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Updated: Sep 18, 2025

Author Spotlight: A Computational Pipeline for Analyzing Chimeric Noncoding RNA-Target RNA Interactions in High-Throughput Sequencing Data
Published on: December 1, 2023
Systematic analysis of siRNA and mRNA features impacting fully chemically modified siRNA efficacy
Sarah M Davis1, Samuel Hildebrand1, Hannah J MacMillan1
1Morningside Graduate School of Biomedical Sciences, T.H. Chan School of Medicine, Interdisciplinary Graduate Program, RNA Therapeutics Institute, Program in Molecular Medicine, Systems Biology, Biochemistry and Molecular Biotechnology, Microbiology and Physiological Systems, MD/PhD Program, University of Massachusetts Chan Medical School, Worcester, MA 01655, United States.
Abstract:
Chemically modified small interfering RNAs (siRNAs) are a promising drug class that silences disease-causing genes via mRNA degradation. Both siRNA-specific features (e.g. sequence, modification pattern, and structure) and target mRNA-specific factors contribute to observed efficacy. Systematically defining the relative contributions of siRNA sequence, structure, and modification pattern versus the native context of the target mRNA is necessary to inform design considerations and facilitate the widespread application of this therapeutic platform. To address this, we synthesized a panel of ∼1260 differentially modified siRNAs and evaluated their silencing efficiency against therapeutically relevant mRNAs (APP, BACE1, MAPT, and SNCA) using both reporter-based and native expression assays. Our results demonstrate that the siRNA modification pattern (e.g. level of 2'-O-methyl content) significantly impacts efficacy, while structural features (e.g. symmetric versus asymmetric configurations) do not. Furthermore, we observed substantial differences in the number of effective siRNAs identified per target. These target-specific differences in hit rates are largely mitigated when efficacy is tested in the context of a reporter assay, confirming that native mRNA-specific features influence siRNA performance. Key target-specific factors, including exon usage, polyadenylation site selection, and ribosomal occupancy, partially explained efficacy variability. These insights led to a proposed framework of parameters for optimizing therapeutic siRNA design.
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