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Results for “single cell RNA sequencing”

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bioRxiv2025

The immune landscape of pediatric Brain and Solid Tumors: A systematic review and integration of immunohistochemistry and single-cell RNA sequencing data

BackgroundImmunotherapies achieved remarkable success in adult cancers, yet their efficacy in pediatric brain and solid tumors remains limited. Insights into the unique immune landscape of pediatric tumors are crucial to improve immunotherapies for pediatric patients. MethodsWe performed a systematic search for studies reporting immunohistochemistry (IHC), single-cell- or single-nucleus RNA-sequencing (sc/snSeq) data on the immune landscape of pediatric tumors. For IHC studies, data on macrophages, T cells, T helper cells, regulatory T cells, NK cells and B cells were extracted. For sc/snSeq studies, cell cluster counts were extracted. 47 IHC studies and 26 sc/snSeq studies were included in the analysis. ResultsOur integrative in-depth analysis of 73 studies covered 35 unique pediatric tumor types with 17 tumor types analyzed by IHC, 4 by sc/snSeq, and 14 by both techniques. Regardless of variability in analysis methods, both IHC and sc/snSeq showed that peripheral nerve tumors and soft tissue sarcomas had relatively immune-infiltrated, T cell-rich tumor microenvironments (TME). Brain tumors exhibited a macrophage/microglia-rich, NK cell- infiltrated and T cell-depleted TME. Sc/snSeq data confirmed these observations, showing a macrophage/microglia-rich brain TME. Compared to adult tumors, (CD8+) T cell infiltration and macrophage infiltration was low for all pediatric tumor types. Integrated IHC and sc/snSeq data were visualized in interactive heatmaps, publicly available on R2 as a comprehensive atlas [https://hgserver1.amc.nl/cgi-bin/r2/main.cgi?option=imi2_targetmap_v1; map Immune_landscape_mm2(by patient)_v4]. ConclusionWe provide a comprehensive, integrated overview of the immune landscape of pediatric brain and solid tumors. These insights can aid the development and selection of immunotherapeutic strategies for specific pediatric cancers, tailored to their unique immune characteristics.

immunology↗

bioRxiv2023

Single-cell RNA sequencing reveals microenvironment context-specific routes for epithelial-mesenchymal transition in pancreas cancer cells

In the PDAC tumor microenvironment, multiple factors initiate the epithelial-mesenchymal transition (EMT) that occurs heterogeneously among transformed ductal cells, but it is unclear if different drivers promote EMT through common or distinct signaling pathways. Here, we use single-cell RNA sequencing (scRNA-seq) to identify the transcriptional basis for EMT in pancreas cancer cells in response to hypoxia or EMT-inducing growth factors. Using clustering and gene set enrichment analysis, we find EMT gene expression patterns that are unique to the hypoxia or growth factor conditions or that are common between them. Among the inferences from the analysis, we find that the FAT1 cell adhesion protein is enriched in epithelial cells and suppresses EMT. Further, the receptor tyrosine kinase AXL is preferentially expressed in hypoxic mesenchymal cells in a manner correlating with YAP nuclear localization, which is suppressed by FAT1 expression. AXL inhibition prevents EMT in response to hypoxia but not growth factors. Relationships between FAT1 or AXL expression with EMT were confirmed through analysis of patient tumor scRNA-seq data. Further exploration of inferences from this unique dataset will reveal additional microenvironment context-specific signaling pathways for EMT that may represent novel drug targets for PDAC combination therapies.

cancer biology↗

bioRxiv2026

Benchmarking Imputation Methods for Single-Cell RNA Sequencing Data Using Peripheral Blood Mononuclear Cells from Acute Myocardial Infarction Patients

