Walking the Cattle Continuum: Moving From the BovineSNP50 to Higher- and Lower-Density SNP Panels

1. Walking the Cattle Continuum: Moving From the BovineSNP50 to Higher- and Lower-Density SNP Panels

2. Introduction • The Illumina Bovine SNP50 Bead Chip has been very successful • A new high-density chip with 778K markers is now available • A low-density chip with 3K markers will be available soon • Other densities under development

3. Bovine SNP50 Bead Chip • The Illumina Bovine SNP50 Bead Chip has been very successful • 43,382 SNP used for genetic prediction • 47,645 animals genotyped in the US, many more worldwide • 2nd generation chip with a slightly different SNP set has been developed

4. Uses of the SNP50 • Genetic improvement • Genomic prediction • Parentage and breed confirmation • Scientific research • Improving the assembly • QTL discovery (calving traits, SCS) • Recessives and causative mutations • Phylogeny

5. Most Holstein genotypes Feb 2010

6. Genotyped Holsteins August 2010 *Traditional evaluation **No traditional evaluation

7. 5000 4500 4000 Bulls (no.) 3500 3000 2500 2000 1500 1000 500 0 60 61 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 REL (%) for mlk yield REL for young Holstein bulls July 2010

8. Bovine High-Density Bead Chip (HD) • 778K SNP chosen to • Be evenly spaced • Include some Y-specific SNP • Include mitochondrial SNP • Utilize across-breed information • Fine mapping of QTL • Enhanced performance in Zebu cattle

9. Collaboration was essential • University of Missouri • Roslin Institute • UNCEIA (France) • Sao Paulo State University • University of Milan • Technische Universitaet Muenchen • Beef CRC • Embrapa • National University (Korea) • Illumina provided: • DNA sequence for a range of breeds • Pfizer provided: • DNA sequence of additional breeds • SNP discovery expertise • USDA-ARSprovided: • DNA and library construction • SNP discovery expertise • Assay design expertise

10. Data highlights • Enormous amount of DNA sequence data • ~180-200x genome equivalent coverage • ~600 BILLION base-pairs • Represents: • ~120 libraries • >300 animals • Animals from breeds representing: • European and Zebu cattle • Beef and dairy • Temperate and tropically adapted

11. Partners Deep SNP Discovery N’Dama Sahiwal Simmental Hanwoo Blonde d’Aquitaine Montbeliard BFGL Genome Assemblies Nelore Water Buffalo BFGL-Illumina Deep SNP Discovery Angus Holstein Limousin Jersey Nelore Brahman Romagnola Gir Pfizer Light SNP Discovery Angus Holstein Jersey Hereford Charolais Simmental Brahman Waygu

12. High-density chip design • >45 million SNPs discovered • ~6 million were used to design the high density chip • ~800,000 new SNPs added • Kept almost all of the BovineSNP50 SNPs • Breed groups included • Holstein, Angus, Nelore, Taurine dairy, Taurine beef, Indicine, tropically adapted Taurine • 852,645 total gaps • 850,816 (99.8%) < 20kb • 1,795 >20kb, < 100kb • 34 > 100 kb

13. The HD chip in practice • 777,962 available SNP • 160 bulls genotyped • 186,705 SNP edited-out • 1,269 unassigned chromosome • 3,197 low call rate • 1,804 Hardy-Weinberg failures • 115,850 MAF < 0.01 • 64,585 uncertain location • 591,258 useable SNP

14. Bovine Low-Density Bead Chip (3K) • 2,900 SNP • Evenly spaced • 2,882 useable SNP • 14 Y-specific SNP • Includes 82 SNP for breed determination • Expected to ship very soon • Allflex tissue-collection tags to be released • Canada will use DNA Genotek nasal swabs • Large initial use anticipated

15. Applications of the 3K chip • Producing AI sires • Accuracy adequate for initial screening • 50K or HD genotyping for bulls acquired • Confirm ID • Second-stage selection • Genotype more candidates for less money • Parentage verification and pedigree discovery • Traceability for disease outbreaks

