Statistical Inference of Allopolyploid Species Networks in the Presence of Incomplete Lineage Sorting.
Artikel i vetenskaplig tidskrift, 2013

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 species network or as a multi-labeled species tree, in which some pairs of tips are labeled with the same species. In one of the models (AlloppMUL), the multi-labeled species 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).







Robert Graham Jones

Chalmers, Matematiska vetenskaper

Göteborgs universitet

Serik Sagitov

Göteborgs universitet

Chalmers, Matematiska vetenskaper, matematisk statistik

Bengt Oxelman

Göteborgs universitet

Systematic Biology

1063-5157 (ISSN) 1076-836X (eISSN)

Vol. 62 467-478



Biologisk systematik


Biologiska vetenskaper

Sannolikhetsteori och statistik