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Related Concept Videos

Ribosomes01:27

Ribosomes

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Ribosomes translate genetic information encoded by messenger RNA (mRNA) into proteins. Both prokaryotic and eukaryotic cells have ribosomes. Cells that synthesize large quantities of protein—such as secretory cells in the human pancreas—can contain millions of ribosomes.
Ribosome Structure and Assembly
Ribosomes are composed of ribosomal RNA (rRNA) and proteins. In eukaryotes, rRNA is transcribed from genes in the nucleolus—a part of the nucleus that specializes in ribosome...
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Ribosomes01:27

Ribosomes

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Ribosomes translate genetic information encoded by messenger RNA (mRNA) into proteins. Both prokaryotic and eukaryotic cells have ribosomes. Cells that synthesize large quantities of protein—such as secretory cells in the human pancreas—can contain millions of ribosomes.
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Ribosome Profiling02:24

Ribosome Profiling

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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.
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Ribosomal RNA Synthesis02:53

Ribosomal RNA Synthesis

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Ribosome synthesis is a highly complex and coordinated process involving more than 200 assembly factors. The synthesis and processing of ribosomal components occurs not only in the nucleolus but also in the nucleoplasm and the cytoplasm of eukaryotic cells.
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Chromatin Position Affects Gene Expression02:35

Chromatin Position Affects Gene Expression

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Chromatin is the massive complex of DNA and proteins packaged inside the nucleus. The complexity of chromatin folding and how it is packaged inside the nucleus greatly influences  access to genetic information. Generally, the nucleus' periphery is considered transcriptionally repressive, while the cell's interior is considered a transcriptionally active area. 
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Global Identification of Co-Translational Interaction Networks by Selective Ribosome Profiling
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Global Identification of Co-Translational Interaction Networks by Selective Ribosome Profiling

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RiboProP: a probabilistic ribosome positioning algorithm for ribosome profiling.

Dengke Zhao1, William D Baez2, Kurt Fredrick3,4

  • 1Interdisciplinary Biophysics Graduate Program, Division of Hematology, The Ohio State University, Columbus, OH, USA.

Bioinformatics (Oxford, England)
|October 11, 2018
PubMed
Summary
This summary is machine-generated.

This study introduces a novel computational method to accurately map ribosome positions on mRNA fragments, overcoming limitations of existing techniques. The new approach mitigates sequence bias from micrococcal nuclease (MNase) for precise ribosome pausing site identification in bacteria.

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Area of Science:

  • Molecular Biology
  • Bioinformatics
  • Genomics

Background:

  • Ribosome profiling is crucial for genome-wide translation studies.
  • Accurate mapping of ribosome-protected fragments is essential for identifying translation dynamics like ribosome pausing.
  • Existing methods struggle with micrococcal nuclease (MNase) sequence bias and low resolution.

Purpose of the Study:

  • To develop a computational method for precise mapping of ribosome-protected fragments.
  • To address the challenges posed by MNase sequence bias in ribosome profiling.
  • To enable accurate identification of ribosome pausing sites at codon resolution in bacteria.

Main Methods:

  • Developed a mathematical model of MNase digestion and ribosome protection.
  • Reconstructed ribosome occupancy profiles using the developed model.
  • Implemented a novel computational approach for fragment mapping.

Main Results:

  • The new method effectively mitigates MNase sequence bias.
  • Accurate identification of ribosome pausing sites at codon resolution was achieved.
  • The computational method reconstructs ribosome occupancy profiles on a per-gene level.

Conclusions:

  • The developed method offers improved accuracy for ribosome profiling in bacteria.
  • This approach is broadly applicable to bacterial ribosome profiling studies requiring codon resolution.
  • The computational tool is available for download and use in relevant research.