# Presentation: 394566

## Use of Genomics for Selecting Sires 

## Genomic Methods

**Direct**** genomic evaluation**
**Sum of effects for 38,416 genetic markers**
**Not published**
**Combined**** genomic evaluation**
**Include phenotypes of non-genotyped ancestors **
**Selection index includes 3 PTAs per animal**
**Traditional, direct genomic, and subset PTA**
**Transferred**** genomic evaluation**
**Propagate from genotyped animals to non-genotyped descendants by selection index**
**Propagation to ancestors being developed**

## January Evaluation

**HO, JE genomic PTAs ****official in Jan.**
**Genomic from Dec 1, domestic Dec 18**
**Traditional PTAs sent to Interbull**
**MACE used if foreign daughters included**
**Genomic PTA used for most bulls (80%)**
**Traditional used if many new daughters**
**Genomic PTA transferred to descendants (to ancestors in future)**
**Brown Swiss not yet official**

## February Evaluation

**Official only for ****new genotypes**
**Animals genotyped during Dec and Jan**
**Active bulls not updated officially**
**Unofficial PTAs provided in March for proven bulls**
**March evaluation**
**Added 96 bulls accidentally left out of Feb**
**Tested fast reliability approximation**
**Brown Swiss now have >800 genotyped**
**Traded with Switzerland in March 2009**

## April Evaluation (Plans)

**Genomic PTAs ****all official**
**Compute domestic, then genomic**
**Redo last step after MACE arrives:**
**Selection index recalculation**
**Replace ****previous**** with ****current MACE**
**SNP effects and subset PTA same**
**Similar to young bull calving ease**
**Suggested by CDN researchers**

## August Evaluation (Plans)

**Interbull**** converts genomic PTAs**
**Young bulls only**
**Proven bulls next year ****(2010)**** **
**AIPL**** must compute domestic and genomic ****earlier**** to meet deadline**
**Decrease ****yield heritability**** to make PAs and cow PTAs less biased **

## Genomic Tested BullsAvailable Jan 2009

|  | Age (yrs) | Reliability | Net Merit |
| --- | --- | --- | --- |
| Freddie | 4 | 69 | 918 |
| Al | 1 | 67 | 914 |
| Russell | 1 | 65 | 854 |
| Alan | 1 | 68 | 841 |
| O-Man | 10 | 99 | 778 |

## Net Merit of Top 20 Bulls from 2009 data based on selection in 2004 

| Bulls | Selection | Net Merit |
| --- | --- | --- |
| young | Parent average | $395 |
|  | Genomic | $516 |
| proven | Traditional | $381 |
|  | Genomic | $463 |

## Changes in Net Merit means for top 20 bulls (2009 – 2004)

| Bulls | Selection | Change |
| --- | --- | --- |
| young | Parent average | -$278 |
|  | Genomic | -$130 |
| proven | Traditional | -$96 |
|  | Genomic | -$30 |

## Average regressions across all traits  Predict 2009 from 2004 data, expected = 1.00

| Bulls | Selection | Regression |
| --- | --- | --- |
| young | Parent average | 0.85 |
|  | Genomic | 0.92 |
| proven | Traditional | 1.03 |
|  | Genomic | 1.05 |

## Net Merit regressions  Predict 2009 from 2004 data, expected = 1.00

| Bulls | Selection | Regression |
| --- | --- | --- |
| young | Parent average | 0.63 |
|  | Genomic | 0.74 |
| proven | Traditional | 0.91 |
|  | Genomic | 1.10 |

## Genomic vs. traditional – protein PTA

## Genomic vs. traditional – net merit

## Genomic vs. trad. – protein reliability

## Genomic vs. trad. – net merit reliability

**Genomic vs. trad. – ****net merit reliability**

## Expected Change in Net Merit

**SD = 163 * ****√****(REL****G**** – REL****T**** )**
**= ****$91**** for young bulls (.66 - .35)**
**= ****$33**** for proven bulls (.88 - .84)**
**Daughter equivalents for NM$**
**10**** from parent average**
_**25**_** from genomics**
**35**** total for young animals**

