Using Genomic Location and Coalescent Simulation to Investigate Gene Tree Discordance in Medicago L

Area of Science:

• Evolutionary Biology
• Phylogenetics
• Genomics

Background:

• Evolutionary processes such as incomplete lineage sorting, hybridization, and gene duplication create conflicts between species and gene phylogenies.
• Existing methods struggle to simultaneously address these three major challenges in species tree inference.
• Unwarranted comparisons of paralogous genes due to gene duplication can lead to inaccurate phylogenetic results.

Purpose of the Study:

• To propose a novel stepwise method for discerning and resolving phylogenetic conflicts caused by incomplete lineage sorting, hybridization, and gene duplication.
• To improve the accuracy of species tree inference by accounting for multiple evolutionary processes simultaneously.
• To identify ancient hybridization events and undetected paralogy in phylogenetic datasets.

Main Methods:

• A stepwise approach combining genomic location information with coalescent simulations.
• Step 1: Identification and exclusion of highly discordant genes within genomic blocks (putative paralogs).
• Step 2: Grouping of linked genes based on hybrid history, followed by application of multispecies coalescent software.

Main Results:

• The method successfully untangled incomplete lineage sorting, hybridization, and gene duplication in simulated data from a species network.
• Application to the plant genus Medicago identified ancient hybridization in the Medicago orbicularis lineage.
• The approach demonstrated significant improvement in species tree inference accuracy when dealing with phylogenetic incongruence.

Conclusions:

• The proposed stepwise method offers a powerful new approach to analyzing phylogenetic sequence data.
• It significantly enhances species tree inference in the presence of hybridization, paralogy, and other sources of discordance.
• This method provides a robust framework for exploring complex evolutionary histories and resolving phylogenetic uncertainties.