Course: Advanced Animal Breeding

1. Course: Advanced Animal Breeding MS program in Animal Production Faculty of Graduate Studies An-najah National University Instructor: Dr. Jihad Abdallah Genetic Model for Quantitative Traits And Genetic Parameters

2. The basic model • P = µ + G + E • P = phenotypic value of an animal for a given trait. • µ = population mean or average phenotypic value for the trait of all animals in the population. • G = the genotypic value of the animal for the trait. • E = the effect of the environmental factors on the phenotype of the animal. • G and E are expressed as deviations from the mean of the population. Therefore, the mean of G in the population and the mean of E is equal to zero.

3. Genotypic Value • Genotypic value is the overall effect of all the genes carried by the animal (singly and in combination) on the phenotype of the animal for the trait. • Unlike the phenotypic value, G is not directly measurable. • The genotypic value is the sum of two values: breeding value (BV or A) and Gene Combination Value (GCV). G = A + GCV = A + D + I

4. Breeding value • Breeding value (also called the additive genetic value) is the part of genotypic value that can be transmitted from parents to offspring. It is the sum of the average effects of individual genes • Breeding value is considered as a parental value (the value of an individual as a contributor of genes to the next generation). • Before we select animals to be parents of the next generation, we first estimate their breeding values and choose those with the best breeding values.

5. Example: assume that a trait is affected by 5 loci and the additive gene effects for the 10 alleles at the 5 loci are as given in the table. The breeding value is the sum of these effects.

6. An individual only transmits a sample composed of half of its genes to each of its offspring; this half is a random half of its genes. • Progeny difference (PD) or transmitting ability (TA) are used in practice by some countries to rank animals. • PD = TA = ½ A • Progeny difference and transmitting ability are practical concepts. These are defined as the expected difference between the mean performance of the progeny of a parent and the mean performance of the progeny of all the parents in the population: • PDi = TAi = µ offspring of parent i – µ offspring of all parents

7. Progeny difference and transmitting ability are not directly measurable but can be predicted using performance data. • The predicted value for PD is called EPD (expected progeny difference) • The predicted value for TA is called PTA (predicted transmitting ability). • Both terms mean the same thing but EPD is used in beef cattle, swine and sheep breeding while PTA is used in dairy cattle breeding.

8. The breeding value of an offspring can be viewed as the sum of the additive effects of the genes inherited from the sire (father) and the additive effects of the genes inherited from the dam (mother).

9. For example, if the estimated BV of a sire for weaning weight is + 2.5 kg and the estimated BV of the dam is + 1.5 kg, then the average expected BV of their offspring is equal to (2.5 + 1.5)/2= +2 kg. • That is, we expect the average of offspring of these sire and dam to be 2 kg heavier at weaning than the average of all offspring in the population. Therefore, if the population mean of weaning weight is 18 kg then the average phenotype of the offspring of these sire and dam is 18 + 2 = 20 kg.

10. Gene Combination Value (GCV) • GCV is the part of the genotypic value that is due to gene combination effects (dominance and epistasis). • Because individual genes and not gene combinations survive segregation and independent assortment during meiosis, GCV can not be transmitted from parent to offspring and therefore it is not important in selection.

11. The Model for Repeated Traits • Repeated trait: a trait for which the animal have more than one performance record during its lifetime (measured more than once on the same animal). • Examples: - milk production - wool production - litter size (number born)

12. For repeated traits, the environmental effects are divided into two types: • Permanent environmental effects (EP):the factors which permanently affect the performance of the animal (they influence all records of the same animal in the same way). Examples: - Nutrition at early stages of development affects the ability of beef and dairy cows to produce milk permanently. - A permanent problem in the udder will affect milk production during all productive life of the cow or ewe.

13. 2.Temporary environmental effects (ET):The environmental effects which do not affect performance permanently. Examples: - forage quality - weather conditions - and some management practices. • These factors vary from season to season or year to year and so they do not influence different records in the same way.

14. Producing Ability (PA) • Producing ability is the performance potential of an animal for a repeated trait (the ability of the animal to repeat its performance in future records). • Producing ability is a function of all permanent factors ( which permanently affect the performance potential of the animal) which include: • All genetic factors. • All permanent environmental factors.

15. PA = G + EPPA = A + D + I + EP • The average of PA is 0 across the population because it is expressed as a deviation from the mean. • The genetic model for repeated traits is: P = µ + A + D + I + EP + ET

16. Example: two records of 305-d milk production (in lbs) for two cows: PA for cow 1 = 1500 – 1000 + 2500 = 3000 lb PA for cow 2 = 1000 + 500 – 4500 = -3000 lb If we were to cull (discard) one of these cows we will cull cow 2.

17. Importance of producing ability • It is important to commercial producers as a measure of productive capacity. • Typically dairy farmers feed their cows according to their producing ability. • Therefore, prediction of PA is quite useful in practice. The predicted value of PA is called Most probable Producing Ability (MPPA). • P = µ + MPPA is a prediction of the animal’s next record.

18. Genetic Parameters

19. Components of Phenotypic variation • The phenotype of an animal for a repeatedquantitative trait can be modeled as: • P = µ + A + D + I + EP + ET • A = Additive genetic effect (breeding value) • D = Dominance effects • I = Epistasis effects • Ep= Permanent environmental effects • ET = Temporary environmental effects

20. 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

21. Heritability 1. 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.

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

23. 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.

24. 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.

25. Beef cattle h2 birth weight .35 weaning weight .30 weaning score .25 feedlot gain .45 carcass grade .40 fat thickness .33 rib eye area .58 marbling .42 retail product % .30 calving interval .08conception rate .05

26. Dairy cattle h2 milk yield .25fat yield .25 solids-not-fat yield .25 protein yield .25 fat % .50 solids-not-fat % .50 protein % .50 type score .30

27. Layers h2 • chick livability .05 adult livability .10 body depth .25 adult body weight .55 egg production .15 egg weight .55 fertility .05Broilers 7-week weight .45 feed consumption .70 feed conversion .35 breast fleshing .10 fat deposition .50

28. Sheep h2 90-day weight .25 postweaning gain .40 grease fleece wt .35 fiber diameter .40 staple length .55 fat thickness .30loin eye area .50ewe fertility .05prolificacy .10lamb survival .05carcass weight .35dressing % .10

29. 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.

30. 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)

31. Heritability is important in prediction of breeding values and producing ability. • Prediction of BV of animal i based on its phenotypic value, Pi ,is obtained as:

32. 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).

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

34. 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.

35. 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.

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

37. 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:

38. 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

39. 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.

40. 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