RESUMO
Selection for feed efficiency (FE) is a strategy to reduce the production costs per unit of animal product, which is one of the major objectives of current animal breeding programs. In pig breeding, selection for FE and other traits traditionally takes place based on purebred pig (PB) performance at the nucleus level, while pork production typically makes use of crossbred animals (CB). The success of this selection, therefore, depends on the genetic correlation between the performance of PB and CB (rpc) and on the genetic correlation (rg) between FE and the other traits that are currently under selection. Different traits are being used to account for FE, but the rpc has been reported only for feed conversion rate. Therefore, this study aimed 1) to estimate the rpc for growth performance, carcass, and FE traits; 2) to estimate rg between traits within PB and CB populations; and 3) to compare three different traits representing FE: feed conversion rate, residual energy intake (REI), and residual feed intake (RFI). Phenotypes of 194,445 PB animals from 23 nucleus farms, and 46,328 CB animals from three farms where research is conducted under near commercial production conditions were available for this study. From these, 22,984 PB and 8,657 CB presented records for feed intake. The PB population consisted of five sire and four dam lines, and the CB population consisted of terminal cross-progeny generated by crossing sires from one of the five PB sire lines with commercially available two-way maternal sow crosses. Estimates of rpc ranged from 0.61 to 0.71 for growth performance traits, from 0.75 to 0.82 for carcass traits, and from 0.62 to 0.67 for FE traits. Estimates of rg between growth performance, carcass, and FE traits differed within PB and CB. REI and RFI showed substantial positive rg estimates in PB (0.84) and CB (0.90) populations. The magnitudes of rpc estimates indicate that genetic progress is being realized in CB at the production level from selection on PB performance at nucleus level. However, including CB phenotypes recorded on production farms, when predicting breeding values, has the potential to increase genetic progress for these traits in CB. Given the genetic correlations with growth performance traits and the genetic correlation between the performance of PB and CB, REI is an attractive FE parameter for a breeding program.
Assuntos
Ingestão de Alimentos/genética , Ingestão de Energia/genética , Metabolismo Energético/genética , Suínos/genética , Animais , Cruzamento , Feminino , Modelos Lineares , Masculino , Fenótipo , Suínos/crescimento & desenvolvimentoRESUMO
We studied the effect of including GWAS results on the accuracy of single- and multipopulation genomic predictions. Phenotypes (backfat thickness) and genotypes of animals from two sire lines (SL1, n = 1146 and SL3, n = 1264) were used in the analyses. First, GWAS were conducted for each line and for a combined data set (both lines together) to estimate the genetic variance explained by each SNP. These estimates were used to build matrices of weights (D), which was incorporated into a GBLUP method. Single population evaluated with traditional GBLUP had accuracies of 0.30 for SL1 and 0.31 for SL3. When weights were employed in GBLUP, the accuracies for both lines increased (0.32 for SL1 and 0.34 for SL3). When a multipopulation reference set was used in GBLUP, the accuracies were higher (0.36 for SL1 and 0.32 for SL3) than in single-population prediction. In addition, putting together the multipopulation reference set and the weights from the combined GWAS provided even higher accuracies (0.37 for SL1, and 0.34 for SL3). The use of multipopulation predictions and weights estimated from a combined GWAS increased the accuracy of genomic predictions.
Assuntos
Peso Corporal , Estudo de Associação Genômica Ampla , Sus scrofa/genética , Tecido Adiposo , Animais , Polimorfismo de Nucleotídeo Único , Sus scrofa/classificação , Sus scrofa/fisiologiaRESUMO
The objective of this work was to evaluate the efficiency of the supervised independent component regression (SICR) method for the estimation of genomic values and the SNP marker effects for boar taint and carcass traits in pigs. The methods were evaluated via the agreement between the predicted genetic values and the corrected phenotypes observed by cross-validation. These values were also compared with other methods generally used for the same purposes, such as RR-BLUP, SPCR, SPLS, ICR, PCR and PLS. The SICR method was found to have the most accurate prediction values.
Assuntos
Cruzamento , Genótipo , Suínos/genética , Androsterona/metabolismo , Animais , Distribuição da Gordura Corporal , Técnicas de Genotipagem , Fenótipo , Polimorfismo de Nucleotídeo Único , Análise de Componente Principal , Análise de Regressão , Seleção Genética , Suínos/anatomia & histologiaRESUMO
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.
