RNA functions as the central conduit for information transfer in biology - in simple replicating entities like RNA viruses and in complex multi-cellular organisms. RNA is uniquely able to play this role because it encodes information at two levels: in its linear primary sequence and in its ability to form functionally critical higher-order folds. Work to date, largely focused on intensive study of a few specific regulatory motifs, has revealed that RNA secondary and tertiary structures regulate splicing, translation and protein folding, binding by small ligands and drugs and proteins, and collapse into large-scale structural domains. There are only a small number of examples in which genome-scale RNA structures have been characterized. However, numerous new biological insights were uncovered in each case. RNA viruses are especially informative systems because their compact genomes feature a dense array of functionally important secondary and tertiary structure elements. Moreover, every identification of a new regulatory motif in a pathogenic virus presents a unique target for anti-virus therapeutic design. Guided by several years of preliminary and exploratory studies, we are poised to make very high- throughput and high-content RNA secondary and tertiary structure analysis straightforward. We will apply newly invented massively parallel secondary and tertiary structure constraint-generation technologies coupled with novel molecular dynamics-driven structural refinement to understand the biological roles of higher-order structure in the hepatitis C virus (HCV) RNA genome. Our Specific Aims are designed to reveal numerous new roles for RNA structure in the replication cycle of HCV, to do so in a way likely to inform many fields of biology, to make possible new therapeutic strategies for inhibiting viral replication, and to create tools that can be widely adopted by non-expert laboratories for analysis of complex, biologically authentic RNAs. Aim 1: Analyze the structure of three representative HCV RNA genomes using SHAPE, detected by massively parallel sequencing, to identify conserved base pairing and tertiary structure motifs. Aim 2: Create and validate an accurate and scalable approach for using experimental base pairing and through-space tertiary constraints to drive three-dimensional fold refinement for large RNAs. Aim 3: Integrate the technologies developed in this work to refine three-dimensional structure models and to discover new regulatory motifs for plus-sense HCV RNA genomes.