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Variation and genetic control of protein abundance in humans
Open accessAbstract
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 populations, 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 modest. 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 Project. 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.
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“Yet, in contrast to comparative work, there are few reports of QTLs associated with protein levels (pQTLs) in humans (15-17).”
From Impact of regulatory variation from RNA to protein (2015) · cites this paper as [15]
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“Our observation that many SNPs identified as eQTLs are not associated with differences in protein levels is consistent with the notion that, across species, protein levels diverge less than transcript levels (12-17).”
From Impact of regulatory variation from RNA to protein (2015) · cites this paper as [15]
In the citing paper
“An analysis of individuals genotyped in the HapMap project reported that almost two-thirds of 185 observed cis-acting pQTLs were not found in a complementary analysis of the RNA89.”
From Decoding neuroproteomics: integrating the genome, translatome and functional anatomy (2014) · cites this paper as [89]
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Metadata
- Authors
- Wu, L., Candille, S. I., Choi, Y., Xie, D., Jiang, L., Li-Pook-Than, J., Tang, H., & Snyder, M.
- Affiliations
- Stanford Medicine (US)
- Corresponding author
- Tang, Hua
- Snyder, Michael
- Venue
- Nature
- Published
- 2013-05-15
- Volume
- 499
- Issue
- 7456
- Pages
- 79-82
- ISSN
- 0028-0836 (ISSN-L)
- 1476-4687
- PMC
- PMC3789121
- OpenAlex
- W2073109785
- Cited by
- 364
- References
- 25
- Citations by year
- 2026: 6 · 2025: 16 · 2024: 25 · 2023: 18 · 2022: 26 · 2021: 25 · 2020: 21 · 2019: 37 · 2018: 31 · 2017: 24 · 2016: 31 · 2015: 46 · 2014: 44 · 2013: 14
- FWCI
- 29.86
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Licence
- www.springer.com/tdm (tdm)
- Locations
- Nature (publishedVersion)
- PubMed (publishedVersion)
- PubMed Central (acceptedVersion)
- RePEc: Research Papers in Economics (submittedVersion)
- Funders
- National Institutes of Health
- National Heart, Lung, and Blood Institute (U01HL107393)
- National Human Genome Research Institute (P50HG002357)
- National Institute of General Medical Sciences (R01GM073059)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genetic Associations and Epidemiology
- Physical Sciences › Chemistry › Spectroscopy › Advanced Proteomics Techniques and Applications
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genetic Mapping and Diversity in Plants and Animals
- Keywords
- protein abundance, protein quantitative trait loci, cis-pQTL, interindividual variability, heritability, post-transcriptional regulation, mRNA-protein correlation, gene expression regulation, lymphoblastoid cell lines, sex differences, population variation, HapMap
- MeSH terms
- Cell Line, Ethnicity, Female, Gene Expression Regulation, Genotype, Humans, Male, Phenotype, RNA, Messenger, Mass Spectrometry, Protein Biosynthesis, Genetic Variation, Proteome, Gene Expression Profiling, Quantitative Trait Loci, Proteomics, Transcriptome, HapMap Project
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