Acute myocardial infarction (AMI) remains one of the leading causes of mortality worldwide, and the following post-effects, such as post-AMI inflammation and tissue repair, involve peripheral blood mononuclear cells playing a critical role. The influence of imputation methods in biological data is assessed with respect to high-resolution single-cell RNA sequencing (scRNAseq) data relevant to these cells. Still scRNAseq data often encounter a lot of dropout events, leading to sparse and noisy datasets, hampering downstream results. To assess the influence of the missingness in the data, we artificially impose different levels of dropout in available scRNAseq data by leveraging various imputation techniques. Specifically, we introduce artificial missingness at 10%, 20%, and 30% levels under a missing completely at random (MCAR) framework, repeated across 10 independent runs. We benchmarked six imputation strategies - MAGIC, IterativeImputer, KNNImputer, Mean Imputation, SoftImpute, and a Generative adversarial network (GAN) - based approaches using multiple evaluation metrics: marker gene preservation, clustering consistency (Adjusted Rand Index - ARI), gene-wise correlation with ground truth, and structural separation (silhouette scores). The results clearly underline that no single imputation method dominated across all metrics. Overall, Mean and KNN imputers showed limited recovery across all benchmarks. GAN excelled in global transcriptional recovery and SoftImpute in preserving biologically meaningful cell-type signals. Our results highlight the importance of selecting the imputation methods as part of the pre-processing step towards the downstream biological questions related to transcriptome recovery, detection of marker genes, or maintaining cell-type-specific resolution.

bioinformatics↗

bioRxiv2026

Single-cell RNA sequencing of CTLA-4 and PD-1 blockade in pulmonary paracoccidioidomycosis highlights a protective transcriptional program mediated by activated Th17 cells, neutrophils and macrophages

Pulmonary paracoccidioidomycosis (PCM) relies on a finely balanced lung-immune network in which Th17, Treg, neutrophils, and macrophages orchestrate fungal control and tissue integrity. Furthermore, within the context of single-cell sequencing, little is known about how immune checkpoint inhibition modulates this balance during systemic mycosis. In a previous study we verified that the blockade of checkpoint molecules (CTLA-4 and PD-1) restores protective immunity that reduces fungal loads, tissue pathology and mortality of infected mice. Here, we have further studied this model by single-cell RNA sequencing on lung leukocytes from mice infected with Paracoccidioides brasiliensis and treated with anti-CTLA-4 or anti-PD-1 antibodies to define the cellular and molecular consequences of checkpoint blockade in vivo. We generated a high-resolution atlas covering T cells, neutrophils, macrophages/monocytes, B cells, NK cells, and epithelial subsets. Checkpoint inhibition consistently remodeled the CD4 T cell compartment toward a Th17-enriched program, with reduced interleukin-10 expressing Treg frequencies and a prominent interleukin-17A (IL-17), C-C chemokine receptor type 2, CXC chemokine (CXC) receptor type 6, CD44 (Il17aCcr2Cxcr6Cd44) signature. This shift was accompanied by the expansion and activation of neutrophils and macrophages expressing tumor necrosis factor and chemokines (including CXC motif chemokine ligand (Cxcl1, Cxcl2 and Ccl4), microbicidal-associated genes (S100 calcium-binding protein A8 and A9), and regulatory mediators such as secretory leukocyte protease inhibitor and interleukin-15. Ligand-receptor and trajectory analyses revealed a reinforced Th17-myeloid communication axis, particularly under CTLA-4 blockade, converging on IL17-centered inflammatory circuits while attenuating canonical Treg checkpoints (cytotoxic T-lymphocyte-associated protein 4, programmed cell death protein 1, interleukin-10). Together, these data demonstrate that anti-CTLA-4 and anti-PD-1 immunotherapies profoundly rewire the lung-immune microenvironment during PCM, amplifying effector Th17-neutrophil-macrophage networks that benefits protective antifungal activity Our work provides a mechanistic framework for evaluating immune checkpoint inhibitors in chronic fungal infections.

immunology↗

bioRxiv2021

Reference transcriptomes of porcine peripheral immune cells created through bulk and single-cell RNA sequencing

