Identification of functional elements in unaligned nucleic acid sequences by a novel tuple search algorithm.

We present an algorithm to identify potential functional elements like protein binding sites in DNA sequences, solely from nucleotide sequence data. Prerequisites are a set of at least seven not closely related sequences with a common biological function which is correlated to one or more unknown sequence elements present in most but not necessarily all of the sequences. The algorithm is based on a search for n-tuples which occur at least in a minimum percentage of the sequences with no or one mismatch, which may be at any position of the tuple. In contrast to functional tuples, random tuples show no preferred pattern of mismatch locations within the tuple nor is the conservation extended beyond the tuple. Both features of functional tuples are used to eliminate random tuples. Selection is carried out by maximization of the information content first for the n-tuple, then for a region containing the tuple and finally for the complete binding site. Further matches are found in an additional selection step, using the ConsInd method previously described. The algorithm is capable of identifying and delimiting elements (e.g. protein binding sites) represented by single short cores (e.g. TATA box) in sets of unaligned sequences of about 500 nucleotides using no information other than the nucleotide sequences. Furthermore, we show its ability to identify multiple elements in a set of complete LTR sequences (more than 600 nucleotides per sequence).