Theoretical and Applied Genetics

, Volume 126, Issue 1, pp 13–22 | Cite as

Genomewide predictions from maize single-cross data

  • Jon M. Massman
  • Andres Gordillo
  • Robenzon E. Lorenzana
  • Rex BernardoEmail author
Original Paper


Maize (Zea mays L.) breeders evaluate many single-cross hybrids each year in multiple environments. Our objective was to determine the usefulness of genomewide predictions, based on marker effects from maize single-cross data, for identifying the best untested single crosses and the best inbreds within a biparental cross. We considered 479 experimental maize single crosses between 59 Iowa Stiff Stalk Synthetic (BSSS) inbreds and 44 non-BSSS inbreds. The single crosses were evaluated in multilocation experiments from 2001 to 2009 and the BSSS and non-BSSS inbreds had genotypic data for 669 single nucleotide polymorphism (SNP) markers. Single-cross performance was predicted by a previous best linear unbiased prediction (BLUP) approach that utilized marker-based relatedness and information on relatives, and from genomewide marker effects calculated by ridge-regression BLUP (RR-BLUP). With BLUP, the mean prediction accuracy (r MG) of single-cross performance was 0.87 for grain yield, 0.90 for grain moisture, 0.69 for stalk lodging, and 0.84 for root lodging. The BLUP and RR-BLUP models did not lead to r MG values that differed significantly. We then used the RR-BLUP model, developed from single-cross data, to predict the performance of testcrosses within 14 biparental populations. The r MG values within each testcross population were generally low and were often negative. These results were obtained despite the above-average level of linkage disequilibrium, i.e., r 2 between adjacent markers of 0.35 in the BSSS inbreds and 0.26 in the non-BSSS inbreds. Overall, our results suggested that genomewide marker effects estimated from maize single crosses are not advantageous (compared with BLUP) for predicting single-cross performance and have erratic usefulness for predicting testcross performance within a biparental cross.


Quantitative Trait Locus Single Nucleotide Polymorphism Marker General Combine Ability Specific Combine Ability Heterotic Group 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Supplementary material

122_2012_1955_MOESM1_ESM.pdf (64 kb)
Supplementary material 1 (PDF 63 kb)


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Copyright information

© Springer-Verlag 2012

Authors and Affiliations

  • Jon M. Massman
    • 1
  • Andres Gordillo
    • 2
  • Robenzon E. Lorenzana
    • 2
  • Rex Bernardo
    • 1
    Email author
  1. 1.Department of Agronomy and Plant GeneticsUniversity of MinnesotaSaint PaulUSA
  2. 2.AgReliant GeneticsWestfieldUSA

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