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This presentation has been supported by the Erasmus

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Plus K2 Cooperation Partnerships.

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Innovation of the structure and content of study programs
in the field of animal

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genetic and food resources management

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with the use of digitalization innovation.

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Support for the production 

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of this presentation

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does not constitute

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an endorsement of the contents,
which reflects the views only of the authors.

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And the Commission cannot be held responsible for any use
which may be made

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of the information  

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contained

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therein.

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This presentation

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 has been created by Stanislav

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Socha, University of Siedlce.

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This lecture will be concerning

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genetic parameters, repeatability and genetic correlations

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Modul no. 3: Improvement of Animals

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The genetic parameters

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of the population include heritability of features,
repeatability of features and correlations,

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including genetic phenotypic and environmental correlations.

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Further, 

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characteristics important

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in animal husbandry include performance of animals.

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For example, milk yield, animal reproduction and health.

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Generally, the features can be classified into two groups.

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Quality features and quantitative characteristics.

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The main factor

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differentiating these two

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groups of traits
is the number of pairs of alleles genes affecting their formation

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and the number of classes of differentiated phenotypes.

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In the case of qualitative traits.

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The number of pairs genes or a series of alleles

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influencing their formation is limited, ranging

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from one to a maximum of 2 to 4.

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This, in turn affects a limited number of genotypes.

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Hereditary assumptions of individuals and consequently individuals
with specific phenotypes.

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Total characteristics of the organism.

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In the case of features

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defined as quantitative, the situation is much more complex.

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Firstly, the number of genes polygens

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affecting their shape is very numerous,
sometimes difficult to determine.

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Then, in addition to genetic assumptions,

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environmental factors
have a significant impact on their formation.

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This type of inheritance
significantly increases the diversity of individuals in the herd

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and makes it extremely difficult to identify genotypes

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based on phenotype.

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With the multiplicity of factors influencing traits

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it is impossible to determine the contribution of a single gene
to the formation of a quantitative trait.

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Only statistical methods allow to determine the influence
of genotype and environment on the variability

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of the trait in the herd, and to estimate the heritability
of the traits of interest on this basis.

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And if

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each heritability H2

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informs us in a very general sense

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about what part of the general phenotypic variation
of a given trait in

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the population is genetic variation
diversity caused by the action of genes.

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Heritability also determines
how much of the selection difference will be transferred

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to the offspring in the form of breeding progress.

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The heritability of traits is measured

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by the heritability coefficient h two.

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It is the ratio of genetic variation to phenotypic variation.

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We can express this with the formula

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H two equals delta two G slash delta 2P

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where Delta 2P equals delta 2G plus delta 2E.

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Were delta 2P - phenotypic variability,

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total variable ity of a given trait in a herd population.

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Delta 2G - genetic variation, delta 2E - environmental variability

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Discover

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ratio of genetic variation to overall phenotypic variation.

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The degree of influence of the variability
of the hereditary assumptions

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of a given trait
on the manifestation of variability in the phenotype.

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The regression coefficient of the breeding value
against the phenotypic

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value of the same individual (refers to the population)

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After

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a note,

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it makes it possible to determine to what extent the observed
phenotypic

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variability results from genetic variability

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determines the regression of G against P allows

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to predict 

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estimate the breeding value.

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Allows you to predict the effectiveness of selection

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because

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h to the symbol derived from the analysis of variance

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refers to the mean square of deviations of some of its components.

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H to correlation between genotype and phenotype.

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But again, that this is not the problem, the more we divide

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Analysis of variance,
we estimate the mean and variance

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for the whole population.

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for all groups of half siblings.

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for all sibling groups.

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We rely on analysis of

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Half sibling groups.

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Cattle, sheep, 

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and full sibling groups.

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Poultry, pigs.

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We calculate on the basis of intraclass correlation coefficients

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analysis of full sibling groups

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h2  → population parameter

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Varied depending on the characteristics.

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Varied depending on time in the same populations.

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Varied depending on the population.

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For the same features H2 from 0 to 1

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or from 0 to 100.00%.

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Group

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The repetition of traits

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is one of the genetic parameters of a population.

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The repeatability of traits can be estimated for traits
that are cyclically repeated in animals.

