USING GENOMICS TO AFFECT COW HERD REPRODUCTION. Matt Spangler University of Nebraska-Lincoln

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1 USING GENOMICS TO AFFECT COW HERD REPRODUCTION Matt Spangler University of Nebraska-Lincoln

2 Relative Economic Weights for Traditional Beef Firm Reproduction:Growth:End Product 10:5:1 (Melton, 1995)

3 Improvement of Herd Efficiency [Dam Weight*Lean Value of Dam + No. Progeny*Progeny Weight*Lean Value of Progeny] - [Dam Feed*Value of Feed for Dam + No. Progeny*Progeny Feed*Value of Feed for Progeny]. By simply increasing number of progeny per dam through either selection, heterosis from crossing, or better management, we will increase efficiency of production. Adapted from Dickerson 1970

4 Advantages of the crossbred cow Trait Observed Improvement Adapted from Cundiff and Gregory, % Heterosis Longevity Cow Lifetime Production: No. Calves Cumulative Wean. Wt., lb

5 March 1, 2010 Beef Magazine Survey

6 Genomic Technology Adoption in Beef Industry

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

8 Accuracy

9 Impact on Accuracy--%GV=40% BIF Accuracy of < 0.3

10 Impact on Accuracy--%GV=10%

11 If breeds are contained in training, predictions work well If not, correlations decrease Across Breed Predictions for REA AN 0.43 (0.07) SM 0.34 (0.09) HH 0.33 (0.08) GV 0.17 (0.11) Pooled Training (AN, SM, HH, LM)

12 Breed Specificity (Kachman et al., 2013)

13 Trait Country 2 Scrotal circumference Days to calving Heifer pregnancy Heifer calving success Age at 1 st calving Calving interval Stayability/productive life AU, NZ, SA, NA, AR, UK, IR, BR, FR, US, CA, ME AU, NZ, SA, NA US, VE, BR FR IR, UK, BR IR, DE, UK US, CA, VE, UK, FR, BR Adapted from Johnston (2014).

14 What Is a Selection Index? Selection on aggregate merit (Hazel, 1943) List of traits that influence satisfaction Relative Economic Value (REV) of each trait Increase in satisfaction with one unit change in a trait, all others held constant List of characteristics to be measured on animal Relationships between characteristics (phenotypes) and traits (genotypes) H a BV a BV a BV i 1 i1 2 i2 n in

15 Why Do We Need Selection Indexes? There is no easily accessible, objective way for breeders, particularly breeders in the beef and sheep industries where ownership is diverse and production environments vary a great deal, to use these predictions intelligently. -- R. M. Bourdon, 1998

16 Terminal or Maternal? Terminal $B, $F, $G (Angus) TI (Simmental) CHB$ (Hereford) MTI (Limousin) EPI and FPI (Gelbvieh) Charolais GridMaster (Red Angus) Maternal $W, $EN (Angus) API (Simmental) BMI$, BII$, CEZ$ (Hereford) HerdBuilder (Red Angus) $Cow (Gelbvieh)

17 Improving Indices Improvement in current indices can be made by increasing the number of ERT that have EPD Input traits Fertility

18 Selection Efficiency Pathways of Selection Genetic gain in population driven by intensity and accuracy of selection of parents and generation interval The FOUR paths: Sires of Sires (Paternal Grand Sires) Dams of Sires (Paternal Grand Dams) Sires of Dams (Maternal Grand Sires) Dams of Dams (Maternal Grand Dams) Which are the longest generation interval? Highest intensity? Lowest Accuracy?

