Paul VanRaden Animal Improvement Programs Laboratory Agricultural Research Service, USDA Beltsville, MD 2014 Paul VanRaden Advancing.

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Paul VanRaden Animal Improvement Programs Laboratory Agricultural Research Service, USDA Beltsville, MD 2014 Paul VanRaden Advancing Dairy Cattle Genetics: Genomics and Beyond, Phoenix, AZ, Feb 19, 2014 (1) Impact of Genomics on Genetic Improvement

Paul VanRaden 2014 Advancing Dairy Cattle Genetics: Genomics and Beyond, Phoenix, AZ Feb 19, 2014 (2) Progress from previous workshops l Previous progress w 1995 workshop - PL w 2003 workshop - DPR l Progress requires w Organized trait definition, collection w Large database and genetic evaluation w Extension, education l Future progress will require increased cooperation DPR Trend

Paul VanRaden 2014 Advancing Dairy Cattle Genetics: Genomics and Beyond, Phoenix, AZ Feb 19, 2014 (3) NM$ trend measured by historical indexes

Paul VanRaden 2014 Advancing Dairy Cattle Genetics: Genomics and Beyond, Phoenix, AZ Feb 19, 2014 (4) Expected and realized NM$ progress l Actual progress $80 / year vs. $90 in theory l Female selection has largest genomic benefit w Shorter generation interval and higher REL w Embryo transfer now more valuable l Male selection has reduced age and REL w 3% of sons in AI had young sires in 2008 compared to 81% in 2012, >90% in theory

Paul VanRaden 2014 Advancing Dairy Cattle Genetics: Genomics and Beyond, Phoenix, AZ Feb 19, 2014 (5) Embryo transfer calves, by year

Paul VanRaden 2014 Advancing Dairy Cattle Genetics: Genomics and Beyond, Phoenix, AZ Feb 19, 2014 (6) Genetic choices l Before genomics: w Proven bulls with daughter records (PTA) w Young bulls with parent average (PA) l After genomics: w Young animals with DNA test (GPTA) w Reliability of GPTA ~70% compared to PA ~35% and PTA ~85% for Holstein NM$

Paul VanRaden 2014 Advancing Dairy Cattle Genetics: Genomics and Beyond, Phoenix, AZ Feb 19, 2014 (7) Young bulls: 2013 NM$ vs PA

Paul VanRaden 2014 Advancing Dairy Cattle Genetics: Genomics and Beyond, Phoenix, AZ Feb 19, 2014 (8) Proven bulls: 2013 vs NM$

Paul VanRaden 2014 Advancing Dairy Cattle Genetics: Genomics and Beyond, Phoenix, AZ Feb 19, 2014 (9) Young bulls: 2013 vs NM$

Paul VanRaden 2014 Advancing Dairy Cattle Genetics: Genomics and Beyond, Phoenix, AZ Feb 19, 2014 (10) Top Proven Bulls from April 2010 Net MeritDaughters PA Freddie O-Man Planet Super Man O Man Mano McCormack Alta Ross Top 8 Avg

Paul VanRaden 2014 Advancing Dairy Cattle Genetics: Genomics and Beyond, Phoenix, AZ Feb 19, 2014 (11) Top Young Bulls from April 2010 Net MeritDaughters PA Observer Robust Twist Edward Erdman Networth Bookem Mauser Top 8 Avg

Paul VanRaden 2014 Advancing Dairy Cattle Genetics: Genomics and Beyond, Phoenix, AZ Feb 19, 2014 (12) Proven bull: Reliability across time

Paul VanRaden 2014 Advancing Dairy Cattle Genetics: Genomics and Beyond, Phoenix, AZ Feb 19, 2014 (13) Young bull: Reliability across time Revised calculation

Paul VanRaden 2014 Advancing Dairy Cattle Genetics: Genomics and Beyond, Phoenix, AZ Feb 19, 2014 (14) Example PTA changes (Observer) Daugh-ProteinSCS ReleasetersDYDTradPTAGPTAPAGPTA Aug ’ Dec ’ Apr ’ Aug ’ Dec ’131,

Paul VanRaden 2014 Advancing Dairy Cattle Genetics: Genomics and Beyond, Phoenix, AZ Feb 19, 2014 (15) Genomic reliability by breed Breed ReliabilityAYBSJE 1 HO Genomic REL (%) PA REL (%)2830 Difference Bulls in reference6805,7674,20724,547 Animals genotyped1,7889,01659,923469,960 Exchange partnersCANInterbull, CAN CAN, DNKCAN, ITA, GBR 1 Jersey statistics include 2% REL gain from 1,068 DNK bulls added in January

Paul VanRaden 2014 Advancing Dairy Cattle Genetics: Genomics and Beyond, Phoenix, AZ Feb 19, 2014 (16) Genomic reliability by trait for HO Trait ReliabilityYieldSCSPLDPR Genomic REL (%) PA REL (%) Difference TypeStatureUd DepDCE Genomic REL (%) PA REL (%) Difference

