Selection of core animals in the Algorithm for Proven and Young using a simulation model.

HL Bradford, Ivan Pocrnic, BO Fragomeni, DAL Lourenco, I Misztal

Research output: Contribution to journalArticlepeer-review

Abstract / Description of output

The Algorithm for Proven and Young (APY) enables the implementation of single-
step genomic BLUP (ssGBLUP) in large, genotyped populations by separating
genotyped animals into core and non-core subsets and creating a computationally
efficient inverse for the genomic relationship matrix (G). As APY became the
choice for large-scale genomic evaluations in BLUP-based methods, a common
question is how to choose the animals in the core subset. We compared several
core definitions to answer this question. Simulations comprised a moderately heritable
trait for 95,010 animals and 50,000 genotypes for animals across five generations.
Genotypes consisted of 25,500 SNP distributed across 15 chromosomes.
Genotyping errors and missing pedigree were also mimicked. Core animals were
defined based on individual generations, equal representation across generations,
and at random. For a sufficiently large core size, core definitions had the same
accuracies and biases, even if the core animals had imperfect genotypes. When
genotyped animals had unknown parents, accuracy and bias were significantly
better (p ≤ .05) for random and across generation core definitions.
Original languageEnglish
JournalJournal of Animal Breeding and Genetics
Volume134
Issue number6
Early online date2 May 2017
DOIs
Publication statusPublished - Dec 2017

Keywords / Materials (for Non-textual outputs)

  • APY
  • genetic evaluation
  • genomic selection
  • imputation
  • single-step genomic BLUP

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