1Mouse Heart spatial transcriptomeSource: STOmics DB (ID: STT0000009 )
The spatial transcriptomic data of mouse heart
2A cellular resolution spatial transcriptomic landscape of the adult human cortexSource: STOmics DB (ID: STT0000059 )
In our pursuit of creating a comprehensive human cortical atlas to understand human intelligence, we examined the single-nuclei transcriptomes of 307,738 cells alongside spatial transcriptomics data from 46,948 VISIUM spots and 1,355,582 Stereo cells. Atlases reveal distinct expression patterns and spatial arrangements of cortical neural cell types. Glutamatergic neurons exhibit precise laminar patterns, often mirroring expression patterns in adjacent cortical regions. Overlaying our atlas with functional networks delineated substantial correlations between neural cell types and cortical region function. Notably, regions involved in processing sensory information (pain) display a pronounced accumulation of extratelencephalic neurons. Additionally, our atlas enabled precise localization of the thicker layer 4 of the visual cortex and an in-depth study of the stabilized subplate structure, known as layer 6b, revealed specific marker genes and cellular compositions. Collectively, our research sheds light on the cellular foundations of the intricate and intelligent regions within the human cortex.
3Fate Determination of Cancer-associated Fibroblast Drives Polarized Immunity in Cancer-stroma BoundarySource: STOmics DB (ID: STT0000036 )
The exciting responding rate to anti-PD1 treatment makes dMMR colorectal cancer (CRC) an outstanding model to explore the mechanism underlying immunotherapy sensitivity. This study provides a spatial transcriptomic landscape of CRC tumor at 50 μm resolution and highlights the plasticity of the cancer-stroma boundary immunity. It demonstrates the utility of high-resolution spatial transcriptome to study the cellular components and molecular pattern in the microscopic boundary, in which cancer cells co-opt stromal cells to alter the boundary immunity.
4The Single-cell Stereo-seq reveals region-specific cell subtypes and transcriptome profiling in Arabidopsis leavesSource: STOmics DB (ID: STT0000023 )
Understanding the complex functions of plant leaves requires a thorough characterization of discrete cell features. Although single-cell gene expression profiling technologies have been developed, their application in characterizing cell subtypes has not been achieved yet. Here, we present scStereo-seq (single-cell SpaTial Enhanced REsolution Omics-sequencing) that enabled us to firstly show the bona fide single-cell spatial transcriptome profiles of Arabidopsis leaves. Subtle but significant transcriptomic differences between upper and lower epidermal cells have been successfully distinguished. Furthermore, we discovered cell-type-specific gene expression gradients from the main vein to the leaf edge, which for the first time led to the finding of distinct spatial developmental trajectories of vascular cells and guard cells. Our study showcases the importance of physical locations of individual cells for exerting complex biologic functions in plants and demonstrates that scStereo-seq is a powerful tool to integrate single cell location and transcriptome information for plant biology study.
5Establishment of the pig testis spatial transcriptome atlasSource: STOmics DB (ID: STT0000068 )
Single-cell and spatial transcriptomics have revolutionized our understanding of cellular heterogeneity and gene expression patterns. In this study, we constructed the single-cell and spatial atlas of pig testis cells and identified the trajectory of germ cells and cell-cell communication to dissect the pig spermatogenesis process. Our findings shed new light on the molecular mechanisms underlying pig spermatogenesis and present a valuable resource for future studies investigating reproduction and breeding of pigs.
6Spatial transcriptomic data of Oryza longistaminata rhizomeSource: STOmics DB (ID: STT0000024 )
Spatial transcriptomic data of Oryza longistaminata rhizome
7Spatial and Single Nucleus Transcriptomics Decoding the Molecular Landscape and Cellular Organization of Avian Optic TectumSource: STOmics DB (ID: STT0000064 )
The avian optic tectum (OT) has been extensively studied for its diverse functions, yet a comprehensive understanding of its molecular landscape at the cellular level has been lacking. In this study, we applied a high-resolution spatial transcriptome sequencing technique and single nucleus RNA sequencing (snRNA-seq) to explore the cellular organization and molecular characteristics of the avian OT from two species: Columba livia and Taeniopygia guttata. We identified layer structures consistent with traditional anatomical research and provided comprehensive layer-specific signatures that were highly conserved across avian species. Based on the layer-specific genes, we elucidated diverse functions in different layers, with the stratum griseum periventriculare (SGP) potentially playing a key role in advanced functions of OT, like fear response and associative learning. Furthermore, we clarified the precise laminar distribution of six inhibitory neuron subtypes in OT, which was not observed in mouse superior colliculus, a homologous region of OT. Focusing on the multimodal functions of deeper layers in avian OT, we characterized detailed neuronal subtypes and identified a population of FOXG1+ excitatory neurons, resembling those found in the mouse neocortex, potentially involved in neocortex-related functions and expansion of avian OT. Investigation of inhibitory neurons (INN) indicated the medial and lateral ganglionic eminence as the main origins for INN in OT and uncovered a potentially species-specific subtype. These findings could contribute to improving our understanding of the molecular and cellular architecture of avian OT, shedding light on visual perception and multifunctional association.
8PRISTA4D: Planarian Regenerative Interactive Spatiotemporal Transcriptomic Atlas in four DimensionsSource: STOmics DB (ID: STT0000028 )
Regeneration requires the proper formation of the body axis and dynamic cellular interactions, presenting a significant challenge to dissect in four-dimensional (4D) time and space. Here, we introduce 4D-ST (Spatial Transcriptomics), which retains single-cell resolution while resolving spatial heterogeneity in four dimensions at the organismal level. The 4D-ST provides a comprehensive understanding of the cell types and molecular coordinates of the entire planarian at single-cell resolution. By analyzing the whole-body regeneration cycle of planarian fragments over eight consecutive time points, the 4D-ST captures the spatially and cell-type resolved genes that respond to regeneration, revealing intricate patterns of gene expression and positional gradients along the body axis.
9Spatiotemporal transcriptomic atlas of mouse placentationSource: STOmics DB (ID: STT0000055 )
The intrauterine environment undergoes intricate and significant changes during embryonic development, which, however, is not systematically investigated by spatially resolved transcriptomic technologies. We used Stereo-seq to establish the comprehensive transcriptome landscapes on 13 segments of the mouse uterus ranging from E7.5 to E14.5. In addition, two segments of mouse model with a high-fat diet were included to investigate the impact of adverse intrauterine environments on spatial gene expression patterns during placentation.
10Resolution in Bleomycin-Induced Pulmonary Fibrosis Mouse Model Revealed by Spatial Transcriptome AnalysisSource: STOmics DB (ID: STT0000032 )
The bleomycin-induced pulmonary fibrosis mouse model is commonly used in idiopathic pulmonary fibrosis research, but its cellular and molecular changes and efficiency as a model at the molecular level are not fully understood. In this study, we used spatial transcriptome technology to investigate the cellular and molecular changes in the lungs of bleomycin-induced pulmonary fibrosis mouse models. Our analyses revealed cell dynamics during fibrosis in epithelial cells, mesenchymal cells, immunocytes, and erythrocytes with their spatial distribution available. We confirmed the differentiation of the alveolar type II (AT2) cell type expressing Krt8, and we inferred their trajectories from both the AT2 cells and Club cells. In addition to the fibrosis process, we also noticed evidence of self-resolving, especially to identify possible self-resolving related genes, including Prkca. Our findings provide insights into the cellular and molecular mechanisms underlying fibrosis resolution and represent the first spatiotemporal transcriptome dataset of the bleomycin-induced fibrosis mouse model.