Abstract
Introgression is an evolutionary process which provides an important source of innovation for evolution. Although various methods have been used to detect introgression, very few methods are currently available for constructing evolutionary histories involving introgression. In this paper we propose a new method for constructing such evolutionary histories whose starting point is a species forest (consisting of a collection of lineage trees, usually arising as a collection of clades or monophyletic groups in a species tree), and a gene tree for a specific allele of interest, or allele tree for short. Our method is based on representing introgression in terms of a certain 'overlay' of the allele tree over the lineage trees, called an overlaid species forest (OSF). OSFs are similar to phylogenetic networks although a key difference is that they typically have multiple roots because each monophyletic group in the species tree has a different point of origin. Employing a new model for introgression, we derive an efficient algorithm for building OSFs called OSF-Builder that is guaranteed to return an optimal OSF in the sense that the number of potential introgression events is minimized. As well as using simulations to assess the performance of OSF-Builder, we illustrate its use on a butterfly dataset in which introgression has been previously inferred. The OSF-Builder software is available for download from https://www.uea.ac.uk/computing/software/OSF-Builder
Original language | English |
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Pages (from-to) | 717–729 |
Number of pages | 13 |
Journal | Systematic Biology |
Volume | 68 |
Issue number | 5 |
Early online date | 22 Jan 2019 |
DOIs | |
Publication status | Published - Sep 2019 |
Keywords
- introgression
- allele
- lineage
- phylogenetic network
- OSF-Builder
- Fitch-Hartigan algorithm
Profiles
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Katharina Huber
- School of Computing Sciences - Associate Professor
- Computational Biology - Member
Person: Research Group Member, Academic, Teaching & Research
-
Vincent Moulton
- School of Computing Sciences - Professor in Computational Biology
- Norwich Epidemiology Centre - Member
- Computational Biology - Member
Person: Research Group Member, Academic, Teaching & Research
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Martin Taylor
- School of Biological Sciences - Associate Professor in Molecular Ecology
- Collaborative Centre for Sustainable Use of the Seas - Member
- Organisms and the Environment - Member
Person: Research Group Member, Academic, Teaching & Research