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Related Concept Videos

Ribosome Profiling02:24

Ribosome Profiling

4.0K
Ribosome profiling or ribo-sequencing is a deep sequencing technique that produces a snapshot of active translation in a cell. It selectively sequences the mRNAs protected by ribosomes to get an insight into a cell’s translation landscape at any given point in time.
Applications of ribosome profiling
Ribosome profiling has many applications, including in vivo monitoring of translation inside a particular organ or tissue type and quantifying new protein synthesis levels.
The technique...
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Improving Translational Accuracy02:07

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Base complementarity between the three base pairs of mRNA codon and the tRNA anticodon is not a failsafe mechanism. Inaccuracies can range from a single mismatch to no correct base pairing at all. The free energy difference between the correct and nearly correct base pairs can be as small as 3 kcal/ mol. With complementarity being the only proofreading step, the estimated error frequency would be one wrong amino acid in every 100 amino acids incorporated. However, error frequencies observed in...
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Updated: Dec 29, 2025

RIBO-seq in Bacteria: a Sample Collection and Library Preparation Protocol for NGS Sequencing
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XPRESSyourself: Enhancing, standardizing, and automating ribosome profiling computational analyses yields improved

Jordan A Berg1, Jonathan R Belyeu2, Jeffrey T Morgan1

  • 1Department of Biochemistry, University of Utah, Salt Lake City, Utah, United States of America.

Plos Computational Biology
|February 1, 2020
PubMed
Summary

XPRESSyourself is a new toolkit for analyzing ribosome profiling data, improving protein translation studies. This open-source software standardizes analysis, making complex data more accessible and reproducible for researchers.

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Area of Science:

  • Molecular Biology
  • Bioinformatics
  • Genomics

Background:

  • Ribosome profiling is crucial for understanding protein translation dynamics.
  • Existing computational tools for ribosome profiling data lack standardization and accessibility.
  • This gap hinders efficient and reproducible analysis for researchers.

Purpose of the Study:

  • To introduce XPRESSyourself, an analytical toolkit for ribosome profiling data.
  • To address bottlenecks and standardize analysis procedures for ribosome profiling.
  • To make ribosome profiling data analysis more accessible to both experts and non-experts.

Main Methods:

  • Development of the XPRESSyourself analytical toolkit.
  • Automation and standardization of ribosome profiling data analysis workflows.
  • Demonstration of the toolkit using publicly available ribosome profiling datasets.

Main Results:

  • XPRESSyourself successfully automates and standardizes ribosome profiling analysis.
  • The toolkit decreases time-to-discovery and increases the reproducibility of results.
  • Rapid identification of mechanisms related to neurodegenerative phenotypes and ISRIB's neuroprotective effects was achieved.

Conclusions:

  • XPRESSyourself provides a robust and rapid solution for ribosome profiling data analysis.
  • The toolkit enhances the accessibility and reproducibility of translation regulation measurements.
  • This open-source software promotes wider adoption and advancement in the field.