Estimation of Pool Construction and Technical Error

John Keele, Tara McDaneld, Ty Lawrence, Jenny Jennings and Larry Kuehn
Additional contact information
John Keele: USDA, ARS, U.S. Meat Animal Research Center, P.O. Box 166, Clay Center, NE 68933, USA
Tara McDaneld: USDA, ARS, U.S. Meat Animal Research Center, P.O. Box 166, Clay Center, NE 68933, USA
Ty Lawrence: Department of Agricultural Sciences, West Texas A&M University, Canyon, TX 79016, USA
Jenny Jennings: Five Rivers Cattle Feeding, LLC, Amarillo, TX 79022, USA
Larry Kuehn: USDA, ARS, U.S. Meat Animal Research Center, P.O. Box 166, Clay Center, NE 68933, USA

Agriculture, 2021, vol. 11, issue 11, 1-11

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.

Keywords: DNA pooling; genomic relationship; genomic prediction (search for similar items in EconPapers)
JEL-codes: Q1 Q10 Q11 Q12 Q13 Q14 Q15 Q16 Q17 Q18 (search for similar items in EconPapers)
Date: 2021
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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