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This study examines whether phylogenetic networks, which represent evolutionary histories including hybridization and gene transfer, can be uniquely determined from observable genetic data. The researchers prove that for level-1 networks under standard evolutionary models (Jukes-Cantor, Kimura 2-parameter, and Kimura 3-parameter), the network structure is fully identifiable from leaf-pattern distributions across all biologically reasonable parameters. Additionally, they demonstrate that phylogenetic networks produce statistically distinguishable patterns from simple phylogenetic trees, meaning reticulate evolution leaves a detectable signature in genetic data.
Why it matters
These findings strengthen the theoretical foundation for reconstructing evolutionary histories that involve hybridization, horizontal gene transfer, or recombination from genetic sequence data. The results provide mathematical assurance that methods designed to detect complex evolutionary events can reliably distinguish them from simpler tree-like evolution, which is crucial for accurately understanding species relationships in groups where hybridization is common.
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arXiv:2607.12919v2 Announce Type: replace
Abstract: Phylogenetic networks generalize phylogenetic trees to evolutionary histories that include reticulate events such as recombination, horizontal gene transfer, and hybridization. Under a Markov model of nucleotide substitution, a phylogenetic network determines a distribution of leaf-patterns. Here, we study the identifiability of the network topology from this distribution under the Jukes-Cantor (JC), Kimura 2-parameter (K2P), and Kimura 3-parameter (K3P) models. Our first result is that the semi-directed network parameter of a level-1 phylogenetic network (modulo redirecting triangles) is fully identifiable under all three models, on a biologically reasonable parameter space in which substitution rates are probabilistic and mixing parameters are non-trivial (i.e., not 0 or 1). In contrast to the generic identifiability established in prior work, this holds at every point of the parameter space, not merely off of a measure-zero subset. Our second result distinguishes phylogenetic networks from phylogenetic trees, on the same parameter space, under JC and K2P. We prove that no phylogenetic network and phylogenetic tree can induce the same leaf-pattern distribution unless the network is a tree, possibly augmented with certain substructures called $2$-blobs. This means the presence of reticulate evolution creates, in most cases, a detectable signature in the leaf-pattern distribution. More broadly, these results have consequences for identifiability beyond the models and network classes studied here, including for several coalescent-based models.
Source: On Tree-Network Distinguishability and Full Identifiability of Phylogenetic Networks