## Net Merit by Chromosome Freddie - highest Net Merit bull

## Net Merit by Chromosome O Man – Sire of Freddie

## Net Merit by Chromosome Die-Hard - maternal grandsire

## Net Merit by Chromosome Planet – high Net Merit bull

## Adoption of Genomic TestingUS young bulls purchased by AI companies

| Birth Year | Bulls Sampled | Bulls Tested | Genomic Tested % |
| --- | --- | --- | --- |
| 2008* | 193 | 166 | 86 |
| 2007* | 1455 | 896 | 62 |
| 2006 | 1657 | 717 | 43 |
| 2005 | 1642 | 818 | 50 |
| 2004 | 1638 | 742 | 45 |

*** 2007-2008 counts are incomplete**

## Genetic Progress

**Assume 60% REL for net merit**
**Sires mostly ****1-3**** instead of ****6**** years old**
**Dams of sons mostly heifers with 60% REL instead of cows with phenotype and genotype (66% REL)**
**Progress could increase by ****>50%**
**0.37 vs. 0.23 genetic SD per year**
**Reduce generation interval more than accuracy**

## Worldwide Dairy Genotypingas of January 2009

| Countries | Animals |
| --- | --- |
| United States and Canada | 22,344 |
| France | 8,500 |
| Netherlands, New Zealand1 | 6,000 |
| New Zealand and Ireland | 4,500 |
| Germany | 3,000 |
| Australia | 2,000 |
| Denmark, Finland, Sweden | 2,000 |

**1****Using a customized Illumina 50K chip (different markers)**

## Foreign DNA in North American DataProven bulls, Young bulls, and Females

| Ctry | old | yng | fem | Ctry | old | yng | fem |
| --- | --- | --- | --- | --- | --- | --- | --- |
| NLD | 25 | 134 | 53 | GBR | 7 | 7 | 1 |
| DEU | 22 | 31 | 64 | DNK | 5 | 5 | 0 |
| ITA | 14 | 17 | 5 | LUX | 0 | 0 | 8 |
| AUS | 12 | 30 | 0 | BEL | 3 | 1 | 0 |
| HUN | 6 | 29 | 2 | CHE | 4 | 0 | 0 |
| FRA | 12 | 19 | 2 | NZL | 4 | 0 | 0 |
| CZE | 3 | 15 | 0 | FIN | 1 | 0 | 0 |

## Country Borders

**Most ****phenotypic**** data collected and stored within country**
**Genomic**** data allows simple, accurate prediction across borders**
**Need ****traditional**** EBV or PA for foreign animals, but not available for young bulls, cows, or heifers**
**May need full foreign pedigrees**
**Genomic**** evaluations official on USA scale for many foreign animals (not just CAN)**

## Simulation ResultsWorld Holstein Population

**40,360 older bulls to predict 9,850**** ****younger bulls in Interbull file**
**50,000**** or ****100,000 SNP****; 5,000 QTL **
**Reliability vs. parent average REL**
**Genomic REL = corr****2**** (EBV, true BV) **
**81% vs 30%**** observed using ****50K**
**83% vs 30%**** observed using ****100K**

## International Evaluation

**Traditional**** genetic evaluations**
**MACE instead of merging phenotypes**
**Small benefits expected from data merger**
**Proven bulls only, not cows or young bulls**
**Parentage testing, genetic recessives, pedigrees done by breed associations**
**Genomics****: what role for Interbull?**
**Benefits of sharing genotypes are large**

## Genotype Exchange Options

**Give away for free (not likely)**
**Genotype own bulls, then trade?**
**Trade an equal number or all bulls?**
**Country A has ****5000 ****and B has ****1000**
**Proportional to population size?**
**Trade among organization pairs or create central genomic database?**
**Service fee for young animals to pay for ancestor genotyping?**

## Share Young Bull, Cow Genotypes?

**May be marketed in >1 country**
**Exchange of young animals and females ****more important as their REL increases**** with genomics**
**Helps to synchronize databases**
**Could lead to joint evaluation**

