A novel method for multiple alignment of sequences with repeated and shuffled elements

Abstract

We describe ABA (A-Bruijn alignment), a new method for multiple alignment of biological sequences. The major difference between ABA and existing multiple alignment methods is that ABA represents an alignment as a directed graph, possibly containing cycles. This representation provides more flexibility than does a traditional alignment matrix or the recently introduced partial order alignment (POA) graph by allowing a larger class of evolutionary relationships between the aligned sequences. Our graph representation is particularly well-suited to the alignment of protein sequences with shuffled and/or repeated domain structure, and allows one to construct multiple alignments of proteins containing (1) domains that are not present in all proteins, (2) domains that are present in different orders in different proteins, and (3) domains that are present in multiple copies in some proteins. In addition, ABA is useful in the alignment of genomic sequences that contain duplications and inversions. We provide several examples illustrating the applications of ABA.

An Integrative Method for Accurate Comparative Genome Mapping

“…To validate the similarity of the KISs in the two organisms, we globally align them. Among the currently available methods for global alignments, e.g., [40][41][42][43][44][45][46][47][48][49] (see also [50] for a recent review), we used AVID [41]. AVID is a heuristic that runs in time and space that are linear with respect to the size of the genomic sequences.…”

The Basics of Protein Sequence Analysis

“…In the approach implemented in AliWABA the graph may contain cycles, which enables alignment of protein sequences with shuffled and/or repeated domain structure. 107 Currently the best methods for MSA such as SPEM 108 or PROMALS 109 employ PSI-BLAST database searches and secondary structure prediction to construct meta-profiles for all input sequences, then carry out profile-profile alignments (with HMMs or with regular profile methods), often refine these alignments based on consistency scoring, and only then combine the input sequences into an MSA. These methods are therefore much slower than simple (but still very popular) methods like CLUSTAL, but are much more accurate, at least for individual domains.…”

Multiple whole-genome alignments without a reference organism

“…The more recent algorithms for wholegenome alignments attempt to incorporate the likely evolutionary events as ''operations'' into their scoring schemes, including several tools that decide whether to accept or reject a local alignment based on other alignments near it. These include Shuffle-LAGAN (Brudno et al 2003b), Chains and Nets on the UCSC Browser , Mercator (Dewey 2007), A-Bruijn Block Aligner (Raphael et al 2004), and Mauve (Darling et al 2004).…”

“…Most recently, nonreferenced genome alignment implementations have appeared, for example, the Enredo package (Paten et al 2008), used by the Ensembl genome browser. Enredo builds a genome alignment graph, akin to the A-Bruijn graph alignment of Raphael et al (2004), and all of the genomes are aligned simultaneously. This approach has the disadvantage of not taking into account the phylogenetic information about the species, making it more difficult to align distant genomes.…”