Project description:The postnatal development and maturation of the mammalian heart involve highly intricate processes that remain incompletely understood, particularly concerning the molecular signature and roles of the diverse cell types involved. In this study, we present a comprehensive dataset generated from murine hearts at three key postnatal developmental stages, using advanced spatially resolved transcriptomic technology, Spatio-Temporal Enhanced Resolution Omics-Sequencing (Stereo-seq). This dataset encompasses the spatial transcriptomes of approximately 1.86 million individual cells within intact sections of murine hearts at postnatal developmental stages. Our dataset serves as a valuable resource for investigating the mechanisms underlying mammalian heart development and maturation. Through initial analyses, we identified distinct cell types and their spatial distributions, including 850,000 cardiomyocytes within a single heart section. This extensive dataset provides researchers with opportunities for data mining and facilitates diverse analyses, including studies on transcriptional regulation, cell-to-cell communication, and the functional activities of the genes and signalling molecules during critical phases of heart development.
Project description:The recent development of spatial omics enables single-cell profiling of the transcriptome and the 3D organization of the genome in a spatially resolved manner. A spatial epigenomics method would expand the repertoire of spatial omics tools and accelerate our understanding of the spatial regulation of cellular processes and tissue functions. Here, we developed an imaging approach for spatially resolved profiling of epigenetic modifications in single cells
Project description:Understanding the spatial distribution of T cells is pivotal to decrypting immune dysfunction in cancer. Current spatially resolved transcriptomics fall short in directly annotating T cell receptors (TCRs), limiting the comprehension of anti-cancer immunity. We introduce a novel technology, Spatially Resolved T Cell Receptor Sequencing (SPTCR-seq), integrating target enrichment and long-read sequencing for highly sensitive TCR sequencing. This approach yields an on-target rate of ~85%, and via a bespoke computational pipeline, it provides meticulous spatial mapping, error correction, and UMI refinement. SPTCR-seq outperforms PCR-based methods, offering superior reconstruction of the complete TCR architecture, inclusive of V, D, J regions and the vital complementarity-determining region 3 (CDR3). Applying SPTCR-seq, we reveal local T cell diversity, clonal expansion, and transcriptional evolution across spatially distinct niches in glioblastoma, identifying critical involvement of NK and B cells in spatial T cell adaptation. SPTCR-seq, by bridging spatially resolved omics and TCR sequencing, stands as a robust tool for exploring T cell dysfunction in cancers and beyond.
Project description:Spatially resolved transcriptomics technologies allow for the measurement of gene expression in situ. We applied direct RNA hybridization-based in situ sequencing (ISS, Cartana) to compare male and female healthy mouse kidneys and the male kidneys injury and repair timecourse of ischemic reperfusion injury (IRI). A pre-selected panel of 200 genes were used to identify the dynamics of cell states and their spatial distributions during injury and repair. We developed a new computational pipeline, CellScopes, for the rapid analysis, multi-omic integration and visualization of spatially resolved transcriptomic datasets. The resulting atlas allowed us to resolve distinct kidney niches, dynamic alterations in cell state over the course of injury and repair and cell-cell interactions between leukocytes and kidney parenchyma. Projection of snRNA-seq dataset from the same injury and repair samples allowed us to impute the spatial localization of genes not directly measured by Cartana.
Project description:Spatially resolved transcriptomics technologies allow for the measurement of gene expression in situ. We applied direct RNA hybridization-based in situ sequencing (ISS, Cartana) to compare male and female healthy mouse kidneys and the male kidneys injury and repair timecourse of ischemic reperfusion injury (IRI). A pre-selected panel of 200 genes were used to identify the dynamics of cell states and their spatial distributions during injury and repair. We developed a new computational pipeline, CellScopes, for the rapid analysis, multi-omic integration and visualization of spatially resolved transcriptomic datasets. The resulting atlas allowed us to resolve distinct kidney niches, dynamic alterations in cell state over the course of injury and repair and cell-cell interactions between leukocytes and kidney parenchyma. Projection of snRNA-seq dataset from the same injury and repair samples allowed us to impute the spatial localization of genes not directly measured by Cartana.
Project description:Idiopathic pulmonary fibrosis (IPF) is a progressive lung disease with poor prognosis and limited treatment options. Efforts to identify effective treatments are thwarted by limited understanding of IPF pathogenesis and poor translatability of available preclinical models. To address these limitations, we generated spatially resolved transcriptome maps of human IPF and bleomycin-induced mouse lung fibrosis.
Project description:We investigated spatiotemporal molecular patterns related to AD pathophsiology using spatially resolved transcriptome of the AD mouse model. The late change of gray matters of AD was commonly related to neuroinflammation, while the early change in the white matter of AD represented neuronal projection and ensheathment of axons before the amyloid plaques accumulation. Disease-associated microglia and astrocyte signatures were spatially differently enriched. Our results provide a key spatiotemporally heterogeneous molecular change particularly related to inflammation in AD.