Estimating Breeding Value

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Estimating Breeding Value
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Breeding Value (BV)

• Genetic merit of an animal for a given trait.
• Often expressed as a deviation from herd or group
  average.

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Breeding Value (BV)

• In real life we observe the phenotype but want to
  estimate the breeding value (or its genetic
  additive effect)

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Breeding Value (BV)

• We observed that the phenotype of a given animal
  is 630 lbs at Weaning
• But what is its breeding value (i.e. values of
  its genes to its offspring)?

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Some DefinitionsPredicting Genetic Gain

• Breeding Value (BV) The value of an animal as a
  (genetic) parent.
• Breeding Value The part of an individual
  genotypic value that is due to additive effect
  and therefore transmittable. (Breed true)
• Independent Gene Effect The effect of an allele
  is independent of the effect of the other allele
  at the same locus (dominance) and the effects of
  alleles at other loci (epistasis). ADDITIVE
  EFFECT.
• Estimated Breeding Value (EBV) An estimation of
  a breeding Value.

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Some DefinitionsPredicting Genetic Gain

• Independent Gene Effect The effect of an allele
  is independent of the effect of the other allele
  at the same locus (dominance) and the effects of
  alleles at other loci (epistasis). ADDITIVE
  EFFECT.
• Estimated Breeding Value (EBV) An estimation of
  a breeding Value.
• Additive Genetic Value Breeding Value.
• Breed True" (i.e., average offspring performance
  closely approximates average parent performance
  assuming constant environment)

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Genotypic Value is not the same as Breeding
Value

• Genotypic Value of an animal is the value of its
  genes on itself and includes Additive, Dominant
  and Epistatic Effects.
• Breeding Value is the value of its genes on the
  progeny and is related to the Additive Effects
  (Breed True and narrow sense heritability)

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Progeny Differences

• Progeny Difference (PD) or Transmitting Ability
  (TA) Half of an individuals breeding value. The
  expected difference of the individuals progeny
  and the mean performance of all progenies.
• Expected Progeny Difference (EPD) or Predicted
  Transmitting Ability (PTA) A prediction of a
  progeny difference.

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Expected Progeny Difference (EPD) or Predicted
Transmitting Ability (PTA) The expected
difference of the individuals progeny and the
mean performance of all progenies.

• Its called prediction because its an estimation
  of the future performance of the animals
  offspring in relation to all progenies

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EPD or PTA Half of an individuals breeding
value (BV).

• A parent passes 1/2 of its BV to an offspring.
• The other half comes from the other parent
• On phenotypic selection the gain is determined by
  selection differential averaged for males and
  females

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Estimated Breeding Value (EBV)

• Actual BV is unknown for most traits.
• We can estimate BV of an animal based on
  performance of the animal itself and its
  relatives.
• Similar to EPD, PTA, etc.

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Estimating Breeding Value

• Within Herd Contemporary Group
• Breeding Value Estimation

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• Animal of Interest
• Animal whose BV is being estimated.
• Animal(s) of Record
• Animal(s) being evaluated or measured. Can be the
  animal of interest and(or) relatives.

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Predicting Breeding Value

• Phenotypic deviation from a contemporary mean!!
• Population mean
• Herd or flock mean
• Mean of animal born in same management group
• Its a way to correct for non- genetic effects

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Predicting Breeding Value Within Herd Genetic
Evaluation
Standardization of Performance Records (WW205,
YW365, SC365, REA480) Adjustments (Age of the
Cow, Age at weight data collection)
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Predicting Breeding Value Within Herd Genetic
Evaluation
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Predicting Breeding Value Within Herd Genetic
Evaluation
Table Birth weight adjustment factor for
age of the dam.
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Predicting Breeding Value Within Herd Genetic
Evaluation
Example 1 Rank animals based on BW, WW205 and
YW365
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Predicting Breeding Value Within Herd Genetic
Evaluation
Example 1 Rank animals based on BW, WW205 and
YW365
Rank for Males FgtHgtBgtE Rank for Females
CgtGgtAgtD
Rank for BW
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Predicting Breeding Value Within Herd Genetic
Evaluation
Example 1 Rank animals based on BW, WW205 and
YW365
Rank for Males FgtHgtBgtE Rank for Females
CgtGgtAgtD
Rank for Males EgtFgtBgtH Rank for Females
AgtDgtGgtC
Rank for WW205
Rank for BW
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Predicting Breeding Value Within Herd Genetic
Evaluation
Example 1 Rank animals based on BW, WW205 and
YW365
Rank for Males FgtHgtBgtE Rank for Females
CgtGgtAgtD
Rank for Males EgtFgtBgtH Rank for Females
AgtGgtCgtD
Rank for Males EgtFgtBgtH Rank for Females
AgtDgtGgtC
Rank for WW205
Rank for YW365
Rank for BW
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Breeding Value (BV)

