ASOG: AntiSense Oligonucleotide Generator

Antisense oligonucleotides (ASOs) are used in both fundamental research and clinical applications to modulate gene expression by targeting the RNA transcript of specific genes. Historically, ASOs were designed manually, a time-consuming process that limited exhaustive searches through the ASO space. More recently, resources have been developed based on traditional or deep learning approaches to facilitate ASO design, each with their specific use cases and limitations. In this context, we propose an original and generalistic pipeline for ASO design, based on explicit criteria, original algorithms, and third-party software, encapsulated in a web application we named AntiSense Oligonucleotide Generator (ASOG). The ASOG pipeline requires only a target gene sequence as input, and it proceeds with ASO generation, predicts the structural properties of target subsequences, predicts splice site masking, detects off-target effects, and computes thermodynamic hybridization parameters, taking into account some of the most common RNA modifications. ASOG is designed to enable users to quickly navigate the ASO space, assisting them in making informed decisions. The ASOG webserver is available at asog.iecb.u-bordeaux.fr.

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Publication Details

Journal
Computational and Structural Biotechnology Journal
Published
2025-01-01
DOI
https://doi.org/10.1016/j.csbj.2025.09.022
Primary Topic
RNA Interference and Gene Delivery
Type
article
Field-Weighted Citation Impact
0.00

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article

ASOG: AntiSense Oligonucleotide Generator

Brune Vialet, Florian Malard, Philippe Barthélémy, Sébastien Campagne et al.
Computational and Structural Biotechnology Journal
RNA Interference and Gene Delivery
article

ASOG: AntiSense Oligonucleotide Generator

Brune Vialet, Florian Malard, Philippe Barthélémy, Sébastien Campagne, Jonah Kimi, Patricia Korczak, Eric Roubin
article en

Abstract

Antisense oligonucleotides (ASOs) are used in both fundamental research and clinical applications to modulate gene expression by targeting the RNA transcript of specific genes. Historically, ASOs were designed manually, a time-consuming process that limited exhaustive searches through the ASO space. More recently, resources have been developed based on traditional or deep learning approaches to facilitate ASO design, each with their specific use cases and limitations. In this context, we propose an original and generalistic pipeline for ASO design, based on explicit criteria, original algorithms, and third-party software, encapsulated in a web application we named AntiSense Oligonucleotide Generator (ASOG). The ASOG pipeline requires only a target gene sequence as input, and it proceeds with ASO generation, predicts the structural properties of target subsequences, predicts splice site masking, detects off-target effects, and computes thermodynamic hybridization parameters, taking into account some of the most common RNA modifications. ASOG is designed to enable users to quickly navigate the ASO space, assisting them in making informed decisions. The ASOG webserver is available at asog.iecb.u-bordeaux.fr.

Computational and Structural Biotechnology JournalVol. 27
Centre National de la Recherche Scientifique (FR), Université de Bordeaux (FR), Inserm (FR), Bordeaux Population Health (FR), Institut Européen de Chimie et Biologie (FR)
Institut National de la Santé et de la Recherche Médicale, Fondation pour la Recherche Médicale
Openalex Percentile: Top 78%
RNA Interference and Gene Delivery
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ASOG: AntiSense Oligonucleotide Generator — Brune Vialet, Florian Malard, et al. · Computational and Structural Biotechnology Journal (2025) | TGRS Research Map | TGRS