Mitogenomic phylogeny of nymphalid subfamilies confirms the basal clade position of Danainae (Insecta: Lepidoptera: Nymphalidae)

Abstract

AbstractThe phylogenetic relationships among the nymphalid subfamilies have largely been resolved using both morphological and molecular datasets, with the exception of a conflicting basal clade position for Libytheinae or Danainae that remains contentious between morphological and molecular studies. Several phylogenomic analyses have found that the danaine clade is sister to other nymphalid subfamilies; however, it largely depends on utilizing different molecular datasets, analysis methods, and taxon sampling. This study aimed to resolve the basal clade position and relationships among subfamilies and tribes of Nymphalinae by combining the most comprehensive available mitogenomic datasets with various analyses methods by incorporating a new Symbrenthia lilaea Hewitson sequence data. Phylogenetic relationships among 11 nymphalid subfamilies and the tribes of Nymphalinae were inferred by combining new and available mitogenomic sequence data from 80 ingroup and six outgroup species. The phylogenetic trees were reconstructed using maximum‐likelihood (ML) and Bayesian inference (BI) methods based on five concatenated datasets: amino acid sequences and nucleotides from different combinations of protein‐coding genes (PCGs), ribosomal RNA (rRNAs), and transfer RNA (tRNAs). Danainae is well‐supported as the basal clade and sister to the remaining nymphalid subfamilies, except for the paraphyletic Libytheinae. Libytheinae was either recovered as a sister to the danaine clade followed by the satyrine clade or sister to the nymphaline + heliconiine clades, and is consistent with recent phylogenetic studies on Nymphalidae. The monophyletic Nymphalinae has been recovered in all analyses and resolves tribal‐level relationships with high support values in both BI and ML analyses. We supported the monophyletic Nymphalini as a sister clade to Victorini, Melitaeini, and Kallimini + Junoniini with high supporting values in BI and ML analyses, which is consistent with previously published morphological and molecular studies.