BMS2042 Lecture Notes - Lecture 16: Relative Risk, Candidate Gene, Twin Study

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Week 6. Quantitative genetics
QUANTITATIVE GENETICS
Qualitative eg. CF or no CF
Quantitative eg. height, weight, skin colour
Multifactorial inheritance = polygenic inheritance + environmental
Polygenic:
o Each gene exerts a small additive effect
o No single gene is dominant or recessive to another
o Display normal distribution
Two common characteristics of quantitative traits:
1. Many genes contribute to one trait: polygenic or multigenic inheritance
2. Trait can be affected by environment
A quantitative trait is the sum of the effects of all genes involved
Multiple gene hypothesis :
o There are two genes each with an additive allele and a non-additive allele
o Eg. cross red grain and white grain F1 shows intermediate colour -> not a single gene
pattern (ould’e been 1:2:1)
1. Quantitative trait has continuous variation that can be quantified
2. Two or more genes scattered in the genome account for hereditary influence on the
trait in an additive way
3. Each gene locus is occupied by either additive or non-additive allele
4. Contribution of each additive allele is approximately equal
5. Together the additive alleles contributing to a single quantitative character produces
substantial phenotype variation (may affect more than one trait)
Heritability: proportion of the total phenotypic variation in a population that is due to genetic
factors
o Familial: trait shared by family (may not share same genotype)
o Heritable: trait shared by people with the same genotype
o Different in different environments
o Proportion of total phenotypic variation in a population that is due to genetic factors
(looking at variances in range not absolute)
o Eg. mean heritability estimate for height sis 0.65 = 65% of overall variation in height
could be explained by genotypic differences among people)
Interaction between genes and environment can also play an important role in quantitative
traits
Estimates of variation and heritability:
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o The mean assume normal distribution
o Variance useful for understanding environmental and genetic effects
Covariance: how much do two traits vary together?
(rare for traits o vary independently)
-negative, no or positive correlation
Broad sense heritability:
o Tells the proportion of variance in a population within a single generation that is due to
genetic factors
o Low heritability: variation is due to mainly environmental
o High heritability: variation is due to mainly genotypic effects
o Ignored genotype/environment interactions
o Not useful for breeding of livestock or crops because it considers ALL genotypic effects
o H2 = Vg/Vp
Narrow sense heritability:
o Fully additive genetic variance means that the animals/plants with the desired trait are
al homozygotes (at extremes)
o Dominant genetic variance: plants/animals with desired trait could be homozygte or
heterozygote selection takes longer to breed
o H2 = Va/Vp
o Measure of how heritable a trait is by using family data
-> used in breeding to determine if a population can be changed by selective breeding
Identifying genes that affect a quantitative trait:
o Candidate gene
o QTL mapping (quantitative trait loci): especially for animals and plants
o GWAS (genome wide association studies): for human traits and disorders eg.
schizophrenia
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Document Summary

> used in breeding to determine if a population can be changed by selective breeding. Identifying genes that affect a quantitative trait: candidate gene, qtl mapping (quantitative trait loci): especially for animals and plants, gwas (genome wide association studies): for human traits and disorders eg. schizophrenia. If both parents are carriers then 1 in. If 1 child is already affected then risk is still 1 in 4. If 1 child is affected, recurrent risk is. If 2 children affected, recurrent risk is now 1 in 12 (know predisposed: recurrent risk increases because the couple are high risk, cleft palate is an example of a continuous trait with a disease threshold. Is a spectrum: relative risk ratio, odds ratio: ratio of risk to relatives of affected individual compared to general population incidence, parts of odds ratio can be distributed to susceptibility loci. Identifying multifactorial disorder genes: linkage analysis (better for single gene disorders: affected sibling pair analysis (asp)

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