1. 2007 Paul VanRaden, George Wiggans, Jeff O’Connell, John Cole, Animal Improvement Programs Laboratory Tad Sonstegard, and Curt Van Tassell Bovine Functional Genomics Laboratory USDA Agricultural Research Service, Beltsville, MD, USA Paul.VanRaden@ars.usda.gov Paul.VanRaden@ars.usda.gov 2009 Distribution and Location of Genetic Effects for Dairy Traits

2. Genex emerging markets conference, March 2009 (2)John B. Cole 2009 Questions of Interest  What model best fits our data?  Have we found any genes of large effect?  Can we use marker effects to locate autosomal recessives?  How do we handle the X chromosome?  How can we use marker effects to make better breeding decisions?

3. Genex emerging markets conference, March 2009 (3)John B. Cole 2009 Experimental Design  Predict April 2008 daughter deviations from August 2003 PTA Similar to Interbull trend test 3 3576 older Holstein bulls 1759 younger bulls (total = 5335)‏  Results computed for 27 traits: 5 yield, 5 health, 16 conformation, and Net Merit (NM$)‏

4. Genex emerging markets conference, March 2009 (4)John B. Cole 2009 Linear and Nonlinear Predictions  Linear model Infinitesimal alleles model in which all loci have non-zero effects  Nonlinear models Model A: infinitesimal alleles with a heavy-tailed prior Model B: finite locus model with normally-distributed marker effects Model AB: finite locus model with a heavy-tailed prior

5. Genex emerging markets conference, March 2009 (5)John B. Cole 2009 Regressions for marker allele effects

6. Genex emerging markets conference, March 2009 (6)John B. Cole 2009 R-square values comparing linear to nonlinear genomic predictions Model TraitLinearABAB Net Merit28.228.427.6 Milk47.248.546.747.3 Fat41.844.241.543.6 Protein47.547.046.846.6 Fat %55.363.357.563.9 Protein %51.457.751.456.6 Longevity25.627.425.426.4 Somatic cell37.338.337.337.6

7. Genex emerging markets conference, March 2009 (7)John B. Cole 2009 Largest Effects  Fat %: largest effect on BTA 14 flanking the DGAT1 gene, with lesser effects on milk and fat yield  Protein %: large effects on BTA 6 flanking the ABCG2 gene  Net Merit: a marker on BTA 18 had the largest effect on NM$, in a region previously identified as having a large effect on fertility

8. Genex emerging markets conference, March 2009 (8)John B. Cole 2009 Distribution of Marker Effects (Net Merit)

9. Genex emerging markets conference, March 2009 (9)John B. Cole 2009 Distribution of Marker Effects (DPR)

10. Genex emerging markets conference, March 2009 (10)John B. Cole 2009 Dystocia Complex  Markers on BTA 18 had the largest effects for several traits: Dystocia and stillbirth: Sire and daughter calving ease and sire stillbirth Conformation: rump width, stature, strength, and body depth Efficiency: longevity and net merit  Large calves contribute to shorter PL and decreased NM$

11. Genex emerging markets conference, March 2009 (11)John B. Cole 2009 Marker Effects for Dystocia Complex

12. Genex emerging markets conference, March 2009 (12)John B. Cole 2009 Biology of the Dystocia Complex  The key marker is ss86324977 at 57,125,868 Mb on BTA 18  Located in a cluster of CD33- related Siglec genes Many Siglecs are involved in the leptin signaling system  Preliminary results also indicate an effect on gestation length

13. Genex emerging markets conference, March 2009 (13)John B. Cole 2009 Locating Causative Mutations  Genomics may allow for faster identification of causative mutations  Identifies SNP in strong linkage disequilibrium with recessive loci  Tested using BLAD, CVM, and RED  Only a few dozen genotyped carriers are needed

14. Genex emerging markets conference, March 2009 (14)John B. Cole 2009 Marker Effects for Autosomal Recessives

15. Genex emerging markets conference, March 2009 (15)John B. Cole 2009 SNP on X Chromosome  Each animal has two evaluations Expected genetic merit of daughters Expected genetic merit of sons Difference is sum of effects on X SD = 0.1 σ G, smaller than expected  Correlation with sire’s daughter vs. son PTA difference was significant (P < 0.0001), regression close to 1.0

16. Genex emerging markets conference, March 2009 (16)John B. Cole 2009 X, Y, Pseudo-autosomal SNP 487 SNP 35 SNP 0 SNP 35 SNP

17. Genex emerging markets conference, March 2009 (17)John B. Cole 2009 Chromosomal EBV  Sum of marker effects for individual chromosomes Individual chromosomal EBV sum to an animal’s genomic EBV  Chromosomal EBV are normally distributed in the absence of QTL  QTL can change the mean and SD of chromosomal EBV

18. Genex emerging markets conference, March 2009 (18)John B. Cole 2009 Distribution of Chromosomal EBV fat percent on BTA 14 (DGAT)

19. Genex emerging markets conference, March 2009 (19)John B. Cole 2009 Distribution of Chromosomal EBV sire calving ease on BTA 14 (no QTL)

20. Genex emerging markets conference, March 2009 (20)John B. Cole 2009 Positive or Negative Traits

21. Genex emerging markets conference, March 2009 (21)John B. Cole 2009 Net Merit by Chromosome Freddie - highest Net Merit bull

22. Genex emerging markets conference, March 2009 (22)John B. Cole 2009 Net Merit by Chromosome O Man – Sire of Freddie

23. Genex emerging markets conference, March 2009 (23)John B. Cole 2009 Net Merit by Chromosome Die-Hard - maternal grandsire

24. Genex emerging markets conference, March 2009 (24)John B. Cole 2009 Net Merit by Chromosome Planet – high Net Merit bull

25. Genex emerging markets conference, March 2009 (25)John B. Cole 2009 Conclusions  A heavy-tailed model fits the data better than linear or finite loci models  Markers on BTA 18 had large effects on net merit, longevity, calving traits, and conformation  Marker effects may be useful for locating causative mutations for recessive alleles  Results validate quantitative genetic theory, notably the infinitessimal model

26. Genex emerging markets conference, March 2009 (26)John B. Cole 2009 Acknowledgments  Genotyping and DNA extraction: USDA Bovine Functional Genomics Lab, U. Missouri, U. Alberta, GeneSeek, Genetics & IVF Institute, Genetic Visions, and Illumina  Computing: AIPL staff (Mel Tooker, Leigh Walton, Jay Megonigal)  Funding: National Research Initiative grants – 2006-35205-16888, 2006-35205-16701 Agriculture Research Service Holstein and Jersey breed associations Contributors to Cooperative Dairy DNA Repository (CDDR)