title: Genomic selection in a pig population including information from slaughtered full sibs of boars within a sib-testing program.
abstract: Genomic selection is becoming a common practise in dairy cattle, but only few works have studied its introduction in pig selection programs. Results described for this species are highly dependent on the considered traits and the specific population structure. This paper aims to simulate the impact of genomic selection in a pig population with a training cohort of performance-tested and slaughtered full sibs. This population is selected for performance, carcass and meat quality traits by full-sib testing of boars. Data were simulated using a forward-in-time simulation process that modeled around 60K single nucleotide polymorphisms and several quantitative trait loci distributed across the 18 porcine autosomes. Data were edited to obtain, for each cycle, 200 sires mated with 800 dams to produce 800 litters of 4 piglets each, two males and two females (needed for the sib test), for a total of 3200 newborns. At each cycle, a subset of 200 litters were sib tested, and 60 boars and 160 sows were selected to replace the same number of culled male and female parents. Simulated selection of boars based on performance test data of their full sibs (one castrated brother and two sisters per boar in 200 litters) lasted for 15 cycles. Genotyping and phenotyping of the three tested sibs (training population) and genotyping of the candidate boars (prediction population) were assumed. Breeding values were calculated for traits with two heritability levels (h 2=0.40, carcass traits, and h 2=0.10, meat quality parameters) on simulated pedigrees, phenotypes and genotypes. Genomic breeding values, estimated by various models (GBLUP from raw phenotype or using breeding values and single-step models), were compared with the classical BLUP Animal Model predictions in terms of predictive ability. Results obtained for traits with moderate heritability (h 2=0.40), similar to the heritability of traits commonly measured within a sib-testing program, did not show any benefit from the introduction of genomic selection. None of the considered genomic models provided improvements in prediction ability of pigs with no recorded phenotype. However, a few advantages were found for traits with low heritability (h 2=0.10). These heritability levels are characteristic for meat quality traits recorded after slaughtering or for reproduction or health traits, typically recorded on field and not in performance stations. Other scenarios of data recording and genotyping should be evaluated before considering the implementation of genomic selection in a pig-selection scheme based on sib testing of boars.
authors.affiliation: 1Department of Agricultural and Food Sciences,Division of Animal Sciences,University of Bologna,40127 Bologna,Italy.
authors.forename: A B
authors.initials: AB
authors.lastname: Samorè
authors.affiliation: 2Centro di Ricerca per la Produzione delle Carni e il Miglioramento Genetico,Consiglio per la Ricerca e la Sperimentazione in Agricoltura,Monterotondo Scalo,00016 Roma,Italy.
authors.forename: L
authors.initials: L
authors.lastname: Buttazzoni
authors.affiliation: 3Associazione Nazionale Allevatori Suini,00161 Roma,Italy.
authors.forename: M
authors.initials: M
authors.lastname: Gallo
authors.affiliation: 1Department of Agricultural and Food Sciences,Division of Animal Sciences,University of Bologna,40127 Bologna,Italy.
authors.forename: V
authors.initials: V
authors.lastname: Russo
authors.affiliation: 1Department of Agricultural and Food Sciences,Division of Animal Sciences,University of Bologna,40127 Bologna,Italy.
authors.forename: L
authors.initials: L
authors.lastname: Fontanesi
mesh_terms: D000818:Animals; D001947:Breeding; D005260:Female; D023281:Genomics / Q000379:methods*; D005838:Genotype; D008297:Male; D008957:Models, Genetic; D010375:Pedigree; D010641:Phenotype; D020641:Polymorphism, Single Nucleotide; D040641:Quantitative Trait Loci; D012641:Selection, Genetic; D013552:Swine / Q000235:genetics*
keywords: GEBV