Multiple sequence alignment: in pursuit of homologous DNA positions.
DNA sequence alignment is a prerequisite to virtually all comparative genomic analyses, including the identification of conserved sequence motifs, estimation of evolutionary divergence between sequences, and inference of historical relationships among genes and species. While it is mere common sense that inaccuracies in multiple sequence alignments can have detrimental effects on downstream analyses, it is important to know the extent to which the inferences drawn from these alignments are robust to errors and biases inherent in all sequence alignments. A survey of investigations into strengths and weaknesses of sequence alignments reveals, as expected, that alignment quality is generally poor for two distantly related sequences and can often be improved by adding additional sequences as stepping stones between distantly related species. Errors in sequence alignment are also found to have a significant negative effect on subsequent inference of sequence divergence, phylogenetic trees, and conserved motifs. However, our understanding of alignment biases remains rudimentary, and sequence alignment procedures continue to be used somewhat like benign formatting operations to make sequences equal in length. Because of the central role these alignments now play in our endeavors to establish the tree of life and to identify important parts of genomes through evolutionary functional genomics, we see a need for increased community effort to investigate influences of alignment bias on the accuracy of large-scale comparative genomics.
Kumar
Sudhir
S
Center for Evolutionary Functional Genomics, Biodesign Institute and School of Life Sciences, Arizona State University, Tempe, Arizona 85287-5301, USA. s.kumar@asu.edu
Filipski
Alan
A
D000465:Algorithms; D000818:Animals; D001483:Base Sequence; D004247:DNA / Q000235:genetics*; D019143:Evolution, Molecular; D006801:Humans; D008957:Models, Genetic; D010802:Phylogeny; D016415:Sequence Alignment / Q000379:methods* / Q000706:statistics & numerical data
D004247:DNA