Confounding factors in HGT detection: statistical error, coalescent effects, and multiple solutions

Area of Science:

• Evolutionary Biology
• Genomics
• Bioinformatics

Background:

• Prokaryotes exchange genetic material via horizontal gene transfer (HGT), crucial for genome diversification.
• Phylogeny-based methods detect HGT by reconciling gene trees with species phylogeny.
• Accurate HGT detection is vital for understanding prokaryotic evolution and complexity.

Purpose of the Study:

• To investigate factors confounding the accurate detection of horizontal gene transfer events.
• To develop methods for distinguishing HGT from lineage sorting in phylogenetic analysis.
• To improve the accuracy and efficiency of inferring HGT events in prokaryotes.

Main Methods:

• Experimental and theoretical analysis of statistical error in gene tree estimation.
• Evaluation of topological comparisons for reconciling gene and species trees.
• Development of a stochastic framework integrating lineage sorting and HGT.
• Application of dynamic programming for enumerating coalescent scenarios.

Main Results:

• Statistical error in gene trees leads to overestimation of HGT events.
• Reconciling gene and species trees can yield an exponential number of HGT scenarios without branch length information.
• A novel framework effectively distinguishes between HGT and lineage sorting, especially in closely related organisms.
• A polynomial-time algorithm for enumerating coalescent scenarios significantly reduces computational search space.

Conclusions:

• HGT detection methods must account for statistical error and unresolved gene trees.
• Accurate branch lengths and robust reconciliation strategies are essential for inferring HGT.
• Integrating lineage sorting into phylogenetic analysis is critical for accurate evolutionary inference in prokaryotes.