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US Genetic Improvement Program: Methods and Results

US Genetic Improvement Program: Methods and Results. AIPL Mission. Conduct research to discover, test, and implement improved genetic evaluation techniques for economically important traits of dairy cattle and goats Genetically improve efficiency of dairy animals for yield and fitness.

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US Genetic Improvement Program: Methods and Results

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  1. US Genetic Improvement Program: Methods and Results

  2. AIPL Mission • Conduct research to discover, test, and implement improved genetic evaluation techniques for economically important traits of dairy cattle and goats • Genetically improve efficiency of dairy animals for yield and fitness

  3. AIPL Research Objectives • Maintain a national database with animal identification, production, fitness, reproduction, and health traits to support research on dairy genetics and management • Provide data to others researchers submitting proposals compatible with industry needs

  4. AIPL Research Objectives (cont.) • Increase accuracy of genetic evaluations for traits through improved methodology and through inclusion and appropriate weighting of deviant data • Develop bioinformatic tools to automate data processing in support of quantitative trait locusdetection, marker testing, and mapping methods

  5. AIPL Research Objectives (cont.) • Improve genetic rankings for overall economic merit by evaluating appropriate traits and by determining economic values of those traits in the index • Improved profit functions are derived from reviewing incomes and expenses associated with each trait available for selection

  6. AIPL Research Objectives (cont.) • Characterize dairy industry practices in milk recording, breed registry, and artificial-insemination to document status and changes in data collection and use and in observed and genetic trends in the population

  7. U.S. Dairy Statistics (2009) • 9.2 million cows • 48% milk recorded through Dairy Herd Information (DHI) • 22,246 DHI herds • 200 cows/herd • 22,200 lb (10,070 kg)/cow • ~93% Holsteins, ~5% Jerseys • ~75% bred AI

  8. U.S. Dairy Population and Yield

  9. U.S. Progeny-test Bulls born 2007 • Major and marketing-only AI organizations

  10. Dairy Genetic Evaluation Program PDCA NAAB DHI AIPL CDCB Universities AIPL Animal Improvement Programs Lab., USDA CDCB Council on Dairy Cattle Breeding DHI Dairy Herd Information (milk recording organizations) NAAB National Association of Animal Breeders (AI) PDCA Purebred Dairy Cattle Association (breed registries)

  11. Genetic Evaluation Advances

  12. Daughter-Dam Difference • 1926-1961 • Introduced by: • R. R. Graves • 1926 USDA Bulletin #1372 • Advantages: • Allowed progeny testing of bulls • Adjusted for herd effect via dam • (Over) adjusted for merit of mates

  13. Herdmate Comparison • 1962-1973 • Introduced by: • Robert Miller • Rankings in Hoards Dairyman (1964) • Advantages: • Sire effect random (informative prior) • High rank requires more daughters, n / (n + k) • Did not require records on dam • More data, less bias, 1st cow index (1964)

  14. Modified Contemporary Comparison • 1974-1989 • Introduced by: • Duane Norman, Ben McDaniel, Rex Powell, and Frank Dickinson • Advantages: • Ancestor and daughter merit combined • Sire-MGS pedigree introduced 1 year before Henderson’s relationship inverse • Genetic group effects inherited (similar to Westell et al., 1988) • Adjusted for merit of competing sires • Cow indexes included more relatives

  15. 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)

  16. Models Borrowed from Others • Calving ease threshold model • Berger and Freeman (Iowa State, 1978) • Service sire conception rate • Clay (NC State, 1986), programs by Misztal (Georgia) • 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)

  17. Genomic Selection • Use many markers to track inheritance of chromosomal segments • Estimate the impact of each chromosomal segment on each trait • Combine estimates with traditional evaluations to produce genomic evaluation (GPTA) • Select animals shortly after birth using GPTA • Replaces searching for individual genes of large effect (Major Genes)

  18. Genomic Evaluation System • Provides timely evaluations of young bulls for purchasing decisions • Increases accuracy of evaluations of bull dams • Assists in selection of service sires, particularly for low-reliability traits

  19. Traits Evaluated by AIPL 1Sire calving ease evaluated by Iowa State U. 1978-1999 2Estimated relative conception rate evaluated by DRMS@Raleigh 1986-2005

  20. Evaluation Methods Heritability 25 – 40% 7 – 54% 8.5% 12% 4% • Animal model (linear) • Yield (milk, fat, protein) • Type (Ayrshire, Brown Swiss, Guernsey, Jersey) • Productive life • SCS • Daughter pregnancy rate • Sire – maternal grandsire model (threshold) • Service sire calving ease • Daughter calving ease • Service sire stillbirth • Daughter stillbirth 8.6% 3.6% 3.0% 6.5%

  21. Type Traits • Feet and Leg Score • Fore Udder Attachment • Rear Udder Height • Rear Udder Width • Udder Cleft • Udder Depth • Front Teat Placement • Rear Teat Placement • Teat Length • Stature • Strength • Body Depth • Dairy Form • Rump Angel • Thurl Width • Rear Legs (side) • Rear Legs (rear) • Foot Angle

  22. Genetic Trend – Milk 1000 500 Phenotypic base = 11,638 kg 0 -500 -1000 Breeding value (kg) -1500 sires cows -2000 -2500 -3000 -3500 1960 1970 1980 1990 2000 Holstein birth year

  23. Genetic Trend –Fat Phenotypic base = 424 kg cows sires

  24. sires Genetic Trend –Protein Phenotypic base = 350 kg cows

  25. sires Genetic Trend –Productive Life (mo) Phenotypic base = 24.6 months cows

  26. sires Genetic Trend – Somatic cell score Phenotypic base = 3.08 (log base 2) cows

  27. sires Genetic Trend –Daughter preg. rate cows Phenotypic base = 21.53%

  28. service sire daughter Genetic Trend – calving ease SCE Phenotypic base = 8.47% DBH DCE Phenotypic base = 7.99% DBH

  29. service sire daughter Genetic Trend – stillbirth Phenotypic base = 8% SBH

  30. Genetic-economic Indices

  31. Index Changes

  32. Summary • Evaluation procedures have improved • Fitness traits have been added • Effective selection has produced substantial annual genetic improvement • Indexes enable selection for overall economic merit • Increased weight on fertility necessary to prevent continued decline • AIPL serves the dairy industry with reliable evaluations and research to improve procedures

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