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Resolving evolutionary relationships in lichen-forming fungi using diverse phylogenomic datasets and analytical approaches.

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journal contribution
posted on 08.08.2016 by SD Leavitt, F Grewe, T Widhelm, L Muggia, B Wray, HT Lumbsch
Evolutionary histories are now being inferred from unprecedented, genome-scale datasets for a broad range of organismal groups. While phylogenomic data has helped in resolving a number of difficult, long-standing questions, constructing appropriate datasets from genomes is not straightforward, particularly in non-model groups. Here we explore the utility of phylogenomic data to infer robust phylogenies for a lineage of closely related lichen-forming fungal species. We assembled multiple, distinct nuclear phylogenomic datasets, ranging from ca. 25 Kb to 16.8 Mb and inferred topologies using both concatenated gene tree approaches and species tree methods based on the multispecies coalescent model. In spite of evidence for rampant incongruence among individual loci, these genome-scale datasets provide a consistent, well-supported phylogenetic hypothesis using both concatenation and multispecies coalescent approaches (ASTRAL-II and SVDquartets). However, the popular full hierarchical coalescent approach implemented in *BEAST provided inconsistent inferences, both in terms of nodal support and topology, with smaller subsets of the phylogenomic data. While comparable, well-supported topologies can be accurately inferred with only a small fraction of the overall genome, consistent results across a variety of datasets and methodological approaches provide reassurance that phylogenomic data can effectively be used to provide robust phylogenies for closely related lichen-forming fungal lineages.




The study was financially supported by The Negaunee Foundation, and a generous gift by the Lauer family enabled the purchase of a MiSeq system sequencer for the Pritzker Laboratory for Molecular Systematics, The Field Museum. LM was supported by the FWF project T481-B20.


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This is a copy of an article published in Scientific Reports. © 2016 Nature Publishing Group Publications. © The Author(s).


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