Transcript Combining Gene-based Methods And Reproductive Technologies

Combining Gene-based Methods
And Reproductive Technologies
To Enhance Genetic Improvement Of
Livestock In Developing Countries
Julius van der Werf & Karen Marshall
School of Rural Science and Agriculture
University of New England
Armidale, Australia
Outline
• Marker Assisted Selection
• Reproductive technologies
• Their joint effect on breeding programs
• Application in developing countries
Using gene testing in livestock
• Parentage testing
• Marker Assisted Selection
• Marker Assisted Introgression
• Marker Assisted Conservation
• Development of transgenics
Selection for Quantitative Traits
polygenes and major genes
True situation
Effects
Genetic
Genome
A
B
C
-2
+4
+2
+1
+1
+10
+2
0
-2
+1
+1
-2
0
-2
-1
-1
Environment Phenotype
+16
-10
+6
+3
+5
+9
+14
-4
-10
+20
+10
Observed situation
Phenotype
Genome
A
B
C
-2
0
-2
-1
-1
+10
+6
-2
0
-2
-1
-1
+3
+14
-2
0
-2
-1
-1
-4
+10
polygenic
Major
gene
The distribution of QTL effects
• Maybe 5-10 large QTL
explain the majority of the
genetic variance.
0.5
Proportion of QTL
0.4
0.3
• Mapping experiments
should be able to detect
QTL as small as 0.2p?
0.2
0.1
0
0
0.2
0.4
0.6
0.8
1
Size of QTL (phenotypic standard deviations)
Many small QTL, few of large effect
Indirect genetic markers
Marker gene
alleles
A
B
A Ram:
Major gene
alleles
His semen:
A
B
B
B
B
A
B
A
A
B
B
A
A
B
A
B
A
Indirect genetic markers
Can select among offspring ...
A
A
A
A
A
A
B
B
B
B
B
B
B
A
B
B
A
B
A
‘recombinants’
Indirect genetic markers
In reality,
we are colorblind ...
A
A
A
A
B
B
B
B
B
A
B
A
B
A
A
A
B
B
B
‘recombinants’
Indirect genetic markers
Not useful in homozygous sires
A
A
A
B
B
B
A
B
B
A
B
A
B
A
A
A
B
B
B
‘recombinants’
Indirect genetic markers
Phase can be opposite
A
A
A
B
B
B
B
A
B
A
A
B
B
A
B
B
A
B
A
‘recombinants’
Direct genetic markers
We like to find
the actual
mutations!
A
B
- always circle, always good
- always triangle, always bad
‘Direct Markers’ in Livestock
•
•
•
•
•
•
•
Genestar Marbling
Genestar Tenderness
Booroola Gene
Inverdale Gene
Callypyge Gene
Double Muscling Gene
DGAT Milk Fat%
commercialized
commercialized
Effect of MAS on rate of genetic gain
Selection after recording
Selection before
recording
Gen 1
Gen 5
Gen 1
Gen 5
2
+21%
+6%
+45%
+23%
2
+9%
+2.3%
+38%
+15%
2
+1.3%
+1.3%
+8%
+6%
h = 0.11, VQTL=0.33
h = 0.27, VQTL=0.33
h = 0.27, VQTL=0.11
Meuwissen and Goddard, 1996
Conditions that are good for MAS
• Where heritability is low
– e.g. fecundity
• Where the trait is sex limited.
– e.g. milk production, fecundity
• Trait not measurable before first selection
– e.g. milk production, longevity.
– Most traits when using juvenile selection.
• Trait is difficult to measure.
–
e.g. disease resistance, recessive conditions,
pigmented fibres, carcass traits
Short and long term effects of
Marker Assisted Selection
MAS
Normal selection
Response
Short-terms benefits 2% to 60%
0
5
10
15
Year
20
25
30
Discussion on simulation studies
• They assume response in one trait
 Need whole breeding objective context
• They assume abundant recording of pedigree
and gene testing
 Will we have cheap DNA testing available?
 We can apply strategies to save on genotyping.
 Some degree of phase-testing is needed
• They assume gene effects are known
 Need monitoring by measurement
Conclusion on MAS
• Effect on extra gain in breeding programs
maybe limited to cases where
– There are special genes with large effect
− Disease resistance, Booroola, etc.
