Monte Carlo simulation and statistical analysis of genetic information coding

Abstract

The rules that specify how the information contained in DNA codes amino acids, is called "the genetic code". Using a simplified version of the Penna nodel, we are using computer simulations to investigate the importance of the genetic code and the number of amino acids in Nature on population dynamics. We find that the genetic code is not a random pairing of codons to amino acids and the number of amino acids in Nature is an optimum under mutations.

A Statistical Analysis of the Robustness of Alternate Genetic Coding Tables

“…A different explanation, in the light of still ongoing codon reassignments, could equally well be that the genetic codes are still changing and even possibly, evolving. Our hypothesis is more in line with the latter explanation, where the standard code was quite possibly the first optimal scheme reached by natural selection, but that it is still evolving, both reassigning certain codons, as well as expanding the amount of information contained by the table to the optimal number calculated for this coding table, 22 [5,7,8,9,10]. However such hypotheses need to be further tested after additional parameters such as the changeability have been included in the calculations.…”

“…A previous study [8] had studied how an in silico population survived over generations, by calculating the probability of “survival” upon random mutations of an essential gene – the so-called “human cytokine” gene – where a mutation that renders the protein non-functional resulted in death of the organism. The results in that study were rather interesting, showing that the optimum number of amino acids that could be encoded by the coding table that resulted in optimum survival of the population was indeed 22, rather than the 20 amino acids normally found in the Universal Coding Table (Figure 1, [8]).…”

“…The results in that study were rather interesting, showing that the optimum number of amino acids that could be encoded by the coding table that resulted in optimum survival of the population was indeed 22, rather than the 20 amino acids normally found in the Universal Coding Table (Figure 1, [8]).…”

“…This is based on previous reports that a lineage of organisms where mutations result in chemically conserved amino acid substitutions may actually have higher survivability as compared to those with a less conservative code [5,6], and according to the error-minimization hypotheses, the universal or standard genetic code has evolved an inverse relationship between the severity and frequency of these alterations [5,7]. We have previously used this model to show the optimal number of amino acids that could be encoded by 64 codons without affecting survivability of populations due to deleterious mutations [8]. In this initial set of analyses, we make two simplified assumptions: first of all, we assumed that nucleotide substitutions occur at similar frequencies (current work is integrating unequal substitution rates; unpublished data).…”

“…Our analysis is based on the fundamental assumption that if the gene being analyzed is coding for an essential component of the cells in that organism, such as integrity, metabolism, or replication of DNA, it becomes very important that the gene remain functional in order for the organism to survive. The underlying assumption is that the mutations which render this particular gene completely inactive would mean that the individual would not “survive” [8]. Thus, over a number of generations, we could analyze what the survivability outcome is with respect to the entire population – since the mutation is considered in the light of the particular coding table analyzed, the better the survivability, the more robust the coding table (for details, see Methods).…”