A genomic selection index applied to simulated and real data

J. Jesus Ceron-Rojas, José Crossa, Vivi N. Arief, Kaye Basford, Jessica Rutkoski, Diego Jarquín, Gregorio Alvarado, Yoseph Beyene, Kassa Semagn, Ian DeLacy

Research output: Contribution to journalArticlepeer-review


A genomic selection index (GSI) is a linear combination of genomic estimated breeding values that uses genomic markers to predict the net genetic merit and select parents from a nonphenotyped testing population. Some authors have proposed a GSI; however, they have not used simulated or real data to validate the GSI theory and have not explained how to estimate the GSI selection response and the GSI expected genetic gain per selection cycle for the unobserved traits after the first selection cycle to obtain information about the genetic gains in each subsequent selection cycle. In this paper, we develop the theory of a GSI and apply it to two simulated and four real data sets with four traits. Also, we numerically compare its efficiency with that of the phenotypic selection index (PSI) by using the ratio of the GSI response over the PSI response, and the PSI and GSI expected genetic gain per selection cycle for observed and unobserved traits, respectively. In addition, we used the Technow inequality to compare GSI vs. PSI efficiency. Results from the simulated data were confirmed by the real data, indicating that GSI was more efficient than PSI per unit of time.

Original languageEnglish (US)
Pages (from-to)2155-2164
Number of pages10
JournalG3: Genes, Genomes, Genetics
Issue number10
StatePublished - 2015
Externally publishedYes


  • Genomic estimated breeding value
  • Genomic selection
  • GenPred
  • Net genetic merit
  • Selection index
  • Selection response
  • Shared data resource

ASJC Scopus subject areas

  • Molecular Biology
  • Genetics
  • Genetics(clinical)


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