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Although Mendel chose seven unrelated traits in peas to study gene segregation, most traits involve multiple gene interactions that create a spectrum of phenotypes. When the interaction of various genes or alleles at different locations influences a phenotype, this is called epistasis. Epistasis often involves one gene masking or interfering with the expression of another (antagonistic epistasis). Epistasis often occurs when different genes are part of the same biochemical pathway. The...

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In addition to multiple alleles at the same locus influencing traits, numerous genes or alleles at different locations may interact and influence phenotypes in a phenomenon called epistasis. For example, rabbit fur can be black or brown depending on whether the animal is homozygous dominant or heterozygous at a TYRP1 locus. However, if the rabbit is also homozygous recessive at a locus on the tyrosinase gene (TYR), it will have an unshaded coat that appears white, regardless of its TYRP1...

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Related Experiment Video

Updated: May 15, 2026

Candidate Gene Testing in Clinical Cohort Studies with Multiplexed Genotyping and Mass Spectrometry

Candidate Gene Testing in Clinical Cohort Studies with Multiplexed Genotyping and Mass Spectrometry

Published on: June 21, 2018

Multi-gene-loci inheritance in resistance modeling.

Dirk Langemann¹, Otto Richter, Antje Vollrath

¹Technische Universität Braunschweig, Institute for Computational Mathematics, Pockelsstr. 14, 38106 Braunschweig, Germany. d.langemann@tu-bs.de

Mathematical Biosciences

|January 1, 2013

Summary

Organisms can develop metabolic resistance, degrading toxins into less harmful compounds. This resistance complicates pest management by shifting how populations respond to pesticides.

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Area of Science:

Ecology
Evolutionary Biology
Toxicology

Background:

Metabolic resistance enables organisms to detoxify harmful substances, altering their response to toxicants.
This resistance poses significant challenges for effective pest and disease management using pesticides.
Understanding the genetic and evolutionary basis of metabolic resistance is crucial.

Purpose of the Study:

To develop a novel polygenic fitness model simulating the emergence of metabolic resistance.
To analyze the evolutionary dynamics of dose-response curves under pesticide selection pressure.
To investigate different scenarios of metabolic resistance development.

Main Methods:

A polygenic fitness model incorporating a new tensor product approach for heredity matrices.
Integration of a genetic submodel into a time-continuous population model for diverse biotypes.
Analysis of differential equations to identify polymorphic equilibria and evolutionary shifts.

Main Results:

The model demonstrates a gradual shift in the population's mean dose-response curve under sustained pesticide application.
Evolution acts on dose-response curve parameters, specifically mortality rates and ED(50) values.
Numerical experiments illustrate various scenarios of metabolic resistance evolution.

Conclusions:

The developed model accurately simulates the emergence and progression of metabolic resistance in populations.
Long-term pesticide use drives evolutionary adaptation, leading to increased resistance.
The findings have implications for optimizing pest management strategies and predicting resistance evolution.