Literature DB >> 11675587

On the evolution of redundancy in genetic codes.

D H Ardell1, G Sella.   

Abstract

We simulate a deterministic population genetic model for the coevolution of genetic codes and protein-coding genes. We use very simple assumptions about translation, mutation, and protein fitness to calculate mutation-selection equilibria of codon frequencies and fitness in a large asexual population with a given genetic code. We then compute the fitnesses of altered genetic codes that compete to invade the population by translating its genes with higher fitness. Codes and genes coevolve in a succession of stages, alternating between genetic equilibration and code invasion, from an initial wholly ambiguous coding state to a diversified frozen coding state. Our simulations almost always resulted in partially redundant frozen genetic codes. Also, the range of simulated physicochemical properties among encoded amino acids in frozen codes was always less than maximal. These results did not require the assumption of historical constraints on the number and type of amino acids available to codes nor on the complexity of proteins, stereochemical constraints on the translational apparatus, nor mechanistic constraints on genetic code change. Both the extent and timing of amino-acid diversification in genetic codes were strongly affected by the message mutation rate and strength of missense selection. Our results suggest that various omnipresent phenomena that distribute codons over sites with different selective requirements--such as the persistence of nonsynonymous mutations at equilibrium, the positive selection of the same codon in different types of sites, and translational ambiguity--predispose the evolution of redundancy and of reduced amino acid diversity in genetic codes.

Mesh:

Substances:

Year:  2001        PMID: 11675587     DOI: 10.1007/s002390010217

Source DB:  PubMed          Journal:  J Mol Evol        ISSN: 0022-2844            Impact factor:   2.395


  20 in total

1.  On the evolution of primitive genetic codes.

Authors:  Günter Weberndorfer; Ivo L Hofacker; Peter F Stadler
Journal:  Orig Life Evol Biosph       Date:  2003-10       Impact factor: 1.950

Review 2.  The case for an error minimizing standard genetic code.

Authors:  Stephen J Freeland; Tao Wu; Nick Keulmann
Journal:  Orig Life Evol Biosph       Date:  2003-10       Impact factor: 1.950

3.  No accident: genetic codes freeze in error-correcting patterns of the standard genetic code.

Authors:  David H Ardell; Guy Sella
Journal:  Philos Trans R Soc Lond B Biol Sci       Date:  2002-11-29       Impact factor: 6.237

4.  A unified model of codon reassignment in alternative genetic codes.

Authors:  Supratim Sengupta; Paul G Higgs
Journal:  Genetics       Date:  2005-03-21       Impact factor: 4.562

5.  Mitochondrial genetic codes evolve to match amino acid requirements of proteins.

Authors:  Jonathan Swire; Olivia P Judson; Austin Burt
Journal:  J Mol Evol       Date:  2005-01       Impact factor: 2.395

6.  Collective evolution and the genetic code.

Authors:  Kalin Vetsigian; Carl Woese; Nigel Goldenfeld
Journal:  Proc Natl Acad Sci U S A       Date:  2006-07-03       Impact factor: 11.205

Review 7.  The coevolution of genes and genetic codes: Crick's frozen accident revisited.

Authors:  Guy Sella; David H Ardell
Journal:  J Mol Evol       Date:  2006-07-12       Impact factor: 2.395

Review 8.  Pathways of Genetic Code Evolution in Ancient and Modern Organisms.

Authors:  Supratim Sengupta; Paul G Higgs
Journal:  J Mol Evol       Date:  2015-06-09       Impact factor: 2.395

9.  An alternative look at code evolution: using non-canonical codes to evaluate adaptive and historic models for the origin of the genetic code.

Authors:  David W Morgens; Andre R O Cavalcanti
Journal:  J Mol Evol       Date:  2013-01-24       Impact factor: 2.395

10.  The action of key factors in protein evolution at high temporal resolution.

Authors:  Armin Schmitt; Johannes Schuchhardt; Gudrun A Brockmann
Journal:  PLoS One       Date:  2009-03-12       Impact factor: 3.240

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