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Unbiased Deep Sequencing of RNA Viruses from Clinical Samples
Published on: July 2, 2016
Genomic Analysis of the Emergence, Evolution, and Spread of Human Respiratory RNA Viruses
Tommy T-Y Lam1,2,3, Huachen Zhu1,2,3, Yi Guan1,2,3,4
1State Key Laboratory of Emerging Infectious Diseases and Centre of Influenza Research, School of Public Health, The University of Hong Kong, Hong Kong, China; email: ttylam@hku.hk , zhuhch@hku.hk , yguan@hku.hk.
Abstract:
The emergence and reemergence of rapidly evolving RNA viruses-particularly those responsible for respiratory diseases, such as influenza viruses and coronaviruses-pose a significant threat to global health, including the potential of major pandemics. Importantly, recent advances in high-throughput genome sequencing enable researchers to reveal the genomic diversity of these viral pathogens at much lower cost and with much greater precision than they could before. In particular, the genome sequence data generated allow inferences to be made on the molecular basis of viral emergence, evolution, and spread in human populations in real time. In this review, we introduce recent computational methods that analyze viral genomic data, particularly in combination with metadata such as sampling time, geographic location, and virulence. We then outline the insights these analyses have provided into the fundamental patterns and processes of evolution and emergence in human respiratory RNA viruses, as well as the major challenges in such genomic analyses.
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