Parameters affecting genome simulation for evaluating genomic selection method

Motohide Nishio, Masahiro Satoh

Research output: Contribution to journalArticlepeer-review

2 Citations (Scopus)

Abstract

The present study investigated the parameter settings for obtaining a simulated genome at steady state of allele frequency (mutation-drift equilibrium) and linkage disequilibrium (LD), and evaluated the impact of whether or not the simulated genome reached steady state of allele frequency and LD on the accuracy of genomic estimated breeding values (GEBVs). After 500 to 50000 historical generations, the base population and subsequent seven generations were generated as recent populations. The allele frequency distribution of the last generations of the historical population and LD in the base population were calculated when varying the values of five parameters: initial minor allele frequency, mutation rate, effective population size, number of markers and chromosome length. The accuracies of GEBVs in the last generation of the recent population were calculated by genomic best linear unbiased prediction. The number of historical generations required to reach mutation-drift equilibrium depended on the initial allele frequency and mutation rate. Regardless of the parameters, LD reached a steady state before allele frequency distribution reached mutation-drift equilibrium. The accuracies of GEBVs largely reflect the extent of linkage disequilibrium with the exception of varying chromosome length, although there were no associations between the accuracies of GEBVs and allele frequency distribution.

Original languageEnglish
Pages (from-to)879-887
Number of pages9
JournalAnimal Science Journal
Volume85
Issue number10
DOIs
Publication statusPublished - 2014 Oct 1
Externally publishedYes

Keywords

  • Accuracy
  • Allele frequency
  • Genomic selection
  • Linkage disequilibrium
  • Simulation

ASJC Scopus subject areas

  • Agricultural and Biological Sciences(all)

Fingerprint Dive into the research topics of 'Parameters affecting genome simulation for evaluating genomic selection method'. Together they form a unique fingerprint.

Cite this