Spatial transcriptomic analyses of distal colon cross-sections from mice fed high fiber and control diet
Ontology highlight
ABSTRACT:
ORGANISM(S): Mus musculus
PROVIDER: GSE183696 | GEO | 2022/08/17
REPOSITORIES: GEO
Similar Datasets
Project description:We used Visium technology (10X Genomics) to infer cell-to-cell communication in ovarian and uterine tissue based on spatial proximity. Organs from 3-month mice in diestrus and 18-month old mice were collected and frozen in OCT. 10 µm thick tissue slices were placed on Visium Spatial Gene Expression Slides (10X Genomics) and stained with Hematoxylin and Eosin (H&E). Libraries were prepared by manufacturer’s recommendations and sequenced on NovaSeq6000. For samples that were sequenced in two runs, both sequencing runs were merged when running spaceranger (10X Genomics). Original nd2 microscopy images and results of scRNA-seq (linked datasets) and spatial transcriptomics analysis are available at Biostudies (S-BIAD482 and S-BSST852).
2024-01-30 | E-MTAB-12105 | biostudies-arrayexpress
Project description:Mouse brain 10x Genomics Visium Spatial Transcriptomics profiles sequence either with Illumina for standard profiling and Nanopore promethION long read sequencer for full-length profiling.
2020-08-26 | GSE153859 | GEO
Project description:We developed cell2location, a principled and versatile Bayesian model that is designed to resolve fine-grained cell types in spatial transcriptomic data and create comprehensive cellular maps of diverse tissues. To validate cell2location in real tissue, we applied the model to data from the mouse brain, which features diverse neural cell types organised in a well characterised spatial architecture across brain areas, thus presenting a canonical use case to test spatial genomics. We generated matched single nucleus (sn, this submission) and Visium spatial RNA-seq (10X Genomics) profiles of adjacent mouse brain sections that contain multiple regions from the telencephalon and diencephalon. To assess the biological and intra-organ technical variation in spatial mapping, we assayed two mouse brains and serial tissue sections from each brain (total of 3 and 2 matched sections from two animals, respectively, and an extra section for snRNA-seq), creating a rich multi-modal and replicated transcriptomic dataset. Tissue processing. Brains of wild-type adult C57BL/6 mice (postnatal day 56, 1 female and 1 male) were dissected, snap frozen, embedded in optimal cutting temperature compound (Tissue-Tek) and stored at -80oC. Brain hemispheres were cryosectioned at -20oC using a cryostat (Leica, CM3050S). To assess tissue quality, RNA was extracted from test tissue sections using the RNeasy Pico Kit (Qiagen) and yielded high RIN values (9.6 and 9.7) on an Agilent Bioanalyser, indicating high RNA quality. For matched single nuclei and Visium RNA-seq experiments, brain hemispheres were cryosectioned to adjacent thick (200 µm) and thin (10 µm) coronal sections, respectively, and processed the same day. In total, four consecutive sets of thick and thin tissue sections were collected from each brain. Five sets of tissue sections yielded both good quality single nuclei and Visium data (three adjacent sections from mouse 1 and two sections from mouse 2) while one additional section from mouse 2 yielded good single nuclei; these were considered for analysis in this study. Visium spatial transcriptomics. Thin (10 µm) mouse brain sections were cryosectioned and mounted directly onto separate capture areas on 10X Visium Spatial Gene Expression slides (beta product version). Processing was done per manufacturer’s protocols. Briefly, sections were methanol-fixed, hematoxylin and eosin (H&E)-stained, and imaged on a NanoZoomer 2.0 slide scanner (Hamamatsu). Sections were then permeabilized and further processed to obtain cDNA libraries that were quality controlled using the Agilent Bioanalyser. The cDNA libraries were sequenced on the Illumina HiSeq 4000 system, aiming at 300 million raw reads per section with read lengths 28cy R1, 8cy i7 index, 0cy i5 index, 91cy read 2. 10X Visium spatial sequencing data was aligned to mouse pre-mRNA genome reference version mm10 using 10X SpaceRanger and mRNA count matrices were generated by adding intronic and exonic reads for each gene in each location. The paired histology H&E images were processed using 10X SpaceRanger to select locations covered by tissue by aligning pre-recorded spot locations with fiducial border spots in the histology image. This allows evaluating the correspondence between cell maps produced using our method and the known brain anatomy. This also allows identifying the number of nuclei in each spot using nuclear segmentation as described in Suppl. Methods and reported in Fig S8A-D. The histology image was used to manually annotate cortical layers in the primary somatosensory cortex (SSp) region using the lasso tool in the 10X Loupe browser.
