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Genomic Prediction Results. 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.
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Measuring Genetic Similarity • Cattle genome sequenced in 2004 • 30 chromosome pairs (including X,Y) • 3 billion letters from each parent • Illumina Bovine SNP50TM Chip • 58,000 genetic markers in 2007 • 39,835 used in genomic predictions • Cost about $200 per animal
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. • SD 3.5% reported previously was low
Simulated Results (Apr 2007) • 1777 older and 500 younger bulls • 10,000 SNPs and 100 QTLs • Reliability vs parent average REL • 58% vs 36% for young bulls • Higher REL if major loci and Bayesian methods used, lower if many loci (>100) affect trait
Simulated Results (2008) • 8271 older and 1984 younger bulls • 40,000 SNPs and 500 QTLs • Provided timing, memory test • Reliability vs parent average REL • 79% vs 37% expected for young bulls • 76% vs 37% observed in simulation
Genotyped Bulls (Feb 2007)from Cooperative Dairy DNA Repository • DNA of bulls stored in Beltsville (BFGL) • 2560 proven bulls used to computed predictions • Bulls born 1994-1996 with >75% reliability of Net Merit • Plus ancestor bulls born 1952-1993 • 659 later bulls used to test predictions • Born 2001 with >75% reliability of Net Merit
Proposed Genotyping (Apr 2007) Data cutoff
Acknowledgments • Funding: • NRI grants 2006-35205-16888, 16701 • CDDR Contributors (NAAB, Semex) • Genotyping and DNA extraction: • BFGL, U. Missouri, U. Alberta, GeneSeek, GIFV, and Illumina • Computing from AIPL staff
Genomic Methods • Direct genomic evaluation • Inversion for linear prediction, REL • Iteration for nonlinear prediction • Combined genomic evaluation • Traditional PA or PTA, subset PA or PTA, and direct genomic combined by REL in 3 x 3 selection index • Nonlinear genomic predictions used
Actual Results (Feb 2007 data) • August 2003 PTAs for 2650 older bulls to predict January 2008 daughter deviations for 569 younger bulls (total = 3119 bulls) • Results computed for 27 traits: 5 yield, 5 health, 16 conformation, and Net Merit • Nonlinear A used, B didn’t work
Reliabilities and R-square values comparing traditional to genomic predictions
Reliabilities and R-square values comparing traditional to genomic predictions
Expected vs Observed Reliability • Reliability for predictee bulls • Average across traits: 57% expected vs. 48% observed vs. 30% PA • Observed range 72% (fat pct) to 36% • PTA regressions .8 to .9 of expected • Redo 2003 cutoff using April data • Develop REL and PTA adjustments
Clones and Identical Twins21HO2121, 21HO2125, 21HO2100, CAN6139300, CAN6139303
X, Y, Pseudo-autosomal SNPs 35 SNPs 35 SNPs 0 SNPs 487 SNPs
SNPs on X Chromosome • Each animal has two evaluations • Expected genetic merit of daughters • Expected genetic merit of sons • Difference is sum of effects on X • SD = .1 σG, smaller than expected • Correlation with sire’s daughter vs. son PTA difference was significant (P<.0001), regression close to 1.0
Genetic Evaluation Advancesand increases in genetic progress
Conclusions • Genomic predictions significantly better than parent average (P < .0001) for all 26 traits tested • Gains in reliability from 2650 bulls (Feb data) equivalent on average to 9 daughters with records • April data included 5285 proven bulls, more analysis needed