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Related Concept Videos

Protein Networks02:26

Protein Networks

An organism can have thousands of different proteins, and these proteins must cooperate to ensure the health of an organism. Proteins bind to other proteins and form complexes to carry out their functions. Many proteins interact with multiple other proteins creating a complex network of protein interactions.
These interactions can be represented through maps depicting protein-protein interaction networks, represented as nodes and edges. Nodes are circles that are representative of a protein,...
Protein Networks02:26

Protein Networks

An organism can have thousands of different proteins, and these proteins must cooperate to ensure the health of an organism. Proteins bind to other proteins and form complexes to carry out their functions. Many proteins interact with multiple other proteins creating a complex network of protein interactions.
These interactions can be represented through maps depicting protein-protein interaction networks, represented as nodes and edges. Nodes are circles that are representative of a protein,...
Epistasis Analysis01:09

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...
Protein-protein Interfaces02:04

Protein-protein Interfaces

Many proteins form complexes to carry out their functions, making protein-protein interactions (PPIs) essential for an organism's survival. Most PPIs are stabilized by numerous weak noncovalent chemical forces. The physical shape of the interfaces determines the way two proteins interact. Many globular proteins have closely-matching shapes on their surfaces, which form a large number of weak bonds. Additionally, many PPIs occur between two helices or between a surface cleft and a polypeptide...
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...
Genetic Screens02:46

Genetic Screens

Genetic screens are tools used to identify genes and mutations responsible for phenotypes of interest. Genetic screens help identify individuals or a group of people at risk of developing  genetic diseases and help them with early intervention, targeted therapy, and reproductive options.
Forward genetic screens
Forward or “classical” genetic screens involve creating random mutations in an organism’s DNA using radiation, mutagens, or insertion of additional bases, which result in visible changes...

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Mapping Bacterial Functional Networks and Pathways in Escherichia Coli using Synthetic Genetic Arrays
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Identifying genetic interactions in genome-wide data using Bayesian networks.

Xia Jiang1, M Michael Barmada, Shyam Visweswaran

  • 1Department of Biomedical Informatics, University of Pittsburgh, Pittsburgh, Pennsylvania, USA. xij6@pitt.edu

Genetic Epidemiology
|June 23, 2010
PubMed
Summary
This summary is machine-generated.

Detecting gene-gene interactions (epistasis) is key for understanding common diseases. This study introduces a novel Bayesian network method that outperforms existing approaches in analyzing complex genetic data from genome-wide association studies (GWAS).

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Area of Science:

  • Genetics
  • Bioinformatics
  • Computational Biology
  • Disease Susceptibility

Background:

  • Epistasis, or gene-gene interactions, is increasingly recognized as crucial for common disease susceptibility.
  • Genome-wide association studies (GWAS) are widely used to identify genetic variants associated with diseases.
  • Single-locus analysis methods often fail to detect epistatic interactions, necessitating advanced multi-locus approaches.

Purpose of the Study:

  • To develop an efficient method for detecting epistatic interactions in high-dimensional genome-wide data.
  • To compare the performance of the novel method against existing combinatorial methods like multifactor dimensionality reduction (MDR).
  • To apply the developed method to a real-world GWAS dataset for late-onset Alzheimer's disease (LOAD).

Main Methods:

  • Development of a novel method utilizing Bayesian networks and the minimum description length principle.
  • Comparison with multifactor dimensionality reduction (MDR) using 28,000 simulated datasets across 70 genetic models.
  • Application to a large-scale GWAS dataset comprising over 300,000 single nucleotide polymorphisms (SNPs) for late-onset Alzheimer's disease.

Main Results:

  • The proposed Bayesian network-based method demonstrated superior performance in detecting gene-gene interactions compared to MDR.
  • The method proved efficient in analyzing high-dimensional genome-wide data.
  • The analysis successfully identified the GAB2 gene as associated with late-onset Alzheimer's disease, substantiating previous findings.

Conclusions:

  • The developed Bayesian network approach offers a powerful and efficient tool for model-based epistatic analysis of large-scale GWAS data.
  • This study represents the first successful application of a model-based epistatic analysis to a high-dimensional genome-wide dataset.
  • The findings reinforce the importance of considering gene-gene interactions in understanding complex diseases like Alzheimer's.