Abstract:

The accurate analyses of massive amounts of data obtained through next‐generation sequencing depend on the selection of appropriate evolutionary models. Many plastid phylogenomic studies typically analyze plastome data as a single partition, or divided by a region, using a concatenate “supergene” approach. The effects of molecular evolutionary models and character partition strategies on plastome‐based phylogenies have generally been evaluated at higher taxonomic levels in green plants. Using plastome data from 32 species of Amphilophium, a genus of Neotropical lianas, we explored potential sources of topological incongruence with different plastid genome datasets and approaches. Specifically, we evaluated the effects of compositional heterogeneity, codon usage bias, positive selection, and incomplete lineage sorting as sources of systematic error (i.e., the recovery of well‐supported conflicting topologies). We compared different datasets (e.g., non‐coding regions, exons, and codon‐aligned and translated amino acids) using concatenated approaches under site‐heterogeneous and site‐homogeneous models, as well as multispecies coalescent (MSC) methods. We found incongruences in recovered phylogenetic relationships, which were mainly located in short internodes. The MSC and concatenated approaches recovered similar topologies. The analysis of GC content and codon usage bias indicated higher substitution rates and AT excess at the third codon positions, and we found evidence of positive selection in 3% of amino acid sites. There were no significant differences among species in site biochemical profiles. We argue that the selection of appropriate partition strategies and evolutionary models is important to increase accuracy in phylogenetic relationships, even when using plastome datasets, which is still the primarily used genome in plant phylogenetics.

Key words: codon usage bias, compositional heterogeneity, gene tree incongruence, Neotropical lianas, NGS, plastome, positive selection, species‐level phylogenomics