Staff Publications

Staff Publications

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    'Staff publications' is the digital repository of Wageningen University & Research

    'Staff publications' contains references to publications authored by Wageningen University staff from 1976 onward.

    Publications authored by the staff of the Research Institutes are available from 1995 onwards.

    Full text documents are added when available. The database is updated daily and currently holds about 240,000 items, of which 72,000 in open access.

    We have a manual that explains all the features 

Record number 442012
Title Multi-trait and multi-environment QTL analyses of yield and a set of physiological traits in pepper
Author(s) Alimi, N.A.; Bink, M.C.A.M.; Dieleman, J.A.; Magán, J.J.; Wubs, A.M.; Palloix, A.; Eeuwijk, F.A. van
Source Theoretical and Applied Genetics 126 (2013)10. - ISSN 0040-5752 - p. 2597 - 2625.
DOI https://doi.org/10.1007/s00122-013-2160-3
Department(s) Biometris (WU MAT)
Biometris (PPO/PRI)
WUR GTB Gewasfysiologie Management en Model
Horticultural Supply Chains
PE&RC
Publication type Refereed Article in a scientific journal
Publication year 2013
Keyword(s) mixed-model approach - capsicum-annuum - complex traits - fruit size - loci - populations - barley - maize - covariables - regression
Abstract 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.
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