Is Multiple-Sequence Alignment Required for Accurate Inference of Phylogeny?

Abstract

The process of inferring phylogenetic trees from molecular sequences almost always starts with a multiple alignment of these sequences but can also be based on methods that do not involve multiple sequence alignment. Very little is known about the accuracy with which such alignment-free methods recover the correct phylogeny or about the potential for increasing their accuracy. We conducted a large-scale comparison of ten alignment-free methods, among them one new approach that does not calculate distances and a faster variant of our pattern-based approach; all distance-based alignment-free methods are freely available from http://www.bioinformatics.org.au (as Python package decaf+py). We show that most methods exhibit a higher overall reconstruction accuracy in the presence of high among-site rate variation. Under all conditions that we considered, variants of the pattern-based approach were significantly better than the other alignment-free methods. The new pattern-based variant achieved a speed-up of an order of magnitude in the distance calculation step, accompanied by a small loss of tree reconstruction accuracy. A method of Bayesian inference from k-mers did not improve on classical alignment-free (and distance-based) methods but may still offer other advantages due to its Bayesian nature. We found the optimal word length k of word-based methods to be stable across various data sets, and we provide parameter ranges for two different alphabets. The influence of these alphabets was analyzed to reveal a trade-off in reconstruction accuracy between long and short branches. We have mapped the phylogenetic accuracy for many alignment-free methods, among them several recently introduced ones, and increased our understanding of their behavior in response to biologically important parameters. In all experiments, the pattern-based approach emerged as superior, at the expense of higher resource consumption. Nonetheless, no alignment-free method that we examined recovers the correct phylogeny as accurately as does an approach based on maximum-likelihood distance estimates of multiply aligned sequences.

Phylogenetic Methods and its Applications

“…Multiple sequence alignment methods emphasize that more closely related sequences should be aligned first. In cases of sequences being less related to one another, however sharing a common ancestor may be clustered separately [4,5]. This implies that they can be more accurately aligned, but may result in incorrect phylogeny.…”

“…Multiple alignments of related sequences may often yield the most helpful information on its phylogeny. However, it can produce incorrect results when applied to more divergent sequence rearrangements [5]. Some computationally intensive multiple alignment methods align sequences strictly based on the order in which they receive them, i.e.…”

“…Some methods are based on finding the minimal number of changes required to transform one tree into another. One of its variation is the maximum agreement subtree [5] that finds the maximum common patterns among binary trees.…”

Graphical and numerical representations of DNA sequences: statistical aspects of similarity

“…It becomes more and more popular to replace the alignment methods by alternative ones. In particular, Hönl and Ragan consider numerical alignment-free methods that can replace multiple-sequence alignment to infer a phylogenetic tree that represents the history of a set of molecular sequences [37]. Graphical representations have been also used for the construction of phylogenetic trees.…”

Phylogenetic Tree Estimation With and Without Alignment: New Distance Methods and Benchmarking

“…The similarity measures include concepts like the compression-based Lempel-Ziv (LZ) complexity (Otu and Sayood 2003) and an information theory-based average common substring (ACS) metric (Ulitsky et al 2006), but the most popular is to calculate the relative occurrences of k-mers (Vinga and Almeida 2003). These similarity methods have been widely studied and have shown to be successful when estimating trees, mostly through simulation studies (Höhl and Ragan 2007). There are, however, no studies that systematically compare these alignment-free methods with more conventional twostep approaches to the tree estimation problem.…”