Polyphest: fast polyploid phylogeny estimation.

Area of Science:

• Evolutionary Biology
• Computational Biology
• Genomics

Background:

• Polyploidy is common in plants, but reconstructing polyploid phylogenies is computationally challenging.
• Existing methods often ignore incomplete lineage sorting (ILS) or are too slow.
• There's a need for efficient and robust methods for polyploid phylogeny estimation.

Purpose of the Study:

• Introduce Polyphest, a novel computational method for inferring species phylogenies in the presence of polyploidy and ILS.
• Evaluate Polyphest's performance against existing polyploid phylogeny estimation methods.
• Apply Polyphest to empirical data to confirm findings.

Main Methods:

• Polyphest generates a multilabeled tree from gene trees, then converts it to a species phylogeny.
• Bypasses computationally intensive network space searches.
• Compared Polyphest with PADRE (no ILS) and MPAllopp (with ILS).

Main Results:

• Polyphest achieves comparable accuracy to MPAllopp while being significantly faster.
• Polyphest outperforms PADRE in accuracy.
• Applied to bread wheat, Polyphest confirmed its allopolyploid origin and identified its closest relatives.

Conclusions:

• Polyphest offers an efficient and accurate solution for polyploid phylogeny reconstruction.
• The method effectively handles both polyploidy and incomplete lineage sorting.
• Polyphest is a valuable tool for studying the evolution of polyploid organisms.