Single-cell mRNA quantification and differential analysis with Census

Generation of hypothalamic arcuate organoids from human induced pluripotent stem cells

Human brain organoids represent remarkable platforms for recapitulating features of human brain development and diseases. Existing organoid models do not resolve fine brain subregions, such as different nuclei in the hypothalamus. We report the generation of arcuate organoids (ARCOs) from human induced pluripotent stem cells (iPSCs) to model the development of the human hypothalamic arcuate nucleus. Single-cell RNA sequencing of ARCOs revealed significant molecular heterogeneity underlying different arcuate cell types, and machine learning-aided analysis based on the neonatal human hypothalamus single-nucleus transcriptome further showed a human arcuate nucleus molecular signature. We also explored ARCOs generated from Prader-Willi syndrome (PWS) patient iPSCs. These organoids exhibit aberrant differentiation and transcriptomic dysregulation similar to postnatal hypothalamus of PWS patients, indicative of cellular differentiation deficits and exacerbated inflammatory responses. Thus, patient iPSC-derived ARCOs represent a promising experimental model for investigating nucleus-specific features and disease-relevant mechanisms during early human arcuate development.

A multicenter study benchmarking single-cell RNA sequencing technologies using reference samples

Comparing diverse single-cell RNA sequencing (scRNA-seq) datasets generated by different technologies and in different laboratories remains a major challenge. Here we address the need for guidance in choosing algorithms leading to accurate biological interpretations of varied data types acquired with different platforms. Using two well-characterized cellular reference samples (breast cancer cells and B cells), captured either separately or in mixtures, we compared different scRNA-seq platforms and several preprocessing, normalization and batch-effect correction methods at multiple centers. Although preprocessing and normalization contributed to variability in gene detection and cell classification, batch-effect correction was by far the most important factor in correctly classifying the cells. Moreover, scRNA-seq dataset characteristics (for example, sample and cellular heterogeneity and platform used) were critical in determining the optimal bioinformatic method. However, reproducibility across centers and platforms was high when appropriate bioinformatic methods were applied. Our findings offer practical guidance for optimizing platform and software selection when designing an scRNA-seq study.

Machine Learning Approaches on High Throughput NGS Data to Unveil Mechanisms of Function in Biology and Disease

In this review, the fundamental basis of machine learning (ML) and data mining (DM) are summarized together with the techniques for distilling knowledge from state-of-the-art omics experiments. This includes an introduction to the basic mathematical principles of unsupervised/supervised learning methods, dimensionality reduction techniques, deep neural networks architectures and the applications of these in bioinformatics. Several case studies under evaluation mainly involve next generation sequencing (NGS) experiments, like deciphering gene expression from total and single cell (scRNA-seq) analysis; for the latter, a description of all recent artificial intelligence (AI) methods for the investigation of cell sub-types, biomarkers and imputation techniques are described. Other areas of interest where various ML schemes have been investigated are for providing information regarding transcription factors (TF) binding sites, chromatin organization patterns and RNA binding proteins (RBPs), while analyses on RNA sequence and structure as well as 3D dimensional protein structure predictions with the use of ML are described. Furthermore, we summarize the recent methods of using ML in clinical oncology, when taking into consideration the current omics data with pharmacogenomics to determine personalized treatments. With this review we wish to provide the scientific community with a thorough investigation of main novel ML applications which take into consideration the latest achievements in genomics, thus, unraveling the fundamental mechanisms of biology towards the understanding and cure of diseases.

Prospects and challenges of cancer systems medicine: from genes to disease networks

It is becoming evident that holistic perspectives toward cancer are crucial in deciphering the overwhelming complexity of tumors. Single-layer analysis of genome-wide data has greatly contributed to our understanding of cellular systems and their perturbations. However, fundamental gaps in our knowledge persist and hamper the design of effective interventions. It is becoming more apparent than ever, that cancer should not only be viewed as a disease of the genome but as a disease of the cellular system. Integrative multilayer approaches are emerging as vigorous assets in our endeavors to achieve systemic views on cancer biology. Herein, we provide a comprehensive review of the approaches, methods and technologies that can serve to achieve systemic perspectives of cancer. We start with genome-wide single-layer approaches of omics analyses of cellular systems and move on to multilayer integrative approaches in which in-depth descriptions of proteogenomics and network-based data analysis are provided. Proteogenomics is a remarkable example of how the integration of multiple levels of information can reduce our blind spots and increase the accuracy and reliability of our interpretations and network-based data analysis is a major approach for data interpretation and a robust scaffold for data integration and modeling. Overall, this review aims to increase cross-field awareness of the approaches and challenges regarding the omics-based study of cancer and to facilitate the necessary shift toward holistic approaches.

Study of cellular heterogeneity and differential dynamics of autophagy in human embryonic kidney development by single-cell RNA sequencing

Background

Autophagy is believed to participate in embryonic development, but whether the expression of autophagy-associated genes undergoes changes during the development of human embryonic kidneys remains unknown.

Methods

In this work, we identified 36,151 human renal cells from embryonic kidneys of 9–18 gestational weeks in 16 major clusters by single-cell RNA sequencing (scRNA-seq), and detected 1350 autophagy-related genes in all fetal renal cells. The abundance of each cell cluster in Wilms tumor samples from scRNA-seq and GDC TARGET WT datasets was detected by CIBERSORTx. R package Monocle 3 was used to determine differentiation trajectories. Cyclone tool of R package scran was applied to calculate the cell cycle scores. R package SCENIC was used to investigate the transcriptional regulons. The FindMarkers tool from Seurat was used to calculate DEGs. GSVA was used to perform gene set enrichment analyses. CellphoneDB was utilized to analyze intercellular communication.

Results

It was found that cells in the 13th gestational week showed the lowest transcriptional level in each cluster in all stages. Nephron progenitors could be divided into four subgroups with diverse levels of autophagy corresponding to different SIX2 expressions. SSBpod (podocyte precursors) could differentiate into four types of podocytes (Pod), and autophagy-related regulation was involved in this process. Pseudotime analysis showed that interstitial progenitor cells (IPCs) potentially possessed two primitive directions of differentiation to interstitial cells with different expressions of autophagy. It was found that NPCs, pretubular aggregates and interstitial cell clusters had high abundance in Wilms tumor as compared with para-tumor samples with active intercellular communication.

Conclusions

All these findings suggest that autophagy may be involved in the development and cellular heterogeneity of early human fetal kidneys. In addition, part of Wilms tumor cancer cells possess the characteristics of some fetal renal cell clusters.

Graphical abstract

Supplementary Information

The online version contains supplementary material available at 10.1186/s12935-021-02154-w.

BRIE2: computational identification of splicing phenotypes from single-cell transcriptomic experiments

RNA splicing is an important driver of heterogeneity in single cells through the expression of alternative transcripts and as a determinant of transcriptional kinetics. However, the intrinsic coverage limitations of scRNA-seq technologies make it challenging to associate specific splicing events to cell-level phenotypes. BRIE2 is a scalable computational method that resolves these issues by regressing single-cell transcriptomic data against cell-level features. We show that BRIE2 effectively identifies differential disease-associated alternative splicing events and allows a principled selection of genes that capture heterogeneity in transcriptional kinetics and improve RNA velocity analyses, enabling the identification of splicing phenotypes associated with biological changes.

