Estimation of pool construction and technical error

Authors: Keele, John; McDaneld, Tara; LAWRENCE, TY - West Texas A & M University; JENNINGS, JENNY - Five Rivers Cattle Feeding; Kuehn, Larry

Submitted to: Agriculture
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 11/1/2021
Publication Date: 11/4/2021
Citation: Keele, J., McDaneld, T., Lawrence, T., Jennings, J., Kuehn, L. 2021. Estimation of pool construction and technical error. Agriculture. 11(11). Article 1091. https://doi.org/10.3390/agriculture11111091.
DOI: https://doi.org/10.3390/agriculture11111091

Interpretive Summary: Management practices and environmental conditions in the commercial cattle sector are different than in the seedstock sector; hence, breeding values estimated from seedstock data may not correctly rank bulls for commercial performance of their progeny. Large numbers of commercial cattle can be inexpensively phenotyped in beef processing plants, feedlots, and cow calf operations. Pedigree is typically unknown in commercial cattle where cows are often bred in multi-sire pastures to improve fertility and pregnancy rate at a lower cost compared to single sire pastures or artificial insemination. Obtaining genotypes on large numbers of individual commercial cattle is prohibitively expensive. Pooling animals with extreme phenotypes can improve accuracy of genetic evaluation or provide genetic evaluation for novel traits at relatively low cost by exploiting large amounts of low-cost phenotypic data from animals in the commercial. Making pools from tissue requires only 1 DNA extraction per pool compared to many for all the animals in the pool. We estimate pool construction error based on combining liver tissue from the same animals with variable representations. Each animal is represented in 3 pools at 3 different planned contributions. Twelve pools were made with planned contributions varying from 1 to 40 %. Errors in representing each animal correctly increase with the planned contribution of an animal to a pool. Errors in estimating the representation of individual animals decreases with number of SNPs used to estimate. These results imply that limiting animal representation within pools (for instance by increasing numbers of animals per pool) and using multiple SNP in breeding value estimation can control these sources of error.

Technical Abstract: Pooling animals with extreme phenotypes can improve the accuracy of genetic evaluation or provide genetic evaluation for novel traits at relatively low cost by exploiting large amounts of low-cost phenotypic data from animals in the commercial sector without pedigree (data from commercial ranches, feedlots, stocker grazing or processing plants). The average contribution of each animal to a pool is inversely proportional to the number of animals in the pool or pool size. We constructed pools with variable planned contributions from each animal to approximate errors with different numbers of animals per pool. We estimate pool construction error based on combining liver tissue, from pulverized frozen tissue mass from multiple animals, into eight sub-pools containing four animals with planned proportionality (1:2:3:4) by mass. Sub-pools were then extracted for DNA and genotyped using a commercial array. The extracted DNA from the sub-pools was used to form super pools based on DNA concentration as measured by spectrophotometry with planned contribution of sub-pools of 1:2:3:4. We estimate technical error by comparing estimated animal contribution using sub-samples of single nucleotide polymorphism (SNP). Overall, pool construction error increased with planned contribution of individual animals. Technical error in estimating animal contributions decreased with the number of SNP used.