Search research articles

ABOUT JoVE

Overview Leadership Blog JoVE Help Center

AUTHORS

Publishing Process Editorial Board Scope & Policies Peer Review FAQ Submit

LIBRARIANS

Testimonials Subscriptions Access Resources Library Advisory Board FAQ

RESEARCH

JoVE Journal Methods Collections JoVE Encyclopedia of Experiments Archive

EDUCATION

JoVE Core JoVE Business JoVE Science Education JoVE Lab Manual Faculty Resource Center Faculty Site

Terms & Conditions of Use

Search research articles

Related Experiment Videos

Predicting gene expression level from codon usage bias.

Ian Henry, Paul M Sharp

Molecular Biology and Evolution

|October 14, 2006

Summary

This summary is machine-generated.

Related Concept Videos

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by

Same author

Plasma proteomics stratification identifies phospholamban R14del carriers at risk for disease progression.

Cardiovascular research·2026

Same author

Topological Data Analysis for Unsupervised Feature Selection in Large Scale Spatial Omics Data Sets.

Bulletin of mathematical biology·2026

Same author

Atomic-scale observation of vacancy ordering in magnetite nanoparticles.

Ultramicroscopy·2026

Same author

Targeted Chromosomal Sequencing of Wild Bonobos Identifies a Genetically Distinct Subpopulation East of the Lomami River.

bioRxiv : the preprint server for biology·2026

Same author

A multi-omics microbiome signature is associated with the benefits of gastric bypass surgery and is differentiated from diet induced weight loss through 2 years of follow-up.

Mucosal immunology·2025

Same author

Plasmodium falciparum CyRPA Glycan Binding Does Not Explain Adaptation to Humans.

Genome biology and evolution·2025

Same journal

Population Epigenetics: Deciphering DNA Methylation Diversity and its Implications for Health, Disease, and Evolution.

Molecular biology and evolution·2026

Same journal

Genomic signature of repeated transitions to diurnality in spiders.

Molecular biology and evolution·2026

Same journal

Phylogenomic blind spots: The limits of UCE and BUSCO loci in the presence of gene flow.

Molecular biology and evolution·2026

Same journal

seqLens: Optimizing Language Models for Genomic Predictions.

Molecular biology and evolution·2026

Same journal

The transcriptional and translational outcomes for pseudogenes in bacterial endosymbionts.

Molecular biology and evolution·2026

Same journal

800 million years of co-evolution in the green plant lineage - the case of LEUNIG and SEUSS transcriptional co-regulators.

Molecular biology and evolution·2026

See all related articles

The expression measure (E(g)) for gene expression prediction from codon usage bias has limitations. This study identifies issues with E(g) and proposes a refined approach for analyzing gene expression levels.

Area of Science:

Genomics
Bioinformatics
Molecular Biology

Background:

The expression measure (E(g)) is a statistic used to predict gene expression levels based on codon usage bias in prokaryotic genomes.
E(g) has been widely applied for analyzing prokaryotic genome sequences.

Discussion:

The formulation of E(g) leads to a weak correlation between predicted and actual expression levels, particularly for highly expressed genes.
In certain species, highly expressed genes lack unusual codon usage, rendering E(g) an unreliable predictor.

Key Insights:

Identified limitations in the E(g) statistic for accurately predicting gene expression from codon usage bias.
Demonstrated that strong codon usage bias does not always correlate with high gene expression.
Highlighted species-specific variations where codon usage is not a reliable indicator of expression levels.

Related Experiment Videos

Outlook:

Developed a straightforward method to first detect selected codon usage bias in a genome.
Proposed assessing the strength of codon usage bias in genes to infer their likely expression levels.
Illustrated the refined approach using an analysis of Shewanella oneidensis.