Human molecular genetics · 2015
The molecular basis of variable phenotypic severity among common missense mutations causing Rett syndrome.
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Brown Kyla, Selfridge Jim, Lagger Sabine, Connelly John, De Sousa Dina, Kerr Alastair, Webb Shaun, Guy Jacky, Merusi Cara, Koerner Martha V, Bird Adrian
Аннотация
Rett syndrome is caused by mutations in the X-linked MECP2 gene, which encodes a chromosomal protein that binds to methylated DNA. Mouse models mirror the human disorder and therefore allow investigation of phenotypes at a molecular level. We describe an Mecp2 allelic series representing the three most common missense Rett syndrome (RTT) mutations, including first reports of Mecp2[R133C] and Mecp2[T158M] knock-in mice, in addition to Mecp2[R306C] mutant mice. Together these three alleles comprise ∼25% of all RTT mutations in humans, but they vary significantly in average severity. This spectrum is mimicked in the mouse models; R133C being least severe, T158M most severe and R306C of intermediate severity. Both R133C and T158M mutations cause compound phenotypes at the molecular level, combining compromised DNA binding with reduced stability, the destabilizing effect of T158M being more severe. Our findings contradict the hypothesis that the R133C mutation exclusively abolishes binding to hydroxymethylated DNA, as interactions with DNA containing methyl-CG, methyl-CA and hydroxymethyl-CA are all reduced in vivo. We find that MeCP2[T158M] is significantly less stable than MeCP2[R133C], which may account for the divergent clinical impact of the mutations. Overall, this allelic series recapitulates human RTT severity, reveals compound molecular aetiologies and provides a valuable resource in the search for personalized therapeutic interventions.
Предметные рубрики MeSH
AllelesAmino Acid SubstitutionAnimalsDNADNA MethylationDisease Models, AnimalGene Expression RegulationGene Knock-In TechniquesHumansMaleMethyl-CpG-Binding Protein 2MiceMice, TransgenicModels, MolecularMutation, MissensePhenotypeProtein BindingRett SyndromeSeverity of Illness IndexSignal TransductionSurvival Analysis