PlateletSeq: a novel method for discovery of blood-based biomarkers

Ryan J Collinson, Darren Boey, Lynne Wilson, Zi Yun Ng, Bob Mirzai, Hun Chuah, Michael F Leahy, Rebecca Howman, Matthew Linden, Kathy Fuller, Wendy N Erber, Belinda B Guo

Research output: Contribution to journalArticlepeer-review

1 Citation (Scopus)

Abstract

Platelets are small circulating fragments of cells that play important roles in thrombosis, haemostasis, immune response, inflammation and cancer growth. Although anucleate, they contain a rich RNA repertoire which offers an opportunity to characterise changes in platelet gene expression in health and disease. Whilst this can be achieved with conventional RNA sequencing, a large input of high-quality RNA, and hence blood volume, is required (unless a pre-amplification step is added), along with specialist bioinformatic skills for data analysis and interpretation. We have developed a transcriptomics next-generation sequencing-based approach that overcomes these limitations. Termed PlateletSeq, this method requires very low levels of RNA input and does not require specialist bioinformatic analytical skills. Here we describe the methodology, from sample collection to processing and data analysis. Specifically, blood samples can be stored for up to 8 days at 4°C prior to analysis. Platelets are isolated using multi-step centrifugation and a purity of <1 leucocyte per 0.26x10 6 platelets is optimal for gene expression analysis. We have applied PlateletSeq to normal adult blood samples and show there are no age-associated variations and only minor gender-associated differences. In contrast, platelets from patients with myeloproliferative neoplasms show differences in platelet transcript profiles from normal and between disease subtypes. This illustrates the potential applicability of PlateletSeq for biomarker discovery and studying platelet biology in patient samples. It also opens avenues for assessing platelet quality in other fields such as transfusion research.

Original languageEnglish
Pages (from-to)139-149
Number of pages11
JournalMethods
Volume219
DOIs
Publication statusPublished - Nov 2023

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