Fine mapping of quantitative trait loci (QTL) from previous linkage studies was performed on pig chromosomes 1, 4, 7, 8, 17, and X which were known to harbor QTL. Traits were divided into: growth performance, carcass, internal organs, cut yields, and meat quality. Fifty families were used of a F2 population produced by crossing local Brazilian Piau boars with commercial sows. The linkage map consisted of 237 SNP and 37 microsatellite markers covering 866 centimorgans. QTL were identified by regression interval mapping using GridQTL. Individual marker effects were estimated by Bayesian LASSO regression using R. In total, 32 QTL affecting the evaluated traits were detected along the chromosomes studied. Seven of the QTL were known from previous studies using our F2 population, and 25 novel QTL resulted from the increased marker coverage. Six of the seven QTL that were significant at the 5% genome-wide level had SNPs within their confidence interval whose effects were among the 5% largest effects. The combined use of microsatellites along with SNP markers increased the saturation of the genome map and led to smaller confidence intervals of the QTL. The results showed that the tested models yield similar improvements in QTL mapping accuracy.

The objective was to map QTL on porcine chromosome 4 and to associate them with carcass and internal organ traits in an F2 population. The F1 population was produced by outbreed crossing, using two native Brazilian breed Piau boars and 18 commercial sows. A total of 617 F2 animals issued from 11 F1 boars and 54 F1 sows were typed for a total of five microsatellite markers. The data were analyzed by multiple regressions developed for the analysis of crosses between outbred lines, using the QTL Express software. Significant evidence for QTL was found for pig chromosome 4 regarding carcass and internal organ traits. All QTL were detected in the same region of the chromosome, designated FAT1.

RESUMO -Objetivou-se com este trabalho realizar o mapeamento de Locos de características quantitativas (QTL) nos cromossomo 16, 17 e 18 de suínos e associar seus efeitos com características de desempenho. Utilizou-se uma população F2 proveniente do cruzamento de dois varrões da raça naturalizada brasileira Piau com 18 fêmeas de linhagem comercial (Landrace × Large White × Pietrain). A população foi genotipada para 11 marcadores microssatélites e o mapa de ligação específico dos marcadores para a população foi construído. Os marcadores de microssatélites foram considerados adequados para estudos de características quantitativas quando analisado o conteúdo de informação polimórfica (PIC). Para identificação do QTL, utilizou-se o método de regressão por intervalo de mapeamento e realizaram-se as análises por meio do programa QTLExpress. Foram detectados QTL não descritos na literatura para: número de tetas no cromossomo 16; peso aos 63 e aos 77 dias de idade no cromossomo 17; e peso aos 21 dias e idade de abate no cromossomo 18. Foram também identificados QTL já descritos em outras populações, como para peso aos 21 dias de idade no SSC16. As informações dos QTL significativos encontrados servem para futuros estudos de mapeamento fino com identificação de genes e para maior entendimento dos fenótipos produtivos de suínos. Palavras-chave: análise genômica, população F2, produção de suínos Detection of QTL for production traits on swine chromosomes 16, 17 and 18ABSTRACT -The objectives of this study were to map Quantitative Trait Loci (QTL) in chromosomes 16, 17 and 18 and to associate their effects with performance traits in a F2 pig population developed by mating two Brazilian Piau sires with 18 crossbred dams (Landrace × Large White × Pietrain). The linkage map for this population was constructed after genotyping the animals for 11 microsatellite markers and scoring the genotype. Estimates of polymorphic information content (PIC) indicated that the microsatellite markers were appropriate for QTL analyses. Data were analyzed by interval mapping using the QTLEXPRESS program. New QTL were identified for teat number on SSC16, weight at 63 and 77 days of age on SSC17, weight at 21 days of age and slaughter age on SSC18. QTL already known in other populations were also identified for weight at 21 days of age on SSC16. The information of the significant QTL detected in this study is useful for future fine-mapping studies for identification of genes and to improve the knowledge about production traits in pig populations.

ABSTRACT. The aim of the present study was to propose and evaluate the use of factor analysis (FA) in obtaining latent variables (factors) that represent a set of pig traits simultaneously, for use in genomewide selection (GWS) studies. We used crosses between outbred F2 populations of Brazilian Piau X commercial pigs. Data were obtained on 345 F2 pigs, genotyped for 237 SNPs, with 41 traits. FA allowed us to obtain four biologically interpretable factors: "weight", "fat", "loin", and "performance". These factors were used as dependent variables in multiple regression models of genomic selection (Bayes A, Bayes B, RR-BLUP, and Bayesian LASSO). The use of FA is presented as an interesting alternative to select individuals for multiple variables simultaneously in GWS studies; accuracy measurements of the factors were similar to those obtained when the original traits were considered individually. The similarities between the top 10% of individuals selected by the factor, and those selected by the individual traits, were also satisfactory. Moreover, the estimated markers effects for the traits were similar to those found for the relevant factor.

The objective of this study was to map quantitative trait loci (QTL) on porcine chromosomes 16, 17 and 18 and to determine their association with carcass, organ and meat quality traits. An F2 population was produced by crossing two boars of the naturalized Brazilian Piau breed with 18 commercial females (Landrace x Large White x Pietrain). The population was genotyped for 11 microsatellite markers distributed over the three chromosomes and the results were used to construct a marker-specific linkage map for the population. Analysis of the polymorphic information content showed that the microsatellite markers were adequate for the study of quantitative traits. QTL were identified by regression interval mapping using QTL Express software. QTL not previously described in the literature were detected on chromosome 16, whereas QTL described in other populations were detected on chromosomes 17 and 18. The information from the significant QTL identified here will be useful for future fine-mapping studies and should provide a better understanding of productive phenotypes in pigs.