No accident: genetic codes freeze in error–correcting patterns of the standard genetic code

Abstract

The standard genetic code poses a challenge in understanding the evolution of information processing at a fundamental level of biological organization. Genetic codes are generally coadapted with, or 'frozen' by, the protein-coding genes that they translate, and so cannot easily change by natural selection. Yet the standard code has a significantly non-random pattern that corrects common errors in the transmission of information in protein-coding genes. Because of the freezing effect and for other reasons, this pattern has been proposed not to be due to selection but rather to be incidental to other evolutionary forces or even entirely accidental.We present results from a deterministic population genetic model of code-message coevolution. We explicitly represent the freezing effect of genes on genetic codes and the perturbative effect of changes in genetic codes on genes. We incorporate characteristic patterns of mutation and translational error, namely, transition bias and positional asymmetry, respectively. Repeated selection over small successive changes produces genetic codes that are substantially, but not optimally, error correcting. In particular, our model reproduces the error-correcting patterns of the standard genetic code. Aspects of our model and results may be applicable to the general problem of adaptation to error in other natural information-processing systems.

The information capacity of the genetic code: Is the natural code optimal?

“…that the genetic code co-evolved to a point that it would have been too disruptive to change anymore (Crick, 1968;Sella and Ardell, 2006), so its evolution was stopped prematurely. 2. that it is not completely an accidental code in that it is indeed an error-correcting code better than a large number of competitors (Ardell and Sella, 2002) 3. that at some point in the past the codons were composed of 2 nucleotides only and the third nucleotide was acquired afterwards. This may be the reason why the natural code does not seem to be optimized for 3-codons and that almost all redundancies are in the third position (Sella and Ardell, 1973;Santos and Monteagudo, 2009).…”

Genetic Hotels for the Standard Genetic Code: Evolutionary Analysis Based upon Novel Three-Dimensional Algebraic Models

“…It has been convincingly shown that mistranslation in the first and third codon positions is more common than in the second position (Woese 1965;Kramer and Farabaugh 2007), but the transitional biased misreading in the second position is hard to justify from the available data. Ardell and Sella (2002) formulated the first population-genetic model of code evolution where the changes in genomic content of a population are modeled along with the code changes. This approach is a generalization of the adaptive concept of code evolution that unifies the lethal-mutation and translation-error minimization hypotheses and incorporates the well-known fact that, among mutations, transitions are far more frequent than transversions (Collins and Jukes 1994;Kumar 1996).…”

“…This approach is a generalization of the adaptive concept of code evolution that unifies the lethal-mutation and translation-error minimization hypotheses and incorporates the well-known fact that, among mutations, transitions are far more frequent than transversions (Collins and Jukes 1994;Kumar 1996). Essentially, the Ardell-Sella model describes coevolution of a code with genes that utilize it to produce proteins and explicitly takes into account the "freezing effect" of genes on a code that is due to the massive deleterious effect of code changes (Ardell and Sella 2002). Thus, once the universal code was established, it became fixed and resistant to evolutionary changes.…”

Collective evolution and the genetic code

“…We employ genetic code dynamics similar to that first introduced by Sella and Ardell (24)(25)(26). The main feature is the coevolution between the genetic code and codon usage at different functional sites.…”