1. Milt Thomas, Department of Animal and Range Sciences Identification of Molecular Markers to Improve Fertility of Beef Cattle (USDA-NRI 200835205-18751)

2. Milt Thomas, Department of Animal and Range Sciences Outline I.Molecular markers and research - background. II.Fertility traits in beef cattle –background. III.Evolution of a fertility project. IV.Fertility project specifics. A. Team of scientists. B. Hypothesis and objectives (I and II). C. Populations. D. Additional efforts. V. Questions.

3. Milt Thomas, Department of Animal and Range Sciences Quantitative Trait Loci (QTL): chromosomal-locus associated with a quantitative trait. Genetic Marker: unique DNA sequence passed from parent to progeny (molecular alleles). Marker Assisted Selection (MAS): using genetic marker(s) in selection. Marker Assisted Management (MAM): using genetic markers for management decisions. bovineSNP50: a genotyping tool containing ~54,000 SNP across the bovine genome. gEPD: genetic marker information used in EPD estimation. Whole Genome Selection (WGS): using genetic markers across the genome in selection Linkage disequilibrium: non-random association of alleles at 2 or more loci. Molecular Markers – Background Important Definitions

4. Milt Thomas, Department of Animal and Range Sciences Research approach: QTL Detection Molecular Markers – Background Trait = pregnancy rate http://www.animalgenome.org/QTLdb/cattle.html

5. Milt Thomas, Department of Animal and Range Sciences DeAtley, K. L., G. Rincon, C. R. Farber, J. F. Medrano, R. M. Enns, G. A. Silver, and M. G. Thomas. 2008. Association of microsatellite ETH10 genotypes with growth and carcass trait levels in Brangus cattle. Proc. West. Sect. Am. Soc. Anim. Sci. 59:69-71. Research approach: Fine mapping/resequencing of genes under a QTL Molecular Markers – Background Eth10

6. Milt Thomas, Department of Animal and Range Sciences Research approach: identify important/functional markers Molecular Markers – Background Growth and carcass QTL on Chromosome 20. Growth hormone receptor gene underlies the QTL Resequenced ~1,000 bp flanking GT-SSR Discovered A/G tag SNP (ss86273136) segregating in Brangus Garrett, A.J., G. Rincon, J.F. Medrano, M.A. Elzo, G.A. Silver, and M.G. Thomas. 2008. Promoter region of the bovine growth hormone receptor gene: single nucleotide polymorphisms discovery in cattle and association with performance in Brangus bull. J. Anim. Sci. published ahead of print: doi:10.2527/jas.2008-0990.

7. Milt Thomas, Department of Animal and Range Sciences Research approach: association of genotype:phenotype Molecular Markers – Background Item Genotypes Pooled SEP > F AAAGGG n87283180 205-d weight, kg271.85267.44273.394.370.2114 365-d weight, kg510.34500.00499.146.070.1855 Test ADG, kg/d1.571.521.510.040.1558 Scrotal circumference, cm35.4235.1435.080.350.3525 Intramuscular fat, %3.563.553.640.060.1202 LM area/BW, cm 2 /kg0.17 0.0020.8178 LM area, cm 2 81.8181.2782.011.180.6062 Rib fat, cm0.62 0.660.0150.0204 Table 4. Least squares means among tag SNP ss86273136 genotypes in the GHR gene in Brangus bulls. +

8. Milt Thomas, Department of Animal and Range Sciences Validation: Molecular Markers – Background

9. Milt Thomas, Department of Animal and Range Sciences Age at puberty: number of Julian days from birth until puberty is achieved (h 2 ~0.4). Age at first calving: number of Julian days from birth until first parturition (~24 mo). Pregnant as a yearling: pregnant after yearling breeding season (h 2 ~0.2; yes or no). Calving interval: number of days between successive calvings. Stayability: probability a cow will remain in the herd until six years of age. Whole herd reporting: data inventory/recording system for each cow each year. Fertility traits – Background Important Definitions:

10. Milt Thomas, Department of Animal and Range Sciences Reproduction has been described as the most economically relevant component in beef production systems (Willham, 1973 and 1991; Melton, 1995). National survey results suggest opportunities exist to improve calf survivability and reproductive efficiency in many beef herds (Dargatz et al., 2004). Genetic improvement programs for reproductive traits have been much slower to develop than for growth and carcass traits due to the difficulty in developing whole-herd data collection systems and the time required to ample data (personal experience with IBBA). Genetic marker association studies involving fertility are limited as are the number of SNP within dbSNP that are within functional regions of genes (current research program). Fertility traits – Background Important Information:

11. Konni Shirley, Department of Animal and Range Sciences TraitCCCTTTχ2χ2 P- value First observed estrus61.836.41.830.00.01 Estrus at synchronization66.333.7 0 9.10.01 Pregnant during 1 st breeding season57.141.91.053.20.01 AI pregnancy66.733.3 0 3.30.07 Calved by 2 yr of age59.239.81.051.60.01 Percentages of IGF-I genotypes for categorical reproductive trait Evolution of a Fertility Project NBCEC Large Herd Managers Symposium, KC -2005 –Spring born Brangus (n = 190) heifers –Born 1997 to 2002 –Progeny of 14 Brangus sires