## Problems of Not Sharing

**Genetic progress ****not as fast**** as with full access to genotypes**
**Severe limits on researcher access to genotypes (****secrecy****)**
**Genomics may lead to natural monopoly, similar to railroads**
**Small companies / countries can’t afford to buy sufficient genotypes**

## Genomic MACEInterbull Genomics Task Force

**Residuals correlated across countries**
**Repeated tests**** of the same major gene, or**
**SNP effects estimated from ****common bulls**
**Let c****ij ****= proportion of common bulls **
**Let g****i**** = DE****gen**** / (DE****dau**** + DE****gen****)**
**Corr(e****i****, e****j****) = c****ij ***** Corr(a****i****, a****j****) * ****√****(g****i**** * g****j****)**
**Avoids double counting genomic information from multiple countries i, j**
**New deregression formulas needed**

## Low Density SNP Chip

**Choose ****384**** marker subset**
**SNP that best predict net merit**
**Parentage markers to be shared**
**Use for initial screening of cows**
**40%**** benefit of full set for ****10%**** cost**
**Could get larger benefits using haplotyping (Habier et al., 2008)**

## Marker Effects for Net Merit 

## Genomic vs. Expected Future Inbreeding

| Bull | EFI |  | GFI |
| --- | --- | --- | --- |
| Blackstar | 7.9 |  | 7.9 |
| Elevation | 7.6 |  | 7.4 |
| Chief | 7.1 |  | 6.8 |
| Emory | 7.0 |  | 6.9 |
| RC Matt | 7.0 |  | 6.7 |
| Juror | 7.0 |  | 6.7 |

## Genomic vs. PedigreeInbreeding

| Bull | Pedigree F |  | Genomic F |
| --- | --- | --- | --- |
| O Man | 4.5 |  | 15.8 |
| Ramos | 2.3 |  | 11.5 |
| Shottle | 5.6 |  | 11.9 |
| Planet | 6.7 |  | 18.8 |
| Earnit | 6.2 |  | 12.8 |
| Nifty | 3.1 |  | 11.7 |

**Correlation = .68**

## Pedigree Relationship Matrix1HO9167 O-Style

|  | PGS | PGD | MGS | MGD | Sire | Dam | Bull |
| --- | --- | --- | --- | --- | --- | --- | --- |
| Manfred | 1.053 | .090 | .090 | .105 | .571 | .098 | .334 |
| Jezebel | .090 | 1.037 | .051 | .099 | .563 | .075 | .319 |
| Teamster | .090 | .051 | 1.035 | .120 | .071 | .578 | .324 |
| Dima | .105 | .099 | .120 | 1.042 | .102 | .581 | .342 |
| O-Man | .571 | .563 | .071 | .102 | 1.045 | .086 | .566 |
| Deva | .098 | .075 | .578 | .581 | .086 | 1.060 | .573 |
| O-Style | .334 | .319 | .324 | .342 | .566 | .573 | 1.043 |

## Genomic Relationship Matrix 1HO9167 O-Style

|  | PGS | PGD | MGS | MGD | Sire | Dam | Bull |
| --- | --- | --- | --- | --- | --- | --- | --- |
| Manfred | 1.201 | .058 | .050 | .093 | .609 | .054 | .344 |
| Jezebel | .058 | 1.131 | .008 | .135 | .618 | .079 | .357 |
| Teamster | .050 | .008 | 1.110 | .100 | .014 | .613 | .292 |
| Dima | .093 | .135 | .100 | 1.139 | .131 | .610 | .401 |
| O-Man | .609 | .618 | .014 | .131 | 1.166 | .080 | .626 |
| Deva | .054 | .079 | .613 | .610 | .080 | 1.148 | .613 |
| O-Style | .344 | .357 | .292 | .401 | .626 | .613 | 1.157 |

