The Alternative Splicing Mutation Database: a hub for investigations of alternative splicing using mutational evidence.

BACKGROUND: Some mutations in the internal regions of exons occur within splicing enhancers and silencers, influencing the pattern of alternative splicing in the corresponding genes. To understand how these sequence changes affect splicing, we created a database of these mutations. FINDINGS: The Alternative Splicing Mutation Database (ASMD) serves as a repository for all exonic mutations not associated with splicing junctions that measurably change the pattern of alternative splicing. In this initial published release (version 1.2), only human sequences are present, but the ASMD will grow to include other organisms, (see Availability and requirements section for the ASMD web address).This relational database allows users to investigate connections between mutations and features of the surrounding sequences, including flanking sequences, RNA secondary structures and strengths of splice junctions. Splicing effects of the mutations are quantified by the relative presence of alternative mRNA isoforms with and without a given mutation. This measure is further categorized by the accuracy of the experimental methods employed. The database currently contains 170 mutations in 66 exons, yet these numbers increase regularly.We developed an algorithm to derive a table of oligonucleotide Splicing Potential (SP) values from the ASMD dataset. We present the SP concept and tools in detail in our corresponding article. CONCLUSION: The current data set demonstrates that mutations affecting splicing are located throughout exons and might be enriched within local RNA secondary structures. Exons from the ASMD have below average splicing junction strength scores, but the difference is small and is judged not to be significant.

Calculation of splicing potential from the Alternative Splicing Mutation Database.

BACKGROUND: The Alternative Splicing Mutation Database (ASMD) presents a collection of all known mutations inside human exons which affect splicing enhancers and silencers and cause changes in the alternative splicing pattern of the corresponding genes. FINDINGS: An algorithm was developed to derive a Splicing Potential (SP) table from the ASMD information. This table characterizes the influence of each oligonucleotide on the splicing effectiveness of the exon containing it. If the SP value for an oligonucleotide is positive, it promotes exon retention, while negative SP values mean the sequence favors exon skipping. The merit of the SP approach is the ability to separate splicing signals from a wide range of sequence motifs enriched in exonic sequences that are attributed to protein-coding properties and/or translation efficiency. Due to its direct derivation from observed splice site selection, SP has an advantage over other computational approaches for predicting alternative splicing. CONCLUSION: We show that a vast majority of known exonic splicing enhancers have highly positive cumulative SP values, while known splicing silencers have core motifs with strongly negative cumulative SP values. Our approach allows for computation of the cumulative SP value of any sequence segment and, thus, gives researchers the ability to measure the possible contribution of any sequence to the pattern of splicing.

Genomic mid-range inhomogeneity correlates with an abundance of RNA secondary structures.

BACKGROUND: Genomes possess different levels of non-randomness, in particular, an inhomogeneity in their nucleotide composition. Inhomogeneity is manifest from the short-range where neighboring nucleotides influence the choice of base at a site, to the long-range, commonly known as isochores, where a particular base composition can span millions of nucleotides. A separate genomic issue that has yet to be thoroughly elucidated is the role that RNA secondary structure (SS) plays in gene expression. RESULTS: We present novel data and approaches that show that a mid-range inhomogeneity (~30 to 1000 nt) not only exists in mammalian genomes but is also significantly associated with strong RNA SS. A whole-genome bioinformatics investigation of local SS in a set of 11,315 non-redundant human pre-mRNA sequences has been carried out. Four distinct components of these molecules (5'-UTRs, exons, introns and 3'-UTRs) were considered separately, since they differ in overall nucleotide composition, sequence motifs and periodicities. For each pre-mRNA component, the abundance of strong local SS (< -25 kcal/mol) was a factor of two to ten greater than a random expectation model. The randomization process preserves the short-range inhomogeneity of the corresponding natural sequences, thus, eliminating short-range signals as possible contributors to any observed phenomena. CONCLUSION: We demonstrate that the excess of strong local SS in pre-mRNAs is linked to the little explored phenomenon of genomic mid-range inhomogeneity (MRI). MRI is an interdependence between nucleotide choice and base composition over a distance of 20-1000 nt. Additionally, we have created a public computational resource to support further study of genomic MRI.