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Spatial transcriptomics technologies permit the study of the spatial distribution of RNA at near-single-cell resolution genome-wide. However, the feasibility of studying spatial allele-specific expression (ASE) from these data remains uncharacterized. Here, we introduce spASE, a computational framework for detecting and estimating spatial ASE. To tackle the challenges presented by cell type mixtures and a low signal to noise ratio, we implement a hierarchical model involving additive mixtures of spatial smoothing splines. We apply our method to allele-resolved Visium and Slide-seq from the mouse cerebellum and hippocampus and report new insight into the landscape of spatial and cell type-specific ASE therein.
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Alelos , Cerebelo , Transcriptoma , Animales , Ratones , Cerebelo/metabolismo , Hipocampo/metabolismo , Perfilación de la Expresión Génica , Análisis de la Célula IndividualRESUMEN
Naive CD4+ T cells must differentiate in order to orchestrate immunity to Plasmodium, yet understanding of their emerging phenotypes, clonality, spatial distributions, and cellular interactions remains incomplete. Here, we observe that splenic polyclonal CD4+ T cells differentiate toward T helper 1 (Th1) and T follicular helper (Tfh)-like states and exhibit rarer phenotypes not elicited among T cell receptor (TCR) transgenic counterparts. TCR clones present at higher frequencies exhibit Th1 skewing, suggesting that variation in major histocompatibility complex class II (MHC-II) interaction influences proliferation and Th1 differentiation. To characterize CD4+ T cell interactions, we map splenic microarchitecture, cellular locations, and molecular interactions using spatial transcriptomics at near single-cell resolution. Tfh-like cells co-locate with stromal cells in B cell follicles, while Th1 cells in red pulp co-locate with activated monocytes expressing multiple chemokines and MHC-II. Spatial mapping of individual transcriptomes suggests that proximity to chemokine-expressing monocytes correlates with stronger effector phenotypes in Th1 cells. Finally, CRISPR-Cas9 gene disruption reveals a role for CCR5 in promoting clonal expansion and Th1 differentiation. A database of cellular locations and interactions is presented: https://haquelab.mdhs.unimelb.edu.au/spatial_gui/.
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Linfocitos T CD4-Positivos , Diferenciación Celular , Malaria , Animales , Ratones , Linfocitos T CD4-Positivos/citología , Linfocitos T CD4-Positivos/inmunología , Linfocitos T CD4-Positivos/metabolismo , Malaria/inmunología , Malaria/parasitología , Ratones Endogámicos C57BL , Fenotipo , Receptores de Antígenos de Linfocitos T/metabolismo , Receptores CCR5/metabolismo , Receptores CCR5/genética , Bazo/inmunología , Células TH1/inmunologíaRESUMEN
Background: Decompensated heart failure (HF) can be categorized as de novo or worsening of chronic HF. In PARAGLIDE-HF (Prospective comparison of ARNI with ARB Given following stabiLization In DEcompensated HFpEF), among patients with an ejection fraction >40% that stabilized after worsening HF, sacubitril/valsartan led to a significantly greater reduction in N-terminal pro-B-type natriuretic peptide (NT-proBNP) and was associated with clinical benefit compared to valsartan. Objectives: This prespecified analysis characterized patients with de novo vs worsening chronic HF in PARAGLIDE-HF and assessed the interaction between HF chronicity and the effect of sacubitril/valsartan. Methods: Patients were classified as de novo (first diagnosis of HF) or chronic (known HF prior to the index event). Time-averaged proportional change in NT-proBNP from baseline to weeks 4 and 8 was analyzed using an analysis of covariance model. A win ratio consisting of time to cardiovascular death, number and times of HF hospitalizations during follow-up, number and times of urgent HF visits during follow-up, and time-averaged proportional change in NT-proBNP was assessed for each group. Results: Of the 466 participants, 153 (33%) had de novo HF and 313 (67%) had chronic HF. De novo patients had lower rates of atrial fibrillation/flutter and lower creatinine. There was a nonsignificant reduction in NT-proBNP with sacubitril/valsartan vs valsartan for de novo (0.82; 95% CI: 0.62-1.07) and chronic HF (0.88; 95% CI: 0.73-1.07), interaction P = 0.66. The win ratio was nominally in favor of sacubitril/valsartan for both de novo (1.12; 95% CI: 0.70-1.58) and chronic HF (1.24; 95% CI: 0.89-1.71). Conclusions: There is no interaction between HF chronicity and the effect of sacubitril-valsartan.
