Search research articles

ABOUT JoVE

Overview Leadership Blog JoVE Help Center

AUTHORS

Publishing Process Editorial Board Scope & Policies Peer Review FAQ Submit

LIBRARIANS

Testimonials Subscriptions Access Resources Library Advisory Board FAQ

RESEARCH

JoVE Journal Methods Collections JoVE Encyclopedia of Experiments Archive

EDUCATION

JoVE Core JoVE Business JoVE Science Education JoVE Lab Manual Faculty Resource Center Faculty Site

Terms & Conditions of Use

Related Concept Videos

Epistasis Analysis

Epistasis Analysis

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...

Epistasis

Epistasis

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...

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by

Same author

<i>Acropora millepora</i> 's microbiome is predicted by algal symbionts, host genetics, and environment.

bioRxiv : the preprint server for biology·2025

Same author

No evidence for sex-differential transcriptomes driving genome-wide sex-differential natural selection.

American journal of human genetics·2025

Same author

Two decades of bacterial ecology and evolution in a freshwater lake.

Nature microbiology·2025

Same author

The battle of the sexes in humans is highly polygenic.

Proceedings of the National Academy of Sciences of the United States of America·2024

Same author

Bacterial ecology and evolution converge on seasonal and decadal scales.

bioRxiv : the preprint server for biology·2024

Same author

How does evolution work in superabundant microbes?

Trends in microbiology·2024

Search research articles

Related Experiment Video

Updated: May 24, 2026

QTL Mapping and CRISPR/Cas9 Editing to Identify a Drug Resistance Gene in Toxoplasma gondii

QTL Mapping and CRISPR/Cas9 Editing to Identify a Drug Resistance Gene in Toxoplasma gondii

Published on: June 22, 2017

Using known QTLs to detect directional epistatic interactions.

Montgomery Slatkin¹, Mark Kirkpatrick

¹Department of Integrative Biology, University of California, Berkeley, 94720-3140, USA. slatkin@berkeley.edu

Genetics Research

|February 23, 2012

Summary

This summary is machine-generated.

We introduce a new method to study epistasis, a gene interaction crucial for evolution. This strategy tracks changes in "marginal differences" to detect directional epistasis, even when epistatic genetic variance is small.

More Related Videos

Screening for Functional Non-coding Genetic Variants Using Electrophoretic Mobility Shift Assay (EMSA) and DNA-affinity Precipitation Assay (DAPA)

Screening for Functional Non-coding Genetic Variants Using Electrophoretic Mobility Shift Assay (EMSA) and DNA-affinity Precipitation Assay (DAPA)

Published on: August 21, 2016

Large-Scale Multi-Omics Genome-Wide Association Studies (Mo-GWAS): Guidelines for Sample Preparation and Normalization

Large-Scale Multi-Omics Genome-Wide Association Studies (Mo-GWAS): Guidelines for Sample Preparation and Normalization

Published on: July 27, 2021

Related Experiment Videos

Last Updated: May 24, 2026

QTL Mapping and CRISPR/Cas9 Editing to Identify a Drug Resistance Gene in Toxoplasma gondii

QTL Mapping and CRISPR/Cas9 Editing to Identify a Drug Resistance Gene in Toxoplasma gondii

Published on: June 22, 2017

Screening for Functional Non-coding Genetic Variants Using Electrophoretic Mobility Shift Assay (EMSA) and DNA-affinity Precipitation Assay (DAPA)

Screening for Functional Non-coding Genetic Variants Using Electrophoretic Mobility Shift Assay (EMSA) and DNA-affinity Precipitation Assay (DAPA)

Published on: August 21, 2016

Large-Scale Multi-Omics Genome-Wide Association Studies (Mo-GWAS): Guidelines for Sample Preparation and Normalization

Large-Scale Multi-Omics Genome-Wide Association Studies (Mo-GWAS): Guidelines for Sample Preparation and Normalization

Published on: July 27, 2021

Area of Science:

Evolutionary genetics
Quantitative genetics

Background:

Epistasis, or gene interactions, is vital for evolutionary processes like recombination.
Existing methods for studying epistasis have limitations.

Purpose of the Study:

To propose a novel strategy for studying epistasis by analyzing marginal differences.
To develop a statistical test for detecting directional epistasis.

Main Methods:

Define marginal differences as phenotypic differences between genotypes at a specific quantitative trait locus (QTL).
Analyze how marginal differences respond to directional selection on a quantitative character.
Develop a likelihood ratio test to detect significant changes in marginal differences.

Main Results:

The response of marginal differences to selection is dependent on epistatic gene interactions.
Directional epistasis causes predictable changes in marginal differences under selection.
The likelihood ratio test shows power in detecting directional epistasis with realistic sample sizes.
Epistatic interactions influencing marginal differences evolution may not significantly contribute to genetic variance.

Conclusions:

The proposed method effectively detects directional epistasis by monitoring marginal differences.
This approach offers a valuable tool for understanding the role of epistasis in evolution.
The study highlights that significant epistatic effects on evolution may not always be apparent in genetic variance components.