A geometric representation of gene-by-gene and gene-by-environment interactions on the extended complex plane
Abstract
The relationship between genotypic and phenotypic variation is determined by the complex interaction of genetic and environmental factors. While statistical methods capable of detecting such interactions exist, an axiomatic mathematical framework that seamlessly describes the combined effects of genetic modifications and environmental exposures on a common scale is lacking. In this report, buffering concepts are used to construct a measurement system that enables the geometric representation of both gene-by-gene and gene-by-environment interactions on the extended complex plane (i.e., as projections on the Riemann sphere). In this manner, any such interaction, or combination thereof, can be precisely defined and quantified as the deviation from the neutral value calculated through the applicable complex transformation. When thus conceptualized, the frameworks parameterization defines the "state space" of a given measurable phenotype along both the real and imaginary dimensions, thus establishing an unambiguous and broadly applicable method for determining the phenotypic value expected upon combinatorial changes in genetic and/or environmental variables. Remarkably, by applying these methods, it is possible to quantify the effects of any gene-by-environment interaction using the equation, [Formula], where zobs and zexp are complex numbers representing the observed and expected phenotypes of a given genotype expressed in terms of the buffering parameters, and b.
02 /Specification & Classification
Click any tag to browse matching papersReproducibility ledger
Nobody has reported trying to reproduce this paper yet. Did you replicate an experiment or run the code? Your report saves the next lab a week.
Sign in to file a reproducibility report.
Related papers
- Phenotypic distribution and selection response for linear-product gene-environment interaction in quantitative traits
Reginald D. Smith·bioRxiv·May 12, 2021
- A biobank-scale method for learning modulators of gene-environment interaction underlying human complex traits from multiple environmental exposures
Z LIU, Arush Ramteke, … Sriram Sankararaman·bioRxiv·Mar 16, 2026
- A Mathematical Framework for the Quantitative Analysis of Genetic Buffering
Jim Karagiannis·PLoS GeneticsPeer-reviewed·Jun 10, 2025
- Extracting the GEMs: Genotype, Environment and Microbiome interactions shaping host phenotypes
B. O. Oyserman, V. Cordovez, … J. M. Raaijmakers·bioRxiv·Dec 3, 2019
- Inference of gene-environment interaction from heterogeneous case-parent trios
Pulindu Ratnasekera, Jinko Graham, Brad McNeney·Frontiers in GeneticsPeer-reviewed·Jan 4, 2023
- Environment by environment interactions (ExE) differ across genetic backgrounds (ExExG)
Kara Schmidlin, C. Brandon Ogbunugafor, … Kerry Geiler‐Samerotte·Molecular Biology and EvolutionPeer-reviewed·Oct 29, 2025