Package models and the information crisis of prebiotic evolution


Autoria(s): SILVESTRE, Daniel A. M. M.; FONTANARI, Jose Fernando
Contribuinte(s)

UNIVERSIDADE DE SÃO PAULO

Data(s)

20/10/2012

20/10/2012

2008

Resumo

The coexistence between different types of templates has been the choice solution to the information crisis of prebiotic evolution, triggered by the finding that a single RNA-like template cannot carry enough information to code for any useful replicase. In principle, confining d distinct templates of length L in a package or protocell, whose Survival depends on the coexistence of the templates it holds in, could resolve this crisis provided that d is made sufficiently large. Here we review the prototypical package model of Niesert et al. [1981. Origin of life between Scylla and Charybdis. J. Mol. Evol. 17, 348-353] which guarantees the greatest possible region of viability of the protocell population, and show that this model, and hence the entire package approach, does not resolve the information crisis. In particular, we show that the total information stored in a viable protocell (Ld) tends to a constant value that depends only on the spontaneous error rate per nucleotide of the template replication mechanism. As a result, an increase of d must be followed by a decrease of L, so that the net information gain is null. (C) 2008 Elsevier Ltd. All rights reserved.

Identificador

JOURNAL OF THEORETICAL BIOLOGY, v.252, n.2, p.326-337, 2008

0022-5193

http://producao.usp.br/handle/BDPI/30028

10.1016/j.jtbi.2008.02.012

http://dx.doi.org/10.1016/j.jtbi.2008.02.012

Idioma(s)

eng

Publicador

ACADEMIC PRESS LTD ELSEVIER SCIENCE LTD

Relação

Journal of Theoretical Biology

Direitos

restrictedAccess

Copyright ACADEMIC PRESS LTD ELSEVIER SCIENCE LTD

Palavras-Chave #template coexistence #error threshold #genetic diversity #STOCHASTIC CORRECTOR MODEL #ERROR THRESHOLD #FINITE POPULATIONS #GROUP SELECTION #VESICLE MODELS #ORIGIN #HYPERCYCLES #LIFE #ORGANIZATION #COMPARTMENTS #Biology #Mathematical & Computational Biology
Tipo

article

original article

publishedVersion