Spatial organization of the mouse retina at single cell resolution by MERFISH

Single-cell and spatial omics: exploring hypothalamic heterogeneity

Elucidating the complex dynamic cellular organization in the hypothalamus is critical for understanding its role in coordinating fundamental body functions. Over the past decade, single-cell and spatial omics technologies have significantly evolved, overcoming initial technical challenges in capturing and analyzing individual cells. These high-throughput omics technologies now offer a remarkable opportunity to comprehend the complex spatiotemporal patterns of transcriptional diversity and cell-type characteristics across the entire hypothalamus. Current single-cell and single-nucleus RNA sequencing methods comprehensively quantify gene expression by exploring distinct phenotypes across various subregions of the hypothalamus. However, single-cell/single-nucleus RNA sequencing requires isolating the cell/nuclei from the tissue, potentially resulting in the loss of spatial information concerning neuronal networks. Spatial transcriptomics methods, by bypassing the cell dissociation, can elucidate the intricate spatial organization of neural networks through their imaging and sequencing technologies. In this review, we highlight the applicative value of single-cell and spatial transcriptomics in exploring the complex molecular-genetic diversity of hypothalamic cell types, driven by recent high-throughput achievements.

Paired DNA and RNA sequencing uncovers common and rare genetic variants regulating gene expression in the human retina

Genetic disorders impacting vision affect millions of individuals worldwide, including age-related macular degeneration (common) and inherited retinal disorders (rare). There is incomplete understanding of the impact of genetic variation on gene expression in the human retina, and its role in genetic disorders. Through the generation of whole genome sequencing and bulk RNA-sequencing of neurosensory retina (NSR) and retinal pigment epithelium (RPE) from 201 post-mortem eyes, we uncovered common and rare genetic variants shaping retinal expression profiles. This includes 1,483,595 significant cis-expression quantitative trait loci (eQTLs) impacting 9,959 and 3,699 genes in NSR and RPE, respectively, with associated genetic variants enriched to cis-candidate regulatory elements and notable shared eGenes between NSR and RPE. We also detected 1051 expression outliers and prioritised 299 rare non-coding single-nucleotide, structural variants or copy number variants as plausible drivers for 28% of outlier events. This study increases understanding of gene expression regulation in the human retina.

Spatial transcriptomics reveals regionally altered gene expression that drives retinal degeneration

Photoreceptor cell death is a hallmark of age-related macular degeneration. Environmental, lifestyle and genetic risk factors are known contributors to disease progression, whilst at the molecular level, oxidative stress and inflammation are central pathogenetic drivers. However, the spatial and cellular origins of these molecular mechanisms remain unclear. We used spatial transcriptomics to investigate the spatio-temporal gene expression changes in the adult mouse retina in response to photo-oxidative stress. We identify regionally distinct transcriptomes, with higher expression of immunity related genes in the superior retina. Exposure to stress induced expression of genes involved in inflammatory processes, innate immune responses, and cytokine production in a highly localised manner. A distinct region ~800 µm superior from the optic nerve head seems a key driver of these molecular changes. Further, we show highly localised early molecular changes in the superior mouse retina during retinal stress and identify novel genes drivers. We provide evidence of angiogenic changes in response to photo-oxidative stress and suggest additional angiogenic signalling pathways within the retina including VEGF, pleiotrophin and midkine. These new insights into retinal angiogenesis pave the way to identify novel drivers of retinal neovascularisation with an opportunity for therapeutic development.

In vivo prime editing rescues photoreceptor degeneration in nonsense mutant retinitis pigmentosa

The next-generation gene editing tool, prime editing (PE), is adept at correcting point mutations precisely with high editing efficiency and rare off-target events and shows promising therapeutic value in treating hereditary diseases. Retinitis pigmentosa (RP) is the most common type of inherited retinal dystrophy and is characterized by progressive degeneration of retinal photoreceptors and, consequently, visual decline. To date, effective treatments for RP are lacking. Herein, a PE system is designed to target the PDE6B Y347X mutation in the rd1 mouse strain, a preclinical RP model. We screen and develop the PE system with epegRNA and RTΔRnH, which is delivered via dual-AAV in vivo with an editing efficiency of 26.47 ± 13.35%, with negligible off-target effects confirmed by AID-Seq and PE-tag. Treatment with the PE system in vivo greatly restores PDE6B protein expression and protects rod cells from degeneration. Mouse behavioural experiments also show that compared with no treatment, prime editing inhibits vision deterioration in littermate rd1 mice. This study provides a therapeutic opportunity for the use of PE to correct mutated RPs at the genomic level.

