Multiplexed Error-robust Fluorescence In Situ Hybridization Research Articles

Charting the cellular biogeography in colitis reveals fibroblast trajectories and coordinated spatial remodeling

Gut inflammation involves contributions from immune and non-immune cells, whose interactions are shaped by the spatial organization of the healthy gut and its remodeling during inflammation. The crosstalk between fibroblasts and immune cells is an important axis in this process, but our understanding has been challenged by incomplete cell-type definition and biogeography. To address this challenge, we used multiplexed error-robust fluorescence in situ hybridization (MERFISH) to profile the expression of 940 genes in 1.35 million cells imaged across the onset and recovery from a mouse colitis model. We identified diverse cell populations, charted their spatial organization, and revealed their polarization or recruitment in inflammation. We found a staged progression of inflammation-associated tissue neighborhoods defined, in part, by multiple inflammation-associated fibroblasts, with unique expression profiles, spatial localization, cell-cell interactions, and healthy fibroblast origins. Similar signatures in ulcerative colitis suggest conserved human processes. Broadly, we provide a framework for understanding inflammation-induced remodeling in the gut and other tissues.

A spatially-resolved transcriptional atlas of the murine dorsal pons at single-cell resolution

The “dorsal pons”, or “dorsal pontine tegmentum” (dPnTg), is part of the brainstem. It is a complex, densely packed region whose nuclei are involved in regulating many vital functions. Notable among them are the parabrachial nucleus, the Kölliker Fuse, the Barrington nucleus, the locus coeruleus, and the dorsal, laterodorsal, and ventral tegmental nuclei. In this study, we applied single-nucleus RNA-seq (snRNA-seq) to resolve neuronal subtypes based on their unique transcriptional profiles and then used multiplexed error robust fluorescence in situ hybridization (MERFISH) to map them spatially. We sampled ~1 million cells across the dPnTg and defined the spatial distribution of over 120 neuronal subtypes. Our analysis identified an unpredicted high transcriptional diversity in this region and pinpointed the unique marker genes of many neuronal subtypes. We also demonstrated that many neuronal subtypes are transcriptionally similar between humans and mice, enhancing this study’s translational value. Finally, we developed a freely accessible, GPU and CPU-powered dashboard (http://harvard.heavy.ai:6273/) that combines interactive visual analytics and hardware-accelerated SQL into a data science framework to allow the scientific community to query and gain insights into the data.

Clearance of VWF by hepatic macrophages is critical for the protective effect of ADAMTS13 in sickle cell anemia mice

AbstractAlthough it is caused by a single-nucleotide mutation in the β-globin gene, sickle cell anemia (SCA) is a systemic disease with complex, incompletely elucidated pathologies. The mononuclear phagocyte system plays critical roles in SCA pathophysiology. However, how heterogeneous populations of hepatic macrophages contribute to SCA remains unclear. Using a combination of single-cell RNA sequencing and spatial transcriptomics via multiplexed error-robust fluorescence in situ hybridization, we identified distinct macrophage populations with diversified origins and biological functions in SCA mouse liver. We previously found that administering the von Willebrand factor (VWF)–cleaving protease ADAMTS13 alleviated vaso-occlusive episode in mice with SCA. Here, we discovered that the ADAMTS13-cleaved VWF was cleared from the circulation by a Clec4f+Marcohigh macrophage subset in a desialylation-dependent manner in the liver. In addition, sickle erythrocytes were phagocytized predominantly by Clec4f+Marcohigh macrophages. Depletion of macrophages not only abolished the protective effect of ADAMTS13 but exacerbated vaso-occlusive episode in mice with SCA. Furthermore, promoting macrophage-mediated VWF clearance reduced vaso-occlusion in SCA mice. Our study demonstrates that hepatic macrophages are important in the pathogenesis of SCA, and efficient clearance of VWF by hepatic macrophages is critical for the protective effect of ADAMTS13 in SCA mice.