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Children in malaria-endemic regions can experience repeated Plasmodium infections over short periods of time. Effects of re-infection on multiple co-existing CD4+ T cell subsets remain unresolved. Here, we examine antigen-experienced CD4+ T cells during re-infection in mice, using scRNA-seq/TCR-seq and spatial transcriptomics. TCR transgenic TEM cells initiate rapid Th1/Tr1 recall responses prior to proliferating, while GC Tfh counterparts are refractory, with TCM/Tfh-like cells exhibiting modest non-proliferative responses. Th1-recall is a partial facsimile of primary Th1-responses, with no upregulated effector-associated genes being unique to recall. Polyclonal, TCR-diverse, CD4+ T cells exhibit similar recall dynamics, with individual clones giving rise to multiple effectors including highly proliferative Th1/Tr1 cells, as well as GC Tfh and Tfh-like cells lacking proliferative capacity. Thus, we show substantial diversity in recall responses mounted by multiple co-existing CD4+ T cell subsets in the spleen, and present graphical user interfaces for studying gene expression dynamics and clonal relationships during re-infection.
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Linfocitos T CD4-Positivos , Malaria , Reinfección , Animales , Malaria/inmunología , Malaria/parasitología , Linfocitos T CD4-Positivos/inmunología , Ratones , Reinfección/inmunología , Células TH1/inmunología , Ratones Endogámicos C57BL , Bazo/inmunología , Bazo/parasitología , Receptores de Antígenos de Linfocitos T/metabolismo , Receptores de Antígenos de Linfocitos T/inmunología , Receptores de Antígenos de Linfocitos T/genética , Ratones Transgénicos , Femenino , Memoria InmunológicaRESUMEN
Neuroblastoma is a pediatric cancer arising from the developing sympathoadrenal lineage with complex inter- and intra-tumoral heterogeneity. To chart this complexity, we generated a comprehensive cell atlas of 55 neuroblastoma patient tumors, collected from two pediatric cancer institutions, spanning a range of clinical, genetic, and histologic features. Our atlas combines single-cell/nucleus RNA-seq (sc/scRNA-seq), bulk RNA-seq, whole exome sequencing, DNA methylation profiling, spatial transcriptomics, and two spatial proteomic methods. Sc/snRNA-seq revealed three malignant cell states with features of sympathoadrenal lineage development. All of the neuroblastomas had malignant cells that resembled sympathoblasts and the more differentiated adrenergic cells. A subset of tumors had malignant cells in a mesenchymal cell state with molecular features of Schwann cell precursors. DNA methylation profiles defined four groupings of patients, which differ in the degree of malignant cell heterogeneity and clinical outcomes. Using spatial proteomics, we found that neuroblastomas are spatially compartmentalized, with malignant tumor cells sequestered away from immune cells. Finally, we identify spatially restricted signaling patterns in immune cells from spatial transcriptomics. To facilitate the visualization and analysis of our atlas as a resource for further research in neuroblastoma, single cell, and spatial-omics, all data are shared through the Human Tumor Atlas Network Data Commons at www.humantumoratlas.org.
