multialignment

Multialignment, or multiple sequence alignment (MSA), is the process of aligning three or more biological sequences—DNA, RNA, or proteins—so that residues in homologous positions appear in columns. The goal is to identify regions of similarity that may reflect shared ancestry, conserved structure, or similar function.

Computational methods for MSA construct an alignment by scoring pairwise relationships and inserting gaps to optimize an objective. Classic progressive aligners (such as the Clustal family) build a guide tree from pairwise distances and align sequences along the tree. More recent methods emphasize accuracy through iterative refinement (MUSCLE, MAFFT) or consistency-based information (ProbCons, T-Coffee). Scoring uses substitution matrices for proteins (PAM, BLOSUM) with affine gap penalties, and some approaches employ probabilistic or consistency models. Outputs are multiple sequence alignments used to derive consensus sequences and to infer conserved motifs.

Applications and interpretation: MSA underpins phylogenetic analyses, identification of conserved regions and functional motifs, prediction of structural elements, and annotation transfer between related sequences. Reliability depends on sequence similarity, guide tree quality, and alignment consistency; many alignments include confidence estimates and may require manual curation.

Challenges: Computational complexity grows with the number of sequences and their length; highly divergent or gapped regions reduce accuracy; correct gap placement is difficult, and assessing alignment quality is nontrivial. Common formats for MSA include CLUSTAL, Stockholm, and FASTA with multiple sequences.