Bulletin of Mathematical Biology

, Volume 81, Issue 2, pp 384–407 | Cite as

On the Number of Non-equivalent Ancestral Configurations for Matching Gene Trees and Species Trees

  • Filippo DisantoEmail author
  • Noah A. Rosenberg
Special Issue: Algebraic Methods in Phylogenetics


An ancestral configuration is one of the combinatorially distinct sets of gene lineages that, for a given gene tree, can reach a given node of a specified species tree. Ancestral configurations have appeared in recursive algebraic computations of the conditional probability that a gene tree topology is produced under the multispecies coalescent model for a given species tree. For matching gene trees and species trees, we study the number of ancestral configurations, considered up to an equivalence relation introduced by Wu (Evolution 66:763–775, 2012) to reduce the complexity of the recursive probability computation. We examine the largest number of non-equivalent ancestral configurations possible for a given tree size n. Whereas the smallest number of non-equivalent ancestral configurations increases polynomially with n, we show that the largest number increases with \(k^n\), where k is a constant that satisfies \(\root 3 \of {3}\,\le \,k\,<\,1.503\). Under a uniform distribution on the set of binary labeled trees with a given size n, the mean number of non-equivalent ancestral configurations grows exponentially with n. The results refine an earlier analysis of the number of ancestral configurations considered without applying the equivalence relation, showing that use of the equivalence relation does not alter the exponential nature of the increase with tree size.


Ancestral configurations Combinatorics Gene trees and species trees Phylogenetics 



We thank Elizabeth Allman, James Degnan, and John Rhodes for discussions, and two reviewers for comments. Support was provided by National Institutes of Health grant R01 GM117590 and by a 2014 Rita Levi Montalcini grant to FD from the Ministero dell’Istruzione, dell’Università e della Ricerca.


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Copyright information

© Society for Mathematical Biology 2017

Authors and Affiliations

  1. 1.Department of BiologyStanford UniversityStanfordUSA
  2. 2.Department of MathematicsUniversity of PisaPisaItaly

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