Dimensionality of genomic information and performance of the Algorithm for Proven and Young for different livestock species

Ivan Pocrnic, Daniela A. L. Lourenco, Yutaka Masuda, Ignacy Misztal

Research output: Contribution to journalArticlepeer-review

Abstract

Background: A genomic relationship matrix (GRM) can be inverted efficiently with the Algorithm for Proven and
Young (APY) through recursion on a small number of core animals. The number of core animals is theoretically linked
to effective population size (Ne). In a simulation study, the optimal number of core animals was equal to the number
of largest eigenvalues of GRM that explained 98% of its variation. The purpose of this study was to find the optimal
number of core animals and estimate Ne for different species.
Methods: Datasets included phenotypes, pedigrees, and genotypes for populations of Holstein, Jersey, and Angus
cattle, pigs, and broiler chickens. The number of genotyped animals varied from 15,000 for broiler chickens to 77,000
for Holsteins, and the number of single-nucleotide polymorphisms used for genomic prediction varied from 37,000 to
61,000. Eigenvalue decomposition of the GRM for each population determined numbers of largest eigenvalues corresponding
to 90, 95, 98, and 99% of variation.
Results: The number of eigenvalues corresponding to 90% (98%) of variation was 4527 (14,026) for Holstein, 3325
(11,500) for Jersey, 3654 (10,605) for Angus, 1239 (4103) for pig, and 1655 (4171) for broiler chicken. Each trait in each
species was analyzed using the APY inverse of the GRM with randomly selected core animals, and their number was
equal to the number of largest eigenvalues. Realized accuracies peaked with the number of core animals corresponding
to 98% of variation for Holstein and Jersey and closer to 99% for other breed/species. Ne was estimated based on
comparisons of eigenvalue decomposition in a simulation study. Assuming a genome length of 30 Morgan, Ne was
equal to 149 for Holsteins, 101 for Jerseys, 113 for Angus, 32 for pigs, and 44 for broilers.
Conclusions: Eigenvalue profiles of GRM for common species are similar to those in simulation studies although
they are affected by number of genotyped animals and genotyping quality. For all investigated species, the APY
required less than 15,000 core animals. Realized accuracies were equal or greater with the APY inverse than with regular
inversion. Eigenvalue analysis of GRM can provide a realistic estimate of Ne.
Original languageEnglish
JournalGenetics Selection Evolution
Volume48
DOIs
Publication statusPublished - 31 Oct 2016

Fingerprint

Dive into the research topics of 'Dimensionality of genomic information and performance of the Algorithm for Proven and Young for different livestock species'. Together they form a unique fingerprint.

Cite this