1. Norman, 2014ICAR / Interbull annual meeting, Berlin, Germany, May 20, 2014 (1) Dr. H. Duane Norman Interim Administrator Council on Dairy Cattle Breeding Beltsville, MD 20705-2350 301-525-2006 (voice) duane.norman@cdcb.us Selection changes in the United States due to genomics

2. Norman, 2014ICAR / Interbull annual meeting, Berlin, Germany, May 20, 2014 (2) Coauthors  Janice R. Wright 1  Jana L. Hutchison 1  Jay M. Mattison 2  1 Animal Scientist, Animal Genomic and Improvement Laboratory, Beltsville, Maryland  2 Chief Executive Officer, National Dairy Herd Information Association, Verona, Wisconsin

3. Norman, 2014ICAR / Interbull annual meeting, Berlin, Germany, May 20, 2014 (3) Introduction  Genomic testing of dairy cattle accelerated in the United States in early 2008.  Genomics is changing the way breeding programs are operating.  Genomics is changing information available & choice of parents producing replacements.  It is impacting genetic improvement. Some differences in programs will be described.

4. Norman, 2014ICAR / Interbull annual meeting, Berlin, Germany, May 20, 2014 (4) Objectives  Show number of genomic tests across time.  Show how age of bulls’ ancestors have changed.  Show genetic merit of bulls entering artificial insemination (AI) service across time.  Determine expected genetic merit of future animals derived from examining confirmed pregnancies.

5. Norman, 2014ICAR / Interbull annual meeting, Berlin, Germany, May 20, 2014 (5) Traits examined  Milk  Fat  Protein  Somatic cell score (SCS)  Productive life (Prod. Life)  Daughter Pregnancy Rate (Dau. Preg. Rate)  Net Merit Dollars

6. Norman, 2014ICAR / Interbull annual meeting, Berlin, Germany, May 20, 2014 (6) Number of US animals genotyped by year (Holstein) YearFemalesMales 2007 772389 2008 27408810 2009 44457083 2010 14,2126786 2011 37,0919668 2012 81,38211,699 2013 125,31417,417

7. Norman, 2014ICAR / Interbull annual meeting, Berlin, Germany, May 20, 2014 (7) Number of US animals genotyped by year (Jersey) Year FemalesMales 2008 901123 2009 5321290 2010 3201757 2011 74271287 2012 12,6401598 2013 20,2062829

8. Norman, 2014ICAR / Interbull annual meeting, Berlin, Germany, May 20, 2014 (8) Mean PTA* of Holstein bulls entering AI by year (yield traits) YearMilkFatProteinNumber bulls -------------------(kg)-------------------- 2005 144651818 2006 175871755 2007 180971910 2008 2331081797 2009 2491491766 2010 28616101613 2011 33518131731 2012 46621171811 2013 53327201593 *Based on April 2014 evaluations

9. Norman, 2014ICAR / Interbull annual meeting, Berlin, Germany, May 20, 2014 (9) Mean PTA* of Holstein bulls entering AI by year (other traits) YearSCS Prod. Life Dau. Preg. Rate Net Merit 2005 2.99 -0.2-0.473 2006 2.94 0.3-0.4133 2007 2.91 0.4-0.2161 2008 2.92 0.6-0.1195 2009 2.88 1.60.2281 2010 2.85 2.30.2335 2011 2.81 2.90.5426 2012 2.80 3.60.5511 2013 2.75 4.20.8618 *Based on April 2014 evaluations

10. Norman, 2014ICAR / Interbull annual meeting, Berlin, Germany, May 20, 2014 (10) Mean PTA* of Jersey bulls entering AI by year (yield traits) YearMilkFatProteinNumber bulls ------------------(kg)----------------- 2005 8863181 2006 9484183 2007 90105216 2008 138137204 2009 168148209 2010 2401610209 2011 3132013236 2012 4002416236 2013 3932616264 *Based on April 2014 evaluations

11. Norman, 2014ICAR / Interbull annual meeting, Berlin, Germany, May 20, 2014 (11) Mean PTA* of Jersey bulls entering AI by year (other traits) YearSCS Prod. Life Dau. Preg. Rate Net Merit 2005 3.04 0.3-0.268 2006 3.05 0.4-0.196 2007 3.05 0.60.0120 2008 3.04 0.90.0158 2009 3.05 1.40.1201 2010 3.02 1.90.1243 2011 2.98 2.60.1329 2012 2.96 2.7-0.1376 2013 2.94 3.20.1436 *Based on April 2014 evaluations

12. Norman, 2014ICAR / Interbull annual meeting, Berlin, Germany, May 20, 2014 (12) Age of sire and dam at bull’s birth (all breeds)

13. Norman, 2014ICAR / Interbull annual meeting, Berlin, Germany, May 20, 2014 (13) Age of Paternal and Maternal grandsire at bull’s birth

14. Norman, 2014ICAR / Interbull annual meeting, Berlin, Germany, May 20, 2014 (14) Age of Paternal and Maternal granddam at bull’s birth

15. Norman, 2014ICAR / Interbull annual meeting, Berlin, Germany, May 20, 2014 (15) Mean PTA protein of HO service sires used in matings

16. Norman, 2014ICAR / Interbull annual meeting, Berlin, Germany, May 20, 2014 (16) Mean PTA Daughter pregnancy rate of service sires used in matings

17. Norman, 2014ICAR / Interbull annual meeting, Berlin, Germany, May 20, 2014 (17) Mean PTA Productive life of HO service sires used in matings

18. Norman, 2014ICAR / Interbull annual meeting, Berlin, Germany, May 20, 2014 (18) Mean Net Merit of HO service sires used in matings

19. Norman, 2014ICAR / Interbull annual meeting, Berlin, Germany, May 20, 2014 (19) Conclusions  Amount of genomic testing has been increasing. Still, it seems risky predicting how the number of tests will change in the next few years.  Bulls age when entering AI has not changed, remaining at 16 mo. All ancestors’ ages when the bull entered AI service have declined.

20. Norman, 2014ICAR / Interbull annual meeting, Berlin, Germany, May 20, 2014 (20) Conclusions  Genetic change for bulls entering AI has been accelerating for most of the important traits. A few of the fitness traits have increased faster than the yield traits.  Confirmed pregnancy from breeding records illustrates rapid improvement due to genomics will continue.

21. Norman, 2014ICAR / Interbull annual meeting, Berlin, Germany, May 20, 2014 (21)  Appreciation to all producers in the U.S. dairy industry and the industry support personnel who provided information to the Council on Dairy Cattle Breeding’s national database  Also, to personnel in the Animal Genomics and Improvement Laboratory who have assisted in the transition of operations to the Council on Dairy Cattle Breeding Acknowledgments