Pigs are a valuable human biomedical model and an important protein source supporting global food security. The transcriptomes of peripheral blood immune cells in pigs were defined at the bulk cell-type and single cell levels. First, eight cell types were isolated in bulk from peripheral blood mononuclear cells (PBMCs) by cell sorting, representing Myeloid, NK cells and specific populations of T and B cells. Transcriptomes for each bulk population of cells were generated by RNA-seq with 10,974 expressed genes detected. Pairwise comparisons between cell types revealed specific expression, while enrichment analysis identified 1,885 to 3,591 significantly enriched genes across all 8 cell types. Gene Ontology analysis for the top 25% of significantly enriched genes (SEG) showed high enrichment of biological processes related to the nature of each cell type. Comparison of gene expression indicated highly significant correlations between pig cells and corresponding human PBMC bulk RNA-seq data available in Haemopedia. Second, higher resolution of distinct cell populations was obtained by single-cell RNA-sequencing (scRNA-seq) of PBMC. Seven PBMC samples were partitioned and sequenced that produced 28,810 single cell transcriptomes distributed across 36 clusters and classified into 13 general cell types including plasmacytoid dendritic cells (DC), conventional DCs, monocytes, B cell, conventional CD4 and CD8 {beta} T cells, NK cells, and {gamma}{delta} T cells. Signature gene sets from the human Haemopedia data were assessed for relative enrichment in genes expressed in pig cells and integration of pig scRNA-seq with a public human scRNA-seq dataset provided further validation for similarity between human and pig data. The sorted porcine bulk RNAseq dataset informed classification of scRNA-seq PBMC populations; specifically, an integration of the datasets showed that the pig bulk RNAseq data helped define the CD4CD8 double-positive T cell populations in the scRNA-seq data. Overall, the data provides deep and well-validated transcriptomic data from sorted PBMC populations and the first single-cell transcriptomic data for porcine PBMCs. This resource will be invaluable for annotation of pig genes controlling immunogenetic traits as part of the porcine Functional Annotation of Animal Genomes (FAANG) project, as well as further study of, and development of new reagents for, porcine immunology.

immunology↗

bioRxiv2020

Identification of silkworm hemocyte subsets and analysis of their response to BmNPV infection based on single-cell RNA sequencing

A wide range of hemocyte types exist in insects but a full definition of the different subclasses is not yet established. The current knowledge of the classification of silkworm hemocytes mainly comes from morphology rather than specific markers, so our understanding of the detailed classification, hemocyte lineage and functions of silkworm hemocytes is very incomplete. Bombyx mori nucleopolyhedrovirus (BmNPV) is a representative member of the baculoviruses, which are a major pathogens that specifically infects silkworms and cause serious loss in sericulture industry. Here, we performed single-cell RNA sequencing (scRNA-seq) of silkworm hemocytes in BmNPV and mock-infected larvae to comprehensively identify silkworm hemocyte subsets and determined specific molecular and cellular characteristics in each hemocyte subset before and after viral infection. A total of 19 cell clusters and their potential marker genes were identified in silkworm hemocytes. Among these hemocyte clusters, clusters 0, 1, 2, 5 and 9 might be granulocytes (GR); clusters 14 and 17 were predicted as plasmatocytes (PL); cluster 18 was tentatively identified as spherulocytes (SP); and clusters 7 and 11 could possibly correspond to oenocytoids (OE). In addition, all of the hemocyte clusters were infected by BmNPV and some infected cells carried high viral-load in silkworm larvae at 3 day post infection (dpi). Interestingly, BmNPV infection can cause severe and diverse changes in gene expression in hemocytes. Cells belonging to the infection group mainly located at the early stage of the pseudotime trajectories. Furthermore, we found that BmNPV infection suppresses the immune response in the major hemocyte types. In summary, our scRNA-seq analysis revealed the diversity of silkworm hemocytes and provided a rich resource of gene expression profiles for a systems-level understanding of their functions in the uninfected condition and as a response to BmNPV.

microbiology↗

bioRxiv2020

The type 1 diabetes at-risk allele at rs3842753 increases beta cell INS mRNA expression and variance in a meta-analysis of single cell RNA sequencing data

