Monte Carlo Simulation and Statistical Analysis of the Effect of Coding Table Specificity on Genetic Information Coding

TL;DR

This study uses Monte Carlo simulations inspired by the Penna model to analyze how different genetic coding tables impact population resilience to mutations, revealing that the standard code is not the most mutation-resistant.

Contribution

It introduces a simulation framework to compare the effects of various genetic coding tables on population stability and mutation resilience.

Findings

Standard genetic code is not the most resilient to point mutations.

Different coding tables significantly affect population dynamics.

Simulation results challenge common assumptions about genetic code robustness.

Abstract

We present a computer simulation, which is inspired by Penna model, to help understanding the effect of genetic coding tables on population dynamics. To represent populations we used real and artificial gene sequences in this model. We coded these sequences using different amino acid tables in Nature, the standard table as well as the tables which are used by mithocondria and some eukaryotes. Contrary to common belief we find that the standard code table which is used in most organisms in Nature, does not give the most resilient coding against point mutations.