPCR) were used to analyze the genes’ expression in tissues of sheep, and single cell RNA-seq was used to analyze the genes’ expression in oocytes, granulosa cells and follicular theca of polytocous and monotocous Small Tail Han ewes. Bioinformatics was used to analyze advanced structure and phylogeny of JUNO and IZUMO1 proteins. Results The full-length DNA sequence of the Juno gene in sheep was cloned and nine SNPs were screened. We found a significant association between the g.848253 C > A locus of Juno and litter size of Small Tail Han sheep (P Juno and Izumo1 genes from Small Tail Han sheep were obtained. We found a new segment of the Izumo1 CDS consisting of 35 bp, and we confirmed the Izumo1 gene has 9 exons, not 8. RT-qPCR showed that Juno and Izumo1 genes were highly expressed in ovarian and testicular tissues, respectively (P Juno was specifically expressed in oocytes, but not in granulosa cells or follicular theca, while Izumo1 displayed little to no expression in all three cell types. There was no difference in expression of the Juno gene in oocyte and ovarian tissue in sheep with different litter sizes, indicating expression of Juno is not related to litter size traits. Bioinformatic analysis revealed the g.848253 C > A locus of Juno results in a nonconservative missense point mutation leading to a change from Phe to Leu at position 219 in the amino acid sequence. Conclusions For the first time, this study systematically analyzed the expression, structure and function of Juno and Izumo1 genes and their encoded proteins in Small Tail Han sheep, providing the basis for future studies of the regulatory mechanisms of Juno and Izumo1 genes.

The fate of mesenchymal stem cells (MSCs) is regulated by biological, physical and chemical signals. Developments in biotechnology and materials science promoted the occurrence of bioactive materials which can provide physical and chemical signals for MSCs to regulate their fate. In order to design and synthesize materials that can precisely regulate the fate of MSCs, the relationship between the properties of materials and the fate of mesenchymal stem cells need to be clarified, in which the detection of the fate of mesenchymal stem cells plays an important role. In the past 30 years, a series of detection technologies have been developed to detect the fate of MSCs regulated by bioactive materials, among which high-throughput technology has shown great advantages due to its ability to detect large amounts of data at one time. In this review, the latest research progresses of detecting the fate of MSCs regulated by bone bioactive materials (BBMs) are systematically reviewed from traditional technology to high-throughput technology which is emphasized especially. Moreover, current problems and the future development direction of detection technologies of the MSCs fate regulated by BBMs are prospected. The aim of this review is to provide a detection technical framework for researchers to establish the relationship between the properties of BMMs and the fate of MSCs, so as to help researchers to design and synthesize BBMs better which can precisely regulate the fate of MSCs., Graphical abstract The fate of MSCs can be regulated by bone bioactive materials (BBMs). Herein, traditional technology and highthroughput technology which can be used to detect the fate of MSCs regulated by BBMs are reviewed comprehensively and systematically.Image 1, Highlights • In order to design and synthesize materials that can precisely regulate the fate of MSCs, the relationship between the properties of materials and the fate of mesenchymal stem cells need to be clarified. • Current problems and the future development direction of detection technologies of the MSCs fate regulated by BBMs are prospected. •The aim of this review is to provide a detection technical framework for researchers to establish the relationship between the properties of BMMs and the fate of MSCs, so as to help researchers to design and synthesize BBMs better which can precisely regulate the fate of MSCs.

Objectives Bacterial infection remains one of the greatest threats to human health. However, how human hosts respond to bacterial infection has not been thoroughly understood. Better understanding of this response will improve human health. Methods Here, we conducted an investigation on host response to bacterial infection using unperturbed clinical samples and single-cell RNA-Seq (scRNA-Seq) technology. To evaluate immune alteration upon bacterial infection in scRNA-Seq data of peripheral blood mononuclear cells (PBMCs), we developed a barcode analytical framework named PBMCode. Results Using this PBMCode framework, we revealed profound immune alteration in peripheral blood under bacterial infection, including the emergence of natural killer T (NKT) cell cluster, reduction of B cell population, and considerable changes in T cells and monocytes. In addition, we also observed a large quantity of low-density neutrophils. Conclusions Our investigation on single cells provided unprecedented details in the alteration of both cell population and cell state under bacterial infection. These findings may be relevant to clinical decisions. The complexity of host response to bacterial infection revealed by scRNA-Seq deserves further attention in future studies.

Alignment of scRNA-Seq data are the first and one of the most critical steps of the scRNA-Seq analysis workflow, and thus the choice of proper aligners is of paramount importance. Recently, STAR an alignment method and Kallisto a pseudoalignment method have both gained a vast amount of popularity in the single cell sequencing field. However, an unbiased third-party comparison of these two methods in scRNA-Seq is lacking. Here we conduct a systematic comparison of them on a variety of Drop-seq, Fluidigm and 10x genomics data, from the aspects of gene abundance, alignment accuracy, as well as computational speed and memory use. We observe that STAR globally produces more genes and higher gene-expression values, compared to Kallisto, as well as Bowtie2, another popular alignment method for bulk RNA-Seq. STAR also yields higher correlations of the Gini index for the genes with RNA-FISH validation results. Using 10x genomics PBMC 3K scRNA-Seq and mouse cortex single nuclei RNA-Seq data, STAR shows similar or better cell-type annotation results, by detecting a larger subset of known gene markers. However, the gain of accuracy and gene abundance of STAR alignment comes with the price of significantly slower computation time (4 folds) and more memory (7.7 folds), compared to Kallisto.

Graphical abstract, The brain is a highly complex organ consisting of numerous types of cells with ample diversity at the epigenetic level to achieve distinct gene expression profiles. During neuronal cell specification, transcription factors (TFs) form regulatory modules with chromatin remodeling proteins to initiate the cascade of epigenetic changes. Currently, little is known about brain epigenetic regulatory modules and how they regulate gene expression in a cell-type specific manner. To infer TFs involved in neuronal specification, we applied a recursive motif search approach on the differentially methylated regions identified from single-cell methylomes. The epigenetic transcription regulatory modules (ETRM), including EGR1 and MEF2C, were predicted and the co-expression of TFs in ETRMs were examined with RNA-seq data from single or sorted brain cells using a conditional probability matrix. Lastly, computational predications were validated with EGR1 ChIP-seq data. In addition, methylome and RNA-seq data generated from Egr1 knockout mice supported the essential role of EGR1 in brain epigenome programming, in particular for excitatory neurons. In summary, we demonstrated that brain single cell methylome and RNA-seq data can be integrated to gain a better understanding of how ETRMs control cell specification. The analytical pipeline implemented in this study is freely accessible in the Github repository (https://github.com/Gavin-Yinld/brain_TF).

Significance We here present a transcriptional map of peripheral nerve cells in health and autoimmunity. Identified marker genes of nonmyelinating Schwann cells and nerve-associated fibroblasts will facilitate a better understanding of the complex cellular architecture of peripheral nerves. The two distinct populations of nerve-resident homeostatic myeloid cells suggest an unexpectedly unique and heterogeneous local immune repertoire in peripheral nerves with signs of heterogeneous ontogenetic origin. Complex changes of local cell–cell communication networks indicate autoimmune neuritis as a disease affecting “immune networks” rather than single cell types. The findings also suggest that immunological features are partially shared and conserved across different parts of the nervous system., Peripheral nerves contain axons and their enwrapping glia cells named Schwann cells (SCs) that are either myelinating (mySCs) or nonmyelinating (nmSCs). Our understanding of other cells in the peripheral nervous system (PNS) remains limited. Here, we provide an unbiased single cell transcriptomic characterization of the nondiseased rodent PNS. We identified and independently confirmed markers of previously underappreciated nmSCs and nerve-associated fibroblasts. We also found and characterized two distinct populations of nerve-resident homeostatic myeloid cells that transcriptionally differed from central nervous system microglia. In a model of chronic autoimmune neuritis, homeostatic myeloid cells were outnumbered by infiltrating lymphocytes which modulated the local cell–cell interactome and induced a specific transcriptional response in glia cells. This response was partially shared between the peripheral and central nervous system glia, indicating common immunological features across different parts of the nervous system. Our study thus identifies subtypes and cell-type markers of PNS cells and a partially conserved autoimmunity module induced in glia cells.