Type 1 diabetes is characterized by the autoimmune destruction of insulin secreting {beta} cells. Genetic variations upstream at the insulin (INS) locus contribute to ~10% of type 1 diabetes heritable risk. Multiple studies showed an association between rs3842753 C/C genotype and type 1 diabetes susceptibility, but the molecular mechanisms remain unclear. To date, no large-scale studies have looked at the effect of genetic variation at rs3842753 on INS mRNA at the single cell level. We aligned all human islet single cell RNA sequencing datasets available to us in 2020 to the reference genome GRCh38.98 and genotyped rs3842753, integrating 2315 {beta} cells and 1223 {beta}-like cells from 13 A/A protected donors, 23 A/C heterozygous donors, and 35 C/C at-risk donors, including adults without diabetes and with type 2 diabetes. INS expression mean and variance were significantly higher in single {beta} cells from females compared with males. Comparing across {beta} cells and {beta}-like cells, we found that rs3842753 C containing cells (either homozygous or heterozygous) had the highest INS expression. We also found that {beta} cells with the rs3842753 C allele had significantly higher ER stress marker gene expression compared to the A/A homozygous genotype. These findings support the emerging concept that inherited risk of type 1 diabetes may be associated with inborn, persistent elevated insulin production which may lead to {beta} cell ER stress and fragility.

cell biology↗

bioRxiv2019

Dissecting the heterogeneity of DENV vaccine-elicited cellular immunity using single-cell RNA sequencing and cellular metabolic profiling

Generating effective and durable T cell immunity is a critical prerequisite for vaccination against dengue virus (DENV) and other viral diseases. Understanding the precise molecular mechanisms of vaccine-elicited T cell immunity remains a critical knowledge gap in vaccinology. In this study, we utilized single-cell RNA sequencing (scRNAseq) and TCR clonotype analysis to demonstrate that a unique transcriptional signature is present in acutely-activated and clonally-expanded T cells that become committed to the memory repertoire. This effector-associated transcriptional signature is dominated by a unique metabolic transcriptional program. Based on this transcriptional signature, we were able to define a set of functional markers that identify the most potent and durable vaccine-reactive memory precursor CD8+ T cells. The transferrin receptor (CD71) other important transporters of amino acids, and direct measurements of glucose and fatty acid uptake, were further validated as early markers of durable T cell memory using conventional flow cytometry. These data suggest that generating durable T cell immunity is a process that is determined by metabolic programming and metabolite availability during the acute phase of the immune response. This study illustrates the power of scRNAseq as an analytical tool to assess the molecular mechanisms of host control and vaccine modality in determining the magnitude, diversity, and persistence of vaccine-elicited cell-mediated immunity.

immunology↗

bioRxiv2021

Dissecting the Cellular Landscape and Transcriptome Network in Viral Myocarditis by Single-Cell RNA Sequencing

Myocarditis induced with Coxsackievirus B3 (CVB3) is commonly employed to study viral pathogenesis in mice. Although infectious virus is cleared after the acute phase, affected animals chronically develop the features of dilated cardiomyopathy, which may involve the mediation of immune and non-immune cells. To dissect this complexity, we performed single-cell RNA sequencing on heart cells obtained from healthy and myocarditic mice, leading us to note that myocarditic mice had significantly higher proportions of myeloid cells, CD4 and CD8 T cells, and fibroblasts, whereas NK cells, ILCs and B cells were low. While the transcriptome profiles of myeloid cells revealed detection of monocytes and macrophages of M2 phenotype with pathways important in immune metabolism and inflammation, T cells consisted of Th17 cells, CTLs, and Treg cells with transcriptome signatures critical for cytotoxic functions. Although fibroblasts detected in myocarditic mice were phenotypically heterogeneous, their transcriptomes played roles in fibrosis and regulation of inflammation and immune responses. Additionally, analysis of intercellular communication networks revealed unique interactions and signaling pathways in the cardiac cellulome, whereas myeloid cells and T cells in myocarditic mice revealed uniquely upregulated transcription factors modulating cardiac remodeling functions. Taken together, our data suggest that M2 cells, T cells, and fibroblasts may cooperatively or independently participate in the pathogenesis of viral myocarditis.

immunology↗

bioRxiv2022

Single-cell RNA sequencing identifies regulators of differentiation and nutritional cues in Drosophila female germ cells

