title: Hot topic: Use of genomic recursions in single-step genomic best linear unbiased predictor (BLUP) with a large number of genotypes.
abstract: The purpose of this study was to evaluate the accuracy of genomic selection in single-step genomic BLUP (ssGBLUP) when the inverse of the genomic relationship matrix (G) is derived by the "algorithm for proven and young animals" (APY). This algorithm implements genomic recursions on a subset of "proven" animals. Only a relationship matrix for animals treated as "proven" needs to be inverted, and the extra costs of adding animals treated as "young" are linear. Analyses involved 10,102,702 final scores on 6,930,618 Holstein cows. Final score, which is a composite of type traits, is popular trait in the United States and was easily available for this study. A total of 100,000 animals with genotypes were used in the analyses and included 23,000 sires (16,000 with >5 progeny), 27,000 cows, and 50,000 young animals. Genomic EBV (GEBV) were calculated with a regular inverse of G, and with the G inverse approximated by APY. Animals in the proven subset included only sires (23,000), sires+cows (50,000), only cows (27,000), or sires with >5 progeny (16,000). The correlations of GEBV with APY and regular GEBV for young genotyped animals were 0.994, 0.995, 0.992, and 0.992, respectively Later, animals in the proven subset were randomly sampled from all genotyped animals in sets of 2,000, 5,000, 10,000, 15,000, and 20,000; each sample was replicated 4 times. Respective correlations were 0.97 (5,000 sample), 0.98 (10,000 sample), and 0.99 (20,000 sample), with minimal difference between samples of the same size. Genomic EBV with APY were accurate when the number of animals used in the subset is between 10,000 and 20,000, with little difference between the ways of creating the subset. Due to the approximately linear cost of APY, ssGBLUP with APY could support any number of genotyped animals without affecting accuracy.
authors: Department of Animal and Dairy Science, University of Georgia, Athens 30602. Electronic address: fragomen@uga.edu.
authors: B O
authors: BO
authors: Fragomeni
authors: Department of Animal and Dairy Science, University of Georgia, Athens 30602.
authors: D A L
authors: DA
authors: Lourenco
authors: Department of Animal and Dairy Science, University of Georgia, Athens 30602.
authors: S
authors: S
authors: Tsuruta
authors: Department of Animal and Dairy Science, University of Georgia, Athens 30602.
authors: Y
authors: Y
authors: Masuda
authors: Instituto Nacional de Investigacion Agropecuaria, Canelones, 90200, Uruguay.
authors: I
authors: I
authors: Aguilar
authors: INRA, UMR1388 GenePhySE, Castanet Tolosan, 31326, France.
authors: A
authors: A
authors: Legarra
authors: Holstein Association USA Inc., Brattleboro, VT 05302.
authors: T J
authors: TJ
authors: Lawlor
authors: Department of Animal and Dairy Science, University of Georgia, Athens 30602.
authors: I
authors: I
authors: Misztal
mesh_terms: D000465:Algorithms; D000818:Animals; D002417:Cattle / Q000235:genetics*; D005260:Female; D016678:Genome / Q000235:genetics*; D023281:Genomics; D005838:Genotype; D008297:Male; D010641:Phenotype; D013048:Specimen Handling / Q000662:veterinary; D014481:United States
keywords: genomic recursion; genomic selection; single-step method