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October 14, 2024Genome biology17 citationsOpen Access

The ribosome profiling landscape of yeast reveals a high diversity in pervasive translation

CPChris PapadopoulosHAHugo ArbèsDCDavid Cornu

Key Result

Analysis of the yeast ribosome profiling landscape revealed a high diversity of pervasive translation signals in noncoding regions, identifying 239 microproteins from noncoding ORFs.

Structured PICO

P
Population
Analysis of 54 high-quality ribosome profiling datasets from wild-type S. cerevisiae strains to investigate pervasive translation patterns.
E
Exposure
Ribosome profiling (Ribo-Seq) landscape analysis and mass spectrometry (under standard conditions or proteasome inhibition)
O
Outcome
Diversity of translation patterns and identification of microproteins originating from noncoding ORFssurrogate

The study maps the ribosome profiling landscape of yeast, revealing high diversity in pervasive translation and identifying hundreds of novel microproteins from noncoding ORFs.

Limitations

  • Detecting pervasively translated ORFs is challenging due to their short size and typically low expression levels.
  • Caution is warranted for accurate estimation of the frequency of translation of lowly expressed short noncoding ORFs across datasets.
  • The relationship between the quantity of a microprotein and its capacity to ensure a biological role requires further investigation.

Abstract

BACKGROUND: Pervasive translation is a widespread phenomenon that plays a critical role in the emergence of novel microproteins, but the diversity of translation patterns contributing to their generation remains unclear. Based on 54 ribosome profiling (Ribo-Seq) datasets, we investigated the yeast Ribo-Seq landscape using a representation framework that allows the comprehensive inventory and classification of the entire diversity of Ribo-Seq signals, including non-canonical ones. RESULTS: We show that if coding regions occupy specific areas of the Ribo-Seq landscape, noncoding regions encompass a wide diversity of Ribo-Seq signals and, conversely, populate the entire landscape. Our results show that pervasive translation can, nevertheless, be associated with high specificity, with 1055 noncoding ORFs exhibiting canonical Ribo-Seq signals. Using mass spectrometry under standard conditions or proteasome inhibition with an in-house analysis protocol, we report 239 microproteins originating from noncoding ORFs that display canonical but also non-canonical Ribo-Seq signals. Each condition yields dozens of additional microprotein candidates with comparable translation properties, suggesting a larger population of volatile microproteins that are challenging to detect. Our findings suggest that non-canonical translation signals may harbor valuable information and underscore the significance of considering them in proteogenomic studies. Finally, we show that the translation outcome of a noncoding ORF is primarily determined by the initiating codon and the codon distribution in its two alternative frames, rather than features indicative of functionality. CONCLUSION: Our results enable us to propose a topology of a species' Ribo-Seq landscape, opening the way to comparative analyses of this translation landscape under different conditions.

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Cite This Study

Papadopoulos et al. (2024) studied Pervasive translation. Ribosome profiling landscape analysis was evaluated on Identification of Ribo-Seq signals and microproteins from noncoding ORFs. Analysis of the yeast ribosome profiling landscape revealed a high diversity of pervasive translation signals in noncoding regions, identifying 239 microproteins from noncoding ORFs.

synapsesocial.com/papers/6a63780347366de40a287a44https://doi.org/10.1186/s13059-024-03403-7
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