1The 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.

BGI Stereomics Stereo-Seq
Arabidopsis thaliana
Sample: 4
Tissue Section: 4

2Establishment 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.

10x Genomics Visium Spatial Gene Expression
Sus scrofa
Sample: 2
Tissue Section: 2

3Spatial transcriptomic data of Oryza longistaminata rhizomeSource: STOmics DB (ID: STT0000024 )

Spatial transcriptomic data of Oryza longistaminata rhizome

BGI Stereomics Stereo-Seq
Oryza longistaminata
Sample: 10
Tissue Section: 21

4Spatial 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.

BGI Stereomics Stereo-Seq
Columba livia
Taeniopygia guttata
Sample: 3
Tissue Section: 5

5PRISTA4D: 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.

BGI Stereomics Stereo-Seq
Schmidtea mediterranea
Sample: 2
Tissue Section: 55

6Spatiotemporal 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.

BGI Stereomics Stereo-Seq
Mus musculus
Sample: 15
Tissue Section: 15

7Resolution 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.

BGI Stereomics Stereo-Seq
Mus musculus
Sample: 3
Tissue Section: 3

8Mouse Heart spatial transcriptomeSource: STOmics DB (ID: STT0000009 )

The spatial transcriptomic data of mouse heart

BGI Stereomics Stereo-Seq
Mus musculus
Sample: 4
Tissue Section: 7

9Spatial transcriptomics map of the embryonic mouse brain: a tool to explore neurogenesisSource: STOmics DB (ID: STT0000051 )

The developing brain has a complex and well-organized anatomical structure comprising different types of neural and non-neural cells. Stem cells, progenitors, and newborn neurons tightly interact with their neighbouring cells and tissue microenvironment, and this intricate interplay ultimately shapes the output of neurogenesis. Given the relevance of spatial cues during brain development, we acknowledge the necessity for a transcriptomics atlas within the tissue context accessible to the neurodevelopmental community. To fulfil this need, we offer an open-access spatial gene expression browser of the embryonic mouse brain at the peak of neurogenesis. Using 10x Visium technology, we generated spatially-resolved RNAseq data from E13.5 embryonic brain sections. Unsupervised clustering reliably defined specific cell type populations of diverse lineages and maturational states. Differential expression analysis revealed unique transcriptional signatures across specific embryonic brain areas, uncovering novel features inherent to particular anatomical domains. Furthermore, we integrated single-cell RNAseq data from E13.5 mouse brains into our Spatial Transcriptomics data, adding tissue context to single-cell resolution. In summary, we provide a valuable tool that enables the exploration and discovery of unforeseen molecular players involved in neurogenesis, particularly in the crosstalk between different cell types.

10x Genomics Visium Spatial Gene Expression
Mus musculus
Sample: 4
Tissue Section: 4

10Stomic data processingSource: STOmics DB (ID: STT0000048 )

Developing a series algorithm to generate more accurate single cell stomics data.

BGI Stereomics Stereo-Seq
Arabidopsis thaliana
Mus musculus
Glycine max
Sample: 3
Tissue Section: 3