Lecture 15

1

CompetitionProblem and Theory

GxG Interactions

Lecture 15

2

Problem

• Competition (Fighting)– Dominance– Limited Space– Limited Food Supply– Peck Order

Lecture 15

3

Results of Competition• Reduced Gain• Increased Mortality

– Direct• Injuries

– Indirect• Immune response• Diseases susceptibility

• Reduced Feed Efficiency– Energy lost in fighting– Increased Fat

depositionAnimal Well being concernsAnimal Well being concerns

Lecture 15

4

Effects of Group Size on Pig Growth and Composition

• Group Size:1, 4, 8, 16 or 32 pigs per pen

• Similar Pen and Feeder Space Per Pig

• Average Initial and Final Pig Weights25.7 and 108.5 kg

•Frank, G. R., M. E. Spurlock, S. G. Cornelius, G. M. Willis, and M. McComb. 1997a. J. Anim. Sci. Vol. 75(Suppl. 1):37(abstr.)

Lecture 15

5

Average Daily Gain

0.82

0.84

0.86

0.88

0.9

0.92

0.94

0.96

1 4 8 16 32

Group Size•Frank, G. R., M. E. Spurlock, S. G. Cornelius, G. M. Willis, and M. McComb. 1997a. J. Anim. Sci. Vol. 75(Suppl. 1):37(abstr.)

Lecture 15

6

Fat Depth

13.5

14

14.5

15

15.5

16

16.5

1 4 8 16 32

Group SizeFrank, J. W., B. T. Richert, A. P. Schinckel, B. A. Belstra, and A. L. Grant. 1997b.. J. Anim. Sci.(Suppl. 1):38(abstr.).

Lecture 15

7

They May Look Happy, But Competition is a Real Problem in Swine and Poultry

Lecture 15

8

Animal Well-being

• Animal Welfare Issues Are Becoming a Major Concern.– Egg Producers Are Asking for a Different

Type of Hen, Specifically Adapted to ‘Animal Friendly’ Production Systems Preisinger (1998).

Lecture 15

9

The Cause of the Problem

• Environment of Selection– Natural

Unlimited TerritoryLimited FoodMust Attract Mates

• Environment of Production– Domestic

• Limited Territory• Food Provided• Mates Provided

Lecture 15

10

Examples Of Behavioral Problems

• Susceptibility To Hysteria In Large Groups

• Pacing Before Laying, • Feather Pecking• Cannibalistic Deaths• Fearful Or Panic Responses• Cannibalism• Inter-individual Aggression

Lecture 15

11

Contributing to The Problem• Individual Selection

– Group Setting– Non Group Setting

Lecture 15

12

Individual Selection In a Group Setting Selects for the Most Aggressive Animals

Lecture 15

13

Domestication

• Method To Adapt An Animal To A Production Environments

• Stress Is A Manifestation Of How Well The Bird Is Adapted To That Environment

Lecture 15

14

AdaptationBirds in Diverse Ecosystems Evolved from a Common Ancestor

Each Would be Stressed in the Other Environment Because they are Not Adapted to it (GxE Interaction).

Lecture 15

15

Can Genetic Selection Improve Adaptability and Well-being of Birds?

• Appleby and Hughes (1991)– Welfare Problems In

Cages Are Less Likely To Be Alleviated By Genetic Selection Than Those In Alternative Systems

– Welfare Is Compromised If Freedom To Exercise Normal Behavior Is Absent

Lecture 15

16

Genetic Selection Can Change “Normal Behavior”

• A Bird Can Evolve Through Selection– Prefers To Be In Close

Proximity To A Large Number Of Cage Mates

– By This Definition, Its Natural Behavior Is Not Compromised

Lecture 15

17

Breeding Cabbages

• Blind Chickens• Ethics

Lecture 15

18

Solutions?• Management

– Well-being issues– Costly

• Genetics– Continue the Domestication

Process– Get Rid of Unwanted and

Undesirable Characteristics Which Were Needed In Natural Environments (Peck Order, Dominance)

Lecture 15

19

Direct Selection on Behavior?

