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Gene-Environment Interactions01:20

Gene-Environment Interactions

395
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...
395
Behavioral Genetics and Its Designs01:23

Behavioral Genetics and Its Designs

451
Behavior genetics explores how genetic inheritance influences human behavior. It focuses on how genes, passed from parents to offspring, contribute to the development of behavioral traits and tendencies. This branch of genetics seeks to understand the complex interplay between inherited genetic factors and environmental influences in shaping our behaviors.
The primary methodologies used in behavior genetics include family studies, twin studies, and adoption studies, each providing unique...
451
Background and Environment Affect Phenotype02:27

Background and Environment Affect Phenotype

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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...
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Trihybrid Crosses02:27

Trihybrid Crosses

23.6K
Trihybrid Crosses
Some of Mendel’s crosses examined three pairs of contrasting characteristics. Such a cross is called a trihybrid cross. A trihybrid cross is a combination of three individual monohybrid crosses. For example, plant height (tall vs. short), seed shape (round vs. wrinkled), and seed color (yellow vs. green).
The F1 generation plants of a trihybrid cross are heterozygous for all three traits and produce eight gametes. Upon self-fertilization, these gametes have an equal...
23.6K
Inheritance01:25

Inheritance

447
Gregor Mendel's pioneering work on the principles of inheritance fundamentally transformed our understanding of how traits are transmitted from generation to generation. His experiments with pea plants laid the groundwork for the discovery of genes, discrete units within organisms that control heredity.
Each gene exists in pairs, and the combination of these genes from both parents forms an individual's genotype. This genotype is a blueprint of potential traits. Examples of genotype...
447
Epistasis Analysis01:09

Epistasis Analysis

5.1K
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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Related Experiment Video

Updated: Aug 13, 2025

Using Cholesky Decomposition to Explore Individual Differences in Longitudinal Relations between Reading Skills
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Using Cholesky Decomposition to Explore Individual Differences in Longitudinal Relations between Reading Skills

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Inference of gene-environment interaction from heterogeneous case-parent trios.

Pulindu Ratnasekera1, Jinko Graham1, Brad McNeney1

  • 1Department of Statistics and Actuarial Science, Simon Fraser University, Burnaby, BC, Canada.

Frontiers in Genetics
|January 23, 2023
PubMed
Summary

Genetic principal components (PCs) adjust for spurious gene-environment interactions in population strata. This method maintains statistical power and controls type-1 error rates in genetic epidemiology studies.

Keywords:
case-parent trioscleft palategene-environment interactiongenome-wide association studypopulation structureprincipal components

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Area of Science:

  • Genetic Epidemiology
  • Statistical Genetics
  • Population Genetics

Background:

  • Log-linear models analyze genotype and exposure effects on disease relative risk, including gene-environment interactions.
  • Exposure-related genetic structure can cause spurious gene-environment interactions, particularly when linkage disequilibrium exists between test and causal loci.
  • Case-parent trio designs protect against genetic main effect confounding but not for gene-environment interactions in the presence of exposure-related genetic structure.

Purpose of the Study:

  • To address limitations of current methods for reducing bias in gene-environment interaction estimates from case-parent trio data.
  • To propose a novel method that accommodates multiple population strata by adjusting for genetic principal components (PCs).

Main Methods:

  • The study proposes adjusting for genetic principal components (PCs) to directly accommodate multiple population strata.
  • The proposed method is evaluated using simulations to assess its performance in maintaining type-1 error rates and power.
  • The PC-adjustment approach is applied to real-world data from a cleft palate study.

Main Results:

  • Simulations demonstrate that PC adjustment maintains nominal type-1 error rates.
  • The PC adjustment method shows power comparable to an oracle approach that directly uses population strata.
  • Application to cleft palate data suggests the gene-environment interaction signal is primarily from European trios.

Conclusions:

  • Genetic principal component adjustment is an effective method for mitigating spurious gene-environment interactions in genetically structured populations.
  • This approach enhances the reliability of gene-environment interaction findings in genetic epidemiology.
  • The method provides a robust tool for analyzing complex genetic data, particularly in admixed or stratified populations.