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2007 Melvin Tooker Animal Improvement Programs Laboratory USDA Agricultural Research Service, Beltsville, MD, USA

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Presentation on theme: "2007 Melvin Tooker Animal Improvement Programs Laboratory USDA Agricultural Research Service, Beltsville, MD, USA"— Presentation transcript:

1 2007 Melvin Tooker Animal Improvement Programs Laboratory USDA Agricultural Research Service, Beltsville, MD, USA Melvin.Tooker@ars.usda.gov Melvin.Tooker@ars.usda.gov 2009 An Introduction to Sire Proofs and Modeling

2 India Emerging Markets Conference, May 2009 (2) Melvin Tooker 2009 Genetic Evaluation Advances and increases in genetic progress YearAdvance% Gain 1926Daughter-dam comparison100 1962Herdmate comparison50 1973Records in progress10 1974Modified cont. comparison5 1977Protein evaluated4 1989Animal model4 1994Net merit, PL, and SCS50 2008Genomic selection>50

3 India Emerging Markets Conference, May 2009 (3) Melvin Tooker 2009 Traits Evaluated by AIPL TraitYearTraitYear Milk, fat yield1926Calving ease 1 2000 Protein yield1978Dtr. preg. rate2003 Conformation1978Stillbirth2006 Productive life1994Bull CR 2 2006 SCS (mastitis)1994Cow,heifer CR2009 1 Sire calving ease evaluated by Iowa State U. 1978-1999 2 Estimated relative conception rate evaluated by DRMS@Raleigh 1986-2005

4 India Emerging Markets Conference, May 2009 (4) Melvin Tooker 2009 Animal Model 1989-present  Introduced by: George Wiggans and Paul VanRaden  Advantages: Use of all relatives Adjusts for merit of mates Uniform procedures for males and females Best prediction given the model (BLUP) Revised to include crossbreds (2007)

5 India Emerging Markets Conference, May 2009 (5) Melvin Tooker 2009 Models Borrowed from Others  Calving ease threshold model Berger and Freeman (Iowa State, 1978)  Somatic cell score Shook (U. WI, 1980), Boettcher et al (U. MN, 1992)  Multi-trait productive life Weigel et al (Holstein USA, 1994)  Multi-trait linear type Programs by Gengler (Belgium)

6 India Emerging Markets Conference, May 2009 (6) Melvin Tooker 2009 Animal Model Terms  Predicted Transmitting Ability (PTA) is an estimate of genetic merit and is the part of an animal’s genetic makeup that is transmitted to offspring.

7 India Emerging Markets Conference, May 2009 (7) Melvin Tooker 2009 Animal Model Terms  The amount of information about the genetic merit of dairy animals is measured by reliability. This measure of the accuracy of a genetic evaluation varies from animal to animal and ranges from 0 percent for unevaluated animals to 99 percent.

8 India Emerging Markets Conference, May 2009 (8) Melvin Tooker 2009 Animal Model Terms  PTAs are computed relative to a zero point or genetic base. For evaluating dairy cattle, a new genetic base is calculated every five years to account for genetic change.  The current genetic base used for the underlying, unpublished all-breed PTAs sets the average PTA for each trait to zero for all cows born in 2000, regardless of breed.

9 India Emerging Markets Conference, May 2009 (9) Melvin Tooker 2009 All Breed Animal Model  Evaluate crossbred animals without biasing purebred evaluations.  Accurately estimate breed differences.  Compute national evaluations and examine changes.  Display results without confusion.

10 India Emerging Markets Conference, May 2009 (10) Melvin Tooker 2009 All-Breed Analyses  Crossbred animals Will have PTAs, only 3% did before if in breed association grading-up programs. Reliable PTAs from both parents.  Purebred animals Information from crossbred relatives. More herdmates (other breeds, crossbreds)  Routinely used in other populations New Zealand (1994), Netherlands (1997) USA goats (1989), calving ease (2005)

11 India Emerging Markets Conference, May 2009 (11) Melvin Tooker 2009 Methods  All-breed animal model Purebreds and crossbreds together. Relationship matrix among all animals. Unknown parents grouped by breed. Data set to breed base after animal model completes. – Jersey would have poor PTA milk when compared to Holstein – Jersey would have better calving ability than other breeds

12 India Emerging Markets Conference, May 2009 (12) Melvin Tooker 2009 Unknown Parent Groups  Look up PTAs of known parents  Estimate averages for unknowns  Group unknown parents by Birth year Breed Path (dams of cows, sires of cows, parents of bulls) Origin (domestic vs other countries)

13 India Emerging Markets Conference, May 2009 (13) Melvin Tooker 2009 Data Extraction  Genetic Evaluations Applying new data stopped All required data extracted – Pedigree – Herd data – All trait specific data extracted Genetic Evaluations started – Minimal use of database – Performance improvement – Stabilizes data connections Applying new data resumed

14 India Emerging Markets Conference, May 2009 (14) Melvin Tooker 2009 Animal Model Repeatability animal model: y ijkl = hys i + lac j + a k + pe k + β(do jk ) + e ijkl y ijkl = persistency of milk, fat, protein, or SCS hys i = fixed effect of herd-year-season of calving I lac j = fixed effect of lactation j a k = random additive genetic effect of animal k pe k = random permanent environmental effect of animal k do jk = days open for lactation j of animal k e ijkl = random residual error

15 India Emerging Markets Conference, May 2009 (15) Melvin Tooker 2009 Using DHI Data  Not all cows have the same number of test days in a lactation.  Best Prediction is one way of turning different test days into 305- day lactation totals.  Lactations longer than 305 days.

