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Genome-wide Quantification of Translation in Budding Yeast by Ribosome Profiling
Published on: December 21, 2017
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Streamlined and sensitive mono- and di-ribosome profiling in yeast and human cells
Lucas Ferguson1,2, Heather E Upton3, Sydney C Pimentel3
1Department of Molecular and Cell Biology, University of California, Berkeley, CA, USA. lucas_ferguson@berkeley.edu.
Nature Methods
|October 2, 2023
Summary
This study introduces a new ribosome profiling method using P1 nuclease and a streamlined protocol. This approach reduces bias and technical challenges, providing a richer translatome profile for studying translation regulation.
Area of Science:
- Molecular Biology
- Genomics
- Biochemistry
Background:
- Ribosome profiling is a powerful technique for surveying translation and ribosome occupancy across the transcriptome.
- Current methods for generating ribosome footprints are technically demanding and prone to biases.
- These biases can distort the accurate representation of physiological ribosome occupancy.
Purpose of the Study:
- To develop an optimized ribosome profiling method that overcomes technical challenges and reduces bias.
- To improve the accuracy and richness of translatome profiling.
- To provide a more reliable tool for studying translation regulation and dynamics.
Main Methods:
- Utilized P1 nuclease instead of RNase I for generating ribosome footprints.
- Replaced traditional RNA ligation with an ordered two-template relay protocol for library preparation.
- Incorporated adaptors via reverse transcription in a single-tube protocol.
Main Results:
- The new method significantly reduced sequence bias compared to existing protocols.
- Enhanced enrichment of ribosome footprints relative to ribosomal RNA was observed.
- P1 nuclease preserved distinct ribosome complexes, offering insights into translation initiation, stalling, and termination in yeast and human systems.
Conclusions:
- The optimized ribosome footprint generation and capture methods offer a richer translatome profile.
- This streamlined approach requires lower input and presents fewer technical challenges.
- The improved method facilitates a more comprehensive understanding of translational regulation.

