Genomic Selection in Dairy Cattle

Genomic Selection in
Dairy Cattle
AQUAGENOME
Applied Training Workshop, Sterling
Hans Daetwyler, The Roslin Institute and R(D)SVS

• Dairy introduction
Overview
• TTraditional diti l bbreeding di
• Genomic selection
• Advantages
• Disadvantages
• Genomic selection around the world
• SSummary mmar

Dairy Cattle
• Most are specialised dairy breeds
– Holstein, Jersey, Brown Swiss, Ayrshire, etc
• Some dual purpose
– Simmental, Montbeliarde,
NNormande, d etc
t

Dairy Industry
• Relies very heavily (>80%) on artificial
insemination (AI)
• Nucleus herds exist but a large part of
bbreeding di iis still ill ddone bby ffarmer bbreeders d
• Global exchange of genetic material
between countries and AI companies
– International genetic g
evaluation

• Production
Traits selected for
– Milk, fat and protein yield...
• Conformation
– Udder, legs, capacity...
• Functional & Health
– Somatic cell score, fertility,....

Cornerstone of genetic g pprogress g
• AI Companies increase the accuracy of
selection through progeny testing.
– Young bulls sire approx approx. 100 daughters which
provide information for their EBV once the
daughters produce records
– Only 1 in 10 (or less) of bulls return to active
service
– Very costly

Bull
Life cycles
Birth 1 yr 2 yr 5 yr 10 yr
Selected on parent avg
Cow
Daughters g born
Bull is
Son is progeny
progeny tested tested
Birth 1 yr 2 yr 4 yr 7 yr
Gives Birth
Daughter Gives
Birth
Son is progeny
tested

Pedigree +
Records
Traditional Breeding
Estimation
• Accuracy increased with:
• Own phenotypic records
• Information on relatives (sibs, progeny,…)
Breeding
Vl Value

• Works well in:
Traditional Breeding
– Med.- high heritability traits
– Own records or progeny data is available
• Less effective
– Low heritability traits, sex limited traits
– Young animals (no records, no progeny)

Genotypic Information
• Thousands of single nucleotide
polymorphisms (SNP) are now available in
many species i
• SNP have 2 alleles or gene variants
1 2 2 1 2 1 2
2 1 2 1 1 2 2

Genotypic Information
• Thousands of single nucleotide
polymorphisms y (SNP) ( ) are now available in
many species
1 2 2 1 2 1 2
2 1 2 1 1 2 2
Recode 1 1 0 2 1 1 0

Genotype y Data for
Elevation - Chromosome 1
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2201000201100002202211022112101121110122220012112122200200
0200202020122211002222222002212111121002111120011011101120
0202220001112011010211121211102022100211201211001111102111
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2111111212111210110120011111021111011111220121012121101022
202021211222120222002121210121210201100111222121101
• From Filippo Miglior, Canadian Dairy Network.

The Opportunity
• Genotyping gives us ‘picture/snapshot’ of
the genetic makeup of an animal
• The more SNP the clearer the picture (up to a limit)
• This new source of information can now
(or soon) be used in genetic evaluation by:
– Combining genotyping data with traditional
pedigree and phenotypic records

Method
• Meuwissen et al., Genetics, 2001
– Divide the genome g into many y segments g ( (each
with 1+ markers)
– Estimate the genetic g effect of each segment g
from a sample of individuals
• Many small black boxes
– Genotype another population sample and
sum the segment effects to get a breeding
value l ffor eachh

How is this different?
Pedigree +
Records +
Genomic Data
Estimate SNP
effects
Genomic
Breedingg
Value

How is this different?
Pedigree +
Records +
Genomic Data
Estimate SNP
effects
Genomic Breeding
Values for animals
WITHOUT records!
Genomic
Breedingg
Value

2 Main Genomic Estimation Methods
• Genomic BLUP
– Easy to implement because similar to classic
BLUP
• Bayesian methods
– More complicated
– May have higher accuracy than GBLUP
• Papers say yes, yes practice says not so much much…

Advantages of Genomic Selection
• Increase genetic gain
– BBy increasing i i accuracy of f selection l ti
• Parent avg 40%, Genomic BVs higher
– BBy reducing d i th the generation ti iinterval t l
• Select animals before they are of productive and/or
reproductive age
• Reduce/eliminate the need for progeny testing
– Reduces cost

Bull
Life cycles
Birth 1 yr 2 yr 5 yr 10 yr
Selected on parent avg
Cow
Daughters g born
Bull is
Son is progeny
progeny tested tested
Birth 1 yr 2 yr 4 yr 7 yr
Gives Birth
Daughter Gives
Birth
Son is progeny
tested

Life cycles
Bull
Select Select Select Great- Great
Sons here Grand-sons grand-sons
Birth 1 yr 2 yr 5 yr 10 yr
Selected on parent avg
Cow
Daughters g born
Bull is
Son is progeny
progeny tested tested
Birth 1 yr 2 yr 4 yr 7 yr
Gives Birth
Daughter Gives
Birth
Son is progeny
tested