## Difference (Genomic – Pedigree) 1HO9167 O-Style

|  | PGS | PGD | MGS | MGD | Sire | Dam | Bull |
| --- | --- | --- | --- | --- | --- | --- | --- |
| Manfred | .149 | -.032 | -.040 | -.012 | .038 | -.043 | .010 |
| Jezebel | -.032 | .095 | -.043 | .036 | .055 | .004 | .038 |
| Teamster | -.040 | -.043 | .075 | -.021 | -.057 | .035 | -.032 |
| Dima | -.012 | .036 | -.021 | .097 | .029 | .029 | .059 |
| O-Man | .038 | .055 | -.057 | .029 | .121 | -.006 | .060 |
| Deva | -.043 | .004 | .035 | .029 | -.006 | .087 | .040 |
| O-Style | .010 | .038 | -.032 | .059 | .060 | .040 | .114 |

## Genotyped Animals (n=22,344)In North America as of February 2009

## Experimental Design - UpdateHolstein, Jersey, and Brown Swiss breeds

|  | HOL | JER | BSW |
| --- | --- | --- | --- |
| Predictor: |  |  |  |
| Bulls born <2000 | 4,422 | 1,149 | 225 |
| Cows with data | 947 | 212 |  |
| Total | 5,369 | 1,361 | 225 |
| Predicted: |  |  |  |
| Bulls born >2000 | 2,035 | 388 | 118 |

**Data from ****2004 ****used to predict independent data from ****2009**

## Reliability Gain1 by BreedYield traits and NM$ of young bulls

| Trait | HO | JE | BS |
| --- | --- | --- | --- |
| Net merit | 24 | 8 | 3 |
| Milk | 26 | 6 | 0 |
| Fat | 32 | 11 | 5 |
| Protein | 24 | 2 | 1 |
| Fat % | 50 | 36 | 10 |
| Protein % | 38 | 29 | 5 |

**1****Gain above parent average reliability ~35%**

## Reliability Gain by BreedHealth and type traits of young bulls

| Trait | HO | JE | BS |
| --- | --- | --- | --- |
| Productive life | 32 | 7 | 2 |
| Somatic cell score | 23 | 3 | 16 |
| Dtr pregnancy rate | 28 | 7 | - |
| Final score | 20 | 2 | - |
| Udder depth | 37 | 20 | 3 |
| Foot angle | 25 | 11 | - |
| Trait average  | 29 | 13 | N/A |

## Value of Genotyping More AnimalsActual and predicted gains for 27 traits and for Net Merit

| Bulls |  | Reliability Gain |  |
| --- | --- | --- | --- |
| Predictor | Predicted | NM$ | 27 trait avg |
| 2130 | 261 | 13 | 17 |
| 3576 | 1759 | 23 | 23 |
| 4422 | 2035 | 24 | 29 |
| 6184 | 7330 | 31 | 30 |

**Cows:**
**947**
**1916**

## Conclusions - 1

**High accuracy requires very many genotypes and phenotypes**
**100X**** more markers allows MAS across rather than within families**
**5X**** more bulls allows estimation of much smaller QTL effects (HO)**
**Most traits are very quantitative (few major genes)**

## Conclusions - 2

**Reliability ****increases**** by tracing actual genes inherited instead of expected average from parents**
**Genomic reliability > traditional  **
**30-40%**** with traditional parent average**
**60-70%**** using 8,100 genotyped Holsteins **
**81-83%**** from 40,000 simulated bulls**
**Gains smaller for USA JER and BSW breeds**
**Trading, sharing, profit is needed**

## Acknowledgments

**Genotyping and DNA extraction:**
**USDA Bovine Functional Genomics Lab, U. Missouri, U. Alberta, GeneSeek, Genetics & IVF Institute, Genetic Visions, and Illumina**
**Computing:**** **
**AIPL staff (Mel Tooker, Leigh Walton, Jay Megonigal)**
**Funding:**** **
**National Research Initiative grants**
**2006-35205-16888, 2006-35205-16701**
**Agriculture Research Service**
**Holstein and Jersey breed associations**
**Contributors to Cooperative Dairy DNA Repository (CDDR)**