Cell is the fundamental structural and functional unit of complex multicellular organisms. Conventional methods which involve average analysis of cells in bulk populations can undermine physiologically significant cell populations, whereas analysis of cells at a single cell level may reveal unique biomarkers and other mechanisms that govern the genotype and phenotype in various physiological processes in presumed homogenous cell populations. Cellular abnormalities such as irregularities in cellular mechanisms have been linked to human aging and other major diseases including neurodegenerative, vascular, autoimmune, and cancer. Aging is a functional decline associated with various diseases in an organism, majorly arising from cellular abnormalities. Single cell analysis (SCA) which involves isolation and study of single cell proteomics, genomics, transcriptomics and metabolomics which enables research of cellular abnormalities with a molecular resolution, is gaining recognition in the research of human aging and disease. The advances in SCA are producing breakthrough information about cellular heterogeneity, disease progression, cellular microenvironment and its interactions, early diagnostics, improving precision medicine through high throughput drug screening and discovery of novel biomarkers; combinedly, these advances exhibit the potential of SCA to study of human aging and disease. Primarily, we review the role of SCA in understanding cellular mechanisms involved in aging and other major diseases including neurological, vascular, autoimmunity and cancer. Secondly, we also include review of SCA role in studying cell adhesion mechanisms which are involved in tissue development and maintenance and disease progression. Finally, SCA potential to empower precision medicine and its overall challenges along with future directions are discussed.

Objective Homo- or heterodimerization of G protein–coupled receptors (GPCRs) generally alters the normal functioning of these receptors and mediates their responses to a variety of physiological stimuli in vivo. It is well known that melanocortin-3 receptor (MC3R) and melanocortin-4 receptor (MC4R) are key regulators of appetite and energy homeostasis in the central nervous system (CNS). However, the GPCR partners of MC3R and MC4R are not well understood. Our objective is to analyze single cell RNA-seq datasets of the hypothalamus to explore and identify novel GPCR partners of MC3R and MC4R and examine the pharmacological effect on the downstream signal transduction and membrane translocation of melanocortin receptors. Methods We conducted an integrative analysis of multiple single cell RNA-seq datasets to reveal the expression pattern and correlation of GPCR families in the mouse hypothalamus. The emerging GPCRs with important metabolic functions were selected for cloning and co-immunoprecipitation validation. The positive GPCR partners were then tested for the pharmacological activation, competitive binding assay and surface translocation ELISA experiments. Results Based on the expression pattern of GPCRs and their function enrichment results, we narrowed down the range of potential GPCR interaction with MC3R and MC4R for further confirmation. Co-immunoprecipitation assay verified 23 and 32 novel GPCR partners that interacted with MC3R and MC4R in vitro. The presence of these GPCR partners exhibited different effects in the physiological regulation and signal transduction of MC3R and MC4R. Conclusions This work represented the first large-scale screen for the functional GPCR complex of central melanocortin receptors and defined a composite metabolic regulatory GPCR network of the hypothalamic nucleuses., Highlights • More GPCRs are found in the neurons than other cell types in the mouse hypothalamus, and their functions are significantly enriched in energy homeostasis and metabolism. • A total of 23 and 32 GPCRs are confirmed to be novel interacting partners of MC3R and MC4R in vitro, respectively. • The hetero-dimerization of identified GPCRs with MC3R and MC4R alters the signal transduction and surface translocation.

Breast cancer is the most commonly diagnosed cancer in the world, with triple-negative breast cancer (TNBC) making up 12% of these diagnoses. TNBC tumours are highly heterogeneous in both inter-tumour and intra-tumour gene expression profiles, where they form subclonal populations of varying levels of aggressiveness. These aspects make it difficult to study and treat TNBC, requiring further research into tumour heterogeneity as well as potential therapeutic targets and biomarkers. Recently, it was discovered that the majority of the transcribed genome comprises non-coding RNAs, in particular long non-coding RNAs (lncRNAs). LncRNAs are transcripts of &gt, 200 nucleotides in length that do not encode a protein. They have been characterised as regulatory molecules and their expression can be associated with a malignant phenotype. We set out to explore TNBC tumour heterogeneity in vivo at a single cell level to investigate whether lncRNA expression varies across different cells within the tumour, even if cells are coming from the same cell line, and whether lncRNA expression is sufficient to define cellular subpopulations. We applied single-cell expression profiling due to its ability to capture expression signals of lncRNAs expressed in small subpopulations of cells. Overall, we observed most lncRNAs to be expressed at low, but detectable levels in TNBC xenografts, with a median of 25 lncRNAs detected per cell. LncRNA expression alone was insufficient to define a subpopulation of cells, and lncRNAs showed highly heterogeneous expression patterns, including ubiquitous expression, subpopulation-specific expression, and a hybrid pattern of lncRNAs expressed in several, but not all subpopulations. These findings reinforce that transcriptionally defined tumour cell subpopulations can be identified in cell-line derived xenografts, and uses single-cell RNA-seq (scRNA-seq) to detect and characterise lncRNA expression across these subpopulations in xenografted tumours. Future studies will aim to investigate the spatial distribution of lncRNAs within xenografts and patient tissues, and study the potential of subclone-specific lncRNAs as new therapeutic targets and/or biomarkers.

Background: BRCA1 plays critical roles in mammary gland development and mammary tumorigenesis. And loss of BRCA1 induces mammary tumors in a stochastic manner. These tumors present great heterogeneity at both intertumor and intratumor levels. Methods: To comprehensively elucidate the heterogeneity of BRCA1 deficient mammary tumors and the underlying mechanisms for tumor initiation and progression, we conducted bulk and single cell RNA sequencing (scRNA-seq) on both mammary gland cells and mammary tumor cells isolated from Brca1 knockout mice. Results: We found the BRCA1 deficient tumors could be classified into four subtypes with distinct molecular features and different sensitivities to anti-cancer drugs at the intertumor level. Whereas within the tumors, heterogeneous subgroups were classified mainly due to the different activities of cell proliferation, DNA damage response/repair and epithelial-to-mesenchymal transition (EMT). Besides, we reconstructed the BRCA1 related mammary tumorigenesis to uncover the transcriptomes alterations during this process via pseudo-temporal analysis of the scRNA-seq data. Furthermore, from candidate markers for BRCA1 mutant tumors, we discovered and validated one oncogene Mrc2, whose loss could reduce mammary tumor growth in vitro and in vivo. Conclusion: Our study provides a useful resource for better understanding of mammary tumorigenesis induced by BRCA1 deficiency.