The Spatial Transcriptomic Atlas of Human Limbus and Vital Niche Microenvironment Regulating the Fate of Limbal Epithelial Stem Cells

Purpose

This study aimed to generate the spatial atlas of the human limbus using spatial transcriptomic technology and reveal the deep interaction among the niche microenvironment.

Methods

The spatial transcriptomic atlas of human limbus was performed using 10× Genomics Space Ranger software platform. Single-cell RNA sequencing data of human limbal epithelial stem cells (LESCs) were downloaded for integrating analysis.

Results

We profiled more than 400 spots within each sample and spatially located major cell types within the limbus area. LESCs were localized mainly in the basement membrane, and limbal niche cells were situated predominantly within the stromal area. Next, the limbus was divided into four regions based on histological structure, and the differential expressed genes among the four regions were analyzed. Notably, GPHB5 was highly expressed in the epithelium of the middle region and co-staining with deltaNp63 suggested it might be a novel potential biomarker of LESCs. Subsequently, limbal mesenchymal stem cells were found to exhibit the greatest amounts of ligands associated with LESCs. The widespread activity of COL6A2/CD44 signaling among limbal mesenchymal stem cells, melanocytes, immune cells, and LESCs indicate its essential role in mediating bidirectional communication via the collagen pathway.

Conclusions

This research mapped the spatial positioning of key cells within the limbal niche and detailed interactions between major cell types. These findings provide a foundation for further LESC research and enhance our understanding of corneal biology.

A Complete Spatial Map of Mouse Retinal Ganglion Cells Reveals Density and Gene Expression Specializations

Retinal ganglion cells (RGCs) transmit visual information from the eye to the brain. In mice, several RGC subtypes show nonuniform spatial distributions, potentially mediating specific visual functions. However, the full extent of RGC specialization remains unknown. Here, we used en-face cryosectioning, spatial transcriptomics, and machine learning to map the spatial distribution of all RGC subtypes identified in previous single-cell studies. While two-thirds of RGC subtypes were evenly distributed, others showed strong biases toward ventral or dorso-temporal regions associated with sky vision and the area retinae temporalis (ART), the predicted homolog of the area centralis. Additionally, we observed unexpected spatial variation in gene expression within several subtypes along the dorso-ventral axis or within vs. outside the ART, independent of RGC density profiles. Finally, we found limited correlations between the gene profiles of the ART and the primate macula, suggesting divergent specialization between the mouse and primate central vision.

Kinetic changes in microglia-related retinal transcripts in experimental autoimmune uveoretinitis (EAU) of B10.RIII mice

In this study the retinal transcriptome was investigated during the development of experimental autoimmune uveoretinitis (EAU) in mice. EAU was induced by immunizing B10.RIII mice with human interphotoreceptor retinoid binding protein (hIRBP) 161-180 peptide. Genome-wide transcriptional profiles of EAU (day 7, 14 or 21 after immunization) and of control retinas were generated using DNA-microarrays and bioinformatic data mining. Microglia-associated transcripts were identified. Quantitative real-time polymerase chain reaction was performed to validate the expression of differentially expressed genes. Retinal transcript validation revealed that complement and interferon-related pathways, as well as gene clusters specific for antigen-processing and -presentation, and immunosuppression are involved during the course of the disease. Immunofluorescence analysis confirm that upregulated transcripts in EAU are also expressed by retinal microglia. Furthermore, the heterogenous expression patterns observed in retinal microglia, suggests the presence of different subpopulations of retinal microglia in EAU. This study expands our knowledge of the local immune processes involved in EAU pathology.

