Titre : | Development of a bioinformatics tool to predict the impact of genetic variations on splicing (abstract : congrès international de Myologie, 2005) |
contenu dans : | |
Auteurs : | Congrès international de myologie 2005 (International Congress of Myology 2005; 9-13 mai 2005; Nantes, France) ; Martin N ; Dutertre M ; Auboeuf D |
Type de document : | Article |
Année de publication : | 2005 |
Pages : | p. 96 |
Langues: | Anglais |
Mots-clés : | ARN ; ARN messager ; bioinformatique ; colloque ; épissage alternatif ; génétique moléculaire ; génome ; mutation génétique ; séquençage |
Résumé : |
Communication n° 688. Introduction : Important efforts are currently done to identify mutations associated with genetic neuromuscular diseases. Classically, most of the interest is focused in the coding regions of the genes, even if we know that the genes sequences contain information that plays an important role in splicing, a process by which introns are removed from primary transcripts to give rise to mature RNAs. It is widely accepted that recognition of splicing sites is regulated by nearby sequences: splicing regulatory sequences. Such sequences regulate in particular alternative splicing, a process that allows the production of different mRNAs from a single gene. We know that mutations in such sequences can be responsible of different neuromuscular diseases. Objectives : To develop bioinformatics tools that will allow predicting if genetic variants identified in patients can affect the splicing of the gene products. Methods : In a first step I have made a database named FAST DB ("Friendly Alternative Splicing and Transcripts DataBase"), which gathers all the splicing variants of the human gene products. Once data was recovered from public databases ("human may 2004 (hg17) assembly", UCSC, Genebank, etc), FAST DB program analyzed each gene, to define exons and splicing events based on very strict criteria. This database is helping me in the development of other bioinformatics tools that will predict if a given mutation can be responsible of splicing defects of a gene. Results : FAST DB not only serves as a base for the development of other tools, as mentioned in the methods section, but it represents an excellent tool itself. For each human gene, a clear and complete data presentation allows to precisely and clearly visualize its genomic organization and all the different alternative splicing events that produce different transcripts. I am currently developing a new tool that will allow researchers to input a mutated sequence from a given gene in order to graphically localize this mutation in the gene structure to ascertain if a mutation is within a splicing site or within an alternative splicing regulated region. In parallel, I am developing a tool to identify splicing regulatory sequences within regions affected by alternative splicing. Thanks to these tools and to the alignment of the mutated sequence against "potential" splicing regulatory sequences, researchers will be able to predict if a mutation can affect splicing. Conclusions : Our bioinformatics tools will allow predicting the impact of a mutation on the splicing of gene products for a full profitability of genetic screening, avoiding the exclusion of genetic variants that do not affect coding sequences. |