PSI-B-21 Alternative SNP weighting for multi-step and single-step genomic BLUP in the presence of causative variants

This study aimed to evaluate the accuracy of genomic prediction with simulated data, using SNP markers, causal quantitative trait nucleotide (QTN), and the combination of both. The methods used were the best linear unbiased prediction (GBLUP) and single-step GBLUP (ssGBLUP), with alternative SNP weights. Data were simulated using the package AlphasimR. Trait heritability of 0.3 was assumed, and genetic variance was fully accounted for by 100 or 1000 QTNs. A population with an effective size of 200 was selected, and 20 generations were simulated. The genomic information mimicked the 29 bovine chromosomes and included 50k SNP markers evenly distributed across the genome. Approximately 16800 genotypes were available from selected sires and dams in generations 16–19, and 2000 animals in generation 20. Phenotypes for young animals were not included in the analysis, as they were used in the validation. For GBLUP, three pseudo-phenotypes were considered: the raw phenotype, the true breeding value, and the true breeding value with noise added. The genomic relationship matrix was weighted using quadratic weights, calculated based on the SNP variance, and non-linear A, following different equation parameters. The scenario with exclusively causal variants presented accuracies close to 1 for 100 QTL, and slightly lower in the 1000 QTL. For the SNP + QTN scenario, quadratic weights promoted higher accuracy gains than the SNPs alone, especially in the 100 QTN trait. Accuracies converged at higher values for both quadratic and non-linear A weights in the 100 QTN scenario. For the 1000 QTN trait, quadratic weights diverged and reduced accuracy, while non-linear A maintained accuracy at their peaks, depending on the equation parameters. Parameters of non-linear A for highest accuracy were different in each scenario and type of analysis. Proportionally, gains in accuracy were more prominent with GBLUP than with ssGBLUP.

Restricted Selection Index to Relieve the Negative Repercussion in Reproductive Performance of Holstein Cows

The aim of this investigation was to develop restricted selection index aiming to improve 305-day yields of milk (MY), fat (FY) and protein (PY), while keeping the deterioration in days open (DO), calving interval (CI) and number of services per conception (NSPC) at minimum levels in Holstein cows. The data represent 3682 records of 1122 cows, daughters of 95 sires and 712 dams. The data were analyzed by multi-trait animal model with repeated measures. Eight selection indexes (five unrestricted and three restricted) were derived using MY, FY, PY, CI, DO and NSPC in various combinations as sources of information in the indexes. However, the true breeding value included MY, FY and PY. The highest accuracy of selection (0.60) resulted from selection based on the full index. Milk yield and SPC appeared to be the most valuable traits in the full index. Combining the two traits into one index (the best reduced index) gave 0.57 accuracy of selection. The index based on MY alone (the most accurate single trait index) gave 0.53 accuracy. It seems possible to reduce the expected genetic deterioration in the reproductive traits by restricting the full index to result in zero genetic change in NSPC (rTI=0.48). This restriction will allow the breeder to mitigate the deterioration in DO and CI by 12 and 16 days respectively, by sacrificing with part of the expected genetic improvement in productive traits (29, 40 and 48% in MY, FY and PY, respectively).

Estimates of genetic parameters for physic nut traits based in the germplasm two years evaluation

In spite of increasingly widespread interest in planting physic nut, breeding efforts are still in its infancy. In that context, an important resource recently established aiming future breeding efforts was the assembly of a germplasm bank with near 200 accessions. The objective of this study was to estimate genetic parameters, repeatibility coefficients and genetic correlation between seven traits, measured in 110 accessions (half sib families) of this germplasm bank in different stages of development. The results show that higher relative values of additive variance were only found for yield and height, and the existence of low environmental variation (either of temporary or permanent nature) among plots within blocks. Given the high repeatibility values found for all traits, on average three measurements are necessary to predict, accurately and efficiently, the true breeding value of an individual. Based on the results of genetic correlations, breeding effort should initially be use track trees with increased stem diameter, elevated number of branches and canopy volume so as to increase the chances of finding an exceptionally highly productive tree.