Comparison of multi-breed and within-breed genomic evaluation in French dairy goats

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Comparison of multi-breed and within-breed genomic evaluation in French dairy goats

Céline Carillier, Helene Larroque, Christèle Robert-Granié

To cite this version:

Céline Carillier, Helene Larroque, Christèle Robert-Granié. Comparison of multi-breed and within- breed genomic evaluation in French dairy goats. 23. Inernational Plant and Animal Genome, Jan 2015, San Diego, United States. pp.1, 2015. �hal-02792919�

0 0,1 0,2 0,3 0,4 0,5 0,6 0,7 0,8

milk yield fat yield protein content

SCS udder floor position

r²(GEB V*D YD)

two steps

single step multi-breed single step ρ estimated single step ρ=0

single step ρ=0,99 single step per-breed

Comparison of multi-breed and within-breed genomic evaluation in French dairy goat

Céline Carillier, Hélène Larroque ,Christèle Robert-Granié , INRA - UMR1388 GenPhySE - Castanet-Tolosan, FRANCE

INSTITUT NATIONAL DE LA RECHERCHE AGRONOMIQUE INRA-GenPhySE UMR1388

24 Chemin de Borde Rouge, Auzeville,

CS 52627, 31326 Castanet-Tolosan Cedex•

Courriel : celine.carillier@toulouse.inra.fr

Aim of genomic selection in French dairy goat

With genomic selection:  generation interval

 selection intensity, accuracy To apply genomic selection we need:

GEBV accuracy ≥ parent average for candidates

interval generation

accuracy intensity

selection gain

genetic

annual _ ^{ }  ^u

genomic

evaluation 40 Alpins

30 Saanens

100 daughters with performances/sire

genetic

evaluation growth

EBV ^{if AI} 5,5 years

parent average accuracy =0,38 young bucks

GEBV

Genomic selection with two steps approach (using DYD): GEBV accuracy of candidates < parent average accuracy (Carillier et al 2013)

 Find a more accurate approach

Method and models used

GEBV were estimated using blup90iod program thanks to I. Misztal

Single step : genomic evaluation based on female performances

Model A: Multi-breed Alpine + Saanen

y: female performances

β: fixed effect of official evaluation + breed effect u: genomic breeding value (GEBV)

p: effect of lactation repetition H: genomic relationship matrix

e Wp

Zu Xβ

y     u ~ ^{N ( 0 , H  u 2 )}

Model C: multiple trait Alpine≠Saanen but correlated

 

 

alp saa

b u

u u

 





 



   





 





 

 



 H

0 0

2 2

,

, ,

saa saa

alp

saa alp alp

u u

u

N u









~

b b

b b

b b

b

b X β Z u W p ε

y    



 







0.99 0 estimated

,





 u

alp saa

Model B: per-breed Alpine or Saanen

alp: for Alpine breed saa: for Saanen breed

u alp ~ ^{N ( 0 , H alp  u 2 alp )}

alp alp

alp alp

alp alp

alp

alp X β Z u W p e

y    

saa saa

saa saa

saa saa

saa

saa X β Z u W p e

y     ~ ^{N ( 0 , H saa  u 2} _saa ⁾

How do we evaluate model?

Pop1

Reference pop

677 IA bucks

Training pop

genotypes + pedigree +

performances

predicting equation

Validation pop

425 bucks: 1993 - 2005

252 bucks: 2006 - 2009

Validation correlations (GEBV,DYDobs)

GEBV

genotypes

Pop2

148 candidates without daugthers born between 2010 and 2011

2 2

accuracy GEBV

u

u PEV



 



PEV: prediction error variance

2



u

: genetic variance

Results

0,50 0,55 0,60 0,65 0,70 0,75 0,80

milk yield

fat yield protein content

SCS Udder floor position

GEB V acc ur acy of can di da ts

parent average accuracy single step multi-breed single step ρ estimated single step ρ=0

single step ρ=0,99 single step per-breed

A

C

B

A C B

validation correlations similar with all models used genomic accuracy >> parent average accuracy

u saa

Conclusions References

Pop2

Pop1

 Genomic selection is feasible in French dairy goat

 Per-breed model is a good one given small population sizes

 Perspectives: integrate major gene in genomic selection models

Carillier C, Larroque H, Palhière I, Clément V, Rupp R, Robert-Granié C (2013) Journal of Dairy Science, 96:7294-7305.

Carillier C, Larroque H, Robert-Granié C (2014) Genetics Selection Evolution, 46:67 Legarra A, Aguilar I, Misztal I (2009) Journal of Dairy Science, 92:4656-4663.

Misztal I, Tsuruta S, Strabel T, Auvray B, Druet T, Lee DH (2002) 7th WCGALP Congress, 19-23 August

2002, Montpellier, France. 2002