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.

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Record number 387599
Title Mixed model approaches for the identification of QTLs within a maize hybrid breeding program.
Author(s) Eeuwijk, F.A. van; Boer, M.; Totir, L.; Bink, M.C.A.M.; Wright, D.; Winkler, C.; Podlich, D.; Boldman, K.; Baumgarten, R.; Smalley, M.; Arbelbide, M.; Braak, C.J.F. ter; Cooper, M.
Source Theoretical and Applied Genetics 120 (2010)2. - ISSN 0040-5752 - p. 429 - 440.
DOI https://doi.org/10.1007/s00122-009-1205-0
Department(s) Mathematical and Statistical Methods - Biometris
Leerstoel Maatschappelijke aspecten van biologische landbouw
PRI Biometris
PE&RC
Publication type Refereed Article in a scientific journal
Publication year 2010
Keyword(s) quantitative trait loci - linear unbiased prediction - single-cross performance - environmental covariables - genomewide selection - variance-components - plant-populations - marker data - heterosis - pedigree
Abstract Two outlines for mixed model based approaches to quantitative trait locus (QTL) mapping in existing maize hybrid selection programs are presented: a restricted maximum likelihood (REML) and a Bayesian Markov Chain Monte Carlo (MCMC) approach. The methods use the in-silico-mapping procedure developed by Parisseaux and Bernardo (2004) as a starting point. The original single-point approach is extended to a multi-point approach that facilitates interval mapping procedures. For computational and conceptual reasons, we partition the full set of relationships from founders to parents of hybrids into two types of relations by defining so-called intermediate founders. QTL effects are defined in terms of those intermediate founders. Marker based identity by descent relationships between intermediate founders define structuring matrices for the QTL effects that change along the genome. The dimension of the vector of QTL effects is reduced by the fact that there are fewer intermediate founders than parents. Furthermore, additional reduction in the number of QTL effects follows from the identification of founder groups by various algorithms. As a result, we obtain a powerful mixed model based statistical framework to identify QTLs in genetic backgrounds relevant to the elite germplasm of a commercial breeding program. The identification of such QTLs will provide the foundation for effective marker assisted and genome wide selection strategies. Analyses of an example data set show that QTLs are primarily identified in different heterotic groups and point to complementation of additive QTL effects as an important factor in hybrid performance
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