– What Traits Needs to Be Measured

• Biting• Fighting• Other?

– At What Cost?– Diverted Selection Intensity

Lecture 15

20

Link Between Behavior And Stress Can Be Misinterpreted

• Duncan and Filshie (1979)– Flighty Strain Of Birds

• Exhibited Avoidance And Panic Behavior Following Stimulation

• Returned To A Normal Heart Beat Sooner Than A Line Of More Docile Birds

• Docile Birds May Be Too Frightened To Move.

– Is Flightiness Good Or Bad For Well-being

Lecture 15

21

Indirect Selection To Reduce Undesirable Behaviors

• Group Selection– Based On The Hypothesis That When

Productivity Of The Group Is High, Behavioral Stresses Of The Group Must Be Reduced Or Absent (GxG interaction reduced)

– Does Not• Increase Costs• Divert Selection Intensity• Require Measurement Of Behaviour Traits

Lecture 15

22

Among Group Selection

• Foundation Established By Griffing (1967)• Extend Usual Gene Model

– Direct Effects Of Its Own Genes– Associate Contributions From Other Genotypes

In The Group (GxG interactions)

Lecture 15

23

Group Selection• Not to be confuse with individual selection for

the betterment of the group– Wayne Edwards (1962), Hamilton (1964)– Controversial Evolutionary Theory– Appears to have a number of theoretical problems– Even for the case of related individual (usual kin

selection)• Group selection as applied here is among

group selection– The entire group live or dies depending on the

behavior of the group as a whole (pack behavior)

Lecture 15

24

Pigs in Individual Pens

GxG Interactions Not Possible

Lecture 15

25

Y1=19

Y2=16 Y3=17

Example Performance in Individual Pens

Lecture 15

26

Pigs in a Common Pen

GxG Interactions Possible

Lecture 15

27

9

76

-7 -7

0

0

-4

-4

Y1=µ+D1+A2+A3+ε

Y2=µ+D2+A1+A3+ε Y3=µ+D3+A1+A2+ε

Interacting Effects Y1=10+9+0+-4+0=15

Y2=10+6+-7+-4+0=5 Y3=10+7+-7+0+0=10

Lecture 15

28

9

99

-7 -7

-7

-7

-7

-7

Y1=µ+D1+A2+A3+ε

Y2=µ+D2+A1+A3+ε Y3=µ+D3+A1+A2+ε

Clone Top PigY1=10+9-7-7+0=5

Y2=10+9-7-7+0=5 Y3=10+9-7-7+0=5

Y1=10+9-7-7+0=5

Lecture 15

29

6

66

0 0

0

0

0

0

Y1=µ+D1+A2+A3+ε

Y2=µ+D2+A1+A3+ε Y3=µ+D3+A1+A2+ε

Clone Worst Pig Y1=10+6+0+0+0=16

Y2= 10+6+0+0+0=16 Y3= 10+6+0+0+0=16

Lecture 15

30

Cloning the Best Pig Gave Worst Performance and vice versa

GxG Interaction

Lecture 15

31

Individual Selection in a Non Group Setting

•• Selection For Aggression May Still Result Due Selection For Aggression May Still Result Due to Genetic Correlation Between Direct and to Genetic Correlation Between Direct and Associative EffectsAssociative Effects

Lecture 15

32

Individual Selection

( )[ ]AdaAdi σσσµ )(2/ +=∆

2Adσ

Ada σ)(

Additive Genetic Variance of Direct Effects

Covariance between Direct and Associative Effects

Lecture 15

33

Group Selection

( )∆µ σ σ σ σ= + +

id aA A A

2 2 22 ( )da

σa A

2Variance of Associative Effects

This quantity is always positive

Lecture 15

34

To Optimize Productivity In Competitive Environments

• Do Not Select Those Individuals That Perform The Best

• Select The Groups That Produces The Best

Lecture 15

35

N=23 (5.7)

