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Plasma-Free Blood as a Potential Alternative to Whole Blood for Transcriptomic Analysis
RNA sequencing (RNAseq) technology has become increasingly important in precision medicine and clinical diagnostics, and emerged as a powerful tool for identifying protein-coding genes, performing differential gene analysis, and inferring immune cell composition. Human peripheral blood samples are w...
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Published in: | Phenomics (Cham, Switzerland) Switzerland), 2024-04, Vol.4 (2), p.109-124 |
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Main Authors: | , , , , , , , , , , , , , , , |
Format: | Article |
Language: | English |
Subjects: | |
Citations: | Items that this one cites Items that cite this one |
Online Access: | Get full text |
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Summary: | RNA sequencing (RNAseq) technology has become increasingly important in precision medicine and clinical diagnostics, and emerged as a powerful tool for identifying protein-coding genes, performing differential gene analysis, and inferring immune cell composition. Human peripheral blood samples are widely used for RNAseq, providing valuable insights into individual biomolecular information. Blood samples can be classified as whole blood (WB), plasma, serum, and remaining sediment samples, including plasma-free blood (PFB) and serum-free blood (SFB) samples that are generally considered less useful byproducts during the processes of plasma and serum separation, respectively. However, the feasibility of using PFB and SFB samples for transcriptome analysis remains unclear. In this study, we aimed to assess the suitability of employing PFB or SFB samples as an alternative RNA source in transcriptomic analysis. We performed a comparative analysis of WB, PFB, and SFB samples for different applications. Our results revealed that PFB samples exhibit greater similarity to WB samples than SFB samples in terms of protein-coding gene expression patterns, detection of differentially expressed genes, and immunological characterizations, suggesting that PFB can serve as a viable alternative to WB for transcriptomic analysis. Our study contributes to the optimization of blood sample utilization and the advancement of precision medicine research. |
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ISSN: | 2730-583X 2730-5848 |
DOI: | 10.1007/s43657-023-00121-1 |