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AIPL Update

AIPL Update. Genotyped animals (October 2008). Experimental Design Holstein, Jersey, and Brown Swiss breeds. Data from 2003 used to predict independent data from 2008. Reliability Gain 1 by Breed Yield traits and NM$. 1 Gain above parent average reliability ~35%.

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AIPL Update

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  1. AIPL Update

  2. Genotyped animals (October 2008)

  3. Experimental DesignHolstein, Jersey, and Brown Swiss breeds Data from 2003 used to predict independent data from 2008

  4. Reliability Gain1 by BreedYield traits and NM$ 1Gain above parent average reliability ~35%

  5. Reliability Gain by BreedHealth and type traits

  6. New Genetic Terms • Actual vs. expected genetic similarity • Genomic relationships and inbreeding • Genomic future inbreeding (GFI) vs. EFI • Daughter merit vs. son merit • Haplotyping and imputation • Which allele is from sire vs. dam? • Which alleles are linked together? • Can missing genotypes be predicted?

  7. Genomic vs. PedigreeInbreeding Correlation = .68

  8. Genomic vs. Expected Future Inbreeding

  9. Net Merit by ChromosomePlanet - high Net Merit bull

  10. Schedule • Calculate SNP effects with each of 3 annual traditional evaluations • Calculate genomic evaluations once or more between traditional evaluations, monthly? • Recalculate SNP effects if significant number of predictor animals added • Use existing SNP effects if only young animals added

  11. Official release in 2009 • Information from genomic evaluations propagated to evaluations of descendents without genotypes • NAAB to manage bull-owner notification and sharing among AI organizations • Public release of genomic evaluations • Cows soon after calculated • Bulls when enrolled with NAAB or Canadian AI organization • Shared by agreement with owner

  12. Low cost genotyping research • Develop a genetic test that is cheap enough to enable use on most animals • Provide parentage verification/discovery • Provide a genetic estimate useful for first stage screening • 384 SNP proposed for first test • High throughput procedures being developed

  13. Reliability of evaluations • Reliability from inverse of a matrix with order the number of genotyped animals • Approximation necessary as number of genotyped animals increases • Daughter equivalents discounted by 0.6 to represent better the reliability of 2003 data in predicting bulls first evaluated in 2008

  14. Plans to increase accuracy • Genotype more predictor bulls • Reach 1,500 Brown Swiss, possibly through foreign collaboration • Increase genotyped Jerseys from both domestic animals and possible foreign collaboration • Investigate across-breed analysis so Holstein data can improve accuracy for Jerseys and Brown Swiss

  15. Haplotyping • Haplotyping may increase accuracy • Even a SNP very close to a QTL may have a different allele frequency • Haplotype allele may have higher correlation with the QTL • May assist in imputation of genotypes of missing SNP and perhaps whole animals

  16. International implications • All major dairy countries are investigating genomic selection • Interbull meeting in January on integration of genomic evaluations • Studs must balance competitive benefit from treating genotypes as proprietary with benefits from sharing

  17. Interbull • Genomics contribution to accuracy should be reported • Avoid double counting when submitted by multiple countries • Could be processed similar to parent contribution • Change in 10-herd requirement needed to allow marketing bulls with only genomic information in countries without genomic evaluations

  18. Query example

  19. Dystocia Complex • Markers on BTA 18 had the largest effects for several traits: • Dystocia: Sire and daughter calving ease • Conformation: rump width, stature, strength, and body depth • Efficiency: longevity and net merit • Large calves contribute to shorter PL and decreased NM$

  20. Markers on BTA18 with large effects

  21. SIGLEC proteins • Human Siglec-9 highly expressed in the placenta (Foussias, 2000). • Human Siglec-6 may be involved in initiation of parturition (Brinkman-Van der Linden et al., 2007). • Siglec-6 binds and sequesters leptin (Brinkman-Van der Linden et al., 2007).

  22. Proposed mode of action • Leptin-deficient mice delay parturition (Mounzih et al., 1998). • Homozygotes may express high levels of Siglec-6, resulting in leptin deficiency and delayed parturition. • ss86324977 may result in increased calf size associated with longer gestation lengths.

  23. Interbull fertility traits • Heifer conception as a rate (heifer conception rate)‏. • Ability to recycle after calving (days to first breeding)‏. • Cow conception as a rate (cow conception rate) and interval (first breeding to conception)‏. • Calving to conception (days open)‏.

  24. Status of fertility traits • Traits 1 and 3 (heifer and cow conception rates) submitted to Sept. 2008 test run. • Work on Trait 2 (days to first breeding) is underway. • Trait 4 (ability to conceive as an interval) is now required. • We already report Trait 5 (DPR).

  25. Heifer and cow conception rate • Heifer conception rate (HCR) is the percentage of inseminated heifers that become pregnant at each service. • Cow conception rate (CCR) is defined as the percentage of inseminated cows that become pregnant at each service.

  26. Conception rate variance components

  27. Correlations among fertility PTA Correlations among PTA for bulls with at least100 CR daughters.

  28. Distribution of Heifer CR PTA

  29. Distribution of Cow CR PTA

  30. Top bulls – Heifer CR

  31. Bottom bulls – Heifer CR

  32. Top bulls – Cow CR

  33. Bottom bulls – Cow CR

  34. Acknowledgments • Genomics work supported by NRI Grants 2006-35205-16888 and 2006-35205-16701 and by NAAB. • Much of the work on heifer and cow CR was carried out by Dr. Melvin Kuhn while he was at AIPL.

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