N=15 (15)

N=19 (6.3)

N=26 (6.5)

Group Selection

Lecture 15

36

A Positive Response To Selection Is Ensured

• If Selection Is Transferred From The Individual To That Of The Group

• Group Selection Operates On Both Direct And Associate Components

Lecture 15

37

Kin Selection(Not The Usual Definition)

• If The Group Is Composed Of Related Individuals The Efficiency Is Greatly Increased, Particularly As Group Size Increases Griffing (1976)

Lecture 15

38

Group SelectionApplications

Application

Lecture 15

39Goodnight and Stevens 1997. Am. Nat 150:S59-S79.

Lecture 15

40

Eggs per Hen Housed

91

195219 225

237

507090

110130150170190210230250

1 2 3 4 5Generation

Lecture 15

41

Percent Mortality

67.9

8.814.915.213

01020304050607080

1 2 3 4 5Generations

%

Lecture 15

42

Survival After Mechanical Failure in First Month

4838

85 79

Colony Cage Single Cage

Percent Survival

SelectedControl

Lecture 15

43

89

82

9593

Colony Cage Single Cage

Percent Survival

SelectedControl

Survival For Month 2-12

Lecture 15

44

7th Generation

• Selected (KBG), Control (C), And Commercial (DXL) Lines Were Compared

• All Stocks Housed In Both Single- Or 12-Bird Cages

Lecture 15

45

Cumulative Mortality

050

100150200250300350400450

18 21 24 27 30 33 36 39 42 45 48 51 54 57

AGE (WEEKS)

CONTROLKGBCOMMERCIAL

Lecture 15

46

TOTAL EGGS PER CAGE/12

251

198

295

193

266

217

0

50

100

150

200

250

300

350

SINGLE COLONYSTOCK

EG

GS

CONTROLCOMMERCIALSELECTED

Lecture 15

47

RATE OF LAY

0

10

20

30

40

50

60

70

80

90

COLONY SINGLE

%

CONTROLKGBCOMMERCIAL

Lecture 15

48

CONCLUSIONS

• Group Selection Is Effective In Improving Well-being Of Layers In A Relatively Short Period Of Time Without Sacrificing Productivity

• Individual Selection Makes the Problem Worse

Lecture 15

49

Incorporation of Competitive Effects in Breeding Programs

Without GroupSelection

Mixed Model Theory

Lecture 15

50

Problems With Group

Selection

• Group Selection– Requires

• Families Be Housed Together• Selected As a Group.

– Rate of Inbreeding Increases Rapidly

Lecture 15

51

Incorporation of Competitive Effects In The Mixed Model

Equations (MME)

Lecture 15

52

Example

Pen 1 Pen 2 Pen 3

S1 S2D1 D2 D4 D5D3

Lecture 15

53

Usual Animal Model

εµβ ++= ddZXY

[ ]

+

+

=

9

8

7

6

5

4

3

2

1

9

8

7

6

5

4

3

2

1

9

8

7

6

5

4

3

2

1

100000000010000000001000000000100000000010000000001000000000100000000010000000001

111111111

εεεεεεεεε

µµµµµµµµµ

β

yyyyyyyyy

Lecture 15

54

D1

D3D2

A1A1

A2

A2

A3

A3

Y1=µ+D1+A2+A3+ε

Y2=µ+D2+A1+A3+ε Y3=µ+D3+A1+A2+ε

Interacting Effects

Lecture 15

55

Expand Mixed Model Equationsεµµβ +++= aadd ZZXY

Fixed EffectsMeanLocationAge

IncidenceMatrixFixed Effects

Direct Effects

IncidenceMatrixDirect Effects

IncidenceMatrixAssociative Effects

Associative Effects

RandomError

Yield

Lecture 15

56

Associative Effects Incidence Matrix

εµµβ +++= aadd ZZXY

=

010000100100000100000100010001000010000001001000010001110000000001100000000011000

aZ

Animal 1Pigs 4 and 5 in Same pen

Lecture 15

57

MME with Competitive Effects

=

++++

−−

−−

a

d

a

d

aadaa

adddd

ad

ZXZXXX

AkZZAkZZXZAkZZAkZZXZ

ZXZXXX

'''

