Journal article
Deciphering the rules by which 5 '-UTR sequences affect protein expression in yeast
Proceedings of the National Academy of Sciences of the United States of America, Vol.110(30), pp.E2792-E2801
Jul/2013
Abstract
The 5'-untranslated region (5'-UTR) of mRNAs contains elements that affect expression, yet the rules by which these regions exert their effect are poorly understood. Here, we studied the impact of 5'-UTR sequences on protein levels in yeast, by constructing a large-scale library of mutants that differ only in the 10 bp preceding the translational start site of a fluorescent reporter. Using a high-throughput sequencing strategy, we obtained highly accurate measurements of protein abundance for over 2,000 unique sequence variants. The resulting pool spanned an approximately sevenfold range of protein levels, demonstrating the powerful consequences of sequence manipulations of even 1-10 nucleotides immediately upstream of the start codon. We devised computational models that predicted over 70% of the measured expression variability in held-out sequence variants. Notably, a combined model of the most prominent features successfully explained protein abundance in an additional, independently constructed library, whose nucleotide composition differed greatly from the library used to parameterize the model. Our analysis reveals the dominant contribution of the start codon context at positions -3 to -1, mRNA secondary structure, and out-of-frame upstream AUGs (uAUGs) to phenotypic diversity, thereby advancing our understanding of how protein levels are modulated by 5'-UTR sequences, and paving the way toward predictably tuning protein expression through manipulations of 5'-UTRs.
Details
- Title
- Deciphering the rules by which 5 '-UTR sequences affect protein expression in yeast
- Creators
- Shlomi Dvir (null) - The Weizmann Institute of ScienceLars Velten (null)Eilon Sharon (null) - The Weizmann Institute of ScienceDanny Zeevi (null) - The Weizmann Institute of ScienceLucas B. Carey (null)Adina Weinberger (null) - 972WIS_INST___83Eran Segal (null) - 972WIS_INST___83
- Resource Type
- Journal article
- Publication Details
- Proceedings of the National Academy of Sciences of the United States of America, Vol.110(30), pp.E2792-E2801; Jul/2013
- Number of pages
- 10
- Language
- English
- DOI
- https://doi.org/10.1073/pnas.1222534110
- Grant note
- US National Institutes of Health (NIH) [R01-HG004361]We thank S. Lubliner for performing nucleosome occupancy predictions and Y. Kalma for experimental guidance. This work was supported by grant R01-HG004361 from the US National Institutes of Health (NIH) to E. Segal._ALMAME_DELIMITER_
- Record Identifier
- 993267980803596
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