Human Genetics

, Volume 109, Issue 1, pp 73–84 | Cite as

Analysis of splicing parameters in the dystrophin gene: relevance for physiological and pathogenetic splicing mechanisms

  • Manuela Sironi
  • Uberto Pozzoli
  • Rachele Cagliani
  • Giacomo P. Comi
  • Alessandra Bardoni
  • Nereo Bresolin
Original Investigation

Abstract.

The molecular mechanisms that direct splice-site selection and assure orderly exon juxtaposition have not been fully clarified. The extraordinary nature of the dystrophin gene points to several hurdles in the processing of transcripts. In this study, dystrophin statistical and thermodynamic splicing parameters have been evaluated providing the first comprehensive description for a single human gene. We show that concomitant use of consensus values (CV) and ΔDG°37 values for U1snRNA annealing better discriminates between real donor sites and donor-like sequences. Evidence is also provided that, on average, out-of-frame dystrophin exons have significantly stronger CVs and more favorable ΔDG°37 values; this feature has never been reported and might reflect evolutionary-driven minimization of out-of-frame exon misplicing. Dystrophin splicing mutations have been reported to determine either Duchenne or Becker Muscular Dystrophy, but no comprehensive genotypic/phenotypic correlation has ever been investigated. We have analyzed splicing affecting single base-pair substitutions in the dystrophin gene with respect to their effect on splicing parameters; functional and clinical consequences are also reported. We have found 5'-splice-site mutation occurrence to be statistically related to mutability quotients and propose the use of ΔDG°37 values as a more effective tool than CV alone to describe donor site mutation consequences. Our analysis also indicates a nearly 100% correlation between clinical phenotype and the reading-frame rule determined at the RNA level. We consider that elucidation of the relative importance of splicing determinants might help to clarify the molecular mechanisms that direct correct splicing in complex genes and might be useful in the validation of predictive models.

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Copyright information

© Springer-Verlag 2001

Authors and Affiliations

  • Manuela Sironi
    • 1
  • Uberto Pozzoli
    • 1
  • Rachele Cagliani
    • 1
  • Giacomo P. Comi
    • 2
  • Alessandra Bardoni
    • 1
  • Nereo Bresolin
    • 1
  1. 1.IRCCS E. Medea, Associazione La Nostra Famiglia, Via Don Luigi Monza 20, 23842 Bosisio Parini (LC), ItalyItaly
  2. 2.Centro Dino Ferrari, Istituto di Clinica Neurologica, Università di Milano, IRCCS Ospedale Maggiore Policlinico, Milan, ItalyItaly

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