Identification of consensus patterns in unaligned DNA sequences known to be functionally related.
We have developed a method for identifying consensus patterns in a set of unaligned DNA sequences known to bind a common protein or to have some other common biochemical function. The method is based on a matrix representation of binding site patterns. Each row of the matrix represents one of the four possible bases, each column represents one of the positions of the binding site and each element is determined by the frequency the indicated base occurs at the indicated position. The goal of the method is to find the most significant matrix--i.e. the one with the lowest probability of occurring by chance--out of all the matrices that can be formed from the set of related sequences. The reliability of the method improves with the number of sequences, while the time required increases only linearly with the number of sequences. To test this method, we analysed 11 DNA sequences containing promoters regulated by the Escherichia coli LexA protein. The matrices we found were consistent with the known consensus sequence, and could distinguish the generally accepted LexA binding sites from other DNA sequences.
Department of Molecular, Cellular, and Developmental Biology, University of Colorado, Boulder 80309-0347.
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D000465:Algorithms; D001426:Bacterial Proteins / Q000235:genetics; D001483:Base Sequence; D001665:Binding Sites; D004247:DNA; D004269:DNA, Bacterial / Q000235:genetics; D004926:Escherichia coli / Q000235:genetics; D005798:Genes, Bacterial; D008969:Molecular Sequence Data; D010363:Pattern Recognition, Automated; D012697:Serine Endopeptidases; D012984:Software; D000099160:LexA Repressor Protein
D001426:Bacterial Proteins; D004247:DNA; D004269:DNA, Bacterial; D012697:Serine Endopeptidases; D000099160:LexA Repressor Protein