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2007 Paul VanRaden Animal Improvement Programs Laboratory, USDA Agricultural Research Service, Beltsville, MD, USA 2008 New.

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Presentation on theme: "2007 Paul VanRaden Animal Improvement Programs Laboratory, USDA Agricultural Research Service, Beltsville, MD, USA 2008 New."— Presentation transcript:

1 2007 Paul VanRaden Animal Improvement Programs Laboratory, USDA Agricultural Research Service, Beltsville, MD, USA Paul.VanRaden@ars.usda.gov 2008 New Genomic Predictions Combine DNA and DHIA Data

2 NDHIA 2008 (2) Paul VanRaden 2008 Traditional Pedigree Sire of Sire Sire Dam of Sire Animal Sire of Dam Dam Dam of Dam

3 NDHIA 2008 (3) Paul VanRaden 2008 Genomic Pedigree

4 NDHIA 2008 (4) Paul VanRaden 2008 Example of SNP Haplotypes caacgtat caacggat SNP atccgaat atccgcat … …… … SNP tctaggat tctcggat SNP … …Chr1 Chr2 Haplotype is a set of single nucleotide polymorphisms (SNPs) on a chromosome. Haplotype 1tca gacHaplotype 2

5 NDHIA 2008 (5) Paul VanRaden 2008 SNP Pedigree atagatcgatcg ctgtagcttagg agggcgcgcagt cgatctagatcg cggtagatcagt agagatcgatct atggcgcgaacg ctatcgctcagg ctgtagcgatcg agatctagatcg agagatcgcagt atgtcgctcacg ctgtctagatcg atgtcgcgcagt

6 NDHIA 2008 (6) Paul VanRaden 2008 Haplotype Pedigree atagatcgatcg ctgtagcttagg agggcgcgcagt cgatctagatcg cggtagatcagt agagatcgatct atggcgcgaacg ctatcgctcagg ctgtagcgatcg agatctagatcg agagatcgcagt atgtcgctcacg ctgtctagatcg atgtcgcgcagt

7 NDHIA 2008 (7) Paul VanRaden 2008 Haplotypes Sum to Genotypes agatctagatcg 111211120200 ctgtagcgatcg

8 NDHIA 2008 (8) Paul VanRaden 2008 Genotype Pedigree Count number of second allele 121101011110 111211120200 101121101111 122221121111 101101111102 011111012011 121120011010 0 = homozygous for first allele (alphabetically) 1 = heterozygous 2 = homozygous for second allele (alphabetically)

9 NDHIA 2008 (9) Paul VanRaden 2008 How Related are Relatives?  Example: Full sibs are expected to share 50% of their DNA on average, with SD of 5% may actually share 40% to 60% of their DNA because each inherits a different mixture of chromosome segments from the two parents.  Combine genotype and pedigree data to determine exact fractions

10 NDHIA 2008 (10) Paul VanRaden 2008 Measuring Genetic Similarity  Cattle genome sequenced in 2004 30 chromosome pairs (including X,Y) 3 billion letters from each parent  Illumina Bovine SNP50 TM Chip 58,000 genetic markers in 2007 39,835 used in genomic predictions Cost about $200 per animal

11 NDHIA 2008 (11) Paul VanRaden 2008 Genotyped Bulls from Cooperative Dairy DNA Repository  DNA of bulls stored in Beltsville (BFGL)  Genotypes of 2560 proven bulls included in computing predictions Bulls born 1994-1996 with >75% reliability of Net Merit Plus ancestor bulls born 1952-1993  Genotypes of 659 later bulls used to test predictions Born 2001 with >75% reliability of Net Merit

12 NDHIA 2008 (12) Paul VanRaden 2008 Contributors of DNA CDDR bulls to predict born in 2001 AI OrganizationCode Number of bulls chosen CRI / Genex1126 Select Sires7107 Alta Genetics1167 Accelerated1444 ABS Global29120 Semex20032

13 NDHIA 2008 (13) Paul VanRaden 2008 Birth Years of Bulls Genotyped Data cutoff

14 NDHIA 2008 (14) Paul VanRaden 2008 Simulated Results Actual pedigrees and 10,000 SNPs  Normally distributed QTLs, n = 100  Reliability vs parent average REL 58% vs 36% if QTLs are between SNPs 71% vs 36% if QTLs are located at SNPs Higher REL if major loci and Bayesian methods used, lower if many loci (>100) affect trait

15 NDHIA 2008 (15) Paul VanRaden 2008 Actual Results  Predict January 2008 daughter deviations for 569 younger bulls from August 2003 PTAs for 2650 older bulls  Results computed for 5 yield traits, 5 health traits, 16 conformation traits, and Net Merit

16 NDHIA 2008 (16) Paul VanRaden 2008 Reliabilities and R-square values comparing traditional to genomic predictions Squared corr (x100) Reliability TraditionalGenomic Trait PAGenomicPARealizedGain Net Merit 821365418 Milk 3044385416 Fat 1539386527 Protein 3143385113 Fat % 2858387234 Protein % 3251386628

17 NDHIA 2008 (17) Paul VanRaden 2008 Reliabilities and R-square values comparing traditional to genomic predictions Squared corr (x100) Reliability TraditionalGenomic Trait PAGenomicPARealizedGain Prod Life 919284719 SCS 723325422 DPR 1523254015 SCE 192331365 DCE 242731365 Final Score 243228379

18 NDHIA 2008 (18) Paul VanRaden 2008 Conclusions  Genomic predictions significantly better than parent average (P <.0001) for all 26 traits tested  Gains in reliability equivalent on average to 9 daughters with records

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