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For example, the number of young in successive litters, body
weight of successive litters,

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the amount of milk obtained from cows
and other mammals in successive lactation

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When estimating the repeatability index.

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We assume that the genotype of animals
does not change over the course of their lives

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and the differences that arise in subsequent years of use

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result from environmental influences.

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They can also result from the somatic development of animals.

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Estimating the repeatability index 

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(r’, R):    P = H + EES + EEN   

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OR  σ2p = σ2g + σ2Es + σ2En

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σ2p - phenotypic variability

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σ2g – genetic variability

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σ2Es – constant environmental variability,

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σ2En  – variable environmental variability.

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regression method of posterior performances,

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regression method of later performances

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to earlier performances 

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Estimating the repeatability index 

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(r’, R):

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P = H + EES + EEN   OR   
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σ2p = σ2g + σ2Es + σ2En

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σ2p - phenotypic variability 
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σ2g – genetic variability

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σ2Es – constant environmental variability

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σ2En  – variable environmental variability.

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r’ = (σ2g + σ2Es)/(σ2g + σ2Es + σ2En)

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The method of regression 

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of later performances
to earlier performances.

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Variance analysis Method Selected values

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of estimated repeatability ratios.

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number of piglets in pigs.

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0.1 - 0.15

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Number of young in rabbits.

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0.09 - 0.12

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number of young in chinchillas 0.12 - 15.

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repeatability of milk yield 

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in cattle 0.25 - 0.35

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Correlations result from linkage

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of genes -
conditioning individual traits are on the same chromosomes.

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Selection of two features in the same direction,
which in turn leads to the occurrence of interdependence.

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Pleiotropic
influence of individual genes on various traits 

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With low heritability of traits

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the value of the phenotypic correlation
is close to the environmental correlation. With high heritability,

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the phenotypic correlation will be close
to the genetic correlation.

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In the case of medium sized heritability,

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or when one trait has a high and the other a low

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the genetic correlation and may be positive and the phenotypic

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correlation negative.

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VALUES OF SOME PARAMETERS IN ANIMAL HERDS - HERITABILITY

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Cattle: milk yield 0.31 0.39

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Fat content 0.56 - 0.68,

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Milk Protein 

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content about 0.57.

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Body weight at birth about 0.40.

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Body weight at the age of 120 days,
about 0.50 daily gain of about 0.40.

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Slaughter efficiency of about 0.60.

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Height of the withers about 0.542.

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Carcass length about 0.75.

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For area of the eye of the tenderloin about 0.178.

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Pigs:

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Daily gain 0.30.

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Average daily gain 4290 kilograms 0.26

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for fat thickness on the back about 0.50.

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Length of the carcass about 0.50.

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Amount of meat in basic cuts

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about 0.520.

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Area of the eye of the tenderloin about 0.740.

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Lighter weight three weeks approximate 0.080

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litter size at birth is about 0.10.

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Sheep:
body weight at birth 0.30.

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Body weight after weaning 0.30.

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Body weight ten months 0.28.

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Shearing Pure fiber Efficiency 0.28.

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Wool thickness 0.40.

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Human Mass 0.40 000.

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Wool Height 0.52.

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Milk Yield 0.18.

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Fleece weight of the second shearer 0.32.

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Poultry:

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egg size 0.45.

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Egg weight 0.30.

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Laying capacity 0.20.

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Shell Color 0.70.

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Fertility 0.10.

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Feed Efficiency 0.60.

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Body weight eight weeks 0.10 - 0.30

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Stroke Length 0.10 - 0.30

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Cattle correlations

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with milk yield fat content in milk dash zero 41

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phenotypic 0.43 Genetic

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fat content Protein content in milk

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0.57 phenotypic 0.60.

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Genetic weight at birth at the age of one year.

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0.34 phenotypic 0.40.

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Genetic trunk length body weight 0.70 phenotypic 0.83.

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Genetic Poultry Body weight Egg weight

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0.30 phenotypic 0.25.

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Genetic body weight Breast Angle

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0.38 phenotypic 0.68.

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Genetic body weight Stroke Length

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0.4120.74 phenotypic 0.832.

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0.89. Genetic.

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Pigs daily gain back fat thickness

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-0.10 phenotypic -0.20.

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Genetic body length Back fat thickness -0.30

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phenotypic -0.40.

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Genetic.

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Thank you for your attention.