Transcriptome-based exon capture methods provide an approach to recover several hundred markers from genomic DNA, allowing for robust phylogenetic estimation at deep timescales. We applied this method to a highly diverse group of venomous marine snails, Conoidea, for which published phylogenetic trees remain mostly unresolved for the deeper nodes. We targeted 850 protein coding genes (678,322 bp) in ca. 120 samples, spanning all (except one) known families of Conoidea and a broad selection of non-Conoidea neogastropods. The capture was successful for most samples, although capture efficiency decreased when DNA libraries were of insufficient quality and/or quantity (dried samples or low starting DNA concentration) and when targeting the most divergent lineages. An average of 75.4% of proteins was recovered, and the resulting tree, reconstructed using both supermatrix (IQ-tree) and supertree (Astral-II, combined with the Weighted Statistical Binning method) approaches, are almost fully supported. A reconstructed fossil-calibrated tree dates the origin of Conoidea to the Lower Cretaceous. We provide descriptions for two new families. The phylogeny revealed in this study provides a robust framework to reinterpret changes in Conoidea anatomy through time. Finally, we used the phylogeny to test the impact of the venom gland and radular type on diversification rates. Our analyses revealed that repeated losses of the venom gland had no effect on diversification rates, while families with a breadth of radula types showed increases in diversification rates, thus suggesting that trophic ecology may have an impact on the evolution of Conoidea.
Species tree inference from gene family trees is a significant problem in computational biology. However, gene tree heterogeneity, which can be caused by several factors including gene duplication and loss, makes the estimation of species trees very challenging. While there have been several species tree estimation methods introduced in recent years to specifically address gene tree heterogeneity due to gene duplication and loss (such as DupTree, FastMulRFS, ASTRAL-Pro, and SpeciesRax), many incur high cost in terms of both running time and memory. We introduce a new approach, DISCO, that decomposes the multi-copy gene family trees into many single copy trees, which allows for methods previously designed for species tree inference in a single copy gene tree context to be used. We prove that using DISCO with ASTRAL (i.e., ASTRAL-DISCO) is statistically consistent under the GDL model, provided that ASTRAL-Pro correctly roots and tags each gene family tree. We evaluate DISCO paired with different methods for estimating species trees from single copy genes (e.g., ASTRAL, ASTRID, and IQ-TREE) under a wide range of model conditions, and establish that high accuracy can be obtained even when ASTRAL-Pro is not able to correctly roots and tags the gene family trees. We also compare results using MI, an alternative decomposition strategy from Yang and Smith (2014), and find that DISCO provides better accuracy, most likely as a result of covering more of the gene family tree leafset in the output decomposition.
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