Bayesian Markov chain Monte Carlo sequence analysis reveals varying neutral substitution patterns in mammalian evolution

AUTOR(ES)

Hwang, Dick G.

FONTE

National Academy of Sciences

RESUMO

We describe a model of neutral DNA evolution that allows substitution rates at a site to depend on the two flanking nucleotides (“context”), the branch of the phylogenetic tree, and position within the sequence and implement it by using a flexible and computationally efficient Bayesian Markov chain Monte Carlo approach. We then apply this approach to characterize phylogenetic variation in context-dependent substitution patterns in a 1.7-megabase genomic region in 19 mammalian species. In contrast to other substitution types, CpG transition substitutions have accumulated in a relatively clock-like fashion. More broadly, our results support the notion that context-dependent DNA replication errors, cytosine deamination, and biased gene conversion are major sources of naturally occurring mutations whose relative contributions have varied in mammalian evolution as a result of changes in generation times, effective population sizes, and recombination rates.

Documentos Relacionados

• Mapping-Linked Quantitative Trait Loci Using Bayesian Analysis and Markov Chain Monte Carlo Algorithms
• A Bayesian Approach to Detect Quantitative Trait Loci Using Markov Chain Monte Carlo
• Markov chain Monte Carlo without likelihoods
• Markov Chain Monte Carlo analysis of human Y-chromosome microsatellites provides evidence of biased mutation
• MÃtodo adaptativo de Markov Chain Monte Carlo para manipulaÃÃo de modelos Bayesianos