NANOS2 suppresses the cell cycle by repressing mTORC1 activators in embryonic male germ cells

During murine germ cell development, male germ cells enter the mitotically arrested G0 stage, which is an initial step of sexually dimorphic differentiation. The male-specific RNA-binding protein NANOS2 has a key role in suppressing the cell cycle in germ cells. However, the detailed mechanism of how NANOS2 regulates the cell cycle remains unclear. Using single-cell RNA sequencing (scRNA-seq), we extracted the cell cycle state of each germ cell in wild-type and Nanos2-KO testes and revealed that Nanos2 expression starts in mitotic cells and induces mitotic arrest. We identified Rheb, a regulator of mTORC1, and Ptma as possible targets of NANOS2. We propose that repression of the cell cycle is a primary function of NANOS2 and that it is mediated via the suppression of mTORC1 activity through the repression of Rheb in a post-transcriptional manner.

Single paternal dexamethasone challenge programs offspring metabolism and reveals multiple candidates in RNA-mediated inheritance

Single traumatic events that elicit an exaggerated stress response can lead to the development of neuropsychiatric conditions. Rodent studies suggested germline RNA as a mediator of effects of chronic environmental exposures to the progeny. The effects of an acute paternal stress exposure on the germline and their potential consequences on offspring remain to be seen. We find that acute administration of an agonist for the stress-sensitive Glucocorticoid receptor, using the common corticosteroid dexamethasone, affects the RNA payload of mature sperm as soon as 3 hr after exposure. It further impacts early embryonic transcriptional trajectories, as determined by single-embryo sequencing, and metabolism in the offspring. We show persistent regulation of tRNA fragments in sperm and descendant 2-cell embryos, suggesting transmission from sperm to embryo. Lastly, we unravel environmentally induced alterations in sperm circRNAs and their targets in the early embryo, highlighting this class as an additional candidate in RNA-mediated inheritance of disease risk.

Single-cell evaluation reveals shifts in the tumor-immune niches that shape and maintain aggressive lesions in the breast

There is an unmet clinical need for stratification of breast lesions as indolent or aggressive to tailor treatment. Here, single-cell transcriptomics and multiparametric imaging applied to a mouse model of breast cancer reveals that the aggressive tumor niche is characterized by an expanded basal-like population, specialization of tumor subpopulations, and mixed-lineage tumor cells potentially serving as a transition state between luminal and basal phenotypes. Despite vast tumor cell-intrinsic differences, aggressive and indolent tumor cells are functionally indistinguishable once isolated from their local niche, suggesting a role for non-tumor collaborators in determining aggressiveness. Aggressive lesions harbor fewer total but more suppressed-like T cells, and elevated tumor-promoting neutrophils and IL-17 signaling, disruption of which increase tumor latency and reduce the number of aggressive lesions. Our study provides insight into tumor-immune features distinguishing indolent from aggressive lesions, identifies heterogeneous populations comprising these lesions, and supports a role for IL-17 signaling in aggressive progression.

Single-cell sequencing of immune cells from anticitrullinated peptide antibody positive and negative rheumatoid arthritis

The presence or absence of anti-citrullinated peptide antibodies (ACPA) and associated disparities in patients with rheumatoid arthritis (RA) implies disease heterogeneity with unknown diverse immunopathological mechanisms. Here we profile CD45⁺ hematopoietic cells from peripheral blood or synovial tissues from both ACPA+ and ACPA- RA patients by single-cell RNA sequencing and identify subsets of immune cells that contribute to the pathogenesis of RA subtypes. We find several synovial immune cell abnormalities, including up-regulation of CCL13, CCL18 and MMP3 in myeloid cell subsets of ACPA- RA compared with ACPA+ RA. Also evident is a lack of HLA-DRB5 expression and lower expression of cytotoxic and exhaustion related genes in the synovial tissues of patients with ACPA- RA. Furthermore, the HLA-DR15 haplotype (DRB1/DRB5) conveys an increased risk of developing active disease in ACPA+ RA in a large cohort of patients with treatment-naive RA. Immunohistochemical staining shows increased infiltration of CCL13 and CCL18-expressing immune cells in synovial tissues of ACPA- RA. Collectively, our data provide evidence of the differential involvement of cellular and molecular pathways involved in the pathogenesis of seropositive and seronegative RA subtypes and reveal the importance of precision therapy based on ACPA status.

Patients with rheumatoid arthritis are commonly stratified by ACPA serology, with positivity being associated with more severe disease and joint destruction. Here the authors present a single cell RNA sequencing resource comparing peripheral blood and synovial tissue cells from patients with ACPA+ versus ACPA- rheumatoid arthritis.

Spatially patterned excitatory neuron subtypes and projections of the claustrum

The claustrum is a functionally and structurally complex brain region, whose very spatial extent remains debated. Histochemical-based approaches typically treat the claustrum as a relatively narrow anatomical region that primarily projects to the neocortex, whereas circuit-based approaches can suggest a broader claustrum region containing projections to the neocortex and other regions. Here, in the mouse, we took a bottom-up and cell-type-specific approach to complement and possibly unite these seemingly disparate conclusions. Using single-cell RNA-sequencing, we found that the claustrum comprises two excitatory neuron subtypes that are differentiable from the surrounding cortex. Multicolor retrograde tracing in conjunction with 12-channel multiplexed in situ hybridization revealed a core-shell spatial arrangement of these subtypes, as well as differential downstream targets. Thus, the claustrum comprises excitatory neuron subtypes with distinct molecular and projection properties, whose spatial patterns reflect the narrower and broader claustral extents debated in previous research. This subtype-specific heterogeneity likely shapes the functional complexity of the claustrum.

Advances in single-cell sequencing: insights from organ transplantation

Single-cell RNA sequencing (scRNA-seq) is a comprehensive technical tool to analyze intracellular and intercellular interaction data by whole transcriptional profile analysis. Here, we describe the application in biomedical research, focusing on the immune system during organ transplantation and rejection. Unlike conventional transcriptome analysis, this method provides a full map of multiple cell populations in one specific tissue and presents a dynamic and transient unbiased method to explore the progression of allograft dysfunction, starting from the stress response to final graft failure. This promising sequencing technology remarkably improves individualized organ rejection treatment by identifying decisive cellular subgroups and cell-specific interactions.

Epigenetic scarring of exhausted T cells hinders memory differentiation upon eliminating chronic antigenic stimulation

Exhausted CD8 T cells (TEX) are a distinct state of T cell differentiation associated with failure to clear chronic viruses and cancer. Immunotherapies such as PD-1 blockade can reinvigorate TEX cells, but reinvigoration is not durable. A major unanswered question is whether TEX cells differentiate into functional durable memory T cells (TMEM) upon antigen clearance. Here, using a mouse model, we found that upon eliminating chronic antigenic stimulation, TEX cells partially (re)acquire phenotypic and transcriptional features of TMEM cells. These 'recovering' TEX cells originated from the T cell factor (TCF-1+) TEX progenitor subset. Nevertheless, the recall capacity of these recovering TEX cells remained compromised as compared to TMEM cells. Chromatin-accessibility profiling revealed a failure to recover core memory epigenetic circuits and maintenance of a largely exhausted open chromatin landscape. Thus, despite some phenotypic and transcriptional recovery upon antigen clearance, exhaustion leaves durable epigenetic scars constraining future immune responses. These results support epigenetic remodeling interventions for TEX cell-targeted immunotherapies.

