Theories on PHYlogenetic ReconstructioN (PHYRN)

TL;DR

PHYRN is a novel MSA-independent method that uses PSSMs derived from query sequences to improve deep node resolution in phylogenetic trees, especially for rapidly evolving proteins, outperforming traditional MSA-based methods.

Contribution

This paper introduces PHYRN, a new phylogenetic inference method that leverages phylogenetic profiles and PSSMs, offering significant improvements over MSA-dependent approaches for divergent protein families.

Findings

PHYRN achieves 4- to 100-fold more accurate deep node measurements.

PHYRN is scalable to thousands of sequences.

PHYRN effectively resolves evolutionary relationships in rapidly evolving proteins.

Abstract

The inability to resolve deep node relationships of highly divergent/rapidly evolving protein families is a major factor that stymies evolutionary studies. In this manuscript, we propose a Multiple Sequence Alignment (MSA) independent method to infer evolutionary relationships. We previously demonstrated that phylogenetic profiles built using position specific scoring matrices (PSSMs) are capable of constructing informative evolutionary histories(1;2). In this manuscript, we theorize that PSSMs derived specifically from the query sequences used to construct the phylogenetic tree will improve this method for the study of rapidly evolving proteins. To test this theory, we performed phylogenetic analyses of a benchmark protein superfamily (reverse transcriptases (RT)) as well as simulated datasets. When we compare the results obtained from our method, PHYlogenetic ReconstructioN (PHYRN), with other MSA dependent methods, we observe that PHYRN provides a 4- to 100-fold increase in accurate measurements at deep nodes. As phylogenetic profiles are used as the information source, rather than MSA, we propose PHYRN as a paradigm shift in studying evolution when MSA approaches fail. Perhaps most importantly, due to the improvements in our computational approach and the availability of vast amount of sequencing data, PHYRN is scalable to thousands of sequences. Taken together with PHYRNs adaptability to any protein family, this method can serve as a tool for resolving ambiguities in evolutionary studies of rapidly evolving/highly divergent protein families.