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Related Concept Videos

Gene-Environment Interactions01:20

Gene-Environment Interactions

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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...
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Behavioral Genetics and Its Designs01:23

Behavioral Genetics and Its Designs

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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...
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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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Epistasis Analysis01:09

Epistasis Analysis

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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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Human Genetics01:28

Human Genetics

586
Human genetics provides a profound framework for understanding the interplay between genetic predispositions and human psychology. At the heart of this discipline lies the study of how genes influence physical traits, behaviors, and susceptibility to diseases. Each person carries a unique genetic code that subtly or significantly shapes their psychological and behavioral landscape.
The complex relationship between genetics and psychology is observable through common biological components such...
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Genome-wide Association Studies-GWAS01:11

Genome-wide Association Studies-GWAS

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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...
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Related Experiment Video

Updated: Jul 9, 2025

Gene-environment Interaction Models to Unmask Susceptibility Mechanisms in Parkinson's Disease
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Bayesian Approaches in Exploring Gene-environment and Gene-gene Interactions: A Comprehensive Review.

N A Sun1, Y U Wang1, Jiadong Chu1

  • 1Department of Epidemiology and Biostatistics, School of Public Health, Medical College of Soochow University, Suzhou, P.R. China.

Cancer Genomics & Proteomics
|November 30, 2023
PubMed
Summary
This summary is machine-generated.

Bayesian models address missing heritability in complex diseases by integrating gene-gene and gene-environment interactions. These advanced approaches enhance prediction accuracy and reveal disease mechanisms using omics data.

Keywords:
Bayesianeffect hereditygene-environment interactionsgene-gene interactionsmachine learningreview

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Area of Science:

  • Genetics
  • Biostatistics
  • Computational Biology

Background:

  • High-throughput omics data generation supports precision medicine.
  • The challenge of missing heritability in complex diseases remains.
  • Understanding genetic architecture requires incorporating gene interactions.

Purpose of the Study:

  • To review Bayesian approaches for identifying and estimating genetic interactions.
  • To highlight models for gene-environment (G×E) and gene-gene (G×G) interactions.
  • To discuss the application of these models in complex disease research.

Main Methods:

  • Review of Bayesian statistical models for genetic analysis.
  • Focus on models incorporating main effects and interactions (M-I).
  • Inclusion of single-nucleotide polymorphism (SNP)-based studies and machine learning-Bayesian methods.

Main Results:

  • Bayesian models improve accuracy in identifying genetic effects and interactions.
  • Models based on effect heredity and group-based principles offer flexibility.
  • Machine learning-Bayesian approaches show high prediction accuracy.

Conclusions:

  • Bayesian methods offer powerful tools for dissecting complex disease genetics.
  • These approaches enhance understanding of disease mechanisms and biomarker discovery.
  • The reviewed models contribute to improved prognostic prediction in precision medicine.