Biology subjects

Robson, P.

Publications and source records attributed to Robson, P..

At least 19 recordsLinked to original sources

bioRxiv2026

The Genetic Discovery (GeDi) resource: Deep characterization of a multi-ancestry panel of human reference iPSCs for functional genomic studies

Human induced pluripotent stem cells (iPSCs) are essential tools for disease modelling, drug discovery, and functional genomics, yet the field remains anchored to a small number of reference lines, limiting our understanding of how genetic background shapes cellular phenotypes across human populations. Here we describe the Genetic Discovery iPSC panel (GeDi), eight clonal iPSC lines reprogrammed from male and female donors that broadly span global human population diversity. Ancestry analysis confirmed that each line's genetic profile is concordant with donor self-reported ancestry. All GeDi lines are pluripotent and passed comprehensive quality control, demonstrating Sendai virus clearance, intact p53 pathway integrity, reproducible proliferative capacity, and compatibility with standardized genome editing workflows. Transcriptome profiling across five differentiated lineages covered 80% of annotated protein-coding genes and revealed stable donor-intrinsic variability in gene expression within each lineage. Haplotype-resolved genome assemblies were used to catalog structural variants and regions of absence of heterozygosity invisible to short-read sequencing. Whole-genome methylation analysis confirmed successful epigenetic reprogramming, catalogued the status of imprinted loci and captured the early dynamics of erosion of X chromosome inactivation (XCI) in female lines. The GeDi panel is available from The Jackson Laboratory as a quality-controlled resource designed to support functional genomic studies across varied genetic backgrounds.

cell biology↗

bioRxiv2026

Spatial organization of voltage-gated ion channel expression across molecularly defined neuronal populations in the mouse mammillary bodies

The mammillary bodies (MB) are a hypothalamic component of the limbic Papez circuit that plays a critical role in spatial and episodic memory in mammals. Degeneration of the MB occurs in disorders associated with cognitive impairment, including Korsakoff's syndrome and Alzheimer's disease, yet the molecular organization and intrinsic properties of MB neurons remain poorly understood. Recent single-cell RNA sequencing identified multiple transcriptionally distinct neuronal populations within the MB and suggested that they differentially express voltage-gated ion channels that regulate neuronal excitability. Here, we used fluorescence in situ hybridization (FISH) to define the anatomical organization of cluster-enriched molecular markers and determine the spatial distribution of transcripts encoding voltage-gated sodium (NaV), potassium (KV), and hyperpolarization-activated cyclic nucleotide-gated (HCN) channels among defined subregions of the mouse MB. We found that marker transcripts occupy characteristic but partially overlapping spatial domains that broadly correspond to classical anatomical subdivisions. In addition, several ion channel transcripts, including Scn1a, Scn2a, Kcnq2, Kcnq3, and Hcn1, exhibited distinct patterns of enrichment across molecularly defined neuronal populations and MB subregions. Multiplex FISH further revealed unexpected co-expression of Scn1a and Scn2a within Pvalb-enriched neuronal populations, while whole-cell recordings demonstrated distinct intrinsic firing properties of neurons in the lateral and medial mammillary nuclei. Together, these findings establish a molecular framework linking neuronal population identity with voltage-gated ion channel expression in the MB and provide a foundation for future studies investigating how cell type-specific differences in intrinsic excitability contribute to memory function and neurological disease.

neuroscience↗

bioRxiv2026

Distinct senescent β-cell senotypes differentially drive islet aging and dysfunction

Biological aging greatly impacts the bodys ability to handle glucose, and represents a major risk factor the development and progression of type 2 diabetes (T2D). Nonetheless, despite advances in cellular senescence research and the development of new senolytic therapies, the heterogeneity of cellular senescence in the human endocrine pancreas, as well as its roles in normal aging, remains to be elucidated at the single-cell level. Here, we performed single-cell-resolved spatial proteomics and transcriptomics on intact pancreas from 26 donors (ages 20-80) and multiplexed single-cell RNA sequencing and functional assays on dispersed islets from 14 donors (ages 34-69). We identify two discrete SnC subpopulations distinguished by relative expression of CDKN1A and CDKN2A. CDKN1A senescent cells (SnCs) exhibit loss of {beta}-cell identity, impaired insulin secretion, and a proinflammatory SASP associated with increased islet immune infiltration. In contrast, CDKN2A SnCs retain transcriptional identity and functional competence, with lower inflammatory signaling. Together, these findings identify heterogeneous and functionally divergent senotypes in the human pancreas, distinguishing an adaptive (CDKN2A) from a maladaptive (CDKN1A) senescence program, thus providing a mechanism-guided framework for senescence-targeted therapies in T2D.