• The contribution of each effect is proportional
  to the variance explained by effect

• Concepts discussed on Phenotypic Selection still
  valid!!

Additive Effect Dominance
Environment or Breeding Value
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Estimated Breeding Value (EBV)

• Notice that the Breeding Value of an animal is
  the sum of its genes Additive Effects

• Concepts discussed on Phenotypic Selection still
  valid!!

Additive Effect Breeding Value
Genetic Gain When estimated from Phenotypes
Phenot. Selection Phenotype expressed as a
deviation from the mean
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General Formulas for BV and ACC

• P trait mean of the animal(s) of record.
• trait mean of contemporary group.
• b regression factor.
• Phenotype expressed as a deviation from the mean

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Estimated Breeding ValuexExpected Progeny
Difference

• EPD PTA 1/2 EBV the portion of an animals
  BV that is expected to be passed on to its
  progeny for a given trait.

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Estimated Breeding ValuexExpected Progeny
Difference
What is the expected average Phenotype on the
progeny (change on the distribution mean)
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Accuracy (ACC) of EBV

• Mathematical expression of the degree of
  confidence that the EBV accurately predicts true
  BV.
• Ranges between 0 and 1.

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General Formulas for EBV and ACC

• g relationship weighting factor.
• b regression factor.

Correlation between real breeding value and
estimated breeding value i.e. the closest the
estimation to real BV more accurate is the EBV
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ACCURACYExpected Variation on Progeny Difference
What is the expected average Phenotype on the
progeny for high and low accuracy EPDs (change on
the distribution mean)
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Predicting Breeding Value Across-Herd Genetic
Evaluation
Allows comparisons of breeding value estimates of
animals in different herds or contemporary groups.
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Predicting Progeny Performance

• EBV estimated breeding value (all species).
• EPD expected progeny difference (beef, swine,
  and sheep).
• PTA predicted transmitting ability (dairy).

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To compare animals from different herds

• Must account for between-herd differences in
• 1) environment
• 2) overall herd genetic potential (genetic
  potential of mates)
• Variation on mean contemporary group may be due
  environmental and genetic differences
• Question How to differentiate Environmental and
  Genetic effects on different CG?

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To compare animals from different herds

• Must account for between-herd differences in
• 1) environment
• 2) overall herd genetic potential(genetic
  potential of mates)

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To compare animals from different herds

• Must account for between-herd differences in
• 1) environment
• 2) overall herd genetic potential(genetic
  potential of mates)
• 1) is accounted for by using sires in multiple
  herds simultaneously. See next slide.
• 2) relates to the fact that a sire used in a good
  herd will look better than when used in a bad
  herd because of the females hes being mated to.
  Current statistical procedure account for this
  since all available records are used.

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Reference sire concept

• Because of AI, a sire can produce progeny in
  multiple herds simultaneously.
• Such sires serve as a base or reference point in
  order to adjust for differences in E.

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Across-Herd Genetic Evaluation

• Originally, genetic evaluation programs were
  based on within-herd comparisons only.
• Increased use of A.I. And more sophisticated
  computer programs allowed expansion to
  across-herd evaluation.
• Across-herd genetic evaluation programs are
  usually done separately by breed.

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Reference sire concept

• Originally, in beef cattle, each breed with an
  across-herd evaluation program designated
  specific sires as reference sires. In order to
  have across-herd EPDs for animals in your herd,
  some of your calves had to be sired by reference
  sires.
• At that time, EPDs were calculated only for
  sires. Now they can be calculated for virtually
  every animal in the breed as long as the
  necessary trait data is available.