Emerging therapeutic strategies for optic nerve regeneration

The optic nerve, comprising axons from retinal ganglion cells (RGCs), is a component of the central nervous system (CNS) that generally exhibits a limited regeneration capacity following injury in mature mammals, resulting in permanent vision loss. Here, we summarize recent advances in interventions targeting cell-intrinsic and cell-extrinsic mechanisms to enhance RGC axon regeneration. Additionally, we summarize strategies for guiding the reconnection of regenerating axons with brain visual targets, aiming to restore partial visual function. Given the advent of high-throughput screening techniques and multiomics analyses, we discuss how these emerging methodologies deepen our understanding of regenerative mechanisms and expedite the development of innovative therapeutic approaches. Lastly, we explore the translational potential of these strategies in achieving clinically meaningful vision recovery.

Identifying Multiomic Signatures of X-Linked Retinoschisis-Derived Retinal Organoids and Mice Harboring Patient-Specific Mutation Using Spatiotemporal Single-Cell Transcriptomics

X-linked retinoschisis (XLRS) is an inherited retinal disorder with severe retinoschisis and visual impairments. Multiomics approaches integrate single-cell RNA-sequencing (scRNA-seq) and spatiotemporal transcriptomics (ST) offering potential for dissecting transcriptional networks and revealing cell-cell interactions involved in biomolecular pathomechanisms. Herein, a multimodal approach is demonstrated combining high-throughput scRNA-seq and ST to elucidate XLRS-specific transcriptomic signatures in two XLRS-like models with retinal splitting phenotypes, including genetically engineered (Rs1emR209C) mice and patient-derived retinal organoids harboring the same patient-specific p.R209C mutation. Through multiomics transcriptomic analysis, the endoplasmic reticulum (ER) stress/eukryotic initiation factor 2 (eIF2) signaling, mTOR pathway, and the regulation of eIF4 and p70S6K pathways are identified as chronically enriched and highly conserved disease pathways between two XLRS-like models. Western blots and proteomics analysis validate the occurrence of unfolded protein responses, chronic eIF2α signaling activation, and chronic ER stress-induced apoptosis. Furthermore, therapeutic targeting of the chronic ER stress/eIF2α pathway activation synergistically enhances the efficacy of AAV-mediated RS1 gene delivery, ultimately improving bipolar cell integrity, postsynaptic transmission, disorganized retinal architecture, and electrophysiological responses. Collectively, the complex transcriptomic signatures obtained from Rs1emR209C mice and patient-derived retinal organoids using the multiomics approach provide opportunities to unravel potential therapeutic targets for incurable retinal diseases, such as XLRS.

Molecular and spatial analysis of ganglion cells on retinal flatmounts: diversity, topography, and perivascularity

Diverse retinal ganglion cells (RGCs) transmit distinct visual features from the eye to the brain. Recent studies have categorized RGCs into 45 types in mice based on transcriptomic profiles, showing strong alignment with morphological and electrophysiological properties. However, little is known about how these types are spatially arranged on the two-dimensional retinal surface-an organization that influences visual encoding-and how their local microenvironments impact development and neurodegenerative responses. To address this gap, we optimized a workflow combining imaging-based spatial transcriptomics (MERFISH) and immunohistochemical co-staining on thin flatmount retinal sections. We used computational methods to register en face somata distributions of all molecularly defined RGC types. More than 75% (34/45) of types exhibited non-uniform distributions, likely reflecting adaptations of the retina's anatomy to the animal's visual environment. By analyzing the local neighborhoods of each cell, we identified perivascular RGCs located near blood vessels. Seven RGC types are enriched in the perivascular niche, including members of intrinsically photosensitive RGC (ipRGC) and direction-selective RGC (DSGC) subclasses. Orthologous human RGC counterparts of perivascular types - Melanopsin-enriched ipRGCs and ON DSGCs - were also proximal to blood vessels, suggesting their perivascularity may be evolutionarily conserved. Following optic nerve crush in mice, the perivascular M1-ipRGCs and ON DSGCs showed preferential survival, suggesting that proximity to blood vessels may render cell-extrinsic neuroprotection to RGCs through an mTOR-independent mechanism. Overall, our work offers a resource characterizing the spatial profiles of RGC types, enabling future studies of retinal development, physiology, and neurodegeneration at individual neuron type resolution across the two-dimensional space.

