Optimizing Selection on Major Genes

Molecular genetics technology is leading to the discovery of individual genes with large effects for traits of interest in swine. Although the use of such major genes can enhance rates of genetic improvement in the short term, their injudicious use can lead to less response to selection in the longer term. This article describes the development of a method to optimize the use of a major gene in selection. Results show that optimal strategies for selection on the major gene can lead to increased response to selection, in particular for major genes that show dominance. The results imply that major genes can substantially enhance rates of genetic improvement in both the short and long term, provided selection on the major gene is integrated properly within existing selection strategies. Thus, the use of major genes in selection, requires careful formulation of the objectives and strategies for selection. The methods developed in this research provide a framework to formulate such strategies. Further extension of methods to deal with the complexities of practical breeding programs is, however, required

Breeding values for identified quantitative trait loci under selection

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Optimizing purebred selection for crossbred performance using QTL with different degrees of dominance

A method was developed to optimize simultaneous selection for a quantitative trait with a known QTL within a male and a female line to maximize crossbred performance from a two-way cross. Strategies to maximize cumulative discounted response in crossbred performance over ten generations were derived by optimizing weights in an index of a QTL and phenotype. Strategies were compared to selection on purebred phenotype. Extra responses were limited for QTL with additive and partial dominance effects, but substantial for QTL with over-dominance, for which optimal QTL selection resulted in differential selection in male and female lines to increase the frequency of heterozygotes and polygenic responses. For over-dominant QTL, maximization of crossbred performance one generation at a time resulted in similar responses as optimization across all generations and simultaneous optimal selection in a male and female line resulted in greater response than optimal selection within a single line without crossbreeding. Results show that strategic use of information on over-dominant QTL can enhance crossbred performance without crossbred testing

Dealing with Errors in Data from Electronic Swine Feeders

Data from electronic swine feeders contain errors that must be identified, edited, and corrected. The objectives of this study were to develop comprehensive criteria to identify errors in feed intake data from FIRE electronic feeders and to compare the ability of five editing methods to accurately estimate daily feed intake (DFI) and average daily feed intake (ADFI). Data from FIRE feeders on 591 pigs from the National Pork Board’s Maternal Line Genetic Evaluation Program were used. Errors in each visit were identified using 16 criteria. To create an error-free data set as a basis for comparison, data from 124 pigs with few errors were selected and visits with errors were replaced by error-free visits from the same pig. Resulting DFI and ADFI were assumed to be the true trait values. Error visits were then introduced, representative of field data. Data were edited using five methods (EM1-5). For EM1, a DFI record was deleted if DFI \u3c 1000 g or \u3e4500 g. For EM2-5, the 16 criteria were used to identify errors in each visit. For EM2 and 3, all DFI records with \u3e1 and \u3e2 error visits were deleted. For EM4-5, DFI was obtained by summing feed intake over error-free visits. For EM5, DFI records were then adjusted for the effects of presence of error visits on unadjusted DFI, which were estimated from a linear model analysis. For EM1-4, missing DFI records were replaced by linear regression estimates of DFI on test day for each pig. DFI and ADFI from the edited data sets were correlated to true values. Correlations were high (.90 to .99) for both traits for all editing methods except EM1. EM5 had the highest correlation for DFI (.99). EM2 and EM5 had the highest correlations for ADFI (.98 to .99). EM1 had the lowest correlations for both traits (.82 to .93). Results indicate that editing methods affect the accuracy of data from electronic feeders. EM5 is recommended for maximum accuracy for DFI and EM2 is recommended for ADFI for maximum accuracy and ease of implementation

Regression on markers with uncertain allele transmission for QTL mapping in half-sib designs

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Performance of Growing Pigs Fed Using Electronic Versus Commercial Feeders

The effect of electronic feeders on performance of growing boars and gilts was evaluated. Yorkshire boars and gilts (n=475) were randomly assigned to pens with single-space FIRE (electronic) feeders and pens with fivespace SMIDLEY feeders. Pigs began and ended test at an average body weight of 39 and 116 kg. Over the whole test period, pigs on electronic feeders did not differ significantly in growth rate, backfat thickness, and loin muscle area from pigs on commercial feeders. They did, however, use less feed and converted this more efficiently. Further inspection of growth and feed intake curves revealed that gilts on electronic feeders used less feed and grew slightly slower, in particular during early growth, but no differences were found for boars. Results indicate that electronic feeders may cause a genotype by environment interaction for gilts but not for boars

Accuracy of Genomic Prediction when Accounting for Population Structure and Polygenic Effects

Accuracy of genomic estimated breeding values obtained using the standard marker effect model was compared with models that account for population structure, either by applying a transmission disequilibrium test (TDT) approach or by fitting polygenic effects. The TDT approach was inferior to the standard model, whereas fitting polygenic effects in addition to marker effects increased the accuracy of estimated breeding values of the progeny of training individuals but also seven generations after training. Thus, fitting polygenic effects enhances utilization of genomic information both in the short and long-term

Optimal selection on two quantitative trait loci with linkage

A mathematical approach to optimize selection on multiple quantitative trait loci (QTL) and an estimate of residual polygenic effects was applied to selection on two linked or unlinked additive QTL. Strategies to maximize total or cumulative discounted response over ten generations were compared to standard QTL selection on the sum of breeding values for the QTL and an estimated breeding value for polygenes, and to phenotypic selection. Optimal selection resulted in greater response to selection than standard QTL or phenotypic selection. Tight linkage between the QTL (recombination rate 0.05) resulted in a slightly lower response for standard QTL and phenotypic selection but in a greater response for optimal selection. Optimal selection capitalized on linkage by emphasizing selection on favorable haplotypes. When the objective was to maximize total response after ten generations and QTL were unlinked, optimal selection increased QTL frequencies to fixation in a near linear manner. When starting frequencies were equal for the two QTL, equal emphasis was given to each QTL, regardless of the difference in effects of the QTL and regardless of the linkage, but the emphasis given to each of the two QTL was not additive. These results demonstrate the ability of optimal selection to capitalize on information on the complex genetic basis of quantitative traits that is forthcoming

Analysis of Body Weight and Feed Intake Curves in Selection Lines for Residual Feed Intake in Pigs

A selection experiment for reducing residual feed intake (RFI= feed consumed over and above expected requirements for production and maintenance) in Yorkshire pigs consists of a line selected for lower RFI (LRFI) and a random control line (CTRL). Using 64 LRFI and 87 CTRL boars from generation 5 of the selection experiment, cubic polynomial random regression with heterogeneous residual variance for daily feed intake (DFI) and with homogeneous residual variance for bi-weekly body weight (BW) were identified as the best linear mixed models to describe feed intake and body weight curves. Based on the Gompertz model, significant differences in the decay parameter for DFI and in mature body weight and the inflection point for BW were observed between the lines. In conclusion, selection for lower RFI has resulted in a lower feed intake curve toward maturity, lower mature body weight, and earlier inflection points for growth