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

Area of Science:

• Bioinformatics
• Computational Biology
• Phylogenetics

Background:

• Gene tree reconstruction is crucial for evolutionary studies.
• Existing methods may lose sequence information during error correction.
• Reconciliation with species trees is a common but imperfect approach.

Purpose of the Study:

• To develop a new algorithm, GATC, for accurate gene tree reconstruction.
• To combine sequence likelihood and reconciliation scores for improved accuracy.
• To offer a flexible tool for both de novo tree construction and existing tree correction.

Main Methods:

• GATC employs a genetic algorithm to explore the phylogeny space efficiently.
• It optimizes solutions based on a combined measure of tree likelihood and Duplication-Transfer-Loss (DTL) reconciliation score.
• The algorithm uses a population-based approach to avoid local minima.

Main Results:

• GATC demonstrated improved gene tree reconstruction accuracy on simulated and empirical datasets.
• The algorithm showed superior performance compared to current state-of-the-art methods.
• It achieves this efficiency within reasonable computational time.

Conclusions:

• GATC accurately reconstructs gene trees and is suitable for reference tree construction.
• Multi-objective optimization is effective for gene tree reconstruction.
• The GATC algorithm is publicly available on Github.