BACKGROUND: The discovery of cis-regulatory motifs still remains a challenging task even though the number of sequenced genomes is constantly growing. Computational analyses using pattern search algorithms have been valuable in phylogenetic footprinting approaches as have expression profile experiments to predict co-occurring motifs. Surprisingly little is known about the nature of cis-regulatory element (CRE) distribution in promoters. RESULTS: In this paper we used the Motif Mapper open-source collection of visual basic scripts for the analysis of motifs in any aligned set of DNA sequences. We focused on promoter motif distribution curves to identify positional over-representation of DNA motifs. Using differentially aligned datasets from the model species Arabidopsis thaliana, Caenorhabditis elegans, Drosophila melanogaster and Saccharomyces cerevisiae, we convincingly demonstrated the importance of the position and orientation for motif discovery. Analysis with known CREs and all possible hexanucleotides showed that some functional elements gather close to the transcription and translation initiation sites and that elements other than the TATA-box motif are conserved between eukaryote promoters. While a high background frequency usually decreases the effectiveness of such an enumerative investigation, we improved our analysis by conducting motif distribution maps using large datasets. CONCLUSION: This is the first study to reveal positional over-representation of CREs and promoter motifs in a cross-species approach. CREs and motifs shared between eukaryotic promoters support the observation that an eukaryotic promoter structure has been conserved throughout evolutionary time. Furthermore, with the information on positional enrichment of a motif or a known functional CRE, it is possible to get a more detailed insight into where an element appears to function. This in turn might accelerate the in depth examination of known and yet unknown cis-regulatory sequences in the laboratory.

A set of programs has been developed for the definition and handling of nucleic acid sequence consensus information. The sequences of known genetic control signals are combined in a matrix. The origins and positions of the signals are recorded. Old matrices can be updated dynamically: new signals are included and obsolete ones deleted. Matrices of several different types are computed optionally. Several of these matrices can be combined to find possible new signals. The use of matrices allows the exact quantification of signal qualities. The described programs are part of a program library named GENEXPERT. Application examples given are the search for tRNA genes and the search for promoters in the bacteriophage lambda genome.

A program system for nucleic acid sequence analysis has been developed. The detection and prediction of secondary structures in nucleic acids have been especially emphasized. The system is able to handle most of the common problems found with nucleic acid sequencing like testing homologies, searching for reading frames and signals etc., but in addition it is able to locate and predict secondary structures. The predicted structures can either be printed on normal line printers or displayed on drawing devices like plotters or video screens. Another special feature is the data base-like handling of consensus sequence matrices by the programs DYCOM and EAGLE. Detailed descriptions of the programs have been published elsewhere (Stüber, 1985, 1986).

Several interactive Pascal programs have been written for the analysis and display of structural information in nucleic acid sequences. Layout procedures were developed to display the homology and repeat matrices of a sequence and to predict and display the secondary structure of RNA/DNA molecules free of overlap and to predict and display internal repeats. No special plotting devices are required because the output is adapted to line printers. Sequences from several DNA database systems can be used as input. These programs are part of a general nucleic acid sequence analysis package.