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ASTRAL: genome-scale coalescent-based species tree estimation.

S Mirarab¹, R Reaz¹, Md S Bayzid¹

¹Department of Computer Science, The University of Texas at Austin, Austin, TX 78712, USA, Departement d'informatique, Ecole Normale Superieure, 45 Rue d'Ulm, F-75230 Paris Cedex 05, France and Department of Electrical Engineering, The University of Southern California, Los Angeles, CA 90089, USA.

Bioinformatics (Oxford, England)

|August 28, 2014

Summary

ASTRAL is a new, fast, and accurate method for estimating species trees from gene data. It overcomes computational challenges and improves accuracy compared to existing methods, especially for large-scale evolutionary analyses.

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Using Phylogenetic Analysis to Investigate Eukaryotic Gene Origin

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Area of Science:

Phylogenetics and evolutionary biology
Computational biology and bioinformatics

Background:

Species trees are crucial for understanding evolution, biodiversity, and co-evolution, but gene trees often conflict due to incomplete lineage sorting (ILS).
Existing species tree estimation methods face computational limitations for genome-scale data or accuracy issues under realistic conditions.

Purpose of the Study:

To introduce ASTRAL, a novel, fast, and statistically consistent method for species tree estimation from multiple genes.
To address the computational intensity and accuracy limitations of current phylogenetic methods.

Main Methods:

ASTRAL utilizes a coalescent-based approach to infer species trees from gene tree data.
The method is designed for scalability, capable of analyzing datasets with thousands of genes.

Main Results:

ASTRAL demonstrates outstanding accuracy, outperforming established methods like MP-EST and BUCKy's population tree.
It shows improved accuracy over concatenation with maximum likelihood, particularly when incomplete lineage sorting is prevalent.

Conclusions:

ASTRAL offers a computationally efficient and accurate solution for species tree estimation, suitable for large-scale genomic analyses.
The method provides a valuable tool for advancing evolutionary biology research by reliably reconstructing species histories.