Computational evaluation of the strict master and random template models of endogenous retrovirus evolution

Abstract

Transposable elements (TEs) are DNA sequences that are able to replicate and move within and between host genomes. Their mechanism of replication is also shared with endogenous retroviruses (ERVs), which are also a type of TE that represent an ancient retroviral infection within animal genomes. Two models have been proposed to explain TE proliferation in host genomes: the strict master model (SMM), and the random template (or transposon) model (TM). In SMM only a single copy of a given TE lineage is able to replicate, and all other genomic copies of TEs are derived from that master copy. In TM, any element of a given family is able to replicate in the host genome. In this paper, we simulated ERV phylogenetic trees under variations of SMM and TM. To test whether current phylogenetic programs can recover the simulated ERV phylogenies, DNA sequence alignments were simulated and maximum likelihood trees were reconstructed and compared to the simulated phylogenies. Results indicate that visual inspection of phylogenetic trees alone can be misleading. However, if a set of statistical summaries is calculated, we are able to distinguish between models with high accuracy by using a data mining algorithm that we introduce here. We also demonstrate the use of our data mining algorithm with empirical data for the porcine endogenous retrovirus (PERV), an ERV that is able to replicate in human and pig cells in vitro.