Continuous clonal labeling reveals uniform progenitor potential in the adult exocrine pancreas

The tissue dynamics that govern maintenance and regeneration of the pancreas remain largely unknown. In particular, the presence and nature of a cellular hierarchy remains a topic of debate. Previous lineage tracing strategies in the pancreas relied on specific marker genes for clonal labeling, which left other populations untested and failed to account for potential widespread phenotypical plasticity. Here we employed a tracing system that depends on replication-induced clonal marks. We found that, in homeostasis, steady acinar replacement events characterize tissue dynamics, to which all acinar cells have an equal ability to contribute. Similarly, regeneration following pancreatitis was best characterized by an acinar self-replication model because no evidence of a cellular hierarchy was detected. In particular, rapid regeneration in the pancreas was found to be driven by an accelerated rate of acinar fission-like events. These results provide a comprehensive and quantitative model of cell dynamics in the exocrine pancreas.

Single-Cell Transcriptomics Reveals the Complexity of the Tumor Microenvironment of Treatment-Naive Osteosarcoma

Osteosarcoma (OS), which occurs most commonly in adolescents, is associated with a high degree of malignancy and poor prognosis. In order to develop an accurate treatment for OS, a deeper understanding of its complex tumor microenvironment (TME) is required. In the present study, tissues were isolated from six patients with OS, and then subjected to single-cell RNA sequencing (scRNA-seq) using a 10× Genomics platform. Multiplex immunofluorescence staining was subsequently used to validate the subsets identified by scRNA-seq. ScRNA-seq of six patients with OS was performed prior to neoadjuvant chemotherapy, and data were obtained on 29,278 cells. A total of nine major cell types were identified, and the single-cell transcriptional map of OS was subsequently revealed. Identified osteoblastic OS cells were divided into five subsets, and the subsets of those osteoblastic OS cells with significant prognostic correlation were determined using a deconvolution algorithm. Thereby, different transcription patterns in the cellular subtypes of osteoblastic OS cells were reported, and key transcription factors associated with survival prognosis were identified. Furthermore, the regulation of osteolysis by osteoblastic OS cells via receptor activator of nuclear factor kappa-B ligand was revealed. Furthermore, the role of osteoblastic OS cells in regulating angiogenesis through vascular endothelial growth factor-A was revealed. C3_TXNIP⁺ macrophages and C5_IFIT1⁺ macrophages were found to regulate regulatory T cells and participate in CD8⁺ T cell exhaustion, illustrating the possibility of immunotherapy that could target CD8⁺ T cells and macrophages. Our findings here show that the role of C1_osteoblastic OS cells in OS is to promote osteolysis and angiogenesis, and this is associated with survival prognosis. In addition, T cell depletion is an important feature of OS. More importantly, the present study provided a valuable resource for the in-depth study of the heterogeneity of the OS TME.

Single-cell analyses reveal the differentiation shifts of Schwann cells in neonatal rat sciatic nerves

Schwann cells provide essential physical and chemical support for neurons and play critical roles in the peripheral nervous system. To acquire an enhanced understanding of the genetic characteristics of Schwann cells, we analyzed single-cell transcriptional profiling of Schwann cells in neonatal rat sciatic nerves, ordered the pseudotemporal states of Schwann cells, and determined the magnitude of RNA velocity vectors as well as cell cycle stages of Schwann cell subtypes. We discovered the cellular heterogeneity of Schwann cells in neonatal rat sciatic nerves, revealed the dynamic changes of Schwann cell subtypes, and pointed out the differentiation trajectory from Timp3- and Col5a3-expressing Schwann cell subtype 3 to other Schwann cell subtypes. The functional interpretation further indicated that subtype 3 Schwann cells display genetic signatures of DNA replication and the acquisition of mesenchymal traits. Our study presents a transcriptional summarization of the differentiation states of Schwann cell subtypes in neonatal rat sciatic nerves at single-cell resolution and may serve as a foundation for a deeper comprehension of the involvement of Schwann cells in the development and regeneration of peripheral nerves.

Identification of Intercellular Crosstalk between Decidual Cells and Niche Cells in Mice

Decidualization is a crucial step for human reproduction, which is a prerequisite for embryo implantation, placentation and pregnancy maintenance. Despite rapid advances over recent years, the molecular mechanism underlying decidualization remains poorly understood. Here, we used the mouse as an animal model and generated a single-cell transcriptomic atlas of a mouse uterus during decidualization. By analyzing the undecidualized inter-implantation site of the uterus as a control, we were able to identify global gene expression changes associated with decidualization in each cell type. Additionally, we identified intercellular crosstalk between decidual cells and niche cells, including immune cells, endothelial cells and trophoblast cells. Our data provide a valuable resource for deciphering the molecular mechanism underlying decidualization.

Mapping Human Pluripotent Stem Cell-derived Erythroid Differentiation by Single-cell Transcriptome Analysis

There is an imbalance between the supply and demand of functional red blood cells (RBCs) in clinical applications. This imbalance can be addressed by regenerating RBCs using several in vitro methods. Induced pluripotent stem cells (iPSCs) can handle the low supply of cord blood and the ethical issues in embryonic stem cell research and provide a promising strategy to eliminate immune rejection. However, no complete single-cell level differentiation pathway exists for the iPSC-derived RBC differentiation system. In this study, we used iPSC line BC1 to establish a RBCs regeneration system. The 10× genomics single-cell transcriptome platform was used to map the cell lineage and differentiation trajectories on day 14 of the regeneration system. We observed that iPSCs differentiation was not synchronized during embryoid body (EB) culture. The cells (day 14) mainly consisted of mesodermal and various blood cells, similar to the yolk sac hematopoiesis. We identified six cell classifications and characterized the regulatory transcription factors (TFs) networks and cell-cell contacts underlying the system. iPSCs undergo two transformations during the differentiation trajectory, accompanied by the dynamic expression of cell adhesion molecules and estrogen-responsive genes. We identified different stages of erythroid cells, such as burst-forming unit erythroid (BFU-E) and orthochromatic erythroblasts (ortho-E), and found that the regulation of TFs (e.g., TFDP1 and FOXO3) is erythroid-stage specific. Immune erythroid cells were identified in our system. This study provides systematic theoretical guidance for optimizing the iPSCs-derived RBCs differentiation system, and this system is a useful model for simulating in vivo hematopoietic development and differentiation.

Single-cell RNA sequencing reveals distinct cellular factors for response to immunotherapy targeting CD73 and PD-1 in colorectal cancer

BACKGROUND

Although cancer immunotherapy is one of the most effective advanced-stage cancer therapies, no clinically approved cancer immunotherapies currently exist for colorectal cancer (CRC). Recently, programmed cell death protein 1 (PD-1) blockade has exhibited clinical benefits according to ongoing clinical trials. However, ongoing clinical trials for cancer immunotherapies are focused on PD-1 signaling inhibitors such as pembrolizumab, nivolumab, and atezolizumab. In this study, we focused on revealing the distinct response mechanism for the potent CD73 ectoenzyme selective inhibitor AB680 as a promising drug candidate that functions by blocking tumorigenic ATP/adenosine signaling in comparison to current therapeutics that block PD-1 to assess the value of this drug as a novel immunotherapy for CRC.

METHODS

To understand the distinct mechanism of AB680 in comparison to that of a neutralizing antibody against murine PD-1 used as a PD-1 blocker, we performed single-cell RNA sequencing of CD45⁺ tumor-infiltrating lymphocytes from untreated controls (n=3) and from AB680-treated (n=3) and PD-1-blockade-treated murine CRC in vivo models. We also used flow cytometry, Azoxymethane (AOM)/Dextran Sulfate Sodium (DSS) models, and in vitro functional assays to validate our new findings.

