gxe in commercial pig breeding reaction norms selection for the response environment pieter knap...
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![Page 1: GxE in commercial pig breeding reaction norms selection for the response environment Pieter Knap Genus-PIC](https://reader038.vdocuments.us/reader038/viewer/2022110304/551c21c4550346a84f8b5bc5/html5/thumbnails/1.jpg)
GxE in commercial pig breedingreaction norms
selection for the response environment
Pieter KnapGenus-PIC
![Page 2: GxE in commercial pig breeding reaction norms selection for the response environment Pieter Knap Genus-PIC](https://reader038.vdocuments.us/reader038/viewer/2022110304/551c21c4550346a84f8b5bc5/html5/thumbnails/2.jpg)
Selection of genotypes for a particular production environment
Between linesrelatively straightforward
Within-linemuch more interesting
![Page 3: GxE in commercial pig breeding reaction norms selection for the response environment Pieter Knap Genus-PIC](https://reader038.vdocuments.us/reader038/viewer/2022110304/551c21c4550346a84f8b5bc5/html5/thumbnails/3.jpg)
Selection of genotypes for a particular production environment
Selection between linesrelatively straightforward: usually few lines to choose from
![Page 4: GxE in commercial pig breeding reaction norms selection for the response environment Pieter Knap Genus-PIC](https://reader038.vdocuments.us/reader038/viewer/2022110304/551c21c4550346a84f8b5bc5/html5/thumbnails/4.jpg)
Selection of genotypes for a particular production environment
Selection between linesrelatively straightforward: usually few lines to choose from
![Page 5: GxE in commercial pig breeding reaction norms selection for the response environment Pieter Knap Genus-PIC](https://reader038.vdocuments.us/reader038/viewer/2022110304/551c21c4550346a84f8b5bc5/html5/thumbnails/5.jpg)
Selection of genotypes for a particular production environment
Selection between linesrelatively straightforward: usually few lines to choose from
![Page 6: GxE in commercial pig breeding reaction norms selection for the response environment Pieter Knap Genus-PIC](https://reader038.vdocuments.us/reader038/viewer/2022110304/551c21c4550346a84f8b5bc5/html5/thumbnails/6.jpg)
Selection of genotypes for a particular production environment
Selection between linesrelatively straightforward: usually few lines to choose from
![Page 7: GxE in commercial pig breeding reaction norms selection for the response environment Pieter Knap Genus-PIC](https://reader038.vdocuments.us/reader038/viewer/2022110304/551c21c4550346a84f8b5bc5/html5/thumbnails/7.jpg)
Selection of genotypes for a particular production environment
Selection between linesrelatively straightforward: usually few lines to choose from
![Page 8: GxE in commercial pig breeding reaction norms selection for the response environment Pieter Knap Genus-PIC](https://reader038.vdocuments.us/reader038/viewer/2022110304/551c21c4550346a84f8b5bc5/html5/thumbnails/8.jpg)
Selection of genotypes for a particular production environment
Selection between linesrelatively straightforward: usually few lines to choose from
![Page 9: GxE in commercial pig breeding reaction norms selection for the response environment Pieter Knap Genus-PIC](https://reader038.vdocuments.us/reader038/viewer/2022110304/551c21c4550346a84f8b5bc5/html5/thumbnails/9.jpg)
Selection of genotypes for a particular production environment
Selection between linesrelatively straightforward: usually few lines to choose from
![Page 10: GxE in commercial pig breeding reaction norms selection for the response environment Pieter Knap Genus-PIC](https://reader038.vdocuments.us/reader038/viewer/2022110304/551c21c4550346a84f8b5bc5/html5/thumbnails/10.jpg)
Selection of genotypes for a particular production environment
Within-line selectionmuch more interesting: continuous variation to choose from
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Rischkowsky & Pilling (2007)
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Anderson (2004) after Haldane (1946)
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0.60
0.62
0.64
0.66
0.68
0.70
aver
age
daily
gai
n (k
g /
d)
very highinfectiousness
very lowhigh low
Schinckel et al. (1999)
Poster: Antti Kause
