Single-cell transcriptomic atlas of the mouse regenerating muscle tissue
Ontology highlight
ABSTRACT:
ORGANISM(S): Mus musculus
PROVIDER: GSE143437 | GEO | 2020/01/11
REPOSITORIES: GEO
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Project description:We report a series of single-cell transcriptomic datasets of regenerating mouse muscle tissue generated with the 10x Genomics Chromium v3 platform.
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Project description:In this work, we applied single-cell transcriptome sequencing on primary human liver tissue samples to study cellular processes underlying human liver regeneration. In order to study regeneration-specific cellular processes we obtained primary healthy liver tissue samples and liver tissue samples from patients that underwent a preoperative medical procedure called portal vein embolization (PVE). This medical treatment is performed to enlarge part of the liver such that a diseased portion can be removed avoiding liver insufficiency and thus we used post-PVE-derived tissues as a model to study liver regeneration in humans. This paradigm enabled us to catalog cell states related to tissue structure in two important and physiologically relevant conditions: hypertrophy and atrophy. In addition, we overcame technical challenges and provided novel protocols and pipelines for generating high quality liver cell atlases from frozen specimens showing consistency in results between fresh and frozen tissue datasets. Moreover, we established tissue-scale iterative indirect immunofluorescence imaging to enable high-dimensional spatial analysis of perivascular microenvironments and uncover cellular and histological alterations to regenerating liver lobules.
2024-04-13 | E-MTAB-12594 | biostudies-arrayexpress
Project description:Single-cell transcriptomic atlas of the mouse regenerating muscle tissue
| PRJNA600499 | ENA
Project description:This repository contains all the FASTQ files for the five data modalities (scRNA-seq, scATAC-seq, Multiome, CITE-seq+scVDJ-seq, and spatial transcriptomics) used in the article \\"An Atlas of Cells in The Human Tonsil,\\" published in Immunity in 2024. Inspired by the TCGA barcodes, we have named each fastq file with the following convention: [TECHNOLOGY].[DONOR_ID].[SUBPROJECT].[GEM_ID].[LIBRARY_ID].[LIBRARY_TYPE].[LANE].[READ].fastq.gz which allows to retrieve all metadata from the name itself. Here is a full description of each field: - TECHNOLOGY: scRNA-seq, scATAC-seq, Multiome, CITE-seq+scVDJ-seq, and spatial transcriptomics (Visium). We also include the fastq files associated with the multiome experiments performed on two mantle cell lymphoma patients (MCL). - DONOR_ID: identifier for each of the 17 patients included in the cohort. We provide the donor-level metadata in the file \\"tonsil_atlas_donor_metadata.csv\\", including the hospital, sex, age, age group, cause for tonsillectomy and cohort type for every donor. - SUBPROJECT: each subproject corresponds to one run of the 10x Genomics Chromium™ Chip. - GEM_ID: each run of the 10x Genomics Chromium™ Chip consists of up to 8 \\"GEM wells\\" (see https://www.10xgenomics.com/support/software/cell-ranger/getting-started/cr-glossary): a set of partitioned cells (Gel Beads-in-emulsion) from a single 10x Genomics Chromium™ Chip channel. We give a unique identifier to each of these channels. - LIBRARY_ID: one or more sequencing libraries can be derived from a GEM well. For instance, multiome yields two libraries (ATAC and RNA) and CITE-seq+scVDJ yields 4 libraries (RNA, ADT, BCR, TCR). - LIBRARY_TYPE: the type of library for each library_id. Note that we used cell hashing () for a subset of the scRNA-seq libraries, and thus the library_type can be \\"not_hashed\\", \\"hashed_cdna\\" (RNA expression) or \\"hashed_hto\\" (the hashtag oligonucleotides). - LANE: to increase sequencing depth, each library was sequenced in more than one lane. Important: all lanes corresponding to the same sequencing library need to be inputed together to cellranger, because they come from the same set of cells. - READ: for scATAC-seq we have three reads (R1, R2 or R3), see cellranger-atac's documentation. While we find these names to be the most useful, they need to be changed to follow cellranger's conventions. We provide a code snippet in the README file of the GitHub repository associated with the tonsil atlas to convert between both formats (https://github.com/Single-Cell-Genomics-Group-CNAG-CRG/TonsilAtlas/). Besides the fastq files, cellranger (and other mappers) require additional files, which we also provide in this repository: - cell_hashing_metadata.csv: as mentioned above, we ran cell hashing (10.1186/s13059-018-1603-1) to detect doublets and reduce cost per cell. This file provides the sequence of the hashtag oligonucleotides in cellranger convention to allow demultiplexing. - cite_seq_feature_reference.csv: similar to the previous file, this one links each protein surface marker to the hashtag oligonucleotide that identified it in the CITE-seq experiment. - V10M16-059.gpr and V19S23-039.gpr: these correspond to the two slides of the two Visium experiments performed in the tonsil atlas. They are needed to run spaceranger. - [GEM_ID]_[SLIDE]_[CAPTURE_AREA].jpg: 8 images associated with the Visium experiments. Here, GEM_ID refers to each of the 4 capture areas in each slide. - [TECHNOLOGY]_sequencing_metadata.csv: the GEM-level metadata for each technology. It includes the relationship between subproject, gem_id, library_id, library_type and donor_id. These are the other repositories associated with the tonsil atlas: - Expression and accessibility matrices: https://zenodo.org/records/10373041 - Seurat objects: https://zenodo.org/records/8373756 - HCATonsilData package: https://bioconductor.org/packages/release/data/experiment/html/HCATonsilData.html - Azimuth: https://azimuth.hubmapconsortium.org/ - Github: https://github.com/Single-Cell-Genomics-Group-CNAG-CRG/TonsilAtlas
2024-05-02 | E-MTAB-13687 | biostudies-arrayexpress
Project description:Purpose: The goal of this study was to establish the first detailed cell atlas of the regenerating caudal fin of zebrafish larvae. Intact and regenerating caudal fin were used for single-cell RNA-sequencing with the aim to provide the first integrated model of epimorphic regeneration in zebrafish larvae and demonstrate the diversity of the cells required for blastema formation. Methods: 150 of regenerating caudal fin (cut) and intact caudal fine (uncut) samples were dissociated and loaded into the 10x Genomics Chromium Platform, and sequenced using Illumina NovaSeq 6000. Conclusion: Our study constitutes a resource of the gene expression profile in intact and regenerating caudal fin of zebrafish larvae. We report the application of single-molecule-based sequencing technology for high-throughput profiling of both intact (uncut) and regenerating caudal fin samples (cut) at 24hpA. We confirmed the presence of macrophage subsets, previously described by our group to govern zebrafish fin regeneration, and identified a novel blastemal cell population.
2021-07-17 | GSE158851 | GEO