genomic selection in cattle industry: achievements and … selection in cattle industry:...
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Genomic selection in cattle industry: achievements and impact
Dr. Fritz Schmitz-HsuSenior Geneticist
Swissgenetics
CH-3052 Zollikofen
1Scientific Seminar WBFSH 2016
Scientific Seminar WBFSH 2016 2
Source: https://i.ytimg.com/vi/CUvJxLhu79A/hqdefault.jpg
Structure
Genomics: What is it?
Application of genomics in cattle breeding
Achievements and impact experiences
Conclusions
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Genomics: What is it?
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Influence of the chromosome region on milk yield
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VanRaden (2008)
What is the difference between marker and gene tests, and genomic selection?
Lab test on a specific location
Gene test (if the causal mutation is known and tested 100 % accuracy)
Marker test (if the causal mutation is not known, but a marker exists accuracy < 100 %)
Genomic selection: Analysis of many thousands of markers spread over the whole genome
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The basics of genomic selection
Markers are here differences in one single base pair= Single Nucleotide Polymorphism (SNP)
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SNPs can be analyzed in the lab rather cheaply
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Sample
Blood
Semen
Hair bulbs
Nasal swabs
Ear tissue
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Genomic evaluation combines several information sources
Marker information
+ estimation equations
Direct Genomic Value (DGV)
Pedigree Index
own performance (if available)
performance of progeny (if available)
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Genomically
enhanced
Estimated
Breeding
Value
(GEBV)
Genomic evaluation: Uses both traditional and genomic information
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Recordings of performance, type
traits etc.
Data on relationship
Statistical procedures
Genomically enhanced Estimated Breeding Values
GEBVs
Molecular genetic markers
Or simplified
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Direct Genomic Value (DGV)
Traditionally estimated breeding value
Genomically enhanced Estimated Breeding Value (GEBV)
Fast adoption in dairy cattle breeding
2001 Theoretical framework by Meuwissen et al.
2006 Schaeffer presents model calculations showing the large potential of genomic selection
2008 - 2010 Genomic selection implemented in the principal countries
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Why dairy cattle breeding got so fast into genomic selection
Artificial insemination very common concentration on relatively few bulls
Long generation interval and huge costs for developing a progeny tested bull
Well established performance recording and genetic evaluation in place
Industry and research organizations were willing and had the means to invest into this new technology
DNA of ancient key bulls was still available
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Genomic selection in Switzerland
Joint development project of the Swiss breeding associations and the AI industry
For Brown Swiss, Red & White and Holstein
First Direct Genomic Values (DGV) published in Dec 2009
Genomically enhanced estimated breeding values (GEBV) are official since Dec 2010
Interbull validation passed in June 2011
For Original Braunvieh official since Aug 2015, for Simmental starting April 2017
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Costs for genotyping dairy cattle in Switzerland
Low Density Chip ( 30'000 SNP): CHF / US $ 138.00
• CHF / US$ 60.00 for the lab
• CHF / US$ 78.00 for calculating the GEBVs
Medium Density Chip 150'000 SNP: CHF / US $ 185.00
• CHF / US$ 110.00 for the lab
• CHF / US$ 75.00 for calculating the GEBVs
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Enormous increase of genotyped cattle
No. of genotyped cattle in the US (Cole, 2016)
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0
100 000
200 000
300 000
400 000
500 000
600 000
700 000
800 000
…
Imputed, YoungImputed, Old<50k, Young, Female<50k, Young, Male<50k, Old, Female<50k, Old, Male50k, Young, Female50k, Young, Male50k, Old, Female50k, Old, Male
Genomic selection gives for young animals breeding values with much higher reliability
Reliability increase compared to pedigree index (Cole, 2016, modified)
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Trait Bias* Reliability (%)Reliability gain
(% points)
Milk (kg) −80 69 +30
Protein (%) 0.0 86 +48
Productive life (mo) −0.7 74 +42
Somatic cell score 0.0 65 +29
Daughter pregnancy rate (%) 0.2 54 +21
Sire calving ease 0.6 46 +20
Sire stillbirth rate 0.2 28 +6
Type traits -0.2 - +0.2 44 - 75 +13 - +38
*2013 deregressed value – 2009 genomic evaluation
What is a genotype worth?(Cole, 2016)
