Genetics II Flashcards
Example: STATURE
Known to be influenced by genetic variations (~80-90%)
1st known genetic variation to affect height found in 2007
- Single nucleotide change in HMGA2 gene
- Homozygotes = 1cm taller (<1% variation)
Weedon, M. N. et al. Nature Genet. (2007)
* In 2008 genome-wide association study (GWAS)
identifies 20 loci that influence adult height (~3% variation -5cm)
Weedon, M. N. et al. Nature Genet. (2008)
* Allen, H.L. et al. Nature (2010)
- 180 loci explains ~10% of variation (n>100,000)
* GIANT study (Nature Genetics 2014)
- >400 loci explains ~20% of variation (n>250,000)
- Update on n=5.4M - >12,000 loci ~40% of variation (Nature
2022)
Example: Coronary Artery Disease
(CAD) (polygenic/complex - discrete)
*
* Single largest killer (males and females) in
developed countries
* Multiple genetic and environmental influences and
interactions
- Risk factors also complex traits
- continuous and discrete
- Cholesterol
- Hypertension
- Obesity
For complex traits
- how much of the variation between people is due to
genetic differences between them and how much is due to
them experiencing different environments ?
Key questions
- For a particular trait, is the observed variation influenced by genetic variation and/or by
environmental factors? - How important is genetic variation as a source of total phenotypic variation? (Heritability)
- How many genes are involved and where in the genome are they distributed? (Association studies, whole genome sequencing)
- If there is genetic variation, what is the phenotype of the various genotypes in different environments?
(epigenetics)
For complex traits
Heritability
*H= h2
* H can take any value between 0 and 1
* His a feature of a population
The relative sizes of g and Ve tell us about the contribution of the variation in our genetics and environment to the differences between people (phenotypic variation)
Measuring Heritability
Heritability
H and resemblance
between relatives
As H increases, children tend to resemble more
closely their parents
*As H increases so does
the response to selection
H and resemblance
between relatives
Measuring Heritability
Complex traits can be continuous or discontinuous (discrete)
Continuous - shows a series of overlapping phenotypic
classes
- Height, weight
- Can estimate H using correlations
- Discontinuous - shows distinct phenotypes
- Cancer, Schizophrenia
- G + E combine to determine an underlying risk or liability toward trait (continuous)
- Estimate H from the frequency of the trait in relatives and in general
population - Examining difference in concordance rates between MZ and DZ twins
complications
H is not a constant
— varies in space and time
Not the same in all populations or all generations (different gene variations; new variations; different environments)
*
* Shared environment can over-estimate H
- Genotype - Environment Interaction
- Assortative mating (ie non-random)
ー
Makes Vg appear larger - H is overestimated
Assortative mating can affect genotype frequency
and can lead to overestimates of H
How do we assess the effect of assortative mating on the expected genotype frequencies and r (coefficient of relationship)? NB: relates to earlier session on HWE
Assortative mating can affect genotype frequency
and can lead to overestimates of H
Coefficient of inbreeding (F)
* For an individual
* Probability that an individual has 2 genes at a locus that are identical by descent
* F = 1/2 (r) of parents
- “” is the coefficient of relationship
* F = 0 if parents are unrelated
Polygenic inheritance model (Vc)
Each gene can have a small effect
* The separate effect of each gene cannot be detected by
observing the phenotype
* Major or Minor genes
* QTLs (Quantitative Trait Loci) - commonly used in agriculture and
breeding
* eQTLs (variants that affect expression)
Polygenic inheritance model (Vc)
Re-evaluating the complexity
Polygenic (and pleotropic)
a number of genotypes or mutations at different loci contribute to complex
trait (polygenic inheritance)
Locus heterogeneity (act independently) or Epistasis (gene interaction)
* Gene X environment interactions
- Developmental or time-dependent expression of genes
- Gene has its most pronounced effect at a certain time or developmental
stage (e.g., puberty). - General aging of the system
- either through programmatic senescence or general wear and tear
Linkage vs. Association
inkage = Seeks to identify chromosomal segments
shared by affected (family) members
* e.g. affected sib pairs
* Results in large candidate regions
Linkage vs. Association
Association = Measures preferential
segregation of a particular allele with a phenotype across
families
* e.g. case control studies
* Usually highlight smaller candidate regions
Genome-wide Association Studies (GWAS)
Test 500K to 1M SNPs across the genome (tags >90% variation)
- Test whether a particular allele occurs at higher/lower trequency among attected than unaffected individuals
(case-control studies)
disease cases
controls
* Involve population correlation, rather than co-segregation within a family
Example: GWAS for common diseases/disorders
British Population
* ~2000 individuals for each of 7 diseases
* Bipolar, Crohn’ s, T1D, CAD, T2D,
Hypertension, RA
* ~3000 shared controls
* 50 Research Labs
* Non-European ancestry excluded
Missing heritability
- need to go beyond GWAS
Rare variants
Need to use very large number of individuals to examine rare variants
Some variants may be population specific - replication dificult
- Exome Sequencing
genome)
Examine the few percent of genome that contain exons (~ 1% of - Whole genome sequencing still costly for large numbers
Adding to the complexity
Phenotypic plasticity (G-E interaction)
- Variation, under environmental influence, in the phenotype associated with a genotype
- Epigenetics
