Global Integration of Phylogenomic Data and Fine-Scale Partitioning Strategies Refine the Evolutionary Tree of Adephaga Beetles

Over the past decade, genomic-scale data has revolutionized insect phylogenetics by allowing the generation of increasingly comprehensive genomic and taxonomic datasets. However, because different approaches have been used, it is often difficult to understand to what extent these data can be integrated to reconstruct evolutionary trees. In this study, we focus on the beetle suborder Adephaga to explore whether genomic data produced in the past decade can be combined to reconstruct the largest phylogenomic tree of this clade to date. To that end, we collected publicly-available transcriptomes, genomes, and target sequence capture data of Adephaga beetles to generate a global dataset. Taking advantage of a newly developed bioinformatic pipeline, we demonstrate the overall compatibility of data types, especially of ultraconserved elements and exon-capture data. We also examined the impact of factors such as the treatment of off-target flanking genomic regions, data trimming regimes and partitioning, as well as varying levels of taxonomic and genomic sampling on phylogenomic inference. Using a matrix of 2,471 loci, we inferred the most comprehensive fossil-based evolutionary tree of Adephaga beetles. Our results confirm the independent colonization of aquatic ecosystems by two lineages. We also reconstruct Hygrobiidae as sister to Amphizoidae and a paraphyletic Aspidytidae, supporting the evolutionary convergence of prothoracic glands in both Hygrobiidae and Dytiscidae. Our results suggest an origin of Adephaga in the Carboniferous, with subsequent diversification of major lineages in the mid-Permian. Future efforts should focus on expanding the taxonomic sampling in Geadephaga, this clade of terrestrial beetles being the most diverse lineage in Adephaga and paradoxically one of the least sampled. To that end, we introduce a new ultraconserved element probe set tailored for Geadephaga beetles that will help generate compatible genomic data to further refine the Adephaga tree of life.