SELECTION FOR IMPROVED FEED EFFICIENCY: A GENOMICS APPROACH. Matt Spangler, Ph.D. University of Nebraska-Lincoln

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1 SELECTION FOR IMPROVED FEED EFFICIENCY: A GENOMICS APPROACH Matt Spangler, Ph.D. University of Nebraska-Lincoln

2 Where We Rank (F:G) 2:1 1:1 6:1 3:1

3 Fundamental Principles P = G + E Feed Intake = Expected Intake + Residual Intake Profit = Revenue - Expense Efficiency = Output/Input or visa versa Inherent multiple-trait selection

4 WW Selection Success 4 Mean WW EPD Across Breed EPD Genetic Trends-WEANING WEIGHT All Breeds Presented on ANGUS EPD Base AN AR HH CH GV LM MA SM Weaber and Fennewald, 2009

5 YW Selection Success 5 Mean YW EPD Across Breed EPD Genetic Trends- YEARLING WEIGHT All Breeds Presented on ANGUS EPD Base AN AR HH CH GV LM MA SM Weaber and Fennewald, 2009

6 Adoption of Genomic Predictions AAA, with others quickly following Efficacy of this technology is not binary The adoption of this must be centered on the gain in EPD accuracy This is related to the proportion of genetic variation explained by a MBV This is equal to the squared genetic correlation

7 Current Angus Panels Trait Igenity (384SNP) Pfizer (50KSNP) Calving Ease Direct Birth Weight Weaning Weight Yearling Weight Dry Matter Intake Yearling Height Yearling Scrotal Docility Milk Mature Weight Mature Height Carcass Weight Carcass Marbling Carcass Rib Carcass Fat

8 Hereford-based Predictions Trait rg from NBCEC BW 0.43 WW 0.32 YW 0.30 MILK 0.22 CED 0.43 CEM 0.18 FAT 0.40 MARB 0.27 REA 0.36 SCROTAL 0.28

9 Integrated Information EPD (index or interim) MA- EPD MBV (correlated indicator trait)

10 Increased Accuracy-Benefits Mitigation of risk Faster genetic progress BV / t = r BV, EBV L Increased accuracy does not mean higher or lower EPDs! Increased information can make EPDs go up or down i σ BV

11 Impact on Accuracy--%GV=10%

12 Impact on Accuracy--%GV=40%

13 New Traits In the Genomic Era Healthfulness of beef Disease susceptibility Tenderness Adaptation FEED INTAKE AND EFFICIENCY The list will continue to grow INFORMATION OVERLOAD!

14 Measuring feed efficiency Dahlke et al (

15 What Role Does Genetics Play? ADG DMI RFI G:F ADG DMI RFI G:F 0.27

16 EPD for Efficiency and Input do Exist Residual Gain Days to Finish Maternally oriented ME $W

17 Index Based Selection Rolfe et al. (2011)

18 Most Desirable Index? Phenotypic RFI Genetic RFI Economic index of DMI and GAIN Economic index of RFI and Gain

19 Why a Genomic Approach? The components of FE are heritable The input side is expensive to measure FI can be more expensive than HD genotypes Not feasible for routine phenotypes to enter NCE Phenotypes are still need for discovery and validation Here training is on adjusted phenotypes because no EPD exist

20 Types of Discovery Populations Purebreds of a Single Breed Purebreds of Multiple Breeds Crossbreds

21 2,000 Bull Project: Number of Sires Sampled Angus 402 Brangus 68 Hereford 317 Beefmaster 64 Simmental 253 Maine-Anjou 59 Red Angus 173 Brahman 53 Gelbvieh 136 Chiangus 47 Limousin 131 Santa Gertrudis 43 Charolais 125 Salers 42 Shorthorn 86 Braunvieh 27 Total = Used In Training

22 Why didn t we start with these traits? Phenotypes do not exist or are very sparse Discovery Target Validation

23 Example of Robustness--Breed Breed WW YW AN 0.36 (0.07) 0.51 (0.07) AR 0.16 (0.16) 0.08 (0.18)

24 Solutions SNP panel density (770K instead of 50K) Composition of the training population Statistical methodology

25 Summary We need to think about efficiency in terms of economic returns Index values will require both inputs (FI) and outputs (WT) along with body composition Genomics could play a large role here Not fully brought to fruition A genomics approach is robust to the definition of efficiency

26 Summary Phenotypes are still critical to collect Genomic information has the potential to increase accuracy Proportional to %GV Impacts inversely related to EPD accuracy Multiple trait selection is critical and could become more cumbersome Economic indexes help alleviate this Use index values that meet your breeding objective

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28 STAY INFORMED USDA Beef Feed Efficiency Project National Beef Cattle Evaluation Consortium