Single-cell Spatial Transcriptomics Analysis of Alzheimer's Disease Pathogenesis in Mouse Models

Understanding molecular mechanisms of Alzheimer’s disease (AD) has proven challenging as disease effects occur at multiple scales in different brain regions. We apply multiplexed error-robust fluorescence in situ hybridization (MERFISH) to generate spatially resolved single-cell RNA atlases from multiple cortical and subcortical brain regions in 5xFAD and age-matched C57 wild-type mice. We also investigate the effect of the TREM2R47H mutation, a strong risk factor for the development of AD in humans, producing similar atlases for Trem2R47H and Trem2R47H-5xFAD mice. We identify amyloid- beta plaque proximal molecular alterations in microglia and astrocytes, but also in five neuronal cell types. Spatial analysis of microglia and astrocyte concentrations reveals Trem2R47H -dependent regional variations, as well as regional transcriptional variation independent of either 5xFAD or Trem2R47H mutations. Cortical excitatory neurons exhibit a consistent Trem2R47H -induced expression increase in Ntrk2, and other MAPK signaling- associated genes, and thalamic excitatory neurons exhibit both 5xFAD and Trem2R47H induced gene program alterations. Additionally, nearly every neuronal cell type exhibits subclusters with decreased 5xFAD populations. Taken together, our MERFISH analysis of 5xFAD and Trem2R47H Alzheimer’s mouse models reveals spatially localized, cell-type-specific, plaque and Trem2R47H induced transcriptome dysregulations in cortical and subcortical brain regions.

A high-resolution transcriptomic and spatial atlas of cell types in the whole mouse brain

The mammalian brain consists of millions to billions of cells that are organized into many cell types with specific spatial distribution patterns and structural and functional properties1–3. Here we report a comprehensive and high-resolution transcriptomic and spatial cell-type atlas for the whole adult mouse brain. The cell-type atlas was created by combining a single-cell RNA-sequencing (scRNA-seq) dataset of around 7 million cells profiled (approximately 4.0 million cells passing quality control), and a spatial transcriptomic dataset of approximately 4.3 million cells using multiplexed error-robust fluorescence in situ hybridization (MERFISH). The atlas is hierarchically organized into 4 nested levels of classification: 34 classes, 338 subclasses, 1,201 supertypes and 5,322 clusters. We present an online platform, Allen Brain Cell Atlas, to visualize the mouse whole-brain cell-type atlas along with the single-cell RNA-sequencing and MERFISH datasets. We systematically analysed the neuronal and non-neuronal cell types across the brain and identified a high degree of correspondence between transcriptomic identity and spatial specificity for each cell type. The results reveal unique features of cell-type organization in different brain regions—in particular, a dichotomy between the dorsal and ventral parts of the brain. The dorsal part contains relatively fewer yet highly divergent neuronal types, whereas the ventral part contains more numerous neuronal types that are more closely related to each other. Our study also uncovered extraordinary diversity and heterogeneity in neurotransmitter and neuropeptide expression and co-expression patterns in different cell types. Finally, we found that transcription factors are major determinants of cell-type classification and identified a combinatorial transcription factor code that defines cell types across all parts of the brain. The whole mouse brain transcriptomic and spatial cell-type atlas establishes a benchmark reference atlas and a foundational resource for integrative investigations of cellular and circuit function, development and evolution of the mammalian brain.

Cochlear transcriptome analysis of an outbred mouse population (CFW).

Age-related hearing loss (ARHL) is the most common cause of hearing loss and one of the most prevalent conditions affecting the elderly worldwide. Despite evidence from our lab and others about its polygenic nature, little is known about the specific genes, cell types, and pathways involved in ARHL, impeding the development of therapeutic interventions. In this manuscript, we describe, for the first time, the complete cell-type specific transcriptome of the aging mouse cochlea using snRNA-seq in an outbred mouse model in relation to auditory threshold variation. Cochlear cell types were identified using unsupervised clustering and annotated via a three-tiered approach-first by linking to expression of known marker genes, then using the NSForest algorithm to select minimum cluster-specific marker genes and reduce dimensional feature space for statistical comparison of our clusters with existing publicly-available data sets on the gEAR website, and finally, by validating and refining the annotations using Multiplexed Error Robust Fluorescence In Situ Hybridization (MERFISH) and the cluster-specific marker genes as probes. We report on 60 unique cell-types expanding the number of defined cochlear cell types by more than two times. Importantly, we show significant specific cell type increases and decreases associated with loss of hearing acuity implicating specific subsets of hair cell subtypes, ganglion cell subtypes, and cell subtypes within the stria vascularis in this model of ARHL. These results provide a view into the cellular and molecular mechanisms responsible for age-related hearing loss and pathways for therapeutic targeting.

