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Using 90,113 single nucleotide polymorphisms in genomic evaluation of dairy cattle

Using 90,113 single nucleotide polymorphisms in genomic evaluation of dairy cattle. Abstr . 539. To increase accuracy of genomic rankings. Genotype more animals Increase number and informativeness of SNP Add traits Improve evaluation methods. More SNP. Better tracking of QTL

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Using 90,113 single nucleotide polymorphisms in genomic evaluation of dairy cattle

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  1. Using 90,113 single nucleotide polymorphisms in genomic evaluation of dairy cattle Abstr. 539

  2. To increase accuracy of genomic rankings • Genotype more animals • Increase number and informativeness of SNP • Add traits • Improve evaluation methods

  3. More SNP • Better tracking of QTL • IlluminaBovineHD • 777K, cost twice of 50K, only .4% gain in REL • GeneSeek Genomic Profiler-HD (GHD) • 76,999 SNP • 28,376 (63%) of usable 50K SNP (37% missing) • 48,491 BovineHD SNP added • Cost equivalent to 50K

  4. GGP-HD SNP selection • Released December 2012 • Selected for: • Greatest effects on Holstein net merit • High MAF • Reduced gaps between SNP • Parentage SNP • Imputation of microsatellite markers • 76,867 unique nuclear SNP • 13 mitochondrial SNP

  5. SNPused in evaluation • GGP-HD had 74,770 usable and 2,229 not usable • Duplicates • Y chromosome or Mitochondrial • Low call rate • Excess parent-progeny conflicts • MAF <1% for each of 4 breeds • 50K chip had 45,188 usable SNP • LD, GGP, and GGP2 had 6,870 to 9,482 usable • 91,170 usable on either GGP-HD or 50K

  6. SNP (no.) in common among 91,170

  7. Sources for imputation of new SNP

  8. Imputation accuracy to 45K or 90K

  9. Genomic evaluation • Cut off study • Training set – August 2009 traditional evaluations • Validation Set – April 2013 daughter performance • Yield, Health, Calving and Type traits evaluated • SNP sets • 45,188 SNP • 90,113 SNP

  10. Training and Validation sets (yield)

  11. Holstein Gains in Reliability • Average 0.3% gain in reliability across 28 traits

  12. Jersey and Brown Swiss Results

  13. Conclusions • More markers with no increase in genotyping cost • Imputation less accurate to 90K than to 45K • Reliability increases for some traits, decrease in others • Processing times double for most operations (imputation, marker estimation, creating G matrix)

  14. Future • With more GHD genotypes: • Improved imputation accuracy, particularly for breeds other than Holstein • Possible reduction in computing time by eliminating 50K-only SNP that do not contribute to accuracy • SNP that are genetic variants included in future chips

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