BackgroundSingle-cell RNA sequencing (scRNA-seq) has led to remarkable progress in our understanding of tissue heterogeneity in health and disease. Recently, the need for scRNA-seq sample fixation has emerged in many scenarios, such as when samples need long-term transportation, or when experiments need to be temporally synchronized. Methanol fixation is a simple and gentle method that has been routinely applied in scRNA-sEq. Yet, concerns remain that fixation may result in biases which may change the RNA-seq outcome.ResultsWe adapted an existing methanol fixation protocol and performed scRNA-seq on both live and methanol fixed cells. Analyses of the results show methanol fixation can faithfully preserve biological related signals, while the discrepancy caused by fixation is subtle and relevant to library construction methods. By grouping transcripts based on their lengths and GC content, we find that transcripts with different features are affected by fixation to different degrees in full-length sequencing data, while the effect is alleviated in Drop-seq result.ConclusionsOur deep analysis reveals the effects of methanol fixation on sample RNA integrity and elucidates the potential consequences of using fixation in various scRNA-seq experiment designs.

Background: Vascular smooth muscle cells (VSMC) exhibit phenotypic plasticity in atherosclerotic plaques, and among other approaches, has been modeled in vitro by cholesterol loading. Methods: Meta-analysis of scRNA-seq data from VSMC lineage traced cells across five experiments of murine atherosclerosis was performed. In vivo expression profiles were compared to three in vitro datasets of VSMCs loaded with cholesterol and three datasets of polarized macrophages. Results: We identified 24 cell clusters in the meta-analysis of single cells from mouse atherosclerotic lesions with notable heterogeneity across studies, especially for macrophage populations. Trajectory analysis of VSMC lineage positive cells revealed several possible paths of state transitions with one traversing from contractile VSMC to macrophages by way of a proliferative cell cluster. Transcriptome comparisons between in vivo and in vitro states underscored that data from three in vitro cholesterol-treated VSMC experiments did not mirror cell state transitions observed in vivo. However, all in vitro macrophage profiles analyzed (M1, M2, and oxLDL) were more similar to in vivo profiles of macrophages than in vitro VSMCs were to in vivo profiles of VSMCs. oxLDL loaded macrophages showed the most similarity to in vivo states. In contrast to the in vitro data, comparison between mouse and human in vivo data showed many similarities. Conclusions: Identification of the sources of variation across single cell datasets in atherosclerosis will be an important step towards understanding VSMC fate transitions in vivo. Also, we conclude that cholesterol-loading in vitro is insufficient to model the VSMC cell state transitions observed in vivo, which underscores the need to develop better cell models. Mouse models, however, appear to reproduce a number of the features of VSMCs in human plaques

Funder: National Institute for Health Research; Id: http://dx.doi.org/10.13039/501100014338, Funder: NHS Blood and Transplant; Id: http://dx.doi.org/10.13039/100009033, Funder: Bristol‐Myers Squibb; Id: http://dx.doi.org/10.13039/100002491, Funder: European Commission; Id: http://dx.doi.org/10.13039/100013273, Background: Megakaryocytes (MKs) originate from cells immuno‐phenotypically indistinguishable from hematopoietic stem cells (HSCs), bypassing intermediate progenitors. They mature within the adult bone marrow and release platelets into the circulation. Until now, there have been no transcriptional studies of primary human bone marrow MKs. Objectives: To characterize MKs and HSCs from human bone marrow using single‐cell RNA sequencing, to investigate MK lineage commitment, maturation steps, and thrombopoiesis. Results: We show that MKs at different levels of polyploidization exhibit distinct transcriptional states. Although high levels of platelet‐specific gene expression occur in the lower ploidy classes, as polyploidization increases, gene expression is redirected toward translation and posttranslational processing transcriptional programs, in preparation for thrombopoiesis. Our findings are in keeping with studies of MK ultrastructure and supersede evidence generated using in vitro cultured MKs. Additionally, by analyzing transcriptional signatures of a single HSC, we identify two MK‐biased HSC subpopulations exhibiting unique differentiation kinetics. We show that human bone marrow MKs originate from these HSC subpopulations, supporting the notion that they display priming for MK differentiation. Finally, to investigate transcriptional changes in MKs associated with stress thrombopoiesis, we analyzed bone marrow MKs from individuals with recent myocardial infarction and found a specific gene expression signature. Our data support the modulation of MK differentiation in this thrombotic state. Conclusions: Here, we use single‐cell sequencing for the first time to characterize the human bone marrow MK transcriptome at different levels of polyploidization and investigate their differentiation from the HSC.

Background The development of multiple myeloma (MM) is considered to involve a multistep transformation process, but the role of cytogenetic abnormalities and molecular alterations in determining the cell fate of multiple myeloma (MM) remains unclear. Here, we have analyzed single cell RNA-seq data and bulk gene profiles to reveal a novel signature associated with MM development. Methods The scRNA-seq data from GSE118900 was used to profile the transcriptomes of cells from MM patients at different stages. Pseudotemporal ordering of the single cells was performed using Monocle package to feature distinct transcriptomic states of the developing MM cells. The bulk microarray profiles from GSE24080 and GSE9782 were applied to identify a signature associated with MM development. Results The 597 cells were divided into 7 clusters according to different risk levels. They were initiated mainly from monoclonal gammopathy of undetermined significance (MGUS), newly diagnosed MM (NDMM), or relapsed and/or refractory myeloma (RRMM) with cytogenetically favorable t(11;14), moved towards the cells from smoldering MM (SMM) or NDMM without t(11;14) or t(4;14), and then finally to cells from SMM or RRMM with t(4;14). Based on the markers identified in the late stage, the bulk data was used to develop a 20-gene signature stratifying patients into high and low-risk groups (GSE24080: HR = 3.759, 95% CI 2.746–5.145; GSE9782: HR = 2.612, 95% CI 1.894–3.603), which was better than the previously published gene signatures (EMC92, UAMS70, and UAMS17) and International Staging System. This signature also succeeded in predicting the clinical outcome of patients treated with bortezomib (HR = 2.884, 95% CI 1.994–4.172, P = 1.89e−8). The 20 genes were further verified by quantitative real-time polymerase chain reaction using samples obtained from the patients with MM. Conclusion Our comprehensive analyses offered new insights in MM development, and established a 20-gene signature as an independent biomarker for MM.

Background Whole lung tissue transcriptomic profiling studies in chronic obstructive pulmonary disease (COPD) have led to the identification of several genes associated with the severity of airflow limitation and/or the presence of emphysema, however, the cell types driving these gene expression signatures remain unidentified. Methods To determine cell specific transcriptomic changes in severe COPD, we conducted single-cell RNA sequencing (scRNA seq) on n = 29,961 cells from the peripheral lung parenchymal tissue of nonsmoking subjects without underlying lung disease (n = 3) and patients with severe COPD (n = 3). The cell type composition and cell specific gene expression signature was assessed. Gene set enrichment analysis (GSEA) was used to identify the specific cell types contributing to the previously reported transcriptomic signatures. Results T-distributed stochastic neighbor embedding and clustering of scRNA seq data revealed a total of 17 distinct populations. Among them, the populations with more differentially expressed genes in cases vs. controls (log fold change >|0.4| and FDR = 0.05) were: monocytes (n = 1499); macrophages (n = 868) and ciliated epithelial cells (n = 590), respectively. Using GSEA, we found that only ciliated and cytotoxic T cells manifested a trend towards enrichment of the previously reported 127 regional emphysema gene signatures (normalized enrichment score [NES] = 1.28 and = 1.33, FDR = 0.085 and = 0.092 respectively). Among the significantly altered genes present in ciliated epithelial cells of the COPD lungs, QKI and IGFBP5 protein levels were also found to be altered in the COPD lungs. Conclusions scRNA seq is useful for identifying transcriptional changes and possibly individual protein levels that may contribute to the development of emphysema in a cell-type specific manner.

