Phylogenomic resolution of sea spider relationships via integration of phylogenetic data classes


Meeting Abstract

59-8  Sunday, Jan. 5 14:45 – 15:00  Phylogenomic resolution of sea spider relationships via integration of phylogenetic data classes SHARMA, PP*; ARANGO, CP; BALLESTEROS, JA; BRENNEIS, G; DILLY, GF; SETTON, EVW; WHEELER, WC; University of Wisconsin-Madison; Queensland Museum; University of Wisconsin-Madison; University of Greifswald; California State University-Channel Islands; University of Wisconsin-Madison; American Museum of Natural History prashant.sharma@wisc.edu http://www.sharmalabuw.org

Pycnogonida (sea spiders) is a fascinating group of marine arthropods renowned for their bizarre appearance and the widespread trait of exclusive paternal care of egg masses. The sister group to the remaining Chelicerata, the ca. 1350 known species of this lineage have an ancient origin, with crown-group body fossils present in the Silurian. However, higher-level phylogenetic relationships of sea spiders remain poorly understood, which has hindered inferences of morphological and developmental evolution, as well as estimation of divergence times. Previous efforts to infer the phylogenetic relationships of sea spiders have been hindered by the low informativeness of some Sanger-sequenced markers, the rarity of species in small-bodied families, and the pervasiveness of missing data in molecular phylogenetic matrices. To overcome these hurdles, we devised a phylogenomic approach to inferring sea spider relationships, capitalizing upon museum collections and sorted material from benthic surveys. Our sequencing strategy aimed to integrate several data classes, namely, ultraconserved elements, targeted exons, and mitochondrial genomes. Here, we show that integration of these data classes results in a robustly resolved basal phylogeny of sea spiders, with high nodal support for interfamilial relationships. We infer the age of crown-group Pycnogonida for the first time using internal fossil calibrations in a Bayesian inference framework. Finally, upon this temporal context, we contrast the different data partitions to identify which are the most informative for resolving relationships of varying phylogenetic depths.

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