Dependence among Sites in RNA Evolution

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 that 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.

A Model-Based Approach to Study Nearest-Neighbor Influences Reveals Complex Substitution Patterns in Non-coding Sequences

“…As the approach of Parisi and Echave (2001) is computationally inefficient, MCMC approaches which sample substitution histories either between two observed sequences or along a phylogenetic tree have been devised (Robinson et al, 2003;Rodrigue et al, 2005;Yu and Thorne, 2006).…”

Context-Dependent Evolutionary Models for Non-Coding Sequences: An Overview of Several Decades of Research and an Analysis of Laurasiatheria and Primate Evolution

“…However, their calculations take 10-15 days (on relatively small datasets) for a number of taxa ranging between 4 and 10. Yu and Thorne (2006) modify the sequence path approach of Robinson et al (2003) in a similar way to that outlined in Rodrigue et al (2005).…”

Basing population genetic inferences and models of molecular evolution upon desired stationary distributions of DNA or protein sequences

“…The Jensen-Pedersen and other inference techniques have been applied when dependence stems from context-dependent mutation (Hwang & Green 2004;Siepel & Haussler 2004;Christensen et al 2005) and natural selection (Robinson et al 2003;Rodrigue et al 2005;Yu & Thorne 2006). Here, we focus on dependence due to natural selection but not on parameter inference.…”