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The function of the mammalian brain relies upon the specification and spatial positioning of diversely specialized cell types. Yet, the molecular identities of the cell types and their positions within individual anatomical structures remain incompletely known. To construct a comprehensive atlas of cell types in each brain structure, we paired high-throughput single-nucleus RNA sequencing with Slide-seq1,2-a recently developed spatial transcriptomics method with near-cellular resolution-across the entire mouse brain. Integration of these datasets revealed the cell type composition of each neuroanatomical structure. Cell type diversity was found to be remarkably high in the midbrain, hindbrain and hypothalamus, with most clusters requiring a combination of at least three discrete gene expression markers to uniquely define them. Using these data, we developed a framework for genetically accessing each cell type, comprehensively characterized neuropeptide and neurotransmitter signalling, elucidated region-specific specializations in activity-regulated gene expression and ascertained the heritability enrichment of neurological and psychiatric phenotypes. These data, available as an online resource ( www.BrainCellData.org ), should find diverse applications across neuroscience, including the construction of new genetic tools and the prioritization of specific cell types and circuits in the study of brain diseases.
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Encéfalo , Perfilación de la Expresión Génica , Animales , Ratones , Encéfalo/anatomía & histología , Encéfalo/citología , Encéfalo/metabolismo , Perfilación de la Expresión Génica/métodos , Secuenciación de Nucleótidos de Alto Rendimiento , Hipotálamo/citología , Hipotálamo/metabolismo , Mesencéfalo/citología , Mesencéfalo/metabolismo , Neuropéptidos/metabolismo , Neurotransmisores/metabolismo , Fenotipo , Rombencéfalo/citología , Rombencéfalo/metabolismo , Análisis de Expresión Génica de una Sola Célula , Transcriptoma/genéticaRESUMEN
Understanding kidney disease relies on defining the complexity of cell types and states, their associated molecular profiles and interactions within tissue neighbourhoods1. Here we applied multiple single-cell and single-nucleus assays (>400,000 nuclei or cells) and spatial imaging technologies to a broad spectrum of healthy reference kidneys (45 donors) and diseased kidneys (48 patients). This has provided a high-resolution cellular atlas of 51 main cell types, which include rare and previously undescribed cell populations. The multi-omic approach provides detailed transcriptomic profiles, regulatory factors and spatial localizations spanning the entire kidney. We also define 28 cellular states across nephron segments and interstitium that were altered in kidney injury, encompassing cycling, adaptive (successful or maladaptive repair), transitioning and degenerative states. Molecular signatures permitted the localization of these states within injury neighbourhoods using spatial transcriptomics, while large-scale 3D imaging analysis (around 1.2 million neighbourhoods) provided corresponding linkages to active immune responses. These analyses defined biological pathways that are relevant to injury time-course and niches, including signatures underlying epithelial repair that predicted maladaptive states associated with a decline in kidney function. This integrated multimodal spatial cell atlas of healthy and diseased human kidneys represents a comprehensive benchmark of cellular states, neighbourhoods, outcome-associated signatures and publicly available interactive visualizations.
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Perfilación de la Expresión Génica , Enfermedades Renales , Riñón , Análisis de la Célula Individual , Transcriptoma , Humanos , Núcleo Celular/genética , Riñón/citología , Riñón/lesiones , Riñón/metabolismo , Riñón/patología , Enfermedades Renales/metabolismo , Enfermedades Renales/patología , Transcriptoma/genética , Estudios de Casos y Controles , Imagenología TridimensionalRESUMEN
Spatiotemporal orchestration of gene expression is required for proper embryonic development. The use of single-cell technologies has begun to provide improved resolution of early regulatory dynamics, including detailed molecular definitions of most cell states during mouse embryogenesis. Here we used Slide-seq to build spatial transcriptomic maps of complete embryonic day (E) 8.5 and E9.0, and partial E9.5 embryos. To support their utility, we developed sc3D, a tool for reconstructing and exploring three-dimensional 'virtual embryos', which enables the quantitative investigation of regionalized gene expression patterns. Our measurements along the main embryonic axes of the developing neural tube revealed several previously unannotated genes with distinct spatial patterns. We also characterized the conflicting transcriptional identity of 'ectopic' neural tubes that emerge in Tbx6 mutant embryos. Taken together, we present an experimental and computational framework for the spatiotemporal investigation of whole embryonic structures and mutant phenotypes.
