Literature DB >> 11688713

Evolution in silico and in vitro: the RNA model.

P Schuster1.   

Abstract

Theoretical concepts and experiments dealing with the evolution of molecules in vitro reached a state that allows for direct applications to the design of biomolecules with predefined properties. RNA evolution in vitro represents a basis for the development of a new and comprehensive model of evolution, focusing on the phenotype and its fitness relevant properties. Relations between genotypes and phenotypes are described by mappings from genotype space onto a space of phenotypes, which are many-to-one and thus give ample room for neutrality as expressed by the existence of extended neutral networks in genotype space. The RNA model reduces genotype-phenotype relations to mappings from sequences into secondary structures of minimal free energies and allows for derivation of otherwise inaccessible quantitative results. Continuity and discontinuity in evolution are defined through a new notion of accessibility in phenotype space that provides a basis for straight forward interpretation of computer simulations on RNA optimization; furthermore, it reveals the constructive role of random genomic drift in the search for phenotypes of higher fitness. The effects of population size on the course of evolutionary optimization can be predicted quantitatively by means of a simple stochastic model based on a birth-anddeath process with immigration.

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Year:  2001        PMID: 11688713     DOI: 10.1515/BC.2001.162

Source DB:  PubMed          Journal:  Biol Chem        ISSN: 1431-6730            Impact factor:   3.915


  9 in total

Review 1.  The modern theory of biological evolution: an expanded synthesis.

Authors:  Ulrich Kutschera; Karl J Niklas
Journal:  Naturwissenschaften       Date:  2004-03-17

Review 2.  Folding and finding RNA secondary structure.

Authors:  David H Mathews; Walter N Moss; Douglas H Turner
Journal:  Cold Spring Harb Perspect Biol       Date:  2010-08-04       Impact factor: 10.005

3.  Rapid construction of empirical RNA fitness landscapes.

Authors:  Jason N Pitt; Adrian R Ferré-D'Amaré
Journal:  Science       Date:  2010-10-15       Impact factor: 47.728

Review 4.  Evolutionary dynamics of RNA-like replicator systems: A bioinformatic approach to the origin of life.

Authors:  Nobuto Takeuchi; Paulien Hogeweg
Journal:  Phys Life Rev       Date:  2012-06-13       Impact factor: 11.025

5.  A minimal and self-consistent in silico cell model based on macromolecular interactions.

Authors:  Christoph Flamm; Lukas Endler; Stefan Müller; Stefanie Widder; Peter Schuster
Journal:  Philos Trans R Soc Lond B Biol Sci       Date:  2007-10-29       Impact factor: 6.237

6.  Varying environments can speed up evolution.

Authors:  Nadav Kashtan; Elad Noor; Uri Alon
Journal:  Proc Natl Acad Sci U S A       Date:  2007-08-14       Impact factor: 11.205

7.  Structural differences within the loop E motif imply alternative mechanisms of viroid processing.

Authors:  Robert A Owens; Tilman Baumstark
Journal:  RNA       Date:  2007-04-16       Impact factor: 4.942

8.  Evolutionary dynamics and population control during in vitro selection and amplification with multiple targets.

Authors:  Hua Shi; Xiaochun Fan; Zhuoyu Ni; John T Lis
Journal:  RNA       Date:  2002-11       Impact factor: 4.942

9.  On the emergence of structural complexity in RNA replicators.

Authors:  Carlos G Oliver; Vladimir Reinharz; Jérôme Waldispühl
Journal:  RNA       Date:  2019-08-29       Impact factor: 4.942

  9 in total

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