Characterization of Niche Cells and Signals Regulating Stepwise Embryonic Hematopoiesis Using Slide-Seq and Merfish Spatial Transcriptomics

Stagewise HSC development initiates in the aorta-gonad-mesonephros (AGM) region during mouse embryonic day (E)9.5-E12.5 and progresses through stages including hemogenic endothelial cell (HEC) specification, the endothelial to hematopoietic transition (EHT), and maturation. The nascent HSCs (pre-HSCs) form in the AGM region and subsequently migrate to the fetal liver where they undergo further maturation and expansion. Recent advances in single cell technologies have significantly enhanced our understanding of intrinsic cellular programs involved in HSC development. However, our knowledge about niche cells and the signals they emanate in the AGM region, as well as their contribution to HSC development, remain limited. Here we've conducted spatial transcriptomics analysis using Slide-seq on mouse trunk tissues, including both the AGM region and the fetal liver, at E10.5, E11.5 and E12.5. In addition, we performed scRNA-seq on the cells collected from the AGM and trunk at E10.5, E11.5 and E12.5, as well as the fetal liver at E12.5. To integrate the Slide-seq and scRNA-seq data, we developed an algorithm that leverages capabilities from both spatial and in-depth transcriptional sequencing. As a result, we were able to successfully reconstitute the structures of the trunk tissues and obtain gene expression profiles of individual cells at 10 µm resolution. From the analysis, we identified 7 cell clusters surrounding the aorta, with one cluster comprised of Nfgr + cells predominantly occupying the dorsal aorta. The ventral part of aorta displayed a complex and multilayered cellular architecture, featuring pre-HSCs, endothelial cells, mesonephric cells, and macrophages. Notably, we identified a unique mesenchymal stromal cell (MSC) population that co-express Cdh2 (encodes N-cadherin or N-cad) and Pdgfra; thus, we call these cells N-cad + MSCs. These N-cad + MSCs were particularly enriched at the ventral part of the aorta, forming a single cell layer positioned between an inner layer of aortic endothelial cells and an outer layer of mesonephric cells. Next, we utilized several bioinformatics tools (CellphoneDB, CellChat, NicheChat, and StringDB) in effort to identify potential signals that could impact embryonic hematopoiesis. The results revealed intricate interactions between N-cad + MSCs and pre-HSCs, for example, involving JAG1-NOTCH1 and SDF-1 (encoded by Cxcl12)-CXCR4 ligand-receptor pairs. To validate the findings obtained by the Slide-seq data, we selected and designed customized RNA probes for 140 genes of interest, including cell markers and potential signals. We then conducted MERFISH (Multiplexed Error-Robust Fluorescence in situ Hybridization) on 18 E11.5 trunk sections. The MERFISH data enabled us to characterize the spatially resolved niche cells and their derived signals in the AGM region at the single-cell level, which largely corroborated the results obtained from the Slide-seq data. Specifically, the MERFISH data indicates that N-cad + MSCs are in direct contact with aortic endothelial cells and are the primary cellular source of Jag1 and Cxcl12 around the aorta. Given the unique position of N-cad + MSCs and their intricate interactions with pre-HSCs, we formulated the hypothesis that N-cad + MSCs play a crucial role in embryonic hematopoiesis. To functionally validate our hypothesis, we are conducting a series of experiments using Ncad CreER; Cxcl12 flox/floxand Ncad CreER; Jag1 flox/flox mouse models. We anticipate that embryos lacking N-cad + MSC derived Jag1 or Cxcl12 will exhibit a substantial decline in intra-aortic hematopoietic clusters, phenotypic pre-HSCs, and functional HSCs. In summary, our study employed sequencing-based (Slide-seq) and imaging-based (MERFISH) spatial transcriptomics technologies to successfully characterize dynamic, spatially resolved profiles of niche components and associated signaling in the AGM region at the single cell level. This work significantly enhances our understanding of niche signaling and its role in regulating embryonic hematopoiesis and may aid the development of novel methods for inducing the transition from pluripotent stem cells to HSCs.

