Post-Alignment Adjustment and Its Automation

Abstract

Multiple sequence alignment (MSA) is the basis for almost all sequence comparison and molecular phylogenetic inferences. Large-scale genomic analyses are typically associated with automated progressive MSA without subsequent manual adjustment, which itself is often error-prone because of the lack of a consistent and explicit criterion. Here, I outlined several commonly encountered alignment errors that cannot be avoided by progressive MSA for nucleotide, amino acid, and codon sequences. Methods that could be automated to fix such alignment errors were then presented. I emphasized the utility of position weight matrix as a new tool for MSA refinement and illustrated its usage by refining the MSA of nucleotide and amino acid sequences. The main advantages of the position weight matrix approach include (1) its use of information from all sequences, in contrast to other commonly used methods based on pairwise alignment scores and inconsistency measures, and (2) its speedy computation, making it suitable for a large number of long viral genomic sequences.

Heuristic Pairwise Alignment in Database Environments

“…The development of methods for multiple alignment is an area of active research. For example, [ 9 ] presents automatable methods to correct some common alignment errors. Further, Korotkov et al [ 10 , 11 ] present new mathematical methods that can cope with cases where the average number of substitutions per position in the sequences is above a certain threshold, in contrast to previous work.…”

Three-Way Alignment Improves Multiple Sequence Alignment of Highly Diverged Sequences

“…The optimal alignment for these three sequences has the highest score based on the SPS criterion. Therefore, any other alignment has a lower score, leading to the following inequality: S(γ * ) − S(γ e ) ≥ 0, (1) where γ * and γ e are the optimal and arbitrary alignments, respectively. The SPS of a 3-way alignment is as follows:…”

“…Inferring evolutionary relationships among various species from molecular data, such as protein, DNA, and RNA sequences, is a basic problem in evolutionary biology. Multiple sequence alignment (MSA) is a primary step in phylogenetic reconstruction, and the accuracy of MSA directly affects the accuracy of reconstructing a phylogeny, especially a deep phylogeny [1][2][3][4].…”

“…Virtually everyone interested in deep phylogeny is looking for ways to improve MSA. Some have incorporated secondary structure to guide the sequence alignment [20][21][22][23], while others explored post-alignment refinement [1,17]. The improvement of MSA with these approaches remains limited.…”

“…Therefore, different strategies for improving guide trees have been proposed [24]. Two criteria have been used to evaluate the effect of guide trees on the accuracy of MSA generated by MAFFT and ClustalW, including (1) the sum-of-pair score (SPS), excluding shared gaps in pairwise comparisons, and (2) the accuracy of phylogenetic reconstruction [27,28]. The result indicates that the final SPS is affected little by the initial guide tree, but better guide trees significantly improve the accuracy of the reconstructed phylogenies.…”