cell biology↗

bioRxiv2026

DIANNE: Segmentation-Free Localization of Histology Differential Attributes

Pathologist-guided distinctions within histology and spatial omic images provide insights into health and disease, with digital pathology leveraging artificial intelligence to automate such assessments. To train computational models, current digital pathology methods rely on upfront manual annotations, which are time-consuming to generate. Pre-annotation is poorly suited to investigating novel spatial behaviors--a major need driven by advances in spatial profiling--for which annotation criteria and data needs will be uncertain. To address these challenges, we present DIANNE, a digital pathology annotation support and discovery approach for rapid training and inference of spatial differential attributes, enabled by train-time Positive Class Mixup Augmentation. DIANNE can compute foundation model-derived segmentation-free localization of differential classifiers across whole slide H&E images within seconds on a workstation, enabling interactive investigation of spatial niches. Predictive models can be re-trained in real-time in response to patch or regional annotation changes, clarifying determinative biological attributes across slides from only a few dozen annotated patches. We demonstrate the effectiveness of DIANNE for tumor detection, artifact identification, and exploration of pancreatic, fetal membranes and kidney tissue structures. DIANNE also provides analogous capabilities for IHC, multiplex immunofluorescence, and registered spatial transcriptomic+H&E images. DIANNE is implemented in a Jupyter toolkit, enabling rapid development of high-resolution classifiers from weakly-supervised training. DIANNE provides a practical system to quantitatively understand known and novel spatial phenotypes.

pathology↗

bioRxiv2025

spCorr: flexible and scalable inference of spatially varying correlation in spatial transcriptomics

Spatial transcriptomics has transformed our ability to explore gene expression within its tissue context, enabling us to dissect subtle yet biologically significant variations in situ. While numerous computational methods have been proposed for detecting Spatially Varying Genes (SVGs) expression by modeling each individual gene separately, much less effort has been devoted to understanding how correlations between genes change across space. Such Spatially Varying Correlations (SVCs) are critical for understanding biological processes such as gene regulatory mechanisms shaped by local tissue environments, yet existing tools remain limited for this task. To address this gap, we present spCorr, a flexible and scalable regression framework for studying SVCs. spCorr provides interpretable, spot-level estimates of gene correlation and detects gene pairs whose correlations vary across locations or between tissue domains. Through extensive simulations and real-data analyses, we show that spCorr achieves high detection power, reliably controls the False Discovery Rate (FDR), and is computationally efficient. Importantly, spCorr reveals biologically meaningful correlation patterns that highlight fine-scale tissue structures, gene module functions, and region-specific interactions, offering new opportunities to study coordinated gene regulation in spatial transcriptomics.

bioinformatics↗

bioRxiv2025

High-Resolution Spatial Transcriptomics Reveals Fibroblast and Neuroimmune Microenvironments in Endometriosis Lesions

Endometriosis is a chronic, systemic, inflammatory disease characterized by the presence of endometrium-like tissue growing outside of the uterus. One of its main symptoms is chronic pain and inflammation leading to a decreased quality of life. This is a common disease, as at least one in ten female-born individuals have endometriosis. Yet the understanding of the mechanisms that drive pain symptoms and disease progression remain poorly defined. This study establishes the precise spatial transcriptomic cartography of human ovarian and peritoneal lesions, two of the most commonly found lesions. We identified shared spatial features across lesion types, including immune cell infiltration, fibroblast specific compartments surrounding epithelial glands, and distinct distributions of neuronal and macrophage subsets. We precisely defined sensory neuronal subtypes, and mapped their spatial location relative to immune cells. We further validate the epithelial-neuronal interactome, using an in vitro 3D model of peripheral sensory brain organoids co-cultured with human endometriosis epithelial and fibroblast cells. By mapping spatial cellular interactions and identifying conserved features across lesion types linked to pain, our study provides emerging insights into endometriosis pathophysiology, paving the way for the development of novel targeted therapeutic strategies.