Drosophila ovarian germline stem cells (GSCs) are powerful model for stem cell research. However, due to the scarcity of GSCs in ovarian tissue, it is difficult to obtain the transcriptional profile of GSCs and identify novel GSC markers. In this study, we took advantage of single cell RNA sequencing (scRNA-seq) to profile the germline cells and somatic cells in wild type Drosophila ovary. We then performed an in vivo RNAi screen and network analysis to identify genes that are involved in the early stages of germ cell differentiation. We identified 33 genes with limited expression during early germ cell development and identified 19 genes that potentially regulate germ cell differentiation. Among these, an uncharacterized gene, which we named eggplant (eggpl), is highly expressed in GSC and downregulated in early daughter cells. Upon RNAi knockdown of eggpl, we observed an increase in germ cell proliferation, an accumulation of cysts in the early mitotic (2- and 4-cell) stages and an increase in overall ovary size compared to control when flies were maintained on a standard diet. In flies fed a rich yeast diet, the expression of eggpl was significantly lower and the effects of eggpl RNAi were suppressed, suggesting that downregulation of eggpl may link nutritional status to germ cell proliferation and differentiation. We also found that the matrix metalloproteases, Mmp1 and Mmp2 as well as the tissue inhibitor of metalloproteases (Timp) are additional regulators of eggpl. Collectively, this study provides new insight into the signaling networks that regulate early germ cell development and identifies eggpl as a key player in this process.

genetics↗

bioRxiv2020

Diversity of developing peripheral glia revealed by single cell RNA sequencing

The peripheral nervous system responds to a wide variety of sensory stimuli, a process that requires great neuronal diversity. These diverse peripheral sensory neurons are closely associated with glial cells that originate from the neural crest (NC). However, the molecular nature and origins of diversity among peripheral glia is not understood. Here we used single cell RNA sequencing to profile and compare developing and mature glia from somatosensory lumbar dorsal root ganglia (DRG) and auditory spiral ganglia (SG). We found that the glial precursors (GPs) differ in their transcriptional profile and prevalence in these two systems. Despite their unique features, somatosensory and auditory GPs undergo convergent differentiation to generate myelinating and non-myelinating Schwann cells that are molecularly uniform. By contrast, although satellite glia surround the neuronal cell bodies in both ganglia, we found that those in the SG express multiple myelination-associated genes, while DRG satellite cells express components that suppress myelination. Lastly, we identified a set of glial signature genes that are also expressed by placode-derived supporting cells, providing new insights into commonalities among glia across the nervous system. This comprehensive survey of gene expression in peripheral glia constitutes a valuable resource for understanding how glia acquire specialized functions and how their roles differ across sensory modalities.

neuroscience↗

bioRxiv2026

LongAllele: a joint inference framework for allele-specific analysis on long-read bulk and single-cell RNA sequencing

Allele-specific analysis from RNA-seq is a powerful approach to characterize cis-regulatory effects. However, existing methods remain limited in both haplotype inference and allelic testing. Their haplotype-inference workflows separate variant calling, haplotype phasing, and read-haplotype assignment into sequential steps, failing to fully exploit within-read single-nucleotide variant (SNV) linkage information and propagating errors into downstream allelic analysis. At the testing stage, they ignore non-phasable reads lacking heterozygous SNVs, biasing calls and inflating false positives, and remain incomplete across gene-, isoform-, and local-event-level variant effects. Here, we present LongAllele, a statistical framework that employs an expectation-maximization algorithm to jointly infer heterozygous variants, haplotype structure, and read-haplotype assignments from long-read bulk and single-cell RNA sequencing. LongAllele further introduces phasability-aware testing that explicitly accounts for non-phasable reads, avoiding inflated false-positive calls when haplotype information is incomplete. It also enables comprehensive allelic testing across gene-level allele-specific expression (ASE), isoform-level allele-specific transcript usage (ASTU), and local-event-level haplotype-associated exon and junction usage (HAEU and HAJU), providing a multi-scale view of cis-regulation across biological contexts. We applied LongAllele to long-read RNA-seq datasets spanning GTEx (multi-tissue bulk), peripheral blood mononuclear cells (single-cell), human hippocampus (single-nucleus), and human cortex from two Alzheimers disease (AD) case-control cohorts (bulk, Oxford Nanopore and PacBio). LongAllele consistently revealed greater context dependence in expression-level than isoform-level allelic regulation across tissues, cell types, and disease states, and pinpointed high-impact regulatory variants including rare splice-site mutations missed by standalone variant callers. It further showed that purifying selection constrains allelic imbalance at both gene and isoform levels and resolved AD-associated variant effects in individual transcriptomes across long-read platforms.

