GATC: a genetic algorithm for gene tree construction under the Duplication-Transfer-Loss model of evolution

Emmanuel Noutahi,Nadia El-Mabrouk

doi:10.1186/s12864-018-4455-x

Abstract

BackgroundSeveral methods have been developed for the accurate reconstruction of gene trees. Some of them use reconciliation with a species tree to correct, a posteriori, errors in gene trees inferred from multiple sequence alignments. Unfortunately the best fit to sequence information can be lost during this process.ResultsWe describe GATC, a new algorithm for reconstructing a binary gene tree with branch length. GATC returns optimal solutions according to a measure combining both tree likelihood (according to sequence evolution) and a reconciliation score under the Duplication-Transfer-Loss (DTL) model. It can either be used to construct a gene tree from scratch or to correct trees infered by existing reconstruction method, making it highly flexible to various input data types. The method is based on a genetic algorithm acting on a population of trees at each step. It substantially increases the efficiency of the phylogeny space exploration, reducing the risk of falling into local minima, at a reasonable computational time. We have applied GATC to a dataset of simulated cyanobacterial phylogenies, as well as to an empirical dataset of three reference gene families, and showed that it is able to improve gene tree reconstructions compared with current state-of-the-art algorithms.ConclusionThe proposed algorithm is able to accurately reconstruct gene trees and is highly suitable for the construction of reference trees. Our results also highlight the efficiency of multi-objective optimization algorithms for the gene tree reconstruction problem. GATC is available on Github at: https://github.com/UdeM-LBIT/GATC.

Highlights

Several methods have been developed for the accurate reconstruction of gene trees
We present Genetic algorithm for gene tree construction (GATC) (Genetic Algorithm for gene Tree Construction), a new software for gene tree reconstruction under the DTL model that can take as input completely unresolved, partially unresolved or fully resolved trees, and outputs a tree minimizing a measure combining both tree likelihood and a reconciliation score
Our results show that GATC is more accurate than existing methods, suggesting that it substantially increases the efficiency of the phylogeny space exploration

Summary

Introduction

Several methods have been developed for the accurate reconstruction of gene trees. Some of them use reconciliation with a species tree to correct, a posteriori, errors in gene trees inferred from multiple sequence alignments. Phylogenetic tree reconstruction is an important component of most bioinformatic pipelines. Standard phylogenetic tools are based on maximum likelihood (ML) or bayesian methods reconstructing a. To address this limitation, more recent gene tree reconstruction methods, designated here as integrative methods, include information from the species tree. The idea is to consider, in addition to a maximum likelihood value measuring the fitness of a tree to a sequence alignment (according to a model of sequence evolution), a measure reflecting the evolution of a whole gene family

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