Analysis of tissue-specificity in unintended off-target occurrences for ASO therapeutics

Poster presented on Sept. 18, 2024 by Nathalie Gocht at 23rd European Conference on Computational Biology, Turku, Finland.

Abstract: Antisense oligos (ASO) are used in oligo therapeutics to treat rare, chronic, genetic diseases. The most common mechanism is RNase H1 mediated knockdown of mRNA targets. The current challenge in the field is the understanding of factors for efficacy of ASOs. Research has show that ASO activity can be improved by administering a nontargeting ASO which suggests the existence a nonproductive bulk uptake pathway in the cell. Therefore, we look at unintended off-targets, sequences to which the ASO can bind with low specificity and lower affinity, in the mRNA environment in the cell effecting the target knockdown. We also think that the differences in gene expression profiles of different tissues are preserved in tissue-specific k-mer environments. Searching for unintended off-targets in the mRNA environment of a tissue is a non-trivial task due to the high mRNA abundance. Our algorithm samples k-mers from RNAseq data according to their frequencies. This sampled set is completed by off-target sites searched in the RNAseq data with high similarity to the target site. Binding energies between candidate oligos and off-targets are calculated using RNAcofold. The extracted off-target profile shows the k-mer abundance at different ddG levels for a specific oligo and tissue. We evaluated the off-target profiles with a kinetic model for RNase H1 mediated knockdown predicting the potential knockdown for the oligo including off-targets. For DNADNA and RNA-RNA parameters, the observation suggest little impact on ASO efficacy, while for RNA-DNA parameter the change in knockdown increases significantly for many oligos.

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