measuring genomic pre-selection in theory and in...
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![Page 1: Measuring genomic pre-selection in theory and in practiceen.france-genetique-elevage.org/IMG/pdf/s3-2_measuring_genomic_p… · Interbull annual meeting, Nantes, France, August 2013](https://reader033.vdocuments.us/reader033/viewer/2022050205/5f58550a9681257e6953fed5/html5/thumbnails/1.jpg)
2007
Paul VanRaden and Jan Wright Animal Improvement Programs Lab, Beltsville, MD [email protected]
2013
Measuring genomic pre-selection in theory and in practice
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Interbull annual meeting, Nantes, France, August 2013 (2) Paul VanRaden 2013
Traditional mixed models do not account for genomic selection • Phenotypes only for animals with
highest Mendelian sampling • GBV differ from EBV for progeny,
mates, parents, or herdmates
Multi-step methods may be biased Single-step methods reduce bias
In Theory
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Interbull annual meeting, Nantes, France, August 2013 (3) Paul VanRaden 2013
1-Step Relationship Inverse Aguilar et al. (2010)
H-1 = A11 A12 A21 A22 + G-1 - A22
-1
1 = non-genotyped animals (60 million) 2 = genotyped animals (400,000)
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Interbull annual meeting, Nantes, France, August 2013 (4) Paul VanRaden 2013
Animal model • EBV = w1 PA + w2 YD + w3 PC • (parent average, yield deviation,
progeny contribution)
1-step genomic info (GI) model • GBV = w1PAg + w2YDg + w3PCg + w4GI • GI = ∑off-diagonalj of G-1–A22
-1(GBVj) divided by diagonali of G-1–A22
-1 • Numerator of w4 in denominator of w
Traditional and 1-Step Models
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Interbull annual meeting, Nantes, France, August 2013 (5) Paul VanRaden 2013
Computed for 8,300 Brown Swiss Diagonals of G and A22 are similar
• G: mean FG = 3.98% and SD = 4.15% • A22: mean FA = 3.95% and SD = 2.97%
Diagonals of G-1 larger than A22-1
• Mean = 5.83 for G, 2.18 for A22 • G-1, A22
-1 and difference all highly correlated
Diagonals of G-1–A22-1
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Interbull annual meeting, Nantes, France, August 2013 (6) Paul VanRaden 2013
G A G-1 A-1 G-1 - A-1 G 1.0 .70 .05 .03 .06 A 1.0 .02 -.02 .04 G-1 1.0 .98 .99 A-1 1.0 .94 G-1 - A-1 1.0
Correlations of Diagonals Genotyped Brown Swiss
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Interbull annual meeting, Nantes, France, August 2013 (7) Paul VanRaden 2013
Phenotyped only animals with good Mendelian sampling genotypes
Discrete or overlapping generations • Bias if discrete (Patry, Ducrocq 2011) • OK with overlap (Nielsen et al, 2012) • Large bias for dams (Liu et al, 2009)
Actual studies of pre-selection and genomic assortative mating needed
Simulations of Pre-Selection Bias
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Interbull annual meeting, Nantes, France, August 2013 (8) Paul VanRaden 2013
Test actual selection and mating Quantify genomic pre-selection in:
• Mates of proven bulls (group 1) • Mates of young bulls (group 2) • Dams of young selected sons
Measure future bias because pre-selection has already occurred
In Practice
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Interbull annual meeting, Nantes, France, August 2013 (9) Paul VanRaden 2013
Percentage of Genotyped Mates Group 2 bulls ranked by NM$
0
10
20
30
40
50
60
70
80
90
100
700 725 750 775 800 825 850 875 900 925
Maurice
Elvis ISY Altatrust
Fernand
Net Merit (Aug 2013)
Perc
enta
ge o
f mat
es g
enot
yped
Supersire
Numero Uno
S S I Robust Topaz
Garrold
Mogul
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Interbull annual meeting, Nantes, France, August 2013 (10) Paul VanRaden 2013
Group 1 (proven bulls) • Daughters with records • Top 50, no dtrs in April 2010 • Were mates pre-selected?
Group 2 (young bulls) • Top 50, born 2009 and 2010 • Study calves born in USA • Will pre-selected mates cause bias?
Mates of Group 1 and 2 Bulls
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Interbull annual meeting, Nantes, France, August 2013 (11) Paul VanRaden 2013
Trait Mean SD Min Max NM$ 2 4 -5 13 Protein 0 0 -1 1 Prod Life .0 .0 .0 .1 Dtr Preg Rate .0 .0 .0 .1 SCS .00 .00 -.01 .01 Final Score .00 .01 -.04 .02 Udder Depth .00 .01 -.02 .02
Group 1 Realized Mate Bias
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Interbull annual meeting, Nantes, France, August 2013 (12) Paul VanRaden 2013
Trait Mean SD Min Max NM$ 8 9 0 33 Protein 0 0 0 1 Prod Life .1 .1 .0 .5 Dtr Preg Rate .1 .1 .0 .3 SCS -.01 .01 -.03 .00 Final Score .02 .03 -.01 .10 Udder Depth .03 .04 -.01 .13
Group 2 Future Bias from Mates
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Interbull annual meeting, Nantes, France, August 2013 (13) Paul VanRaden 2013
Dams with ≥ 1 sampled son born 2008 to 2012
Son selection differential = ∑(GPTA – PA) / # of sons sampled
Dam’s bias = 2 * sons’ selection differential * (DE from sampled sons) / (total conventional DE) • DE = daughter equivalents or EDC
Future Bias – Dams of Young Bulls
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Interbull annual meeting, Nantes, France, August 2013 (14) Paul VanRaden 2013
29 sons genotyped, 6 selected, each will provide 5.4 DE
Son selection differential for milk = ∑(GPTA – PA) / 6 = 583 pounds
30 daughters, each provide 1.5 DE 8.3 DE from PA, 7.8 from records Dam’s future bias = 2 * 583 * 6 * 5.4
/ [8.3 + 7.8 + 6 * 5.4 + 30 * 1.5] = 808
Example Dam HOUSA000065597532
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Interbull annual meeting, Nantes, France, August 2013 (15) Paul VanRaden 2013
Trait Mean SD Min Max NM$ 29 33 -124 156 Protein 1 3 -10 14 PL .3 .5 -1.7 2.0 DPR .1 .2 -.9 .9 SCS -.01 .04 -.22 .14
Expected Future Bias – Bull Dams
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Interbull annual meeting, Nantes, France, August 2013 (16) Paul VanRaden 2013
Also from preferential treatment • High-priced early daughters • Lack of random sampling
Deregression removes some bias • Example: dam gets credit only for
own records and non-genotyped progeny, not genotyped sons
• Use matrix instead of simple one at a time deregression
Potential Biases
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Interbull annual meeting, Nantes, France, August 2013 (17) Paul VanRaden 2013
Conclusions
Evaluations should adjust for GBV instead of EBV of: • Progeny, mates, contemporaries, and
parents Biases from pre-selection:
• Very small for recently proven bulls • Moderate from mates top young bulls • Will be large for dams of several highly
selected sons, but deregression can remove some of the bias
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Interbull annual meeting, Nantes, France, August 2013 (18) Paul VanRaden 2013
Phenotypes, genotypes, and pedigrees were provided by the Council on Dairy Cattle Breeding
Acknowledgments