'Iterative Bleaching Extends Multiplexity' facilitates simultaneous identification of all major retinal cell types

To understand the multicellular composition of tissues, and how it is altered during development, ageing and/or disease, we must visualise the complete cellular landscape. Currently, this is hindered by our limited ability to combine multiple cellular markers. To overcome this, we adapted a highly multiplexed immunofluorescence (IF) technique called 'Iterative Bleaching Extends Multiplexity' (IBEX) to the zebrafish retina. We optimised fluorescent antibody micro-conjugation to perform sequential rounds of labelling on a single tissue to simultaneously visualise all major retinal cell types with 11 cell-specific antibodies. We further adapted IBEX to be compatible with fluorescent transgenic reporter lines, in situ hybridisation chain reaction (HCR), and whole-mount immunofluorescence (WMIF). We applied IBEX at multiple stages to study the spatial and temporal relationships between glia and neurons during retinal development. Finally, we demonstrate the utility of IBEX across species by testing it on the turquoise killifish (Nothobranchius furzeri) and African clawed frog (Xenopus laevis) to glean large amounts of information from precious tissues. These techniques will revolutionise our ability to visualise multiple cell types in any organism where antibodies are readily available.

Single-Cell Multiomics Profiling Reveals Heterogeneity of Müller Cells in the Oxygen-Induced Retinopathy Model

Purpose

Retinal neovascularization poses heightened risks of vision loss and blindness. Despite its clinical significance, the molecular mechanisms underlying the pathogenesis of retinal neovascularization remain elusive. This study utilized single-cell multiomics profiling in an oxygen-induced retinopathy (OIR) model to comprehensively investigate the intricate molecular landscape of retinal neovascularization.

Methods

Mice were exposed to hyperoxia to induce the OIR model, and retinas were isolated for nucleus isolation. The cellular landscape of the single-nucleus suspensions was extensively characterized through single-cell multiomics sequencing. Single-cell data were integrated with genome-wide association study (GWAS) data to identify correlations between ocular cell types and diabetic retinopathy. Cell communication analysis among cells was conducted to unravel crucial ligand-receptor signals. Trajectory analysis and dynamic characterization of Müller cells were performed, followed by integration with human retinal data for pathway analysis.

Results

The multiomics dataset revealed six major ocular cell classes, with Müller cells/astrocytes showing significant associations with proliferative diabetic retinopathy (PDR). Cell communication analysis highlighted pathways that are associated with vascular proliferation and neurodevelopment, such as Vegfa-Vegfr2, Igf1-Igf1r, Nrxn3-Nlgn1, and Efna5-Epha4. Trajectory analysis identified a subset of Müller cells expressing genes linked to photoreceptor degeneration. Multiomics data integration further unveiled positively regulated genes in OIR Müller cells/astrocytes associated with axon development and neurotransmitter transmission.

Conclusions

This study significantly advances our understanding of the intricate cellular and molecular mechanisms underlying retinal neovascularization, emphasizing the pivotal role of Müller cells. The identified pathways provide valuable insights into potential therapeutic targets for PDR, offering promising directions for further research and clinical interventions.

Deep Spectral Library of Mice Retina for Myopia Research: Proteomics Dataset generated by SWATH and DIA-NN

The retina plays a crucial role in processing and decoding visual information, both in normal development and during myopia progression. Recent advancements have introduced a library-independent approach for data-independent acquisition (DIA) analyses. This study demonstrates deep proteome identification and quantification in individual mice retinas during myopia development, with an average of 6,263 ± 86 unique protein groups. We anticipate that the use of a predicted retinal-specific spectral library combined with the robust quantification achieved within this dataset will contribute to a better understanding of the proteome complexity. Furthermore, a comprehensive mice retinal-specific spectral library was generated, encompassing a total identification of 9,401 protein groups, 70,041 peptides, 95,339 precursors, and 761,868 transitions acquired using SWATH-MS acquisition on a ZenoTOF 7600 mass spectrometer. This dataset surpasses the spectral library generated through high-pH reversed-phase fractionation by data-dependent acquisition (DDA). The data is available via ProteomeXchange with the identifier PXD046983. It will also serve as an indispensable reference for investigations in myopia research and other retinal or neurological diseases.

