Study of the genetic code adaptability by means of a genetic algorithm

We used simulated evolution to study the adaptability level of the canonical genetic code. An adapted genetic algorithm (GA) searches for optimal hypothetical codes. Adaptability is measured as the average variation of the hydrophobicity that the encoded amino acids undergo when errors or mutations...

Full description

Saved in:
Bibliographic Details
Published in:Journal of theoretical biology 2010-06, Vol.264 (3), p.854-865
Main Authors: Santos, José, Monteagudo, Ángel
Format: Article
Language:English
Subjects:
Adaptation, Physiological - genetics
Algorithms
Amino Acids - genetics
Codon - genetics
Computer Simulation
Error-minimization hypothesis
Evolution, Molecular
Genetic algorithms
Genetic Code - genetics
Genetic code evolution
Genetic code theories
Models, Genetic
Mutation
Citations: Items that this one cites
Items that cite this one
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:We used simulated evolution to study the adaptability level of the canonical genetic code. An adapted genetic algorithm (GA) searches for optimal hypothetical codes. Adaptability is measured as the average variation of the hydrophobicity that the encoded amino acids undergo when errors or mutations are present in the codons of the hypothetical codes. Different types of mutations and point mutation rates that depend on codon base number are considered in this study. Previous works have used statistical approaches based on randomly generated alternative codes or have used local search techniques to determine an optimum value. In this work, we emphasize what can be concluded from the use of simulated evolution considering the results of previous works. The GA provides more information about the difficulty of the evolution of codes, without contradicting previous studies using statistical or engineering approaches. The GA also shows that, within the coevolution theory, the third base clearly improves the adaptability of the current genetic code.
ISSN:0022-5193
1095-8541
DOI:10.1016/j.jtbi.2010.02.041