Overview of the Dairy Genetic Evaluation System

1. Overview of the Dairy Genetic Evaluation System

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. U.S. Dairy Population and Yield

4. Why genetic evaluations? • A valuable tool for genetic selection • Allows for comparison of animals in different environments • Can include all of the information available for each animal • Greatest impact on progress is from selection of males

5. What is an evaluation? Phenotype = Genotype + Environment • Phenotype is measurable • Pounds of milk produced • Stature • An evaluation is an estimate of merit of the Genotype

6. 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)

7. Genetic Evaluation Advances

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

9. 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

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

11. Economic Indexes • An index combines evaluations for a group of traits based on their contribution to a selection goal • Net Merit $ • Cheese Merit • Fluid Merit • TPI – Total production Index (Holstein)

12. Factors Affecting Value of Data • Completeness of ID and parentage reporting • Years herd has collected data • Size of herd • Frequency of testing and component determination

13. How Accurate are Evaluations? • Reliability measures the amount of information contributing to an evaluation • Increases at a decreasing rate as daughters are added • Also affected by: • Number of contemporaries • Reliability of parents’ evaluations • Heritability of the trait

14. What do the Numbers Mean? • Evaluations are predictions • The true value is unknown • The predictions rank animals relative to one another using a defined base • The base is the zero- or center-point for evaluations • For example: the performance of animals born in a given year

15. Expressing Evaluations • Estimated Breeding value (EBV) • Animal’s own genetic value • Predicted Transmitting ability (PTA) • ½ EBV • Expected contribution to progeny

16. Factors in Genetic Improvement • Heritability is the portion of total variation due to genetics • Milk: 30% • Daughter Pregnancy Rate: 4% • Rate of genetic improvement is determined by: • Generation interval • Selection intensity • Heritability

17. Bull Selection • Purchase promising young bulls for progeny test (PT) • Select only the best of the PT bulls for widespread use • Only about 1 in 10 PT bulls enter active service • Remove bulls from active service as better new bulls become available • Bulls remain active only a few years

18. Whole-genome Selection in Dairy Cattle

19. What is Whole-Genome Selection • Use many markers to track inheritance of chromosomal segments • Estimate the impact of each 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)

20. What is a SNP? • Single-nucleotide polymorphism • Place on the chromosome where animals differ in the nucleotides (A, C, T, or G) they have • Usually not part of the gene that controls a trait – quantitative trait locus (QTL) • With enough SNPs, association between SNP alleles and QTL alleles gives useful evaluations • SNPs chosen to be distributed evenly and have both alleles well represented in population

21. Source of Genomic Evaluations • DNA extracted from blood, hair, or semen • ~43,400 genetic markers (SNPs) evaluated • Genotypes represented as 0, 1, 2; number of A alleles (5 indicates missing) • Genomic evaluation combines SNP effect estimates with existing PA or PTA • Genomic data contribute ~11 daughter equivalents to reliability

22. Genotype Data for Elevation Chromosome 1 1000111220020012111011112111101111001121100020122002220111 1202101200211122110021112001111001011011010220011002201101 1200201101020222121122102010011100011220221222112021120120 2010020220200002110001120201122111211102201111000021220200 0221012020002211220111012100111211102112110020102100022000 2201000201100002202211022112101121110122220012112122200200 0200202020122211002222222002212111121002111120011011101120 0202220001112011010211121211102022100211201211001111102111 2110211122000101101110202200221110102011121111011202102102 1211011022122001211011211012022011002220021002110001110021 1021101110002220020221212110002220102002222121221121112002 0110202001222222112212021211210110012110110200220002001002 0001111011001211021212111201010121202210101011111021102112 2111111212111210110120011111021111011111220121012121101022 202021211222120222002121210121210201100111222121101

23. Genotype Data from Inbred Bull Chromosome 24 of Megaster 1021222101021021011102110112112211211002202000222020002020220 0000220020222202202000020020222222000020222200000220200002002 2002000000222200022220000000000020222022002000222020222220002 2022222222200002002202022202000200022000000002202220000002200 2020002222002020020020202220222222220222020002022022022220202 2202020202200022002220220022200000220200002002002000200222220 0022220202002220022202000020200000022222020200002002002222000 2022022220022000222202200222202020002202202222002220022000200 2202000002200220222000022000022000222202002222000220020020202 2020002220002220022202202200000220220020020020220002000222202 2002220020220200222202220000020220002020020202000220022000002 2022200202220200022002000200022002002000200220222220022022000 2000020002000020220020220200200002220000222002000200222000022 0220020022002202202020202020200022202000220200202202220220000 2020200002020200022222200222200020022022220000020220020200202 022022020200002000200220220002200

24. What Can Go Wrong • Sample doesn’t provide adequate DNA quality or quantity • Genotype has many SNPs that can’t be determined (90% call rate required) • Parent-Progeny conflicts • Pedigree error • Sample ID error • Laboratory error • Unrelated animal qualifies as parent or progeny

25. Parent-Progeny Verification Parent 10212002101201211001020120100 Progeny 10202010100200221001120120220

26. X Chromosome Bull 202220200002022220002020222020202 Cow 1201201212222010111022210210212022

27. Genomic vs. Traditional PTA • Genotype can be thought of as source of information like parents, progeny, and records • Indicator added to official PTA that include a genomic contribution • An animal’s one genotype can be used to calculate its genomic evaluations for all 29 traits • Genomic evaluations used the same as traditional PTA • Expected to increase rate of genetic improvement because of a large decrease in generation interval

28. Data & Evaluation Flow AI organizations, breed associations nominations samples evaluations Animal Improvement Programs Laboratory, USDA Dairy producers samples samples genotypes DNA laboratories

29. Impact on Producers • Young-bull evaluations with accuracy of early 1st-crop evaluations • AI organizations marketing genomically evaluated 2-year-olds • Bull dams likely to be required to be genotyped • Rate of genetic improvement likely to increase by up to 50% • Progeny-test programs changing

30. International Implications • All major dairy countries investigating genomic selection • Interbull meeting January 2009 discussed how genomic evaluations should be integrated • AI organizations may see benefits in wider sharing of genotypes • Importing countries must change rules to allow for genomically evaluated young bulls

31. World Market Competitiveness • US bulls recognized as siring high yield • Genetic evaluation system perceived as unbiased • Large program offers bulls with a wide range of strengths • Effective international marketing effort • Leader in genomic selection • Large population of high producing cows offers many selection candidates • Intense competition among bull studs yields good value for customer

32. Summary • Evaluation procedures have improved • Selection is the basis of genetic improvement • Effective selection has produced substantial annual genetic improvement • Indexes enable selection for overall economic merit • Increased weight on fertility necessary to prevent continued decline • Genomic evaluations are rapid and allow the use of young bulls • AIPL serves the dairy industry with reliable evaluations and research to improve procedures • Competitive in the world market

33. Financial Support • National Research Initiative grants, USDA • NAAB (Columbia, MO) • ABS Global (DeForest, WI) • Accelerated Genetics (Baraboo, WI) • Alta (Balzac, AB) • Genex (Shawano, WI) • New Generation Genetics (Fort Atkinson, WI) • Select Sires (Plain City, OH) • Semex Alliance (Guelph, ON) • Taurus-Service (Mehoopany, PA) • Holstein Association USA (Brattleboro, VT) • American Jersey Cattle Association (Reynoldsburg, OH) • American Brown Swiss Association (Beloit, WI) • Agricultural Research Service, USDA