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Potential and Pitfalls for Genomic Selection
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Topics
• Review of genomic technology and implementation 4-path model
• Comparisons of early genomic predictions to actual daughter proofs Traits to be careful Who should be using genomics, who not? Spread risk
• Genomics as a herd management tool• Inbreeding• Beyond SNPs
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From Phenotype to Genotype:diacylglycerol acyltransferase 1
• Enzyme involved in triglyceride synthesis Chromosome 14 Knockout mice: complete absence of milk production
• Bi-nucleotide substitution: lysine to alanine +300 lbs milk +5 lbs protein +.17% fat -13 lbs fat Fatty acid profiles altered
• Terrific – but…Grisart et al., 2002
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Whole Genome Approach
• Single nucleotide polymorphisms 10 – 50 million present in genome Not inherited independently of each other
• Tests Bovine SNP 50
• Cost: $125 Low density
• 9,000 currently (replaces 6K, which replaced 3K)• Used to “impute” 50K• Cost: $45
High density• ~777,000• Early research has not been exciting• Cost: $250
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Association of SNP with Fat Yield
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Association of SNP with Final Score
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Genetic Progress
• How does this speed genetic progress?
IntervalGeneration
ianceGeneticVarntensitySelectionIyreliabilitYearG
**/
Calf
SireSire of Sire
Dam of Sire
DamSire of Dam
Dam of Dam
1.Lower generation interval2.Higher accuracy for females3.Selection Intensity
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Implementation
• First official proofs in January of 2009• Quickly adopted
Sires of sons – vast majority• Marketing differs by
bull stud Mixed lineup separate lineups
2008 201105
101520253035404550
Young sire matings
Holstein Jersey
Perc
ent
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Comparison of Jan 2009 to Dec 2012 Daughters Deviations
517 bulls0 daughters in 2009 and ≥100 daughters currently
R² = 0.546563821115401
Milk Yield
2009 PTAM
2012
Dau
Yie
ld D
evia
tion
R² = 0.340733769228037
Productive Life
2009 PTAPL
2012
Dau
Dev
iatio
n
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Realized Reliabilities
Milk yield Daughter Preg Rate Productive Life0%
10%
20%
30%
40%
50%
60%
70%
80%
HolsteinJerseyBrown Swiss
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Top 25 Young Sires and Proven Bulls in 2009
Average 2009 Average 2012 Top 20120
100
200
300
400
500
600
700
800
900
Genomic YSProven
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Net Merit Changes
Aug-08
Nov-08
Feb-09
May
-09
Aug-09
Nov-09
Feb-10
May
-10
Aug-10
Nov-10
Feb-11
May
-11
Aug-11
Nov-11
Feb-12
May
-12
Aug-12
0100200300400500600700800900
1000
FreddieCassinoSholtonAtwood
$
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Traits to watch
• Productive Life Must wait for cows to die Predictors to help
• Calving related traits
Body Size
Udder Feet & Legs
DPR SCS-0.6
-0.4
-0.2
0
0.2
0.4
0.6
0.8
Productive Life Genetic Corre-lations
Previous Current
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Who Should Use Genomic Young Sires?
Use• Involved with marketing
Will have hits and misses Goes with the territory
• Not marketing Watching calving traits on
virgin heifers Spreading risk by using a
selection Willing to accept some
misses
Do not use• Not marketing• You want to minimize
calving issues• Willing to miss out on the
best for 3 years Average may not be
different, but top will be lower
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Beyond Sire Selection
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DNA Level Mating Decisions
• Replacement for visual appraisal mating programs?
• Chromosome level mating http://
aipl.arsusda.gov/CF-queries/Bull_Chromosomal_EBV/bull_chromosomal_ebv.cfm
Use 17 digit ID style (HOUSA000000000000) Cows entered on same page as bulls
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Can we Improve Her?
23 gallons/day for a year
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Haplotype Projections: Milk
Brown Swiss Holstein Jersey0
10000
20000
30000
40000
50000
60000
70000
80000
90000
Largest DGV Lower Bound Upper Bound
Sele
ction
Lim
it M
ilk (l
bs)
Cole et al., 2011
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Haplotype Projections: DPR
Brown Swiss Holstein Jersey0
20
40
60
80
100
120
140
160
Largest DGV Lower Bound Upper Bound
Sele
ction
Lim
it D
PR
Cole et al., 2011
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Opportunity 2013
• Only bull studs can genotype males 6 Studs• Contributed $ and DNA
License agreement• Newer chips detect Y chromosome genes• Agreement ends in 2013• If you have a good bull, do you sell him?
Market your own bull? What will it cost?
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Genomics as a Herd Management Tool
• Premise: Genomics can play a role for commercial milk producers with excess heifers
• Helpful link http://edis.ifas.ufl.edu/pdffiles/AN/AN27000.pdf
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NY-PA Replacement Rates
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NY-PA Cull Rates
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Maintaining Herd Size
• More replacements than needed Increase cull rate?• Fewer problem cows• Less “mature milk”
Sell heifers?• Lower feed costs• Heifer market sustainable?
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Selling Heifers
• Value of testing• Herd improvement by culling the bottom end
70%, 80%, or 90% of calves kept What happens to the value of my remaining
calves if I genomically test first? What is the $ Net Present Value of testing?
**First culling threshold: sick/diseased calves
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$Net Merit of Remaining Calves
0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%0
50
100
150
200
250
90% kept 80% kept 70% kept
% of calves tested
$ N
et M
erit
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$Value = $NM – Test Cost
0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%0
20
40
60
80
100
120
140
90% Kept 80% Kept 70% Kept
% Tested
$ N
et M
erit
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Net Present Value
• We don’t need to test every calf Top sires will rarely have offspring you want to
cull• Net Present Value compared with parent
average selection
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What to Sell
• Lots of heifers = limited marketing potential Save on feed costs
• Beef sires Male sexed semen Gaining traction Helpful with Jerseys
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Individualized Cow Management?
• Should we alter management to accommodate genetic potential? High dairy form = high early lactation BCS loss
risk• Calving BCS should be LOW
Lower yield potential• Breed back more quickly?
• Group cows by genetic potential?
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Will Genomics Impact Inbreeding Rates?
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Close Inbreeding (F=14.7%): Double Grandson of Aerostar
Aerostar
Aerostar
Megastar
Chromosome 24
Megabuck
Digne
VanRaden, 2008
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• Likely to accelerate with genomics Shorter generation interval Technology is “pattern recognition”• Unusual genetic make-up = unrecognized pattern
• Line developmentAerostar
AerostarMegastar
Chromosome 24
Megabuck
Digne
Inbreeding
Identical by descent = inbred
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If we know the DNA code
• Why are genomic tests 100% accurate? Markers are random & may have nothing to do
with performance themselves Copy number variation Not accounting for dominance/gene interactions “Epigenetic” effects• Alter gene expression independently of DNA code• High milk yield during gestation = lower milk yield
daughter?
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The more we learn, the less we know• Intelligent design cannot explain the presence of a
nonfunctional pseudogene … the designer made serious errors, wasting millions of bases of DNA … junk … Evolution, however, can explain them easily … they persist in the genome as evolutionary remnants of the past history (Miller, 1994)
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Marker Effects
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Thank you and are there any questions?