Abstracts
Résumé
Les anomalies de l’épissage, et plus largement de la transcription, sont fréquemment sous les feux de l’actualité scientifique et médicale. On observe, notamment, un flot croissant de publications concernant l’impact des modifications nucléotidiques de signification inconnue sur l’épissage. Parallèlement, se développent des outils de bio-informatique destinés à identifier les séquences contrôlant la transcription et à prédire leurs altérations. Cet engouement est motivé par la nature variée et complexe des anomalies de la transcription qui sont, de fait, difficiles à appréhender dans le cadre du diagnostic. La problématique diagnostique est, en effet, bien distincte de celle de la recherche, où les analyses sont généralement faites sur des cas isolés ou de petites séries, sans date limite, ni même nécessité de rendu de résultats. Le diagnostic en génétique moléculaire se fait sur de grandes séries, avec des délais de réalisation, et le résultat est utilisé pour le conseil génétique et le suivi médical du patient. Il s’agit donc, pour le biologiste, de relever le défi de la complexité et de le concilier avec la finalité diagnostique, c’est-à-dire le résultat attendu pour le patient. Nous présentons dans cet article les différents mécanismes de la transcription intéressant le cadre diagnostique, puis les approches à envisager pour identifier les anomalies, avant de conclure sur les évolutions à prévoir.
Summary
There is a rapidly growing literature on transcription abnormalities, e.g. differential expression of alleles and the role of some single nucleotide polymorphisms in altering splicing patterns. An average 10 % of splicing mutations is reported in the Human Gene Mutation Database but this figure could climb to 50 % for some genes such as NF1 or ATM. This paper therefore aims at clarifying some important aspects of transcriptional abnormalities in genetic testing. The main types of alterations are presented, i.e. exonic, intronic and promoter modifications that could modify or create consensus motif and/or secondary structures. DNA, RNA based-diagnostic strategies and in silico tools are then presented and their performances and limitations outlined to build up a picture of the current state of the art.
Appendices
Références
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