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Monaco G, Lee B, Xu W, Mustafah S, Hwang YY, Carré C, Burdin N, Visan L, Ceccarelli M, Poidinger M, Zippelius A, Pedro de Magalhães J, Larbi A. RNA-Seq Signatures Normalized by mRNA Abundance Allow Absolute Deconvolution of Human Immune Cell Types. Cell Rep 2019; 26:1627-1640.e7. [PMID: 30726743 PMCID: PMC6367568 DOI: 10.1016/j.celrep.2019.01.041] [Citation(s) in RCA: 440] [Impact Index Per Article: 88.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/22/2018] [Revised: 12/03/2018] [Accepted: 01/10/2019] [Indexed: 01/22/2023] Open
Abstract
The molecular characterization of immune subsets is important for designing effective strategies to understand and treat diseases. We characterized 29 immune cell types within the peripheral blood mononuclear cell (PBMC) fraction of healthy donors using RNA-seq (RNA sequencing) and flow cytometry. Our dataset was used, first, to identify sets of genes that are specific, are co-expressed, and have housekeeping roles across the 29 cell types. Then, we examined differences in mRNA heterogeneity and mRNA abundance revealing cell type specificity. Last, we performed absolute deconvolution on a suitable set of immune cell types using transcriptomics signatures normalized by mRNA abundance. Absolute deconvolution is ready to use for PBMC transcriptomic data using our Shiny app (https://github.com/giannimonaco/ABIS). We benchmarked different deconvolution and normalization methods and validated the resources in independent cohorts. Our work has research, clinical, and diagnostic value by making it possible to effectively associate observations in bulk transcriptomics data to specific immune subsets.
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Affiliation(s)
- Gianni Monaco
- Singapore Immunology Network (SIgN), Agency for Science Technology and Research, Biopolis, 8A Biomedical Grove, 138648, Singapore, Singapore; Integrative Genomics of Ageing Group, Institute of Ageing and Chronic Disease, University of Liverpool, Liverpool L78TX, UK; Department of Biomedicine, University Hospital and University of Basel, 4031 Basel, Switzerland.
| | - Bernett Lee
- Singapore Immunology Network (SIgN), Agency for Science Technology and Research, Biopolis, 8A Biomedical Grove, 138648, Singapore, Singapore
| | - Weili Xu
- Singapore Immunology Network (SIgN), Agency for Science Technology and Research, Biopolis, 8A Biomedical Grove, 138648, Singapore, Singapore
| | - Seri Mustafah
- Singapore Immunology Network (SIgN), Agency for Science Technology and Research, Biopolis, 8A Biomedical Grove, 138648, Singapore, Singapore
| | - You Yi Hwang
- Singapore Immunology Network (SIgN), Agency for Science Technology and Research, Biopolis, 8A Biomedical Grove, 138648, Singapore, Singapore
| | | | | | | | - Michele Ceccarelli
- BIOGEM Research Center, Ariano Irpino, Italy; Department of Science and Technology, University of Sannio, Benevento, Italy
| | - Michael Poidinger
- Singapore Immunology Network (SIgN), Agency for Science Technology and Research, Biopolis, 8A Biomedical Grove, 138648, Singapore, Singapore
| | - Alfred Zippelius
- Department of Biomedicine, University Hospital and University of Basel, 4031 Basel, Switzerland
| | - João Pedro de Magalhães
- Integrative Genomics of Ageing Group, Institute of Ageing and Chronic Disease, University of Liverpool, Liverpool L78TX, UK.
| | - Anis Larbi
- Singapore Immunology Network (SIgN), Agency for Science Technology and Research, Biopolis, 8A Biomedical Grove, 138648, Singapore, Singapore; Department of Biology, Faculty of Sciences, University Tunis El Manar, Tunis, Tunisia; Faculty of Medicine, University of Sherbrooke, Sherbrooke, QC, Canada; Department of Microbiology, Immunology Programme, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore.
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