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Organogénesis , Transcriptoma , Ratones , Animales , Transcriptoma/genética , Organogénesis/genética , Desarrollo Embrionario/genética , Embrión de Mamíferos , Fenotipo , Regulación del Desarrollo de la Expresión Génica/genética , Proteínas de Dominio T Box/genéticaRESUMEN
The function of the mammalian brain relies upon the specification and spatial positioning of diversely specialized cell types. Yet, the molecular identities of the cell types, and their positions within individual anatomical structures, remain incompletely known. To construct a comprehensive atlas of cell types in each brain structure, we paired high-throughput single-nucleus RNA-seq with Slide-seq-a recently developed spatial transcriptomics method with near-cellular resolution-across the entire mouse brain. Integration of these datasets revealed the cell type composition of each neuroanatomical structure. Cell type diversity was found to be remarkably high in the midbrain, hindbrain, and hypothalamus, with most clusters requiring a combination of at least three discrete gene expression markers to uniquely define them. Using these data, we developed a framework for genetically accessing each cell type, comprehensively characterized neuropeptide and neurotransmitter signaling, elucidated region-specific specializations in activity-regulated gene expression, and ascertained the heritability enrichment of neurological and psychiatric phenotypes. These data, available as an online resource (BrainCellData.org) should find diverse applications across neuroscience, including the construction of new genetic tools, and the prioritization of specific cell types and circuits in the study of brain diseases.
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Transferring annotations of single-cell-, spatial- and multi-omics data is often challenging owing both to technical limitations, such as low spatial resolution or high dropout fraction, and to biological variations, such as continuous spectra of cell states. Based on the concept that these data are often best described as continuous mixtures of cells or molecules, we present a computational framework for the transfer of annotations to cells and their combinations (TACCO), which consists of an optimal transport model extended with different wrappers to annotate a wide variety of data. We apply TACCO to identify cell types and states, decipher spatiomolecular tissue structure at the cell and molecular level and resolve differentiation trajectories using synthetic and biological datasets. While matching or exceeding the accuracy of specialized tools for the individual tasks, TACCO reduces the computational requirements by up to an order of magnitude and scales to larger datasets (for example, considering the runtime of annotation transfer for 1 M simulated dropout observations).
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Multiómica , Análisis de la Célula Individual , Curaduría de DatosRESUMEN
The treatment of low-risk primary prostate cancer entails active surveillance only, while high-risk disease requires multimodal treatment including surgery, radiation therapy, and hormonal therapy. Recurrence and development of metastatic disease remains a clinical problem, without a clear understanding of what drives immune escape and tumor progression. Here, we comprehensively describe the tumor microenvironment of localized prostate cancer in comparison with adjacent normal samples and healthy controls. Single-cell RNA sequencing and high-resolution spatial transcriptomic analyses reveal tumor context dependent changes in gene expression. Our data indicate that an immune suppressive tumor microenvironment associates with suppressive myeloid populations and exhausted T-cells, in addition to high stromal angiogenic activity. We infer cell-to-cell relationships from high throughput ligand-receptor interaction measurements within undissociated tissue sections. Our work thus provides a highly detailed and comprehensive resource of the prostate tumor microenvironment as well as tumor-stromal cell interactions.