16 India Emerging Markets Conference, May 2009 (16) Melvin Tooker 2009 Using DHI data (cont.)  All records are standardized to a twice- a-day milking frequency basis, and are adjusted to 36 months.  (2009) All lactation information is used up to 999 days.  The animal model includes up to five lactation records on cows.  Records from 1970 to present.

17 India Emerging Markets Conference, May 2009 (17) Melvin Tooker 2009 Using DHI data (cont.)  Information for daughter pregnancy rate and somatic cell score also comes from the first five lactation records.  Daughter pregnancy rate is measured from calving intervals.  Productive life is unique in that it is expressed only once at the end of the life of a cow.

18 India Emerging Markets Conference, May 2009 (18) Melvin Tooker 2009 Using DHI data (cont.)  The greatest challenge to any genetic evaluation system is to separate environmental effects from genetic ones.  Use contemporary groups. Herd Calving groups Registered status

19 India Emerging Markets Conference, May 2009 (19) Melvin Tooker 2009 Genetic relationships  Pedigree data is vital.  Pedigree information helps separate favorable or unfavorable permanent environmental effects. A cow with favorable parentage may not produce very well because of permanent effects of mastitis as a young cow.

20 India Emerging Markets Conference, May 2009 (20) Melvin Tooker 2009 Genetic relationships (cont.)  The most important genetic relationship in dairy cattle breeding is between a daughter of an AI bull and her many half-sisters distributed across many different herd environments.  Used to evaluate the bull himself and contributes to the accuracy of the PTA on each of the half-sisters as well.

21 India Emerging Markets Conference, May 2009 (21) Melvin Tooker 2009 Genetic relationships (cont.)  It would be difficult to find a U.S. Holstein cow that is not related to Elevation or Chief, or a U.S. Jersey cow that didn’t have Duncan or Generator in her pedigree somewhere.  This means Holstein or Jersey cows are related in some way to almost all other cows in their breed.

22 India Emerging Markets Conference, May 2009 (22) Melvin Tooker 2009 Special Procedures  Cow must have a first lactation for her to influence her relatives.  Cows may change herds or stop testing.  Bulls need to have daughters in 10 different herds to be official.

23 India Emerging Markets Conference, May 2009 (23) Melvin Tooker 2009 Sire Proofs  Animal Model programs are run by Leigh Walton.  Domestic proofs are produced.  Bull data sent to Interbull.  Returned 2 weeks later with Multiple Across Country Evaluations (MACE).

24 India Emerging Markets Conference, May 2009 (24) Melvin Tooker 2009 Published Proofs  Interbull data combined with US domestic data.  Highest reliability determines which evaluation is official.

25 India Emerging Markets Conference, May 2009 (25) Melvin Tooker 2009 Data Distribution  All data distributed electronically  Web queries Public and restricted  Computer optimized files Bull evaluations – format 38 Cow evaluation – format 105 Public and restricted Password-protected zip files

26 India Emerging Markets Conference, May 2009 (26) Melvin Tooker 2009 Data Distribution (cont.)  Formatted reports Complete Sire List Elite Cow List Active/Foreign/Genomic Lists  XML files Schema Style sheet

27 India Emerging Markets Conference, May 2009 (27) Melvin Tooker 2009 Trends  AIPL Website http://aipl.arsusda.gov/

28 India Emerging Markets Conference, May 2009 (28) Melvin Tooker 2009 Milk (kg) Genetic trend on all-breed base

29 India Emerging Markets Conference, May 2009 (29) Melvin Tooker 2009 Fat (kg) Genetic trend on all-breed base

30 India Emerging Markets Conference, May 2009 (30) Melvin Tooker 2009 Protein (kg) Genetic trend on all-breed base

31 India Emerging Markets Conference, May 2009 (31) Melvin Tooker 2009 Somatic Cell Score Genetic trend on all-breed base

32 India Emerging Markets Conference, May 2009 (32) Melvin Tooker 2009 Productive Life Genetic trend on all-breed base

33 India Emerging Markets Conference, May 2009 (33) Melvin Tooker 2009 Daughter Pregnancy Rate Genetic trend on all-breed base

34 India Emerging Markets Conference, May 2009 (34) Melvin Tooker 2009 Questions or Comments

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