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Integrative analysis of RNA, translation and protein levels reveals distinct regulatory variation across humans
Open accessPreprint — published as 10.1101/gr.193342.115 · Paper page
Abstract
Elucidating the consequences of genetic differences between humans is essential for understanding phenotypic diversity and personalized medicine. Although variation in RNA levels, transcription factor binding and chromatin have been explored, little is known about global variation in translation and its genetic determinants. We used ribosome profiling, RNA sequencing, and mass spectrometry to perform an integrated analysis in lymphoblastoid cell lines from a diverse group of individuals. We find significant differences in RNA, translation, and protein levels suggesting diverse mechanisms of personalized gene expression control. Combined analysis of RNA expression and ribosome occupancy improves the identification of individual protein level differences. Finally, we identify genetic differences that specifically modulate ribosome occupancy - many of these differences lie close to start codons and upstream ORFs. Our results reveal a new level of gene expression variation among humans and indicate that genetic variants can cause changes in protein levels through effects on translation.
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Cites
Global quantification of mammalian gene expression control
Schwanhäusser, B., Busse, D., Li, N., Dittmar, G., Schuchhardt, J., Wolf, J., Chen, W., & Selbach, M. (2011) · Nature · doi:10.1038/nature10098 · Cited by 6,566
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Metadata
- Authors
- Cenik, C., Sarinay Cenik, E., Byeon, G. W., Grubert, F., Candille, S. I., Spacek, D., Alsallakh, B., Tilgner, H., Araya, C. L., Tang, H., Ricci, E., & Snyder, M. P.
- Affiliations
- Stanford Medicine (US)
- TU Wien (AT)
- Inserm (FR)
- Corresponding author
- Snyder, Michael P
- ORCID
- Venue
- Genome Research
- Publisher
- openRxiv
- Published
- 2015-04-26
- Volume
- 25
- Issue
- 11
- Pages
- 1610-1621
- ISSN
- 1088-9051 (ISSN-L)
- PMC
- PMC4617958
- OpenAlex
- W1906706885
- Cited by
- 208
- References
- 1
- Citations by year
- 2026: 13 · 2025: 14 · 2024: 23 · 2023: 14 · 2022: 20 · 2021: 28 · 2020: 16 · 2019: 22 · 2018: 23 · 2017: 14 · 2016: 20 · 2015: 1
- Type
- posted content
- Language
- en
- Open access
- hybrid
- doi.org
- Licence
- other-oa
- Locations
- Genome Research (publishedVersion, other-oa)
- bioRxiv (Cold Spring Harbor Laboratory) (acceptedVersion, cc-by-nc-nd)
- Europe PMC (PubMed Central) (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- The Journal of the American Medical Association (JAMA) Network (American Medical Association) (submittedVersion, cc-by-nc-nd)
- eScholarship@UMassChan (submittedVersion, cc-by)
- HAL (submittedVersion, other-oa)
- Funders
- Georgia Clinical and Translational Science Alliance
- Child Health Research Foundation (UL1TR000093)
- National Institutes of Health (UL1TR000093, UL1TR001085, GM07305907, NIH NHGRI T32HG000044)
- Genentech
- Child Health Research Institute, University of Nebraska Medical Center (UL1TR000093)
- National Heart, Lung, and Blood Institute (R01HL122887)
- National Human Genome Research Institute (U54HG006996, HG006996, NIH/NHGRI T32, HG007611, 1U01HG00761101, HG000044, U01HG007611, T32HG000044)
- National Institute of General Medical Sciences (R01GM073059, GM07305907)
- National Center for Advancing Translational Sciences
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › RNA and protein synthesis mechanisms
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › RNA Research and Splicing
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genetic Associations and Epidemiology
- Keywords
- translational regulation, ribosome profiling, ribosome occupancy, protein abundance, genetic variants, lymphoblastoid cell lines, upstream open reading frames, start codon, personalized medicine, phenotypic diversity
- MeSH terms
- Chromatin, Gene Expression Regulation, Humans, Ribosomes, RNA, RNA, Messenger, Protein Biosynthesis, Sequence Alignment, Sequence Analysis, RNA, Polymorphism, Single Nucleotide, Gene Expression Profiling, Quantitative Trait Loci, Proteomics
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