Study / S4S12Z0PF2023-05-25

Unraveling the influences of sequence and position on yeast uORF activity using massively parallel reporter systems and machine learning

Gemma E May, Christina Akirtava, Matthew Agar-Johnson, Jelena Micic, John Woolford et al.

About this study

Upstream open-reading frames (uORFs) are potent cis-acting regulators of mRNA translation and nonsense-mediated decay (NMD). While both AUG- and non-AUG initiated uORFs are ubiquitous in ribosome profiling studies, few uORFs have been experimentally tested. Consequently, the relative influences of sequence, structural, and positional features on uORF activity have not been determined. We quantified thousands of yeast uORFs using massively parallel reporter assays in wildtype and ∆upf1 yeast. While nearly all AUG uORFs were robust repressors, most non-AUG uORFs had relatively weak impacts on expression. Machine learning regression modeling revealed that both uORF sequences and locations within transcript leaders predict their effect on gene expression. Indeed, alternative transcription start sites highly influenced uORF activity. These results define the scope of natural uORF activity, identify features associated with translational repression and NMD, and suggest that the locations of uORFs in transcript leaders are nearly as predictive as uORF sequences.

Full author list & citation

Gemma E May, Christina Akirtava, Matthew Agar-Johnson, Jelena Micic, John Woolford, Joel McManus. Unraveling the influences of sequence and position on yeast uORF activity using massively parallel reporter systems and machine learning. 2023-05-25. https://doi.org/10.7554/eLife.69611

Experiments 2

E2W75NCEV

FACS-uORF protein-expression activity in yeast

An episomal dual-fluorescence reporter MPRA compared natural yeast transcript leaders containing individual uORFs with matched AAG start-codon mutants. YFP/mCherry fluorescence was measured by sorting cells into nine FACS bins, and targeted sequencing of each bin was used to estimate protein-expression effects in BY4741 wildtype and upf1Δ yeast.

Sort-Seq / Flow-Seq MPRABudding yeast
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E7BCT5PVF

PoLib-seq ribosome loading of yeast uORFs

A polysome-library sequencing MPRA measured how natural yeast transcript leaders and matched AAG start-codon mutants distribute between translating and non-translating sucrose-gradient fractions. The processed table reports uORF effects on ribosome loading in wildtype BY4741 yeast.

5' UTR / Translation Efficiency MPRA (MPTA)Budding yeast
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Raw source data 3 files

Original supplemental and deposited inputs retained for this study. Download files individually or together as a ZIP; nested folders are preserved. Source reuse terms apply, and sequencing reads may be omitted.

Download all 3 files (ZIP)bioproject_PRJNA721222.xmlelife-69611-supp1-v2.xlsxsra_PRJNA721222_runinfo.csv

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