Phylogenomic analysis provides diagnostic tools for the identification of Anastrepha fraterculus (Diptera:...

Insect pests cause tremendous impact to agriculture worldwide. Species identification is crucial for implementing appropriate measures of pest control but can be challenging in closely related species. True fruit flies of the genus Anastrepha Schiner (Diptera: Tephritidae) include some of the most serious agricultural pests in the Americas, with the Anastrepha fraterculus (Wiedemann) complex being one of the most important due to its extreme polyphagy and wide distribution across most of the New World tropics and subtropics. The eight morphotypes described for this complex as well as other closely related species are classified in the fraterculus species group, whose evolutionary relationships are unresolved due to incomplete lineage sorting and introgression. We performed multifaceted phylogenomic approaches using thousands of genes to unravel the evolutionary relationships within the A. fraterculus complex to provide a baseline for molecular diagnosis of these pests. We used a methodology that accommodates variable sources of data (transcriptome, genome, and whole-genome shotgun sequencing) and developed a tool to align and filter orthologs, generating reliable datasets for phylogenetic studies. We inferred 3031 gene trees that displayed high levels of discordance. Nevertheless, the topologies of the inferred coalescent species trees were consistent across methods and datasets, except for one lineage in the A. fraterculus complex. Furthermore, network analysis indicated introgression across lineages in the fraterculus group. We present a robust phylogeny of the group that provides insights into the intricate patterns of evolution of the A. fraterculus complex supporting the hypothesis that this complex is an assemblage of closely related cryptic lineages that have evolved under interspecific gene flow. Despite this complex evolutionary scenario, our subsampling analysis revealed that a set of as few as 80 loci has a similar phylogenetic resolution as the genome-scale dataset, offering a foundation to develop more efficient diagnostic tools in this species group.