cell biology↗

bioRxiv2025

A human and mouse subpopulation of senescent β-cells induces pathologic dysfunction through targetable paracrine signaling

Cellular senescence is a stress response mechanism marked by irreversible growth arrest, upregulation of antiapoptotic pathways, loss of cellular function, and remodelling of the cellular secretory profile. In both humans and mice, pancreatic {beta}-cells undergo senescence with age and insulin resistance. Targeted removal of senescent cells in mouse models of diabetes improves glucose homeostasis, demonstrating the role {beta}-cell senescence in diabetes progression. In contrast, {beta}-cell senescence also promotes immune surveillance, promoting {beta}-cell survival and function. Thus, a better understanding of senescent cells phenotypic and functional heterogeneity is needed to develop effective therapeutic strategies. Herein, we show that subpopulations of senescent {beta}-cells in mice and humans, which were identified through the expression of Cdkn1a (encoding p21Cip1) and Cdkn2a (encoding p16Ink4a) by single-cell RNA sequencing (scRNA-seq), flow cytometry, spatial transcriptomics, and spatial proteomics, exhibit distinct transcriptional and functional identities. The predominant senescent {beta}-cell subpopulation expressed Cdkn1a and was characterized by a lack of glucose responsiveness, high basal insulin secretion, and transcription of canonical SASP factors. The SASP of Cdkn1a-expressing {beta}-cells had non-cell autonomous effects on neighbouring cells. A subset of four SASP factors from Cdkn1a+ cells was sufficient to induce secondary senescence and {beta}-cell dysfunction in vitro. JAK inhibitors (JAK1/2 and JAK1/3) counteracted secondary senescence induction and restored {beta}-cell function in high-fat diet-fed mice and human islets from donors with or without type 2 diabetes. GRAPHICAL ABSTRACT O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=196 SRC="FIGDIR/small/648438v1_ufig1.gif" ALT="Figure 1"> View larger version (34K): org.highwire.dtl.DTLVardef@9b8addorg.highwire.dtl.DTLVardef@1b9c4eborg.highwire.dtl.DTLVardef@12f2964org.highwire.dtl.DTLVardef@1468297_HPS_FORMAT_FIGEXP M_FIG C_FIG

developmental biology↗

bioRxiv2025

Prediction of Outcome from Spatial Protein Profiling of Triple-Negative Breast Cancers

In tumors, reciprocal spatial interactions between immune cells, their mediators, the extracellular matrix, and mutated neoplastic cells impact all aspects of treatment resistance. The operational mechanisms of these interactions are foundational for developing insights and targets for cancer therapy and prevention. Spatial quantification of the tumor microenvironment system from image data has untapped potential for patient stratification. Here, we present SparTile, a powerful computational approach for analysis of multiplex proteomics images to reveal clinically relevant structural organization in the tumor microenvironment. SparTile enables the robust unbiased identification and characterization of tumor microenvironments based on spatial relationships among protein markers without the need for cell segmentation or classification. Applied to tissues of patients with triple negative breast cancer (TNBC), an aggressive subtype of breast cancer, SparTile identified repeatable microenvironments with specific cellular relationships. These included microenvironments characterized by risk markers such as Ki67+ (p-value= 0.052) and vimentin+ (p-value<0.01) tumor cells, which correlate with poor survival. Furthermore, myeloid markers in an MX1 positive tumor environment correlate with shorter survival (p-value=0.04). Finally, we identified a relative distance between tumor and myeloid cell markers as a strong prognostic risk factor in multivariate Cox models (p-value=0.01). This distance metric was externally validated on two datasets of breast cancer multiplex images (p-values<0.01). Thus, unbiased protein-based and segmentation-free spatial analysis is effective for identifying clinically relevant biomarkers from multiplex tumor images and identifies novel predictive biology.

