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Using Phylogenetic Analysis to Investigate Eukaryotic Gene Origin

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Gene Transfer-Based Phylogenetics: Analytical Expressions and Additivity via Birth-Death Theory.

Guy Katriel¹, Udi Mahanaymi², Shelly Brezner²

¹Department of Mathematics, Braude College of Engineering, Karmiel, Israel.

Systematic Biology

|October 20, 2023

Summary

This study introduces a new method using genome dynamics (GD) and synteny index (SI) to accurately infer evolutionary distances between organisms. This approach enables the construction of large-scale phylogenetic trees, improving upon existing methods.

Keywords:

Genome dynamics prokaryotic phylogenetics statistical consistency synteny index

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Area of Science:

Genomics
Molecular Systematics
Phylogenetics

Background:

Standard phylogenetic methods using point mutations are slow for fine-scale evolutionary history. Genome dynamics (GD) events offer richer phylogenetic information.
Existing genome dynamics models lack precise estimators, relying on heuristic solutions. Synteny index (SI) combines gene order and content but requires robust analytical methods.

Purpose of the Study:

To develop a novel analytical framework for inferring evolutionary distances using genome dynamics.
To establish an accurate and consistent method for phylogenetic analysis based on gene order and content.

Main Methods:

Modeled genome dynamics as a continuous-time Markov process and gene distance as a birth-death-immigration process.
Applied birth-death theory to derive explicit probabilistic dynamics and analytically accurate evolutionary distances from the synteny index (SI).
Established the additivity of the estimated evolutionary distance for phylogenetic consistency.

Main Results:

Derived explicit expressions for probabilistic dynamics, enabling analytical inference of evolutionary distances from SI.
Demonstrated the accuracy and consistency of the new distance measure in simulations, including gene gain/loss scenarios.
Constructed the largest gene-order-based phylogenetic tree to date (>4.5K taxa) using the ordered orthology database.

Conclusions:

The new method provides analytically accurate evolutionary distances, overcoming limitations of previous heuristic approaches.
The developed framework supports robust phylogenetic inference and construction of large-scale gene-order-based trees.
This approach offers a valuable tool for molecular systematics, complementing existing phylogenetic methods.