2007 Paul VanRaden, Mel Tooker, and Nicolas Gengler Animal Improvement Programs Lab, Beltsville, MD, USA, and Gembloux Agricultural U., Belgium

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Presentation transcript:

2007 Paul VanRaden, Mel Tooker, and Nicolas Gengler Animal Improvement Programs Lab, Beltsville, MD, USA, and Gembloux Agricultural U., Belgium 2008 Effects of Allele Frequency Estimation on Genomic Predictions and Inbreeding Coefficients

FASS annual meeting, July 2008 (2) Mel Tooker 2008 Experimental Design  Predict April 2008 PTA from August 2003 PTA 3,576 older Holstein bulls 1,759 younger bulls (total = 5,335)  Using 38,416 SNP from Illumina Bovine SNP50 TM Chip

FASS annual meeting, July 2008 (3) Mel Tooker 2008 Goals  Compare genomic to traditional relationships and inbreeding Formulas to compute G and A G – A differences for 5,335 bulls  Compare genomic predictions using different estimates of frequency Estimate 38,416 allele frequencies Simple estimates vs. base population Or ignore frequency, use 0.5 instead

FASS annual meeting, July 2008 (4) Mel Tooker 2008 Differences in G and A  Detected clones, identical twins, and duplicate samples  Detected incorrect DNA samples  Detected incorrect pedigrees  Identified correct source of DNA by genomic relationships with other animals

FASS annual meeting, July 2008 (5) Mel Tooker 2008 Genotype Data for Elevation Chromosome

FASS annual meeting, July 2008 (6) Mel Tooker 2008 Genotype Data from Inbred Bull Chromosome 24 of Megastar

FASS annual meeting, July 2008 (7) Mel Tooker 2008 Close Inbreeding (F=14.7%): Double Grandson of Aerostar Aerostar Megastar Chromosome 24

FASS annual meeting, July 2008 (8) Mel Tooker Formulas to Compute G  Sum products of genotypes (g) adjusted for allele frequency (p) G1 jk = ∑ (g ij -p i ) (g ik -p i ) / [2 ∑ p i (1-p i )]  Or individually weighted by p G2 jk = ∑ (g ij -p i ) (g ik -p i ) / 2p i (1-p i )  Or scaled by intercept (b 0 ) and regression (b 1 ) on A, using p = 0.5 G3 jk = [∑ (g ij - 0.5) (g ik - 0.5) – b 0 ] / b 1

FASS annual meeting, July 2008 (9) Mel Tooker 2008 Compare A with 3 formulas for G Simulated Data Diagonals 1 of G FormulaMeanSDCorr. with A A G G G Diagonal = 1 + Inbreeding

FASS annual meeting, July 2008 (10) Mel Tooker 2008 Compare A with 3 formulas for G Actual Data Diagonals 1 of G FormulaMeanSDCorr. with A A G G G Diagonal = 1 + Inbreeding

FASS annual meeting, July 2008 (11) Mel Tooker 2008 Summary of G Formulas for Genomic Inbreeding  Correlations ranked G3 > G1 > G2 in simulation vs. G2 > G1 > G3 with real data (opposite)  G2 and G1 biased down, G3 up G1 and G2 can be adjusted toward A using b 0 and b 1, similar to G3 formula After adjusting, mean G1 = 1.08 and G2 = 1.09 compared to G3 = 1.13 and A = 1.05 G1 was unbiased in simulation using true rather than estimated frequencies

FASS annual meeting, July 2008 (12) Mel Tooker 2008 Allele Frequency Estimation  Base population frequencies Combine genotypes and pedigrees Efficient algorithm (Gengler, 2007)  Simple frequency estimates p i = ∑ g ij / 2n  Extra simple estimates (p = 0.5) Z = 0.5, 0, -0.5 in mixed model

FASS annual meeting, July 2008 (13) Mel Tooker 2008 Effects of Frequency on G1 Frequency Estimate Mean of Diagonal Corr (G1, A) DiagonalOff-diag Base Simple

FASS annual meeting, July 2008 (14) Mel Tooker 2008 R 2 of Genomic Predictions Frequency estimates Trait.5SimpleBase Net Merit Milk Protein yield Fat % Productive life Somatic cell score Dtr pregnancy rate

FASS annual meeting, July 2008 (15) Mel Tooker 2008 Conclusions  Genomic relationships and inbreeding are more useful than Wright’s 1922 pedigree formulas  Formulas to compute G have Large effects on inbreeding coefficients Small effects on reliability of predictions  Estimates of allele frequencies For base population better than simple Not needed using regression of G on A

FASS annual meeting, July 2008 (16) Mel Tooker 2008 Acknowledgments  Funding: National Research Initiative grants CDDR Contributors (NAAB, Semex)  Genotyping and DNA extraction: BFGL, U. Missouri, U. Alberta, GeneSeek, GIFV, and Illumina  Computing from AIPL staff George Wiggans, Leigh Walton