Phylogenies from unaligned proteomes using sequence environments of amino acid residues

Abstract

Alignment-free methods for sequence comparison and phylogeny inference have attracted a great deal of attention in recent years. Several algorithms have been implemented in diverse software packages. Despite the great number of existing methods, most of them are based on word statistics. Although they propose different filtering and weighting strategies and explore different metrics, their performance may be limited by the phylogenetic signal preserved in these words. Herein, we present a different approach based on the species-specific amino acid neighborhood preferences. These differential preferences can be assessed in the context of vector spaces. In this way, a distance-based method to build phylogenies has been developed and implemented into an easy-to-use R package. Tests run on real-world datasets show that this method can reconstruct phylogenetic relationships with high accuracy, and often outperforms other alignment-free approaches. Furthermore, we present evidence that the new method can perform reliably on datasets formed by non-orthologous protein sequences, that is, the method not only does not require the identification of orthologous proteins, but also does not require their presence in the analyzed dataset. These results suggest that the neighborhood preference of amino acids conveys a phylogenetic signal that may be of great utility in phylogenomics.

Estimating Genome-wide Phylogenies Using Probabilistic Topic Modeling

“…Many authors (cf. Edwards et al 2002;Chan et al 2014;Balaban et al 2022;Van Etten et al 2023;Aledo 2022;Dylus et al 2023) declared that k-mers from unaligned data deliver good phylogenetic information, but our analysis shows that k-mers derived from unaligned sequences contain less information than sequences augmented with alignment information. We agree that unaligned data analysis is a great first and quick step to evaluate phylogenetic relationships, but if great accuracy is needed, then aligned sequences will be necessary.…”

“…For example, they can be used to derive distances to be summarized into phylogenies (Edwards et al 2002; Chan et al 2014; Balaban et al 2022; Van Etten et al 2023). Alignment-free approaches for phylogeny inference have attracted considerable attention in recent years (Dylus et al 2023; Aledo 2022; Bernard et al 2021; Zielezinski et al 2017). For example, several studies have shown that the alignment artifacts can significantly impact tree topology (Ogden and Rosenberg 2006; Wong et al 2008; Du et al 2019).…”