Genomic Evaluations

G. R. Wiggans

Animal Improvement Programs LaboratoryAgricultural Research Service, USDA Beltsville, MD

G.R. WiggansSpanish Visitors June 2010 (1)

Genomic Evaluations


Structure of genomic evaluations All genotypes shared with Canada

Holstein, Jersey, Brown Swiss included

Participants

3 Breed Associations

7 major studs and 5 small ones

4 genotyping laboratories

Monthly evaluations


Bull genomic evaluations

Designated studs have exclusive right to receive genomic evaluations of bulls until May 2013


Genotyped Holstein by run

Run Date

Old* Young**

TotalMale Female Male Female

0904 7600 2711 9690 1943 21944

0906 7883 3049 11459 2974 25365

0908 8512 3728 12137 3670 28047

0910 8568 3965 13288 4797 30618

1001 8974 4348 14061 6031 33414

1002 9378 5086 15328 7620 37412

1004 9770 7415 16007 8630 41822

1005 9958 7940 16594 9772 44264

1006 9958 8122 17507 10713 46300

* Animals with traditional evaluation** Animals with no traditional evaluation


How the system works

Studs and breeds nominate animals through web site

Hair, blood, semen, or extracted DNA sent to Labs

Genotypes sent to AIPL monthly

Evaluation updates provided to studs and breeds monthly

All evaluations updated at tri-annual traditional runs


Conflict checking

Parent-progeny conflicts detected

Sex and breed checked

Conflicts reported to lab and requester for resolution


Recent changes

Genotypes for some dams imputed from progeny

Traditional evaluations of genotyped cows adjusted to improve accuracy of genomic evaluations


Imputation

Determine an animal’s genotype from genotypes of its parents and progeny

Genotype separated into sire and dam contributions. Identifies the allele on each member of a chromosome pair


O-Style Haplotypeschromosome 15


Imputation (cont.)

Inheritance of haplotypes tracked

Accuracy of imputation improves with number of progeny

Crossovers during meiosis contribute to uncertainty


Cow Adjustment

Evaluations of elite cows biased upward

Cutoff studies showed little benefit from including cows as predictors

Reducing heritability would reduce the problem but industry is reluctant to do so

Adjustment of cow evaluations implemented


Effect of Adjustment on Holstein

Bias Regression Gain REL

No Yes Diff No Yes Diff No Yes Diff

Milk (lb) -75.3

-27.9

47.4

.93 .90 -.03

29.5 32.5

3.0

Fat (lb) -5.7 -2.9 2.8 .98 .97 -.01

34.0 37.1

3.1

Protein (lb)

-0.2 0.8 1.0 .90 .97 .07 25.0 27.1

2.1

Fat (%) 0.0 0.0 0.0 .97 .99 .02 49.8 52.4

2.6

Protein (%)

0.0 0.0 0.0 .87 .88 .01 38.8 41.5

2.7


Increased reliability of genomic predictions

Genomic evaluations of the top cows, top young bulls, and top heifers decreased

Among bulls, foreign bulls with a high proportion of genotyped daughters had largest changes

Cow Adjustment Summary


Reliability for young HO Bulls

0

500

1000

1500

2000

2500

3000

3500

4000

52 5354 55 5657 58 5960 61626364 6566 67 6869 70 7172 73 7475 76 7778 79

Milk REL

Nu

mb

er

of

Bu

lls

N = 15,226


Chip diversity

Low cost chip with 3072 (3K) SNP expected this summer

High density chip (860K) in development

Version 2 of BovineSNP50 announced with changes in SNP list


Accommodating chip diversity Impute to higher density

Calculate effects for all high density SNP

Mechanism for accounting for loss in accuracy due to imputation error needed Percent missing genotypes

Only observed genotypes stored in database

Evaluations labeled as to source of genotype


Illumina 3K chip

SNP chosen 3072, evenly spaced Some Y specific SNP 90 SNP for breed determination

Expect to impute genotypes for 43,382 SNP with high accuracy

Expect breeds to use 3K chip to replace microsatellites for parentage verification

Breeds allowed to genotype bulls for parentage only


Proposed stud use of 3K chip Accuracy adequate for first stage

screening

Higher density genotyping reserved for bulls acquired. Confirm ID Second stage selection

Maximize accuracy of evaluation used for marketing

Genotype more candidates


Current research

Prepare for Interbull validation of genomic evaluations

Improve accuracy of imputation Refine cow adjustment for use with 3K

chip Evaluate how to restore comparability

between evaluations of genotyped and non-genotyped cows

Investigate ways to increase accuracy by increasing predictor population

Genomic Evaluations

Documents

Transcript of Genomic Evaluations