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Single cell atlas of the human optic nerve

The optic nerve is essential for transmitting visual information from the retina to the brain, where it is processed into images. Damage to the optic nerve can cause vision loss, leading to conditions such as glaucoma, optic neuritis, and optic neuropathy. To advance our understanding of the transcriptomic and epigenetic landscapes, as well as the dynamic cellular processes of the optic nerve, we conducted single-nucleus RNA sequencing (snRNA-seq) and single-nucleus ATAC sequencing (snATAC-seq) on the optic nerve head (ONH) and optic nerve (ON) tissues from over 80 healthy human donor eyes spanning diverse ages, genders, and ethnic backgrounds. By integrating newly generated and previously published snRNA-seq datasets, we constructed a comprehensive ONH and ON cell atlas encompassing transcriptomic profiles of 959,629 nuclei. Our analysis identified 25 distinct cell classes and 86 cell types/states, including diverse populations of astrocytes, oligodendrocytes, oligodendrocyte precursor cells, microglia, and macrophages. Furthermore, snATAC-seq profiling of approximately 1 million nuclei generated high-resolution chromatin accessibility landscapes, enabling the identification of cis-regulatory elements and transcription factors specific to individual cell classes and types. As part of the Human Cell Atlas initiative, our ON atlas serves as a crucial resource for studying optic nerve physiology and deepening our understanding of the cellular and molecular mechanisms underlying optic neuropathies and related diseases.

Spatial proteogenomics reveals distinct and evolutionarily conserved hepatic macrophage niches

The liver is the largest solid organ in the body, yet it remains incompletely characterized. Here we present a spatial proteogenomic atlas of the healthy and obese human and murine liver combining single-cell CITE-seq, single-nuclei sequencing, spatial transcriptomics, and spatial proteomics. By integrating these multi-omic datasets, we provide validated strategies to reliably discriminate and localize all hepatic cells, including a population of lipid-associated macrophages (LAMs) at the bile ducts. We then align this atlas across seven species, revealing the conserved program of bona fide Kupffer cells and LAMs. We also uncover the respective spatially resolved cellular niches of these macrophages and the microenvironmental circuits driving their unique transcriptomic identities. We demonstrate that LAMs are induced by local lipid exposure, leading to their induction in steatotic regions of the murine and human liver, while Kupffer cell development crucially depends on their cross-talk with hepatic stellate cells via the evolutionarily conserved ALK1-BMP9/10 axis.

Pan-disease fibroblast atlas in skin fibrosis, inflammation, and cancer

Fibroblasts are essential cells that sculpt the architecture and cellular microenvironments within various tissues. Understanding fibroblast heterogeneity and their spatial context in health and disease has major clinical relevance. In this study, we constructed a spatially-resolved atlas of 357 276 human skin fibroblasts from healthy skin and 23 skin disorders. We define 6 major skin fibroblast populations in health and a further three skin disease-specific fibroblast subtypes, and demonstrate the fibroblast composition in different types of skin disease. We also show that inflammatory myofibroblasts (IL11+MMP1+CXCL5+IL7R+) present in early human wounds are a conserved fibroblast subtype in inflammatory disorders and cancer, that likely recruit neutrophils and monocytes to different human tissues. We characterise a human-specific fibroblastic reticular cell (FRC)-like subtype in the skin superficial perivascular niche and postulate their origin from prenatal skin lymphoid tissue organiser (LTo)-like cells. We provide a harmonised nomenclature for skin fibroblasts that integrates previous findings from human skin and other tissues.

Consensus Spinal Cord Atlas

Integrated human endoderm-derived organoids cell atlas (HEOCA)

Organoids of the endoderm can recapitulate aspects of developing and adult human physiology. Organoids derived from embryonic or induced pluripotent stem cells model development and are guided to specific tissue types via morphogens, whereas organoids derived from tissue-resident fetal or adult stem cells are organ-identity-determined and may model ontogenetic features. However, it has remained difficult to assess the similarity and differences between organoid protocols, and to understand the precision and accuracy of organoid cell states through comparison with primary counterparts. Advances in computational single-cell biology allow the comprehensive integration of datasets with high technical variability. Here, we integrate published single-cell transcriptome datasets from organoids of diverse endoderm-derived tissues including lung, pancreas, intestine, salivary glands, liver, biliary system, stomach, and prostate to establish an initial version of a human endoderm organoid cell atlas (HEOCA). The integration includes nearly one million cells across diverse conditions and data sources. We align and compare cell types and states between organoid models, and harmonize cell type annotations by mapping the atlas to primary tissue counterparts. We focus on intestine and lung, and clarify developmental and adult physiology that can be modeled in vitro. We provide examples of data incorporation from new organoid protocols to expand the atlas, and showcase how comparison to the atlas can illuminate interesting biological features of new datasets. We also show that mapping disease organoid single-cell samples to HEOCA identifies shifts in cell proportion and gene expressions between normal and diseased cells. Taken together, the atlas makes diverse datasets centrally available, and it will be useful to assess organoid fidelity, characterize perturbed and diseased states, streamline protocol development, and will continuously grow in the future.

