Reference: Griffiths et al.
Modern
Genetic Analysis, 2nd Edition 2003
Chapter 18
Quantitative Genetics - The study of genetics of
continuosly varying characteristics
- Variations in most populations consist of a
continuous phenotypic range instead of discrete phenotypic classes (ie: complete
blue or green eyes and partial amounts of blue and green)
Quantitave
versus Qualitative
- Mendelian Genetics applys qualitative measurements and is not useful
when dealing with continuous phenotypic range
THEREFORE
Statistical techniques and analysis are
applied to measure these variations
Examples of Statistical Measures Used in Quantitative Genetics
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Multiple factor hypothesis
- describes that a large number of genes, each with a small effect, are
segregating to produce quantitative variation.
Example: Wilhelm
Johannsen corn experiment
Johannsen used pure line ( family lines that are true breeding
from generation to generation) in his quantitative genetics analysis experiment.
He produced these true lines of corn by inbreeding and selfing.
He hypothesized that each subsequent generation would exhibit the same
phenotypic expression. He calculated the number of expression by the formula
:
Heritability of a Trait
- Question of the day about a quantitative
trait!!!
Does the observed variation in the character influenced
by genes at all???????
- Every character has a gene influenced developmental
process within it, but variation is not neccesarially the results of genetic
varaition.
- Most traits are polygenic (influenced by more than
one gene)
- Traits that are familial are when members of the same
family share them
- Traits are heritable when the similarity arises from
shared genotypes
Two general methods of finding the heritability of a trait
- Depends on phenotypic similarity between relatives
- Uses marker-gene segregation
Determining whether a trait is heritable in a human population,
relys on adoption studies to avoid enviromental similarities between relatives
Ideal subjects are identical twins
Quantifying Heritability
Phenotypic variance (Sp^2) can be broken into two parts
- Genetic variance (Sg^2) - variance between genotypic
means
- Enviromental variance (Se^2)
Sp^2 = Sg^2 + Se^2
Problem: Excludes
co-variance between genotype and enviroment
Example: Musical parents rearing musical children - Genetics
versus Enviroment ???
Therefore, essential to include co-variance: Sp^2 = Sg^2 + Se^2 + 2 cov
ge
Broad heritability (H^2): the degree of heritability of a character
Method of estimating H^2
- Makes use of genetic similarity between siblings
- Genetic correlation for siblings = 1/2
- Therfore, the difference in genetic correlation between
full and half sibs is 1/4
- Have to include enviromental variance, so use phenotypic
correlation
H^2 = 4 [(correlation of full siblings) - (correlation of
half-siblings)]
Can also use parent or twin inforamtion
Meaning H^2
Two conclusions from heritability studies
- If H^2 is non-zero, genetic differences have influenced
variation between individuals, if 0, does not neccesarily mean genes are relevant
- H^2 is limited in prediction of effects of enviromental
modification under particular circumstances
Locating the Genes
Not possible with genetic techniques to identify all genes
that influence the development of a given trait.
Genetic Analysis - detects only when there is some allelic
variation
Molecular Analysis - can identify genes even when they do
not vary (provided the gene products can be identified
A trait may show continuous phenotypic variation, but the genetic basis
for the differences must be an allelic variation at a single locus.
It is possible to use prior knowledge of biochemistry and development to
guess that variation at a known locus is responsible for at least some of
the variation in phenotype.
This locus is then a candidate gene for investigation of continuous phenotypic
variation
Marker Gene Segregation
- Quantitative Trait Loci (QLTs) = genes segregating
for a quantitative trait
- Cannot be individually identified in most cases
- Possible to localize those regions of the genome
in which the relevant loci lie
- Analysis is done in experimental organisms by
crossing two lines that differ markedly in the quantitative trait and differ
in alleles at known loci, Marker Genes
- Has to be where different genotypes can be
distinguished by criteria such as some visible phenotypic effect (ie. Drosophilia
eye color)
Linkage Analysis
- Localization of QLTs to small regions within a chromosome
requires that there be closely spaced markers along the chromosome
- An unlinked marker locus will have the same average
value of the quantitative trait for all its genotypes
- For humans:
- Possible to use the differences among sibs carrying
different marker alleles from heterozygous parents. This method has much less
power to find QLTs.
- Consequence - attempts to map QLTs for human traits
have not been succesful
- Although, segregating marker techniques has
been a success in finding loci whose mutations are responsible for 1 gene
disorder
More analysis of variance
Two Types
- Additive Variance (Sa^2) - The genetic variance associated
with the average effects of substituting one allele for another
- Dominance Variance (Sd^2) – The genetic variance at
a single locus that is attributable to dominance of one allele over another
Sg^2 = Sa^2 + Sd^2 OR
Sp^2 = Sg^2 + Se^2 = Sa^2 + Sd^2
h^2 – proportion of phenotypic variance accounted for by additive genetic
variance only (heritability in a narrow sense). This value is useful in determining
whether a program of selective breeding will succeed in changing a population.
h^2 = Sa^2 / Sp^2
The effect of selection depends on the amount of additive genetic variance
in a population and not on the genetic variance in general. Therefore, the
narrow heritability, h2, not the broad heritability H2, is relevant for a
prediction of response to selection.
Estimating the Components of Genetic Variance
• All non additive variance is attributed to dominance
variance
• The slope of a regression line in comparing offspring
values to midparent values for a character with heritability can be used
to estimate h2. This can then be used to predict the effects of artificial
selection (figure 18-14)
Midparent value – average phenotype of two parents
Selection Response – difference between the offspring of the selected
parents and mean of the parental generation
Selection differential – the difference between the mean of a population
and the mean of the individuals selected to be parents of the next generation.
Selection Response = h2 * Selection Differential
• h2 estimate depends on the assumption that there is no
correlation between similarity of individuals’ environments and the similarity
of their phenotypes
• h2 in one population in one set of environments will
not be the same as h2 in a different population in a different set of environments
(figure 18-13)
Use of h2 in Breeding
• Higher value of h2 reflects a higher offspring-parent
correlation in heritability
• If h2 is low, then only a small fraction of parental
superiority will appear in the next generation
• If h2 and H2 are both low, then this signifies a large
proportion of genetic variance
• If h2 is low, but H2 is high, then there is not much
environmental variance
Hybrid – Inbred Method – Large number of inbred lines from selfing.
Lines are then crossed in many different combinations, and the cross that
gives the best hybrid is chosen
The subdivision of genetic variation and environmental variation provides
important information about gene action that can be used in plant and animal
breeding.