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Anderson (2004) after Haldane (1946)
Within-line selectionmuch more interesting:
continuous variation to choose from
![Page 15: GxE in commercial pig breeding reaction norms selection for the response environment Pieter Knap Genus-PIC](https://reader038.vdocuments.us/reader038/viewer/2022110304/551c21c4550346a84f8b5bc5/html5/thumbnails/15.jpg)
Within-line selectionmuch more interesting:
continuous variation to choose from
Anderson (2004) after Haldane (1946)
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0.60
0.62
0.64
0.66
0.68
0.70
aver
age
daily
gai
n (k
g /
d)
very highinfectiousness
very lowhigh low 0.62 0.64 0.66 0.68 0.70
treatment mean: average daily gain (kg / d)
0.60
0.62
0.64
0.66
0.68
0.70
average daily gain (kg / d)
y = 0.30 + 0.57 x
y = –0.30 + 1.43 x
Schinckel et al. (1999)
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Within-line selectionmuch more interesting:
continuous variation to choose from
Anderson (2004) after Haldane (1946)
![Page 18: GxE in commercial pig breeding reaction norms selection for the response environment Pieter Knap Genus-PIC](https://reader038.vdocuments.us/reader038/viewer/2022110304/551c21c4550346a84f8b5bc5/html5/thumbnails/18.jpg)
E > I : incentive to improve the environment
I > E : incentive to match genotype to environment
• Select in the response envrmnt
• Select on data from theresponse environment
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Knap & Su (2008)
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Knap & Su (2008)
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Individual reaction norms
intercept : the conventional EBVfor productivity(when they differ, the trait is heritable)
slope :the EBV for environmental sensitivity of productivity(when they differ, the trait shows GxE)
two breeding goal traits
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environment
phen
otyp
e
EN
PN
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EH
PH
b
PC
EC
EL
PL
EN
PN
PC = PN – b × ( EN – EC )
selection environment
response environment
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EH
PH
b
PC
EC
EL
PL
EN
PN
PC = PN – b × ( EN – EC )
average performance in commercial conditions:= the breeding goal trait
genetic potential
environmental sensitivity
how far away is the nucleus from the
commercial level ?
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P = WT × KO × [Vcarcass+ LEAN × Vlean]
– DAYS120 × [Cday + ADF × Cfeed ]
P = WT × KO × [Vcarcass+ LEAN × Vlean]
– [ PN, DAYS – bDAYS × (DAYSN – DAYSC) ] × [Cday + ADF × Cfeed ]
Set up the profit equation to derive economic values
Two breeding goal traits
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Differentiate to derive marginal economic values
MEV(PN, DAYS) = dP / dPN, DAYS = – [Cday + ADF × Cfeed ]
P = WT × KO × [Vcarcass+ LEAN × Vlean]
– [ PN, DAYS – bDAYS × (DAYSN – DAYSC) ] × [Cday + ADF × Cfeed ]
MEV(bDAYS) = dP / dbDAYS = (DAYSN – DAYSC) × [Cday + ADF × Cfeed ]
= – (DAYSN – DAYSC) × MEV(PN, DAYS)
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Differentiate to derive marginal economic values
MEV(bDAYS) = dP / dbDAYS = (DAYSN – DAYSC) × [Cday + ADF × Cfeed ] =
= – (DAYSN – DAYSC) × MEV(PN, DAYS)
The MEV of the environmental sensitivity depends on
• the MEV of the trait as such• the distance selection environment response environment
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Differentiate to derive marginal economic values
MEV(PN, DAYS) = – [Cday + ADF × Cfeed ] =
= – [0.24 + 2.3 × 0.29 ] = –0.16 € per d
MEV(bDAYS) = – (DAYSN – DAYSC) × MEV(PN, DAYS) =
= –(163 – 179) × –0.16 = –2.56 € per d/d
Negative MEV : a reduction of DAYS120 means faster growth
Negative MEV : a reduction of the slope brings commercial performance closer to the potential
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Individual reaction norms
intercept : the conventional EBVfor productivity(when they differ, the trait is heritable)
slope :the EBV for environmental sensitivity of productivity(when they differ, the trait shows G×E)
two breeding goal traits
An elegant option to deal with G×E on the individual level:
Calculate sensitivity EBVs, and include them in the index, weighted by the MEV as usual.
is that feasible?
