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CHAPTER 14: MULTIPLE TRAIT SELECTION

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Introduction •  Thus far we have only considered single-

trait selection.

•  However, practical breeding plans generally incorporate simultaneous selection for more than one trait.

– There is more than one trait of interest to the breeder.

– Because of correlated response, attention in selection must often be given to more than one trait to avert undesired outcomes.

Livestock Production Science , 95:217-230 •  A general bio-economic model for beef production

was used to define breeding objectives for Charolais cattle to be utilized in a variety of linked production systems. Economic weights were calculated for 16 traits (some with both direct and maternal components) in three production systems (pure-breeding and terminal crossing with beef or dairy cows) and two marketing strategies (sale or fattening of weaned surplus calves). Economic weights for the total breeding objective were calculated as weighted averages, where weights were numbers of cows expected to be mated with Charolais bulls in each production system and marketing strategy.

•  How to decide what traits to include?

•  economic importance •  heritability •  standard deviation •  genetic correlations among traits •  phenotypic correlations among traits •  ease or expense of measurement

Introduction

•  The goal of multiple trait selection is to improve Aggregate Breeding Value

– This is also referred to breeding for net merit.

– This involves considering both the traits to select for and the relative merit or importance of each trait in the overall breeding program.

Methods of Multiple Trait Selection

•  In practice, breeders typically conceive of Aggregate Breeding Value (H) in an intuitive manner

•  However, theoretically speaking, there are basically 3 Methods of multi-trait selection

1.  Tandem Selection 2.  Independent Culling Levels 3.  Selection Indexes (Economic)

1.  Tandem Selection is alternating the practice of selection between traits (first one, then another, then still another or back to the first) = Serial Selection.

Select for one trait at a time –  improve first trait until satisfied –  improve second trait until satisfied –  improve third trait until satisfied, etc.

Thus, over time Tandem Selection represents multi-trait selection, but at any one point in time only a single trait is being selected for.



•  This often results in a see-saw pattern of selection and response

– Example: First, select only for Yearling Weight until increasing Birth Weight becomes a problem (due to correlated response);

– Then switch selection exclusively to Birth Weight until it is under control again.


•  Because all selection pressure in Tandem Selection is applied to one trait at a time, its effectiveness is dependent on the Genetic Correlations among the traits of interest.

– Favorable rGG results in genetic improvement for correlated trait(s) as well as the trait selected for

– Unfavorable rGG results in genetic improvement of the selected trait and decreases in the correlated trait(s).

Which would be the best situation to practice tandem selection?

A.  When only interested in one trait, and it does not have any known favorable or unfavorable traits correlated with it.

B.  When the two traits most interested in have unfavorable traits associated with them with low correlation values and low heritabilities

C.  When the two traits most interested in have unfavorable traits associated with them with high correlation values and high heritabilities

Which would be the best situation to practice tandem selection?

•  When the two traits most interested in have favorable traits associated with them with low correlation values and low heritabilities

•  When the two traits most interested in have favorable traits associated with them with high correlation values and high heritabilities


•  Genetic correlations between traits make it impossible to maintain any selected trait at its optimum level, since switching selection to another trait will result in slippage in BV for the first trait (since rGG ≠ 1)

•  Therefore, tandem selection is not very effective. Especially bad if adverse correlations exist among traits.


2. Independent Culling Levels = Selection method in which minimum acceptable phenotypic levels are assigned to several traits. •  In this method, the breeder sets a floor

independently for each selected trait and rejects (culls) any animal that falls below the minimum standard for any trait.

– Example: a beef breeder rejects any heifer as a replacement if

» its BW is greater than 4 lbs above herd avg., or

» its YW is less than 33 lbs above herd avg.


•  Independent Culling Levels are easy to apply…

– If there is a clear distinction between the levels of performance that are acceptable or not as in Simply Inherited or Threshold traits.

– When selection occurs at different stages of life, different culling practices are carried out:

» BW: high weight bull calves castrated » WW: low weight calves marketed » YW: further selections of future breeding

stock made » This reduces costs by not maintaining

animals that will never make the cut as potential breeders as soon as that becomes obvious.


•  Problems with Independent Culling Levels

• Too restrictive: not enough animals pass the tests.

• Too loose: animals with undesirably low performance in one or more traits may make the cut.

• Strength in one trait cannot make up for another weakness

• At any level it is possible to cull animals that may be superior in specific traits and keep those that are mediocre all around.


3. Selection Indexes (Economic)

“An index or combination of weighting factors and genetic information – either phenotypic data or genetic predictions – on more than one trait. Economic selection indexes are used in multiple-trait selection to predict aggregate breeding value.”

