Out-licensing

Development of the MAPPER Platform for the Identification of Transcription Factor Binding Sites

Introduction/Background

A substantial portion of human phenotypic variation may be due to the effects of genetic polymorphism on gene expression. Currently, there are no effective tools available to identify and explore polymorphism effecting transcriptional regulation of genes. Algorithms to predict transcription factor binding sites are suboptimal and poorly integrated into effective platforms to explore and mine such information.

Aims/Hypothesis

A novel tool is required to identify and explore polymorphism effecting transcriptional regulation of genes.

Research

MAPPER is a web-based platform for the exploration of polymorphism is transcription factor binding sites. Using a hidden Markov model-(HMM-) based method for identifying transcription factor binding sites, MAPPER has been used to generate a database of binding sites flanking all known genes in the human, mouse, fly, worm and yeast genomes. The data is available for exploration and analysis through a web interface, allowing the user to search and display of the transcription factor binding sites and to drill-down to annotation of the neighbouring genes.

HMM-based detection is a more accurate probabilistic method for predicting binding sites than existing nucleotide-weighted matrix-based methods, allowing for compensation for insertions and deletions and allowing for matches to fragments of the whole binding site. Tests of MAPPER versus the existing programs show higher or equivalent identification of authentic sites with significantly lower false positives. Using HMM-based algorithms also allow better statistical description of the results. HMM-based site prediction has been reported of individual transcription factors. MAPPER is the first genome-wide application of HMM-based binding sites, and certainly one of the most user-friendly interfaces to the data.

The MAPPER interface available to academic and non-commercial users via an Internet interface. Since its release in January, on-line usage of MAPPER has grown to about 500 unique users each month.

Conclusion

We have developed a search engine for the computational identification of putative transcription factor binding sites in multiple genomes.

Relevance/Opportunity

Licenses are available for commercial use of MAPPER, through the on-line interface, for local installation, for use in commercial services or for adaptation to commercial analysis packages. Please enquire quoting reference no. CMCC 1402.

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