Search algorithm for pattern match analysis of nuleic add sequences

Abstract

A new type of search algorithm to find biological information inherited in nucleic acid sequences was developed. The algorithm is of pattern match type and is based on the fact that genetic information often is a function of a predictable statistical occurrence of the four bases within parts of the sequence. The search algorithm compares the known statistical pattern of bases in e.g. a promoter, with an unknown sequence and calculates the statistical significance of the match at all positions in the unknown sequence. The program was tested on 54 published prokaryotic promoters. 44 or 49 could be found with 1 or 4 false answers, respectively. The program was also used on plasmid pBR322. All promoters functioning in an in vitro transcription system were found (tet, anti-tet, p4, bla and ori) except the so called p5 promoter. A search for donor and acceptor sites was performed in a human HLA genomic sequence that contains six introns. Five of the possible six donor and acceptor sites were found.

The evolutionary selection of DNA base pairs in gene-regulatory binding sites.

“…The dissimilarity index (in previous communications denoted AE) is a measure of the statistical sequence difference ofthe studied site from the consensus sequence for the natural sites. Similar indexes-or homology scoreshave been defined and used by others (10)(11)(12), but the one given in Eq. 1 has the advantage that it is expected to be directly related to the functional strength of a recognition sequence.…”

“…A small change 8Mp in the protein burden (for instance by a nonfunctional protein) should lead to a proportional change As in the relative growth rate constant: Os = L-Mp/2Ne, [10] where the parameter 1L has been defined, such that jL/2N, is the proportionality constant. Mp is the total amount of amino acids invested in protein in the cell.…”

Characterization of a gene encoding a major .BETA.-endoglucanase from Xanthomonas albilineans.

“…The region upstream of this presumptive translation start site was analyzed for potential promoters homologous to E. coli and Pseudomonas putida consensus sequences (15,24) using PAT (14) and BESTFIT (7). Two E. coli type promoter sequences (P1 and P2) were found.…”

Isolation and characterization of Zymomonas mobilis DNA fragments acting as promoter transcriptional elements in Escherichia coli.

“…Table 2. Zymomonas mobilis promoter sequences aligned at the hexamers as identified by the algorithm of Harr et al (11).…”

“…Computer analysis of the nucleotide sequence Inspection of each promoter fragment sequence for sites similar to the E. coli sigma 70 consensus sequence (TTGACA-17bp-TATAAT), was achieved by using the pattern recognition algorithm of Harr et al (11). The algorithm measures the statistical similarity between the E. coli promoter consensus and the target sequence, with weightings for minor bases and the distance between the -35 and -10 hexamers .…”