Lecture 2 The genetic Model for Quantitative Traits

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Animal Breeding and Genetics
Instructor Dr. Jihad Abdallah Genetic Parameters
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Components of Phenotypic variation

• The phenotype of an animal for a repeated
  quantitative 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

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• 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

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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

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

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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.

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• The h2 can 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).

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• Heritability is always positive ranging from 0 to
  1.0.
• Traits with low heritability (h2 lt 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 (h2gt 0.4)
• Carcass traits and traits related to skeletal
  dimensions like mature body weight
• Fat and protein in milk.

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• 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.

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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)

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• 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

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• 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).

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Repeatability

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

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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.

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Importance of repeatability

• It is useful in prediction of producing ability
  and therefore the animals next record from the
  current and previous records
• - If r is high, we can predict the animals
  next record more accurately
• - If r is low then the prediction of the
  next record has low accuracy.

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• 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.
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• 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

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• 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
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• 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.

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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