Advantages
• Lower rate of inbreeding per generation
(Daetwyler ( y et al., JABG, 2007) )
– Moves from family selection to individual selection
– Example:
• Parent average same for full sib newborns
• Genomic BV different for full sibs
– If generation intervals are shortened substantially
then annual inbreeding rates could be higher

Inbreeding rates of methods
Inbreeding
ratee
per gen. (%)
3
2
1
0
Phenotypic Sel.
Classic BLUP
Genomic Sel.
0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1
Heritability
Daetwyler et al., J. Anim. Breed. Genet., 2007

Advantages g
• Once marker effects are estimated they
can bbe used d ffor a ffew generations ti
– BUT accuracy will reduce in each generation
if not t re-estimated ti t d
• Selection on novel traits, expensive
phenotyping
• New breeding g strategies g

Disadvantages
• New method, not fully proven and tested
• Need to genotype a sufficiently large set of
animals for accurate marker estimates
(Daetwyler et al., PLoS One, 2008)
• Lower heritability more records needed
• Marker estimates must be estimated in
population that they will be used in
• Across breed accuracy low

Disadvantages
• Genotypes still costly (125£ dairy)
• Some species have no dense marker
maps yet
• When generation intervals are already low
genetic gain due to genomic selection will
be less
• In large litters accuracy can be gained
ffrom info i f on sibs ib lless advantage d t of f GS

Genotyping
• Illumina BovineSNP50 TM BeadChip
– 58,000 genetic markers, equally spaced
– 38,416 used in genomic predictions
• Total of one-third non-informative (currently) or
without variation across dairy cattle
– Openly commercialized to several
laboratories in various countries
– Current genotyping cost ≈$250 USD per
animal
Miglior, Can. Dairy Network

Genomic selection around the
world ld
• USA & Canada (N.A.) Collaboration
• New Zealand (LIC)
• Netherlands (CRV)
• Australia (ADHIS & co.)
• DDenmark k & SSweden d (Viki (Viking GGenetics) ti )
• Several other countries likely to follow
fairly soon
Miglior, Can. Dairy Network

Trait
Australian results
Table 1. Accuracy of genomic breeding values calculated at time of birth for
Genetic Australia’s 2003 progeny test team with two genomic selection
methods, BLUP and a Bayesian method (BAYES).
Records in
reference
population
Number of
SNPs used
Sire pathway
EBV GBLUP GBayesA
AUS Selection
Index 637 3889 0.62 0.66 0.69
AUS Profit
Ranking 635 3414 0.59 0.73 0.74
Protein yield 637 4055 0.53 0.67 0.69
Protein % 637 4369 0.45 0.54 0.60
Fertility 332 3090 0.40 0.42 0.37
Hayes et al, Review, JDS, 2008

• North America
World wide results
– GS Accuracy avg 71%, PA 52%
– Diff Difference bbetween t BLUP and d BBayesian i was 1%
• Netherlands
– Large increases in accuracy of GS over PA
– Use Bayesian y methods
• New Zealand
– GS accuracy avg 70 – 80%, PA 58%
Hayes et al, Review, JDS, 2008

Higher risk vs. Lower risk
• How will different AI companies use it?
• Examples:
– LIC: Reduce progeny testing from 300 to 100-
150 bulls, emphasis on DNA teams
– Recent recall announcement for HO team(s)
– CRV: Reduce progeny p g y testing g from 500 to
300 bulls, reduce YS incentives
– North-American units likely y to use a more
conservative transitional approach
Miglior, Can. Dairy Network

Possible strategy
• Genotype a large number of elite females
and bull calves
• Put the best GEBV bulls into organized
progeny testing
• Use the best of those as sires of sons, and
in teams for the GEBV bull market
• Use the best proven bulls for the proven
bull bu market a et
Miglior, Can. Dairy Network

How can we do better?
• Genotype more SNP to get clearer
‘picture’ picture of genetic variation (up to a limit)
• Genotype and get records for more
animals i l
• Refine estimation methods
– Determine when to use BLUP or Bayes
• Develop p
new estimation methods

Summary
• Dairy industry uniquely suited for genomic
selection
– Faster genetic progress possible with higher
accuracy and shorter generation intervals
• Several countries are implementing
genomic selection
– Hybrid systems merging classic and genomic
selection

Summary
• UUsefulness f l of f genomic i selection l ti ddepends d
on:
– PPopulation l ti structure/history
t t /hi t
• Size of sib families
• Generation interval
– Availability y of dense marker maps p
– Availability of many genotyped individuals
with records

Acknowledgements
• Filippo Miglior, Canadian Dairy Network,
Guelph
• BBen HHayes, Vi Victoria t i DDep. PPrimary i
Industries, Melbourne
• And my y funding... g
SABRETRAIN is funded by the Marie Curie Host fellowships for
Early Stage Research Training funding mechanism, as part of the
6th Framework Programme of the European Union European
Commission.