# Reconciling Event-Labeled Gene Trees with MUL-trees and Species Networks

## TL;DR

This paper addresses the challenge of reconciling event-labeled gene trees with species networks, proving that any such gene tree can be reconciled with a network, especially in complex evolutionary scenarios like polyploidy.

## Contribution

It introduces methods to reconcile event-labeled gene trees with species networks, including folding MUL-trees into networks, expanding phylogenomic analysis capabilities.

## Key findings

- Any event-labeled gene tree can be reconciled with some species network.
- Under mild conditions, the network can be multi-arc free.
- Reconciliation with MUL-trees facilitates network construction.

## Abstract

Phylogenomics commonly aims to construct evolutionary trees from genomic sequence information. One way to approach this problem is to first estimate event-labeled gene trees (i.e., rooted trees whose non-leaf vertices are labeled by speciation or gene duplication events), and to then look for a species tree which can be reconciled with this tree through a \emph{reconciliation map} between the trees. In practice, however, it can happen that there is no such map from a given event-labeled tree to \emph{any} species tree. An important situation where this might arise is where the species evolution is better represented by a \emph{network} instead of a tree. In this paper, we therefore consider the problem of reconciling event-labeled trees with species networks. In particular, we prove that any event-labeled gene tree can be reconciled with some network and that, under certain mild assumptions on the gene tree, the network can even be assumed to be multi-arc free. To prove this result, we show that we can always reconcile the gene tree with some multi-labeled (MUL-)tree, which can then be "folded up" to produce the desired reconciliation and network. In addition, we study the interplay between reconciliation maps from event-labeled gene trees to MUL-trees and networks. Our results could be useful for understanding how genomes have evolved after undergoing complex evolutionary events such as polyploidy.