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Supermatrices, supertrees and serendipitous scaffolding: inferring a well-resolved, genus-level phylogeny of Styphelioideae (Ericaceae) despite missing data
Authors:Johnson Karen A  Holland Barbara R  Heslewood Margaret M  Crayn Darren M
Institution:a School of Geography and Environmental Studies, University of Tasmania, Private Bag 78, Hobart, Tasmania 7001, Australia
b School of Mathematics and Physics, University of Tasmania, Private Bag 37, Hobart, Tasmania 7001, Australia
c National Herbarium of New South Wales, Royal Botanic Gardens and Domain Trust, Mrs Macquarie Road, Sydney 2000, Australia
d Australian Tropical Herbarium, James Cook University, PO Box 6811, Cairns, Queensland 4870, Australia
Abstract:For the predominantly southern hemisphere plant group Styphelioideae (Ericaceae) published sequence datasets of five markers are now available for all except one of the 38 recognised genera. However, several markers are highly incomplete therefore missing data is problematic for producing a genus level phylogeny. We explore the relative utility of supertree and supermatrix approaches for addressing this challenge, and examine the effects of missing data on tree topology and resolution. Although the supertree approach returned a more conservative hypothesis, overall, both supermatrix and supertree analyses concurred in the topologies they returned. Using multiple genes and a dataset of variably complete taxa we found improved support for the monophyly and position of the tribes and genus level relationships. However, there was mixed support for the Richeeae tribe appearing one node basal to the Cosmelieae tribe or vice versa. It is probable that this will only be resolved through further sequencing. Our study supports previous findings that the amount of data is more critical than the completeness of the dataset in estimating well-resolved trees. Our results suggest that a “serendipitous” scaffolding approach that includes a mixture of well and poorly sequenced taxa can lead to robust phylogenetic hypotheses.
Keywords:Bayesian  Epacridaceae  Maximum likelihood  Missing data  Matrix Representation with Parsimony  Scaffold concept
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