cancer biology↗

bioRxiv2023

Immunosuppressive tumor microenvironment of osteosarcoma

Osteosarcoma is the most common malignant bone tumor in children, characterized by a high degree of genomic instability, resulting in copy-number alterations and genomic rearrangements without disease-defining recurrent mutations. Clinical trials based on molecular characterization have failed to find new effective therapies or improve outcomes over the last 40 years. To better understand the immune microenvironment of osteosarcoma, we performed single-cell RNA sequencing on six tumor biopsy samples, combined with a previously-published cohort of six samples. Additional osteosarcoma samples were profiled using spatial transcriptomics for validation of discovered subtypes and to add spatial context. Analysis revealed immunosuppressive cells, including myeloid-derived suppressor cells (MDSCs), regulatory and exhausted T-cells, and LAMP3+ dendritic cells. Using cell-cell communication modeling, we identified robust interactions between MDSCs and other cells, leading to NF-{kappa}B upregulation and an immunosuppressive microenvironment, as well as interactions involving regulatory T-cells and osteosarcoma cells that promoted tumor progression and a proangiogenic niche. Statement of SignificanceOsteosarcoma patient survival has remained stagnant for several decades due to lack of successful therapy for high-risk patients, including those with metastatic disease. Identifying novel therapeutics including immunotherapies is of great clinical importance. Our study highlights several important immunosuppressive mechanisms within osteosarcoma that should be considered when developing future immunotherapies.

cancer biology↗

bioRxiv2022

Simultaneous multifunctional transcriptome engineering by CRISPR RNA scaffold

RNA processing and metabolism are subjected to precise regulation in the cell to ensure integrity and functions of RNA. Though targeted RNA engineering has become feasible with the discovery and engineering of the CRISPR-Cas13 system, simultaneous modulation of different RNA processing steps remains unavailable. In addition, off-target events resulting from effectors fused with dCas13 limit its application. Here we developed a novel platform, Combinatorial RNA Engineering via Scaffold Tagged gRNA (CREST), which can simultaneously execute multiple RNA modulation functions on different RNA targets. In CREST, RNA scaffolds are appended to the 3 end of Cas13 gRNA and their cognate RNA binding proteins are fused with enzymatic domains for manipulation. We show that CREST is capable of simultaneously manipulating RNA alternative splicing and A-to-G or C-to-U base editing. Furthermore, by fusing two split fragments of the deaminase domain of ADAR2 to dCas13 and PUFc respectively, we reconstituted its enzyme activity at target sites. This split design can reduce more than 90% of off-target events otherwise induced by a full-length effector. The flexibility of the CREST framework will enrich the transcriptome engineering toolbox for the study of RNA biology and the development of RNA-focused therapeutics.

bioengineering↗

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↗

bioRxiv2022

Conserved cell-type specific signature of resilience to Alzheimer's disease nominates role for excitatory cortical neurons

Alzheimers disease (AD), the leading cause of dementia, affects millions of people worldwide. With no disease-modifying medication currently available, the human toll and economic costs are rising rapidly. Under current standards, a patient is diagnosed with AD when both cognitive decline and pathology (amyloid plaques and neurofibrillary tangles) are present. Remarkably, some individuals who have AD pathology remain cognitively normal. Uncovering factors that lead to "cognitive resilience" to AD is a promising path to create new targets for therapies. However, technical challenges discovering novel human resilience factors limit testing, validation, and nomination of novel drugs for AD. In this study, we use single-nucleus transcriptional profiles of postmortem cortex from human individuals with high AD pathology who were either cognitively normal (resilient) or cognitively impaired (susceptible) at time of death, as well as mouse strains that parallel these differences in cognition with high amyloid load. Our cross-species discovery approach highlights a novel role for excitatory layer 4/5 cortical neurons in promoting cognitive resilience to AD, and nominates several resilience genes that include ATP1A1, GRIA3, KCNMA1, and STXBP1. This putative cell type has been implicated in resilience in previous studies on bulk RNA-seq tissue, but our single-nucleus and cross-species approach identifies particular resilience-associated gene signatures in these cells. These novel resilience candidate genes were tested for replication in orthogonal data sets and confirmed to be correlated with cognitive resilience. Based on these gene signatures, we identified several potential mechanisms of resilience, including regulation of synaptic plasticity, axonal and dendritic development, and neurite vesicle transport along microtubules that are potentially targetable by available therapeutics. Because our discovery of resilience-associated genes in layer 4/5 cortical neurons originates from an integrated human and mouse transcriptomic space from susceptible and resilient individuals, we are positioned to test causality and perform mechanistic, validation, and pre-clinical studies in our human-relevant AD-BXD mouse panel.

