Strategies for selecting crosses using genomic prediction in two wheat breeding programs

Bettina Lado, Sarah Battenfield, Carlos Guzmán, Martín Quincke, Ravi P. Singh, Susanne Dreisigacker, R. Javier Peña, Allan Fritz, Paula Silva, Jesse Poland, Lucía Gutiérrez

Research output: Contribution to journalArticlepeer-review

36 Scopus citations

Abstract

The single most important decision in plant breeding programs is the selection of appropriate crosses. The ideal cross would provide superior predicted progeny performance and enough diversity to maintain genetic gain. The aim of this study was to compare the best crosses predicted using combinations of mid-parent value and variance prediction accounting for linkage disequilibrium (VLD) or assuming linkage equilibrium (VLE). After predicting the mean and the variance of each cross, we selected crosses based on mid-parent value, the top 10% of the progeny, and weighted mean and variance within progenies for grain yield, grain protein content, mixing time, and loaf volume in two applied wheat (Triticum aestivum L.) breeding programs: Instituto Nacional de Investigación Agropecuaria (INIA) Uruguay and CIMMYT Mexico. Although the variance of the progeny is important to increase the chances of finding superior individuals from transgressive segregation, we observed that the mid-parent values of the crosses drove the genetic gain but the variance of the progeny had a small impact on genetic gain for grain yield. However, the relative importance of the variance of the progeny was larger for quality traits. Overall, the genomic resources and the statistical models are now available to plant breeders to predict both the performance of breeding lines per se as well as the value of progeny from any potential crosses.
Original languageEnglish (US)
JournalPlant Genome
Volume10
Issue number2
DOIs
StatePublished - Jan 1 2017
Externally publishedYes

Bibliographical note

Generated from Scopus record by KAUST IRTS on 2022-09-13

ASJC Scopus subject areas

  • Genetics
  • Agronomy and Crop Science
  • Plant Science

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