Fate specification is spatially intermingled across planarian stem cells

Regeneration requires mechanisms for producing a wide array of cell types. Neoblasts are stem cells in the planarian Schmidtea mediterranea that undergo fate specification to produce over 125 adult cell types. Fate specification in neoblasts can be regulated through expression of fate-specific transcription factors. We utilize multiplexed error-robust fluorescence in situ hybridization (MERFISH) and whole-mount FISH to characterize fate choice distribution of stem cells within planarians. Fate choices are often made distant from target tissues and in a highly intermingled manner, with neighboring neoblasts frequently making divergent fate choices for tissues of different location and function. We propose that pattern formation is driven primarily by the migratory assortment of progenitors from mixed and spatially distributed fate-specified stem cells and that fate choice involves stem-cell intrinsic processes.

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

The visual signal processing in the retina requires the precise organization of diverse neuronal types working in concert. While single-cell omics studies have identified more than 120 different neuronal subtypes in the mouse retina, little is known about their spatial organization. Here, we generated the single-cell spatial atlas of the mouse retina using multiplexed error-robust fluorescence in situ hybridization (MERFISH). We profiled over 390,000 cells and identified all major cell types and nearly all subtypes through the integration with reference single-cell RNA sequencing (scRNA-seq) data. Our spatial atlas allowed simultaneous examination of nearly all cell subtypes in the retina, revealing 8 previously unknown displaced amacrine cell subtypes and establishing the connection between the molecular classification of many cell subtypes and their spatial arrangement. Furthermore, we identified spatially dependent differential gene expression between subtypes, suggesting the possibility of functional tuning of neuronal types based on location.

Abstract P1185: Spatial Transcriptome Profiling In The Mouse Heart With Single-Cell Resolution

Background: The spatial organization of the diverse cells in the heart shapes biological function. For instance, during the inflammatory and fibrotic processes that are central to heart disease, many cells act mainly within their local microenvironment. Recent studies using single-cell RNA sequencing (scRNA-seq) have provided a detailed list of the cell types and states involved in development, homeostasis and in cardiovascular diseases. However, scRNA-seq requires tissue dissociation, which removes spatial information and thereby limits our ability to determine how cells interact with each other to maintain health or cause disease. As a consequence, the precise spatial organization of cell types and states in the mammalian heart remains unknown. We sought to address this knowledge gap by using multiplexed error-robust fluorescence in situ hybridization (MERFISH), a method that enables simultaneous identification and localization of single transcripts from hundreds of different genes in intact tissue sections. Methods/Results: We adapted MERFISH and developed a new single-cell image segmentation method to creating a single-cell atlas of the mouse heart. First, we designed and constructed a 128-gene MERFISH probe library including cell type marker genes and also genes covering a broad range of cardiac signaling pathways. We then optimized sample preparation, including cell boundary staining and tissue clearing. Once optimized, we used this approach to image 10 μm-thick sections from healthy mouse heart, resolving tens of thousands of cells and millions of transcripts. Our data thus constitute the first single-cell spatial transcriptome atlas of the mouse heart. Conclusion: Through our newly developed cardiac MERFISH platform, we identified tens of thousands of cells and labeled millions of individual RNA transcripts in intact sections of mouse heart. Our cellular transcriptome profile maps enable new insights into how the organization of the heart shapes its biological function.

Spatial Transcriptomics-correlated Electron Microscopy maps transcriptional and ultrastructural responses to brain injury

Understanding the complexity of cellular function within a tissue necessitates the combination of multiple phenotypic readouts. Here, we developed a method that links spatially-resolved gene expression of single cells with their ultrastructural morphology by integrating multiplexed error-robust fluorescence in situ hybridization (MERFISH) and large area volume electron microscopy (EM) on adjacent tissue sections. Using this method, we characterized in situ ultrastructural and transcriptional responses of glial cells and infiltrating T-cells after demyelinating brain injury in male mice. We identified a population of lipid-loaded “foamy” microglia located in the center of remyelinating lesion, as well as rare interferon-responsive microglia, oligodendrocytes, and astrocytes that co-localized with T-cells. We validated our findings using immunocytochemistry and lipid staining-coupled single-cell RNA sequencing. Finally, by integrating these datasets, we detected correlations between full-transcriptome gene expression and ultrastructural features of microglia. Our results offer an integrative view of the spatial, ultrastructural, and transcriptional reorganization of single cells after demyelinating brain injury.