neuroscience↗

bioRxiv2021

A Cellular Reference Resource for the Mouse Urinary Bladder

The urinary bladder functions as a reservoir to store and extrude liquid bodily waste. Significant debate exists as to this tissues cellular composition and genes associated with their functions. We use a repertoire of cell profiling tools to comprehensively define and spatial resolve cell types. We characterize spatially validated, basal-to-luminal gene expression dynamics within the urothelium, the cellular source of most bladder cancers. We define three distinct populations of fibroblasts that spatially organize from the sub-urothelial layer through to the detrusor muscle, clarifying knowledge around these controversial interstitial cells, and associate increased fibroblasts with aging. We overcome challenges of profiling the detrusor muscle, absence from earlier single cell studies, to report on its transcriptome with many novel and neuronal-like features presumably associated with neuromuscular junctions. Our approach provides a blueprint for tissue atlas construction and the data provides the foundation for future studies of bladder function in health and disease.

genomics↗

bioRxiv2021

Single cell analysis of endometriosis reveals a coordinated transcriptional program driving immunotolerance and angiogenesis across eutopic and ectopic tissues.

Endometriosis is characterized by growth of endometrial-like tissue outside of the uterus affecting many women in their reproductive age, causing years of pelvic pain and potential infertility. Its pathophysiology remains largely unknown, limiting diagnosis and treatment. We characterized peritoneal and ovarian lesions at single-cell transcriptome resolution and compared to matched eutopic endometrium, control endometrium, and organoids derived from these tissues, generating data on over 100,000 cells across 12 individuals. We spatially localized many of the cell types using imaging mass cytometry. We identify a perivascular mural cell unique to the peritoneal lesions with dual roles in angiogenesis promotion and immune cell trafficking. We define an immunotolerant peritoneal niche, fundamental differences in eutopic endometrium and between lesions microenvironments, and a novel progenitor-like epithelial cell subpopulation. Altogether, this study provides a holistic view of the endometriosis microenvironment representing the first comprehensive cell atlas of the disease, essential information for advancing therapeutics and diagnostics.

genomics↗

bioRxiv2020

Single-cell multimodal glioma analyses reveal epigenetic regulators of cellular plasticity and environmental stress response

Glioma intratumoral heterogeneity enables adaptation to challenging microenvironments and contributes to universal therapeutic resistance. Here, we integrated 914 single-cell DNA methylomes, 55,284 single-cell transcriptomes, and bulk multi-omic profiles across 11 adult IDH-mutant or IDH-wild-type gliomas to delineate sources of intratumoral heterogeneity. We found that local DNA methylation instability, or epimutation burden, was elevated in more aggressive tumors, reflected intratumoral variability, linked with transcriptional disruption, and associated with environmental stress response. We show that the activation of cell-state specific transcription factors is impacted by epimutations and that loosened epigenetic control may facilitate cellular plasticity. Our analyses support that somatic copy number alterations (SCNAs) promote epigenetic instability and that SCNAs largely precede epigenetic and transcriptomic diversification during glioma evolution. We confirmed the link between genetic and epigenetic instability by analyzing larger cohorts of bulk longitudinally collected and spatially separated DNA methylation data. Increased DNA methylation instability was associated with accelerated disease progression, and recurrently selected DNA methylation changes were enriched for environmental stress response pathways. Our work provides an integrative framework to better understand glioma evolution and highlights the importance of epigenetic heterogeneity in shaping therapeutic response.

