Statistical Genetics - week 7 Flashcards
Hardy Weinberg equilibrium. When to use?
when you have 2 versions of a gene or 2 alleles – may be the normal and the affected or 2 alleles of a SNP
what is hardy weinberg equilibrium?
p^2 + 2pq + q^2 = 1
p + q = 1
p =
the normal allele
q =
the affected allele
p^2 =
represent the proportion of individuals homozygous for the normal allele
2pq =
represents the number of heterozygous or carrier individuals
q^2 =
• q2 represents the proportion of individuals homozygous for the disease allele, and affected with the disease
If the genotype or allele frequencies are significantly different from what you’d expect (not in equilibrium) then it can be an indicator that
there’s a genotyping error with the technology so it’s one of the main reasons you use Hardy Weinberg equilibrium in genetic analysis.
Defn of linkage disequilibrium
The non-random association of alleles at different loci
What results in linkage disequilibrium in populations?
shared ancestral chromosome segments
- Imagine there’s an ancestral chromosome in yellow that picks up a mutation in a disease causing gene
This is a marker of the chromosome and it’s allele 2 of the marker locus. As the ancestral chromosome gets passed through many generations and the disease causing gene becomes prevalent in the population there’s recombination of this chromosome during meiosis. You no longer have a whole yellow chromosome, it gets broken up with the other chromosome in meiosis. So you might see a pattern like the image depending on recombination (if it occurs).
- If that marker locus with the allele 2 on it, is sufficiently close to the disease causing gene
then they will not be separated by recombination very often so will be inherited together. If inherited together more often that you’d expect by chance (i.e. equivalent to if they were on a different chromosome - 50/50 chance they’d be inherited together) then you say that the 2 variants are in linkage disequilibrium
When is linkage disequilibrium useful?
Linkage disequilibrium is really useful for mapping genes
Can think about how variation occurs within the genome i.e. SNPS
If everything segregated at random and if you assume that the allele frequency of each of these alleles is 50% then you’d expect to see the following pattern:
We’d expect for two SNPs with four alleles each at 50% frequency four “chromosomes” each at 25%
i.e. A-C, A-D, B-C, B-D
each at 25%
Can think about how variation occurs within the genome i.e. SNPS
However in reality if 2 loci are in linkage disequilibrium what you see is:
2 options
1st option: A-C 33%, A-D 33% or B-C 33%
2nd option: A-C 50%, A-D 50%