This project is supported by The Swedish Taxonomy Initiative (SLU) through a PhD grant to UJ. Marika Maranzano is the PhD student. We plan to analyse about 80 genomes from microscopic marine animals belonging to the group Acoelomorpha. About half of the genomes have been sequenced to-date. Bioinformatics which initially focuses on assembly ofmitogenomes is on-going . The aim is to generate robust phylogenetic hypotheses to resolve some outstanding questions in the Acoelomorpha phylogeny through improved taxonomic sampling and improved sampling of the genome. We also intend to analyse potential cryptic biodiversity in Acoelomorpha and perform introgression analyses in the genus Notocelis. Hypotheses of genome duplication which are based on the occurrence of multiple Hox gene copies in some species and the fact that genome size varies considerably within Acoelomorpha will also be tested. Finally, we will conduct some additional analyses of eDNA where the initial bioinformatics have been carried out elsewhere. As well as analyses of metabarcoding data that will be collected during 2025 and 2026. Acoelomorpha are an abundant and diverse group of microscopic marine animals that are poorly known from a taxonomic and phylogenetic perspective. Our goal here is to resolve difficult phylogenetic problems within Acoela through better taxonomic sampling of genomes, sort out some problematic taxa where there are signs of introgression at the family level, analyse the extent of cryptic diversity indicated by our previous Sanger-based studies, and to evaluate the efficacy of our sampling of these animals through analysis of eDNA and additionally to get a better picture of Acoelomorpha diversity in Swedish habitats. After initial assembly steps, we will perform the phylogenomic analyses, tests for introgression, phylogenetic placement of eDNA data etc. We foresee a relatively high demand for processor hours as the parameter rich nucleotide substitution models implemented in e.g. PhyloBayes are computationally very demanding. Furthermore we will need to perform a set of sensitivity analyses where the dataset is modified in various ways and then reanalysed, which multiplies the resource requirements.