Cell-cell communication: new insights and clinical implications

Multicellular organisms are composed of diverse cell types that must coordinate their behaviors through communication. Cell-cell communication (CCC) is essential for growth, development, differentiation, tissue and organ formation, maintenance, and physiological regulation. Cells communicate through direct contact or at a distance using ligand-receptor interactions. So cellular communication encompasses two essential processes: cell signal conduction for generation and intercellular transmission of signals, and cell signal transduction for reception and procession of signals. Deciphering intercellular communication networks is critical for understanding cell differentiation, development, and metabolism. First, we comprehensively review the historical milestones in CCC studies, followed by a detailed description of the mechanisms of signal molecule transmission and the importance of the main signaling pathways they mediate in maintaining biological functions. Then we systematically introduce a series of human diseases caused by abnormalities in cell communication and their progress in clinical applications. Finally, we summarize various methods for monitoring cell interactions, including cell imaging, proximity-based chemical labeling, mechanical force analysis, downstream analysis strategies, and single-cell technologies. These methods aim to illustrate how biological functions depend on these interactions and the complexity of their regulatory signaling pathways to regulate crucial physiological processes, including tissue homeostasis, cell development, and immune responses in diseases. In addition, this review enhances our understanding of the biological processes that occur after cell-cell binding, highlighting its application in discovering new therapeutic targets and biomarkers related to precision medicine. This collective understanding provides a foundation for developing new targeted drugs and personalized treatments.

Multiplexed spatial transcriptomics methods and the application of expansion microscopy

While spatial transcriptomics has undeniably revolutionized our ability to study cellular organization, it has driven the development of a great number of innovative transcriptomics methods, which can be classified into in situ sequencing (ISS) methods, in situ hybridization (ISH) techniques, and next-generation sequencing (NGS)-based sequencing with region capture. These technologies not only refine our understanding of cellular processes, but also open up new possibilities for breakthroughs in various research domains. One challenge of spatial transcriptomics experiments is the limitation of RNA detection due to optical crowding of RNA in the cells. Expansion microscopy (ExM), characterized by the controlled enlargement of biological specimens, offers a means to achieve super-resolution imaging, overcoming the diffraction limit inherent in conventional microscopy and enabling precise visualization of RNA in spatial transcriptomics methods. In this review, we elaborate on ISS, ISH and NGS-based spatial transcriptomic protocols and on how performance of these techniques can be extended by the combination of these protocols with ExM. Moving beyond the techniques and procedures, we highlight the broader implications of transcriptomics in biology and medicine. These include valuable insight into the spatial organization of gene expression in cells within tissues, aid in the identification and the distinction of cell types and subpopulations and understanding of molecular mechanisms and intercellular changes driving disease development.

Deciphering brain cellular and behavioral mechanisms: Insights from single-cell and spatial RNA sequencing

The brain is a complex computing system composed of a multitude of interacting neurons. The computational outputs of this system determine the behavior and perception of every individual. Each brain cell expresses thousands of genes that dictate the cell's function and physiological properties. Therefore, deciphering the molecular expression of each cell is of great significance for understanding its characteristics and role in brain function. Additionally, the positional information of each cell can provide crucial insights into their involvement in local brain circuits. In this review, we briefly overview the principles of single-cell RNA sequencing and spatial transcriptomics, the potential issues and challenges in their data processing, and their applications in brain research. We further outline several promising directions in neuroscience that could be integrated with single-cell RNA sequencing, including neurodevelopment, the identification of novel brain microstructures, cognition and behavior, neuronal cell positioning, molecules and cells related to advanced brain functions, sleep-wake cycles/circadian rhythms, and computational modeling of brain function. We believe that the deep integration of these directions with single-cell and spatial RNA sequencing can contribute significantly to understanding the roles of individual cells or cell types in these specific functions, thereby making important contributions to addressing critical questions in those fields. This article is categorized under: RNA Evolution and Genomics > Computational Analyses of RNA RNA in Disease and Development > RNA in Development RNA in Disease and Development > RNA in Disease.