Background Classic dendritic cells (cDCs) play a central role in the immune system by processing and presenting antigens to activate T cells, and consist of two major subsets: CD141+ cDC (cDC1) and CD1c+ cDC (cDC2). A population of migratory precursor cells, the pre-cDCs, is the immediate precursors to both cDC subsets. Previous studies showed that there were two pre-committed pre-cDC subpopulations. However, the key molecular drivers of pre-commitment in human pre-cDCs were not investigated. Results To identify the key molecular drivers for pre-commitment in human pre-cDCs, we performed single cell RNA sequencing (RNA-Seq) of two cDC subsets and pre-cDCs, and bulk RNA-Seq of pre-cDCs and cDCs from human peripheral blood. We found that pre-DC subpopulations cannot be separated by either variable genes within pre-cDCs or differentially expressed genes between cDC1 and cDC2. In contrast, they were separated by 16 transcription factors that are themselves differentially expressed or have regulated targets enriched in the differentially expressed genes between bulk cDC1 and cDC2, with one subpopulation close to cDC1 and the other close to cDC2. More importantly, these two pre-cDC sub-populations are correlated with ratio of IRF8 to IRF4 expression level more than their individual expression level. We also verified these findings using three recently published datasets. Conclusions In this study, we demonstrate that single cell transcriptome profiling can reveal pre-cDCs differentiation map, and our results suggest the concept that combinatorial dose of transcription factors determines cell differentiation fate. Electronic supplementary material The online version of this article (10.1186/s12860-019-0199-y) contains supplementary material, which is available to authorized users.

The implications of stem cell heterogeneity for disease pathogenesis and therapy are poorly defined. JAK2V617F+ myeloproliferative neoplasms (MPNs), harboring the same mutation in hematopoietic stem cells (HSCs), display diverse phenotypes, including polycythemia vera (PV), essential thrombocythemia (ET), and primary myelofibrosis (PMF). These chronic malignant disorders are ideal models to analyze the pathological consequences of stem cell heterogeneity. Single-cell gene expression profiling with parallel mutation detection demonstrated that the megakaryocyte (Mk)-primed HSC subpopulation expanded significantly with enhanced potential in untreated individuals with JAK2V617F+ ET, driven primarily by the JAK2 mutation and elevated interferon signaling. During treatment, mutant HSCs were targeted preferentially in the Mk-primed HSC subpopulation. Interestingly, homozygous mutant HSCs were forced to re-enter quiescence, whereas their heterozygous counterparts underwent apoptosis. This study provides important evidence for the association of stem cell heterogeneity with the pathogenesis and therapeutic response of a malignant disease.

Single-cell RNA sequencing of the bronchoalveolar lavage fluid (BALF) samples from COVID-19 patients has enabled us to examine gene expression changes of human tissue in response to the SARS-CoV-2 virus infection. However, the underlying mechanisms of COVID-19 pathogenesis at single-cell resolution, its transcriptional drivers, and dynamics require further investigation. In this study, we applied machine learning algorithms to infer the trajectories of cellular changes and identify their transcriptional programs. Our study generated cellular trajectories that show the COVID-19 pathogenesis of healthy-to-moderate and healthy-to-severe on macrophages and T cells, and we observed more diverse trajectories in macrophages compared to T cells. Furthermore, our deep-learning algorithm DrivAER identified several pathways (e.g., xenobiotic pathway and complement pathway) and transcription factors (e.g., MITF and GATA3) that could be potential drivers of the transcriptomic changes for COVID-19 pathogenesis and the markers of the COVID-19 severity. Moreover, macrophages-related functions corresponded more to the disease severity compared to T cells-related functions. Our findings more proficiently dissected the transcriptomic changes leading to the severity of a COVID-19 infection.

Objective: Early treatment-naïve rheumatoid arthritis (RA) has defective regulatory T (Treg) cells and increased inflammation response. In this study, we aim to illustrate the regulation of Treg cells in pathogenesis of early rheumatoid arthritis by arsenic trioxide (As2O3).Methods: We studied the effects of As2O3 on gene expression in early treatment-naïve RA Treg cells with single cell RNA-seq (scRNA-seq). Treg cells were sorted from peripheral blood mononuclear cells (PBMCs) and purified by fluorescence-activated cell sorting (FACS) and cultured with or without As2O3 (at 0.1 µM) for 24 h. Total RNA was isolated and sequenced, and functional analysis was performed against the Gene Ontology (GO) database. Results for selected genes were confirmed with RT-qPCR.Results: As2O3 exerts no significant effect on CD4+ T-cell apoptosis under physical condition, and selectively modulate CD4+ T cells toward Treg cells not Th17 cells under special polarizing stimulators. As2O3 increased the expression of 200 and reduced that of 272 genes with fold change (FC) 2.0 or greater. Several genes associated with inflammation, Treg-cell activation and differentiation as well as glucose and amino acids metabolism were among the most strongly affected genes. GO function analysis identified top ten ranked significant biological process (BPs), molecular functions (MFs), and cell components (CCs) in treatment and nontreatment Treg cells. In GO analysis, genes involved in the immunoregulation, cell apoptosis and cycle, inflammation, and cellular metabolism were enriched among the significantly affected genes. The KEGG pathway enrichment analysis identified the forkhead box O (FoxO) signal pathway, apoptosis, cytokine–cytokine receptor interaction, cell cycle, nuclear factor-kappa B (NF-κB) signaling pathway, tumor necrosis factor α (TNF-α), p53 signaling pathway, and phosphatidylinositol 3′-kinase (PI3K)-Akt signaling pathway were involved in the pathogenesis of early treatment-naïve RA.Conclusion: This is the first study investigating the genome-wide effects of As2O3 on the gene expression of treatment-naïve Treg cells. In addition to clear anti-inflammatory and immunoregulation effects, As2O3 affect amino acids and glucose metabolism in Treg cells, an observation that might be particularly important in the metabolic phenotype of treatment-naïve RA.

Purpose Single cell (sc) analyses of key embryonic, fetal and adult stages were performed to generate a comprehensive single cell atlas of all the corneal and adjacent conjunctival cell types from development to adulthood. Methods Four human adult and seventeen embryonic and fetal corneas from 10 to 21 post conception week (PCW) specimens were dissociated to single cells and subjected to scRNA- and/or ATAC-Seq using the 10x Genomics platform. These were embedded using Uniform Manifold Approximation and Projection (UMAP) and clustered using Seurat graph-based clustering. Cluster identification was performed based on marker gene expression, bioinformatic data mining and immunofluorescence (IF) analysis. RNA interference, IF, colony forming efficiency and clonal assays were performed on cultured limbal epithelial cells (LECs). Results scRNA-Seq analysis of 21,343 cells from four adult human corneas and adjacent conjunctivas revealed the presence of 21 cell clusters, representing the progenitor and differentiated cells in all layers of cornea and conjunctiva as well as immune cells, melanocytes, fibroblasts, and blood/lymphatic vessels. A small cell cluster with high expression of limbal progenitor cell (LPC) markers was identified and shown via pseudotime analysis to give rise to five other cell types representing all the subtypes of differentiated limbal and corneal epithelial cells. A novel putative LPCs surface marker, GPHA2, expressed on the surface of 0.41% ± 0.21 of the cultured LECs, was identified, based on predominant expression in the limbal crypts of adult and developing cornea and RNAi validation in cultured LECs. Combining scRNA- and ATAC-Seq analyses, we identified multiple upstream regulators for LPCs and demonstrated a close interaction between the immune cells and limbal progenitor cells. RNA-Seq analysis indicated the loss of GPHA2 expression and acquisition of proliferative limbal basal epithelial cell markers during ex vivo LEC expansion, independently of the culture method used. Extending the single cell analyses to keratoconus, we were able to reveal activation of collagenase in the corneal stroma and a reduced pool of limbal suprabasal cells as two key changes underlying the disease phenotype. Single cell RNA-Seq of 89,897 cells obtained from embryonic and fetal cornea indicated that during development, the conjunctival epithelium is the first to be specified from the ocular surface epithelium, followed by the corneal epithelium and the establishment of LPCs, which predate the formation of limbal niche by a few weeks. Conclusions Our scRNA-and ATAC-Seq data of developing and adult cornea in steady state and disease conditions provide a unique resource for defining genes/pathways that can lead to improvement in ex vivo LPCs expansion, stem cell differentiation methods and better understanding and treatment of ocular surface disorders., Graphical abstract Schematic presentation of main techniques and findings presented in this manuscript.Image 1