12. Milt Thomas, Department of Animal and Range Sciences Evolution of a Fertility Project NBCEC Large Herd Managers Symposium, KC -2005 Initial Results from Rex Ranch Project Relative NMSU Angus Heifers Herd Pregnancy Status Number of Heifers Genotypic Frequency, % CCCTTT 1non-pregnant1601549.435.6 1pregnant16619.241.639.2 3non-pregnant75204436 3pregnant852040 NMSU Pregnancy rate > 90%1101051.838.2

13. Milt Thomas, Department of Animal and Range Sciences Discussions at the Large Herd Managers helped form a team of scientist with many industry and ag-experiment cooperators. Identification of Molecular Markers to Improve Fertility of Beef Cattle; USDA-NRI 200835205-18751. Milt Thomas, PD, New Mexico State University, Reproductive Physiology Jim Reecy, Co-PD, Iowa State University, Molecular Genetics and Bioinformatics Rohan Fernando, Co-PD, Iowa State University, Quantitative Genetics (QTL) Bob Weaber, Supporting Scientist, University of Missouri, Quantitative Genetics John Pollak, Supporting Scientist, Cornell University, Quantitative Genetics Sunday Peters, Ph.D. student, New Mexico State University, Molecular Biology (Associate Professor, Department of Animal Breeding and Genetics, University of Agriculture, Abeokuta, Nigeria)

14. Milt Thomas, Department of Animal and Range Sciences Long-term goal: understand in molecular detail the genetic pathways regulating reproductive performance in beef cattle, with the intent of using this information to develop genetic improvement programs for fertility.

15. Milt Thomas, Department of Animal and Range Sciences Objective 1: Conduct a SNP-based whole-genome scan to identify QTL associated with heifer pregnancy rate. Objective 2: Develop data and DNA resources from large commercial beef operations to serve as test populations for validation and technology transfer created by achieving Objective 1 and other future candidate gene association efforts. Objectives Identification of Molecular Markers to Improve Fertility of Beef Cattle (USDA-NRI 200835205-18751)

16. Milt Thomas, Department of Animal and Range Sciences Objective 1: Conduct a SNP-based whole-genome scan to identify QTL associated with heifer pregnancy rate. Use Brangus cattle as admixed populations of livestock have proven useful in detecting QTL. Relationship fostered from efforts of IBBA –BIC.

17. Milt Thomas, Department of Animal and Range Sciences Population for Objective 1: Registered Brangus heifers from Camp Cooley Ranch 1.Brangus heifer pregnancy records collected since 1993. 2.DNA and phenotypes on >800 heifers from 54 sires born 2005, 2006, 2007. 3.Brangus generation, 4.5 ± 0.04 4.Trait, pregnant as a yearling, yes (80.6%) or no (19.4%). 5.Pregnancy success appears similar among heifers born in the fall vs. spring 6.Good success rate with AI. 7.Simple statistics for growth and carcass traits: Birth weight 77.2 ± 0.4 lbs 205-day weight532.2 ± 2.2 lbs 365-day weight799.0 ± 3.3 lbs Ribeye area 9.8 ± 0.05 in 2 Fat thickness 0.24 ± 0.002 in intramuscular fat % 4.24 ± 0.032 %

18. Milt Thomas, Department of Animal and Range Sciences Lab work and Statistical Analyses for Objective 1. 1.DNA extraction of WBC-buffy coat at NMSU. 2.bovineSNP50 genotyping (54,000 SNP across the genome). 3.QTL detection at ISU using a Bayesian approach (Meuwissen et al., 2001 and XU, 2003). 4.QTL visualization: QTLdb Trait = pregnancy rate http://www.animalgenome.org/QTLdb/cattle.html

19. Milt Thomas, Department of Animal and Range Sciences Objective 2: Develop data and DNA resources from large commercial beef operations to serve as test populations for validation and technology transfer created by achieving Objective 1 and other future candidate gene association efforts. Note: failure of the 1 st -calf heifer to rebreed has been considered to be one of the largest economic drains on the beef industry (Clark et al., 2005). 1.Varied production systems and environments which represent the beef industry in the U.S. 2.Obtain resources that could grow into additional trait evaluations (1 st calf heifer rebreeding, stayability, etc.)

20. Milt Thomas, Department of Animal and Range Sciences Locations of Cooperators (numbers 1-19) and Research Scientists (letters A-D) Working to Study: Identification of Molecular Markers to Improve Fertility in Beef Cattle 1 23 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 A B C D

21. Milt Thomas, Department of Animal and Range Sciences Additional Efforts 1.Whole genome breeding value estimates (collaboration with Dorian Garrick, ISU). 2. Transcriptome sequencing of important tissues (i.e., hypothalamus-NCGR) and evaluate bovineSNP50 QTL-SNP relative gene expression loci.

22. Milt Thomas, Department of Animal and Range Sciences Identification of Molecular Markers to Improve Fertility of Beef Cattle (USDA-NRI 200835205-18751) 1.Conclusions 2.Acknowledgements 3.Questions/Discussion