RESULTS

We initially observed that the expressions of Nt5e (a gene for CD73) and Entpd1 (a gene for CD39) affect T cell receptor (TCR) diversity and transcriptional profiles of T cells, thus suggesting their critical roles in T cell exhaustion within tumor. Importantly, PD-1 blockade significantly increased the TCR diversity of Entpd1-negative T cells and Pdcd1-positive T cells. Additionally, we determined that AB680 improved the anticancer functions of immunosuppressed cells such as Treg and exhausted T cells, while the PD-1 blocker quantitatively reduced Malat1^high Treg and M2 macrophages. We also verified that PD-1 blockade induced Treg depletion in AOM/DSS CRC in vivo models, and we confirmed that AB680 treatment caused increased activation of CD8⁺ T cells using an in vitro T cell assay.

CONCLUSIONS

The intratumoral immunomodulation of CD73 inhibition is distinct from PD-1 inhibition and exhibits potential as a novel anticancer immunotherapy for CRC, possibly through a synergistic effect when combined with PD-1 blocker treatments. This study may contribute to the ongoing development of anticancer immunotherapies targeting refractory CRC.

Single-cell analysis reveals cell communication triggered by macrophages associated with the reduction and exhaustion of CD8+ T cells in COVID-19

Background

The coronavirus disease 2019 (COVID-19) outbreak caused by severe acute respiratory syndrome coronavirus 2 (SARS-Cov-2) has become an ongoing pandemic. Understanding the respiratory immune microenvironment which is composed of multiple cell types, together with cell communication based on ligand–receptor interactions is important for developing vaccines, probing COVID-19 pathogenesis, and improving pandemic control measures.

Methods

A total of 102 consecutive hospitalized patients with confirmed COVID-19 were enrolled in this study. Clinical information, routine laboratory tests, and flow cytometry analysis data with different conditions were collected and assessed for predictive value in COVID-19 patients. Next, we analyzed public single-cell RNA-sequencing (scRNA-seq) data from bronchoalveolar lavage fluid, which offers the closest available view of immune cell heterogeneity as encountered in patients with varying severity of COVID-19. A weighting algorithm was used to calculate ligand–receptor interactions, revealing the communication potentially associated with outcomes across cell types. Finally, serum cytokines including IL6, IL1β, IL10, CXCL10, TNFα, GALECTIN-1, and IGF1 derived from patients were measured.

Results

Of the 102 COVID-19 patients, 42 cases (41.2%) were categorized as severe. Multivariate logistic regression analysis demonstrated that AST, D-dimer, BUN, and WBC were considered as independent risk factors for the severity of COVID-19. T cell numbers including total T cells, CD4⁺ and CD8⁺ T cells in the severe disease group were significantly lower than those in the moderate disease group. The risk model containing the above mentioned inflammatory damage parameters, and the counts of T cells, with AUROCs ranged from 0.78 to 0.87. To investigate the molecular mechanism at the cellular level, we analyzed the published scRNA-seq data and found that macrophages displayed specific functional diversity after SARS-Cov-2 infection, and the metabolic pathway activities in the identified macrophage subtypes were influenced by hypoxia status. Importantly, we described ligand–receptor interactions that are related to COVID-19 serverity involving macrophages and T cell subsets by communication analysis.

Conclusions

Our study showed that macrophages driving ligand–receptor crosstalk contributed to the reduction and exhaustion of CD8⁺ T cells. The identified crucial cytokine panel, including IL6, IL1β, IL10, CXCL10, IGF1, and GALECTIN-1, may offer the selective targets to improve the efficacy of COVID-19 therapy.

Trial registration: This is a retrospective observational study without a trial registration number.

Molecular topography of an entire nervous system

We have produced gene expression profiles of all 302 neurons of the C. elegans nervous system that match the single-cell resolution of its anatomy and wiring diagram. Our results suggest that individual neuron classes can be solely identified by combinatorial expression of specific gene families. For example, each neuron class expresses distinct codes of ∼23 neuropeptide genes and ∼36 neuropeptide receptors, delineating a complex and expansive "wireless" signaling network. To demonstrate the utility of this comprehensive gene expression catalog, we used computational approaches to (1) identify cis-regulatory elements for neuron-specific gene expression and (2) reveal adhesion proteins with potential roles in process placement and synaptic specificity. Our expression data are available at https://cengen.org and can be interrogated at the web application CengenApp. We expect that this neuron-specific directory of gene expression will spur investigations of underlying mechanisms that define anatomy, connectivity, and function throughout the C. elegans nervous system.

Single-cell RNA-seq reveals lineage-specific regulatory changes of fibroblasts and vascular endothelial cells in keloids

Keloids are a benign dermal fibrotic disorder with features similar to malignant tumors. keloids remain a therapeutic challenge and lack medical therapies, which is partially due to the incomplete understanding of the pathogenesis mechanism. We performed single-cell RNA-seq of 28,064 cells from keloid skin tissue and adjacent relatively normal tissue. Unbiased clustering revealed substantial cellular heterogeneity of keloid tissue, which included 21 clusters assigned to 11 cell lineages. We observed significant expansion of fibroblast and vascular endothelial cell subpopulations in keloids, reflecting their strong association with keloid pathogenesis. Comparative analyses were performed to identify the dysregulated pathways, regulators and ligand-receptor interactions in keloid fibroblasts and vascular endothelial cells. Our results highlight the roles of transforming growth factor beta and Eph-ephrin signaling pathways in both the aberrant fibrogenesis and angiogenesis of keloids. Critical regulators probably involved in the fibrogenesis of keloid fibroblasts, such as TWIST1, FOXO3 and SMAD3, were identified. TWIST1 inhibitor harmine could significantly suppress the fibrogenesis of keloid fibroblasts. In addition, tumor-related pathways were activated in keloid fibroblasts and vascular endothelial cells, which may be responsible for the malignant features of keloids. Our study put insights into the pathogenesis of keloids and provides potential targets for medical therapies.

Dynamic Transcriptional and Epigenetic Changes Drive Cellular Plasticity in the Liver

BACKGROUND AND AIMS

Following liver injury, a fraction of hepatocytes adopt features of biliary epithelial cells (BECs) in a process known as biliary reprogramming. The aim of this study was to elucidate the molecular events accompanying this dramatic shift in cellular identity.

APPROACH AND RESULTS

We applied the techniques of bulk RNA-sequencing (RNA-seq), single-cell RNA-seq, and assay for transposase-accessible chromatin with high-throughput sequencing to define the epigenetic and transcriptional changes associated with biliary reprogramming. In addition, we examined the role of TGF-β signaling by profiling cells undergoing reprogramming in mice with hepatocyte-specific deletion in the downstream TGF-β signaling component mothers against decapentaplegic homolog 4 (Smad4). Biliary reprogramming followed a stereotyped pattern of altered gene expression consisting of robust induction of biliary genes and weaker repression of hepatocyte genes. These changes in gene expression were accompanied by corresponding modifications at the chromatin level. Although some reprogrammed cells had molecular features of "fully differentiated" BECs, most lacked some biliary characteristics and retained some hepatocyte characteristics. Surprisingly, single-cell analysis of Smad4 mutant mice revealed a dramatic increase in reprogramming.

