Missing the forest for the trees: phylogenetic compression and its implications for inferring complex evolutionary...

Area of Science:

• Evolutionary Biology
• Bioinformatics
• Computational Biology

Background:

• Phylogenetic tree reconstruction is challenged by processes like lateral gene transfer, leading to conflicting evolutionary signals.
• Existing methods may struggle to reconcile these conflicting signals effectively.

Purpose of the Study:

• To develop a novel approach for phylogenetic tree reconstruction that addresses conflicting evolutionary signals.
• To leverage algorithmic information theory for a more robust method of inferring evolutionary history.

Main Methods:

• The study employs principles from algorithmic information theory to develop a phylogenetic compression method.
• This approach selects the evolutionary hypothesis that minimizes the combined descriptive complexity of the tree(s) and the encoded data.

Main Results:

• Phylogenetic compression demonstrates high efficiency in encoding phylogenetic datasets, outperforming schemes designed for single sequences.
• The method provides a clear information-theoretic criterion for evaluating single versus multiple conflicting trees as explanations for the data.
• It challenges the assumption that a total-evidence tree is always the most parsimonious explanation.

Conclusions:

• Phylogenetic compression offers an efficient and information-theoretically grounded method for phylogenetic inference.
• This approach provides a principled way to handle conflicting signals and evaluate competing evolutionary hypotheses.
• The study suggests that the most economical explanation of phylogenetic data may not always involve a single, all-encompassing tree.