Microarray-Based Genotyping for GWAS Quiz

Podcast

Play an AI-generated podcast conversation about this lesson

Questions and Answers

What is the most commonly used method for obtaining genotypes for GWAS?

Microarray-based genotyping (correct)

Whole genome sequencing

Next-generation sequencing

Sanger sequencing

What is the purpose of genotype imputation in GWAS?

To infer unobserved genotypes in a sample of individuals (correct)

To validate the accuracy of genotyping results

To identify novel genetic variants associated with a trait

To increase the statistical power of the association analysis

How do DNA microarrays (SNP chips) compare to sequencing in terms of cost-effectiveness for GWAS?

Microarrays cannot be used for GWAS due to their high cost

Sequencing is more cost-effective than microarrays

Microarrays and sequencing have similar costs

Microarrays are more cost-effective than sequencing (correct)

What is a key limitation of using DNA microarrays (SNP chips) for GWAS?

They cannot capitalize on all the genomic information Signup and view all the answers

What is the main purpose of the 1000 Genomes Project in the context of GWAS?

To provide a reference panel for genotype imputation Signup and view all the answers

What is the key step prior to conducting a GWAS?

Performing quality control on the genotype data Signup and view all the answers

What is the DNA sequence variation commonly studied in GWAS?

Single-nucleotide polymorphisms (SNPs) Signup and view all the answers

What are the blocks of correlated SNPs that show a significant association with a trait known as in GWAS?

Genomic risk loci Signup and view all the answers

What is the main technology used in the HapMap Project for genotyping?

Genotyping microarrays Signup and view all the answers

Why do GWAS often require very large sample sizes?

To identify reproducible genome-wide significant associations Signup and view all the answers

Which type of cohorts can be used in GWAS data collection?

Biobanks or cohorts with disease-focused or population-based recruitment Signup and view all the answers

Where do the majority of GWAS draw their data from?

Pre-existing resources with genotypic and phenotypic information Signup and view all the answers

What does the Manhattan plot represent in a GWAS?

It shows the strength of association between genetic variants and a phenotype, with the y-axis representing the -log10 transformed p-values. Signup and view all the answers

What is the purpose of functional follow-up analyses in GWAS?

To identify the causal variants and their potential mechanisms of action. Signup and view all the answers

What is the role of expression quantitative trait loci (eQTLs) in functional follow-up analyses of GWAS?

To identify the target genes associated with the GWAS locus. Signup and view all the answers

What is the purpose of pathway enrichment analysis in GWAS follow-up studies?

To identify the biological pathways that may be perturbed by the GWAS-implicated genes. Signup and view all the answers

What is the role of CRISPR perturbation in functional follow-up of GWAS?

To experimentally validate the causal role of GWAS loci or genes and study their cellular phenotypes. Signup and view all the answers

What is the significance of the 1000 Genomes Project in GWAS?

It provided a comprehensive catalog of human genetic variation for imputation and quality control. Signup and view all the answers

Study Notes

Genome-Wide Association Studies (GWAS)

Single-nucleotide polymorphisms (SNPs) are the most commonly studied genetic variants in GWAS.
GWAS typically report blocks of correlated SNPs that show a statistically significant association with the trait of interest, known as genomic risk loci.

The HapMap Project

Mission: Develop a haplotype map of the human genome and describe the common patterns of human DNA sequence variation.
Major technology used: genotyping microarrays.
Genomic features assayed: single nucleotide polymorphisms (SNPs).

How GWAS Works

The first step of a GWAS involves identifying the disease or trait to be studied and selecting an appropriate study population.
GWAS often require very large sample sizes to identify reproducible genome-wide significant associations.
The choice of data resource and study design depends on the required sample size, the experimental question, and the availability of pre-existing data or the ease with which new data can be collected.
GWAS can be conducted using data from resources such as biobanks or cohorts with disease-focused or population-based recruitment.
Public resources provide access to large cohorts with both genotypic and phenotypic information.

Manhattan Plot

A Manhattan plot shows the significance of each variant's association with a phenotype.
Each dot represents a single-nucleotide polymorphism (SNP), with SNPs ordered on the x-axis according to their genomic position.
The y-axis represents the strength of their association measured as – log10 transformed P values.
The red line marks the genome-wide significance threshold of P < 5 × 10–8.

Functional Follow-up on GWAS

GWAS identifies associated variants, which are visualized as a Manhattan plot to show their genomic positions and strength of association.
To prioritize likely causal variants, specific statistical analyses are applied to identify a set of variants that are likely to include the causal variant.
Functional annotations of the genome can be integrated with GWAS data to identify epigenetic mechanisms that may be perturbed by the causal variant, including enhancers, promoters, or other functional elements.
Additional approaches include mapping molecular quantitative trait loci (molQTL) and expression quantitative trait loci (eQTLs).
To identify pathways whose perturbation may mediate the trait in question, one can analyze the enrichment of multiple GWAS-implicated genes in predefined pathways.

Genotyping Methods

Microarray-based genotyping is the most commonly used method for obtaining genotypes for GWAS due to the current cost of next-generation sequencing.
DNA microarrays contain hundreds of thousands or millions of probes that can be used to interrogate genomic sequence.
Advances in array-based approaches have enabled detection of the main forms of genomic variation: amplifications, deletions, insertions, rearrangements, and base-pair changes.
Imputation is a key step prior to a genome-wide association study (GWAS) or genomic prediction.
Genotype imputation is the process of inferring unobserved genotypes in a sample of individuals using a sequenced haplotype reference panel such as the 1000 Genomes Project.

Studying That Suits You

Use AI to generate personalized quizzes and flashcards to suit your learning preferences.

Description

Test your knowledge on microarray-based genotyping and its application in Genome-Wide Association Studies (GWAS). Learn about the probes, genomic variations, and how GWAS works in genotyping. Practice questions on sample and variant quality control processes.