CONCLUSION

Hepatocytes undergo widespread chromatin and transcriptional changes during biliary reprogramming, resulting in epigenetic and gene expression profiles that are similar to, but distinct from, native BECs. Reprogramming involves a progressive accumulation of biliary molecular features without discrete intermediates. Paradoxically, canonical TGF-β signaling through Smad4 appears to constrain biliary reprogramming, indicating that TGF-β can either promote or inhibit biliary differentiation depending on which downstream components of the pathway are engaged. This work has implications for the formation of BECs and bile ducts in the adult liver.

Gene expression variation in Arabidopsis embryos at single-nucleus resolution

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

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

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

Integrated analysis of Xist upregulation and X-chromosome inactivation with single-cell and single-allele resolution

To ensure dosage compensation between the sexes, one randomly chosen X chromosome is silenced in each female cell in the process of X-chromosome inactivation (XCI). XCI is initiated during early development through upregulation of the long non-coding RNA Xist, which mediates chromosome-wide gene silencing. Cell differentiation, Xist upregulation and gene silencing are thought to be coupled at multiple levels to ensure inactivation of exactly one out of two X chromosomes. Here we perform an integrated analysis of all three processes through allele-specific single-cell RNA-sequencing. Specifically, we assess the onset of random XCI in differentiating mouse embryonic stem cells, and develop dedicated analysis approaches. By exploiting the inter-cellular heterogeneity of XCI onset, we identify putative Xist regulators. Moreover, we show that transient Xist upregulation from both X chromosomes results in biallelic gene silencing right before transitioning to the monoallelic state, confirming a prediction of the stochastic model of XCI. Finally, we show that genetic variation modulates the XCI process at multiple levels, providing a potential explanation for the long-known X-controlling element (Xce) effect, which leads to preferential inactivation of a specific X chromosome in inter-strain crosses. We thus draw a detailed picture of the different levels of regulation that govern the initiation of XCI. The experimental and computational strategies we have developed here will allow us to profile random XCI in more physiological contexts, including primary human cells in vivo.

Airway basal stem cells reutilize the embryonic proliferation regulator, Tgfβ-Id2 axis, for tissue regeneration

During development, quiescent airway basal stem cells are derived from proliferative primordial progenitors through the cell-cycle slowdown. In contrast, basal cells contribute to adult tissue regeneration by shifting from slow cycling to proliferating and subsequently back to slow cycling. Although sustained proliferation results in tumorigenesis, the molecular mechanisms regulating these transitions remain unknown. Using temporal single-cell transcriptomics of developing murine airway progenitors and genetic validation experiments, we found that TGF-β signaling decelerated cell cycle by inhibiting Id2 and contributed to slow-cycling basal cell specification during development. In adult tissue regeneration, reduced TGF-β signaling restored Id2 expression and initiated regeneration. Id2 overexpression and Tgfbr2 knockout enhanced epithelial proliferation; however, persistent Id2 expression drove basal cell hyperplasia that resembled a precancerous state. Together, the TGF-β-Id2 axis commonly regulates the proliferation transitions in basal cells during development and regeneration, and its fine-tuning is critical for normal regeneration while avoiding basal cell hyperplasia.

Tracing the origin of hair follicle stem cells

Tissue stem cells are generated from a population of embryonic progenitors through organ-specific morphogenetic events^1,2. Although tissue stem cells are central to organ homeostasis and regeneration, it remains unclear how they are induced during development, mainly because of the lack of markers that exclusively label prospective stem cells. Here we combine marker-independent long-term 3D live imaging and single-cell transcriptomics to capture a dynamic lineage progression and transcriptome changes in the entire epithelium of the mouse hair follicle as it develops. We found that the precursors of different epithelial lineages were aligned in a 2D concentric manner in the basal layer of the hair placode. Each concentric ring acquired unique transcriptomes and extended to form longitudinally aligned, 3D cylindrical compartments. Prospective bulge stem cells were derived from the peripheral ring of the placode basal layer, but not from suprabasal cells (as was previously suggested³). The fate of placode cells is determined by the cell position, rather than by the orientation of cell division. We also identified 13 gene clusters: the ensemble expression dynamics of these clusters drew the entire transcriptional landscape of epithelial lineage diversification, consistent with cell lineage data. Combining these findings with previous work on the development of appendages in insects^4,5, we describe the 'telescope model', a generalized model for the development of ectodermal organs in which 2D concentric zones in the placode telescope out to form 3D longitudinally aligned cylindrical compartments.

The Immune Atlas of Human Deciduas With Unexplained Recurrent Pregnancy Loss

Recurrent pregnancy loss (RPL) is a common fertility problem that affects 1%-2% of couples all over the world. Despite exciting discoveries regarding the important roles of the decidual natural killer cell (dNK) and regulatory T cell in pregnancy, the immune heterogeneity in patients with unexplained recurrent pregnancy loss (URPL) remains elusive. Here, we profiled the transcriptomes of 13,953 CD45⁺ cells from three normal and three URPL deciduas. Based on our data, the cellular composition revealed three major populations of immune cells including dNK cell, T cell, and macrophage, and four minor populations including monocytes, dendritic cell (DC), mast cell, and B cell. Especially, we identified a subpopulation of CSF1+ CD59+ KIRs-expressing dNK cells in normal deciduas, while the proportion of this subpopulation was decreased in URPL deciduas. We also identified a small subpopulation of activated dDCs that were accumulated mainly in URPL deciduas. Furthermore, our data revealed that in decidua at early pregnancy, CD8⁺ T cells exhibited cytotoxic properties. The decidual macrophages expressed high levels of both M1 and M2 feature genes, which made them unique to the conventional M1/M2 classification. Our single-cell data revealed the immune heterogeneity in decidua and the potentially pathogenic immune variations in URPL.

Genetic mapping of developmental trajectories for complex traits and diseases

Genome-wide association studies (GWAS) have identified numerous common genetic variants associated with complex human traits and diseases. However, the translation of GWAS discoveries into biological and clinical insights is highly challenging. In this study, we present a novel bioinformatics approach for enhancing the functional interpretation of GWAS signals, based on their integration with single-cell (sc)RNA-seq datasets that examine developmental processes. Our approach performs three tasks: (1) Identification of links between cell differentiation trajectories and traits; (2) Elucidation of biological processes and molecular pathways that underlie such trajectory-trait links; and (3) Prioritization of target genes that carry the links between trajectories, pathways and traits. We applied our method to a set of 11 traits of various pathologies, and 12 scRNA-seq datasets of diverse developmental processes, and it readily detected well-established biological connections, including those between the maturation of cortical inhibitory interneurons and schizophrenia, hepatocytes and cholesterol levels, and pancreatic beta-islet cells and type-2 diabetes. For each of these associations, our method pinpointed top candidate genes that are strongly associated with both the kinetics of the differentiation trajectory and the disease's genetic risk. By the identification of trajectory-disease links, molecular pathways that underlie them and prioritizing candidate risk genes, our method improves the understanding of the etiology of complex diseases, and thus holds promise for enhancing rational drug development that is aimed at targeting specific biological processes that mediate the genetic predisposition to diseases.