Single cell atlas of the human retinal pigment epithelium and the choroid

The survival and proper function of the neural retina depend on the support of two underlying tissues: the retinal pigment epithelium (RPE) and the choroid. Dysfunction in the RPE and choroid can lead to a range of inherited and complex diseases. To better characterize the cellular, transcriptomic, and epigenomic heterogeneity and dynamics within the RPE and choroid, we conducted single-cell and single-nucleus RNA sequencing (sc/snRNA-seq) as well as single-nucleus ATAC sequencing (snATAC-seq) on donor tissue samples. By integrating newly generated and previously published datasets, we developed version 1 of the human RPE and choroid cell atlas. This atlas includes scRNA-seq data from 205,925 cells from 67 donors and snRNA-seq data from 742,625 nuclei from 54 donors. Additionally, we incorporated snRNA-seq data from 136,555 nuclei from developmental RPE/choroid tissues spanning post-conception weeks (PCW) 10-23. This comprehensive dataset enabled the identification of 15 major cell classes, which were further subdivided into 25 cell types. Additionally, open chromatin profiling was performed on over 234,007 nuclei using snATAC-seq, providing an in-depth characterization of chromatin accessibility for each cell type. As part of the Human Cell Atlas project, this resource lays a robust foundation for advancing research into the biology of the RPE and choroid and the diseases associated with these tissues.

An atlas of healthy and injured cell states and niches in the human kidney (Version 1.5)

Understanding kidney health and disease relies upon defining the complexity of cell types and states, their associated molecular profiles, and interactions within tissue neighborhoods. We have applied single-cell and single-nucleus assays to a broad spectrum of healthy reference and disease kidneys. This has provided a high-resolution cellular atlas that includes rare and novel cell populations. We further identify and define cellular states altered in kidney injury, encompassing cycling, adaptive or maladaptive repair, transitioning and degenerative states affecting several nephron segments. These analyses further define biological pathways relevant to injury niches, including signatures underlying the transition from reference to predicted maladaptive states that are associated with a decline in kidney function during chronic kidney disease. Our collaborative efforts across the Kidney Precision Medicine Project (KPMP), the Human BioMolecular Atlas Program (HuBMAP) and the Human Cell Atlas consortia aim to generate a comprehensive human kidney cell atlas that includes injury and disease-relevant cell states and neighborhoods as a valuable resource to the research community. Here we provide an expanded data set from that published previously (Lake et al., Nature 2023) that includes additional KPMP biopsy data.

An integrated transcriptomic cell atlas of human neural organoids

The Human Cell Atlas data provides the “recipe” for tissue engineering, including organoids. Human organoids – three-dimensional structures of cells that recapitulate organ development in vitro – hold tremendous potential for biomedical applications. They provide tractable models of human physiology and pathology, thereby enabling interventional studies that are difficult or impossible to conduct in human subjects, and reducing the need for animal experiments. Moreover, they can provide patient-specific “avatars” for drug development and personalized therapies, and they help advance regenerative medicine, with the ultimate goal of aiming towards regenerative medicine, and producing functional biological structures that can be transplanted into patients. Single-cell epigenome/transcriptome sequencing and spatial profiling can provide a comprehensive assessment of cell composition and cell states within organoids, enabling a comparison to matched primary tissue samples. These comparisons can catalyse the development of better organoid protocols. The Organoid Cell Atlas will foster the production, quality control, dissemination, and utilization of single-cell data for human organoids, and it will connect such datasets with the comprehensive profiles of primary tissue that are being generated within the HCA.

Single cell atlas of the human trabecular meshwork and ciliary body

The trabecular meshwork (TM) and ciliary body (CB) play critical roles in regulating aqueous humor homeostasis in the human eye. The TM serves as the primary outflow pathway for aqueous humor, while the CB controls lens shape and produces aqueous humor. Both tissues are composed of diverse cell types, with cell abundances varying across several orders of magnitude. To create a comprehensive single-cell atlas and advance our understanding of TM and CB biology, we generated large-scale datasets from healthy human donors using single-nucleus RNA-seq (snRNA-seq), single-cell RNA-seq (scRNA-seq), and single-nucleus ATAC-seq (snATAC-seq) across a range of ages, genders, and ethnic backgrounds. Additionally, we performed a meta-analysis by integrating previously published datasets. All data were uniformly preprocessed and combined, resulting in a comprehensive TM and CB atlas that includes transcriptomic profiles of over 1 million cells from 70 donors. We identified 19 distinct cell types, including rare populations such as immune cells, with the least abundant types representing as little as 0.08% of the total cell population. Furthermore, snATAC-seq profiling of over 500,000 nuclei provided detailed chromatin accessibility landscapes, allowing for the identification of cis-regulatory elements specific to each cell type. All datasets are publicly accessible via CELLxGENE and the UCSC Cell Browser, enabling interactive exploration of gene expression and chromatin states at the single-cell level. As part of the Human Cell Atlas initiative, our TM and CB atlas offers a valuable resource for understanding eye physiology and establishes a foundation for further research into the cellular and molecular mechanisms regulating intraocular pressure and related ocular diseases.

