2007 Paul VanRaden, George Wiggans, Animal Improvement Programs Laboratory Curt Van Tassell, Tad Sonstegard, Bovine Functional Genomics Laboratory USDA.

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Presentation transcript:

2007 Paul VanRaden, George Wiggans, Animal Improvement Programs Laboratory Curt Van Tassell, Tad Sonstegard, Bovine Functional Genomics Laboratory USDA Agricultural Research Service, Beltsville, MD, USA Flavio Shenkel CGIL, University of Guelph, Guelph, ON, Canada 2009 Benefits from Cooperation in Genomics

Interbull Genomics Workshop, Jan (2)Paul VanRaden 2009 Topics  Genomic cooperation Simulation of very large population Proposals for genotype sharing Country border issues and North American experience Genomic MACE equations  USA update Actual HOL, JER, and BSW results Database and implementation

Interbull Genomics Workshop, Jan (3)Paul VanRaden 2009 Cooperative International Projects  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?

Interbull Genomics Workshop, Jan (4)Paul VanRaden 2009 Sequencing of Genomes SpeciesYear Human - $3 billion2000 Cow - $53 million funded by: % Nat’l Human Genome Res Inst 50% USA, CAN, AUS, NZL Chicken2004 Pig - < $20 million2009

Interbull Genomics Workshop, Jan (5)Paul VanRaden 2009 Human DNA Data Sharing "The highest priority of the International Human Genome Sequencing Consortium is ensuring that sequencing data from the human genome is available to the world's scientists rapidly, freely and without restriction." National Human Genome Research Institute, 2008 "The principle of rapid pre-publication release should apply to other types of data from other large-scale production centers." Wellcome Trust, 2003

Interbull Genomics Workshop, Jan (6)Paul VanRaden 2009 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

Interbull Genomics Workshop, Jan (7)Paul VanRaden 2009 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?

Interbull Genomics Workshop, Jan (8)Paul VanRaden 2009 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

Interbull Genomics Workshop, Jan (9)Paul VanRaden 2009 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

Interbull Genomics Workshop, Jan (10)Paul VanRaden 2009 North American Cooperation  174 markers, 1068 USA and CAN bulls Illinois, Israel, and USDA researchers  367 markers, 1415 USA and CAN bulls USDA, Illinois, and Israel  38,416 markers, 19,464 animals USDA, Missouri, Canada, and Illumina Oct Dec 2008

Interbull Genomics Workshop, Jan (11)Paul VanRaden 2009 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)

Interbull Genomics Workshop, Jan (12)Paul VanRaden 2009 Foreign DNA in North American Data Proven bulls, Young bulls, and Females CtryoldyngfemCtryoldyngfem NLD GBR771 DEU223164DNK550 ITA14175LUX008 AUS12300BEL310 HUN6292CHE400 FRA12192NZL400 CZE3150FIN100

Interbull Genomics Workshop, Jan (13)Paul VanRaden 2009 USA Update  Genomic PTAs official in January Traditional PTAs sent to Interbull MACE used if foreign dtrs included Genomic info used for most bulls Genomic PTA transferred to descendants (to ancestors in future)  Jersey results also are official  More Brown Swiss needed (CHE)

Interbull Genomics Workshop, Jan (14)Paul VanRaden 2009 Genomic Methods  Direct genomic evaluation Sum of effects for 38,416 genetic markers Not published  Combined genomic evaluation Include phenotypes of non-genotyped ancestors by selection index  Transferred genomic evaluation Propagate info from genotyped animals to non-genotyped relatives by selection index

Interbull Genomics Workshop, Jan (15)Paul VanRaden 2009 Genotyped Animals (n=19,464) As of December 2008

Interbull Genomics Workshop, Jan (16)Paul VanRaden 2009 Experimental Design - Update Holstein, Jersey, and Brown Swiss breeds HOLJERBSW Predictor: Bulls born <20004,4221, Cows with data Total5,3691, Predicted: Bulls born >20002, Data from 2004 used to predict independent data from 2009

Interbull Genomics Workshop, Jan (17)Paul VanRaden 2009 Reliability Gain 1 by Breed Yield traits and NM$ of young bulls TraitHOJEBS Net merit2483 Milk2660 Fat32115 Protein2421 Fat % Protein % Gain above parent average reliability ~35%

Interbull Genomics Workshop, Jan (18)Paul VanRaden 2009 Reliability Gain by Breed Health and type traits of young bulls TraitHOJEBS Productive life3272 Somatic cell score23316 Dtr pregnancy rate287- Final score201- Udder depth37183 Foot angle258- Trait average2911N/A

Interbull Genomics Workshop, Jan (19)Paul VanRaden 2009 Value of Genotyping More Animals Actual and predicted gains for 27 traits and for Net Merit BullsReliability Gain PredictorPredictedNM$27 trait avg Cows:

Interbull Genomics Workshop, Jan (20)Paul VanRaden 2009 Genomic MACE Genomics Task Force, Pete Sullivan  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

Interbull Genomics Workshop, Jan (21)Paul VanRaden 2009 Conclusions  Reliability for young animals 30-38% for traditional parent averages 60-70% genomic REL for USA HOL traits 81% using 40,360 simulated bulls 83% using 100K instead of 50K markers  High reliability requires large numbers of genotyped animals Gains much smaller for USA JER and BSW breeds  Trading, sharing, profit is needed  Revised MACE may include genomics

Interbull Genomics Workshop, Jan (22)Paul VanRaden 2009 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 – , Agriculture Research Service Holstein and Jersey breed associations Contributors to Cooperative Dairy DNA Repository (CDDR)

Interbull Genomics Workshop, Jan (23)Paul VanRaden 2009 CDDR Contributors  National Association of Animal Breeders (NAAB, Columbia, MO) ABS Global (DeForest, WI) Accelerated Genetics (Baraboo, WI) Alta (Balzac, AB, Canada) Genex (Shawano, WI) New Generation Genetics (Fort Atkinson, WI) Select Sires (Plain City, OH) Semex Alliance (Guelph, ON, Canada) Taurus-Service (Mehoopany, PA)