PT  - JOURNAL ARTICLE
AU  - Kristina Crona
AU  - Alex Gavryushkin
AU  - Devin Greene
AU  - Niko Beerenwinkel
TI  - Inferring Genetic Interactions From Comparative Fitness Data
AID  - 10.1101/137372
DP  - 2017 Jan 01
TA  - bioRxiv
PG  - 137372
4099  - http://biorxiv.org/content/early/2017/11/22/137372.short
4100  - http://biorxiv.org/content/early/2017/11/22/137372.full
AB  - Darwinian fitness is a central concept in evolutionary biology. In practice, however, it is hardly possible to measure fitness for all genotypes in a natural population. Here, we present quantitative tools to make inferences about epistatic gene interactions when the fitness landscape is only incompletely determined due to imprecise measurements or missing observations. We demonstrate that genetic interactions can often be inferred from fitness rank orders, where all genotypes are ordered according to fitness, and even from partial fitness orders. We provide a complete characterization of rank orders that imply higher order epistasis. Our theory applies to all common types of gene interactions and facilitates comprehensive investigations of diverse genetic interactions. We analyzed various genetic systems comprising HIV-1, the malaria-causing parasite Plasmodium vivax, the fungus Aspergillus niger, and the TEM-family of β-lactamase associated with antibiotic resistance. For all systems, our approach revealed higher order interactions among mutations.