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Assessment of a complete and classified platelet proteome from genome-wide transcripts of human platelets and megakaryocytes covering platelet functions.

Published version
Peer-reviewed

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Article

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Authors

Huang, Jingnan 
Swieringa, Frauke 
Solari, Fiorella A 
Provenzale, Isabella 
Grassi, Luigi 

Abstract

Novel platelet and megakaryocyte transcriptome analysis allows prediction of the full or theoretical proteome of a representative human platelet. Here, we integrated the established platelet proteomes from six cohorts of healthy subjects, encompassing 5.2 k proteins, with two novel genome-wide transcriptomes (57.8 k mRNAs). For 14.8 k protein-coding transcripts, we assigned the proteins to 21 UniProt-based classes, based on their preferential intracellular localization and presumed function. This classified transcriptome-proteome profile of platelets revealed: (i) Absence of 37.2 k genome-wide transcripts. (ii) High quantitative similarity of platelet and megakaryocyte transcriptomes (R = 0.75) for 14.8 k protein-coding genes, but not for 3.8 k RNA genes or 1.9 k pseudogenes (R = 0.43-0.54), suggesting redistribution of mRNAs upon platelet shedding from megakaryocytes. (iii) Copy numbers of 3.5 k proteins that were restricted in size by the corresponding transcript levels (iv) Near complete coverage of identified proteins in the relevant transcriptome (log2fpkm > 0.20) except for plasma-derived secretory proteins, pointing to adhesion and uptake of such proteins. (v) Underrepresentation in the identified proteome of nuclear-related, membrane and signaling proteins, as well proteins with low-level transcripts. We then constructed a prediction model, based on protein function, transcript level and (peri)nuclear localization, and calculated the achievable proteome at ~ 10 k proteins. Model validation identified 1.0 k additional proteins in the predicted classes. Network and database analysis revealed the presence of 2.4 k proteins with a possible role in thrombosis and hemostasis, and 138 proteins linked to platelet-related disorders. This genome-wide platelet transcriptome and (non)identified proteome database thus provides a scaffold for discovering the roles of unknown platelet proteins in health and disease.

Description

Funder: Ministerium für Innovation, Wissenschaft und Forschung from Nordrhein-Westfalen

Keywords

Blood Platelets, Hematologic Diseases, Humans, Megakaryocytes, Molecular Sequence Annotation, Proteome, Transcriptome

Journal Title

Sci Rep

Conference Name

Journal ISSN

2045-2322
2045-2322

Volume Title

11

Publisher

Springer Science and Business Media LLC
Sponsorship
Horizon 2020 (766118)
Centre for Molecular Translational Medicine (INCOAG)
German Federal Ministry of Education and Research (BMBF 01EO1503)
Deutsche Forschungsgemeinschaft (ZA 639/4-1, JU 273/2-1)
British Heart Foundation (FS/18/53/22863)