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Updated: May 21, 2026

Identifying Amino Acid Overproducers Using Rare-Codon-Rich Markers

Identifying Amino Acid Overproducers Using Rare-Codon-Rich Markers

Published on: June 24, 2019

Translational selection on codon usage in the genus Aspergillus.

Andrés Iriarte¹, Manuel Sanguinetti, Tamara Fernández-Calero

¹Laboratorio de Organización y Evolución del Genoma, Depto. de Ecología y Evolución, Facultad de Ciencias (UDELAR), Iguá 4225, 11400 Montevideo, Uruguay.

|June 30, 2012

Summary

This study analyzes codon usage patterns in eight Aspergillus fungal genomes. Results indicate translational efficiency and accuracy are key evolutionary drivers, with implications for biotechnology.

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Area of Science:

Mycology
Genomics
Molecular Evolution

Background:

Aspergillus is a genus of over 200 fungal species, with many being significant pathogens or economically important.
Previous codon usage analysis in Aspergillus was limited to a single species and a small gene set.

Purpose of the Study:

To investigate codon usage patterns across eight fully sequenced Aspergillus genomes.
To identify the evolutionary pressures shaping codon usage in this fungal genus.
To explore the relationship between codon usage, gene expression, and tRNA availability.

Main Methods:

Comparative genomic analysis of eight Aspergillus species.
Codon usage bias analysis.
Molecular evolutionary rate estimation.
tRNA gene pool characterization.

Main Results:

Translational efficiency and accuracy are identified as major factors influencing codon usage across all studied Aspergillus species.
Highly expressed genes exhibit slower evolution at synonymous sites.
A conserved set of translationally optimal codons was identified.
A strong correlation exists between preferred codons and the copy number of their cognate tRNAs in each genome.

Conclusions:

The findings suggest that selection for translational efficiency and accuracy has been active since the last common ancestor of Aspergillus.
Codon usage patterns are shaped by both evolutionary pressures and the available tRNA pool.
This research has potential applications in heterologous protein expression for biotechnology.