Abstract 4332: Characterizing cancer-associated fibroblasts in prostate cancer using Vizgen’s MERSCOPETM Platform

Abstract Understanding the spatial complexities within cancer provides crucial information for evaluating individual tumor development and progression; recent research in prostate cancer has shown how critical it is for oncologists to maintain a spatial context while characterizing a highly heterogeneous tumor microenvironment. As more and more research groups acknowledge the need for spatial biology solutions to solve difficult questions surrounding cell identity, heterogeneity, and interaction, Vizgen’s MERSCOPETM Platform provides a powerful tool to illuminate spatial information. Built on Multiplexed Error-Robust Fluorescence in situ Hybridization (MERFISH) technology, Vizgen’s MERSCOPETM enables the direct profiling of the spatial organization of intact tissue with subcellular resolution. Here, we use a 500-gene panel to demonstrate the MERSCOPE’s spatial capability, assessing the canonical signaling pathways of cancer, cancer type-specific genes, select immune genes, proto-oncogenes, and tumor-suppressor genes in patient-derived prostate cancer samples. Using the Vizgen Cell Boundary Stain kit, we were able to generate a molecular and cellular atlas of these individual patient tumors by clustering cells based on gene expression and mapping these clusters back onto a spatial representation of the tumor. We found specific clusters relating to prognostic outcomes in cancer-associated fibroblasts (CAFs) and myofibroblasts. Subsequently, we used single-cell RNA-seq datasets to impute related transcriptome data for these various fibroblast clusters to help characterize them more specifically. To understand the heterogeneity intrinsic to CAFs, we performed a neighborhood analysis to determine how proximity to immune cells, tumor cells, and other stromal cells altered gene expression in different CAF clusters. We found gene expression changes associated with inflammation and reactive stromal signaling in CAFs based on their proximity to tumor versus stromal tissue compartments. We also compared the gene expression of tumor cells near CAFs to those more deeply embedded within the tumor compartment. This revealed interesting transcriptional covariations between superficial layers of tumor and their surrounding stromal milieu involved in cell proliferation and signaling. These analyses demonstrate the transcriptional variation possible across fibroblastic stromal cells acting in tumor-adjacent or stromal contexts. Notably, we were able to map and catalogue different patterns of gene expression relating to inflammation, tumor proliferation, and reactive stromal signaling. These findings demonstrate how the MERSCOPE platform can provide deep insights into the complex heterogeneity observed in the tumor microenvironment. Citation Format: Ben Patterson, Cheng-Yi Chen, Nicolas Fernandez, Simran Kaushal, Leiam Colbert, Jiang He. Characterizing cancer-associated fibroblasts in prostate cancer using Vizgen’s MERSCOPETM Platform. [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 4332.

Abstract 5148: Interrogating immuno-oncological interactions in the tumor microenvironment

Abstract Single-cell RNA sequencing is a powerful and innovative tool for assessing individual cancer prognoses and outcomes; however, the process of generating this data typically destroys the spatial complexity of the tumor microenvironment. Understanding the spatial complexities within cancer provides crucial information for evaluating individual tumor development and progression. Vizgen’s MERSCOPETM Platform, built on Multiplexed Error-Robust Fluorescence in situ Hybridization (MERFISH) technology, enables the direct profiling of the spatial organization of intact tissue with subcellular resolution. Here, we present a Pan-Cancer approach to demonstrate the MERSCOPE’s ability to characterize breast, colon, prostate, ovarian, lung, and skin cancers from human clinical samples. Specifically, using a 500-gene panel to assess the canonical signaling pathways of cancer, cancer type-specific genes, select immune genes, proto-oncogenes, and tumor-suppressor genes, we show that the MERSCOPE was able to spatially profile gene expression across multiple tumor types. We utilized the Vizgen Cell Boundary Stain kit to generate a molecular and cellular atlas of individual patient tumors by clustering cells based on gene expression and mapping their spatial organization. To gather insight into immuno-oncological interactions and their effect on gene expression across these tumor types, we performed a neighborhood analysis to determine how proximity to immune cells altered gene expression in tumor cells, and vice versa. We found significant gene expression changes in MHC activation and downstream pathways in immune cells located nearest to tumor cells; in tumor cells nearest to immune cells, we identified increased expression of genes related to immune response mediation and inflammation. Furthermore, we compared the annotated immune cell populations across the various cancer types to observe differences in gene expression. Here, we used publicly available single-cell RNA-sequencing data to impute gene expression for these immune cell populations. This analysis demonstrated the transcriptional variation possible in identical immune cell types that are acting in different tissue contexts. Notably, we were able to map and catalogue different patterns of gene expression relating to inflammation, immune signaling, and immune cell exhaustion. These findings demonstrate how the MERSCOPE platform can provide deep insights into the complex heterogeneity observed between different tumor types and tissues. Citation Format: Ben Patterson, g-Yi Chen, Nicolas Fernandez, Leiam Colbert, Jiang He. Interrogating immuno-oncological interactions in the tumor microenvironment. [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 5148.

