High-Throughput Genetics in Virus Research: Application and Insight

Traditional genetics, which includes forward and reverse genetics, has been employed extensively to study influenza virus. Although traditional genetics is powerful, it has a limited throughput which only focuses on the linkage of one mutation with one phenotype at a time. In my thesis research, a high-throughput genetics platform is being developed to examine the phenotypic outcomes of all point mutations in a viral gene or genome in parallel. The underlying concept is to randomly mutagenize every nucleotide of an entire genome, monitor enrichment or diminishment of all point mutations under specified growth conditions, and perform massive deep-sequencing to determine which mutations contribute to negative, neutral, or positive outcomes under the given conditions. Using this high-throughput genetics platform, the fitness effects of individual point mutations was profiled across influenza A virus hemagglutinin gene. This technique was further applied to identify novel functional residues and interferon-sensitive mutation. The high-throughput genetics platform can potentially be adapted to study any microbes that can be genetically manipulated. My thesis also describes a novel experimental approach, tag linkage sequencing, to monitor viral quasispecies. Tag linkage sequencing utilizes a molecular tag to identify short sequencing reads that are from the same original DNA template. This allows the reconstruction of individual viral genomes within a viral quasispecies from deep sequencing data. This approach was employed to investigate the genetic content of a clinical sample from a patient infected with human immunodeficiency virus (HIV)