Back

Protein expression is amplified by stabilizing mRNA using gene-specific antisense oligonucleotides

Boros, B. D.; Nambiar, A.; Hu, M.; Galloway, D.; Florian, C. P.; Jungers, C. F.; Dougherty, J. D.; Schoch, K. M.; Djuranovic, S.; Miller, T. M.

2026-09-17 molecular biology
10.64898/2026.09.14.749961 bioRxiv
Show abstract

Effective and safe strategies to restore gene expression in haploinsufficiency disorders or to augment protective protein signaling have long been attractive but challenging therapeutic goals. Here, we demonstrate the potential of antisense oligonucleotides (ASOs) to upregulate gene targets through mRNA stabilization. The 3 untranslated regions (UTRs) of mRNAs regulate stability via activating and repressive elements. One prominent destabilizing cis-element found in ~30% of transcripts is the Pumilio RNA-binding protein recognition element (PRE), which can be targeted to enable gene-specific protein upregulation. A scan for PREs highlights hundreds of disease-relevant transcripts that may be targetable via ASO-mediated gene-specific blocking of Pumilio binding. We show that masking specific PREs with ASOs produces sustained protein upregulation through mRNA stabilization using multiple reporter and endogenous gene targets. Using PRE-masking ASOs, we neutralized PRE-mediated destabilization of TANK-binding kinase-1 (TBK1) mRNA and restored TBK1 protein expression in participant-derived fibroblasts with TBK1 haploinsufficiency, causal for amyotrophic lateral sclerosis. Additionally, by targeting PRE sites in the myoprotective gene follistatin (FST), we achieved effective FST mRNA upregulation in tested mouse tissues. These findings suggest that ASO strategies that neutralize destabilizing 3UTR sequences like PREs may provide a powerful approach to upregulate haploinsufficiency-related genes or enhance protective protein levels for therapeutic benefit.

Matching journals

The top 3 journals account for 50% of the predicted probability mass.

50% of probability mass above

"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.