Single-Cell Sequencing Methodologies: From Transcriptome to Multi-Dimensional Measurement

Cells are the basic building blocks of biological systems, with inherent unique molecular features and development trajectories. The study of single cells facilitates in-depth understanding of cellular diversity, disease processes, and organization of multicellular organisms. Single-cell RNA sequencing (scRNA-seq) technologies have become essential tools for the interrogation of gene expression patterns and the dynamics of single cells, allowing cellular heterogeneity to be dissected at unprecedented resolution. Nevertheless, measuring at only transcriptome level or 1D is incomplete; the cellular heterogeneity reflects in multiple dimensions, including the genome, epigenome, transcriptome, spatial, and even temporal dimensions. Hence, integrative single cell analysis is highly desired. In addition, the way to interpret sequencing data by virtue of bioinformatic tools also exerts critical roles in revealing differential gene expression. Here, a comprehensive review that summarizes the cutting-edge single-cell transcriptome sequencing methodologies, including scRNA-seq, spatial and temporal transcriptome profiling, multi-omics sequencing and computational methods developed for scRNA-seq data analysis is provided. Finally, the challenges and perspectives of this field are discussed.

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

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

ASCL1 represses a SOX9+ neural crest stem-like state in small cell lung cancer

ASCL1 is a neuroendocrine lineage-specific oncogenic driver of small cell lung cancer (SCLC), highly expressed in a significant fraction of tumors. However, ∼25% of human SCLC are ASCL1-low and associated with low neuroendocrine fate and high MYC expression. Using genetically engineered mouse models (GEMMs), we show that alterations in Rb1/Trp53/Myc in the mouse lung induce an ASCL1+ state of SCLC in multiple cells of origin. Genetic depletion of ASCL1 in MYC-driven SCLC dramatically inhibits tumor initiation and progression to the NEUROD1+ subtype of SCLC. Surprisingly, ASCL1 loss promotes a SOX9+ mesenchymal/neural crest stem-like state and the emergence of osteosarcoma and chondroid tumors, whose propensity is impacted by cell of origin. ASCL1 is critical for expression of key lineage-related transcription factors NKX2-1, FOXA2, and INSM1 and represses genes involved in the Hippo/Wnt/Notch developmental pathways in vivo. Importantly, ASCL1 represses a SOX9/RUNX1/RUNX2 program in vivo and SOX9 expression in human SCLC cells, suggesting a conserved function for ASCL1. Together, in a MYC-driven SCLC model, ASCL1 promotes neuroendocrine fate and represses the emergence of a SOX9+ nonendodermal stem-like fate that resembles neural crest.

Reprogramming lineage identity through cell-cell fusion

The conversion of differentiated cells to a pluripotent state through somatic cell nuclear transfer provided the first unequivocal evidence that differentiation was reversible. In more recent times, introducing a combination of key transcription factors into terminally differentiated mammalian cells was shown to drive their conversion to induced pluripotent stem cells (iPSCs). These discoveries were transformative, but the relatively slow speed (2-3 weeks) and low efficiency of reprogramming (0.1-1%) made deciphering the underlying molecular mechanisms difficult and complex. Cell fusion provides an alternative reprogramming approach that is both efficient and tractable, particularly when combined with modern multi-omics analysis of individual cells. Here we review the history and the recent advances in cell-cell fusion that are enabling a better understanding cell fate conversion, and we discuss how this knowledge could be used to shape improved strategies for regenerative medicine.

Meiosis-specific ZFP541 repressor complex promotes developmental progression of meiotic prophase towards completion during mouse spermatogenesis

During spermatogenesis, meiosis is accompanied by a robust alteration in gene expression and chromatin status. However, it remains elusive how the meiotic transcriptional program is established to ensure completion of meiotic prophase. Here, we identify a protein complex that consists of germ-cell-specific zinc-finger protein ZFP541 and its interactor KCTD19 as the key transcriptional regulators in mouse meiotic prophase progression. Our genetic study shows that ZFP541 and KCTD19 are co-expressed from pachytene onward and play an essential role in the completion of the meiotic prophase program in the testis. Furthermore, our ChIP-seq and transcriptome analyses identify that ZFP541 binds to and suppresses a broad range of genes whose function is associated with biological processes of transcriptional regulation and covalent chromatin modification. The present study demonstrates that a germ-cell specific complex that contains ZFP541 and KCTD19 promotes the progression of meiotic prophase towards completion in male mice, and triggers the reconstruction of the transcriptional network and chromatin organization leading to post-meiotic development.

Totipotency of mouse zygotes extends to single blastomeres of embryos at the four-cell stage

In multicellular organisms, oocytes and sperm undergo fusion during fertilization and the resulting zygote gives rise to a new individual. The ability of zygotes to produce a fully formed individual from a single cell when placed in a supportive environment is known as totipotency. Given that totipotent cells are the source of all multicellular organisms, a better understanding of totipotency may have a wide-ranging impact on biology. The precise delineation of totipotent cells in mammals has remained elusive, however, although zygotes and single blastomeres of embryos at the two-cell stage have been thought to be the only totipotent cells in mice. We now show that a single blastomere of two- or four-cell mouse embryos can give rise to a fertile adult when placed in a uterus, even though blastomere isolation disturbs the transcriptome of derived embryos. Single blastomeres isolated from embryos at the eight-cell or morula stages and cultured in vitro manifested pronounced defects in the formation of epiblast and primitive endoderm by the inner cell mass and in the development of blastocysts, respectively. Our results thus indicate that totipotency of mouse zygotes extends to single blastomeres of embryos at the four-cell stage.

Single-Cell RNA-Sequencing Reveals the Breadth of Osteoblast Heterogeneity

The current paradigm of osteoblast fate is that the majority undergo apoptosis, while some further differentiate into osteocytes and others flatten and cover bone surfaces as bone lining cells. Osteoblasts have been described to exhibit heterogeneous expression of a variety of osteoblast markers at both transcriptional and protein levels. To explore further this heterogeneity and its biological significance, Venus‐positive (Venus⁺) cells expressing the fluorescent protein Venus under the control of the 2.3‐kb Col1a1 promoter were isolated from newborn mouse calvariae and subjected to single‐cell RNA sequencing. Functional annotation of the genes expressed in 272 Venus⁺ single cells indicated that Venus⁺ cells are osteoblasts that can be categorized into four clusters. Of these, three clusters (clusters 1 to 3) exhibited similarities in their expression of osteoblast markers, while one (cluster 4) was distinctly different. We identified a total of 1920 cluster‐specific genes and pseudotime ordering analyses based on established concepts and known markers showed that clusters 1 to 3 captured osteoblasts at different maturational stages. Analysis of gene co‐expression networks showed that genes involved in protein synthesis and protein trafficking between endoplasmic reticulum (ER) and Golgi are active in these clusters. However, the cells in these clusters were also defined by extensive heterogeneity of gene expression, independently of maturational stage. Cells of cluster 4 expressed Cd34 and Cxcl12 with relatively lower levels of osteoblast markers, suggesting that this cell type differs from actively bone‐forming osteoblasts and retain or reacquire progenitor properties. Based on expression and machine learning analyses of the transcriptomes of individual osteoblasts, we also identified genes that may be useful as new markers of osteoblast maturational stages. Taken together, our data show much more extensive heterogeneity of osteoblasts than previously documented, with gene profiles supporting diversity of osteoblast functional activities and developmental fates. © 2021 The Authors. JBMR Plus published by Wiley Periodicals LLC on behalf of American Society for Bone and Mineral Research.