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For protein yield (h2=0.30), the SNP genotype provides information equivalent to an additional 34 daughters
Pedigree is equivalent to information on about 7 daughters
What is a genotype worth?(Cole, 2016)
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And for daughter pregnancy rate (h2=0.04), SNP = 131 daughters
The way to a new AI bull- before genomic selection
Year 0 1 2 3 4 5 6
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Selecting parents planned mating
Buying 1 out of 2 - 3 bull calves
Rearing, producing ~5000 straws
Field test ~80 daughters
Lay-off Selecting 1 out of 6 - 10 progeny-tested bulls for large scale marketing
The way to a new AI bull- with genomic selection
Year 0 1 2 3 4 5 6
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Selecting parents planned mating
Genotyping,buying 1 out of 10 - 20 bull calves
Rearing, producing >5000 straws
Marketing as genomicallytested bull
(Lay-off) (Marketing as progeny-tested bull)
Much more younger bulls are used in Artificial Insemination (AI)
No. of marketed AI Holstein bulls in the US (Cole, 2015)
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Year entered AI Traditional progeny tested
Genomic marketed
All bulls
2008 1'768 170 1'938
2009 1'474 346 1'820
2010 1'388 393 1'781
2011 1'254 648 1'902
2012 1'239 706 1'945
2013 907 747 1'654
2014 661 792 1'453
Trend to using younger bulls shorter generation interval
García-Ruiz et al. (2016), US HolsteinSB = Sire Bull; SC = Sire Cow; DB = Dam Bull; DC = Dam Cow
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Genomic selection enables an increased genetic progress
Cole (2015):
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-100
0
100
200
300
400
500
600
700
800
00 01 02 03 04 05 06 07 08 09 10 11 12 13 14
Ave
rage
net
mer
it (
$)
Year entered AI
Average gain:$19.77/year
Average gain:$52.00/year
Average gain:$85.60/year
Other effects of genomic selection
Initially, in many countries only large AI companies invested into genomic selection
They kept the GEBVs of males for themselves
Concentration on a few companies, breeders lost information
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Other effects of genomic selection
A large reference population of well-proven bulls from which the effects of the individual SNPs are computed, is essential
Genomic selection still only works for large breeds / populations
Multi-country consortiums sharing genotypes were formed
Several new genetic defects (recessives) affecting fertility were discovered
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Hopes in genomic selection,and reality
Hope: New lines and families with large potential are discovered
Reality: Still a few top families dominate, but top animalsare quickly bypassed by even better ones
Hope: Reduced inbreeding thanks to broader selection base
Reality: With the focus on few animals, inbreeding still has to be monitored carefully, but genomics give more insight
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Hopes in genomic selection,and reality
Hope: Gain in reliability of GEBVs by using more SNPs or even sequence data
Reality: Up to now only minor increases
Hope: SNP effects estimated in one breed can be successfully applied in other breeds
Reality: Does not work satisfactorily each breed needs an own reference population
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Trends
Race of reducing the generation interval even moremore embryo transfer, ovum pick-up (OPU), in vitro
fertilization (IVF), semen sexing, genotyping embryos
GEBVs as a herd management tool which females to rear
Application in small breeds
Application of sequence data
Novel traits (health traits, feed efficiency, methane emission etc.)
Cows as an additional source for the reference population
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Conclusions
Genomic selection is in dairy cattle breeding the most important technology since the introduction of artificial insemination
It accelerates very substantially the genetic progress due to reduced generation interval and increased reliability of the estimated breeding values
It works for all traits
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Conclusions
Dairy cattle breeding was ideal for introducing this technology due to
well established performance recording
widely used artificial insemination
population structure
long generation interval
well organized breeding organizations and breeding programs
a favorable industry framework (close collaboration)
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Conclusions
Genomic selection requires
the availability of enough clearly defined phenotypes
a large reference population of proven animals to estimate the SNP effects
a substantial investment to establish it
a continued genetic evaluation based on progeny performance
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Thank you for your attention!
Questions?
34
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