Gene duplication is a key evolutionary phenomenon, prevalent in all organisms but particularly so in plants, where whole genome duplication (WGD; polyploidy) is a major force in genome evolution. Much effort has been expended in attempting to understand the evolution of duplicate genes, addressing such questions as why some paralog pairs rapidly return to single copy status whereas, in other pairs, both paralogs are retained and may diverge in expression pattern or function. The effect of a gene – its site of expression and thus the initial locus of its function – occurs at the level of a cell comprising a single cell type at a given state of the cell’s development. Using Arabidopsis thaliana single cell transcriptomic data we categorized patterns of expression for 11,470 duplicate gene pairs across 36 cell clusters comprising nine cell types and their developmental states. Among these 11,470 pairs, 10,187 (88.8%) had at least one copy expressed in at least one of the 36 cell clusters. Pairs produced by WGD more often had both paralogs expressed in root cells than did pairs produced by small scale duplications. Three quarters of gene pairs expressed in the 36 cell clusters (7,608/10,187) showed extreme expression bias in at least one cluster, including 352 cases of reciprocal bias, a pattern consistent with expression subfunctionalization. More than twice as many pairs showed reciprocal expression bias between cell states than between cell types or between roots and leaves. A group of 33 gene pairs with reciprocal expression bias showed evidence of concerted divergence of gene networks in stele vs. epidermis. Pairs with both paralogs expressed without bias were less likely to have paralogs with divergent mutant phenotypes; such bias-free pairs showed evidence of preservation by maintenance of dosage balance. Overall, we found considerable evidence of shifts in gene expression following duplication, including in >80% of pairs encoding 7,653 genes expressed ubiquitously in all root cell types and states for which we inferred the polarity of change.

Severe COVID-19 patients can show respiratory failure, T-cell reduction, and cytokine release syndrome (CRS), which can be fatal in both young and aged patients and is a major concern of the pandemic. However, the pathogenetic mechanisms of CRS in COVID-19 are poorly understood. Here we show single cell-level mechanisms for T-cell dysregulation in severe SARS-CoV-2 infection, and thereby demonstrate the mechanisms underlying T-cell hyperactivation and paralysis in severe COVID-19 patients. By in silico sorting CD4+ T-cells from a single cell RNA-seq dataset, we found that CD4+ T-cells were highly activated and showed unique differentiation pathways in the lung of severe COVID-19 patients. Notably, those T-cells in severe COVID-19 patients highly expressed immunoregulatory receptors and CD25, whilst repressing the expression of the transcription factor FOXP3 and interestingly, both the differentiation of regulatory T-cells (Tregs) and Th17 was inhibited. Meanwhile, highly activated CD4+ T-cells express PD-1 alongside macrophages that express PD-1 ligands in severe patients, suggesting that PD-1-mediated immunoregulation was partially operating. Furthermore, we show that CD25+ hyperactivated T-cells differentiate into multiple helper T-cell lineages, showing multifaceted effector T-cells with Th1 and Th2 characteristics. Lastly, we show that CD4+ T-cells, particularly CD25-expressing hyperactivated T-cells, produce the protease Furin, which facilitates the viral entry of SARS-CoV-2. Collectively, CD4+ T-cells from severe COVID-19 patients are hyperactivated and FOXP3-mediated negative feedback mechanisms are impaired in the lung, while activated CD4+ T-cells continue to promote further viral infection through the production of Furin. Therefore, our study proposes a new model of T-cell hyperactivation and paralysis that drives pulmonary damage, systemic CRS and organ failure in severe COVID-19 patients.

Among the brainstem raphe nuclei, the dorsal raphe nucleus (DR) contains the greatest number of Pet1-lineage neurons, a predominantly serotonergic group distributed throughout DR subdomains. These neurons collectively regulate diverse physiology and behavior and are often therapeutically targeted to treat affective disorders. Characterizing Pet1 neuron molecular heterogeneity and relating it to anatomy is vital for understanding DR functional organization, with potential to inform therapeutic separability. Here we use high-throughput and DR subdomain-targeted single-cell transcriptomics and intersectional genetic tools to map molecular and anatomical diversity of DR-Pet1 neurons. We describe up to fourteen neuron subtypes, many showing biased cell body distributions across the DR. We further show that P2ry1-Pet1 DR neurons – the most molecularly distinct subtype – possess unique efferent projections and electrophysiological properties. These data complement and extend previous DR characterizations, combining intersectional genetics with multiple transcriptomic modalities to achieve fine-scale molecular and anatomic identification of Pet1 neuron subtypes.

Cell clustering is one of the most common routines in single cell RNA-seq data analyses, for which a number of specialized methods are available. The evaluation of these methods ignores an important biological characteristic that the structure for a population of cells is hierarchical, which could result in misleading evaluation results. In this work, we develop two new metrics that take into account the hierarchical structure of cell types. We illustrate the application of the new metrics in constructed examples as well as several real single cell datasets and show that they provide more biologically plausible results.

The COVID-19 pandemic demands assimilation of all biomedical knowledge to decode mechanisms of pathogenesis. Despite the recent renaissance in neural networks, a platform for the real-time synthesis of the exponentially growing biomedical literature and deep omics insights is unavailable. Here, we present the nferX platform for dynamic inference from over 45 quadrillion possible conceptual associations from unstructured text, and triangulation with insights from single-cell RNA-sequencing, bulk RNA-seq and proteomics from diverse tissue types. A hypothesis-free profiling of ACE2 suggests tongue keratinocytes, olfactory epithelial cells, airway club cells and respiratory ciliated cells as potential reservoirs of the SARS-CoV-2 receptor. We find the gut as the putative hotspot of COVID-19, where a maturation correlated transcriptional signature is shared in small intestine enterocytes among coronavirus receptors (ACE2, DPP4, ANPEP). A holistic data science platform triangulating insights from structured and unstructured data holds potential for accelerating the generation of impactful biological insights and hypotheses.