Cell-Cell Communication at the Embryo Implantation Site of Mouse Uterus Revealed by Single-Cell Analysis

As a crucial step for human reproduction, embryo implantation is a low-efficiency process. Despite rapid advances in recent years, the molecular mechanism underlying embryo implantation remains poorly understood. Here, we used the mouse as an animal model and generated a single-cell transcriptomic atlas of embryo implantation sites. By analyzing inter-implantation sites of the uterus as control, we were able to identify global gene expression changes associated with embryo implantation in each cell type. Additionally, we predicted signaling interactions between uterine luminal epithelial cells and mural trophectoderm of blastocysts, which represent the key mechanism of embryo implantation. We also predicted signaling interactions between uterine epithelial-stromal crosstalk at implantation sites, which are crucial for post-implantation development. Our data provide a valuable resource for deciphering the molecular mechanism underlying embryo implantation.

Flexible comparison of batch correction methods for single-cell RNA-seq using BatchBench

As the cost of single-cell RNA-seq experiments has decreased, an increasing number of datasets are now available. Combining newly generated and publicly accessible datasets is challenging due to non-biological signals, commonly known as batch effects. Although there are several computational methods available that can remove batch effects, evaluating which method performs best is not straightforward. Here, we present BatchBench (https://github.com/cellgeni/batchbench), a modular and flexible pipeline for comparing batch correction methods for single-cell RNA-seq data. We apply BatchBench to eight methods, highlighting their methodological differences and assess their performance and computational requirements through a compendium of well-studied datasets. This systematic comparison guides users in the choice of batch correction tool, and the pipeline makes it easy to evaluate other datasets.

Differential gene expression analysis for multi-subject single cell RNA sequencing studies with aggregateBioVar

Motivation

Single-cell RNA-sequencing (scRNA-seq) provides more granular biological information than bulk RNA-sequencing; bulk RNA sequencing remains popular due to lower costs which allows processing more biological replicates and design more powerful studies. As scRNA-seq costs have decreased, collecting data from more than one biological replicate has become more feasible, but careful modeling of different layers of biological variation remains challenging for many users. Here, we propose a statistical model for scRNA-seq gene counts, describe a simple method for estimating model parameters and show that failing to account for additional biological variation in scRNA-seq studies can inflate false discovery rates (FDRs) of statistical tests.

Results

First, in a simulation study, we show that when the gene expression distribution of a population of cells varies between subjects, a naïve approach to differential expression analysis will inflate the FDR. We then compare multiple differential expression testing methods on scRNA-seq datasets from human samples and from animal models. These analyses suggest that a naïve approach to differential expression testing could lead to many false discoveries; in contrast, an approach based on pseudobulk counts has better FDR control.

Availability and implementation

A software package, aggregateBioVar, is freely available on Bioconductor (https://www.bioconductor.org/packages/release/bioc/html/aggregateBioVar.html) to accommodate compatibility with upstream and downstream methods in scRNA-seq data analysis pipelines.

Supplementary information

Raw gene-by-cell count matrices for pig scRNA-seq data are available as GEO accession GSE150211. Supplementary data are available at Bioinformatics online.

Cycling Stem Cells Are Radioresistant and Regenerate the Intestine

A certain number of epithelial cells in intestinal crypts are DNA damage resistant and contribute to regeneration. However, the cellular mechanism underlying intestinal regeneration remains unclear. Using lineage tracing, we show that cells marked by an Msi1 reporter (Msi1⁺) are right above Lgr5^high cells in intestinal crypts and exhibit DNA damage resistance. Single-cell RNA sequencing reveals that the Msi1⁺ cells are heterogeneous with the majority being intestinal stem cells (ISCs). The DNA damage-resistant subpopulation of Msi1⁺ cells is characterized by low-to-negative Lgr5 expression and is more rapidly cycling than Lgr5^high radiosensitive crypt base columnar stem cells (CBCs). This enables an efficient repopulation of the intestinal epithelium at early stage when Lgr5^high cells are not emerging. Furthermore, relative to CBCs, Msi1⁺ cells preferentially produce Paneth cells during homeostasis and upon radiation repair. Together, we demonstrate that the DNA damage-resistant Msi1⁺ cells are cycling ISCs that maintain and regenerate the intestinal epithelium.

Quiescent reserve stem cells in the intestine are thought to activate following irradiation to restore the depleted Lgr5^high CBCs. Now, Sheng et al. demonstrate that cycling Msi1⁺ cells represent DNA damage-resistant ISCs that support efficient repopulation of the intestinal epithelium at the early stage of post-radiation repair, ahead of Lgr5^high CBCs.

Molecular identity of human limbal heterogeneity involved in corneal homeostasis and privilege

PURPOSE

The corneal limbus maintains the homeostasis, immune and angiogenic privilege of cornea. This study aimed to depict the landscape of human limbal tissues by single-cell RNA sequencing (scRNA-seq).

METHODS

Single cells of human limbus collected from donor corneas were subjected to 10x scRNA-seq, followed by clustering cell types through the t-distributed stochastic neighbor embedding (t-SNE) and unbiased computational informatic analysis. Immunofluorescent staining was performed using human corneas to validate the analysis results.

RESULTS

47,627 cells acquired from six human limbal tissues were collected and subjected to scRNA-seq. 14 distinct clusters were identified and 8 cell types were annotated with representative markers. In-depth dissection revealed three limbal epithelial cell subtypes and refined the X-Y-Z hypothesis of corneal epithelial maintenance. We further unveiled two cell states with higher stemness (TP63⁺ and CCL20⁺ cells), and two other differentiated cell states (GPHA2⁺ and KRT6B ⁺ cells) in homeostatic limbal stem/progenitor cells (LSPCs) that differ in transcriptional profiles. Cell-cell communication analysis revealed the central role of LSPCs and their bidirectional regulation with various niche cells. Moreover, comparative analysis between limbus and skin deciphered the pivotal contribution of limbal immune cells, vascular and lymphatic endothelial cells to corneal immune and angiogenic privilege.

CONCLUSIONS

The human limbus atlas provided valuable resources and foundations for understanding corneal biology, disease and potential interventions.

Differential chromatin binding of the lung lineage transcription factor NKX2-1 resolves opposing murine alveolar cell fates in vivo

Differential transcription of identical DNA sequences leads to distinct tissue lineages and then multiple cell types within a lineage, an epigenetic process central to progenitor and stem cell biology. The associated genome-wide changes, especially in native tissues, remain insufficiently understood, and are hereby addressed in the mouse lung, where the same lineage transcription factor NKX2-1 promotes the diametrically opposed alveolar type 1 (AT1) and AT2 cell fates. Here, we report that the cell-type-specific function of NKX2-1 is attributed to its differential chromatin binding that is acquired or retained during development in coordination with partner transcriptional factors. Loss of YAP/TAZ redirects NKX2-1 from its AT1-specific to AT2-specific binding sites, leading to transcriptionally exaggerated AT2 cells when deleted in progenitors or AT1-to-AT2 conversion when deleted after fate commitment. Nkx2-1 mutant AT1 and AT2 cells gain distinct chromatin accessible sites, including those specific to the opposite fate while adopting a gastrointestinal fate, suggesting an epigenetic plasticity unexpected from transcriptional changes. Our genomic analysis of single or purified cells, coupled with precision genetics, provides an epigenetic basis for alveolar cell fate and potential, and introduces an experimental benchmark for deciphering the in vivo function of lineage transcription factors.

