Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

Gene-Environment Interactions01:20

Gene-Environment Interactions

Gene expression is a dynamic process that is significantly influenced by environmental factors. This interaction underlies the complex nature of biological development and the phenotypic differences observed among individuals, even among those with identical genetic makeups. Factors such as radiation, temperature, behavior, nutrition, and stress play pivotal roles in determining how genes are expressed. The concept of the reaction range is central to understanding this interaction. It posits...
Heritability01:06

Heritability

Heritability is a statistical concept that measures the degree to which genetic differences among individuals contribute to trait variations within a population. It is a fundamental idea in genetics, often prone to misinterpretation. Heritability is expressed as a percentage, reflecting the proportion of variation in a specific trait across a population that can be linked to genetic differences. However, it's important to understand that heritability does not determine how "genetic" a trait is,...
Background and Environment Affect Phenotype02:27

Background and Environment Affect Phenotype

Although the genetic makeup of an organism plays a major role in determining the phenotype, there are also several environmental factors, such as temperature, oxygen availability, presence of mutagens, that can alter an organism’s phenotype.
An example of how genetic background affects phenotype can be seen in horses. The Extension gene in horses is responsible for their coat color. A wild-type gene (EE) produces black pigment in the coat, while a mutant gene (ee) produces red pigment. A...
Polygenic Traits01:18

Polygenic Traits

When more than one gene is responsible for a given phenotype, the trait is considered polygenic. Human height is a polygenic trait. Studies have uncovered hundreds of loci that influence height, and there are believed to be many more. Due to the high number of genes involved, as well as environmental and nutritional factors, height varies significantly within a given population. The distribution of height forms a bell-shaped curve, with relatively few individuals in the population at the...
Genome-wide Association Studies-GWAS01:11

Genome-wide Association Studies-GWAS

Genome-wide association studies or GWAS are used to identify whether common SNPs are associated with certain diseases. Suppose specific SNPs are more frequently observed in individuals with a particular disease than those without the disease. In that case, those SNPs are said to be associated with the disease. Chi-square analysis is performed to check the probability of the allele likely to be associated with the disease.
GWAS does not require the identification of the target gene involved in...
Testing a Claim about Mean: Known Population SD01:11

Testing a Claim about Mean: Known Population SD

A complete procedure of testing the hypothesis about a population mean is explained here.
Estimating a population mean requires the samples to be distributed normally. The data should be collected from the randomly selected samples having no sampling bias. The sample size needed to be higher than 30, and most importantly, the population standard deviation should be already known.
In most realistic situations, the population standard deviation is often unknown, but in rare circumstances, when it...

You might also read

Related Articles

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

Sort by
Same author

Multimodal Proteomics Reveals Dysregulated Secretion and ECM Remodelling in Schizophrenia Patient iPSC-Derived Astrocytes.

Cells·2026
Same author

Simplifying causal gene identification in GWAS loci.

PLoS genetics·2026
Same author

The genetic landscape of human functional brain connectivity.

Nature communications·2026
Same author

Genomic insights into substance use and disinhibitory disorders.

medRxiv : the preprint server for health sciences·2026
Same author

Rare-variant aggregation highlights disease-linked genes associated with brain volume variation.

American journal of human genetics·2026
Same author

Identifying drug targets for schizophrenia through gene prioritization.

Translational psychiatry·2026

Related Experiment Video

Updated: Jun 13, 2026

Candidate Gene Testing in Clinical Cohort Studies with Multiplexed Genotyping and Mass Spectrometry
05:53

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

Published on: June 21, 2018

Statistical power to detect genetic Loci affecting environmental sensitivity.

Peter M Visscher1, Danielle Posthuma

  • 1Queensland Institute of Medical Research, Herston 4006, Australia. peter.visscher@qimr.edu.au

Behavior Genetics
|April 30, 2010
PubMed
Summary

Detecting genetic control over trait variability requires careful study design. Unrelated individuals are better for phenotypic variance, while monozygotic (MZ) twins are more efficient for environmental variation, impacting genetic research power.

More Related Videos

Combined Immunofluorescence and DNA FISH on 3D-preserved Interphase Nuclei to Study Changes in 3D Nuclear Organization
13:55

Combined Immunofluorescence and DNA FISH on 3D-preserved Interphase Nuclei to Study Changes in 3D Nuclear Organization

Published on: February 3, 2013

Large-Scale Multi-Omics Genome-Wide Association Studies (Mo-GWAS): Guidelines for Sample Preparation and Normalization
08:27

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: Jun 13, 2026

Candidate Gene Testing in Clinical Cohort Studies with Multiplexed Genotyping and Mass Spectrometry
05:53

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

Published on: June 21, 2018

Combined Immunofluorescence and DNA FISH on 3D-preserved Interphase Nuclei to Study Changes in 3D Nuclear Organization
13:55

Combined Immunofluorescence and DNA FISH on 3D-preserved Interphase Nuclei to Study Changes in 3D Nuclear Organization

Published on: February 3, 2013

Large-Scale Multi-Omics Genome-Wide Association Studies (Mo-GWAS): Guidelines for Sample Preparation and Normalization
08:27

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

Published on: July 27, 2021

Area of Science:

  • Quantitative genetics
  • Statistical genomics
  • Twin studies

Background:

  • Genetic factors can influence environmental variation in traits across species.
  • Understanding the statistical power to detect genetic control is crucial for quantitative trait research.

Purpose of the Study:

  • To analytically investigate the statistical power for detecting genetic control of environmental or phenotypic variability.
  • To compare the efficiency of different study designs (unrelated individuals vs. monozygotic twins) for detecting genetic effects on variance.

Main Methods:

  • Analytical investigation of statistical power.
  • Utilized a monozygotic (MZ) twin difference design and a design using unrelated individuals.
  • Modeled additive or multiplicative allele effects on trait variance and employed additive regression for analysis.

Main Results:

  • For genetic control on phenotypic variance, designs with unrelated individuals are more efficient but require tens of thousands of observations.
  • For genetic control purely on environmental variation, MZ twin difference designs are more efficient if the MZ trait correlation exceeds approximately 0.3.
  • Detecting loci influencing variance requires twice the observations compared to detecting loci influencing phenotype directly, for equivalent variance proportions.

Conclusions:

  • Study design choice significantly impacts the power to detect genetic control of trait variability.
  • Distinguishing between genetic control of phenotypic vs. environmental variance is key for efficient study design in quantitative genetics.
  • Large sample sizes are necessary for detecting subtle genetic influences on variance components.