3.  Selection Indexes (Economic) Equation that combines all traits of importance - factors in calculation:

• economic importance • heritability • standard deviation • genetic correlations • phenotypic correlations • The Selection Index is a first order

linear equation: I = b1 x1 + b2 x2 + ÿ bn xn


•  The Selection Index is based on the Breeding Objective (H), which defines the aggregate breeding value of the traits in the Index according to their relative economic importance.

•  The traits in the Selection Index may not be the same ones that appear in the Breeding Objective. – The traits in the Breeding Objective are the

ones that are of economic importance.


– The traits in the Selection Index are the ones on which Performance data can be collected easily and cheaply.

– Therefore, Indicator Traits may be used in the Selection Index that are not part of the Breeding Objective. Ex: Birth Weight


•  The calculations used to construct a Selection Index from the Breeding Objective are shown in the boxed section on pg. 299-300.

– These calculations provide the appropriate weighting factors (b’s) in the Selection Index to optimize selection for Economic Value with the traits involved.


•  The Phenotypic Selection Index is the name given to an Economic Selection Index based on observations of the individuals subject to selection alone (no pedigree or progeny information included). – Example: Selection for BW and YW in beef

cattle H = 1.1 YW - 6.52 BW

» This is based on an economic value of $1.10 for each 1 lb increase in YW and a decrease of $6.52 in economic value for each 1 lb increase in BW.


– By solving the equations on p. 299-300 using appropriate variances and covariances for YW and BW, and accounting for genetic and phenotypic relationships, the following Phenotypic Selection Index is derived:

I = YW - 5.8 BW – The results of these calculations for a

sample set of data shown in Table 14.1.


•  Theoretically, the Selection Index is the most efficient means of improving Aggregate Breeding Value in multi-trait selection. – Advantage over Independent Culling Levels:

SI rationally balances superiority in one trait with inferiority in another to select best animals overall.

– SI explicitly defines the breeding objectives, which are only implicit in Tandem and Independent Culling Levels.


•  Problems with Selection Indexes – The true economic weights (v’s) are difficult to

determine. – Economic weights are changeable over much

shorter time intervals than the duration of a breeding program with large animals.

– SI provides direction for selection, but no clearly defined end points (Selection Targets).

– Simple SI’s without screens may favor selection of undesirably extreme individuals.


•  Selection Indexes are widely used by Corporate animal breeders (poultry, swine), but not much by “on farm” breeders, who tend to have a closer knowledge of their individual animals.


•  Combination of Multi-Trait Selection Methods

– Example: Add Independent Culling Level for BW to a Selection Index based on BW and YW to eliminate unacceptably high BW individuals regardless of their index scores.

Selection Intensity and Multi-Trait Selection

•  Selection Intensity (i) for any one trait in a multi-trait selection program will be less than it would be under single trait selection. – Relaxing culling level is the same as reducing

selection intensity. • The distance between the solid and dotted

lines represents the loss of intensity for each trait (BW, YW) when the same Independent Culling Levels as in Figure 14.1 are used to select for both traits simultaneously rather than each trait separately.


Objective: 40 replacement heifers


–  In terms of Truncation Selection, the data in Figures 14.1,2,3 represent selecting 40 out of 77 heifers available = .52 proportion saved.

• By Table 10.1 (p. 205) this represents a Selection Intensity (i) of .77 standard deviation units for Single Trait Selection (not very intense)

• With the Independent Culling Levels illustrated:

– Save 74 of 77 on BW; i = .08 – Save 43 of 77 on YW; i = .71


•  Loss of Selection Intensity and Correlations between Traits

– The loss of Selection Intensity per trait with Multi-Trait Selection depends on:

• The magnitude of the correlation between traits

• Whether the correlation is favorable or unfavorable.


– With BW and YW, these factors combine in the most undesirable way: correlation is both high and unfavorable.

– With favorable correlations the loss of Selection Intensity is much less severe.

» WW and YW are positively and favorably correlated.

» note 30 of 44 selected heifers will be saved by single trait selection on either WW or YW (contrasted with 12 when BW and YW were the two traits; see Figure 14.4).

Selection Intensity and

Multi-Trait Selection

Positively correlated traits Loss of selection intensity is less severe


– Perspectives on loss of Selection Intensity with Multi-Trait Selection

• Do not include frivolous or unimportant traits in a multi-trait selection program - be selective about what you select for!

• However, no truly meaningful trait should be excluded from selection, because the goal of multi-trait selection is to optimally improve overall aggregate value, not to make the most rapid possible improvement in any single trait.

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