Single cell atlas of the human ocular surface

The cornea, limbus, and sclera form the ocular surface, a critical interface that protects the eye, maintains visual function, and provides structural support. The cornea serves as the primary refractive surface and barrier against external pathogens. The limbus, located at the corneal-scleral junction, houses limbal stem cells essential for the regeneration of the corneal epithelium. The sclera provides structural integrity, protects the eye, and serves as the attachment site for extraocular muscles. Together, these three components play integral roles in sustaining ocular function and homeostasis. To capture the major cell types and subclasses of the ocular surface, we generated large-scale datasets using scRNA-seq and snRNA-seq technologies from healthy human donors spanning a wide range of ages, genders, and ethnicities. Additionally, publicly available datasets were integrated to expand the scope of the atlas. In total, the atlas includes over 1 million cells and nuclei from 102 donors. We identified 10 major cell classes and 31 types in the atlas, including rare populations such as limbal progenitor cells, Schlemn’s canel endothelium, and specific immune subtypes. The atlas also captures the full trajectory of epithelial differentiation. To further enhance our understanding of gene regulation, we generated a snATAC-seq atlas, profiling over 362k nuclei from 26 donors, including 8 developmental samples, facilitating the characterization of cell type-specific chromatin accessibility landscapes and regulatory elements. All datasets underwent a unified preprocessing pipeline and data integration to ensure consistency and quality. The atlas is publicly accessible through CELLxGENE, enabling interactive exploration of gene expression and regulatory landscapes. As part of the Human Cell Atlas initiative, this comprehensive ocular surface atlas marks a significant advance in understanding ocular tissue physiology and provides a valuable resource for studying ocular surface development, aging, and diseases such as corneal dystrophies, limbal stem cell deficiency, and scleral remodeling.

Single cell atlas of the human retina

As the light sensing part of the visual system, the human retina is composed of five classes of neuron, including photoreceptors, horizontal cells, amacrine, bipolar, and retinal ganglion cells. Each class of neuron can be further classified into subgroups with the abundance varying three orders of magnitude. Therefore, to capture all cell types in the retina and generate a complete single cell reference atlas, it is essential to scale up from currently published single cell profiling studies to improve the sensitivity. In addition, to gain a better understanding of gene regulation at single cell level, it is important to include sufficient scATAC-seq data in the reference. To fill the gap, we performed snRNA-seq and snATAC-seq for the retina from healthy donors. To further increase the size of the dataset, we then collected and incorporated publicly available datasets. All data underwent a unified preprocessing pipeline and data integration. Multiple integration methods were benchmarked by scIB, and scVI was chosen. To harness the power of multiomics, snATAC-seq datasets were also preprocessed, and scGlue was used to generate co-embeddings between snRNA-seq and snATAC-seq cells. To facilitate the public use of references, we employ CELLxGENE and UCSC Cell Browser for visualization. By combining previously published and newly generated datasets, a single cell atlas of the human retina that is composed of 2.5 million single cells from 48 donors has been generated. As a result, over 90 distinct cell types are identified based on the transcriptomics profile with the rarest cell type accounting for about 0.01% of the cell population. In addition, open chromatin profiling has been generated for over 400K nuclei via single nuclei ATAC-seq, allowing systematic characterization of cis-regulatory elements for individual cell type. Integrative analysis reveals intriguing differences in the transcriptome, chromatin landscape, and gene regulatory network among cell class, subgroup, and type. In addition, changes in cell proportion, gene expression and chromatin openness have been observed between different gender and over age. Accessible through interactive browsers, this study represents the most comprehensive reference cell atlas of the human retina to date. As part of the human cell atlas project, this resource lays the foundation for further research in understanding retina biology and diseases.