Summary Acute myeloid leukemia (AML) is a hematopoietic malignancy caused by recurrent mutations in genes encoding transcriptional, chromatin, and/or signaling regulators. The t(8;21) translocation generates the aberrant transcription factor RUNX1-ETO (RUNX1-RUNX1T1), which by itself is insufficient to cause disease. t(8;21) AML patients show extensive chromatin reprogramming and have acquired additional mutations. Therefore, the genomic and developmental effects directly and solely attributable to RUNX1-ETO expression are unclear. To address this, we employ a human embryonic stem cell differentiation system capable of forming definitive myeloid progenitor cells to express RUNX1-ETO in an inducible fashion. Induction of RUNX1-ETO causes extensive chromatin reprogramming by interfering with RUNX1 binding, blocks differentiation, and arrests cellular growth, whereby growth arrest is reversible following RUNX1-ETO removal. Single-cell gene expression analyses show that RUNX1-ETO induction alters the differentiation of early myeloid progenitors, but not of other progenitor types, indicating that oncoprotein-mediated transcriptional reprogramming is highly target cell specific., Graphical Abstract, Highlights • RUNX1-ETO reversibly arrests the growth of human ESC-derived early myeloid cells • RUNX1-ETO disrupts global RUNX1 binding and deregulates RUNX1 target genes • RUNX1-ETO blocks myeloid differentiation by rapidly downregulating SPI1 and CEBPA • The impact of RUNX1-ETO induction is cell type specific, This study uses human-embryonic-stem-cell-derived definitive human blood progenitors to gain insight into the earliest events following leukemic oncogene expression. Nafria et al. show that induction of RUNX1-ETO expression rapidly reprograms chromatin, disrupts global RUNX1 binding, and arrests growth and/or differentiation specifically in early myeloid progenitor cells.

Bone marrow mesenchymal lineage cells are a heterogeneous cell population involved in bone homeostasis and diseases such as osteoporosis. While it is long postulated that they originate from mesenchymal stem cells, the true identity of progenitors and their in vivo bifurcated differentiation routes into osteoblasts and adipocytes remain poorly understood. Here, by employing large scale single cell transcriptome analysis, we computationally defined mesenchymal progenitors at different stages and delineated their bi-lineage differentiation paths in young, adult and aging mice. One identified subpopulation is a unique cell type that expresses adipocyte markers but contains no lipid droplets. As non-proliferative precursors for adipocytes, they exist abundantly as pericytes and stromal cells that form a ubiquitous 3D network inside the marrow cavity. Functionally they play critical roles in maintaining marrow vasculature and suppressing bone formation. Therefore, we name them marrow adipogenic lineage precursors (MALPs) and conclude that they are a newly identified component of marrow adipose tissue.

Murine muscle stem cells (MuSCs) experience a transition from quiescence to activation that is required for regeneration, but it remains unknown if the trajectory and dynamics of activation change with age. Here, we use time-lapse imaging and single cell RNA-seq to measure activation trajectories and rates in young and aged MuSCs. We find that the activation trajectory is conserved in aged cells, and we develop effective machine-learning classifiers for cell age. Using cell-behavior analysis and RNA velocity, we find that activation kinetics are delayed in aged MuSCs, suggesting that changes in stem cell dynamics may contribute to impaired stem cell function with age. Intriguingly, we also find that stem cell activation appears to be a random walk-like process, with frequent reversals, rather than a continuous linear progression. These results support a view of the aged stem cell phenotype as a combination of differences in the location of stable cell states and differences in transition rates between them., Highlighted Article: Aged muscle stem cells display delayed activation dynamics, but retain a youthful activation trajectory, suggesting that changes to cell state dynamics might contribute to aging pathology.

Background CCCTC-Binding Factor (CTCF), also known as 11-zinc finger protein, participates in many cellular processes, including insulator activity, transcriptional regulation and organization of chromatin architecture. Based on single cell flow cytometry and single cell RNA-FISH analyses, our previous study showed that deletion of CTCF binding site led to a significantly increase of cellular variation of its target gene. However, the effect of CTCF on genome-wide landscape of cell-to-cell variation remains unclear. Results We knocked down CTCF in EL4 cells using shRNA, and conducted single cell RNA-seq on both wild type (WT) cells and CTCF-Knockdown (CTCF-KD) cells using Fluidigm C1 system. Principal component analysis of single cell RNA-seq data showed that WT and CTCF-KD cells concentrated in two different clusters on PC1, indicating that gene expression profiles of WT and CTCF-KD cells were systematically different. Interestingly, GO terms including regulation of transcription, DNA binding, zinc finger and transcription factor binding were significantly enriched in CTCF-KD-specific highly variable genes, implying tissue-specific genes such as transcription factors were highly sensitive to CTCF level. The dysregulation of transcription factors potentially explains why knockdown of CTCF leads to systematic change of gene expression. In contrast, housekeeping genes such as rRNA processing, DNA repair and tRNA processing were significantly enriched in WT-specific highly variable genes, potentially due to a higher cellular variation of cell activity in WT cells compared to CTCF-KD cells. We further found that cellular variation-increased genes were significantly enriched in down-regulated genes, indicating CTCF knockdown simultaneously reduced the expression levels and increased the expression noise of its regulated genes. Conclusions To our knowledge, this is the first attempt to explore genome-wide landscape of cellular variation after CTCF knockdown. Our study not only advances our understanding of CTCF function in maintaining gene expression and reducing expression noise, but also provides a framework for examining gene function.

Directed differentiation of pluripotent stem cells provides an accessible system to model development. However, the distinct cell types that emerge, their dynamics, and their relationship to progenitors in the early embryo has been difficult to decipher because of the cellular heterogeneity inherent to differentiation. Here, we used a combination of bulk RNA-Seq, single cell RNA-Seq, and bioinformatics analyses to dissect the cell types that emerge during directed differentiation of mouse embryonic stem cells as embryoid bodies and we compared them to spatially and temporally resolved transcriptional profiles of early embryos. Our single cell analyses of the day 4 embryoid bodies revealed three populations which had retained related yet distinct pluripotent signatures that resemble the pre- or post-implantation epiblast, one population of presumptive neuroectoderm, one population of mesendoderm, and four populations of neural progenitors. By day 6, the neural progenitors predominated the embryoid bodies, but both a small population of pluripotent-like cells and an anterior mesoderm-like Brachyury-expressing population were present. By comparing the day 4 and day 6 populations, we identified candidate differentiation paths, transcription factors, and signaling pathways that mark the in vitro correlate of the transition from the mid-to-late primitive streak stage. Keywords: Directed differentiation, Embryoid body, Mesendoderm, Single cell rna-seq, Noggin, Transcriptional profiling, Neuroectoderm

Background Single cell transcriptomics is critical for understanding cellular heterogeneity and identification of novel cell types. Leveraging the recent advances in single cell RNA sequencing (scRNA-Seq) technology requires novel unsupervised clustering algorithms that are robust to high levels of technical and biological noise and scale to datasets of millions of cells. Results We present novel computational approaches for clustering scRNA-seq data based on the Term Frequency - Inverse Document Frequency (TF-IDF) transformation that has been successfully used in the field of text analysis. Conclusions Empirical experimental results show that TF-IDF methods consistently outperform commonly used scRNA-Seq clustering approaches.

SUMMARY To understand the cellular basis of behavior, it is necessary to know the cell types that exist in the nervous system and their contributions to function. Spinal networks are essential for sensory processing and motor behavior and provide a powerful system for identifying the cellular correlates of behavior. Here, we used massively parallel single nucleus RNA sequencing (snRNA-seq) to create an atlas of the adult mouse lumbar spinal cord. We identified and molecularly characterized 43 neuronal populations. Next, we leveraged the snRNA-seq approach to provide unbiased identification of neuronal populations that were active following a sensory and a motor behavior, using a transcriptional signature of neuronal activity. This approach can be used in the future to link single nucleus gene expression data with dynamic biological responses to behavior, injury, and disease., In Brief Sathyamurthy et al. use massively parallel single nucleus RNA-seq to probe spinal cord cell types and present an atlas of 43 neuronal populations. By using this approach after a sensory and a motor behavior, they were able to detect and molecularly identify activated neurons associated with each function.