''

'''

13

'12

'

12

'11

'

µµβ

1

2

22

32

21−

=

aad

add

kkkk

σσσσ

σε

Lecture 15

58

Genetic Parameters

2dσ2aσ

adσ

Direct Effect

Associate Effect

Covariance Between Direct and Associative Effect

Lecture 15

59

Maximum Likelihood Estimates of Genetic Parameters

PYY'CGR 5.ln5.ln5.ln5. −−−−=L

)ln(

ln)ln(

lnln

2

2

2

e

Ne

e

N σ

σ

σ

=

+=

=

I

IR

= 2

2

AAD

ADD

σσσσ

AAAA

G

∑++

=

−

=

+

=

RNM

iiC

C

1lnln λ

2e

1σGZZ'XZ'ZX'XX'

Lecture 15

60

Optimal Selection

ad bbI∧∧

+= µµ 21

The optimal weights are found as the partial regression coefficients of mean pen

performance on estimated direct and associative effects

Lecture 15

61

Example Pedigree

4 5 6 7

8 910 11

Pen 1 Pen 2(5) (6) (20) (10)10

2065

Y

211761107629541854

PenAniDamSire

=

1111

X

=

102065

Y[ ]µ=B

Lecture 15

62

=

10000000010000000010000000010000

1Z

Animal4 5 6 7 8 9 10 11

102065

Y

211761107629541854

PenAniDamSire

102065

Y

211761107629541854

PenAniDamSire

=

00100000000100001000000001000000

2Z

4 5 6 7 8 9 10 11

10 is with 8 11 is with 9 8 is with 10

Lecture 15

63

MME

=

++++

−−

−−

yZyZyX

adb

kAZZkAZZXZkAZZkAZZXZ

ZX'ZX'XX'

'2

'1

'

221

2'221

11

'2

'2

121

2'111

11

'1

'1

21

ˆ

ˆˆ

2

1

2

2

2221

1211e

ada

dad

kkkk

σσσσσ

−

=

50105

550 1

2221

1211−

−

−=

kkkk

Lecture 15

64

proc iml;start main;

y={5,20,6,10};

X={1,1,1,1};

A={1 0 0 0 .5 .5 0 0,0 1 0 0 .5 .5 0 0,0 0 1 0 0 0 .5 .5,0 0 0 1 0 0 .5 .5,.5 .5 0 0 1 .5 0 0,.5 .5 0 0 .5 1 0 0,0 0 .5 .5 0 0 1 .5,0 0 .5 .5 0 0 .5 1};

AINV=INV(A);

Z1={ 0 0 0 0 1 0 0 0,0 0 0 0 0 1 0 0,

0 0 0 0 0 0 1 0,0 0 0 0 0 0 0 1};

Z2={ 0 0 0 0 0 0 1 0,0 0 0 0 0 0 0 1,

0 0 0 0 1 0 0 0,0 0 0 0 0 1 0 0};

P={50 -5,-5 10};

K=inv(P)#50;LHS=((X`*X)||(X`*Z1)||(X`*Z2))//((Z1`*X)||(Z1`*Z1+AINV#K[1,1])||(Z1`*

Z2+AINV#K[1,2]))//((Z2`*X)||(Z2`*Z1+AINV#K[2,1])||(Z2`*

Z2+AINV#K[2,2]));RHS=(X`*Y)//(Z1`*Y)//(Z2`*Y);C=INV(LHS);BU=C*RHS;RMSE=(Y`*Y-BU`*RHS)#(1/3);print BU RMSE;finish main;run;quit;

