Variation and genetic control of protein abundance in humans

A large-scale analysis of variation in human protein levels between individuals is performed using mass-spectrometry-based proteomic technology, and a number of protein quantitative trait loci are identified; over 5% of proteins vary by more than 1.5-fold in their expression levels between individuals, and this variation is not always linked to RNA level. Efforts to understand the mechanisms underlying phenotypic variation between individuals have focused mainly on events at the level of RNA and transcription factor binding, and on mapping the genetic loci responsible. Proteins are much closer to phenotypes than RNA but few studies have analysed protein variation on a global level. Here, a large-scale analysis of variation in protein levels between 95 diverse individuals genotyped in the HapMap Project is performed using mass spectrometry-based proteomic technology, and a number of protein quantitative trait loci are identified. Over 5% of proteins vary more than 1.5 fold in their expression levels between individuals, and this variation is not always linked to RNA levels. Gene expression differs among individuals and populations and is thought to be a major determinant of phenotypic variation. Although variation and genetic loci responsible for RNA expression levels have been analysed extensively in human populations1,2,3,4,5, our knowledge is limited regarding the differences in human protein abundance and the genetic basis for this difference. Variation in messenger RNA expression is not a perfect surrogate for protein expression because the latter is influenced by an array of post-transcriptional regulatory mechanisms, and, empirically, the correlation between protein and mRNA levels is generally modest6,7. Here we used isobaric tag-based quantitative mass spectrometry to determine relative protein levels of 5,953 genes in lymphoblastoid cell lines from 95 diverse individuals genotyped in the HapMap Project8,9. We found that protein levels are heritable molecular phenotypes that exhibit considerable variation between individuals, populations and sexes. Levels of specific sets of proteins involved in the same biological process covary among individuals, indicating that these processes are tightly regulated at the protein level. We identified cis-pQTLs (protein quantitative trait loci), including variants not detected by previous transcriptome studies. This study demonstrates the feasibility of high-throughput human proteome quantification that, when integrated with DNA variation and transcriptome information, adds a new dimension to the characterization of gene expression regulation.