Paul VanRaden 2014 Advancing Dairy Cattle Genetics: Genomics and Beyond, Phoenix, AZ Feb 19, 2014 (17) Previous and future biases l Previous biases have been reduced: w Polygenic effect added (2010), cow adjustments (2010), DGV weight reduced (2012, 2013), PL correlations reduced (2012) l Future biases will need to be reduced: w Genomic pre-selection of progeny or mates w Early daughters not from random sampling

Paul VanRaden 2014 Advancing Dairy Cattle Genetics: Genomics and Beyond, Phoenix, AZ Feb 19, 2014 (18) % genotyped mates of top young bulls Net Merit (Aug 2013 ) Percentage of mates genotyped Supersire Numero Uno S S I Robust Topaz Garrold Mogul

Paul VanRaden 2014 Advancing Dairy Cattle Genetics: Genomics and Beyond, Phoenix, AZ Feb 19, 2014 (19) TraitMeanSDMinMax NM$89033 Protein0001 Prod Life Dtr Preg Rate SCS Final Score Udder Depth Future bias from young bull mates

Paul VanRaden 2014 Advancing Dairy Cattle Genetics: Genomics and Beyond, Phoenix, AZ Feb 19, 2014 (20) Economics of fertility defect HH1 l Pawnee Farm Arlinda Chief (born 1962) w Contributed 14% of global Holstein genes w $25 billion value of increased milk yield w $0.4 billion cost of HH1 mid-term abortions l How many more fertility defects are there? w ~0.2 / animal estimated from inbreeding depression (VanRaden and Miller, 2006 JDS)

Paul VanRaden 2014 Advancing Dairy Cattle Genetics: Genomics and Beyond, Phoenix, AZ Feb 19, 2014 (21) Haplotype tests, then lab tests FrequencyLab tests 1 GenotypesJH1HH1JH1HH1 Normal ,867113,792 Carrier ,7502,793 Homozygous No call Total ,893117,049 1 Data from the Geneseek Genomic Profiler (GGP) and GGP-HD for causative mutations (JH1 = CWC15 and HH1 = APAF1)

Paul VanRaden 2014 Advancing Dairy Cattle Genetics: Genomics and Beyond, Phoenix, AZ Feb 19, 2014 (22) Jay Lush, 1948 (The Genetics of Populations) l “The rapid rate at which genes have been found in each species, whenever people started to study it genetically, and the fact that in most of these species the rate of finding new genes actually seemed to increase with continued study until so many genes were known that interest in keeping stocks of each new one waned.” (p. 32)

Paul VanRaden 2014 Advancing Dairy Cattle Genetics: Genomics and Beyond, Phoenix, AZ Feb 19, 2014 (23) Discovery of missing ancestors Ancestor Discovered (if genotyped) SireMGSMGGS Breed% Correct * % Correct Holstein Jersey10095 Brown Swiss * % Correct = Top ranked candidate ancestor matches the true ancestor. In 2013, >50,000 missing or incorrect sires were discovered and reported to breeders

Paul VanRaden 2014 Advancing Dairy Cattle Genetics: Genomics and Beyond, Phoenix, AZ Feb 19, 2014 (24) Haplotype pedigree Chromosome 15, O-Style

Paul VanRaden 2014 Advancing Dairy Cattle Genetics: Genomics and Beyond, Phoenix, AZ Feb 19, 2014 (25) What’s the best cow we can make? A “Supercow” constructed from the best haplotypes in the Holstein population would have an EBV(NM$) of $7515

Paul VanRaden 2014 Advancing Dairy Cattle Genetics: Genomics and Beyond, Phoenix, AZ Feb 19, 2014 (26) After the cow is perfected l Beyond genomics could be transgenics w Create traits not yet available in nature w Add or subtract genes as needed or desired w Produce higher value milk, create polled l Preserving genetic variation is a key to adapting to different definitions of perfection

Paul VanRaden 2014 Advancing Dairy Cattle Genetics: Genomics and Beyond, Phoenix, AZ Feb 19, 2014 (27) Conclusions l Recent progress is much faster, but emphasis has shifted to different traits l Genomic predictions are more accurate for populations with more reference bulls l Statistical adjustments have reduced upward biases, but new biases may soon occur l Young animals with improved reliability and high merit can greatly speed genetic progress

Paul VanRaden 2014 Advancing Dairy Cattle Genetics: Genomics and Beyond, Phoenix, AZ Feb 19, 2014 (28) l Jan Wright, Mel Tooker, Tabatha Cooper, John Cole, Dan Null, and Jana Hutchison assisted with computation and graphics l Members of the Council on Dairy Cattle Breeding (CDCB) provided data Acknowledgments