Computationally-inferred structural landscape of the complete genomes of Dengue serotypes and other viral hemorrhagic fevers
Abstract
BackgroundWith more than 300 million potentially infected people every year, and with the expanded habitat of mosquitoes due to climate change, dengue cannot be considered anymore only a tropical disease. The RNA secondary structure is a functional characteristic of RNA viruses, and together with the accumulated high-throughput sequencing data could provide general insights towards understanding virus biology. Here, we profiled the RNA secondary structure of >7500 complete viral genomes from 11 different species of viral hemorrhagic fevers, including dengue serotypes, ebola, and yellow fever. ResultsWe achieved hig prediction scores (AUC up to 0.85 with experimental data), and computed consensus secondary structure profiles using hundreds of structural in silico models. We observed that virulent viruses such as DENV-2 and ebola tend to be less structured than the other viruses. Furthermore, we observed virus-specific correlations between secondary structure and the number of interaction sites with human proteins, reaching a correlation of 0.89 in the case of zika. We demonstrate that the secondary structure and presence of protein-binding domains in the genomes can be used as intrinsic signature to further classify the viruses. We also used structural data to study the geographical distribution of dengue, finding a significant difference between DENV-3 from Asia and South-America, which could imply different evolutionary routes of this subtype. ConclusionsOur massive computational analysis provided novel results regarding the secondary structure and the interaction with human proteins, not only for Dengue serotypes, but also for other viral hemorrhagic fevers. We also provided a new approach to classify viruses according ot their structure, which could be useful for future cassifications. We envision that these approaches can be used by the scientific community to further classify and characterise these complex viruses.
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