19 Paths of Selection X S D PGS PGD MGS MGD

20 Genomic Impact on Selection Efficiency and Rate Scenario 1: Traditional Selection Using EPD Path Selection % Intensity BIF Acc Acc (rti) Gen. Int (L) i * rti Sires of Bulls Dams of Bulls Sires of Cows Dams of Cows Genetic Gain (sd units) 0.14 Totals Scenario 2: Selection Using Genomically Enhanced EPD Path Selection % Intensity BIF Acc Acc (rti) Gen. Int (L) i * rti Sires of Bulls Dams of Bulls Sires of Cows Dams of Cows Genetic Gain (sd units) 0.22 Totals Rate Improvement 56%

21 Reduced Genetic Risk Through Use of GE-EPDs Production Accuracy CED BW WW YW Doc Reduction in PC % 0.05 => % 16% 15% 16% 16% 0.05 => % 37% 36% 37% 36% Maternal Carcass Accuracy HP CEM Milk MW CW Marb RE Fat Reduction in PC % 0.05 => % 16% 15% 15% 17% 14% 16% 15% 0.05 => % 38% 37% 36% 33% 36% 39% 37%

22 What makes a heifer? What makes her SUCCESSFULL? Environmental Effects? Age at breeding When were they born in calving distribution Body condition score at calving and breeding Genetic Effects Heritability of traits important to maternal performance? LOW.1-.2 Heterosis (value ~$250/cow/year)

23 2017 Longevity in herd based on calving date as heifer Years in herd SDSU MARC 1st 21 d 2nd 21 d later Time of first calving Cushman et al., 2013

24 Heifer Selection: Making testing PAY! Assume you test 80% of your heifer calves as potential replacements and have a 20% replacement rate. How much does each retained heifer have to return to cover all testing costs? You retain ¼ of candidates so each retained heifer has to return 4X test cost to break even. $40 test => $160 value capture to be par money (Igenity test $25-40; Genemax Advantage $44)

25 Bull selection makes the difference Genetic progress is gene flow from bull selection (80% over time) Use DNA parentage to preferentially select daughters of specific sires: Maternal focus AI calves (simplify subsequent breedings) DNA parentage/paternity assignment is low cost ($13-15/test)

26 The Question Changes For MAM, the question revolves around the proportion of phenotypic variation explained. Upward bound is h 2 For example, for a fertility trait the best a genomic test could do is explain 10% of the phenotypic differences between animals. To do the above, it would have to explain 100% of the genetic differences between animals. Our predictions are not that good!

27 Tests Do Exist Tests exist in the market place for use in commercial purebred and crossbred animals (GeneSeek and Zoetis) Some are designed for purebred commercial animals The relatedness question is less of an issue Others are designed for use across breeds and in crossbreds No independent evaluation results exit for these

28 Alternate Approach Knowing the sire of an animal is actually very informative 25% of the additive genetic merit of an animal For a trait with a h 2 = 0.40 this equates to 10% of the phenotypic differences

29 Validation of Variants Created a small panel of severe variants screened for Birth Weight in the Cycle VII population. Genotyped > 600 sires from the Rex Ranch for this panel of 185 variants. Correlation Variant panel Rex Ranch (BW).63

30 Sequencing Is Just Beginning New GGPF250 assay Best chance we have at Predicting across populations Birth weight MBV based on 293 variants-- r g ranged between Single variant (birth weight) r g ranged between 0.17 and 0.34 Developing MAM products An objective, but the highest hanging fruit GxExM

31 Action Point #1 The commercial cow-calf industry needs to utilize composite or F 1 females. The majority of commercial producers should breed these to an unrelated terminal sire breed. Larger commercial producers may take advantage of scale and serve as a multiplier, focusing on the production of commercial replacement females.

32 Action Point #2 Commercial bull buyers should utilize the currently available reproductive EPDs previously detailed in this paper. Buying bulls with GE-EPD will add accuracy to bull buying decisions.

33 Action Point #3 The effective use of economic selection indices in the development of maternal and terminal selection lines.

34 Understanding of Genomic Selection The single thing that has stood out to me the most in the genomic selection era is that the majority of beef producers never understood EPD and accuracy to begin with. At some point this will manifest itself and I fear we run the risk of messing up the end game.

35 Take aways Genomic tools work and have growing application in seedstock sector Value of trait tests not well proven in commercial herds, management and environment bigger factors in heifer success Parentage/paternity assignment is low cost/valuable Best way for commercial producer to use genomics is buy bulls with genomically enhanced EPDs.

36 Helpful Resources