Inference of Evolutionary Jumps in Large Phylogenies using Lévy Processes

Area of Science:

• Evolutionary biology
• Quantitative genetics
• Phylogenetics

Background:

• The rate of phenotypic evolution is not constant across evolutionary history.
• G. G. Simpson hypothesized that rapid evolutionary jumps occur upon entering new adaptive zones.
• Testing Simpson's hypothesis has been computationally challenging due to the complexity of inferring evolutionary jumps.

Purpose of the Study:

• To develop a computationally efficient algorithm for inferring the rate, strength, and phylogenetic location of evolutionary jumps.
• To test Simpson's hypothesis regarding the link between adaptive zone transitions and evolutionary jumps.

Main Methods:

• A novel algorithm was developed to model evolutionary jumps as a compound process.
• The algorithm avoids matrix inversions, enabling scalability to large phylogenetic trees.
• The method efficiently samples jump configurations to infer evolutionary dynamics.

Main Results:

• The developed algorithm accurately infers evolutionary jumps, including their rate, strength, and position in phylogenies.
• Analysis of Anolis lizards and Loriinii parrots revealed significant evolutionary jumps at the base of clades entering new adaptive zones.
• Findings support Simpson's hypothesis on the role of adaptive zone transitions in driving rapid phenotypic evolution.

Conclusions:

• The new algorithm provides an efficient tool for studying evolutionary jumps in large phylogenies.
• Evidence supports the hypothesis that transitions into new adaptive zones trigger periods of rapid phenotypic evolution.
• This work advances our understanding of the tempo and mode of macroevolutionary change.