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Early Fixation of an Optimal Genetic Code

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TLDR
It is shown that if theoretically possible code structures are limited to reflect plausible biological constraints, and amino acid similarity is quantified using empirical data of substitution frequencies, the canonical code is at or very close to a global optimum for error minimization across plausible parameter space.
Abstract
The evolutionary forces that produced the canonical genetic code before the last universal ancestor remain obscure. One hypothesis is that the arrangement of amino acid/codon assignments results from selection to minimize the effects of errors (e.g., mistranslation and mutation) on resulting proteins. If amino acid similarity is measured as polarity, the canonical code does indeed outperform most theoretical alternatives. However, this finding does not hold for other amino acid properties, ignores plausible restrictions on possible code structure, and does not address the naturally occurring nonstandard genetic codes. Finally, other analyses have shown that significantly better code structures are possible. Here, we show that if theoretically possible code structures are limited to reflect plausible biological constraints, and amino acid similarity is quantified using empirical data of substitution frequencies, the canonical code is at or very close to a global optimum for error minimization across plausible parameter space. This result is robust to variation in the methods and assumptions of the analysis. Although significantly better codes do exist under some assumptions, they are extremely rare and thus consistent with reports of an adaptive code: previous analyses which suggest otherwise derive from a misleading metric. However, all extant, naturally occurring, secondarily derived, nonstandard genetic codes do appear less adaptive. The arrangement of amino acid assignments to the codons of the standard genetic code appears to be a direct product of natural selection for a system that minimizes the phenotypic impact of genetic error. Potential criticisms of previous analyses appear to be without substance. That known variants of the standard genetic code appear less adaptive suggests that different evolutionary factors predominated before and after fixation of the canonical code. While the evidence for an adaptive code is clear, the process by which the code achieved this optimization requires further attention.

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Journal ArticleDOI

Analysis of optimality in natural and perturbed metabolic networks

TL;DR: The method of minimization of metabolic adjustment (MOMA), whereby the hypothesis that knockout metabolic fluxes undergo a minimal redistribution with respect to the flux configuration of the wild type is tested, is tested and found to be useful in understanding the evolutionary optimization of metabolism.
Book

The evolution of the genome

TL;DR: This chapter discusses the evolution of genome size in animals and plants, as well as Comparative Genomics in Eukaryotes and Prokaryotes, and macroevolution and the Genome.
Journal ArticleDOI

Rewiring the keyboard: evolvability of the genetic code

TL;DR: The distribution and causes of secondary deviations from the canonical genetic code are examined, with the majority of non-standard codes arise from alterations in the tRNA, with most occurring by post-transcriptional modifications, such as base modification or RNA editing, rather than by substitutions within tRNA anticodons.
Journal ArticleDOI

Collective evolution and the genetic code

TL;DR: A dynamical theory for the evolution of the genetic code is presented, which accounts for its universality and optimality and is illustrated by using a simplified computer model and placed within the context of a sequence of transitions that early life may have made, before the emergence of vertical descent.
References
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Book ChapterDOI

Evolutionary Divergence and Convergence in Proteins

TL;DR: The evaluation of the amount of differences between two organisms as derived from sequences in structural genes or in their polypeptide translation is likely to lead to quantities different from those obtained on the basis of observations made at any other, higher level of biological integration.
Journal ArticleDOI

The origin of the genetic code.

TL;DR: It is considered that originally only a few amino acids were coded, but that most of the possible codons were fairly soon brought into use and the code became frozen in its present form.
Journal ArticleDOI

New optimization heuristics

TL;DR: The quality of the computational results obtained so far by RRT and GDA shows that the new algorithms behave equally well as TA and thus a fortiori better than SA.