Animal Breeding and Genetics

1. Animal Breeding and Genetics Instructor: Dr. Jihad Abdallah Genetic Parameters

2. Components of Phenotypic variation • The phenotype of an animal for a repeatedquantitative trait can be modeled as: P = µ + GA + GD +GI + Ep + Et • GA= Additive genetic effect (breeding value) • GD = Dominance effects • GI = Epistasis effects • Ep= Permanent environmental effects • Et = Temporary environmental effects

3. Based on this model, the phenotypic variance can be decomposed (ignoring covariances) into: VP = VA + VD + VI + VEp + VEt VP = phenotypic variance VA = additive genetic variance VD = variance due to dominance effects VI= variance due to effects of epistasis VEp = variance due to permanent environmental effects VEt = variance due to temporary environmental effects

4. Heritability • Heritability in the broad sense (H2): is the proportion of the phenotypic variance that is due to genetic effects including additive, dominance and epistasis: • It measures the strength of the relationship between the phenotypic values for a trait and the genotypic values. It can be viewed as the squared correlation between the phenotypic values and the genotypic values:

5. Heritability in the narrow sense (h2): is the proportion of the phenotypic variance that is due to additive genetic effects only.

6. What does the heritability in the narrow sense measure? • The strength of the relationship between the phenotypic values and the breeding values for a trait in the population. Therefore, it can be viewed as the coefficient of regression of the breeding value on the phenotypic value. • It measures the degree to which the offspring resemble their parents in performance for a trait. If a trait has a large heritability, animals with high performance for the trait will produce offspring with high performance. If a trait has a small heritability, performance records of parents reveal little information about the performance of their offspring.

7. The h2can be estimated from the regression of the phenotype of the offspring (one offspring or the mean of all offspring) on the phenotype of one parent or on the midparent value (mean phenotype of both parents). • If we use midparent value, then h2= regression coefficient • if we use the phenotype of one parent then h2= 2 (regression coefficient).

9. Heritability is always positive ranging from 0 to 1.0. • Traits with low heritability (h2 < 0.20): • reproductive traits like days open calving interval, litter size, and conception rate • longevity or productive live ( about 0.10) • weaning weight in swine ( about 0.10) • Moderately heritable traits (h2 of 0.2 to 0.4): • Milk yield, fat yield and protein yield (0.25-0.35) • Birth weight in sheep • Yearling weight in sheep • Highly heritable traits (h2> 0.4): • Carcass traits and traits related to skeletal dimensions like mature body weight • Fat and protein% in milk.

10. Notes on heritability: • Heritability is a population measure not a value associated with a single individual. • Heritability of a trait varies from one population to another and from environment to another.

11. Importance of heritability • Heritability is important in selection: The accuracy of selection is higher for a highly heritable trait than a low heritable trait. The larger the accuracy of selection, the larger is the expected response due to selection. With selection based on phenotypic values: • Large h2high accuracy of selection (phenotypic value is a good indicator of breeding value) • Small h2low accuracy of selection (phenotypic value is not a good indicator of breeding value)

12. Heritability is important in prediction of breeding values, predicted differences, and producing abilities. • Prediction of BV of animal i based on phenotypic value, Pi is obtained as:

13. Heritability is important in management: - Large h2genetic factors have important role as in growth traits (performance can be improved by selection). - Small h2environmental factors are important as in reproductive traits (selection is less effective and performance is improved mainly by improving the environmental effects such as improving nutrition and management practices).

14. Repeatability • Repeatability (r) is the proportion of the phenotypic variance that is due to permanent effects (genetic effects and permanent environmental effects):

15. What does the repeatability measure? • The strength of the relationship between repeated records. Therefore, repeatability can be estimated as the correlation between repeated records on the same animals. • The strength of the relationship between single performance records and producing ability (permanent effects). Therefore, repeatability can be viewed as the regression of PA on the phenotype.

16. Importance of repeatability • It is useful in prediction of producing ability and therefore the animal’s next record from the current and previous records: - If ris high, we can predict the animal’s next record more accurately - If r is low then the prediction of the next record has low accuracy.

17. To predict the producing ability (most probable producing ability) from n previous records: is the average of the n records of the animal i is the mean for all animals.

18. Example: suppose a cow has three milk records: 4000kg in the first record, 5000 kg in the second, and 6000 kg in the third. Suppose also that the mean of all cows is 4600 kg and the repeatability of milk yield is 0.60, then the predicted producing ability of this cow is:

19. Repeatability is important in prediction of breeding values from multiple records on the same animals: For the previous example if heritability of milk yield in this population is 0.25 then

20. Repeatability is important in making culling decisions: When r is high we can cull animals of poor performance on the basis of the first record When r is low one should wait for more records before making a culling decision on the animal.

21. Examples of Repeatability Estimates • Beef cattle: - Calving date (trait of the dam): 0.35 - Birth weight (trait of the dam): 0.20 - Weaning weight (trait of the dam): 0.40 - Body measurements: 0.80 • Dairy cattle: - Services per conception: 0.15 - Calving interval: 0.15 - Milk yield: 0.50 - % Fat: 0.60 - Teat placement: 0.55 • Poultry: - Egg weight: 0.90 - Egg shape: 0.95 - Shell thickness: 0.65 • Sheep: - Number born: 0.15 - Birth weight (trait of the dam): 0.35 - 60-day weaning weight (trait of the dam): 0.25 - Fleece grade: 0.60