Assuntos
Cruzamento , Genômica , Suínos/genética , Animais , Meio Ambiente , Feminino , Genoma , Genótipo , Masculino , Modelos Genéticos , Linhagem , Fenótipo , Suínos/fisiologiaRESUMO
Linkage disequilibrium (LD) across the genome is critical information for association studies and genomic selection because it determines the number of SNP that should be used for a successful association analysis and genomic selection. Linkage disequilibrium also influences the accuracy of genomic breeding values. Some studies have demonstrated that SNP in strong LD are organized into discrete blocks of haplotypes, which are separated by possibly hot spots of recombination. To reduce the number of markers needed to be genotyped for association mapping, a set of SNP can be selected that labels all haplotype blocks. We estimated the LD, calculated the average haplotype block size for 6 pig lines, and compared the block size between lines. Six commercial pig lines were genotyped using the Illumina PorcineSNP60 (number of markers M = 62,163) Genotyping BeadChip (Illumina Inc.); on average, a panel of 37,623 SNP with an average minor allelic frequency (MAF) of 0.283 was included in the analysis. The LD declined as a function of distance. All pig lines had an average r(2) above 0.3 for markers 100 to 150 apart. The estimated average block size was 394.885 kb, and blocks between 100 and 400 kb were most prominent (49.96%) in all lines. These results showed that the extent of LD in pigs is much larger than in the cattle population, in accordance with the genetic map length of pigs, which is much shorter than cattle. The evaluated lines have 2,640 to 3,037 blocks, covering 45% of the pig genome, on average. Differences in haplotype block size between lines were observed for some chromosomes (i.e., SSC 3, 5, 7, 13, 14, and 18), which provide a direction for future studies of haplotype block conservation or divergence across lines.
Assuntos
Haplótipos , Desequilíbrio de Ligação , Suínos/genética , Animais , Cruzamento , Feminino , Genômica , Masculino , Polimorfismo de Nucleotídeo ÚnicoRESUMO
Meta-analysis of results from multiple studies could lead to more precise quantitative trait loci (QTL) position estimates compared to the individual experiments. As the raw data from many different studies are not readily available, the use of results from published articles may be helpful. In this study, we performed a meta-analysis of QTL on chromosome 4 in pig, using data from 25 separate experiments. First, a meta-analysis was performed for individual traits: average daily gain and backfat thickness. Second, a meta-analysis was performed for the QTL of three traits affecting loin yield: loin eye area, carcass length and loin meat weight. Third, 78 QTL were selected from 20 traits that could be assigned to one of three broad categories: carcass, fatness or growth traits. For each analysis, the number of identified meta-QTL was smaller than the number of initial QTL. The reduction in the number of QTL ranged from 71% to 86% compared to the total number before the meta-analysis. In addition, the meta-analysis reduced the QTL confidence intervals by as much as 85% compared to individual QTL estimates. The reduction in the confidence interval was greater when a large number of independent QTL was included in the meta-analysis. Meta-QTL related to growth and fatness were found in the same region as the FAT1 region. Results indicate that the meta-analysis is an efficient strategy to estimate the number and refine the positions of QTL when QTL estimates are available from multiple populations and experiments. This strategy can be used to better target further studies such as the selection of candidate genes related to trait variation.
Assuntos
Cromossomos de Mamíferos/genética , Locos de Características Quantitativas , Suínos/genética , Tecido Adiposo , Criação de Animais Domésticos , Animais , Peso Corporal/genética , Mapeamento Cromossômico , Genótipo , Carne , Repetições de Microssatélites , FenótipoRESUMO
The objective of this study was to investigate whether pigs with different genetic merit for survival differed in birth weight, progress of farrowing, early postnatal behavior, or rectal temperature within 24 h after birth. On a nucleus farm in Rio Verde, Brazil, information was collected on 280 pigs, originating from 25 litters with known estimated breeding values for pig survival (EBVps). Litters were selected in such a way that a continuous range of EBVps with a maximum genetic contrast was achieved. Birth weight was recorded for all pigs. Indicators for progress of farrowing were birth intervals and duration of farrowing. Behavioral indicators of pig vitality were time until first upright standing (FUS), time until first udder contact (FUC), time until first teat in mouth (FTM), and time until first colostrum uptake (FCU). Rectal temperature was measured within 24 h after birth. Farrowing survival and early postnatal survival (within 3 d after farrowing) were registered. Farrowing survival and early postnatal survival both increased with increasing EBVps (farrowing survival: P = 0.007; early postnatal survival: P = 0.027). Birth weight decreased with increasing EBVps (P = 0.01). Birth intervals tended to increase with increasing EBVps (P = 0.10) and duration of farrowing was not related to EBVps. Time until first teat in mouth increased with increasing EBVps (P = 0.05), but the other behavioral indicators of pig vitality were not related to EBVps. Rectal temperature within 24 h after birth was not related to EBVps. Pigs with a higher genetic merit for survival have a lower birth weight but nevertheless have an increased farrowing survival and early postnatal survival. Their increased survival cannot be explained by differences in progress of farrowing, early postnatal behavior, or rectal temperature within 24 h after birth.