Quantitative Genetics

The quantitative genetics deals with the hereditary component of features are measured on a continuous scale, eg. B. Height or weight.

history

An early attempt to establish rules for the inheritance of quantitative characteristics was made by Francis Galton in 1889 in his work “Natural Inheritance”. Due to the rediscovery of Mendel 's rules in 1900 (by Hugo de Vries and Carl Correns ), a problem soon arose in the area of Darwin's theory of evolution : Mendel showed that there are “particular” hereditary factors (now called genes ) that are present in specified conditions are passed on to the offspring. It was initially unclear how natural selection can cause a continuous change in a trait (e.g. the size of a pea plant) if the genetic factors are discrete units (e.g. white or red flower ). Ronald Fisher was able to resolve this apparent contradiction in 1918 by showing that the interaction of many genes results in precisely those continuous distributions that are observed in nature. Sewall Wright then showed in 1931 how natural selection can change the gene repertoire that together affect a trait. In the following decades, methods of quantitative genetics were also used successfully in animal and plant breeding. Recently, the methodological arsenal available to geneticists has expanded significantly so that scientists can now examine not only the effects of genes on a trait, but also the molecular causes of the differences in gene effects. These methods are also of great importance for basic medical research, since numerous hereditary diseases are influenced by many genes at the same time.

Methods

Classic quantitative genetics

An essential goal of classical quantitative genetics is to differentiate between environmental influences and genetic factors. For this purpose, one usually considers the variance (V) of the characteristic under the assumption that it is normally distributed . So the geneticists try to break down the observed variance into its components:

${\displaystyle V_{P}=V_{G}+V_{E}}$

${\displaystyle V_{P}}$: phenotypic variance

${\displaystyle V_{G}}$: the proportion of the phenotypic variance that is caused by genetic differences (often problematically called "genetic variance")

${\displaystyle V_{E}}$: the proportion of the phenotypic variance that is caused by environmental influences

The “genetic variance” can then be further broken down to e.g. B. to research the interactions of genes with one another or of genes with environmental factors.

${\displaystyle V_{G}=V_{A}+V_{D}}$

${\displaystyle V_{A}}$: additive "genetic variance"

${\displaystyle V_{D}}$: Dominance variance

A second essential concept is the so-called heredity coefficient and is defined as the proportion of the "genetic variance" in the phenotypic variance:

${\displaystyle h^{2}=V_{A}/V_{P}}$.

The heritability coefficient is a measure of heritability and shows how much z. B. Parents and children are similar in terms of one characteristic due to their relationship.

Further topics of classical quantitative genetics:

• natural and artificial selection
• Effects of inbreeding
• Correlated features

Newer methods

• QTL mapping

" Q uantitative T rait L ocus Mapping" is the loci to find that influence a feature a method. Similar to the mapping of individual genes , attempts are made to demonstrate a link between phenotype and genotype . Since the trait under investigation is continuously distributed, this linkage is often difficult to prove, especially if a gene location has only a weak effect on the trait. Statistical methods (e.g. the maximum likelihood method ) allow a statement to be made about the probability that a certain gene location influences the characteristic. The ultimate goal of a QTL experiment is to find the nucleotides (building blocks) of DNA that change the way the gene works.

literature

• Michael Lynch , Bruce Walsh: Genetics and analysis of quantitative traits. Sinauer, 1998.
• Diethard Tautz : Heredity: Truth lies in the crowd , in: Frankfurter Allgemeine Zeitung June 14, 2019 online