Characterization of the cardiac cellulome, the network of cells that form the heart, is essential for understanding cardiac development and normal organ function and for formulating precise therapeutic strategies to combat heart disease. Recent studies have reshaped our understanding of cardiac cellular composition and highlighted important functional roles for non-myocyte cell types. In this study, we characterized single-cell transcriptional profiles of the murine non-myocyte cardiac cellular landscape using single-cell RNA sequencing (scRNA-seq). Detailed molecular analyses revealed the diversity of the cardiac cellulome and facilitated the development of techniques to isolate understudied cardiac cell populations, such as mural cells and glia. Our analyses also revealed extensive networks of intercellular communication and suggested prevalent sexual dimorphism in gene expression in the heart. This study offers insights into the structure and function of the mammalian cardiac cellulome and provides an important resource that will stimulate studies in cardiac cell biology.

Objective The current study addresses the cellular complexity and plasticity of subcutaneous (inguinal) white adipose tissue (iWAT) in mice during the critical periods of perinatal growth and establishment. Methods We performed a large-scale single cell transcriptomic (scRNA-seq) and epigenomic (snATAC-seq) characterization of cellular subtypes (adipose stromal cells (ASC) and adipocyte nuclei) during inguinal WAT (subcutaneous; iWAT) development in mice, capturing the early postnatal period (postnatal days (PND) 06 and 18) through adulthood (PND56). Results Perinatal and adult iWAT contain 3 major ASC subtypes that can be independently identified by RNA expression profiles and DNA transposase accessibility. Furthermore, the transcriptomes and enhancer landscapes of both ASC and adipocytes dynamically change during postnatal development. Perinatal ASC (PND06) are highly enriched for several imprinted genes (IGs; e.g., Mest, H19, Igf2) and extracellular matrix proteins whose expression then declines prior to weaning (PND18). By comparison, adult ASC (PND56) are more enriched for transcripts associated with immunoregulation, oxidative stress, and integrin signaling. Two clusters of mature adipocytes, identified through single nuclei RNA sequencing (snRNA-seq), were distinctive for proinflammatory/immune or metabolic gene expression patterns that became more transcriptionally diverse in adult animals. Single nuclei assay for transposase-accessible chromatin (snATAC-seq) revealed that differences in gene expression were associated with developmental changes in chromatin accessibility and predicted transcription factor motifs (e.g., Plagl1, Ar) in both stromal cells and adipocytes. Conclusions Our data provide new insights into transcriptional and epigenomic signaling networks important during iWAT establishment at a single cell resolution, with important implications for the field of metabolic programming.

SUMMARYStem cell dysfunction drives many age-related disorders. Identifying mechanisms that initially compromise stem cell function represent early targets to enhance stem cell behavior later in life. Here, we pinpoint multiple factors that disrupt neural stem cells (NSC) in the adult hippocampus. We find that NSCs exhibit asynchronous maintenance by identifying short-term (ST-NSC) and intermediate-term NSCs (IT-NSCs). ST-NSC divide rapidly to generate neurons and deplete in the young brain. Meanwhile, multipotent IT-NSCs persist for months, but are pushed out of homeostasis by lengthening quiescence. Single cell transcriptome analysis of deep NSC quiescence revealed several hallmarks of biological aging in the mature brain and identified tyrosine-protein kinase Abl1 as an NSC pro-aging factor. Treatment with the Abl-inhibitor Imatinib increased NSC proliferation without impairing NSC maintenance in the middle-aged brain. Further intersectional analysis of mature NSC with old epidermal, hematopoietic and muscle stem cell transcriptomes identified consensus changes in stem cell aging. Our study elucidates multiple origins of adult neurogenesis decline and reveals that hippocampal NSCs are particularly vulnerable to a shared stem cell aging signature.

Loss of sensory hair cells leads to deafness and balance deficiencies. In contrast to mammalian hair cells, zebrafish ear and lateral line hair cells regenerate from poorly characterized support cells. Equally ill-defined is the gene regulatory network underlying the progression of support cells to differentiated hair cells. scRNA-Seq of lateral line organs uncovered five different support cell types, including quiescent and activated stem cells. Ordering of support cells along a developmental trajectory identified self-renewing cells and genes required for hair cell differentiation. scRNA-Seq analyses of fgf3 mutants, in which hair cell regeneration is increased, demonstrates that Fgf and Notch signaling inhibit proliferation of support cells in parallel by inhibiting Wnt signaling. Our scRNA-Seq analyses set the foundation for mechanistic studies of sensory organ regeneration and is crucial for identifying factors to trigger hair cell production in mammals. The data is searchable and publicly accessible via a web-based interface.

Accumulating evidence suggests that intra-tumor heterogeneity (ITH) within tumor sub-populations is a major contributor to therapy resistance, with genomically distinct clonal populations exhibiting different therapeutic vulnerabilities. Here we employed single-cell transcriptomics in patient-derived primary cells to understand the impact of phenotypic intra-tumor heterogeneity on drug-induced tumor evolution in oral squamous cell carcinoma.

Amyotrophic lateral sclerosis (ALS) is a neurodegenerative disease in which motor neurons throughout the brain and spinal cord progressively degenerate resulting in muscle atrophy, paralysis and death. Recent studies using animal models of ALS implicate multiple cell-types (e.g., astrocytes and microglia) in ALS pathogenesis in the spinal motor systems. To ascertain cellular vulnerability and cell-type specific mechanisms of ALS in the brainstem that orchestrates oral-motor functions, we conducted parallel single cell RNA sequencing (scRNA-seq) analysis using the high-throughput Drop-seq method. We isolated 1894 and 3199 cells from the brainstem of wildtype and mutant SOD1 symptomatic mice respectively, at postnatal day 100. We recovered major known cell types and neuronal subpopulations, such as interneurons and motor neurons, and trigeminal ganglion (TG) peripheral sensory neurons, as well as, previously uncharacterized interneuron subtypes. We found that the majority of the cell types displayed transcriptomic alterations in ALS mice. Differentially expressed genes (DEGs) of individual cell populations revealed cell-type specific alterations in numerous pathways, including previously known ALS pathways such as inflammation (in microglia), stress response (ependymal and an uncharacterized cell population), neurogenesis (astrocytes, oligodendrocytes, neurons), synapse organization and transmission (microglia, oligodendrocyte precursor cells, and neuronal subtypes), and mitochondrial function (uncharacterized cell populations). Other cell-type specific processes altered in SOD1 mutant brainstem include those from motor neurons (axon regeneration, voltage-gated sodium and potassium channels underlying excitability, potassium ion transport), trigeminal sensory neurons (detection of temperature stimulus involved in sensory perception), and cellular response to toxic substances (uncharacterized cell populations). DEGs consistently altered across cell types (e.g., Malat1), as well as cell-type specific DEGs, were identified. Importantly, DEGs from various cell types overlapped with known ALS genes from the literature and with top hits from an existing human ALS genome-wide association study (GWAS), implicating the potential cell types in which the ALS genes function with ALS pathogenesis. Our molecular investigation at single cell resolution provides comprehensive insights into the cell types, genes and pathways altered in the brainstem in a widely used ALS mouse model.

