L26 Association mapping in Outbred lines

Question 1

QTL Mapping not ideal…

Answer 1

see onenote

not ideal to fully dissect the molecular genetic architecture of trait variation in natural populations

crosses are complicated to carry and limit the genetic variation to what is present in the parents

Question 2

Association mapping

Answer 2

• developed to carry genetic mapping in outbred populations, potentially revealing the effect of all genes and alleles

Molecular genotyping of millions of SNP markers

Amount of data allowed translating association mapping into GWAS

estimates genetic effect and location

Question 3

Association mapping and recombination

Answer 3

see onenote

higher number of recombination => higher resolution but still relies on LD

Question 4

From association test to GWAS - the model

Answer 4

see onenote

Population is highly diverse, expect phenotype to be diverse => normal distribution

1. phenotype measure
2. genome sequencing
3. genome-wide markers

Question 5

From association test to GWAS - the output

Answer 5

see onenote

• test in parallel all the SNPs genotyped
• p-values
• Manhattan plot

Question 6

From association test to GWAS - multiple testing

Answer 6

see onenote

Multiple testing problem

• Bonferroni correction
• Modelling explicitly the False Discovery Rate (FDR) by a random permutation of the data

Question 7

False Discovery Rate

Answer 7

The false discovery rate (FDR) is a method of conceptualizing the rate of type I errors in null hypothesis testing when conducting multiple comparisons. FDR-controlling procedures are designed to control the expected proportion of “discoveries” (rejected null hypotheses) that are false (incorrect rejections).[1]

Question 8

From association test to GWAS - the confounding effect of population structure

Answer 8

see onenote

Populations isolated, have their own evolutionary history

• Within each clade, more co-variance and relatedness
• Doesn’t mean that every single SNP differentiating is involved in height when considering Pygmy population and European population
• Confounding effect, not directly involved with the trait

population structure leads to higher rate of false positives

Question 9

From association test to GWAS - non-independent between SNPS

Answer 9

see onenote

some degree of linkage between SNP resulting in correlated/non-dependent information

testing each SNP effect:
each SNP is tested while controlling for variation at other SNP loci

Question 10

The amount of genetic variance explained can be calculated as:

Answer 10

see onenote

Question 11

Caveat of GWAS

Answer 11

• considerable amount of markers tested introduces multiple testing issues
• big sample size introduced genetic heterogeneity within the sample (populations structure, linkage among SNPs)

=> lots of false positives, many candidate genes among which only a few are relevant

Question 12

Promises of GWAS

Answer 12

see onenote

• time-cost effective mapping technique
• yields high resolution based on ancestral recombinations present in the population

Question 13

Limits of GWAS

Answer 13

see onenote

• false positive association
• heterogenity in the population

Question 14

Make GWAS better

Answer 14

see onenote

repeat the experiment in multiple populations

Question 15

Allelic hetergenity

Answer 15

SNPs used as markers may not tag the same causal allele

Question 16

Functional/non-functional allele

Answer 16

see onenote

multiple mutations may have occurred independently and no SNP is different between functional/non-functional alleles

Question 17

Thinking out of the box

Answer 17

see onenote

To validate genetic effects detected:

• functional genetics
• evolutionary genetics
• ecological/landscape genomics

Question 18

GWAS Aims

Answer 18

see onenote

generating hypothesis due to extensive list of candidate genes identified

move towards a whole systems genetics approach

Question 19

Genomic selection

Answer 19

see onenote

to predict the genotype value based on molecular data from a reference population without connecting the markers to molecular functions