Lecture 15

65

Estimates

EffectAnimal Direct Associate4 .798 -.2175 .798 -.2176 -.798 .2177 -.798 .2178 -1.117 -.2429 3.512 -.41010 -1.732 -.07411 -.662 .727

d a25.10ˆ =u

Note animal with best direct effect has worst associative effect

Vice vesra

102065

Y

211761107629541854

PenAniDamSire

Lecture 15

66

Lab Problem 1 Competition

A B C D

E F

G H

Assume animals are in pens as indicated by the rectangles above. Fit an animal model with competitive effects, assume

J

9 13 4 12

11 11

13 9

10

12

2

=a

e

σσ

1.2

2

=p

e

σσ 152

2

=p

e

σσ

Lecture 15

67

Lab Problem 2 CompetitionImpact of GxG effects on Breeding program

11

1 2 3

4 5 6 7 8 9 10

12 9 8 5 7 5 6 8

Pen 1 1 2 2 2 1 1 2

Assume animals are in pens as indicated.

a) Fit an animal model with and without competitive effects

b) Rank Individuals for breeding using the following indexes

c) Discuss results relative to breeding program

60104

430 1

2

1

2

2

−

−

−

−

e

ada

dad σσσσσ

adI µµ ˆ3ˆ1 +=

dI µ1= Without Competitive Effects

With Competitive Effects

Index

Lecture 15

68

Experimental Testing

• Experimental Model– Quail– Trait: 6 Week Weight (wt)

• Methods tested:– Control: Animal Model BLUP

(AM-BLUP)– Competitive Model BLUP: (CE-

BLUP)

• Selected for 25 Hatches

Lecture 15

69

Estimates of Genetic Parameters

5.124

8.25.55.57.33

2

2

2

=

−

−=

=

e

AAD

ADD

σ

σσσσ

G

Lecture 15

70

Initial ExperimentGroup Size and Feed Restriction

Quail Mortality (%)

05

1015202530354045

4 12 16 20Group Size

36

Lecture 15

71

Initial ExperimentGroup Size and Feed Restriction

6 Week Weight (g)

80859095

100105110115120

4 12 16 20Group Size

36

Lecture 15

72

Results

25 Hatches of Selection

Lecture 15

73

6 Week Weight

70

80

90

100

110

CE-BLUPAM-BLUP

Initial

Lecture 15

74

0.0-0.1-0.2-0.3-0.4-0.5-0.6-0.7-0.8-0.9-1.0-1.1

AM-BLUPCE-BLUP

Associative Effects

Lecture 15

75

Direct Effects

AM-BLUPCE-BLUP

Lecture 15

76

Mortality At Termination of Experiment (Hatch 25)

3.4

23.8

0

5

10

15

20

25

Line

CE-BLUPAM-BLUP

Initial

Lecture 15

77

Feed Efficiency Trial

Full FedNo Feed Restriction2-6 Weeks of Age

Lecture 15

78

Feed Conversion (Feed per Gain)

6.6

6.8

7

7.2

7.4

7.6

CE-BLUP AM-BLUP

Feed

/Gai

n

Lecture 15

79

Conclusions• Estimation of Direct and Associative

Effects Allows– Mapping of QTL of Unseen But Important

Traits– Increased Efficiency of Utilization of

Limited Resources– Increased Yield Without Increasing Inputs – Does Not Increase Cost of Program

Lecture 15

80

Conclusions

• Traditional BLUP Selection– Is Not Optimal– Ignores Competitive

Effects– Assumes No Genotypes

x Genotype Interactions

Lecture 15

81

Conclusions

• BLUP Incorporating Associative Effects– Almost As Good As

Group Selection– Far Superior to

Traditional BLUP– Does Not Increase Rate

of Inbreeding As Fast As Group Selection