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Neoplasias de la Próstata , Transcriptoma , Masculino , Humanos , Próstata/patología , Microambiente Tumoral , Perfilación de la Expresión Génica , Neoplasias de la Próstata/genéticaRESUMEN
BACKGROUND: Guideline-directed medical therapy (GDMT) for heart failure with reduced ejection fraction (HFrEF) improves clinical outcomes and quality of life. Optimizing GDMT in the hospital is associated with greater long-term use in HFrEF. This study aimed to describe the efficacy of a multidisciplinary virtual HF intervention on GDMT optimization among patients with HFrEF admitted for any cause. METHODS: In this pilot randomized, controlled study, consecutive patients with HFrEF admitted to noncardiology medicine services for any cause were identified at a large academic tertiary care hospital between May to September 2021. Major exclusions were end-stage renal disease, hemodynamic instability, concurrent COVID-19 infection, and current enrollment in hospice care. Patients were randomized to a clinician-level virtual peer-to-peer consult intervention providing GDMT recommendations and information on medication costs versus usual care. Primary end points included (1) proportion of patients with new GDMT initiation or use and (2) changes to HF optimal medical therapy scores which included target dosing (range, 0-9). RESULTS: Of 242 patients identified, 91 (38%) were eligible and randomized to intervention (N=52) or usual care (N=39). Baseline characteristics were similar between intervention and usual care (mean age 63 versus 67 years, 23% versus 26% female, 46% versus 49% Black, mean ejection fraction 33% versus 31%). GDMT use on admission was also similar. There were greater proportions of patients with GDMT initiation or continuation with the intervention compared with usual care. After adjusting for optimal medical therapy score on admission, changes to optimal medical therapy score at discharge were higher for the intervention group compared with usual care (+0.44 versus -0.31, absolute difference +0.75, adjusted estimate 0.86±0.42; P=0.041). CONCLUSIONS: Among eligible patients with HFrEF hospitalized for any cause on noncardiology services, a multidisciplinary pilot virtual HF consultation increased new GDMT initiation and dose optimization at discharge.
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COVID-19 , Insuficiencia Cardíaca , Humanos , Femenino , Persona de Mediana Edad , Masculino , Insuficiencia Cardíaca/terapia , Calidad de Vida , Proyectos Piloto , Volumen Sistólico , Hospitales , Derivación y ConsultaRESUMEN
Mobile sources are responsible for a substantial controllable portion of the reactive organic carbon (ROC) emitted to the atmosphere, especially in urban environments of the United States. We update existing methods for calculating mobile source organic particle and vapor emissions in the United States with over a decade of laboratory data that parameterize the volatility and organic aerosol (OA) potential of emissions from on-road vehicles, nonroad engines, aircraft, marine vessels, and locomotives. We find that existing emission factor information from Teflon filters combined with quartz filters collapses into simple relationships and can be used to reconstruct the complete volatility distribution of ROC emissions. This new approach consists of source-specific filter artifact corrections and state-of-the-science speciation including explicit intermediate-volatility organic compounds (IVOCs), yielding the first bottom-up volatility-resolved inventory of US mobile source emissions. Using the Community Multiscale Air Quality model, we estimate mobile sources account for 20 %-25 % of the IVOC concentrations and 4.4 %-21.4 % of ambient OA. The updated emissions and air quality model reduce biases in predicting fine-particle organic carbon in winter, spring, and autumn throughout the United States (4.3 %-11.3 % reduction in normalized bias). We identify key uncertain parameters that align with current state-of-the-art research measurement challenges.
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T cells mediate antigen-specific immune responses to disease through the specificity and diversity of their clonotypic T cell receptors (TCRs). Determining the spatial distributions of T cell clonotypes in tissues is essential to understanding T cell behavior, but spatial sequencing methods remain unable to profile the TCR repertoire. Here, we developed Slide-TCR-seq, a 10-µm-resolution method, to sequence whole transcriptomes and TCRs within intact tissues. We confirmed the ability of Slide-TCR-seq to map the characteristic locations of T cells and their receptors in mouse spleen. In human lymphoid germinal centers, we identified spatially distinct TCR repertoires. Profiling T cells in renal cell carcinoma and melanoma specimens revealed heterogeneous immune responses: T cell states and infiltration differed intra- and inter-clonally, and adjacent tumor and immune cells exhibited distinct gene expression. Altogether, our method yields insights into the spatial relationships between clonality, neighboring cell types, and gene expression that drive T cell responses.
