Towards a Reference Human Platelet Transcriptome: Evaluation Of Inter-Individual Correlations and Its Relationship With a Platelet Proteome

Next generation sequencing of RNA (RNA-seq) is an emerging technology that has so far been used successfully to profile the transcriptomes of several cell types and cell states. For the platelet transcriptome, RNA-seq descriptions exist for only a few subjects. Additionally, there have been no studies of the same individual’s transcriptome using two different technologies. As such, it has been unclear how well platelet transcriptomes correlate among different donors or across different RNA platforms, and what the transcriptomes’ relationship is with the platelet proteome.

We generated RNA-seq profiles of the long RNA transcriptomes from the platelets of 10 healthy young males (5 white and 5 black). In addition to RNA-seq, we profiled the platelet messenger RNAs of the same 10 individuals using the Affymetrix GeneChip System. We observed that the abundance of platelet mRNA transcripts was highly correlated across the 10 individuals, a finding that was independent of race and of the employed technology. Additionally, our RNA-seq data showed that these high inter-individual correlations extend beyond mRNAs to several categories of non-coding RNAs. However, there was a notable exception: the category of pseudogenes exhibited a clear difference in expression by race.

Comparison of our mRNA signatures with the only publicly available quantitative platelet proteome data showed that most (87.5%) identified platelet proteins had a detectable corresponding mRNA. Interestingly, there was also a high number of mRNAs that were present in the transcriptomes of all 10 individuals but had no representation in the proteome. Spearman correlation of the relative abundances for those platelet genes that were represented by both an mRNA and a protein, revealed an unexpectedly weak correlation between the transcriptome and the proteome. Further analysis of the overlapping and non-overlapping platelet mRNAs and proteins identified groups of genes with very distinct characteristics. Gene Ontology analysis of the respective gene identifiers revealed that the gene groups corresponded to distinct cellular processes, an interesting finding that provides novel insights for platelet biology.

The very high inter-individual correlations of the transcriptome signatures across 10 different subjects representing two races together with the results of our analyses indicate that it is feasible to assemble a platelet mRNA-ome that can serve as a reference for future platelet transcriptomic studies of human health and disease.