Unknown,Transcriptomics,Genomics,Proteomics

Dataset Information

Single cell 5’ transcript, TCRαβ enriched, and Cell hashing/CITE-seq library preparation on the 10x chromium, and sequencing

ABSTRACT: Single cells from human colorectal cancer and normal adjacent colon of 16 patients were used for single-cell RNA-seq, TCR-seq, CITE-seq and Cell hashing. In brief, single cells were incubated for 3h with or without PMA/Ionomycin, and were treated with Cell hashing and CITE-seq antibodies to distinguish samples, stimulation/non-stimulation, and cell surface proteins. Sorted viable CD3+TCRαβ+ single cells were loaded into 10x genomics ChromiumTM controller to make nanoliter-scale droplets with uniquely barcoded 5’ gel beads called GEMs. After GEM-RT and the following some cDNA amplification steps, cDNAs derived from cellular mRNA were pooled for downstream processing and library preparation according to the manufacturer’s instructions. The 5’ transcript library was sequenced with Illumina Novaseq. The single cell TCR enriched library was sequenced with Illumina Miseq using 150 paired-end reads. HTO/ADTs from Cell hashing or CITE-seq were amplified using specific primers that append P5 and P7 sequences for illumina sequencing (Miseq or Nextseq). All fastq files were demultiplexed. Cell hashing and CITE-seq barcodes are available in attached text files. Fastq files from RNA-seq and TCR-seq can be processed through cellranger and vdjranger by 10xgenomics. The datasets include the data of independent experiments at May 29, June 16, June 23, and Aug 13, 2019. Details are available in Masuda et al., bioRxiv, 2020, The functional and phenotypic diversity of single T-cell infiltrates in human colorectal cancer as correlated with clinical outcome.

INSTRUMENT(S): Illumina NovaSeq 6000

ORGANISM(S): Homo sapiens

SUBMITTER: Arnold Han

PROVIDER: E-MTAB-9455 | biostudies-arrayexpress |

REPOSITORIES: biostudies-arrayexpress

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Publications

Multiplexed single-cell analysis reveals prognostic and nonprognostic T cell types in human colorectal cancer.

Masuda Kazuya K Kornberg Adam A Miller Jonathan J Lin Sijie S Suek Nathan N Botella Theo T Secener Kerim A KA Bacarella Alyssa M AM Cheng Liang L Ingham Matthew M Rosario Vilma V Al-Mazrou Ahmed M AM Lee-Kong Steven A SA Kiran Ravi P RP Stoeckius Marlon M Smibert Peter P Del Portillo Armando A Oberstein Paul E PE Sims Peter A PA Yan Kelley S KS Han Arnold A

JCI insight 20220408 7

Clinical outcomes in colorectal cancer (CRC) correlate with T cell infiltrates, but the specific contributions of heterogenous T cell types remain unclear. To investigate the diverse function of T cells in CRC, we profiled 37,931 T cells from tumors and adjacent normal colon of 16 patients with CRC with respect to transcriptome, TCR sequence, and cell surface markers. Our analysis identified phenotypically and functionally distinguishable effector T cell types. We employed single-cell gene signa ...[more]

PMID: 35192548

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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

Dataset Information

Single cell 5’ transcript, TCRαβ enriched, and Cell hashing/CITE-seq library preparation on the 10x chromium, and sequencing

Publications

Multiplexed single-cell analysis reveals prognostic and nonprognostic T cell types in human colorectal cancer.

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