Sire evaluation for total number born in pigs using a genomic reaction norms approach.
In the era of genome-wide selection (GWS), genotype-by-environment (G×E) interactions can be studied using genomic information, thus enabling the estimation of SNP marker effects and the prediction of genomic estimated breeding values (GEBV) for young candidates for selection in different environments. Although G×E studies in pigs are scarce, the use of artificial insemination has enabled the distribution of genetic material from sires across multiple environments. Given the relevance of reproductive traits, such as the total number born (TNB) and the variation in environmental conditions encountered by commercial dams, understanding G×E interactions can be essential for choosing the best sires for different environments. The present work proposes a two-step reaction norm approach for G×E analysis using genomic information. The first step provided estimates of environmental effects (herd-year-season, HYS), and the second step provided estimates of the intercept and slope for the TNB across different HYS levels, obtained from the first step, using a random regression model. In both steps, pedigree ( A: ) and genomic ( G: ) relationship matrices were considered. The genetic parameters (variance components, h(2) and genetic correlations) were very similar when estimated using the A: and G: relationship matrices. The reaction norm graphs showed considerable differences in environmental sensitivity between sires, indicating a reranking of sires in terms of genetic merit across the HYS levels. Based on the G: matrix analysis, SNP by environment interactions were observed. For some SNP, the effects increased at increasing HYS levels, while for others, the effects decreased at increasing HYS levels or showed no changes between HYS levels. Cross-validation analysis demonstrated better performance of the genomic approach with respect to traditional pedigrees for both the G×E and standard models. The genomic reaction norm model resulted in an accuracy of GEBV for "juvenile" boars varying from 0.14 to 0.44 across different HYS levels, while the accuracy of the standard genomic prediction model, without reaction norms, varied from 0.09 to 0.28. These results show that it is important and feasible to consider G×E interactions in evaluations of sires using genomic prediction models and that genomic information can increase the accuracy of selection across environments.
Departamento de Zootecnia, Universidade Federal de Viçosa, 36570-000 Viçosa, Brazil fabyanofonseca@ufv.br.
F F
FF
Silva
Animal Breeding and Genomics Centre, Wageningen University, P.O. Box 338, 6700 AH Wageningen, the Netherlands.
H A
HA
Mulder
TOPIGS Research Center IPG, P.O. Box 43, 6640 AA Beuningen, the Netherlands.
E F
EF
Knol
TOPIGS Research Center IPG, P.O. Box 43, 6640 AA Beuningen, the Netherlands.
M S
MS
Lopes
Departamento de Zootecnia, Universidade Federal de Viçosa, 36570-000 Viçosa, Brazil.
S E F
SE
Guimarães
Departamento de Zootecnia, Universidade Federal de Viçosa, 36570-000 Viçosa, Brazil.
P S
PS
Lopes
TOPIGS Research Center IPG, P.O. Box 43, 6640 AA Beuningen, the Netherlands.
P K
PK
Mathur
Departamento de Biologia Geral, Universidade Federal de Viçosa, 36570-000 Viçosa, Brazil.
J M S
JM
Viana
Animal Breeding and Genomics Centre, Wageningen University, P.O. Box 338, 6700 AH Wageningen, the Netherlands.
J W M
JW
Bastiaansen
D000818:Animals; D001947:Breeding; D004777:Environment; D005260:Female; D016678:Genome; D023281:Genomics; D005838:Genotype; D008297:Male; D008957:Models, Genetic; D010375:Pedigree; D010641:Phenotype; D013552:Swine / Q000235:genetics* / Q000502:physiology
SNP markers; genotype by environment interaction; random regression