Comprehensive single-cell atlas of the mouse retina

Single-cell RNA sequencing (scRNA-seq) has advanced our understanding of cellular heterogeneity by characterizing cell types across tissues and species. While several mouse retinal scRNA-seq datasets exist, each dataset is either limited in cell numbers or focused on specific cell classes, thereby hindering comprehensive gene expression analysis across all retina types. To fill the gap, we generated the largest retinal scRNA-seq dataset to date, comprising approximately 190,000 single cells from C57BL/6J mouse retinas, enriched for rare population cells via antibody-based magnetic cell sorting. Integrating this dataset with public datasets, we constructed the Mouse Retina Cell Atlas (MRCA) for wild-type mice, encompassing over 330,000 cells, characterizing 12 major classes and 138 cell types. The MRCA consolidates existing knowledge, identifies new cell types, and is publicly accessible via CELLxGENE, UCSC Cell Browser, and the Broad Single Cell Portal, providing a user-friendly resource for the mouse retina research community.

Emergence of input selective recurrent dynamics via information transfer maximization

Network structures of the brain have wiring patterns specialized for specific functions. These patterns are partially determined genetically or evolutionarily based on the type of task or stimulus. These wiring patterns are important in information processing; however, their organizational principles are not fully understood. This study frames the maximization of information transmission alongside the reduction of maintenance costs as a multi-objective optimization challenge, utilizing information theory and evolutionary computing algorithms with an emphasis on the visual system. The goal is to understand the underlying principles of circuit formation by exploring the patterns of wiring and information processing. The study demonstrates that efficient information transmission necessitates sparse circuits with internal modular structures featuring distinct wiring patterns. Significant trade-offs underscore the necessity of balance in wiring pattern development. The dynamics of effective circuits exhibit moderate flexibility in response to stimuli, in line with observations from prior visual system studies. Maximizing information transfer may allow for the self-organization of information processing functions similar to actual biological circuits, without being limited by modality. This study offers insights into neuroscience and the potential to improve reservoir computing performance.

Non-invasive single cell aptasensing in live cells and animals

We report a genetically encoded aptamer biosensor platform for non-invasive measurement of drug distribution in cells and animals. We combined the high specificity of aptamer molecular recognition with the easy-to-detect properties of fluorescent proteins. We generated six encoded aptasensors, showcasing the platform versatility. The biosensors display high sensitivity and specificity for detecting their specific drug target over related analogs. We show dose dependent response of biosensor performance reaching saturating drug uptake levels in individual live cells. We designed our platform for integration into animal genomes; thus, we incorporated aptamer biosensors into zebrafish, an important model vertebrate. The biosensors enabled non-invasive drug biodistribution imaging in whole animals across different timepoints. To our knowledge, this is the first example of an aptamer biosensor-expressing transgenic vertebrate that is carried through generations. As such, our encoded platform addresses the need for non-invasive whole animal biosensing ideal for pharmacokinetic-pharmacodynamic analyses that can be expanded to other organisms and to detect diverse molecules of interest.

Comprehensive single-cell atlas of the mouse retina

Single-cell RNA sequencing (scRNA-seq) has advanced our understanding of cellular heterogeneity at the single-cell resolution by classifying and characterizing cell types in multiple tissues and species. While several mouse retinal scRNA-seq reference datasets have been published, each dataset either has a relatively small number of cells or is focused on specific cell classes, and thus is suboptimal for assessing gene expression patterns across all retina types at the same time. To establish a unified and comprehensive reference for the mouse retina, we first generated the largest retinal scRNA-seq dataset to date, comprising approximately 190,000 single cells from C57BL/6J mouse whole retinas. This dataset was generated through the targeted enrichment of rare population cells via antibody-based magnetic cell sorting. By integrating this new dataset with public datasets, we conducted an integrated analysis to construct the Mouse Retina Cell Atlas (MRCA) for wild-type mice, which encompasses over 330,000 single cells. The MRCA characterizes 12 major classes and 138 cell types. It captured consensus cell type characterization from public datasets and identified additional new cell types. To facilitate the public use of the MRCA, we have deposited it in CELLxGENE, UCSC Cell Browser, and the Broad Single Cell Portal for visualization and gene expression exploration. The comprehensive MRCA serves as an easy-to-use, one-stop data resource for the mouse retina communities.