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Tackling the phylogenetic conundrum of Hydroidolina (Cnidaria: Medusozoa: Hydrozoa) by assessing competing tree topologies with targeted high-throughput sequencing.


ABSTRACT: Higher-level relationships of the Hydrozoan subclass Hydroidolina, which encompasses the vast majority of medusozoan cnidarian species diversity, have been elusive to confidently infer. The most widely adopted phylogenetic framework for Hydroidolina based on ribosomal RNA data received low support for several higher level relationships. To address this issue, we developed a set of RNA baits to target more than a hundred loci from the genomes of a broad taxonomic sample of Hydroidolina for high-throughput sequencing. Using these data, we inferred the relationships of Hydroidolina using maximum likelihood and Bayesian approaches. Both inference methods yielded well-supported phylogenetic hypotheses that largely agree with each other. Using maximum likelihood and Baysian hypothesis testing frameworks, we found that several alternate topological hypotheses proposed previously may be rejected in light of the genomic data generated for this study. Both the maximum likelihood and Bayesian topologies inferred herein consistently score well across testing frameworks, suggesting that their consensus represents the most likely phylogenetic hypothesis of Hydroidolina. This phylogenetic framework places Aplanulata as sister lineage to the remainder of Hydroidolina. This is a strong deviation from previous phylogenetic analyses that placed Capitata or Siphonophorae as sister group to the remainder of Hydroidolina. Considering that Aplanulata represents a lineage comprised of species that for the most part possess a life cycle involving a solitary polyp and free-swimming medusa stage, the phylogenetic hypotheses presented herein have potentially large implications for clarifying the evolution of life cycles, coloniality, and the division of labor in Hydrozoa as taxon sampling for phylogenetic analyses becomes more complete.

SUBMITTER: Bentlage B 

PROVIDER: S-EPMC8435201 | biostudies-literature |

REPOSITORIES: biostudies-literature

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