Using single-cell chromatin accessibility sequencing to characterize CD4+ T cells from murine tissues
The Assay for Transposase-Accessible Chromatin using sequencing (ATAC-seq) is a cutting-edge technology that enables researchers to assess genome-wide chromatin accessibility and to characterize cell type specific gene-regulatory programs. Recent technological progress allows for using this technolo...
Gespeichert in:
| Hauptverfasser: | , , , , , , , |
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| Dokumenttyp: | Article (Journal) |
| Sprache: | Englisch |
| Veröffentlicht: |
16 October 2023
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| In: |
Frontiers in immunology
Year: 2023, Jahrgang: 14, Pages: 1-33 |
| ISSN: | 1664-3224 |
| DOI: | 10.3389/fimmu.2023.1232511 |
| Online-Zugang: | Resolving-System, kostenfrei, Volltext: https://doi.org/10.3389/fimmu.2023.1232511 Verlag, kostenfrei, Volltext: https://www.frontiersin.org/articles/10.3389/fimmu.2023.1232511 
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| Verfasserangaben: | Kathrin Luise Braband, Annekathrin Silvia Nedwed, Sara Salome Helbich, Malte Simon, Niklas Beumer, Benedikt Brors, Federico Marini and Michael Delacher |
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| 520 | |a The Assay for Transposase-Accessible Chromatin using sequencing (ATAC-seq) is a cutting-edge technology that enables researchers to assess genome-wide chromatin accessibility and to characterize cell type specific gene-regulatory programs. Recent technological progress allows for using this technology also on the single-cell level. In this article, we describe the whole value chain from the isolation of T cells from murine tissues to a complete bioinformatic analysis workflow. We start with methods for isolating scATAC-seq-ready CD4+ T cells from murine tissues such as visceral adipose tissue, skin, colon, and secondary lymphoid tissues such as the spleen. We describe the preparation of nuclei and quality control parameters during library preparation. Based on publicly available sequencing data that was generated using these protocols, we describe a step-by-step bioinformatic analysis pipeline for data pre-processing and downstream analysis. Our analysis workflow will follow the R-based bioinformatics framework ArchR, which is currently well established for scATAC-seq datasets. All in all, this work serves as a one-stop shop for generating and analyzing chromatin accessibility landscapes in T cells. | ||
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