SPRINT: A fast, new software tool for reconstructing the evolutionary past of polyploid datasets

TL;DR

SPRINT is a novel, efficient software tool designed to reconstruct the evolutionary history of polyploid datasets by generating minimal polyploidization event networks based on ploidy profiles.

Contribution

It introduces a new method for reconstructing binary networks that realize ploidy profiles with minimal polyploidization events, improving computational efficiency over existing tools.

Findings

Reconstructs evolutionary histories using minimal polyploidization events.

Operates efficiently on polyploid datasets with complex reticulate evolution.

Available as open-source software on GitHub.

Abstract

Polyploidization is an important evolutionary process which affects organisms ranging from plants to fish and fungi. The signal left behind by it is in the form of a species' ploidy level (number of complete chromosome sets found in a cell) which is inherently non-treelike. Currently available tools for reconstructing the evolutionary past of a polyploid dataset generally start with a multi-labelled tree obtained for a dataset of interest and then derive a (phylogenetic) network from that tree in some way that reflects that past by interpreting the networks's vertices of indegree at least two as polyploidization events. Since obtaining such a tree can be computationally expensive it is paramount to have alternative approaches available that allow one to shed light into the reticulate evolutionary past of a polyploid dataset. SPRINT aims to reconstruct the evolutionary past of a polyploid dataset in terms of a binary network which realises the dataset's ploidy profile (vector of ploidy levels of the dataset's taxa) and requires the fewest number of polyploidization events. It does this by representing the ploidy level of a species x in terms of the number of directed paths from the root of the network to the leaf of the network labelled by x. SPRINT is distributed on GitHub: https://github.com/lmaher1/SPRINT.