Combined Computational-Experimental Analyses of CFTR Exon Strength Uncover Predictability of Exon-Skipping Level. - Archive ouverte HAL Accéder directement au contenu
Article Dans Une Revue Human Mutation Année : 2013

Combined Computational-Experimental Analyses of CFTR Exon Strength Uncover Predictability of Exon-Skipping Level.

Résumé

With the increased number of identified nucleotide sequence variations in genes, the current challenge is to classify them as disease causing or neutral. These variants of unknown clinical significance can alter multiple processes, from gene transcription to RNA splicing or protein function. Using an approach combining several in silico tools, we identified some exons presenting weaker splicing motifs than other exons in the Cystic Fibrosis Transmembrane conductance Regulator (CFTR) gene. These exons exhibit higher rates of basal skipping than exons harboring no identifiable weak splicing signals using minigene assays. We then screened 19 described mutations in three different exons, and identified exon-skipping substitutions. These substitutions induced higher skipping levels in exons having one or more weak splicing motifs. Indeed, this level remained under 2% for exons with strong splicing motifs and could reach 40% for exons having at least one weak motif. Further analysis revealed a functional exon splicing enhancer within exon 3 that was associated with the SR protein SF2/ASF and whose disruption induced exon skipping. Exon skipping was confirmed in vivo in two nasal epithelial cell brushing samples. Our approach, which point out exons with some splicing signals weaknesses, will help spot splicing mutations of clinical relevance.
Fichier principal
Vignette du fichier
Table_humu-2012-0105.R3.pdf (19.19 Ko) Télécharger le fichier
Aissat_humu_2013_Hal.pdf (113.18 Ko) Télécharger le fichier
Supp_Mat-humu-2012-0105.R3.doc (1.17 Mo) Télécharger le fichier
Supp_Mat-humu-2012-0105.R3.pdf (825.53 Ko) Télécharger le fichier
Origine : Fichiers produits par l'(les) auteur(s)
Origine : Fichiers produits par l'(les) auteur(s)
Format : Autre
Format : Autre
Loading...

Dates et versions

inserm-00797975 , version 1 (01-02-2014)

Identifiants

Citer

Abdel Aissat, Alix de Becdelièvre, Lisa Golmard, Christian Vasseur, Catherine Costa, et al.. Combined Computational-Experimental Analyses of CFTR Exon Strength Uncover Predictability of Exon-Skipping Level.. Human Mutation, 2013, 34 (6), pp.873-81. ⟨10.1002/humu.22300⟩. ⟨inserm-00797975⟩
1046 Consultations
972 Téléchargements

Altmetric

Partager

Gmail Facebook X LinkedIn More