More on the Best Evolutionary Rate for Phylogenetic Analysis.

Area of Science:

• Evolutionary biology
• Bioinformatics
• Genomics

Background:

• Genome-scale data aids in resolving the tree of life.
• Conflicting results from phylogenomic studies highlight the need for better experimental design.
• Understanding gene evolutionary rates is crucial for phylogenetic informativeness.

Purpose of the Study:

• To infer optimal evolutionary rates for phylogenetic inference using simulations.
• To investigate the impact of rate variation and taxon sampling on optimal rates.
• To evaluate the performance of different methods for predicting gene utility in phylogenetics.

Main Methods:

• Simulated phylogenetic scenarios with varying tree sizes, taxon sampling, and tree shapes.
• Analysis of the relationship between optimal rates, among-site, and among-lineage rate variation.
• Comparison of six experimental design methods against simulation results.

Main Results:

• Optimal divergence rates are robust to taxon sampling and rate variation.
• Optimal rates range from 0.1 to 0.5 substitutions from root to tip, depending on tree topology.
• Likelihood quartet mapping and signal-noise analysis show good predictive performance; geometric quartet mapping performs poorly.

Conclusions:

• The number of sites evolving at near-optimal rates can directly prioritize genes for phylogenetic inference.
• Integrating model fit with optimal rate site counts can improve marker selection.
• Further testing on empirical data is recommended to validate these findings.