16. Other chips • 96 SNP parentage chip • Use to identify and correct pedigree errors • Very low cost • 384 SNP chip • Use for initial screening of cows • 70 to 80% of benefit of 50K for 10% of cost with haplotyping and parental genotypes • 700K SNP Affymetrix chip • Will be cheaper than Illumina HD chip

17. Illumina chips are [mostly] nested Bovine HD (700K) Missing 7,352 SNP50 markers Missing 5,264 V2 markers Bovine SNP50 (50K) SNP50 v 2 (V2) 50K is missing 14 3K markers Missing 76 3K markers Bovine LD (3K)

18. How do we deal with other chips? • Impute to highest density • Calculate SNP effects for all HD SNP • Account for loss in accuracy due to imputation error • Store only observed genotypes • Label evaluations with source of genotype

19. Why impute haplotypes? • Predict unknown SNP from known • Measure 3,000, predict 50,000 SNP • Measure 50,000, predict 500,000 • Measure each haplotype at highest density only a few times • Predict dam from progeny SNP • Increase reliabilities for less cost

20. How does imputation work? • Identify haplotypes in population using many markers • Track haplotypes with fewer markers • e.g., use 5 SNP to track 25 SNP • 5 SNP: 22020 • 25 SNP: 2022020002002002000202200

21. Example bull haplotypes chromosome 15

22. Expected REL with haplotyping • Actual 3Ksubset of 50K genotypes • Correlation (50K, 3K) was .95 to .97 • REL PA = 35% , 3K = 63% , 50K = 70% • Simulated 500K genotypes • REL, all animals 50K = 82.6%, 500K = 84% • REL improved only if >1,000 had 500K • Gains in reliability above PA • 3K chip gives >80% of 50K REL gain • 50K chip gives >96% of 500K REL gain

23. REL Using 3K, 50K, or 500K SNP

24. Whole-genome sequencing • Whole-genome sequences on individuals will be available in the next 5 years • How will we store and use those data? • Not feasible to calculate SNP effects for 3,000,000,000 SNP • Best application may be SNP identification

25. Other genotyping issues • Collection of genotypes from universities and public research organization • 3K genotypes from cooperator herds need to enter the national dataset for reliable imputation • Encourage even more widespread sharing of genotypes across countries • Funding of genotyping necessary to predict SNP effects for future chips • Intellectual property issues

26. Conclusions • The 50K chip has been very successful, but other densities are coming • We are collaboratively developing tools to increase the ability to characterize cattle with both lower and higher density SNP chips • This technology has the potential to impact the developing world

27. Implementation Team iBMAC Consortium Funding • Illumina (industry) • Marylinn Munson • Cindy Lawley • Diane Lince • LuAnn Glaser • Christian Haudenschild • Beltsville (USDA-ARS) • Curt Van Tassell • Lakshmi Matukumalli • Steve Schroeder • Tad Sonstegard • Univ Missouri (Land-Grant) • Jerry Taylor • Bob Schnabel • Stephanie McKay • Univ Alberta (University) • Steve Moore • Clay Center, NE (USDA-ARS) • Tim Smith • Mark Allan • AIPL • Paul VanRaden • George Wiggans • John Cole • Leigh Walton • Duane Norman • BFGL • Marcos de Silva • Tad Sonstegard • Curt Van Tassell • University of Wisconsin • Kent Weigel • University of Maryland School of Medicine • Jeff O’Connell • Partners • GeneSeek • DNA Landmarks • Expression Analysis • Genetic Visions • USDA/NRI/CSREES • 2006-35616-16697 • 2006-35205-16888 • 2006-35205-16701 • 2008-35205-04687 • 2009-65205-05635 • USDA/ARS • 1265-31000-081D • 1265-31000-090D • 5438-31000-073D • Merial • Stewart Bauck • NAAB • Gordon Doak • Accelerated Genetics • ABS Global • Alta Genetics • CRI/Genex • Select Sires • Semex Alliance • Taurus Service 28

28. Questions about different chips?