Molecular Breeding

, Volume 32, Issue 3, pp 533–546 | Cite as

High-density linkage mapping of yield components and epistatic interactions in maize with doubled haploid lines from four crosses

  • M. Stange
  • T. A. Schrag
  • H. F. Utz
  • C. Riedelsheimer
  • E. Bauer
  • A. E. MelchingerEmail author


Grain yield (GY) is a genetically complex and physiologically multiplicative trait which can be decomposed into the components kernel number (KN) and 100-kernel weight (HKW). Genetic analysis of these less complex yield component traits may give insights into the genetic architecture and predictive ability of complex traits. Here, we investigated how the incorporation of component traits and epistasis in quantitative trait locus (QTL) mapping approaches influences the accuracy of GY prediction. High-density genetic maps with 7,000–10,000 polymorphic single nucleotide polymorphisms were constructed for four biparental populations. The populations comprised between 99 and 227 doubled haploid maize lines which were phenotyped in field trials in two environments. Heritability was highest for HKW (88–89 %), intermediate for KN (72–80 %), and lowest for GY (64–83 %). Mapped QTL explained in total 21–55 %, 22–67 %, and 24–75 % of the genotypic variance for GY, KN, and HKW, respectively. Support intervals of QTL were short, indicating that QTL were located with high precision. Co-located QTLs with same parental origin of favorable alleles were detected within populations for different traits and between populations for the same traits. Using GY predictions based on the detected QTL, prediction accuracies (r) determined by cross validation ranged from 0.18 to 0.52. Epistatic models did not outperform the corresponding additive models. In conclusion, models based on QTL positions of component traits support the identification of favorable alleles for multiplicative traits and provide a basis to select superior inbred lines by marker-assisted breeding.


QTL High-density Epistasis Maize Grain yield 



This research was supported by funds from DFG (Grant No. 1070, International Research Training Group “Sustainable Resource Use in North China”) to Albrecht E. Melchinger and BMBF (Project CornFed, “Integration of advanced mapping and phenotyping methods to identify key alleles for building European maize ideotypes”) to Albrecht E. Melchinger (Grant No. 0315461A) and Chris C. Schön, Technische Universität München (Grant No. 0315461B). Results have been achieved within the framework of the Transnational (Germany, France, Spain) Cooperation within the PLANT-KBBE Initiative Cornfed, with funding from Agence Nationale de la Recherche (ANR), Ministry of Science and Innovation (Ministerio de Ciencia e Innovación, MICINN), and the Federal Ministry of Education and Research (BMBF).

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Copyright information

© Springer Science+Business Media Dordrecht 2013

Authors and Affiliations

  • M. Stange
    • 1
  • T. A. Schrag
    • 1
  • H. F. Utz
    • 1
  • C. Riedelsheimer
    • 1
  • E. Bauer
    • 2
  • A. E. Melchinger
    • 1
    Email author
  1. 1.Institute of Plant Breeding, Seed Science and Population GeneticsUniversity of HohenheimStuttgartGermany
  2. 2.Plant BreedingTechnische Universität MünchenFreisingGermany

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