Abstract
Effective splice site selection is critically controlled by flanking splicing regulatory elements (SREs) that can enhance or repress splice site use. Although several computational algorithms currently identify a multitude of potential SRE motifs, their predictive power with respect to mutation effects is limited. Following a RESCUE-type approach, we defined a hexamer-based 'HEXplorer score' as average Z-score of all six hexamers overlapping with a given nucleotide in an arbitrary genomic sequence. Plotted along genomic regions, HEXplorer score profiles varied slowly in the vicinity of splice sites. They reflected the respective splice enhancing and silencing properties of splice site neighborhoods beyond the identification of single dedicated SRE motifs. In particular, HEXplorer score differences between mutant and reference sequences faithfully represented exonic mutation effects on splice site usage. Using the HIV-1 pre-mRNA as a model system highly dependent on SREs, we found an excellent correlation in 29 mutations between splicing activity and HEXplorer score. We successfully predicted and confirmed five novel SREs and optimized mutations inactivating a known silencer. The HEXplorer score allowed landscaping of splicing regulatory regions, provided a quantitative measure of mutation effects on splice enhancing and silencing properties and permitted calculation of the mutationally most effective nucleotide.