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MBE Advance Access published online on May 23, 2006
Molecular Biology and Evolution, doi:10.1093/molbev/msl015
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© The Author 2006. Published by Oxford University Press on behalf of the Society for Molecular Biology and Evolution. All rights reserved. For permissions, please e-mail: journals.permissions@oxfordjournals.org
Accepted May 8, 2006

Research Article

Dependence Among Sites in RNA Evolution

Jiaye Yu 1 and Jeffrey L. Thorne 2 *

1 Bioinformatics Research Center, North Carolina State University, Raleigh, NC 27695; Current Address: Bioinformatics Centre, University of Copenhagen, Universitetsparken 15, Copenhagen Ø, DK-2100, Denmark
2 Bioinformatics Research Center, North Carolina State University, Raleigh, NC 27695

* To whom correspondence should be addressed.
Jeffrey L. Thorne, E-mail: thorne{at}statgen.ncsu.edu


  Abstract

Although probabilistic models of genotype (e.g., DNA sequence) evolution have been greatly elaborated, less attention has been paid to the effect of phenotype on the evolution of the genotype. Here we propose an evolutionary model and a Bayesian inference procedure that are aimed at filling this gap. In the model, RNA secondary structure links genotype and phenotype by treating the approximate free energy of a sequence folded into a secondary structure as a surrogate for fitness. The underlying idea is that a nucleotide substitution resulting in a more stable secondary structure should have a higher rate than a substitution that yields a less stable secondary structure. This free energy approach incorporates evolutionary dependencies among sequence positions beyond those that are reflected simply by jointly modeling change at paired positions in an RNA helix. Although there is not a formal requirement with this approach that secondary structure be known and nearly invariant over evolutionary time, computational considerations make these assumptions attractive and they have been adopted in a software program that permits statistical analysis of multiple homologous sequences that are related via a known phylogenetic tree topology. Analyses of 5S ribosomal RNA sequences are presented to illustrate and quantify the strong impact that RNA secondary structure has on substitution rates. Analyses on simulated sequences show the new inference procedure has reasonable statistical properties. Potential applications of this procedure, including improved ancestral sequence inference and location of functionally interesting sites, are discussed.

Keywords: RNA secondary structure; Dependence among sites; Substitution rate.
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