eLife · 2020 · 68 citations · 66 references
Life SciencesGeneticsMolecular BiologyGenomicsProteomicsStem Cell BiologyDisease Susceptibility LociProteomic HeterogeneityProteomic ProfilingProteomics Data IntegrationQuantitative ProteomicsStem Cell GenomicsHuman Induced Pluripotent Stem Cell ModelsInduced Pluripotent Stem CellsProtein Abundance AnalysisProtein Abundance ProfilingProtein Expression ProfilingProtein Quantitative Trait LociProteomic Data AnalysisTranscriptome Profiling
Human disease phenotypes are driven primarily by alterations in protein expression and/or function. To date, relatively little is known about the variability of the human proteome in populations and how this relates to variability in mRNA expression and to disease loci. Here, we present the first comprehensive proteomic analysis of human induced pluripotent stem cells (iPSC), a key cell type for disease modelling, analysing 202 iPSC lines derived from 151 donors, with integrated transcriptome and genomic sequence data from the same lines. We characterised the major genetic and non-genetic determinants of proteome variation across iPSC lines and assessed key regulatory mechanisms affecting variation in protein abundance. We identified 654 protein quantitative trait loci (pQTLs) in iPSCs, including disease-linked variants in protein-coding sequences and variants with trans regulatory effects. These include pQTL linked to GWAS variants that cannot be detected at the mRNA level, highlighting the utility of dissecting pQTL at peptide level resolution.
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