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Receptores de Antígenos de Linfocitos T , Transcriptoma , Inmunidad Adaptativa/genética , Animales , Humanos , Ratones , Linfocitos TRESUMEN
Realizing the full utility of brain organoids to study human development requires understanding whether organoids precisely replicate endogenous cellular and molecular events, particularly since acquisition of cell identity in organoids can be impaired by abnormal metabolic states. We present a comprehensive single-cell transcriptomic, epigenetic, and spatial atlas of human cortical organoid development, comprising over 610,000 cells, from generation of neural progenitors through production of differentiated neuronal and glial subtypes. We show that processes of cellular diversification correlate closely to endogenous ones, irrespective of metabolic state, empowering the use of this atlas to study human fate specification. We define longitudinal molecular trajectories of cortical cell types during organoid development, identify genes with predicted human-specific roles in lineage establishment, and uncover early transcriptional diversity of human callosal neurons. The findings validate this comprehensive atlas of human corticogenesis in vitro as a resource to prime investigation into the mechanisms of human cortical development.
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Corteza Cerebral , Organoides , Diferenciación Celular , Corteza Cerebral/metabolismo , Humanos , Neurogénesis , Neuronas , Organoides/metabolismoRESUMEN
A central problem in spatial transcriptomics is detecting differentially expressed (DE) genes within cell types across tissue context. Challenges to learning DE include changing cell type composition across space and measurement pixels detecting transcripts from multiple cell types. Here, we introduce a statistical method, cell type-specific inference of differential expression (C-SIDE), that identifies cell type-specific DE in spatial transcriptomics, accounting for localization of other cell types. We model gene expression as an additive mixture across cell types of log-linear cell type-specific expression functions. C-SIDE's framework applies to many contexts: DE due to pathology, anatomical regions, cell-to-cell interactions and cellular microenvironment. Furthermore, C-SIDE enables statistical inference across multiple/replicates. Simulations and validation experiments on Slide-seq, MERFISH and Visium datasets demonstrate that C-SIDE accurately identifies DE with valid uncertainty quantification. Last, we apply C-SIDE to identify plaque-dependent immune activity in Alzheimer's disease and cellular interactions between tumor and immune cells. We distribute C-SIDE within the R package https://github.com/dmcable/spacexr .
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Perfilación de la Expresión Génica , Transcriptoma , Perfilación de la Expresión Génica/métodosRESUMEN
BACKGROUND: Heart Failure with Preserved Ejection Fraction (HFpEF) is a heterogenous disease with few therapies proven to provide clinical benefit. Machine learning can characterize distinct phenotypes and compare outcomes among patients with HFpEF who are hospitalized for acute HF. METHODS: We applied hierarchical clustering using demographics, comorbidities, and clinical data on admission to identify distinct clusters in hospitalized HFpEF (ejection fraction >40%) in the ASCEND-HF trial. We separately applied a previously developed latent class analysis (LCA) clustering method and compared in-hospital and long-term outcomes across cluster groups. RESULTS: Of 7141 patients enrolled in the ASCEND-HF trial, 812 (11.4%) were hospitalized for HFpEF and met the criteria for complete case analysis. Hierarchical Cluster 1 included older women with atrial fibrillation (AF). Cluster 2 had elevated resting blood pressure. Cluster 3 had young men with obesity and diabetes. Cluster 4 had low resting blood pressure. Mortality at 180 days was lowest among Cluster 3 (KM event-rate 6.2 [95% CI: 3.5, 10.9]) and highest among Cluster 4 (18.8 [14.6, 24.0], P < .001). Twenty four-hour urine output was higher in Cluster 3 (2700 mL [1800, 3975]) than Cluster 4 (2100 mL [1400, 3055], P < .001). LCA also identified four clusters: A) older White or Asian women, B) younger men with few comorbidities, C) older individuals with AF and renal impairment, and D) patients with obesity and diabetes. Mortality at 180 days was lowest among LCA Cluster B (KM event-rate 5.5 [2.0, 10.3]) and highest among LCA Cluster C (26.3 [19.2, 35.4], P < .001). CONCLUSIONS: In patients hospitalized for HFpEF, cluster analysis demonstrated distinct phenotypes with differing clinical profiles and outcomes.
