Do universal codon-usage patterns minimize the effects of mutation and translation error?

Roberto Marquez^*¹ , Sandra Smit^*² and Rob Knight²

¹Department of Computer Science, New Mexico State University, MSC CS, Las Cruces, NM 88003, USA

²Department of Chemistry and Biochemistry, University of Colorado, Boulder, CO 80309, USA

author email corresponding author email* Contributed equally

Genome Biology 2005, 6:R91doi:10.1186/gb-2005-6-11-r91


Published:	19 October 2005

Subject areas: Evolution, Molecular biology, Bioinformatics

Abstract

Background

Do species use codons that reduce the impact of errors in translation or replication? The genetic code is arranged in a way that minimizes errors, defined as the sum of the differences in amino-acid properties caused by single-base changes from each codon to each other codon. However, the extent to which organisms optimize the genetic messages written in this code has been far less studied. We tested whether codon and amino-acid usages from 457 bacteria, 264 eukaryotes, and 33 archaea minimize errors compared to random usages, and whether changes in genome G+C content influence these error values.

Results

We tested the hypotheses that organisms choose their codon usage to minimize errors, and that the large observed variation in G+C content in coding sequences, but the low variation in G+U or G+A content, is due to differences in the effects of variation along these axes on the error value. Surprisingly, the biological distribution of error values has far lower variance than randomized error values, but error values of actual codon and amino-acid usages are actually greater than would be expected by chance.

Conclusion

These unexpected findings suggest that selection against translation error has not produced codon or amino-acid usages that minimize the effects of errors, and that even messages with very different nucleotide compositions somehow maintain a relatively constant error value. They raise the question: why do all known organisms use highly error-minimizing genetic codes, but fail to minimize the errors in the mRNA messages they encode?