C. P. Van Tassell 1,2 and J. B. Cole 2, * 1 Bovine Functional Genomics and 2 Animal Improvement Programs Laboratories Agricultural Research Service, USDA Beltsville, MD Walking the Cattle Continuum: Moving From the BovineSNP50 to Higher- and Lower-Density SNP Panels

9 th WCGALP, August 2010 (2) Van Tassell and Cole 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

9 th WCGALP, August 2010 (3) Van Tassell and Cole 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 2 nd generation chip with a slightly different SNP set has been developed

9 th WCGALP, August 2010 (4) Van Tassell and Cole 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 mutationsRecessives and causative mutations Phylogeny

9 th WCGALP, August 2010 (5) Van Tassell and Cole Most Holstein genotypes Feb 2010 CountryReference bulls Germany17,000 Netherlands16,000 France16,000 Scandinavia (DFS)16,000 United States9,300 Canada8,800

9 th WCGALP, August 2010 (6) Van Tassell and Cole Genotyped Holsteins August 2010 *Traditional evaluation **No traditional evaluation Date Young animals** All animals Bulls*Cows* Bulls Heifers ,600 2,711 9,690 1,94321, ,974 4,348 14,061 6,03133, ,378 5,086 15,328 7,62037, ,770 7,415 16,007 8,63041, ,958 7,940 16,594 9,77244, ,958 8,122 17,507 10,71346, ,963 8,186 18,187 11,30947, ,4309,37218,65211,02149,475

9 th WCGALP, August 2010 (7) Van Tassell and Cole REL (%) for mlk yield Bulls (no.) REL for young Holstein bulls July 2010

9 th WCGALP, August 2010 (8) Van Tassell and Cole 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 th WCGALP, August 2010 (9) Van Tassell and Cole Collaboration was essential Illumina provided: DNA sequence for a range of breeds Pfizer provided: DNA sequence of additional breeds SNP discovery expertise USDA-ARS provided: DNA and library construction SNP discovery expertise Assay design expertise University of Missouri Roslin Institute UNCEIA (France) Sao Paulo State University University of Milan Technische Universitaet Muenchen Beef CRC Embrapa National University (Korea)

9 th WCGALP, August 2010 (10) Van Tassell and Cole Enormous amount of DNA sequence data ~ x 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 Data highlights

9 th WCGALP, August 2010 (11) Van Tassell and Cole BFGL-Illumina Deep SNP Discovery Angus Holstein Limousin Jersey Nelore Brahman Romagnola Gir BFGL Genome Assemblies Nelore Water Buffalo Pfizer Light SNP Discovery Angus Holstein Jersey Hereford Charolais Simmental Brahman Waygu Partners Deep SNP Discovery N’Dama Sahiwal Simmental Hanwoo Blonde d’Aquitaine Montbeliard

9 th WCGALP, August 2010 (12) Van Tassell and Cole >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 High-density chip design

9 th WCGALP, August 2010 (13) Van Tassell and Cole Can replace the 50K chip used in current evaluations 1,500 HD genotypes needed to support imputation of HD from current 50K Expected gain in Rel < 2 May allow HO genotypes to contribute to accuracy of JE & BS evaluations Use of the high-density chip

9 th WCGALP, August 2010 (14) Van Tassell and Cole 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 < ,585 uncertain location 591,258 useable SNP

9 th WCGALP, August 2010 (15) Van Tassell and Cole 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

9 th WCGALP, August 2010 (16) Van Tassell and Cole Producing AI sires Accuracy adequate for initial screening 50K or HD genotyping for bulls acquired Confirm IDConfirm ID Second-stage selectionSecond-stage selection Genotype more candidates for less money Parentage verification and pedigree discovery Traceability for disease outbreaks Applications of the 3K chip

9 th WCGALP, August 2010 (17) Van Tassell and Cole 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

9 th WCGALP, August 2010 (18) Van Tassell and Cole Illumina chips are [mostly] nested Bovine HD (700K) Bovine SNP50 (50K) Bovine LD (3K) Missing 5,264 V2 markers Missing 76 3K markers SNP50 v 2 (V2) Missing 7,352 SNP50 markers 50K is missing 14 3K markers

9 th WCGALP, August 2010 (19) Van Tassell and Cole 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 How do we deal with other chips?

9 th WCGALP, August 2010 (20) Van Tassell and Cole 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 Why impute haplotypes?

9 th WCGALP, August 2010 (21) Van Tassell and Cole Identify haplotypes in population using many markers Track haplotypes with fewer markers e.g., use 5 SNP to track 25 SNP 5 SNP: SNP: How does imputation work?

9 th WCGALP, August 2010 (22) Van Tassell and Cole Example bull haplotypes chromosome 15

9 th WCGALP, August 2010 (23) Van Tassell and Cole Expected REL with haplotyping Actual 3K subset 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

9 th WCGALP, August 2010 (24) Van Tassell and Cole REL Using 3K, 50K, or 500K SNP

9 th WCGALP, August 2010 (25) Van Tassell and Cole 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 Whole-genome sequencing

9 th WCGALP, August 2010 (26) Van Tassell and Cole 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 Other genotyping issues

9 th WCGALP, August 2010 (27) Van Tassell and Cole 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 Conclusions

9 th WCGALP, August 2010 (28) Van Tassell and Cole 28 iBMAC ConsortiumFunding USDA/NRI/CSREES USDA/ARS D D D Merial Stewart Bauck NAAB Gordon Doak Accelerated Genetics ABS Global Alta Genetics CRI/Genex Select Sires Semex Alliance Taurus Service 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 Implementation Team

9 th WCGALP, August 2010 (29) Van Tassell and Cole Questions about different chips?