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Line B; parity 1 only
66 farms with 33.641 records of33.641 daughters of 792 sires
Line B; all parities
93 farms with 73.352 records of52.120 daughters of 1091 sires
Lines A, B and AB; all parities
144 farms with 346.030 records of121.104 daughters of 2040 sires
Litter size: daughter group reaction norms
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sires sires sires
Line B; parity 1 only
66 farms with 33.641 records of33.641 daughters of 792 sires
Line B; all parities
93 farms with 73.352 records of52.120 daughters of 1091 sires
Lines A, B and AB; all parities
144 farms with 346.030 records of121104 daughters of 2040 sires
Litter size reaction norms of sires: standard error of slope vs. HYS environmental range
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Line B; parity 1 only
66 farms with 33.641 records of33.641 daughters of 792 sires
Line B; all parities
93 farms with 73.352 records of52.120 daughters of 1091 sires
Lines A, B and AB; all parities
144 farms with 346.030 records of121104 daughters of 2040 sires
sires sires sires
Litter size reaction norms of sires: standard error of slope vs. number of daughters
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sires siressiressiressires siressiressiressires
Line B; parity 1 only
66 farms with 33.641 records of33.641 daughters of 792 sires
Line B; all parities
93 farms with 73.352 records of52.120 daughters of 1091 sires
Lines A, B and AB; all parities
144 farms with 346.030 records of121104 daughters of 2040 sires
Litter size reaction norms of sires: standard error of slope vs. slope
h2 rG
intcpt 10 26±7
slope 8±3
h2 rG
intcpt 9 69±5
slope 2±0.4
h2 rG
intcpt 10 –9±15
slope 15±8
Knap & Su (2008)
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Line B; parity 1 only
66 farms with 33.641 records of33.641 daughters of 792 sires
Line B; all parities
93 farms with 73.352 records of52.120 daughters of 1091 sires
Lines A, B and AB; all parities
144 farms with 346.030 records of121.104 daughters of 2040 sires
Litter size: daughter group reaction norms
E > I > G
I > E > G
?Same data (Line B; all parities) analyzed with SAS
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E > I : incentive to improve the environment
I > E : incentive to match genotype to environment
• Select in the response envrmnt
• Select on data from theresponse environment
?
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Individual reaction norms
intercept : the conventional EBVfor productivity(when they differ, the trait is heritable)
slope :the EBV for environmental sensitivity of productivity(when they differ, the trait shows G×E)
two breeding goal traits
An elegant option to deal with G×E on the individual level:
Calculate sensitivity EBVs, and include them in the index, weighted by the MEV as usual.
is that feasible?
Not for pigs, today
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The individual reaction norm approach is notfeasible for commercial pig breeding, today
Simplify
Most extreme:
E as a continuous variable (= reaction norms)
two E classes (e.g. nucleus & commercial)
…or anything in between
Poster: Ann McLaren et al.Poster: Anna-Maria Tyrisevä et al.
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Van Sambeek (2010)
Reciprocal Recurrent Selection
Commercial Sibling Test
Combined Crossbred & Purebred Selection
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• Standal (1968)
• McNew & Bell (1971)
• Biswas et al. (1971)
• Wei Ming & Van der Werf (1994)
• Baumung et al. (1997)
• Bijma & Van Arendonk (1998)
• Spilke et al. (1998)
• Misztal et al. (1998)
• Dekkers & Chakraborty (2004)
Theory:
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… grown on commercial farms
An example: PIC's GN-Xbred program
• after that, semen is
used for GN
matings
• semen of GN boars is first used
on crossbred sows
multiplication
commercial crossbred sows
GN
commercial crossbred slaughter pigs
crossbred progeny
purebred progeny
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An example: PIC's GN-Xbred program
multiplication
commercial breeding stock
GN
commercial crossbred slaughter pigs
PICTraqDatabase
selection decisions
CBVs
GN progeny performance data
Commercial progeny performance data
Commercial sowperformance data
• crossbred halfsib performance
CBVs of GN selection
candidates
crossbred halfsibs of purebred
GN selection candidates
• Xbred sow performance
CBVs of GN selection
candidates
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GN-Xbred logistics
sire lines
dam lines
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Reciprocal Recurrent Selection
Commercial Sibling Test
Combined Crossbred & Purebred Selection
Is this useful?
Depends on the coheritability
• ΔGC|N ~ hC × rG (C,N) × hN
• ΔGC|C ~ hC × hC
• is hC > rG (C,N) × hN ?
is rG (C,N) low enough ?
what about hN vs hC ?
