ABSTRACTRNA molecules often fold into evolutionarily selected functional structures. Yet, the literature offers neither a satisfactory definition for “structured RNA regions”, nor a computational method to accurately identify such regions. Here, we define structured RNA regions based on the premise that both stems and loops in functional RNA structures should be conserved among RNA molecules sharing high sequence homology. In addition, we present a computational approach to identify RNA regions possessing evolutionarily conserved secondary structures, RNA ISRAEU (RNA Identification of Structured Regions As Evolutionary Unchanged). Applying this method to H1N1 influenza mRNAs revealed previously unknown structured RNA regions that are potentially essential for viral replication and/or propagation. Evolutionary conservation of RNA structural elements may explain, in part, why mutations in some nucleotide positions within influenza mRNAs occur significantly more often than in others. We found that mutations occurring in conserved nucleotide positions may be more disruptive for structured RNA regions than single nucleotide polymorphisms in positions that are more prone to changes. Finally, we predicted computationally a previously unknown stem-loop structure and demonstrated that oligonucleotides complementing the stem (but not the loop or unrelated sequences) reduce viral replicationin vitro.These results contribute to understanding influenza A virus evolution and can be applied to rational design of attenuated vaccines and/or drug designs based on disrupting conserved RNA structural elements.AUTHOR SUMMARYRNA structures play key biological roles. However, the literature offers neither a satisfactory definition for “structured RNA regions” nor the computational methodology to identify such regions. We define structured RNA regions based on the premise that functionally relevant RNA structures should be evolutionarily conserved, and devise a computational method to identify RNA regions possessing evolutionarily conserved secondary structural elements. Applying this method to influenza virus mRNAs of pandemic and seasonal H1N1 influenza A virus generated Predicted Structured Regions (PSRs), which were previously unknown. This explains the previously mysterious sequence conservation among evolving influenza strains. Also, we have experimentally supported existence of a computationally predicted stem-loop structure predicted computationally. Our approach may be useful in designing live attenuated influenza vaccines and/or anti-viral drugs based on disrupting necessary conserved RNA structures.
The design of optimal therapeutic small interfering RNA molecules targeting diverse strains of influenza A virus