Close lower and upper bounds for the minimum reticulate network of multiple phylogenetic trees

Area of Science:

• Computational Biology
• Phylogenetics
• Evolutionary Biology

Background:

• Reticulate networks model complex evolutionary processes.
• Reconstructing the most parsimonious reticulate network from phylogenetic trees is an NP-hard problem.
• Existing methods often simplify the problem by limiting input trees or network structures.

Purpose of the Study:

• To address the general minimum reticulate network problem without restrictions on input trees or network form.
• To develop novel methods for inferring approximately parsimonious reticulate networks.
• To provide practical tools for analyzing evolutionary history in the presence of reticulation.

Main Methods:

• Developed novel lower and upper bounds for the minimum number of reticulation events.
• Implemented these methods in a program called PIRN.
• PIRN outputs a graphical representation of the inferred reticulate network.

Main Results:

• Presented methods applicable to the fully general minimum reticulate network problem.
• Demonstrated practicality on simulated and biological data.
• Achieved exact solutions for datasets where lower and upper bounds matched, particularly with fewer trees or lower reticulation levels.

Conclusions:

• The developed methods offer a practical and often exact solution to the minimum reticulate network problem.
• PIRN provides a valuable tool for visualizing and analyzing evolutionary networks.
• The approach advances the study of reticulate evolution by handling complex scenarios.