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In silico screening based on predictive algorithms as a design tool for exon skipping oligonucleotides in Duchenne muscular dystrophy.

Echigoya Y, Mouly V, Garcia L, Yokota T, Duddy W - PLoS ONE (2015)

Bottom Line: Previous DMD data were compiled together and, for each oligonucleotide, some 60 descriptors were considered.Statistical modelling approaches were applied to derive algorithms that predict exon skipping for a given target site.We confirmed (1) the binding energetics of the oligonucleotide to the RNA, and (2) the distance in bases of the target site from the splice acceptor site, as the two most predictive parameters, and we included these and several other parameters (while discounting many) into an in silico screening process, based on their capacity to predict high or low efficacy in either phosphorodiamidate morpholino oligomers (89% correctly predicted) and/or 2'O Methyl RNA oligonucleotides (76% correctly predicted).

View Article: PubMed Central - PubMed

Affiliation: University of Alberta, Faculty of Medicine and Dentistry, Department of Medical Genetics, Edmonton, Alberta, Canada.

ABSTRACT
The use of antisense 'splice-switching' oligonucleotides to induce exon skipping represents a potential therapeutic approach to various human genetic diseases. It has achieved greatest maturity in exon skipping of the dystrophin transcript in Duchenne muscular dystrophy (DMD), for which several clinical trials are completed or ongoing, and a large body of data exists describing tested oligonucleotides and their efficacy. The rational design of an exon skipping oligonucleotide involves the choice of an antisense sequence, usually between 15 and 32 nucleotides, targeting the exon that is to be skipped. Although parameters describing the target site can be computationally estimated and several have been identified to correlate with efficacy, methods to predict efficacy are limited. Here, an in silico pre-screening approach is proposed, based on predictive statistical modelling. Previous DMD data were compiled together and, for each oligonucleotide, some 60 descriptors were considered. Statistical modelling approaches were applied to derive algorithms that predict exon skipping for a given target site. We confirmed (1) the binding energetics of the oligonucleotide to the RNA, and (2) the distance in bases of the target site from the splice acceptor site, as the two most predictive parameters, and we included these and several other parameters (while discounting many) into an in silico screening process, based on their capacity to predict high or low efficacy in either phosphorodiamidate morpholino oligomers (89% correctly predicted) and/or 2'O Methyl RNA oligonucleotides (76% correctly predicted). Predictions correlated strongly with in vitro testing for sixteen de novo PMO sequences targeting various positions on DMD exons 44 (R² 0.89) and 53 (R² 0.89), one of which represents a potential novel candidate for clinical trials. We provide these algorithms together with a computational tool that facilitates screening to predict exon skipping efficacy at each position of a target exon.

No MeSH data available.


Related in: MedlinePlus

Screening across exons for predicted exon skipping and comparison with published data (from [29]).Distance from acceptor is given for the first (5’-most) base of the target site. Observed and predicted percentage skipping are shown for 30-mer and 25-mer oligonucleotides, with moving averages shown over 15 and 13 bases, respectively (in this way, the moving average indicates the value for the mid-point of each target site).
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pone.0120058.g003: Screening across exons for predicted exon skipping and comparison with published data (from [29]).Distance from acceptor is given for the first (5’-most) base of the target site. Observed and predicted percentage skipping are shown for 30-mer and 25-mer oligonucleotides, with moving averages shown over 15 and 13 bases, respectively (in this way, the moving average indicates the value for the mid-point of each target site).

Mentions: To visualize trends in predicted efficacy and to compare the predicted with the observed efficacy we created an in silico screening tool (see materials and methods) and applied it across the exons tested in the Popplewell study (Fig. 3), calculating predicted efficacy for 25-mers and 30-mers at every possible target position. Conformity to the model was most notable in the diminishing of efficacy with distance from the acceptor site, except when strong dG of binding counteracted this effect, as for bases 80 to 110 of exon 46. Skipping (both observed and predicted) was generally more effective in exons belonging to Malueka splice type C (exons 44 and 46), than those of type A (45, 51 and 53), especially towards the donor site end of the exon.