– Breeding objective traits are difficult to measure
− Some ‘retrospective measurement is needed’
– When reproductive technologies are used
Reproductive technologies
• Reproductive boosting
– Artificial insemination: AI
– Multiple Ovulation and Embryo Transfer: MOET
– Oocyte Pickup
– Juvenile In Vitro Embryo Transfer, JIVET
• Sexing of semen and embryos
• Cloning
• Whizzy Genetics - breeding in a test-tube
Reproductive technologies
• Increases selection intensities
• Increases accuracy of EBVs
• Decreases generation intervals
• Increases inbreeding
Artificial Insemination
•
•
•
•
More intensive use of best sires
Use of bulls from other regions/populations
Establish links between herds
Progeny testing
• More rapid dissemination of superior genes
Multiple Ovulation & Embryo Transfer - MOET
• More intensive use of best cows
– “turns a cow into a sow”
• Use of cows across regions
Adult dairy MOET scheme
Cow:
MOET progeny:
Normal progeny:
Months:
not selected
0
Birth
15
Mate
24
Birth
34 35
Get record
Select & MOET
Generation interval 44 months
More offspring of top cow after testing it
44
MOET Birth
Juvenile dairy MOET scheme
Cow:
MOET progeny:
Normal progeny:
Months:
not selected
0
Birth
13
15
Mate
Select & MOET
22
24
Birth
MOET Birth
Generation interval 22 months
44
Birth
Mate
Select & MOET
MOET Birth
Generation interval 22 months
More offspring of top cow before testing it
Select based on parent average
35
Oocyte pickup and In Vitro Fertilization
Juvenile In Vitro Fertilization and Embryo Transfer - JIVET
•
•
•
Obtain oocytes before sexual maturity
Selection based on parent average
Less accuracy but much lower generation interval
Australia 1999: 32 lambs born from a 6 mo old ewe
Juvenile beef MOET/JIVET
Cow:
MOET progeny:
Normal progeny:
Months:
0
6
Birth
Select & MOET
14 15
21
29 30
Get records
Get records
MOET Birth
MOET Birth
Select & MOET
Generation interval 15 months
Generation interval 15 months
Even more juvenile beef MOET/JIVET
Cow:
MOET progeny:
Normal progeny:
Months:
0
3
12 14 15
24
28
Get records
MOET Birth
Birth
Select & MOET MOET Birth Select & MOET Get records
Generation interval 12 months
Generation interval 12 months
Between versus within family selection
No own information (performance or genotype):
Selection based on parent average
More between-family selection - more inbreeding
Genetic gain versus genetic diversity
• Sustainable breeding programs require
optimal selection balancing genetic gain
and genetic diversity
• Potential short term benefits from
reproductive technologies are inhibited by
the need to maintain diversity
The balance between increased merit and inbreeding
60
50
Unrestr.
IVEP
mean merit
merit
Mean
40
MOET
AI
30
20
10
0
0
0.04
0.08
0.12
0.16
co-ancestry
Co-ancestry
0.2
0.24
0.28
Between versus within family selection
Own information (performance or genotype):
More variation within families
More within-family selection – less inbreeding
MAS combined with reproductive technologies
• Genotype testing provides within family
information
• Exploiting this variation allows genetic gain
without jeopardizing inbreeding
MAS combined with reproductive technologies
Additional response of MAS over non-MAS under optimal selection
Select.Round
1
4
10
Adult Schemes
AI
MOET
7.8
7.1
0.0
-3.6
-3.3
-8.7
Juvenile Schemes
Juv.MOET
IVEP
63.5
42.7
102.0
54.1
41.6
10.4
Adult Schemes: Own performance is known at selection
Juvenile Schemes: Own performance is not known at selection
Conclusion: MAS mostly beneficial in juvenile selection schemes
Reprod technol. In a breeding design context
AI, MOET, JIVET
genetic improvement
Nucleus
measurement
Genetic lag
sexing, cloning
Commercial producers
dissemination
Sexing semen or embryos
• Ability to sex semen makes little difference to
rates of genetic gain:
 Usually less than 5% extra genetic gains
 About 10% in dairy (sex limited, progeny testing)
• However, effect on commercial production
efficiency can be dramatic:


e.g. Using “male semen” from terminal sires
Gene testing can help target outcomes
Cloning in animals
• Impact on rate of genetic improvement is minimal!
• Effects dissemination of good genetics
Genetic progress in the main breeding program,
and in elite clones.
Today's elite clones are
expected to be as good as
normal animals born in just
over 10 years' time.
Elite clones
Trait
Value
Normal animals
Years
Gene testing helps in clone testing and in targeting outcomes
Future technologies
• MAS in the test tube?
• There will be a continued need for phenotypic
testing
• May go toward the plant breeding practices
• IP implications?
Developing countries
• Do we need markers to improve quantitative traits?
– Unlikely, as best embedded in a program that already works
• There are more examples of ‘specific genes, e.g. for
adaptation, disease resistance, etc.
• There is more need to exploit between breed variation
• Marker assisted introgression is most likely scenario
Conclusions
• Marker assisted selection can have some benefit
in quantitative trait selection
– But genetic improvement should be driven by trait and pedigree recording
• Reproductive rates & gene technology are synergistic
• Main application of gene technologies for ‘special cases’
– Large and special gene effects, disease resistance
• Gene testing most useful in selection across breeds
– Introgression / genetic diversity