cancer biology↗

bioRxiv2019

Antibody Targeting of B7-H4 Enhances the Immune Response in Urothelial Carcinoma

Locally advanced urothelial carcinoma has a poor survival despite a response to immunotherapy in approximately 25% of patients. To develop new therapies targeting other immune checkpoints, we identified increased expression of the T cell inhibitor protein, B7-H4 (VTCN1, B7S1, B7X), during tumor development of murine bladder cancer. Evaluation of B7-H4 in human bladder cancer by single-cell RNA-Seq and immune mass cytometry showed that B7-H4 is expressed by luminal tumors that are not normally responsive to PD-1 inhibitors. Additionally, overexpression B7-H4 was associated with significantly worse patient survival. In support of clinical translation, treatment of human monocyte and T cell co-cultures with a B7-H4 blocking antibody resulted in enhanced IFN-{gamma} secretion by CD4+ and CD8+ T cell. While the study of B7-H4 in mouse cancer models has been difficult using tumor cell lines, our findings show that B7-H4 expression increased at 3 months after exposure to BBN on CD11b+ monocytes/macrophages and delivery of anti-B7-H4 antibody resulted in decreased tumor size and increased CD8 immune cell infiltration with increased CD8+/IFN-{gamma}-producing T cells and a complimentary decrease in tumor infiltrating T regulatory cells (Tregs). Furthermore, treatment with a combination of anti-PD-1 and anti-B7-H4 antibodies resulted in a significant reduction in tumor stage. This data suggests that novel anti-B7-H4 antibodies maybe a viable target for bladder cancers unresponsive to PD-1 checkpoint inhibitors.

cancer biology↗

bioRxiv2018

Single-cell transcriptome analysis reveals estrogen signaling augments the mitochondrial folate pathway to coordinately fuel purine and polyamine synthesis in breast cancer cells

Estrogen regulates diverse physiological effects and drives breast tumor progression by directly activating estrogen receptor (ER). However, due to the stochastic nature of gene transcription and the resulting heterogeneous cellular response, it is important to investigate estrogen-stimulated gene expression profiles at the single-cell level in order to fully understand how ER regulates transcription in breast cancer cells. In this study, we performed single-cell transcriptome analysis on ER-positive breast cancer cell lines following 17{beta}-estradiol stimulation. Overall, we observed robust gene expression diversity between individual cells. Moreover, we found over two thirds of the genes in breast cancer cells displayed a bimodal expression pattern, which caused averaging artifacts and masked the identification of potential estrogen-regulated genes. We overcame this issue by reconstructing a dynamic estrogen-responsive transcriptional network from discrete time points into a pseudotemporal continuum. Pathway analysis of the differentially expressed genes derived from the pseudotemporal analysis showed an estrogen-stimulated metabolic switch that favored biosynthesis and cell proliferation but reduced estrogen degradation. In addition, we identified folate-mediated one-carbon metabolism as a novel estrogen-regulated pathway in breast cancer cells. Notably, estrogen stimulation reprogramed this pathway through the mitochondrial folate pathway to coordinately fuel polyamine and de novo purine synthesis. Finally, we showed AZIN1 and PPAT, key regulators in the above pathways, are direct ER target genes and essential for breast cancer cell survival and growth. In summary, our single-cell study illustrated a dynamic transcriptional heterogeneity in ER-positive breast cancer cells in response to estrogen stimulation and uncovered a novel mechanism of an estrogen-mediated metabolic switch.

genomics↗

bioRxiv2017

Comprehensive Cell Type Specific Transcriptomics of the Human Kidney

The human kidney is a complex organ composed of specialized cell types. To better define this cellular complexity, we profiled the individual transcriptomes of 22,469 normal human kidney cells, identifying 27 cell types. We describe three distinct endothelial cell populations, a novel subset of intercalated cells, interstitial macrophage and dendritic cells, and identify numerous novel cell-type-specific markers, many validated using imaging mass cytometry and immunohistochemistry. Receptor-ligand analysis revealed previously unknown intercalated-endothelial and intercalated-distal nephron interactions, suggesting a role in maintenance of vascular integrity and intercalated cell survival. Notably, kidney disease-associated genes were largely expressed in proximal tubules, podocytes, endothelial and myeloid cells, highlighting an underappreciated role for endothelial cells in kidney pathologies. Our analysis also provides a resource of cell type enriched markers, solute carriers, channels and lncRNAs. In summary, this cell-type-specific transcriptome resource provides the foundation for a comprehensive understanding of kidney function and dysfunction at single cell resolution.

cell biology↗