Vascular endothelial cell (EC) function depends on appropriate organ-specific molecular and cellular specializations. To explore genomic mechanisms that control this specialization, we have analyzed and compared the transcriptome, accessible chromatin, and DNA methylome landscapes from mouse brain, liver, lung, and kidney ECs. Analysis of transcription factor (TF) gene expression and TF motifs at candidate cis-regulatory elements reveals both shared and organ-specific EC regulatory networks. In the embryo, only those ECs that are adjacent to or within the central nervous system (CNS) exhibit canonical Wnt signaling, which correlates precisely with blood-brain barrier (BBB) differentiation and Zic3 expression. In the early postnatal brain, single-cell RNA-seq of purified ECs reveals (1) close relationships between veins and mitotic cells and between arteries and tip cells, (2) a division of capillary ECs into vein-like and artery-like classes, and (3) new endothelial subtype markers, including new validated tip cell markers.

Significance Pulmonary alveolar type I (AT1) cells are essential for the gas-exchange function of lungs. AT1 cells retain their cellular plasticity during injury-induced alveolar regeneration. However, we know very little about the developmental heterogeneity of the AT1 cell population. Our study identified a robust genetic marker of postnatal AT1 cells, insulin-like growth factor-binding protein 2 (Igfbp2). We use this marker to demonstrate that the postnatal AT1 cell population actually consists of two AT1 cell subtypes (Hopx+Igfbp2+ and Hopx+Igfbp2− AT1 cells) with distinct cell fates during alveolar regeneration. The large majority of adult AT1 cells expresses Igfbp2 and cannot transdifferentiate into AT2 cells during post pneumonectomy formation of new alveoli. Therefore, Hopx+Igfbp2+ AT1 cells represent the terminally differentiated population of AT1 cells., Pulmonary alveolar type I (AT1) cells cover more than 95% of alveolar surface and are essential for the air–blood barrier function of lungs. AT1 cells have been shown to retain developmental plasticity during alveolar regeneration. However, the development and heterogeneity of AT1 cells remain largely unknown. Here, we conducted a single-cell RNA-seq analysis to characterize postnatal AT1 cell development and identified insulin-like growth factor-binding protein 2 (Igfbp2) as a genetic marker specifically expressed in postnatal AT1 cells. The portion of AT1 cells expressing Igfbp2 increases during alveologenesis and in post pneumonectomy (PNX) newly formed alveoli. We found that the adult AT1 cell population contains both Hopx+Igfbp2+ and Hopx+Igfbp2− AT1 cells, which have distinct cell fates during alveolar regeneration. Using an Igfbp2-CreER mouse model, we demonstrate that Hopx+Igfbp2+ AT1 cells represent terminally differentiated AT1 cells that are not able to transdifferentiate into AT2 cells during post-PNX alveolar regeneration. Our study provides tools and insights that will guide future investigations into the molecular and cellular mechanism or mechanisms underlying AT1 cell fate during lung development and regeneration.

Endothelial-to-hematopoietic transition (EHT) is an important stage in definitive hematopoietic development. However, the genetic mechanisms underlying human EHT remain poorly characterized. We performed single cell RNA-seq using 55 hemogenic endothelial cells (HECs: CD31+CD144+CD41–CD43–CD45–CD73–RUNX1c+), 47 vascular endothelial cells without hematopoietic potential (non-HE: CD31+CD144+CD41–CD43–CD45–CD73–RUNX1c–), and 35 hematopoietic progenitor cells (HPCs: CD34+CD43+RUNX1c+) derived from human embryonic stem cells (hESCs). HE and HP were enriched in genes implicated in hemogenic endothelial transcriptional networks, such as ERG, GATA2, and FLI. We found transcriptional overlap between individual HECs and HPCs; however, these populations were distinct from non-HE. Further analysis revealed novel biomarkers for human HEC/HPCs, including TIMP3, ESAM, RHOJ, and DLL4. Collectively, we demonstrate that hESC-derived HE and HP share a common developmental pathway, while non-HE are more heterogeneous and transcriptionally distinct. Our findings provide a novel strategy to test new genetic targets and optimize the production of definitive hematopoietic cells from human pluripotent stem cells.

In embryonic development, cells differentiate through stereotypical sequences of intermediate states to generate particular mature fates. By contrast, driving differentiation by ectopically expressing terminal transcription factors (direct programming) can generate similar fates by alternative routes. How differentiation in direct programming relates to embryonic differentiation is unclear. We applied single-cell RNA sequencing to compare two motor neuron differentiation protocols: a standard protocol approximating the embryonic lineage, and a direct programming method. Both initially undergo similar early neural commitment. Later, the direct programming path diverges into a novel transitional state rather than following the expected embryonic spinal intermediates. The novel state in direct programming has specific and uncharacteristic gene expression. It forms a loop in gene expression space that converges separately onto the same final motor neuron state as the standard path. Despite their different developmental histories, motor neurons from both protocols structurally, functionally, and transcriptionally resemble motor neurons isolated from embryos.

Single cell experimental techniques reveal transcriptomic and epigenetic heterogeneity among cells, but how these are related is unclear. We present MATCHER, an approach for integrating multiple types of single cell measurements. MATCHER uses manifold alignment to infer single cell multi-omic profiles from transcriptomic and epigenetic measurements performed on different cells of the same type. Using scM&T-seq and sc-GEM data, we confirm that MATCHER accurately predicts true single cell correlations between DNA methylation and gene expression without using known cell correspondences. MATCHER also reveals new insights into the dynamic interplay between the transcriptome and epigenome in single embryonic stem cells and induced pluripotent stem cells. Electronic supplementary material The online version of this article (doi:10.1186/s13059-017-1269-0) contains supplementary material, which is available to authorized users.

Background PCR clonal artefacts originating from NGS library preparation can affect both genomic as well as RNA-Seq applications when protocols are pushed to their limits. In RNA-Seq however the artifactual reads are not easy to tell apart from normal read duplication due to natural over-sequencing of highly expressed genes. Especially when working with little input material or single cells assessing the fraction of duplicate reads is an important quality control step for NGS data sets. Up to now there are only tools to calculate the global duplication rates that do not take into account the effect of gene expression levels which leaves them of limited use for RNA-Seq data. Results Here we present the tool dupRadar, which provides an easy means to distinguish the fraction of reads originating in natural duplication due to high expression from the fraction induced by artefacts. dupRadar assesses the fraction of duplicate reads per gene dependent on the expression level. Apart from the Bioconductor package dupRadar we provide shell scripts for easy integration into processing pipelines. Conclusions The Bioconductor package dupRadar offers straight-forward methods to assess RNA-Seq datasets for quality issues with PCR duplicates. It is aimed towards simple integration into standard analysis pipelines as a default QC metric that is especially useful for low-input and single cell RNA-Seq data sets. Electronic supplementary material The online version of this article (doi:10.1186/s12859-016-1276-2) contains supplementary material, which is available to authorized users.

Single cell experiments provide an unprecedented opportunity to reconstruct a sequence of changes in a biological process from individual “snapshots” of cells. However, nonlinear gene expression changes, genes unrelated to the process, and the possibility of branching trajectories make this a challenging problem. We develop SLICER (Selective Locally Linear Inference of Cellular Expression Relationships) to address these challenges. SLICER can infer highly nonlinear trajectories, select genes without prior knowledge of the process, and automatically determine the location and number of branches and loops. SLICER recovers the ordering of points along simulated trajectories more accurately than existing methods. We demonstrate the effectiveness of SLICER on previously published data from mouse lung cells and neural stem cells. Electronic supplementary material The online version of this article (doi:10.1186/s13059-016-0975-3) contains supplementary material, which is available to authorized users.