ABSTRACT
Influenza viruses infect various species, including humans, and occasionally cause worldwide pandemics and severe outbreaks in poultry. They have segmented single-stranded negative-sense RNA genomes consisting of seven or eight virus RNA (vRNA) segments. During the virus life cycle, RNAs of positive polarity are synthesized: complementary RNAs (cRNAs), which serve as templates for new vRNAs, and messenger RNAs (mRNAs), which are translated. Higher-order structures formed by both negative- and positive-sense RNAs have a number of important functions required for replication of the virus. These structures have initially been predicted using RNA folding algorithms. Recently, the development of novel high-throughput methods has made it possible to study the structured domains in influenza virus RNA genomes and the interactions between genomic segments in detail. Accumulation of such knowledge is of great importance for understanding virus evolution and the development of antiviral strategies. This chapter discusses bioinformatic approaches used in theoretical predictions and high-throughput studies of functional RNA structures in influenza virus genomes.
Monique I. Spronken and Mathilde Richard