bioinformatics↗

bioRxiv2025

Single Cell RNA Sequencing Reveals Gene Expression Continuums Along the Spatial Hierarchy of the Pulmonary Circulation

BackgroundThe lung vasculature is comprised of a series of branching vessels extending from the main pulmonary artery to the alveolar capillaries, then back to the pulmonary veins. Lung endothelial cells (EC) exist along this continuum, exposed to gradients of shear stress, oxygen tension and pressure. Single cell RNA sequencing (scRNA-seq) has identified lung EC subsets, but many aspects of the vascular continuum, including vessel size and capillary polarity remain undefined from transcriptomic data. MethodsWe created an endothelial-enriched scRNA-seq dataset from the P3 mouse lung. Using diffusion pseudotime across all lung EC, we developed an analytical framework to delineate transcriptomic gradients and assign vessel-size scores to categorize individual endothelial cells (EC) along the vascular continuum. We confirmed size-related gene expression patterns with fluorescence in situ hybridization. ResultsWe categorized capillary 1, arterial and venous EC along two gradients: arterio-venous zonation and vessel size. This approach distinguished large arteries from arterioles, large veins from venules, and revealed arterio-venous polarity within the capillaries. Our data recapitulated previously established zonally defined cell signaling axes, such as high Cxcl12-Cxcr4 signaling in arterioles. We also identified unique cellular communication occurring in large versus small arteries and veins, and localized injury-induced venous EC proliferation to vessels of specific size. This analytical framework was successfully applied to several published mouse and human datasets across different stages of lung development. ConclusionsThese findings provide a comprehensive transcriptional map of EC across the pulmonary vascular tree, enabling assignment of each individual cell to vessels with defined size and position. This framework offers spatial inferences and novel mechanistic insights from scRNA-seq data sets that may elucidate therapeutic targets to treat pulmonary vascular diseases affecting specific vascular segments. We speculate that similar frameworks could be applied to tissues outside the lung.

cell biology↗

bioRxiv2021

Spermiogenesis alterations in the absence of CTCF revealed by single cell RNA sequencing

CTCF is an architectonical protein that organizes the genome inside the cell nucleus in almost all eukaryotic cells. There is evidence that CTCF plays a critical role during spermatogenesis as its depletion produces abnormal sperm and infertility. However, the defects produced by the absence of CTCF throughout spermatogenesis have not been characterized. In this work, we performed single cell RNA sequencing in spermatogenic cells without CTCF. We uncovered defects in transcriptional programs that explain the severity of the damage in the produced sperm. At early stages of spermatogenesis, transcriptional alterations are mild. As germ cells go throughout the specialization stage or spermiogenesis, transcriptional profiles become more altered. We found spermatid defects that support the alterations in the transcriptional profiles, and thus we conclude that CTCF depletion alters several transcriptional profiles mostly during spermiogenesis. Our data highlights the importance of CTCF at the different stages of spermatogenesis.

molecular biology↗

bioRxiv2025

Single-cell RNA sequencing in Hirschsprungs disease tissues reveals lack of neuronal differentiation in the aganglionic colon segment

The enteric nervous system (ENS) is a complex network of neurons and glial cells. Hirschsprungs disease (HSCR) is a congenital condition characterized by the absence of ganglion cells in the distal colon, leading to functional bowel obstruction. In this study, we used single-cell RNA sequencing (scRNA-seq) and whole genome sequencing (WGS) to analyze healthy and aganglionic colon segments from HSCR patients. Using scRNA-seq, we identified 13 major cell types in patient samples and observed that neural progenitor cells were present in both healthy and aganglionic colon regions, while mature neurons were absent from aganglionic colon. In these progenitor cells, critical differentiation pathway genes displayed reduced expression in the aganglionic colon, suggesting a disruption in their transition to mature neuronal cell types. Furthermore, transcriptomic analysis revealed significant alterations in gene expression across several stromal cell types. These transcriptomic shifts, particularly in mast cells, support the hypothesis that altered gene expression in the microenvironment of neural progenitor cells contributes to impaired differentiation. Our findings support the hypothesis that neural precursors in HSCR are capable of migration, but they are defective in their differentiation to mature cell types. Our analysis provides insights into potential therapeutic targets to stimulate neurogenesis in the aganglionic colon.

