Epistasis occurs when the effect of one allele is influenced by another allele. Epistatic interactions play a profound role in evolution. An understanding of epistasis is also crucial in a variety of biomedical endeavors, such as identifying disease variants from genetic association studies and predicting the evolution of pathogens. But many of the most basic questions about epistasis remain unanswered, including: How common are epistatic interactions? How do they arise? And what are the underlying molecular mechanisms? We will address these questions by mapping epistatic interactions along a real evolutionary trajectory. To do this, we will employ a combination of computational and experimental tools to study the influenza nucleoprotein. Because of the unique nature of influenza evolution, we are able to infer in step-by-step detail the 39 mutations that have occurred in the nucleoprotein from human H3N2 since the year 1968. We will construct all 39 intermediate proteins along this evolutionary trajectory. We will also introduce each of the mutations individually into the 1968 parent. All of these variants will be tested for biochemical function and effect on viral fitness. This will provide a clear experimental test for epistasis: a mutation is involved in an epistatic interaction if it has a different effect in the 1968 parent than in the evolutionary intermediate in which it actually occurred. Crucially, our preliminary work has already identified several mutations involved in epistatic interactions.
In Aim 1, we will build on this work by mapping all epistatic interactions since 1968.
In Aim 2, we will address the mystery of how the epistatic interactions arose - did multiple mutations occur simultaneously, were there compensatory or permissive mutations, or did epistasis arise slowly due to a gradually shifting genetic background? Finally, in Aim 3, we will use biophysical and biochemical techniques to identify the molecular mechanisms of each epistatic interaction. At the conclusion of this study, we will have mapped the prevalence, origins, and mechanisms of epistatic interactions along a real evolutionary trajectory. Our findings will provide a new window into one of the most important factors shaping the evolution of proteins and viruses, and will aid in attempts to interpret sequence data and understand interactions between alleles.

Public Health Relevance

An understanding of epistasis - the phenomenon whereby the effect of one gene or mutation is influenced by another - is crucial for achieving goals such as predicting the evolution of viruses and determining disease susceptibilities from personal genomic data. We will analyze the evolution of the influenza nucleoprotein since the year 1968 to identify all mutations with effects that are influenced by other mutations from this same timeframe. Our work will create a detailed mapping of epistasis during the evolution of this viral protein, and will provide a basis for understanding and modeling epistasis in a range of medically important contexts.

National Institute of Health (NIH)
National Institute of General Medical Sciences (NIGMS)
Research Project (R01)
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Genetic Variation and Evolution Study Section (GVE)
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Eckstrand, Irene A
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Fred Hutchinson Cancer Research Center
United States
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Xue, Katherine S; Hooper, Kathryn A; Ollodart, Anja R et al. (2016) Cooperation between distinct viral variants promotes growth of H3N2 influenza in cell culture. Elife 5:e13974
Haddox, Hugh K; Dingens, Adam S; Bloom, Jesse D (2016) Experimental Estimation of the Effects of All Amino-Acid Mutations to HIV's Envelope Protein on Viral Replication in Cell Culture. PLoS Pathog 12:e1006114
Doud, Michael B; Bloom, Jesse D (2016) Accurate Measurement of the Effects of All Amino-Acid Mutations on Influenza Hemagglutinin. Viruses 8:
Hooper, Kathryn A; Crowe Jr, James E; Bloom, Jesse D (2015) Influenza viruses with receptor-binding N1 neuraminidases occur sporadically in several lineages and show no attenuation in cell culture or mice. J Virol 89:3737-45
Doud, Michael B; Ashenberg, Orr; Bloom, Jesse D (2015) Site-Specific Amino Acid Preferences Are Mostly Conserved in Two Closely Related Protein Homologs. Mol Biol Evol 32:2944-60
Machkovech, Heather M; Bedford, Trevor; Suchard, Marc A et al. (2015) Positive Selection in CD8+ T-Cell Epitopes of Influenza Virus Nucleoprotein Revealed by a Comparative Analysis of Human and Swine Viral Lineages. J Virol 89:11275-83
Bloom, Jesse D (2015) Software for the analysis and visualization of deep mutational scanning data. BMC Bioinformatics 16:168
Thyagarajan, Bargavi; Bloom, Jesse D (2014) The inherent mutational tolerance and antigenic evolvability of influenza hemagglutinin. Elife 3:
Bloom, Jesse D (2014) An experimentally determined evolutionary model dramatically improves phylogenetic fit. Mol Biol Evol 31:1956-78
Bloom, Jesse D (2014) An experimentally informed evolutionary model improves phylogenetic fit to divergent lactamase homologs. Mol Biol Evol 31:2753-69

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