In silico screening based on predictive algorithms as a design tool for exon skipping oligonucleotides in Duchenne muscular dystrophy.

Echigoya Y, Mouly V, Garcia L, Yokota T, Duddy W - PLoS ONE (2015)

Screening across exons for predicted exon skipping and comparison with published data (from [29]).Distance from acceptor is given for the first (5’-most) base of the target site. Observed and predicted percentage skipping are shown for 30-mer and 25-mer oligonucleotides, with moving averages shown over 15 and 13 bases, respectively (in this way, the moving average indicates the value for the mid-point of each target site).
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4376395&req=5

pone.0120058.g003: Screening across exons for predicted exon skipping and comparison with published data (from [29]).Distance from acceptor is given for the first (5’-most) base of the target site. Observed and predicted percentage skipping are shown for 30-mer and 25-mer oligonucleotides, with moving averages shown over 15 and 13 bases, respectively (in this way, the moving average indicates the value for the mid-point of each target site).
Mentions: To visualize trends in predicted efficacy and to compare the predicted with the observed efficacy we created an in silico screening tool (see materials and methods) and applied it across the exons tested in the Popplewell study (Fig. 3), calculating predicted efficacy for 25-mers and 30-mers at every possible target position. Conformity to the model was most notable in the diminishing of efficacy with distance from the acceptor site, except when strong dG of binding counteracted this effect, as for bases 80 to 110 of exon 46. Skipping (both observed and predicted) was generally more effective in exons belonging to Malueka splice type C (exons 44 and 46), than those of type A (45, 51 and 53), especially towards the donor site end of the exon.

Bottom Line: Previous DMD data were compiled together and, for each oligonucleotide, some 60 descriptors were considered.Statistical modelling approaches were applied to derive algorithms that predict exon skipping for a given target site.We confirmed (1) the binding energetics of the oligonucleotide to the RNA, and (2) the distance in bases of the target site from the splice acceptor site, as the two most predictive parameters, and we included these and several other parameters (while discounting many) into an in silico screening process, based on their capacity to predict high or low efficacy in either phosphorodiamidate morpholino oligomers (89% correctly predicted) and/or 2'O Methyl RNA oligonucleotides (76% correctly predicted).

View Article: PubMed Central - PubMed

Affiliation: University of Alberta, Faculty of Medicine and Dentistry, Department of Medical Genetics, Edmonton, Alberta, Canada.

ABSTRACT
The use of antisense 'splice-switching' oligonucleotides to induce exon skipping represents a potential therapeutic approach to various human genetic diseases. It has achieved greatest maturity in exon skipping of the dystrophin transcript in Duchenne muscular dystrophy (DMD), for which several clinical trials are completed or ongoing, and a large body of data exists describing tested oligonucleotides and their efficacy. The rational design of an exon skipping oligonucleotide involves the choice of an antisense sequence, usually between 15 and 32 nucleotides, targeting the exon that is to be skipped. Although parameters describing the target site can be computationally estimated and several have been identified to correlate with efficacy, methods to predict efficacy are limited. Here, an in silico pre-screening approach is proposed, based on predictive statistical modelling. Previous DMD data were compiled together and, for each oligonucleotide, some 60 descriptors were considered. Statistical modelling approaches were applied to derive algorithms that predict exon skipping for a given target site. We confirmed (1) the binding energetics of the oligonucleotide to the RNA, and (2) the distance in bases of the target site from the splice acceptor site, as the two most predictive parameters, and we included these and several other parameters (while discounting many) into an in silico screening process, based on their capacity to predict high or low efficacy in either phosphorodiamidate morpholino oligomers (89% correctly predicted) and/or 2'O Methyl RNA oligonucleotides (76% correctly predicted). Predictions correlated strongly with in vitro testing for sixteen de novo PMO sequences targeting various positions on DMD exons 44 (R² 0.89) and 53 (R² 0.89), one of which represents a potential novel candidate for clinical trials. We provide these algorithms together with a computational tool that facilitates screening to predict exon skipping efficacy at each position of a target exon.

No MeSH data available.


Related in: MedlinePlus