High-plex protein and whole transcriptome co-mapping at cellular resolution with spatial CITE-seq
Ontology highlight
ABSTRACT:
ORGANISM(S): Mus musculus Homo sapiens
PROVIDER: GSE213264 | GEO | 2023/01/04
REPOSITORIES: GEO
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Project description:High-plex protein and whole transcriptome co-mapping at cellular resolution with spatial CITE-seq
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Project description:T cell development in the human thymus has primarily been studied using antibody-based approaches, such as flow cytometry, which can create difficulties in translating phenotypic findings to scRNA-seq data. In order to bridge this gap and obtain paired surface protein and RNA information for individual cells, we carried out CITE-seq with a 143-plex customised antibody panel on human postnatal thymocytes. This was further combined with TCR-seq for TRA and TRB loci to gain insights into the V(D)J recombination progress in developing cells. Using information from all three modalities, we annotated over 30 different stages of human T cell development, which align with known surface marker profiles. This data was utilised in the context of the human thymus spatial atlas for high-resolution spatial mapping of developing T cells, which revealed differences in the migration and maturation kinetics of CD4 and CD8 lineage single positive thymocytes.
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Project description:We present spatial-CITE-seq for high-plex protein and whole transcriptome co-mapping, which was firstly demonstrated for profiling 198 proteins and transcriptome in multiple mouse tissue types. It was then applied to human tissues to measure 283 proteins and transcriptome that revealed spatially distinct germinal center reaction in tonsil and early immune activation in skin at the COVID-19 mRNA vaccine injection site. Spatial-CITE-seq may find a range of applications in biomedical research.
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Project description:High-plex spatial RNA profiling reveals cell type-specific biomarker expression during melanoma development
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Project description:In this study, we extended co-indexing of transcriptomes and epitopes (CITE) to the spatial dimension and demonstrated high-plex protein and whole transcriptome co-mapping. We profiled 189 proteins and whole transcriptome in multiple mouse tissue types with spatial CITE sequencing and then further applied the method to measure 273 proteins and transcriptome in human tissues, revealing spatially distinct germinal center reactions in tonsil and early immune activation in skin at the Coronavirus Disease 2019 mRNA vaccine injection site.
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Project description:Within the thymus, regulation of the cellular cross-talk directing T cell development is dependent on spatial interactions within specialized niches. To create a holistic, spatially defined map of tissue niches guiding postnatal T cell development we employed the multidimensional imaging platform CO-detection by indEXing (CODEX), as well as Cellular Indexing of Transcriptomes and Epitopes by Sequencing (CITE-seq) and Assay for Transposable-Accessible Chromatin (ATAC-seq). We generated age-matched 4–5-month-old postnatal thymus datasets for both male and female donors, and describe signaling and cell-cell interaction networks in sequential thymocyte developmental niches. Together, these data represent a unique age-matched spatial multiomic resource to investigate how sex-based differences in thymus regulation and T cell development arise, and provide an essential resource to understand the mechanisms underlying immune function and dysfunction in males and females.
2024-08-30 | GSE264587 | GEO
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:In this study we used single cell multi-omics profiling to create an atlas of the human YS to gain insights into its haematopoietic, metabolic and nutritive functions during early embryonic development. This contains fetal liver CITE-seq (surface protein and cytosolic RNA content) data from six biological replicates. Pooled lanes were demultiplexed using SoupOrCell (for alignment and demultiplexing software and version numbers, please see accompanying manuscript and protocols within this accession). Raw count files provided are directly as output by alignment software, without any quality control applied. Quality control is described in accompanying manuscript methods. Metadata by barcode are provided as supplementary tables in accompanying manuscript.
2022-12-08 | E-MTAB-11613 | biostudies-arrayexpress
Project description:In this study we used single cell multi-omics profiling to create an atlas of the human YS to gain insights into its haematopoietic, metabolic and nutritive functions during early embryonic development. This contains embryonic liver CITE-seq (surface protein and cytosolic RNA content) data from three biological replicates. Pooled lanes were demultiplexed using SoupOrCell (for alignment and demultiplexing software and version numbers, please see accompanying manuscript and protocols within this accession). Raw count files provided are directly as output by alignment software, without any quality control applied. Quality control is described in accompanying manuscript methods. Metadata by barcode are provided as supplementary tables in accompanying manuscript.
2022-12-08 | E-MTAB-11618 | biostudies-arrayexpress