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Genome-wide Association Studies-GWAS

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...

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Related Experiment Video

Updated: Jul 31, 2025

Screening for Functional Non-coding Genetic Variants Using Electrophoretic Mobility Shift Assay EMSA and DNA-affinity Precipitation Assay DAPA

Screening for Functional Non-coding Genetic Variants Using Electrophoretic Mobility Shift Assay EMSA and DNA-affinity Precipitation Assay DAPA

Published on: August 21, 2016

Interpreting non-coding disease-associated human variants using single-cell epigenomics.

Kyle J Gaulton¹, Sebastian Preissl^2,3, Bing Ren^4,5,6

¹Department of Paediatrics, Paediatric Diabetes Research Center, University of California San Diego School of Medicine, La Jolla, CA, USA. kgaulton@health.ucsd.edu.

Nature Reviews. Genetics

|May 10, 2023

Summary

This summary is machine-generated.

Genome-wide association studies link human genome variants to diseases, but interpreting these non-coding regions is difficult. Single-cell epigenomics now provides cell-type-specific maps to understand genetic disease mechanisms.

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Last Updated: Jul 31, 2025

Screening for Functional Non-coding Genetic Variants Using Electrophoretic Mobility Shift Assay EMSA and DNA-affinity Precipitation Assay DAPA

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Area of Science:

Genomics
Epigenetics
Human Biology

Background:

Genome-wide association studies (GWAS) identify numerous genetic variants linked to common traits and diseases.
A significant challenge lies in functionally annotating these variants, especially those in non-coding regions, at a cell-type-specific resolution.

Purpose of the Study:

To leverage single-cell epigenomics to create detailed maps of the epigenome in human tissues.
To enable cell type-specific annotation of regulatory elements and their target genes.
To improve the interpretation of the genetic basis of common traits and diseases.

Main Methods:

Application of advanced single-cell epigenomics assays.
Generation of cell type-, subtype-, and state-resolved epigenome maps.
Integration of epigenomic data for functional annotation of genomic regions.

Main Results:

Creation of high-resolution epigenomic maps for heterogeneous human tissues.
Identification of candidate cis-regulatory elements with cell type specificity.
Establishment of links between regulatory elements and their putative gene targets.

Conclusions:

Single-cell epigenomics provides crucial cell-type resolution for interpreting non-coding variants.
This approach enhances the understanding of the functional consequences of genetic associations.
It offers a powerful framework for dissecting the genetic architecture of common human diseases.