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How the genomic evaluation program works

How the genomic evaluation program works

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How the genomic evaluation program works

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  1. How the genomic evaluation program works

  2. Short history • Illumina BovineSNP50™ BeadChip developed • Accuracy of genomic information assessed by using 2004 evaluations of bulls born before 2000 to predict 2009 evaluations of young bulls • Unofficial genomic evaluations of bull calves provided to industry beginning in April 2008 • Jersey results released in October 2008 • New results released every 2 months • Nearly 23,000 animals genotyped through Mar. 2009

  3. 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

  4. Source of genomic evaluations • DNA extracted from blood, hair, or semen • ~40,000 genetic markers (SNPs) evaluated • For each SNP, difference in PTA estimated between animals with 1 allele compared to the other allele • Genomic evaluation combines SNP effect estimates with existing PA or PTA • Genomic data contribute ~11 daughter equivalents to reliability

  5. SNP edits and counts

  6. How to get animals genotyped • Participating AI organizations have 5-year exclusive right to evaluate bulls genomically • Each AI organization genotypes first-choice flushes, thereby usually avoiding duplicate genotypes • Web-based system collects nominations • Avoid duplication • Confirm validity of ID and pedigree • Associate sample ID with animal ID • Breed associations offer cow genotyping service

  7. Steps to prepare genotypes • Nominate animal for genotyping; confirm not already genotyped • Collect hair, blood, or semen from animal • Blood not suitable for twins • Send to laboratory for extraction • Transfer DNA to BeadChip (12 samples/chip) for 3-day genotyping process

  8. Steps to prepare genotypes (cont.) • Read red/green intensities from chip • Transfer intensity files to AIPL for calling genotypes • Check genotypes for duplicates, parent-progeny conflicts, and wrong sex

  9. DNA laboratories • Research • Bovine Functional Genomics Laboratory (BFGL), USDA (Beltsville, MD) • University of Alberta (Edmonton, AB, Canada) • University of Missouri (Columbia, MO) • Illumina (San Diego, CA) • Commercial (some do extraction only) • GeneSeek (Lincoln, NE) • Genetics & IVF Institute (Fairfax, VA) • Genetic Visions (Middleton, WI) • DNA LandMarks (Saint-Jean-sur-Richelieu, QC, Canada) • Maxxam Analytics (Mississauga, ON, Canada) • ABS (DeForest, WI, through SyGen/PIC, Franklin, KY )

  10. 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) • Genotype conflicts with parent(s) • Pedigree error • Sample ID error • Laboratory error • Genotype checked against all others to find true parent

  11. Accurate evaluations • Accurate genomic evaluations require estimates of SNP effects • Evaluations with high reliability provide the most information • Recent animals are more useful than ones from earlier generations • Reliability of genomic evaluations increases with number of predictor animals

  12. Genomic evaluation & reliability • Calculate parent average (PA) based only on genotyped animals with best linear unbiased prediction • Combine traditional PA (or evaluation) with genomic PA and evaluation using selection index weights • Update traditional evaluation with additional information from genomics • Reliability from inverse of genomic relationship matrix

  13. AI organizations, breed associations nominations samples evaluations Animal Improvement Programs Laboratory, USDA evaluations Dairy producers samples samples genotypes DNA laboratories Data & evaluation flow

  14. Genomic vs. traditional PTA • Genotype can be thought of as source of information like parents, progeny, and records • Official PTA that include a genomic contribution are identified • One genotype used to calculate 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

  15. Genomic vs. traditional (cont.) • Protein • Net merit

  16. Genomic vs. traditional – protein PTA

  17. Genomic vs. traditional – net merit

  18. Genomic vs. trad. – protein reliability

  19. Genomic vs. trad. – net merit reliability

  20. Reliability frequencies – young bulls Traditional PA Genomic PTA

  21. Collaboration with Canada • Semex • Participated since beginning of genomics research • Contributed genotypes to providing a important increase in accuracy for first test • Genotypes will be shared between AIPL and Canadian Dairy Network • AIPL and University of Guelph collaboration

  22. Collaboration with Canada (cont.) • Same set of predictor animals used in Canada and U.S. so that evaluations of genotyped animals have same accuracy • Canada expects official release of genomic evaluations in August 2009 • Common procedures between 2 countries assist in industry acceptance

  23. Use of genomic evaluations • AI organizations determine which young bulls to buy • Considered in selection of mating sires • Impact on bull dam selection will increase • Used to market semen from 2-year-old bulls

  24. January 2009 • Genomic evaluations became official • Genotyped ancestors contribute their evaluations to descendants • Evaluations of all genotyped females are public • Evaluations of males enrolled with NAAB or ≥24 months old are public • Young-bull genomic evaluations may be shared among AI organizations or disclosed by owner

  25. Updates between official evaluations • Genomic evaluations calculated approximately every 2 months • Evaluations of animals that already have an official evaluation not released • Evaluations of new animals distributed to owners • Females by breed associations • Males by NAAB • Usually 1,000–2,000 new genotypes included

  26. Distribution of evaluations • Nomination establishes a requester who receives the genomic evaluation • Requesters • 7 participating AI organizations • U.S. and Canadian Holstein associations • American Jersey Cattle Association • Some laboratories • Requesting AI organization can agree to share an evaluation with other AI organizations

  27. Distribution of evaluations (cont.) • Evaluations of all females sent to respective breed associations for distribution to owners • NAAB distributes bull evaluations to owners and manages sharing of evaluations among AI organizations • Genomic evaluations of animals with official evaluations released as unofficial at updates between official evaluations

  28. 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

  29. Schedule • Calculate SNP effects with each of 3 annual traditional evaluations • Calculate genomic evaluations once or more between traditional evaluations • Recalculate SNP effects if significant number of predictor animals added • May use existing SNP effects if only young animals added

  30. Improvements • Require bar codes on sample containers to reduce errors and improve lab efficiency • Require animals be enrolled with breed association before DNA sample collected • Process genotypes frequently; check for and report conflicts as received • Reduce processing time by improving efficiency of genotype calling either by laboratories or at AIPL

  31. Calling genotypes • Scanner reads chip recording intensities of red and green • Software converts those to AA, AB, or BB • Genotype is missing if assignment is uncertain • Accuracy can be improved by adjusting for variation in intensity due to SNP and animal • Techniques to automate adjustment are underway • Manual intervention can increase accuracy of calling with current software

  32. Plans to increase accuracy • Genotype more predictor bulls • Automatic increase as bulls in waiting receive traditional evaluations • Increase number of SNPs used • Reach 1,500 Brown Swiss through foreign collaboration? • Increase genotyped Jerseys from both domestic animals and possible foreign collaboration

  33. International implications • All major dairy countries investigating genomic selection • Interbull meeting January 2009 discussed how genomic evaluations should be integrated • AI organizations need to find balance between competitive benefits from treating genotypes as proprietary versus sharing • Importing countries must change rules to allow for genomically evaluated young bulls

  34. Longer-term possibilities • Determine inheritance of individual chromosome segments (haplotyping) • May allow better tracking of QTL • Approximate genotypes of missing ancestors to increase predictor population • Increase number of SNPs or even use entire DNA sequence

  35. Implications • Extraordinarily rapid implementation of genomic evaluations • Young bull acquisition and marketing now based on genomic evaluations • Genomic evaluations may allow more cows from commercial herds to be used as bull dams

  36. 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) • Agricultural Research Service, USDA