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Open Access Data Note

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

Jason M Bechtel1, Preeti Rajesh23, Irina Ilikchyan4, Ying Deng5, Pankaj K Mishra2, Qi Wang5, Xiaochun Wu2, Kirill A Afonin4, William E Grose2, Ye Wang4, Sadik Khuder16 and Alexei Fedorov16*

Author Affiliations

1 Program in Bioinformatics and Proteomics/Genomics, University of Toledo Health Science Campus, Toledo, Ohio 43614, USA

2 Dept. of Medical Microbiology and Immunology, University of Toledo Health Science Campus, Toledo, Ohio 43614, USA

3 Dept. of Basic Pharmaceutical Sciences, South Carolina College of Pharmacy, University of South Carolina, Columbia, South Carolina 29208, USA

4 Department of Biological Sciences, Bowling Green State University, Bowling Green, Ohio 43403, USA

5 College of Engineering, University of Toledo, Toledo, Ohio 43606, USA

6 Dept. of Medicine, University of Toledo Health Science Campus, Toledo, Ohio 43614, USA

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BMC Research Notes 2008, 1:3  doi:10.1186/1756-0500-1-3

Published: 26 February 2008

Abstract

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.