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Related Concept Videos

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...
Pharmacogenomics: Identification of New Drug Targets01:29

Pharmacogenomics: Identification of New Drug Targets

Advances in genomics have profoundly influenced drug discovery by increasing both the speed and accuracy of pharmaceutical development. Pharmacogenomics, which examines how genetic variation influences drug response, facilitates the identification of novel therapeutic targets and enables patient stratification for personalized treatment. These strategies contribute to improved drug efficacy, minimized adverse effects, and more efficient clinical trial design.Mapping genetic differences...
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...
Polygenic Traits01:18

Polygenic Traits

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Pleiotropy01:33

Pleiotropy

Pleiotropy is the phenomenon in which a single gene impacts multiple, seemingly unrelated phenotypic traits. For example, defects in the SOX10 gene cause Waardenburg Syndrome Type 4, or WS4, which can cause defects in pigmentation, hearing impairments, and an absence of intestinal contractions necessary for elimination. This diversity of phenotypes results from the expression pattern of SOX10 in early embryonic and fetal development. SOX10 is found in neural crest cells that form melanocytes,...
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Microarrays are high-throughput and relatively inexpensive assays that can be automated to analyze large quantities of data at a time. They are used in genome-wide studies to compare gene or protein expression under two varied conditions, such as healthy and diseased states. Microarrays consist of glass or silica slides on which probe molecules are covalently attached through surface functionalization. Most commonly, the slides are prepared through the chemisorption of silanes to silica...

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Related Experiment Video

Updated: Jun 25, 2026

Mapping Alzheimer's Disease Variants to Their Target Genes Using Computational Analysis of Chromatin Configuration
04:41

Mapping Alzheimer's Disease Variants to Their Target Genes Using Computational Analysis of Chromatin Configuration

Published on: January 9, 2020

Mapping complex disease traits with global gene expression.

William Cookson1, Liming Liang, Gonçalo Abecasis

  • 1National Heart and Lung Institute, Imperial College London, London SW3 6LY, UK. w.cookson@imperial.ac.uk

Nature Reviews. Genetics
|February 19, 2009
PubMed
Summary
This summary is machine-generated.

Gene expression variation influences complex disease susceptibility. Mapping genetic factors (expression quantitative trait loci or eQTLs) provides biological insights into disease associations and gene networks, enhancing our understanding of pathogenesis.

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An Allele-specific Gene Expression Assay to Test the Functional Basis of Genetic Associations
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An Allele-specific Gene Expression Assay to Test the Functional Basis of Genetic Associations

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Related Experiment Videos

Last Updated: Jun 25, 2026

Mapping Alzheimer's Disease Variants to Their Target Genes Using Computational Analysis of Chromatin Configuration
04:41

Mapping Alzheimer's Disease Variants to Their Target Genes Using Computational Analysis of Chromatin Configuration

Published on: January 9, 2020

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

An Allele-specific Gene Expression Assay to Test the Functional Basis of Genetic Associations
10:17

An Allele-specific Gene Expression Assay to Test the Functional Basis of Genetic Associations

Published on: November 3, 2010

Area of Science:

  • Genetics
  • Genomics
  • Molecular Biology

Background:

  • Gene expression variation is a key factor in complex disease susceptibility.
  • Genome-wide association studies (GWA) identify disease-associated genetic regions.
  • Understanding the genetic basis of gene expression is crucial for disease research.

Purpose of the Study:

  • To map genetic factors influencing individual differences in gene expression levels (expression quantitative trait loci or eQTLs).
  • To leverage eQTL information for biological insights into GWA study findings.
  • To identify gene networks involved in disease pathogenesis.

Main Methods:

  • Simultaneous genome-wide assays of gene expression and genetic variation.
  • Analysis of quantitative levels of gene expression.
  • Mapping of genetic factors (eQTLs).

Main Results:

  • Established a framework for mapping expression quantitative trait loci (eQTLs).
  • Demonstrated the utility of eQTL data in interpreting GWA study associations.
  • Highlighted the potential for identifying gene networks in disease.

Conclusions:

  • Systematically generated eQTL information offers direct biological insights into disease associations.
  • eQTL mapping is a valuable tool for understanding disease pathogenesis.
  • Future technological advancements and international collaborations will expand eQTL maps for broader disease understanding.