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Reference Sire concept
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Reference Sire concept
Bull A is siring calves in both herds and so
serves as a benchmark for comparisons. The column
at the right compares each bull to Bull A in
terms of progeny weaning weight. If we used the
WW column, wed rank the bulls A - D - B,E - C.
This would not be correct because Herd 2 has a
better environment and (or) better cows. Using
the column at right, we correctly rank the bulls
A - B - D - E - C. This concept applies for
other species as well.
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Predicting Breeding Value Across-Herd Genetic
Evaluation
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Predicting Breeding Value
Reference Sires Animal used in different
contemporary groups or different farms.
Mean production of Half Sibs from Reference Sires
allows the estimation of the effect of the
contemporay group.
Animals Compared within Contemporary Group. Its
a way to correct for non- genetic effects.
Once the contemporary group effect is calculated
is possible to compare animals born in different
farms.
Within Contemporary Group Animals have
performance adjusted for non-genetics effects
such as age of the Dam
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Reference Sire Concept

• Today, designated reference sires are not usually
  needed.
• Many sires serve as references without being
  designated as such.
• Other relationships between herds also serve as
  ties to adjust for differences in E.

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Reference sire concept

• 1- Same animal in different herds (impossible for
  many traits)
• 2- Clones (not available)
• 3- Full Sibs (ET not very effective)
• 4- Half Sibs (AI Improve connection between CG)
• 5- Any related animal (Connect different CGs)

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Reference sire concept

• 1- Same animal in different herds (impossible for
  many traits)
• 2- Clones (not available)
• 3- Full Sibs (ET not very effective)
• 4- Half Sibs (AI Improve connection between CG)
• 5- Any related animal (Connect different CG)
• Within family variation number of progenies
• _____
• Mean of HS in different CG tend to be similar
• nHS lt n animals with more distant relationship.

Coefficient of Relationship
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Beef Cattle EPDs

• Different programs for different breeds.
• National Sire Evaluation - previous.
• National Cattle Evaluation - today.
• Typical traits
• Growth BW, WW direct, YW, others.
• Maternal Milk, WW maternal.
• Carcass wt, external fat, REA, marbling.
• Others vary by breed

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Breed Average EPD and Values
Genetic Base 1979
Distributions
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Interpretation

• Yearling weight _
• EPD, lb ACC
• Bull A - 5.0 .56
• Bull B 25.0 .72
• Future offspring of B are expected to weigh 30 lb
  more than those of A at one year, on average.

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Interpretation

• Fat thickness _
• EPD, in ACC
• Bull A - .20 .41
• Bull B .08 .38
• Offspring of A are expected, on average, to
  produce carcasses with .28 in less fat than those
  of B at the same slaughter age.

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Beef Cattle EPDs

• Direct WW EPD predicts WW difference of the
  animals own offspring (growth potential).
• Maternal WW EPD predicts WW difference of calves
  of the animals daughters (milk and growth
  potential).
• Milk EPD predicts the portion of WW difference
  of calves of the animals daughters due to milk
  (milk potential).

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Beef Cattle EPDs
Maternal WW EPD Milk EPD 1/2 Direct WW EPD
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Accuracy of EPD

• Similar to ACC of EBV.
• Level of confidence that the EPD closely
  approximates true PD.
• Is not a measure of expected variation among
  progeny.
• Use EPDs to select or rank breeding animals. Use
  ACC to determine how extensively an animal is
  used.

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Accuracy and Associated Possible Change

• The following table lists the possible change
  values associated with each EPD trait at the
  various accuracy levels.
• Possible change is expressed as "" or "-" pounds
  of EPD and can be described as a measure of
  expected change or potential deviation between
  the EPD and the "true" progeny difference.
• This confidence range depends on the standard
  error of prediction for an EPD. For a given
  accuracy, about two-thirds of the time an animal
  should have a "true" progeny difference within
  the range of the EPD plus or minus the possible
  change value.

More info higher Acc. (.3-.4 for young animals
and .99 for sires with more than 500 offspring
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Accuracy and Associated Possible Change

• For example, a sire with an accuracy of .7 and
  birth weight EPD of 1.0 is expected to have his
  "true" progeny value falling within 0.86 pounds
  for birth weight EPD (ranging between 0.14 and
  1.86) about two-thirds of the time.
• With the conservative approach taken with respect
  to heritabilities in the Angus evaluation, actual
  EPD changes of animals within the population are
  much less than statistics would indicate.

