ALLCOPOL: inferring allele co-ancestry in polyploids.

Area of Science:

• Phylogenetics
• Computational Biology
• Genomics

Background:

• Inferring polyploid phylogenies is challenging due to unknown allele assignments to diploid subgenomes.
• Existing parsimony-based methods have practical limitations and require refinement.
• Accurate phylogenetic reconstruction is crucial for understanding plant evolution.

Purpose of the Study:

• To develop a refined computational method for inferring phylogenetic relationships in polyploid species.
• To address the limitations of previous approaches for allele assignment in polyploids.
• To provide a user-friendly tool for phylogenetic reconstruction of polyploids.

Main Methods:

• Developed the AllCoPol Python package implementing a heuristic method.
• Utilized the Minimizing Deep Coalescences (MDC) criterion for allele assignment.
• Incorporated a consensus approach to assess phylogenetic reconstruction confidence.

Main Results:

• AllCoPol effectively assigns alleles from polyploids to diploid subgenomes using the MDC criterion.
• Simulations demonstrate that reconstructed phylogenies show low topological errors under disomic inheritance.
• The consensus approach enhances the reliability of phylogenetic inferences.

Conclusions:

• AllCoPol is a Python package that enhances phylogenetic reconstruction for polyploids.
• The package offers improved functionality and usability for researchers.
• Methods are available as command-line tools, requiring no programming expertise.