2021-11-12 | E-MTAB-11114 | biostudies-arrayexpress
Project description:We used Sequence-Scope (Seq-Scope), which can generate ultra-high definition images of sequence-based molecular signatures resolved at a submicrometer scale, for profiling spatial transcriptome associated with biopsy-associated colon injury. Raw 1st-Seq FASTQ with intact tile and coordinate information could be retrieved from https://doi.org/10.5281/zenodo.13118097
2024-08-29 | GSE266556 | GEO
Project description:We developed cell2location, a principled and versatile Bayesian model that is designed to resolve fine-grained cell types in spatial transcriptomic data and create comprehensive cellular maps of diverse tissues. To validate cell2location in real tissue, we applied the model to data from the mouse brain, which features diverse neural cell types organised in a well characterised spatial architecture across brain areas, thus presenting a canonical use case to test spatial genomics. We generated matched single nucleus (sn, this submission) and Visium spatial RNA-seq (10X Genomics) profiles of adjacent mouse brain sections that contain multiple regions from the telencephalon and diencephalon. To assess the biological and intra-organ technical variation in spatial mapping, we assayed two mouse brains and serial tissue sections from each brain (total of 3 and 2 matched sections from two animals, respectively, and an extra section for snRNA-seq), creating a rich multi-modal and replicated transcriptomic dataset. Tissue processing. Brains of wild-type adult C57BL/6 mice (postnatal day 56, 1 female and 1 male) were dissected, snap frozen, embedded in optimal cutting temperature compound (Tissue-Tek) and stored at -80oC. Brain hemispheres were cryosectioned at -20oC using a cryostat (Leica, CM3050S). To assess tissue quality, RNA was extracted from test tissue sections using the RNeasy Pico Kit (Qiagen) and yielded high RIN values (9.6 and 9.7) on an Agilent Bioanalyser, indicating high RNA quality. For matched single nuclei and Visium RNA-seq experiments, brain hemispheres were cryosectioned to adjacent thick (200 µm) and thin (10 µm) coronal sections, respectively, and processed the same day. In total, four consecutive sets of thick and thin tissue sections were collected from each brain. Five sets of tissue sections yielded both good quality single nuclei and Visium data (three adjacent sections from mouse 1 and two sections from mouse 2) while one additional section from mouse 2 yielded good single nuclei; these were considered for analysis in this study. Single nucleus RNA-sequencing. Thick (200 µm) mouse brain sections were cryosectioned, dissected from OCT and kept in a tube on dry ice until subsequent processing. Nuclei were extracted from each section as described previously. Briefly, nuclei were released from sections via Dounce homogenisation, Hoechst-stained, and isolated via fluorescence-activated cell sorting (FACS). Nuclei were then loaded into the 10X Chromium Single Cell 3′ Kit (v3) to obtain 3,000-7,000 nuclei per well, and library preparation was done per manufacturer’s protocol. Libraries were sequenced on an Illumina NovaSeq S4 system. Sequencing data were processed using 10X CellRanger version 3.0.2, aligned to mouse pre-mRNA genome reference version mm10 and mRNA count matrices were generated by adding intronic and exonic unique molecular identifier (UMI) counts for each gene in each cell. Initially, snRNA-seq counts were processed using standard Seurat V3 workflow without correcting batch effects between 6 individual samples.
2021-11-12 | E-MTAB-11115 | biostudies-arrayexpress
Project description:BACKGROUND: Previous studies of short-term surgical outcomes after preoperative exposure to anti-TNF therapy in ulcerative colitis (UC) patients who have undergone IPAA have been conflicting. We sought to determine whether preoperative exposure to anti-TNF therapy affects histological measures of fibrosis in the colorectum, which may be a potential factor in adverse anastomosis complications following IPAA surgery.
METHODS: Individuals who received infliximab as maintenance therapy and who received their last dose within 180 days of the first stage of IPAA were selected. The control group comprised UC patients who were not exposed to anti-TNF therapy, matched by age, sex, BMI, disease duration, albumin levels, and post-operative leak outcome. Hematoxylin and eosin- (H&E) and trichrome-stained slides from the most distal, well-oriented, full-thickness section of colorectum from each patient’s total colectomy specimen were evaluated. Blinded assessment of the degree of fibrosis in the lamina propria, the submucosa, the submucosa immediately adjacent to the muscularis propria, and the subserosa was performed by a single observer using a semi-quantitative pictorial scale.
| 2289972 | ecrin-mdr-crc
Project description:8 spatial RNA-seq experiments (10x Genomics Visium) and 5 single-cell RNA-seq experiments (10x Genomics Chromium) using high-grade serous ovarian carcinoma (HGSOC) samples obtained from the ovaries during the interval debulking surgery
2022-08-29 | GSE211956 | GEO
Project description:In comparison to bulk sequencing or single cell sequencing, spatial transcriptomics preserves the spatial information in tissue slices and can even be mapped to immunofluorescent stainings. This enables to unravel complex interactions of neighboring cells or to link cell morphology to transcriptome data. The 10x genomics visium spatial assay offers to combine spatial transcriptomics with immunofluorescent staining of cryo-sectioned tissue slices. We applied this technique to 10 µm fresh frozen mouse brain slices and developed a protocol that still protects RNA integrity while improving buffers for immunofluorescent staining. We investigated the influence of various parameters on RNA integrity and on antibody binding of blocking, staining as well as wash buffers. Finally, we propose a protocol that does not alter RNA integrity in comparison the 10x genomics demonstrated protocol but allows the usage of several antibodies that have not been compatible with the protocol before. In addition, we discuss the influence of the tested parameters which offers further development of application specific staining protocols.
2023-06-07 | GSE228891 | GEO
Project description:We study and report the whole transcriptome spatial profiling insights in colorectal cancer using the Visium spatial technique (Visium CytAssist, 10x genomics).
2024-05-17 | GSE267401 | GEO
Project description:We designed a Nextflow DSL2-based pipeline, Spatial Transcriptomics Quantification (STQ), for simultaneous processing of 10x Genomics Visium spatial transcriptomics data and a matched hematoxylin and eosin (H&E)-stained whole slide image (WSI), optimized for Patient-Derived Xenograft (PDX) cancer specimens. Our pipeline enables the classification of sequenced transcripts for deconvolving the mouse and human species and mapping the transcripts to reference transcriptomes. We align the H&E WSI with the spatial layout of the Visium slide and generate imaging and quantitative morphology features for each Visium spot. The pipeline design enables multiple analysis workflows, including single or dual reference genomes input and stand-alone image analysis. We show the utility of our pipeline on a dataset from Visium profiling of four melanoma PDX samples. The clustering of Visium spots and clustering of H&E imaging features reveal similar patterns arising from the two data modalities.
2024-05-21 | GSE238004 | GEO