Defining cell identity beyond the premise of differential gene expression

Identifying genes that define cell identity is a requisite step for characterising cell types and cell states and predicting cell fate choices. By far, the most widely used approach for this task is based on differential expression (DE) of genes, whereby the shift of mean expression are used as the primary statistics for identifying gene transcripts that are specific to cell types and states. While DE-based methods are useful for pinpointing genes that discriminate cell types, their reliance on measuring difference in mean expression may not reflect the biological attributes of cell identity genes. Here, we highlight the quest for non-DE methods and provide an overview of these methods and their applications to identify genes that define cell identity and functionality.

Tmem100- and Acta2-Lineage Cells Contribute to Implant Osseointegration in a Mouse Model

Metal implants are commonly used in orthopedic surgery. The mechanical stability and longevity of implants depend on adequate bone deposition along the implant surface. The cellular and molecular mechanisms underlying peri-implant bone formation (ie, osseointegration) are incompletely understood. Herein, our goal was to determine the specific bone marrow stromal cell populations that contribute to bone formation around metal implants. To do this, we utilized a mouse tibial implant model that is clinically representative of human joint replacement procedures. Using a lineage-tracing approach, we found that both Acta2.creERT2 and Tmem100.creERT2 lineage cells are involved in peri-implant bone formation, and Pdgfra- and Ly6a/Sca1-expressing stromal cells (PαS cells) are highly enriched in both lineages. Single-cell RNA-seq analysis indicated that PαS cells are quiescent in uninjured bone tissue; however, they express markers of proliferation and osteogenic differentiation shortly after implantation surgery. Our findings indicate that PαS cells are mobilized to repair bone tissue and participate in implant osseointegration after surgery. Biologic therapies targeting PαS cells might improve osseointegration in patients undergoing orthopedic procedures. © 2021 American Society for Bone and Mineral Research (ASBMR).

SwarnSeq: An improved statistical approach for differential expression analysis of single-cell RNA-seq data

Single-cell RNA sequencing (scRNA-seq) is a powerful technology that is capable of generating gene expression data at the resolution of individual cell. The scRNA-seq data is characterized by the presence of dropout events, which severely bias the results if they remain unaddressed. There are limited Differential Expression (DE) approaches which consider the biological processes, which lead to dropout events, in the modeling process. So, we develop, SwarnSeq, an improved method for DE, and other downstream analysis that considers the molecular capture process in scRNA-seq data modeling. The performance of the proposed method is benchmarked with 11 existing methods on 10 different real scRNA-seq datasets under three comparison settings. We demonstrate that SwarnSeq method has improved performance over the 11 existing methods. This improvement is consistently observed across several public scRNA-seq datasets generated using different scRNA-seq protocols. The external spike-ins data can be used in the SwarnSeq method to enhance its performance. AVAILABILITY AND IMPLEMENTATION: The method is implemented as a publicly available R package available at https://github.com/sam-uofl/SwarnSeq.

Control of neurogenic competence in mammalian hypothalamic tanycytes

Hypothalamic tanycytes, radial glial cells that share many features with neuronal progenitors, can generate small numbers of neurons in the postnatal hypothalamus, but the identity of these neurons and the molecular mechanisms that control tanycyte-derived neurogenesis are unknown. In this study, we show that tanycyte-specific disruption of the NFI family of transcription factors (Nfia/b/x) robustly stimulates tanycyte proliferation and tanycyte-derived neurogenesis. Single-cell RNA sequencing (scRNA-seq) and single-cell assay for transposase-accessible chromatin sequencing (scATAC-seq) analysis reveals that NFI (nuclear factor I) factors repress Sonic hedgehog (Shh) and Wnt signaling in tanycytes and modulation of these pathways blocks proliferation and tanycyte-derived neurogenesis in Nfia/b/x-deficient mice. Nfia/b/x-deficient tanycytes give rise to multiple mediobasal hypothalamic neuronal subtypes that can mature, fire action potentials, receive synaptic inputs, and selectively respond to changes in internal states. These findings identify molecular mechanisms that control tanycyte-derived neurogenesis, which can potentially be targeted to selectively remodel the hypothalamic neural circuitry that controls homeostatic physiological processes.

Single-cell RNA-seq reveals transcriptional landscape and intratumor heterogenicity in gallbladder cancer liver metastasis microenvironment

Background

Gallbladder cancer (GBC) is a highly aggressive biliary epithelial malignancy. The median survival time of GBC patients was less than 1 year. Tumor invasion and metastasis are the major cause of high mortality of GBC patients. However, the molecular mechanisms involved in GBC metastases are still unclear.

Methods

We performed 10X genomics single-cell RNA sequencing (scRNA-seq) on GBC liver metastasis tissue to evaluate the characteristics of the GBC liver metastasis microenvironment.

Results

In this study, 8 cell types, a total of 7,788 cells, including T cells, B cells, malignant cells, fibroblasts, endothelial cells, macrophages, dendritic cells (DCs), and mast cells were identified. Malignant cells displayed a high degree of intratumor heterogenicity, while neutrophils were found to promote GBC cell proliferation, migration, and invasion. Furthermore, cytotoxic cluster of differentiation (CD8⁺) T cells became exhausted and CD4⁺ regulatory T cells (Tregs) exhibited immunosuppressive characteristics. Macrophages played an important role in the tumor microenvironment (TME). We identified three distinct macrophage subsets and emergent M2 polarization. We also found that cancer-associated fibroblasts exhibited heterogeneity and may be associated with GBC metastasis.

Conclusions

Although preliminary in nature, our study provides a landscape view at the single-cell level. These results offer a unique perspective into understanding the liver metastasis of GBC.

PseudotimeDE: inference of differential gene expression along cell pseudotime with well-calibrated p-values from single-cell RNA sequencing data

To investigate molecular mechanisms underlying cell state changes, a crucial analysis is to identify differentially expressed (DE) genes along the pseudotime inferred from single-cell RNA-sequencing data. However, existing methods do not account for pseudotime inference uncertainty, and they have either ill-posed p-values or restrictive models. Here we propose PseudotimeDE, a DE gene identification method that adapts to various pseudotime inference methods, accounts for pseudotime inference uncertainty, and outputs well-calibrated p-values. Comprehensive simulations and real-data applications verify that PseudotimeDE outperforms existing methods in false discovery rate control and power.

Comparative Transcriptomic Analysis of the Hematopoietic System between Human and Mouse by Single Cell RNA Sequencing

(1) Background: mouse models are fundamental to the study of hematopoiesis, but comparisons between mouse and human in single cells have been limited in depth. (2) Methods: we constructed a single-cell resolution transcriptomic atlas of hematopoietic stem and progenitor cells (HSPCs) of human and mouse, from a total of 32,805 single cells. We used Monocle to examine the trajectories of hematopoietic differentiation, and SCENIC to analyze gene networks underlying hematopoiesis. (3) Results: After alignment with Seurat 2, the cells of mouse and human could be separated by same cell type categories. Cells were grouped into 17 subpopulations; cluster-specific genes were species-conserved and shared functional themes. The clustering dendrogram indicated that cell types were highly conserved between human and mouse. A visualization of the Monocle results provided an intuitive representation of HSPC differentiation to three dominant branches (Erythroid/megakaryocytic, Myeloid, and Lymphoid), derived directly from the hematopoietic stem cell and the long-term hematopoietic stem cells in both human and mouse. Gene regulation was similarly conserved, reflected by comparable transcriptional factors and regulatory sequence motifs in subpopulations of cells. (4) Conclusions: our analysis has confirmed evolutionary conservation in the hematopoietic systems of mouse and human, extending to cell types, gene expression and regulatory elements.