  Polyploidy is an important speciation mechanism, particularly in land plants.
Allopolyploid species are formed after hybridization between otherwise
intersterile parental species. Recent theoretical progress has led to
successful implementation of species tree models that take population genetic
parameters into account. However, these models have not included allopolyploid
hybridization and the special problems imposed when species trees of
allopolyploids are inferred. Here, two new models for the statistical inference
of the evolutionary history of allopolyploids are evaluated using simulations
and demonstrated on two empirical data sets. It is assumed that there has been
a single hybridization event between two diploid species resulting in a genomic
allotetraploid. The evolutionary history can be represented as a network or as
a multiply labeled tree, in which some pairs of tips are labeled with the same
species. In one of the models (AlloppMUL), the multiply labeled tree is
inferred directly. This is the simplest model and the most widely applicable,
since fewer assumptions are made. The second model (AlloppNET) incorporates the
hybridization event explicitly which means that fewer parameters need to be
estimated. Both models are implemented in the BEAST framework. Simulations show
that both models are useful and that AlloppNET is more accurate if the
assumptions it is based on are valid. The models are demonstrated on previously
analyzed data from the genus Pachycladon (Brassicaceae) and from the genus
Silene (Caryophyllaceae).
