Transcript Lektion 12: Bio- og beregningsteknologi

Chapter 12:
Bio- and estimation technology
• Estimation technology for breeding value
estimation
• The significance of artificial insemination (AI) for
breeding value estimation
• Transgenesis and transgenic animals
• Application of DNA-markers for disease genes
• Finding disease genes or QTL‘s
The most important calculation
methods for breeding value
estimation
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Selection index (SI)
Best Linear Prediction (BLP)
Best Linear Unbiased Prediction (BLUP)
Animal Model (AM)
The significance of artificial
insemination for breeding value
estimation
Preconditions for breeding value estimations
• Standardised environment
• Test station or correction for environment
• AI, the precondition for equality, as a bull or a
boar are sire of offspring in many different herds
The significance of artificial
insemination for breeding value
estimation
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Accurate estimation (large families)
Independent of ownership
Comparable
Increased selection intensity and accuracy rIA
by AI and super ovulation
Transgenese and transgenic
animals
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Gene constructs
Methods for gene transfer
Production motives for transgenesis.
Other motives for transgenesis
Gene constructs
• Promoter (regulator-sequence)
• Structure gene (DNA-code for a protein)
Methods of gene transfer
• Micro injection of DNA in male pronucleus
• Embryonic stemcells and homologue
recombination
• Micro injection or other forms of
gene transfer into foetal cells
Motives for transgenese?
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Additive effect 4A
New metabolic traits
Pharmaceutics
Organ donation
Example of application of DNAmarkers for disease genes
DNA-marker (A,B) within families
* = disease gene, + = normal gene
Identification of DNA-marker
linked to disease genes or QTL‘s
• The genome is ca. 3000 centi Morgan (cM)
• A marker covers 20 cM
• 150 DNA-markers are needed to analyse for a given
segregation
• Ca. half of the markers are informative, so ca. 300
all together have to be applied
Family material suited for
identification of a disease gene
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Family size - ca. 50 for an analyse
At least 10 to 15 affected
The best ratio between affected and normal is 1:1
The remaining normal are excluded randomly
Genotype affected not affected
aa
20
3
not aa
4
23
Total
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26
Total
23
27
50
Family material suited for
identification of QTL’s
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Family size - more than 1000
The existence of QTL’s is unknown
Sire or grand-sire design can be applied
F2 animals in relation to exotic crosses
Sire design or Grand sire design
QTL estimation
• Grand sire design
Estimated effect on offspring’s breeding values
• Sire design
Estimated effect on offspring phenotypes
• Marker typing of parents and offspring, in both
cases
Graphic Sire and Grand-sire
design
Sire design or Grand-sire design,
test size
Least significant difference (LSD) in disease frequency
for offspring with A1 and offspring with A2
Number A1 Number A2
S.D.
LSD for disease frequency
5000
500
100
0.0060
0.0190
0.0420
1.8 % units
5.7 % units
12.6 % units
5000
500
100
Number of affected 
bin(N;0.10.9/N)
Results of selection experiments
for disease resistance
Successfull selection experiments in layers
for resistance to neo plasma fatalities, Cole
and Hutt (1973)
Successfull selection for high and low
leukocyte count in mice, Chai (1975)
Selection experiments for high or
low anti sheep erythrocytes titter
in mice.
Challenge experiments in
mice
Conclusion of experiments for
general disease resistance
Breeding measures to healthy animals
Use crosses but avoid F2 and four-way
High uniformity in production