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Ribosome Profiling

Ribosome Profiling

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.
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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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From DNA to Protein

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The flow of genetic information in cells from DNA to mRNA to protein is described by the central dogma, which states that genes specify the sequence of mRNAs, which in turn specify the sequence of amino acids making up all proteins. The decoding of one molecule to another is performed by specific proteins and RNAs. Because the information stored in DNA is so central to cellular function, it makes intuitive sense that the cell would make mRNA copies of this information for protein synthesis...

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mRNA Stability and Gene Expression

The structure and stability of mRNA molecules regulates gene expression, as mRNAs are a key step in the pathway from gene to protein. In eukaryotes, the half-life of mRNA varies from a few minutes up to several days. mRNA stability is essential in growth and development. The absence of the proteins regulating its stability, such as tristetraprolin in mice, can cause systemic issues, including bone marrow overgrowth, inflammation, and autoimmunity.
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mRNA Stability and Gene Expression

mRNA Stability and Gene Expression

The structure and stability of mRNA molecules regulates gene expression, as mRNAs are a key step in the pathway from gene to protein. In eukaryotes, the half-life of mRNA varies from a few minutes up to several days. mRNA stability is essential in growth and development. The absence of the proteins regulating its stability, such as tristetraprolin in mice, can cause systemic issues, including bone marrow overgrowth, inflammation, and autoimmunity.
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Conservation of Protein Domains Over Different Proteins

Conservation of Protein Domains Over Different Proteins

Protein domains are small structurally independent units that are part of a single amino acid chain. Although these domains are often structurally independent, they may rely on synergistic effects to perform their functions as part of a larger protein. Protein domains may be conserved within the same organism, as well as across different organisms.
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Related Experiment Video

Updated: Jun 4, 2026

De novo Identification of Actively Translated Open Reading Frames with Ribosome Profiling Data

De novo Identification of Actively Translated Open Reading Frames with Ribosome Profiling Data

Published on: February 18, 2022

Codon usage variability determines the correlation between proteome and transcriptome fold changes.

Roberto Olivares-Hernández¹, Sergio Bordel, Jens Nielsen

¹Systems Biology, Department of Chemical and Biological Engineering, Chalmers University of Technology, Kemivägen 10, Gothenburg, Sweden.

BMC Systems Biology

|March 1, 2011

Summary

This summary is machine-generated.

Gene codon frequencies significantly explain the weak correlation between protein and mRNA levels. This finding highlights the role of codon composition in regulating protein translation, beyond just mRNA availability.

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De novo Identification of Actively Translated Open Reading Frames with Ribosome Profiling Data

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Combined Nucleotide and Protein Extractions in Caenorhabditis elegans

Combined Nucleotide and Protein Extractions in Caenorhabditis elegans

Published on: March 17, 2019

Area of Science:

Molecular Biology
Genomics
Systems Biology

Background:

High-throughput methods enable proteome-transcriptome analysis.
Protein and mRNA levels show a weak positive correlation, indicating other regulatory factors.
Ribosome and tRNA concentrations are known to influence protein levels.

Purpose of the Study:

Investigate variables affecting protein translation.
Analyze integrated omics data (genomic, transcriptome, proteome).
Determine the impact of gene codon frequencies on protein-mRNA correlation.

Main Methods:

Integrated analysis of omics data.
Utilized Self-Organizing Maps (SOM) for gene clustering based on codon frequencies.
Calculated variance in protein-mRNA correlation within gene clusters.

Main Results:

Identified gene codon frequencies as a key factor explaining variability in protein-mRNA correlation.
Hypothesized that codon frequency influences translation via tRNA binding competition.
Demonstrated that codon composition explains most protein-transcript variability across six cases.

Conclusions:

Gene codon composition is a major determinant of protein and mRNA level correlations.
Understanding codon usage is crucial for deciphering protein translation regulation.
Integrated omics analysis reveals complex regulatory mechanisms.