4.7 Article

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

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SCIENTIFIC REPORTS
卷 11, 期 1, 页码 -

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NATURE RESEARCH
DOI: 10.1038/s41598-021-91661-x

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资金

  1. European Union [766118]
  2. British Heart Foundation [FS/18/53/22863]
  3. Ministerium fur Innovation, Wissenschaft und Forschung from Nordrhein-Westfalen
  4. Cardiovascular Centre (HVC) of Maastricht University Medical Centre+
  5. Centre for Molecular Translational Medicine (INCOAG, MICRO-BAT)
  6. German Federal Ministry of Education and Research [BMBF 01EO1503]
  7. Deutsche Forschungsgemeinschaft [ZA 639/4-1, JU 2735/2-1]

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Novel analysis of platelet and megakaryocyte transcriptome revealed high similarity between their transcriptomes, with redistribution of mRNAs upon platelet shedding from megakaryocytes. A prediction model based on protein function, transcript level and (peri)nuclear localization estimated the achievable proteome of about 10 k proteins, with identification of additional proteins related to thrombosis and platelet disorders. This genome-wide platelet transcriptome provides a valuable resource for studying the roles of unknown platelet proteins in health and disease.
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 similar to 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.

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