Concordance of MERFISH spatial transcriptomics with bulk and single-cell RNA sequencing.

Spatial transcriptomics extends single-cell RNA sequencing (scRNA-seq) by providing spatial context for cell type identification and analysis. Imaging-based spatial technologies such as multiplexed error-robust fluorescence in situ hybridization (MERFISH) can achieve single-cell resolution, directly mapping single-cell identities to spatial positions. MERFISH produces a different data type than scRNA-seq, and a technical comparison between the two modalities is necessary to ascertain how to best integrate them. We performed MERFISH on the mouse liver and kidney and compared the resulting bulk and single-cell RNA statistics with those from the Tabula Muris Senis cell atlas and from two Visium datasets. MERFISH quantitatively reproduced the bulk RNA-seq and scRNA-seq results with improvements in overall dropout rates and sensitivity. Finally, we found that MERFISH independently resolved distinct cell types and spatial structure in both the liver and kidney. Computational integration with the Tabula Muris Senis atlas did not enhance these results. We conclude that MERFISH provides a quantitatively comparable method for single-cell gene expression and can identify cell types without the need for computational integration with scRNA-seq atlases.

Conservation and divergence of cortical cell organization in human and mouse revealed by MERFISH.

The human cerebral cortex has tremendous cellular diversity. How different cell types are organized in the human cortex and how cellular organization varies across species remain unclear. Here, we performed spatially resolved single-cell profiling of 4,000 genes using multiplexed error-robust FISH (MERFISH), identified >100 transcriptionally distinct cell populations, and generated a molecularly defined and spatially resolved cell atlas of the human middle and superior temporal gyrus. We further explored cell-cell interactions arising from soma contact or proximity in a cell-type-specific manner. Comparison with the mouse cortex showed conservation in the laminar organization of cells and differences in somatic interactions across species. Notably, our data revealed human-specific cell-cell proximity patterns and showed a markedly increased enrichment for interactions between neurons and non-neuronal cells in the human cortex.

Cell segmentation in imaging-based spatial transcriptomics.

Single-molecule spatial transcriptomics protocols based on in situ sequencing or multiplexed RNA fluorescent hybridization can reveal detailed tissue organization. However, distinguishing the boundaries of individual cells in such data is challenging and can hamper downstream analysis. Current methods generally approximate cells positions using nuclei stains. We describe a segmentation method, Baysor, that optimizes two-dimensional (2D) or three-dimensional (3D) cell boundaries considering joint likelihood of transcriptional composition and cell morphology. While Baysor can take into account segmentation based on co-stains, it can also perform segmentation based on the detected transcripts alone. To evaluate performance, we extend multiplexed error-robust fluorescence in situ hybridization (MERFISH) to incorporate immunostaining of cell boundaries. Using this and other benchmarks, we show that Baysor segmentation can, in some cases, nearly double the number of cells compared to existing tools while reducing segmentation artifacts. We demonstrate that Baysor performs well on data acquired using five different protocols, making it a useful general tool for analysis of imaging-based spatial transcriptomics.