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Accuracy and Associated Possible Change
Variation on progeny (Distributions)
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Accuracy and Associated Possible Change

• For example, a sire with an accuracy of .7 and
  birth weight EPD of 1.0 is expected to have his
  "true" progeny value falling within 0.86 pounds
  for birth weight EPD (ranging between 0.14 and
  1.86) about two-thirds of the time.
• With the conservative approach taken with respect
  to heritabilities in the Angus evaluation, actual
  EPD changes of animals within the population are
  much less than statistics would indicate.

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Beef Cattle EPDs

• Much information can be found on WWW.
• Breed associations
• Angus - http//www.angus.org/index.html
• Limousin - http//www.ansi.okstate.edu/breeds/catt
  le/limousin/
• Hereford - http//www.hereford.org/tailored.aspx
• Simmental http//www.simmgene.com/
• A.I. Organizations
• ABS Global - http//www.absglobal.com/home.html

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EPDs for commercial beef producers

• Unless using A.I., bulls will likely have low ACC
  values.
• Progeny of low ACC bulls tend to perform as
  expected when averaged over several bulls. Some
  individual bulls will be over- or
  under-estimated.
• The ACC of an EPD averaged over several bulls
  will be higher than the average of their
  individual ACCs.

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Genetic Base

• Base zero-point. EPDs calculated as deviations
  from genetic base.
• Fixed base example all animals born 1979.
• Some breeds now use floating base.
• Implication In general, an EPD of 0.0 does not
  equal current breed average.

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Across-breed EPDs

• In general, cannot compare EPDs computed by
  different breed associations.
• Each breed conducts separate analysis.
• Genetic base (zero-point) is different for each
  breed.
• Table of across-breed adjustment factors from
  USDA MARC.
• Simmental uses some data from other breeds.

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Across-breed EPDs
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National Sheep Improvement Program (NSIP)

• Across-flock EPDs are available for some animals
  in 6 breeds
• Columbia
• Dorset
• Hampshire
• Polypay
• Suffolk
• Targhee
• Cannot compare EPDs between breeds

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Sheep Maternal traits

• Number of lambs born per ewe lambing.
• Milk EPD.
• Milk growth EPD
• milk EPD 1/2 (60-day wt EPD).

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Sheep Growth traits

• Farm flocks
• 60-day and 120-day weight
• Range flocks
• 120-day and yearling weights

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Sheep Wool traits.

• fleece weight (lb).
• fiber length (in).
• fiber diameter (microns).

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Dairy Genetic Evaluation

• USDA computes across-herd values
• Some animals are also included in an
  across-country analysis (Interbull).
• Predicted value is based on records from all
  relatives.
• Values are calculated as deviations from the
  base.
• The base for production traits was recently
  updated to cows born in 1995.

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Dairy Cattle Genetic Evaluation

• Production traits
• PTA predicted transmitting ability (like EPD)
• PPA predicted producing ability (like MPPA)
  females only (repeatability).
• Type traits
• STA standardized transmitting ability (standard
  deviation units)
• REL reliability (like ACC)

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Production Traits

• PTA M (lb milk)
• PTA F (lb fat)
• PTA F ( fat)
• PTA P (lb protein)
• PTA P ( protein)
• PTA PL (productive life, months)
• PTA SCS (somatic cell score lower better)

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Dairy Linear (type) Traits

• Stature (height)
• Strength (frail vs. strong)
• Body depth
• Feet leg score
• Udder traits
• Others

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Dairy Management Traits

• Milking speed
• Temperament
• Non-return rate

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Dairy Cattle

• Milk Yield (305-day) _
• PTA, lb Rel
• Bull A 1125 .66
• Bull B 2525 .92
• Future daughters of B are expected to produce
  1400 lb more milk per lactation than daughters of
  A, on average.

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Dairy Cattle

• Protein _
  
• PTA, lb PTA,
• Bull C 58 - 0.05
• Bull D 48 0.04

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Standard Indexes

• Net Merit
• Fluid Merit
• Cheese Merit
• TPI type/production index
• Udder composite
• Feet leg composite