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Variation and Genetic Control of Protein Abundance in Humans

Gene expression differs among both 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 analyzed extensively in human populations(1–5), our knowledge is limited regarding the...

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Detalles Bibliográficos
Autores principales: Wu, Linfeng, Candille, Sophie I, Choi, Yoonha, Xie, Dan, Li-Pook-Than, Jennifer, Tang, Hua, Snyder, Michael
Formato: Online Artículo Texto
Lenguaje:English
Publicado: 2013
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3789121/
https://www.ncbi.nlm.nih.gov/pubmed/23676674
http://dx.doi.org/10.1038/nature12223
Descripción
Sumario:Gene expression differs among both 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 analyzed extensively in human populations(1–5), our knowledge is limited regarding the differences in human protein abundance and their genetic basis. Variation in mRNA expression is not a perfect surrogate for protein expression because the latter is influenced by a battery of post-transcriptional regulatory mechanisms, and, empirically, the correlation between protein and mRNA levels is generally modest(6,7). Here we used isobaric tandem mass tag (TMT)-based quantitative mass spectrometry to determine relative protein levels of 5953 genes in lymphoblastoid cell lines (LCLs) from 95 diverse individuals genotyped in the HapMap Project(8,9). 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 co-vary 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 which, when integrated with DNA variation and transcriptome information, adds a new dimension to the characterization of gene expression regulation.