• !! effective heritabilities !!
The crucial aspects :Can the trait be recorded at all in nucleus conditions ?
And on how many animals ?
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• Cecchinato et al. (2010): stillbirth rate rG = 0.25 ± 0.34
• Bosch et al. (2000): litter size 0.40 < rG < 0.59
• Zumbach et al. (2007): ADG 0.53 < rG < 0.80; BFT and LMD 0.78 < rG < 0.89
• Ibáñez-Escriche et al. (2011): lean percentage 0.81 < rEBV < 0.96
• Brandt & Täubert (1998): ADG and BFT 0.87 < rG < 1.0
• Standal (1968)
• McNew & Bell (1971)
• Biswas et al. (1971)
• Wei Ming & Van der Werf (1994)
• Baumung et al. (1997)
• Bijma & Van Arendonk (1998)
• Spilke et al. (1998)
• Misztal et al. (1998)
• Dekkers & Chakraborty (2004)
Theory:
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ADG
ADG
BFD
BFD
DFI
DFI
RFI
RFI
cros
sbre
d co
mm
erci
al p
erfo
rman
ce
rEBV = 0.55
rEBV = 0.54
rEBV = –0.06
rEBV = 0.06
rEBV = 0.85
rEBV = 0.78
rEBV = 0.85
rEBV = 0.80
crossbred comm
ercial performance
purebred nucleus performanceKnap & Wang (2012)
Poster: Helene Gilbert et al.
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cros
sbre
d co
mm
erci
al p
erfo
rman
ce
purebred nucleus performance
crossbred comm
ercial performance
rEBV = 0.33 rEBV = 0.24
grower-finisher mortality rate
Poster: Geir Steinheim et al.
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0.0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1.0
With xbred data
EB
V A
ccu
racy
• low rG (C,N)
• many more data from C than from N
• much more variation in C :
σ2 = p × (1 – p) and p is much higher
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E > I : incentive to improve the environment
I > E : incentive to match genotype to environment
• Select in the response envrmnt
• Select on data from theresponse environment
This is the actual worldwide situation in technified pig production,according to the evidence that I have
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E > I : incentive to improve the environment
I > E : incentive to match genotype to environment
• Select in the response envrmnt
• Select on data from theresponse environment
This is what we are targeting,in terms of genetic evaluation:~ "better safe than sorry"
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E > I : incentive to improve the environment
I > E : incentive to match genotype to environment
• Select in the response envrmnt
• Select on data from theresponse environment
![Page 51: GxE in commercial pig breeding reaction norms selection for the response environment Pieter Knap Genus-PIC](https://reader038.vdocuments.us/reader038/viewer/2022110304/551c21c4550346a84f8b5bc5/html5/thumbnails/51.jpg)
In better conditions,the better animalsare more better
Genetic variation can be• detected more easily• exploited and valuated
more easily
Incentive for the breeder: more diversity in better conditions improve them
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E > I : incentive to improve the environment
Genetic Services: live consultancy at the customer level
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Genetic Services:
manuals & documentation
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Genetic Services:
manuals & documentation
![Page 55: GxE in commercial pig breeding reaction norms selection for the response environment Pieter Knap Genus-PIC](https://reader038.vdocuments.us/reader038/viewer/2022110304/551c21c4550346a84f8b5bc5/html5/thumbnails/55.jpg)
Genetic Services:
manuals & documentation
![Page 56: GxE in commercial pig breeding reaction norms selection for the response environment Pieter Knap Genus-PIC](https://reader038.vdocuments.us/reader038/viewer/2022110304/551c21c4550346a84f8b5bc5/html5/thumbnails/56.jpg)
Conclusions
• in technified pig production, G×E is probably not dramatic
• individual reaction norms are the perfect way to deal with it
• but statistically very demanding and too data-hungry
• CCPS is a feasible compromise, and it works very well
• improving production conditions (i) improves performance
and (ii) makes the better animals more better
![Page 57: GxE in commercial pig breeding reaction norms selection for the response environment Pieter Knap Genus-PIC](https://reader038.vdocuments.us/reader038/viewer/2022110304/551c21c4550346a84f8b5bc5/html5/thumbnails/57.jpg)
GxE in commercial pig breedingreaction norms
selection for the response environment
Pieter KnapGenus-PIC