Accuracy of GEBV of sires based on pooled allele frequency of their progeny

Authors: VARGAS JURADO, NAPOLEON - University Of Nebraska; Kuehn, Larry; Keele, John; LEWIS, RONALD - University Of Nebraska

Submitted to: G3, Genes/Genomes/Genetics
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 6/17/2021
Publication Date: 7/14/2021
Citation: Vargas Jurado, N., Kuehn, L.A., Keele, J.W., Lewis, R.M. 2021. Accuracy of GEBV of sires based on pooled allele frequency of their progeny. G3, Genes/Genomes/Genetics. 11(11). Article jkab231. https://doi.org/10.1093/g3journal/jkab231.
DOI: https://doi.org/10.1093/g3journal/jkab231

Interpretive Summary: Utilization of high-density arrays has dramatically increased the utilization of genomic data in genetic evaluation of livestock species. However, the cost of genotyping can still prevent full utilization of genomic information. Genotyping groups of animals using DNA pooling provides a low-cost alternative to individual animal genotyping. This study examines the relative accuracy of several different pooling strategies (differing pool sizes and allocations of animals into pools). Non-random pooling using combinations of phenotypic data and animal relatedness was shown to improve accuracy of predicting genetic merit relative to random pooling. Pool sizes of 25 animals or greater performed similarly. These strategies can be used to genotype groups of animals for use in genetic evaluation when animals have unknown pedigree or genomic linkages.

Technical Abstract: Despite decreasing genotyping costs, in some cases individually genotyping animals is not economically feasible (e.g., in small ruminants). An alternative is to pool DNA, using the pooled allele frequency (PAF) to garner information on performance. Still, the use of PAF for prediction (estimation of genomic breeding values; GEBVs) has been limited. Two potential sources of error on accuracy of GEBV of sires, obtained from PAF of their progeny themselves lacking pedigree information, were tested: (i) pool construction error (unequal contribution of DNA from animals in pools), and (ii) technical error (variability when reading the array). Pooling design (random, extremes, K-means), pool size (5, 10, 25, 50, and 100 individuals), and selection scenario (random, phenotypic) also were considered. These factors were tested by simulating a sheep population. Accuracy of GEBV—the correlation between true and estimated values—was not substantially affected by pool construction or technical error, or selection scenario. A significant interaction, however, between pool size and design was found. Still, regardless of design, mean accuracy was higher for pools of 10 or less individuals. Mean accuracy of GEBV was 0.174 (SE 0.001) for random pooling, and 0.704 (SE 0.004) and 0.696 (SE 0.004) for extreme and K-means pooling, respectively. Non-random pooling resulted in moderate accuracy of GEBV. Overall, pooled genotypes can be used in conjunction with individual genotypes of sires for moderately accurate predictions of their genetic merit with little effect of pool construction or technical error.