genomics↗

bioRxiv2019

Single-cell RNA sequencing of adult Drosophila ovaryidentifies transcriptional programs governing oogenesis

Oogenesis is a complex developmental process that involves spatiotemporally regulated coordination between the germline and supporting, somatic cell populations. This process has been modelled extensively using the Drosophila ovary. While different ovarian cell types have been identified through traditional means, the large-scale expression profiles underlying each cell type remain unknown. Using single-cell RNA sequencing technology, we have built a transcriptomic dataset for the adult Drosophila ovary and connected tissues. This dataset captures the entire transcriptional trajectory of the developing follicle cell population over time. Our findings provide detailed insight into processes such as cell-cycle switching, migration, symmetry breaking, nurse cell engulfment, egg-shell formation, and signaling during corpus luteum formation, marking a newly identified oogenesis-to-ovulation transition. Altogether, these findings provide a broad perspective on oogenesis at a single-cell resolution while revealing new genetic markers and fate-specific transcriptional signatures to facilitate future studies.

developmental biology↗

bioRxiv2024

Single-cell RNA sequencing of iPSC-derived brain organoids reveals Treponema pallidum infection inhibiting neurodevelopment

Congenital syphilis is a vertically transmitted bacterial infection caused by Treponema pallidum, often causing multidomain neurodevelopmental disabilities. However, little is known about the pathogenesis of this disease. Brain organoids platform derived from the induced pluripotent stem cell (iPSC) is exposed to T. pallidum infection for modelling congenital neurodevelopmental impairment. Single-cell RNA sequencing is used for identifying the subpopulations of differentially expressed genes and cellular heterogeneity and reconstructing differentiation trajectories following T. pallidum infection. The results reveal that T. pallidum infection influences the formation of neural rosette structures, reduces the cell number of the neural progenitor cell subcluster 1B (subNPC1B) and hindbrain neurons, and affects the neurodevelopment of the brain organoid. Moreover, it is speculated that T. pallidum inhibits the hindbrain neuron cell number through the suppression of subNPC1B subgroup in the organoids and inhibits transcription factor 3 activity in the subNPC1B-hindbrain neuronal axis. This is the first report on the inhibited effects of T. pallidum on the neurodevelopment of the iPSC-derived brain organoid model. T. pallidum could inhibit the differentiation of subNPC1B in brain organoids, thereby reducing the differentiation from subNPC1B to hindbrain neurons, and ultimately affecting the development and maturation of hindbrain neurons.

neuroscience↗

bioRxiv2022

Single-cell RNA sequencing reveals molecular features of postnatal maturation in the murine retinal pigment epithelium

Transcriptomic analysis of the mammalian retinal pigment epithelium (RPE) aims to identify cellular networks that influence ocular development, maintenance, function, and disease. However, available evidence points to RPE cell heterogeneity in the native tissue, which adds complexity to transcriptomic analysis. Here, to assess cell heterogeneity, we performed single-cell RNA sequencing of RPE cells from two young adult male C57BL/6J mice. Following quality control to ensure robust transcript identification limited to cell singlets, we detected 13,858 transcripts among 2,667 and 2,846 RPE cells, respectively. Dimensional reduction by principal component analysis and uniform manifold approximation and projection revealed six distinct cell popu-lations. All clusters expressed transcripts typical of RPE cells; the smallest (C1, containing 1-2% of total cells) exhibited hallmarks of stem and/or progenitor cells. Placing C1-6 along a pseudotime axis suggested a relative decrease in melanogenesis and stem/progenitor gene expression, and a corresponding increase in visual cycle gene expression upon RPE maturation. K-means testing of all detected transcripts identified additional expression patterns that may advance understanding of RPE stem/pro-genitor cell maintenance and the evolution of cellular metabolic networks during development. This work provides new insights into the transcriptome of the mouse RPE and a baseline for identifying experimentally induced transcriptional changes in future studies of this tissue.

systems biology↗