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Structure-Based Alignment and Consensus Secondary Structures for Three HIV-Related RNA Genomes
Structure-Based Alignment and Consensus Secondary Structures for Three HIV-Related RNA Genomes
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Structure-Based Alignment and Consensus Secondary Structures for Three HIV-Related RNA Genomes
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Structure-Based Alignment and Consensus Secondary Structures for Three HIV-Related RNA Genomes
Structure-Based Alignment and Consensus Secondary Structures for Three HIV-Related RNA Genomes

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Structure-Based Alignment and Consensus Secondary Structures for Three HIV-Related RNA Genomes
Structure-Based Alignment and Consensus Secondary Structures for Three HIV-Related RNA Genomes
Journal Article

Structure-Based Alignment and Consensus Secondary Structures for Three HIV-Related RNA Genomes

2015
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Overview
HIV and related primate lentiviruses possess single-stranded RNA genomes. Multiple regions of these genomes participate in critical steps in the viral replication cycle, and the functions of many RNA elements are dependent on the formation of defined structures. The structures of these elements are still not fully understood, and additional functional elements likely exist that have not been identified. In this work, we compared three full-length HIV-related viral genomes: HIV-1NL4-3, SIVcpz, and SIVmac (the latter two strains are progenitors for all HIV-1 and HIV-2 strains, respectively). Model-free RNA structure comparisons were performed using whole-genome structure information experimentally derived from nucleotide-resolution SHAPE reactivities. Consensus secondary structures were constructed for strongly correlated regions by taking into account both SHAPE probing structural data and nucleotide covariation information from structure-based alignments. In these consensus models, all known functional RNA elements were recapitulated with high accuracy. In addition, we identified multiple previously unannotated structural elements in the HIV-1 genome likely to function in translation, splicing and other replication cycle processes; these are compelling targets for future functional analyses. The structure-informed alignment strategy developed here will be broadly useful for efficient RNA motif discovery.