Spatially resolved cell atlas of the mouse primary motor cortex by MERFISH

A mammalian brain is composed of numerous cell types organized in an intricate manner to form functional neural circuits. Single-cell RNA sequencing allows systematic identification of cell types based on their gene expression profiles and has revealed many distinct cell populations in the brain1,2. Single-cell epigenomic profiling3,4 further provides information on gene-regulatory signatures of different cell types. Understanding how different cell types contribute to brain function, however, requires knowledge of their spatial organization and connectivity, which is not preserved in sequencing-based methods that involve cell dissociation. Here we used a single-cell transcriptome-imaging method, multiplexed error-robust fluorescence in situ hybridization (MERFISH)5, to generate a molecularly defined and spatially resolved cell atlas of the mouse primary motor cortex. We profiled approximately 300,000 cells in the mouse primary motor cortex and its adjacent areas, identified 95 neuronal and non-neuronal cell clusters, and revealed a complex spatial map in which not only excitatory but also most inhibitory neuronal clusters adopted laminar organizations. Intratelencephalic neurons formed a largely continuous gradient along the cortical depth axis, in which the gene expression of individual cells correlated with their cortical depths. Furthermore, we integrated MERFISH with retrograde labelling to probe projection targets of neurons of the mouse primary motor cortex and found that their cortical projections formed a complex network in which individual neuronal clusters project to multiple target regions and individual target regions receive inputs from multiple neuronal clusters.

Characterizing spatial gene expression heterogeneity in spatially resolved single-cell transcriptomic data with nonuniform cellular densities

Recent technological advances have enabled spatially resolved measurements of expression profiles for hundreds to thousands of genes in fixed tissues at single-cell resolution. However, scalable computational analysis methods able to take into consideration the inherent 3D spatial organization of cell types and nonuniform cellular densities within tissues are still lacking. To address this, we developed MERINGUE, a computational framework based on spatial autocorrelation and cross-correlation analysis to identify genes with spatially heterogeneous expression patterns, infer putative cell–cell communication, and perform spatially informed cell clustering in 2D and 3D in a density-agnostic manner using spatially resolved transcriptomic data. We applied MERINGUE to a variety of spatially resolved transcriptomic data sets including multiplexed error-robust fluorescence in situ hybridization (MERFISH), spatial transcriptomics, Slide-seq, and aligned in situ hybridization (ISH) data. We anticipate that such statistical analysis of spatially resolved transcriptomic data will facilitate our understanding of the interplay between cell state and spatial organization in tissue development and disease.

ProbeDealer is a convenient tool for designing probes for highly multiplexed fluorescence in situ hybridization

Fluorescence in situ hybridization (FISH) is a powerful method to visualize the spatial positions of specific genomic loci and RNA species. Recent technological advances have leveraged FISH to visualize these features in a highly multiplexed manner. Notable examples include chromatin tracing, RNA multiplexed error-robust FISH (MERFISH), multiplexed imaging of nucleome architectures (MINA), and sequential single-molecule RNA FISH. However, one obstacle to the broad adoption of these methods is the complexity of the multiplexed FISH probe design. In this paper, we introduce an easy-to-use, versatile, and all-in-one application called ProbeDealer to design probes for a variety of multiplexed FISH techniques and their combinations. ProbeDealer offers a one-stop shop for multiplexed FISH design needs of the research community.

Genome-Scale Imaging of the 3D Organization and Transcriptional Activity of Chromatin

The 3D organization of chromatin regulates many genome functions. Our understanding of 3D genome organization requires tools to directly visualize chromatin conformation in its native context. Here we report an imaging technology for visualizing chromatin organization across multiple scales in single cells with high genomic throughput. First we demonstrate multiplexed imaging of hundreds of genomic loci by sequential hybridization, which allows high-resolution conformation tracing of whole chromosomes. Next we report a multiplexed error-robust fluorescence in situ hybridization (MERFISH)-based method for genome-scale chromatin tracing and demonstrate simultaneous imaging of more than 1,000 genomic loci and nascent transcripts of more than 1,000 genes together with landmark nuclear structures. Using this technology, we characterize chromatin domains, compartments, and trans-chromosomal interactions and their relationship to transcription in single cells. We envision broad application of this high-throughput, multi-scale, and multi-modal imaging technology, which provides an integrated view of chromatin organization in its native structural and functional context.