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Nuts and Bolts of Genetic Improvement Genetic Model Predicting Genetic Levels Increase Commercial Profitability Lauren Hyde Jackie Atkins Wade Shafer Fall.

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Presentation on theme: "Nuts and Bolts of Genetic Improvement Genetic Model Predicting Genetic Levels Increase Commercial Profitability Lauren Hyde Jackie Atkins Wade Shafer Fall."— Presentation transcript:

1 Nuts and Bolts of Genetic Improvement Genetic Model Predicting Genetic Levels Increase Commercial Profitability Lauren Hyde Jackie Atkins Wade Shafer Fall Focus, Gettysburg, PA Sept. 14 th, 2015

2 Punnett Square

3 Qualitative Traits Controlled by one or few pairs of genes Measured on a categorical (either-or) scale Examples – Black or red – Polled or horned – Genetic defects Genotype determined through DNA testing

4 Genetic defects?

5 Quantitative Traits Controlled by many genes Measured on a continuous scale Examples – Weaning weight (lb) – Ribeye area (sq in) Transmittable part of genotype determined through statistical techniques (and DNA testing) – EPD = ½ * EBV

6 Genetic Model Phenotype = Genotype + Environment Phenotype is the observed level of performance Genotype is the genetic makeup of the animal Environment is the effect that non-genetic factors have on performance

7 Genetic Predictions (EPDs) Separate genetics from environment – Nature vs nurture Estimated using highly advanced statistical methods – BLUP – System of linear equations – Solve for x and y if 2x + 3y = 6 and 4x + 9y = 15

8 Mixed Model Equations

9 Heritability Heritability - the proportion of phenotypic variation for a specific trait in a specific population that is due to transmissible genetic merit Ranges from 0 to 1 – h 2 CE = 0.19 – h 2 BW = 0.38 – h 2 REA = 0.46

10 Heritability The higher the heritability of a trait, the more accurately an individual’s own performance predicts genetic merit Even with high heritability we are limited in what we can learn about an animal’s true breeding value from its phenotype

11 Data Large amounts of performance data are the solution – Animal’s own performance – Progeny performance – Performance of ancestors and other relatives Progeny performance records are the most influential

12 Data Collection Accurate pedigree records Performance records for as many traits as possible on complete contemporary groups – Performance Advocate

13 Contemporary Group Same sex Close in age (within 90 days) Raised in same management group from birth – Same pasture – Same feed

14 Contemporary Group Should include as many cattle as can be compared accurately But only takes two

15 Contemporary Group Example Animal IDWeaning Weight (lb) 2142801 2134783 2135756 2147729 2139671

16 Contemporary Group Example Animal IDWeaning Weight (lb) 2142801 2134783 2135756 2147729 2139671 Average WW = 748 lb 2142’s WW ratio = 107.1

17 Contemporary Group Example Animal IDWeaning Weight (lb) 2142801 2134783 2135756 2147729 2139671

18 Contemporary Group Example Animal IDWeaning Weight (lb) 2142801 2134783 2135756 2147729 2139671 Average WW = 780 lb 2142’s WW ratio = 102.7

19 Contemporary Group Example Animal IDWeaning Weight (lb) 2142801 2134783 2135756 2147729 2139671

20 Contemporary Group Example Animal IDWeaning Weight (lb) 2142801 2134783 2135756 2147729 2139671 Average WW = 736 lb 2142’s WW ratio = 111.8

21 Contemporary Group Example What happens when 2142 starts getting used in other herds?

22 Contemporary Group Example Progeny data will get his EPDs going in the right direction Faulty data will get washed away BLUP is very robust

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24 Sire Summary

25 Interpretation 35R – BW EPD = -3.0 (.64) 3C Full Figures C288 BLK – BW EPD = -0.7 (.96) Difference – -3.0 – (-0.7) = -2.3 – We would expect 35R’s progeny to weigh -2.3 pounds less at birth on average than 3C Full Figures C288 BLK’s

26 Accuracy Measure of the strength of the relationship between the true breeding value and its prediction Range from 0 to 1 Affected by the number of progeny records Higher values associated with less risk and lower values with more

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