Genome Wide Association Studies - MCB 104

Question 1

Why should we learn about GWAS?

Answer 1

to understand how genomic variations affect the development of disease. Similar reason to QTL. remember disease is a type of phenotype.

Question 2

What do you need for GWAS to link genotype and phenotype for any trait?

Answer 2

need to collect genotypes and phenotypes from a population.

Question 3

How would you start to understand the way a genome controls a phenotype?

Answer 3

1) Genotype thousands of individuals with densely spaced markers (SNPs)
2) know whether any genotypes correlate with phenotype.

Question 4

But what exactly is GWAS?

Answer 4

A test of the association between markers (single nucleotide polymorphisms or SNPs) across the genome and disease or quantitative trait phenotype, usually involving hundreds of thousands of SNPs spread throughout the genome

Question 5

How do you conduct GWAS?

Answer 5

Question 6

What is linkage disequilibrium?

Answer 6

deviation in the frequency ofhaplotypes in a population from thefrequency expected if the alleles atdifferent loci are associated atrandom

Linkage disequilibrium is the nonrandomassociation between two loci

Question 7

In Linkage equilibrium observed haplotypes fit _________

Answer 7

Question 8

What disrupts linkage disequilibrium? How?

Answer 8

recombination hotspots.

Question 9

What do boxes in the last image show?

Answer 9

Question 10

Pair wise polymorphisms observed and not observed in the image

Answer 10

Question 11

identify all the pairwise polymorphisms

Answer 11

Question 12

example of GWAS study

Answer 12

Question 13

GWAS has found _______

Answer 13

thousands of SNPs associated with many traits and diseases

Question 14

What does association mapping identify?

Answer 14

identifies genes for disease susceptibility using P value. [remember association mapping is just Genome Wide association mapping]

Question 15

What values do you use for association mapping?

Answer 15

• log 10 (P value) = y axis

chromosomes = x axis

Question 16

What is the CD-CV hypothesis?

Answer 16

that many common diseases are caused by common alleles that individually have little effect but in concert confer a higher risk.

Question 17

How do you conduct a GWAS for a disease? eg AWD?

Answer 17

1. Genotype SNPs
2. Do a quality control test on these genotyped SNPs
3. out of the remaining find the ones that lie on the chromosomes
4. Then for the remaining === each SNP, we test to find which allelic variation is linked to the disease status.

Question 18

But how do we know which SNPs of the 1000s genotyped is the right ones?

Answer 18

Using Bonferroni Correction technique. Only SNPs that have a p value < divide p value by the number of tests performed === considered significant. [# of tests = number of SNPs being analyzed]

Question 19

how do you conduct a multiple hypothesis testing?

Answer 19

suppose an association study genotyped 1,000,000 SNPs . Out of these 50,000 SNPs were expected associated with the disease because of chance and the large number of markers tested.

To find the actual number, you first use Bonferroni correction === divide p value by the number of tests performed. therefore, if you were going with p<0.05 level of significance, then your significance of threshold would be p < 0.05/1,000,000 = 5* 10 ^ -8

Question 20

What is linkage disequilibrium?

Answer 20

deviation in frequency of haplotypes in a population from the frequency expected if alleles at different loci are associated at random.

Question 21

How do you use Linkage Disequilibrium to associate genotype with a disease phenotype?

Question 22

What is the odds ratio and how do you use them in GWAS?

Answer 22

a way of representing probability. it is the ratio of probability that an event of interest occurs to the probability that it does not occur. OR number of times an event of interest occurs to number of times that it does not occur.

Answer 23

Question 24

comprehensive GWAS analysis has shown that Most variation is due to __________

Answer 24

Most variation is due to regulatory variants