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Fibrilación Atrial , Insuficiencia Cardíaca , Femenino , Humanos , Aprendizaje Automático , Obesidad , Pronóstico , Volumen Sistólico/fisiología , Masculino , Ensayos Clínicos como AsuntoRESUMEN
High-resolution spatial transcriptomics enables mapping of RNA expression directly from intact tissue sections; however, its utility for the elucidation of disease processes and therapeutically actionable pathways remains unexplored. We applied Slide-seqV2 to mouse and human kidneys, in healthy and distinct disease paradigms. First, we established the feasibility of Slide-seqV2 in tissue from nine distinct human kidneys, which revealed a cell neighborhood centered around a population of LYVE1+ macrophages. Second, in a mouse model of diabetic kidney disease, we detected changes in the cellular organization of the spatially restricted kidney filter and blood-flow-regulating apparatus. Third, in a mouse model of a toxic proteinopathy, we identified previously unknown, disease-specific cell neighborhoods centered around macrophages. In a spatially restricted subpopulation of epithelial cells, we discovered perturbations in 77 genes associated with the unfolded protein response. Our studies illustrate and experimentally validate the utility of Slide-seqV2 for the discovery of disease-specific cell neighborhoods.
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The olfactory system's ability to detect and discriminate between the vast array of chemicals present in the environment is critical for an animal's survival. In mammals, the first step of this odor processing is executed by olfactory sensory neurons, which project their axons to a stereotyped location in the olfactory bulb (OB) to form glomeruli. The stereotyped positioning of glomeruli in the OB suggests an importance for this organization in odor perception. However, because the location of only a limited subset of glomeruli has been determined, it has been challenging to determine the relationship between glomerular location and odor discrimination. Using a combination of single-cell RNA sequencing, spatial transcriptomics and machine learning, we have generated a map of most glomerular positions in the mouse OB. These observations significantly extend earlier studies and suggest an overall organizational principle in the OB that may be used by the brain to assist in odor decoding.
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Bulbo Olfatorio , Neuronas Receptoras Olfatorias , Animales , Mamíferos , Ratones , Odorantes , Bulbo Olfatorio/fisiología , Neuronas Receptoras Olfatorias/fisiología , Olfato , TranscriptomaRESUMEN
The state and behaviour of a cell can be influenced by both genetic and environmental factors. In particular, tumour progression is determined by underlying genetic aberrations1-4 as well as the makeup of the tumour microenvironment5,6. Quantifying the contributions of these factors requires new technologies that can accurately measure the spatial location of genomic sequence together with phenotypic readouts. Here we developed slide-DNA-seq, a method for capturing spatially resolved DNA sequences from intact tissue sections. We demonstrate that this method accurately preserves local tumour architecture and enables the de novo discovery of distinct tumour clones and their copy number alterations. We then apply slide-DNA-seq to a mouse model of metastasis and a primary human cancer, revealing that clonal populations are confined to distinct spatial regions. Moreover, through integration with spatial transcriptomics, we uncover distinct sets of genes that are associated with clone-specific genetic aberrations, the local tumour microenvironment, or both. Together, this multi-modal spatial genomics approach provides a versatile platform for quantifying how cell-intrinsic and cell-extrinsic factors contribute to gene expression, protein abundance and other cellular phenotypes.