Project description:Raw sequencing data for the proof-of-principal 1D and 2D gridmode transcriptomics performed after C3PO in the following article: https://www.biorxiv.org/content/10.1101/2024.03.12.584578v1.full. The 1D data is found in the limb68 samples here (limb #3 in the article) and the 2 replicates of the 2D data is found in the L127 samples (limb #4 in the article) and L128 samples (limb #5 in the article). For the 2D data the P# value in the filename indicates the corresponding FACS gate.
Project description:bri1-5 is a weak mutant of Brassinosteroid Insensitive 1 (BRI1). Suppressors by activation tagging bri1-1D, brs1-1D and bak1-1D can recover bri1-5 phenotype. We use microarray to investigate which pathways or functional categories have been transcriptionally regulated by bri1-1D, brs1-1D and bak1-1D.
Project description:bri1-5 is a weak mutant of Brassinosteroid Insensitive 1 (BRI1). Suppressors by activation tagging bri1-1D, brs1-1D and bak1-1D can recover bri1-5 phenotype. We use microarray to investigate which pathways or functional categories have been transcriptionally regulated by bri1-1D, brs1-1D and bak1-1D. Whole seedlings from wild-type (WS2), bri1-5, bri1-5/brs1-1D, bri1-5/bak1-1D, bri1-5/bri1-1D. Three biological replicates for each genotype.
Project description:These data were used in the spatial transcriptomics analysis of the article titled \\"Single-Cell and Spatial Transcriptomics Analysis of Human Adrenal Aging\\".
Project description:To reveal the spatial distribution and the difference gene expression pattern of cancer cells in colorectal cancer, Visium spatial transcriptomics of four CRC patients was applied
Project description:To investigate spatial heterogeneities in the axolotl forebrain, a coronal section of it was obtained for spatial transcriptomics using Visium V1.
Project description:Spatial organization of different cell types within prenatal skin across various anatomical sites is not well understood. To address this, here we have generated spatial transcriptomics data from prenatal facial and abdominal skin obtained from a donor at 10 post conception weeks. This in combination with our prenatal skin scRNA-seq dataset has helped us map the location of various identified cell types.
Project description:We developed an analysis pipeline that can extract microbial sequences from Spatial Transcriptomic (ST) data and assign taxonomic labels, generating a spatial microbial abundance matrix in addition to the default host expression matrix, enabling simultaneous analysis of host expression and microbial distribution. We called the pipeline Spatial Meta-transcriptome (SMT) and applied it on both human and murine intestinal sections and validated the spatial microbial abundance information with alternative assays. Biological insights were gained from this novel data that that demonstrated host-microbe interaction at various spatial scales. Finally, we tested experimental modification that can increase microbial capture while preserving host spatial expression quality and, by use of positive controls, quantitatively demonstrated the capture efficiency and recall of our methods. This proof of concept work demonstrates the feasibility of Spatial Meta-transcriptomic analysis, and paves the way for further experimental optimization and application.
Project description:Background: The molecular identification of neural progenitor cell populations that connect to establish the sympathetic nervous system (SNS) remains unclear. This is due to technical limitations in the acquisition and spatial mapping of molecular information to tissue architecture. Results: To address this, we applied Slide-seq spatial transcriptomics to intact fresh frozen chick trunk tissue transversely cryo-sectioned at the developmental stage prior to SNS formation. In parallel, we performed age- and location-matched single cell (sc) RNA-seq and 10x Genomics Visium to inform our analysis. Downstream bioinformatic analyses led to the unique molecular identification of neural progenitor cells within the peripheral sympathetic ganglia (SG) and spinal cord preganglionic neurons (PGNs). We then successfully applied the HiPlex RNAscope fluorescence in situ hybridization and multispectral confocal microscopy to visualize 12 gene targets in stage-, age- and location-matched chick trunk tissue sections. Conclusions: Together, these data demonstrate a robust strategy to acquire and integrate single cell and spatial transcriptomic information, resulting in improved resolution of molecular heterogeneities in complex neural tissue architectures. Successful application of this strategy to the developing SNS provides a roadmap for functional studies of neural connectivity and platform to address complex questions in neural development and regeneration.