An Atlas of Cells in the Human Tonsil

Tonsils are constantly exposed to antigens through the upper respiratory tract, making them a valuable secondary lymphoid organ (SLO) for studying the interaction between innate and adaptive immune cells during germinal center (GC) development, which is crucial for building adaptive immunity. This reference includes 377,963 cells (10x Genomics 3' v3) from 17 healthy human donors spanning various age groups, including children, young adults, and older adults. The annotation provided in this first version comprises 42 categories that provide a stable categories to classify single-cell transcriptomes of SLOs, useful for tools like Azimuth (see external URLs). In the next version, we will add a more detailed classification, encompassing all cell types and states identified in the tonsil atlas. A validation cohort was included to confirm the presence and accuracy of each annotation this latter level, using criteria such as cell neighborhood preservation, conservation of bona fide marker genes, and annotation confidence derived from the KNN classifier. For a full description and interpretation of this validation cohort, please refer to the final section of the manuscript. The tonsil atlas is a FAIR resource—findable, accessible, interoperable, and reusable. The raw data has been deposited in ArrayExpress and can be remapped and reanalyzed by following the instructions provided in the TonsilAtlas and TonsilAtlasCAP GitHub repositories. The resulting expression matrices and Seurat objects are available on Zenodo, and the data can be accessed, explored, interpreted, and reused via the HCATonsilAtlas Bioconductor package and the Azimuth web interface. Additionally, we provide a detailed glossary of the marker genes, rationales, and publications used to annotate each cell type and state. The external URLs section contains links to all these resources.

Concerted changes in the pediatric single-cell intestinal ecosystem before and after anti-TNF blockade

Crohn’s disease is an inflammatory bowel disease (IBD) commonly treated through anti-TNF blockade. However, most patients still relapse and inevitably progress. Comprehensive single-cell RNA-sequencing (scRNA-seq) atlases have largely sampled patients with established treatment-refractory IBD, limiting our understanding of which cell types, subsets, and states at diagnosis anticipate disease severity and response to treatment. Here, through combining clinical, flow cytometry, histology, and scRNA-seq methods, we profile diagnostic human biopsies from the terminal ileum of treatment-naïve pediatric patients with Crohn’s disease (pediCD; n=14), matched repeat biopsies (pediCD-treated; n=8) and from non-inflamed pediatric controls with functional gastrointestinal disorders (FGID; n=13). To resolve and annotate epithelial, stromal, and immune cell states among the 201,883 baseline single-cell transcriptomes, we develop a principled and unbiased tiered clustering approach, ARBOL. Through flow cytometry and scRNA-seq, we observe that treatment-naïve pediCD and FGID have similar broad cell type composition. However, through high-resolution scRNA-seq analysis and microscopy, we identify significant differences in cell subsets and states that arise during pediCD relative to FGID. By closely linking our scRNA-seq analysis with clinical meta-data, we resolve a vector of T cell, innate lymphocyte, myeloid, and epithelial cell states in treatment-naïve pediCD (pediCD-TIME) samples which can distinguish patients along the trajectory of disease severity and anti-TNF response. By using ARBOL with integration, we position repeat on-treatment biopsies from our patients between treatment-naïve pediCD and on-treatment adult CD. We identify that anti-TNF treatment pushes the pediatric cellular ecosystem towards an adult, more treatment-refractory state. Our study jointly leverages a treatment-naïve cohort, high-resolution principled scRNA-seq data analysis, and clinical outcomes to understand which baseline cell states may predict Crohn’s disease trajectory.

Asian Immune Diversity Atlas (AIDA) v2

Lack of diversity and proportionate representation in genomics datasets and databases contributes to inequity in healthcare outcomes globally. The relationships of human diversity with biological and biomedical phenotypes are pervasive, yet remain understudied, particularly in a single-cell genomics context. Here we present the Asian Immune Diversity Atlas (AIDA), a multi-national single-cell RNA-sequencing (scRNA-seq) healthy reference atlas of human immune cells. AIDA comprises 1,265,624 circulating immune cells from 619 healthy donors and 6 controls, spanning 7 population groups across 5 countries. AIDA is one of the largest healthy blood datasets in terms of number of cells, and also the most diverse in terms of number of population groups. Though population groups are frequently compared at the continental level, we identified a pervasive impact of sub-continental diversity on cellular and molecular properties of immune cells. These included cell populations and genes implicated in disease risk and pathogenesis as well as those relevant for diagnostics. We identified numerous examples where the effects of age and sex were modulated by self-reported ethnicity. We also detected age, sex, and self-reported ethnicity differences at the resolution of cell neighbourhoods, highlighting finer-grained distinctions than were apparent at cell-type level. We discovered functional genetic variants influencing cell type-specific gene expression, including context-dependent effects, which were under-represented in analyses of non-Asian population groups, and which helped contextualise disease-associated variants. We validated our findings using multiple independent datasets and cohorts. AIDA provides fundamental insights into the relationships of human diversity with immune cell phenotypes, enables analyses of multi-ancestry disease datasets, and facilitates the development of precision medicine efforts in Asia and beyond.