- 1 Epidemic simulations
- 2 Genetic studies
Agent Based Model of the infection spread within a small population of Guinea pigs, dependent on temperature and humidity conditions of the surroundings
Synonymous codons do not occur at equal frequencies. Codon usage and codon bias have been extensively studied. However, the sequential order in which synonymous codons appear within a gene has not been studied until now. Here we describe an in silico method, which is the first attempt to tackle this problem: to what extent this sequential order is unique, and to what extent the succession of synonymous codons is important. This method, which we called Intragenic, Stochastic Synonymous Codon Occurrence Replacement (ISSCOR), generates, by a Monte Carlo approach, a set of genes which code for the same amino acid sequence, and display the same codon usage, but have random permutations of the synonymous codons, and therefore different sequential codon orders from the original gene. We analyze the complete genome of the bacterium Helicobacter pylori (containing 1574 protein coding genes), and show by various, alignment-free computational methods (e.g., frequency distribution of codon-pairs, as well as that of nucleotide bigrams in codon-pairs), that: (i) not only the succession of adjacent synonymous codons is far from random, but also, which is totally unexpected, the occurrences of non-adjacent synonymous codon-pairs are highly constrained, at strikingly long distances of dozens of nucleotides; (ii) the statistical deviations from the random synonymous codon order are overwhelming; and (iii) the pattern of nucleotide bigrams in codon-pairs can be used in a novel way for characterizing and comparing genes and genomes. Our results demonstrate that the sequential order of synonymous codons within a gene must be under a strong selective pressure, which is superimposed on the classical codon usage. This new dimension can be measured by the ISSCOR method, which is simple, robust, and should be useful for comparative and functional genomics.