Dataset Information

Single cell qtSEQ: Cell-indexed quantitative and targeted RNA sequencing for sorted rare lymphocyte subpopulations.

ABSTRACT: Adaptive T and B lymphocytes expand, respond, and persist across a multitude of separable cell differentiation states. Small compartments of these cells present defined cell surface phenotype, but express potentially divergent immune functions. Here, we use high resolution flow cytometry to provide direct access to rare lymphocyte subpopulations for evaluation of steady-state or reactive transcriptional programs. We sort and index single cells by phenotype in 384-well format for quantification of targeted gene amplification through RNA sequencing (single cell qtSEQ). For complete details on the use and execution of this profile, please refer to Dufaud et al. (2021).

SUBMITTER: Shuparski AG

PROVIDER: S-EPMC8715333 | biostudies-literature | 2022 Mar

REPOSITORIES: biostudies-literature

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Single cell qtSEQ: Cell-indexed quantitative and targeted RNA sequencing for sorted rare lymphocyte subpopulations.

Shuparski Andrew G AG Higgins Brett W BW Miller Karen B KB Dufaud Chad R CR Robinson Amanda M AM Dueker Katharina K McHeyzer-Williams Louise J LJ McHeyzer-Williams Michael G MG

STAR protocols 20211222 1

Adaptive T and B lymphocytes expand, respond, and persist across a multitude of separable cell differentiation states. Small compartments of these cells present defined cell surface phenotype, but express potentially divergent immune functions. Here, we use high resolution flow cytometry to provide direct access to rare lymphocyte subpopulations for evaluation of steady-state or reactive transcriptional programs. We sort and index single cells by phenotype in 384-well format for quantification o ...[more]

PMID: 35005646

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Project description:Detrimental health consequences from exposure to space radiation are a major concern for long-duration human exploration missions to the Moon or Mars. Cellular responses to radiation are expected to be heterogeneous for space radiation exposure, where only high-energy protons and other particles traverse a fraction of the cells. Therefore, assessing DNA damage and DNA damage response in individual cells is crucial in understanding the mechanisms by which cells respond to different particle types and energies in space. In this project, we identified a cell-specific signature for radiation response by using single-cell transcriptomics of human lymphocyte subpopulations. We investigated gene expression in individual human T lymphocytes 3 h after ex vivo exposure to 2-Gy gamma rays while using the single-cell sequencing technique (10X Genomics). In the process, RNA was isolated from ~700 irradiated and ~700 non-irradiated control cells, and then sequenced with ~50 k reads/cell. RNA in each of the cells was distinctively barcoded prior to extraction to allow for quantification for individual cells. Principal component and clustering analysis of the unique molecular identifier (UMI) counts classified the cells into three groups or sub-types, which correspond to CD4+, naïve, and CD8+/NK cells. Gene expression changes after radiation exposure were evaluated using negative binomial regression. On average, BBC3, PCNA, and other TP53 related genes that are known to respond to radiation in human T cells showed increased activation. While most of the TP53 responsive genes were upregulated in all groups of cells, the expressions of IRF1, STAT1, and BATF were only upregulated in the CD4+ and naïve groups, but were unchanged in the CD8+/NK group, which suggests that the interferon-gamma pathway does not respond to radiation in CD8+/NK cells. Thus, single-cell RNA sequencing technique was useful for simultaneously identifying the expression of a set of genes in individual cells and T lymphocyte subpopulation after gamma radiation exposure. The degree of dependence of UMI counts between pairs of upregulated genes was also evaluated to construct a similarity matrix for cluster analysis. The cluster analysis identified a group of TP53-responsive genes and a group of genes that are involved in the interferon gamma pathway, which demonstrate the potential of this method for identifying previously unknown groups of genes with similar expression patterns.

Dataset Information

Single cell qtSEQ: Cell-indexed quantitative and targeted RNA sequencing for sorted rare lymphocyte subpopulations.

Publications

Single cell qtSEQ: Cell-indexed quantitative and targeted RNA sequencing for sorted rare lymphocyte subpopulations.

Similar Datasets

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