Multi-trait and multi-environment QTL analyses of yield and a set of physiological traits in pepper

N.A. Alimi, M.C.A.M. Bink, J.A. Dieleman, J.J. Magán, A.M. Wubs, A. Palloix, F.A. van Eeuwijk

Research output: Contribution to journalArticleAcademicpeer-review

33 Citations (Scopus)


For many agronomic crops, yield is measured simultaneously with other traits across multiple environments. The study of yield can benefit from joint analysis with other traits and relations between yield and other traits can be exploited to develop indirect selection strategies. We compare the performance of three multi-response QTL approaches based on mixed models: a multi-trait approach (MT), a multi-environment approach (ME), and a multi-trait multi-environment approach (MTME). The data come from a multi-environment experiment in pepper, for which 15 traits were measured in four environments. The approaches were compared in terms of number of QTLs detected for each trait, the explained variance, and the accuracy of prediction for the final QTL model. For the four environments together, the superior MTME approach delivered a total of 47 regions containing putative QTLs. Many of these QTLs were pleiotropic and showed quantitative QTL by environment interaction. MTME was superior to ME and MT in the number of QTLs, the explained variance and accuracy of predictions. The large number of model parameters in the MTME approach was challenging and we propose several guidelines to help obtain a stable final QTL model. The results confirmed the feasibility and strengths of novel mixed model QTL methodology to study the architecture of complex traits.
Original languageEnglish
Pages (from-to)2597-2625
JournalTheoretical and Applied Genetics
Issue number10
Publication statusPublished - 2013


  • mixed-model approach
  • capsicum-annuum
  • complex traits
  • fruit size
  • loci
  • populations
  • barley
  • maize
  • covariables
  • regression


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