Developing novel statistical and coalescent approaches for the improved study of virus evolution

Project: Research project

Description

Research Overview
The area of viral population genetics is on the verge of important breakthroughs both in our understanding of population genetics under models of highly skewed offspring distributions and extraordinarily high mutation rates, and in our ability to connect the field of evolutionary theory with medicine and improved public health. This proposal offers timely, essential mathematical and statistical updates of classical population genetic approaches to improve applicability to the study of viral populations. Furthermore, given the extensive collaborative network assembled incorporating both virologists and clinicians, this research plan has a clear and unusually direct avenue for truly connecting theory to clinic.

Intellectual merits
The development of multiple merger coalescent theory under a variety of demographic models with and without selection, and the subsequent incorporation of this theory in to improved data inference schemes, are necessary and missing components in bridging currently abstract theory with practical utility. The obtained results under alternative coalescent models will be applicable not only to the study of virus evolution, but to any system characterized by skewed offspring distributions ranging from plants to marine spawners. More fundamentally, this work lays the foundation for the exploration of alternative coalescent models in population genetics, moving the field away from the unnecessary dependence on the specific assumptions underlying the Kingman coalescent, assumptions which are simply inappropriate for many organisms of interest.

Broader impacts
These necessary advances require expertise in population genetic theory, statistical inference, virology, as well as large-scale natural and experimental population analysis all expertise cultivated in the Jensen Lab. Furthermore, transforming theoretical developments into user-friendly and freely available statistical software applications is a hallmark of the lab, enabling the dissemination of this work to the broader evolutionary and ecological communities. This proposal specifically utilizes two viral systems which have been heavily studied in the Jensen Lab and for which unique data access is available via consortium involvements: human cytomegalovirus (HCMV) and influenza A virus (IAV). The anticipated results of this work will shed light on both the within- and between-host demographic and selective processes driving not only genetic variation but also infection risk and outcome. Specifically, this work will illuminate improved drug treatment strategies pertaining to IAV, as well as inform clinical approaches for reducing the risk of HCMV fetal infection.
StatusActive
Effective start/end date9/1/197/31/22

Funding

  • HHS: National Institutes of Health (NIH): $557,724.00

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Population Genetics
Viruses
Influenza A virus
Demography
Plant Dispersal
Biota
Virology
Genetic Models
Cytomegalovirus Infections
Population Dynamics
Mutation Rate
Cytomegalovirus
Research
Human Influenza
Population
Software
Public Health
Medicine
Infection
Pharmaceutical Preparations