GWAS, Linkage Studies and Related Concepts Flashcards
What is a Genome-Wide Association Study (GWAS)?
GWAS is a research approach that scans the entire genome to identify genetic variants (SNPs) associated with specific traits or diseases
How does GWAS work?
1️⃣ Genotype Data Collection: DNA samples are obtained from individuals with and without the disease/trait.
2️⃣ SNP Genotyping: SNP microarrays or sequencing methods are used to analyze genetic variation.
3️⃣ Statistical Association Testing: Each SNP is tested for correlation with the trait using logistic or linear regression.
4️⃣ Multiple Testing Correction: Bonferroni correction is used to account for multiple comparisons.
5️⃣ Visualization: Significant SNPs are displayed using a Manhattan plot
What does a Manhattan plot represent in GWAS?
✔ Each dot represents one SNP tested for association with a trait.
✔ The x-axis = Chromosomal location of each SNP across the genome.
✔ The y-axis = -log₁₀(p-value) → Higher values mean stronger statistical significance.
✔ Tall peaks = SNPs that significantly associate with the trait/disease.
✔ Genome-wide significance threshold (typically p < 5 × 10⁻⁸) marks SNPs most likely to be truly associated rather than false positives.
What is the “missing heritability” problem in GWAS?
The missing heritability problem refers to the fact that GWAS can only explain a small fraction of estimated heritability, suggesting that additional factors such as rare variants, gene-gene interactions, and epigenetics contribute to complex traits
What are the limitations of GWAS?
❌ GWAS primarily identifies common variants with small effects, missing rare mutations.
❌ Cannot establish causation, only statistical association.
❌ Population stratification can introduce bias if genetic ancestry is not controlled for
What is a linkage study?
A linkage study tracks the inheritance of genetic markers within families to find genomic regions linked to inherited traits. It is particularly useful for Mendelian diseases.
How does a linkage study differ from GWAS?
✔ GWAS: Compares unrelated individuals in large populations to identify common variants.
✔ Linkage Studies: Track inheritance of markers within families to detect co-segregation with disease
What is Linkage Disequilibrium (LD)?
LD refers to the non-random association of alleles at different loci, meaning certain genetic variants are inherited together due to reduced recombination
Why is LD important in GWAS?
LD allows researchers to use SNPs as markers for nearby causal variants, even if the causal mutation itself is not directly detected
How does crossover (genetic recombination) affect linkage studies?
✔ Crossover shuffles alleles, breaking up LD over generations.
✔ Low recombination regions maintain strong LD, making them useful for mapping traits.
✔ High recombination rates weaken LD, making causal variant identification harder
What is heritability?
Heritability refers to how much of the variation in a trait within a population is due to genetic differences rather than environmental factors.
What are the different types of heritability?
✔ Estimated Heritability: Derived from twin and family studies, including rare and common variants.
✔ Observed Heritability: Based on SNP associations in GWAS, often lower than estimated heritability.
✔ Explained Heritability: The fraction of observed heritability that can be attributed to known genetic variants
What is a polygenic risk score (PRS)?
PRS sums the effects of multiple SNPs to estimate an individual’s genetic predisposition to a trait or disease
What is a Quantitative Trait Locus (QTL)?
A QTL is a genomic region that contains genetic variants affecting a continuous trait (e.g., height, BMI)
What is epistasis in genetics?
Epistasis refers to interactions between genes, where one gene influences the effect of another, complicating trait inheritance
Broad-Sense vs. Narrow-Sense Heritability
✔ Broad-Sense Heritability (H²) → Includes all genetic effects (additive, dominance, and epistasis).
✔ Narrow-Sense Heritability (h²) → Includes only additive genetic effects, which are inherited directly from parents.
📌 Formula:
H² = V_G / V_P (total genetic variance / total phenotypic variance)
h² = V_A / V_P (additive genetic variance / total phenotypic variance)
Why is Narrow-Sense Heritability (h²) Important?
✔ Helps predict how traits respond to selection (evolution, breeding).
✔ Higher h² = stronger inheritance & more predictable trait transmission.
✔ Used in genetic studies, animal/plant breeding, and GWAS.
