Publications by authors named "Lawrence R Schaeffer"
Background: Egg production traits are economically important in poultry breeding programs. Previous studies have shown that incorporating genomic data can increase the accuracy of genetic prediction of egg production. Our objective was to estimate the genetic and phenotypic parameters of such traits and compare the prediction accuracy of pedigree-based random regression best linear unbiased prediction (RR-PBLUP) and genomic single-step random regression BLUP (RR-ssGBLUP).
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- * SNP genotypes were predicted for ungenotyped fish and showed that including these markers improved evaluations for weight and length in different environments while accounting for gender differences.
- * The use of a smaller number of SNP markers not only made genetic evaluations more cost-effective for large fish populations but also enhanced the understanding of within-family genetic variation compared to traditional methods.
The effects of additive, dominance, additive by dominance, additive by additive and dominance by dominance genetic effects on age at first service, non-return rates and interval from calving to first service were estimated. Practical considerations of computing additive and dominance relationships using the genomic relationship matrix are discussed. The final strategy utilized several groups of 1000 animals (heifers or cows) in which all animals had a non-zero dominance relationship with at least one other animal in the group.
View Article and Find Full Text PDFThe aim of this study was to compare the variance component approach for QTL linkage mapping in half-sib designs to the simple regression method. Empirical power was determined by Monte Carlo simulation in granddaughter designs. The factors studied (base values in parentheses) included the number of sires (5) and sons per sire (80), ratio of QTL variance to total genetic variance (lambda= 0.
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- A simulation study compared Bayesian estimation via Gibbs sampling and empirical BLUP (EBLUP) for analyzing fixed effects and breeding values in animal populations.
- The study considered various scenarios, including different simulation models, selection schemes, heritability levels, and amounts of missing pedigree information.
- Results showed that both methods produced similar correlations and patterns of bias and mean square error, with increased estimation error observed as generations progressed or with the presence of missing pedigree data.