  Simulated nucleotide sequences are widely used in theoretical and empirical
molecular evolution studies. Conventional simulators generally use fixed
parameter time-homogeneous Markov model for sequence evolution. In this work,
we use the folding free energy of the secondary structure of an RNA as a proxy
for its phenotypic fitness, and simulate RNA macroevolution by a
mutation-selection population genetics model. Because the two-step process is
conditioned on an RNA and its mutant ensemble, we no longer have a global
substitution matrix, nor do we explicitly assume any for this inhomogeneous
stochastic process. After introducing the base model of RNA evolution, we
outline the heuristic implementation algorithm and several model improvements.
We then discuss the calibration of the model parameters and demonstrate that in
phylogeny reconstruction with both the parsimony method and the likelihood
method, the sequences generated by our simulator, rnasim, have greater
statistical complexity than those by two standard simulators, ROSE and Seq-Gen,
and are close to empirical sequences.
