Permutation tests for analyzing cospeciation in multiple phylogenies: applications in tri-trophic ecology

Area of Science:

• Ecology and Evolutionary Biology
• Bioinformatics
• Statistical Genetics

Background:

• Assessing cospeciation among multiple phylogenies, especially in tri-trophic systems, requires reliable statistical tests.
• Existing methods often involve pairwise comparisons and lack the ability to handle complex host-parasite ratios or multiple associations.

Purpose of the Study:

• To develop a novel statistical algorithm for testing and inferring three-way cospeciation in multiple phylogenies.
• To provide a flexible method capable of accommodating unequal numbers of hosts and parasites and multiple symbiotic associations.

Main Methods:

• Developed a permutation-based algorithm utilizing a dominant eigenvalue of a covariance matrix to generate an overall p-value for cospeciation detection.
• Introduced new partial correlation-based statistics to detail relationships between phylogenies when cospeciation is identified.
• The method makes no parametric assumptions and processes data in a single step, unlike previous multi-step pairwise approaches.

Main Results:

• The permutation method reliably detects three-way cospeciation in tri-trophic systems.
• Applied to two datasets, the method provided detailed information on association strengths with partial and overall p-values.
• The algorithm successfully identified phylogenies involved in cospeciation events.

Conclusions:

• The new algorithm offers a reliable, intuitive, and efficient statistical framework for assessing cospeciation across multiple phylogenies.
• This method advances the study of co-evolutionary dynamics in complex ecological systems, particularly tri-trophic associations.
• It provides a powerful tool for inferring evolutionary histories and identifying specific species interactions within cospeciation events.