Abstract
The exon recognition and removal of introns (splicing) from pre-mRNA is a crucial step in the gene expression flow. The process is very complex and therefore susceptible to derangements. Not surprisingly, a significant and still underestimated proportion of disease-causing mutations affects splicing, with those occurring at the 5’ splice site (5’ss) being the most severe ones. This led to the development of a correction approach based on variants of the spliceosomal U1snRNA, which has been proven on splicing mutations in several cellular and mouse models of human disease. Since the alternative splicing mechanisms are strictly related to the sequence context of the exon, we challenged the U1snRNA-mediated strategy in the singular model of the exon 5 of coagulation factor (F)VIII gene (F8) in which the authentic 5’ss is surrounded by various cryptic 5’ss. This scenario is further complicated in the presence of nucleotide changes associated with FVIII deficiency (Haemophilia A), which weaken the authentic 5’ss and create/strengthen cryptic 5’ss. We focused on the splicing mutations (c.602-32A > G, c.602-10T > G, c.602G > A, c.655G > A, c.667G > A, c.669A > G, c.669A > T, c.670G > T, c.670+1G > T, c.670+1G > A, c.670+2T > G, c.670+5G > A, and c.670+6T > C) found in patients with severe to mild Haemophilia A. Minigenes expression studies demonstrated that all mutations occurring within the 5’ss, both intronic or exonic, lead to aberrant transcripts arising from the usage of two cryptic intronic 5’ss at positions c.670+64 and c.670+176. For most of them, the observed proportion of correct transcripts is in accordance with the coagulation phenotype of patients. In co-transfection experiments, we identified a U1snRNA variant targeting an intronic region downstream of the defective exon (Exon Specific U1snRNA, U1sh7) capable to re-direct usage of the proper 5’ss (∼80%) for several mutations. However, deep investigation of rescued transcripts from +1 and +2 variants revealed only the usage of adjacent cryptic 5’ss, leading to frameshifted transcript forms. These data demonstrate that a single ExSpeU1 can efficiently rescue different mutations in the F8 exon 5, and provide the first evidence of the applicability of the U1snRNA-based approach to Haemophilia A.
Highlights
In higher eukaryotes, the information necessary for protein synthesis is scattered across the gene, where the coding segments represent a minor proportion
This is difficult for nucleotide changes that, being at the exon-intron boundaries or within introns, are candidate to affect splicing since their precise effect is hardly predictable by computational tools
The experimental evaluation of the impact of nucleotide changes on splicing is mandatory to help diagnosis and counseling. We addressed this issue in a singular gene context, namely the F8 exon 5, where various exonic changes and multiple cryptic 5’ss are respectively located within or in the proximity of the authentic 5’ss, complicating the selection of the right one
Summary
The information necessary for protein synthesis is scattered across the gene, where the coding segments (exons) represent a minor proportion. The exon recognition and the removal of the non-coding sequences (introns) from pre-mRNA are essential for proper gene expression, and this process (splicing) is carried out by a huge macromolecular complex named spliceosome. Nucleotide changes occurring at the 5’ss, by interfering with its recognition and eventually leading to aberrant splicing events, are commonly associated with severe clinical phenotypes and are widely (9%) reported in human inherited diseases (http://www.hgmd.org/). This information led us to develop a correction strategy based on U1snRNAs variants designed to restore the complementarity with the mutated 5’ss (compensatory U1snRNA) (Pinotti et al, 2009). The efficacy has been proven both in several cellular (Glaus et al, 2011; Schmid et al, 2011; Balestra et al, 2015; van der Woerd et al, 2015; Dal Mas et al, 2015a; Dal Mas et al, 2015b; Rogalska et al, 2016; Tajnik et al, 2016; Scalet et al, 2017; Scalet et al, 2018; Balestra et al, 2019; Balestra and Branchini, 2019; Scalet et al, 2019) and animal (Balestra et al, 2014; Balestra et al, 2016; Rogalska et al, 2016; Donadon et al, 2018b; Donadon et al, 2019; Lin et al, 2019) models of human disease
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