The hybrid number of a ploidy profile

Huber, Katharina T. and Maher, Liam J. (2022) The hybrid number of a ploidy profile. Journal of Mathematical Biology, 85 (3). ISSN 0303-6812

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Polyploidization, whereby an organism inherits multiple copies of the genome of their parents, is an important evolutionary event that has been observed in plants and animals. One way to study such events is in terms of the ploidy number of the species that make up a dataset of interest. It is therefore natural to ask: How much information about the evolutionary past of the set of species that form a dataset can be gleaned from the ploidy numbers of the species? To help answer this question, we introduce and study the novel concept of a ploidy profile which allows us to formalize it in terms of a multiplicity vector indexed by the species the dataset is comprised of. Using the framework of a phylogenetic network, we present a closed formula for computing the hybrid number (i.e. the minimal number of polyploidization events required to explain a ploidy profile) of a large class of ploidy profiles. This formula relies on the construction of a certain phylogenetic network from the simplification sequence of a ploidy profile and the hybrid number of the ploidy profile with which this construction is initialized. Both of them can be computed easily in case the ploidy numbers that make up the ploidy profile are not too large. To help illustrate the applicability of our approach, we apply it to a simplified version of a publicly available Viola}dataset.

Item Type: Article
Uncontrolled Keywords: phylogenetic network,ploidy profile,multiplicity vector,hybrid number,simplification sequence,prime factor decomposition,binary representation,ploidy profile,hybrid number,prime factor decomposition,binary representation,simplification sequence,multiplicity vector,applied mathematics,agricultural and biological sciences (miscellaneous),modelling and simulation ,/dk/atira/pure/subjectarea/asjc/2600/2604
Faculty \ School: Faculty of Science > School of Computing Sciences
UEA Research Groups: Faculty of Science > Research Groups > Computational Biology
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Depositing User: LivePure Connector
Date Deposited: 06 Sep 2022 11:48
Last Modified: 27 Oct 2023 02:06
DOI: 10.1007/s00285-022-01792-6


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