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Quantitative transcriptomic profiling of freshly isolated human B cells, monocytes, T cells, and skin mast cells 2618

Year: 2025
Type: article
Abstract: Description Aim To obtain a quantitative map of immune cell phenotypes by studying their transcriptomes. Background: The human body comprises over 200 cell types, each defined by unique gene expression profiles. Quantitative expression data are essential for understanding their biological functions. We analyzed transcriptomes of five immune cell populations: CD19+ B cells, CD14+ monocytes, CD4+ T cells, CD8+ T cells, and skin mast cells (MCs). Methods RNA from freshly isolated cell fractions was analyzed using the Ampliseq platform, covering ∼21,000 human genes. Expression levels were reported as raw reads for precise cross-cell comparisons. Results Differentially expressed genes were categorized into granule proteases, Fc receptors, cytokines, cytokine receptors, transcription factors, and signaling molecules. MCs uniquely expressed granule proteases TPSB2, CTSG, CPA3, CMA1, and receptors FCER1A and MRGPRX2. CD8+ T cells showed low-level expression of all five human granzymes, while CD4+ T cells expressed granzymes A, K, and M. Monocytes expressed CD14, lysozyme, and multiple Fc receptors like FCGR1A. B-cell markers CD19, CD20, and CD21 were prominent in B cells. Key transcription factors identified included GATA1, GATA2 (MCs), GATA3 (T cells), and POU2F2 (OCT2) and PAX5 (B cells). Conclusion This comprehensive transcriptomic analysis of 780+ genes in immune cells offers a valuable reference for understanding gene expression profiles and their implications for immune function. Funding Sources The study was supported by grants from Konsul Berghs Stiftelse (Srinivas Akula), the Knut and Alice Wallenberg Foundation (KAW 2017-0022) (Lars Hellman, Jenny Hallgren, Sara Wernersson, and Gunnar Pejler), and the Deutsche Forschungsgemeinschaft (DFG) (BA-3769/3, BA-3769/4) (Magda Babina). Topic Categories Computational and Systems Immunology (COMP)
Language: English
Subfield: Immunology
Open Access status: bronze
OpenAlex ID: W4416446273
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