Horizontal Gene Transfer Inference: Gene Presence-Absence Outperforms Gene Trees.

Area of Science:

• Evolutionary Biology
• Genomics
• Bioinformatics

Background:

• Horizontal gene transfer (HGT) significantly drives prokaryotic evolution and adaptation.
• Systematic comparisons of HGT inference methods are lacking, hindering understanding of their performance.
• Validating HGT inference is difficult due to the absence of a genomic fossil record, often relying on potentially biased simulations.

Purpose of the Study:

• To systematically assess and compare the accuracy of diverse methods for inferring horizontal gene transfer.
• To evaluate the performance of methods based on gene family presence/absence patterns versus gene tree-species tree reconciliation.
• To provide a benchmark for selecting appropriate HGT inference tools and guide future methodological development.

Main Methods:

• Leveraged the tendency of HGT events to involve multiple neighboring genes for assessment.
• Compared methods analyzing gene family presence/absence patterns across species trees.
• Contrasted these with approaches based on gene tree-species tree reconciliation.

Main Results:

• Methods analyzing gene family presence/absence patterns consistently outperformed gene tree-species tree reconciliation approaches.
• Explicit phylogenetic reconciliation methods were not found to be superior to simpler implicit methods.
• A comprehensive benchmark of HGT inference methods was established.

Conclusions:

• Gene presence/absence analysis is a more accurate approach for inferring horizontal gene transfer than phylogenetic reconciliation.
• The study challenges the assumption that complex phylogenetic methods are inherently superior for HGT detection.
• Provides practical guidance for method selection and identifies future research directions in HGT inference.