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DNA Research Advance Access published online on November 13, 2007
DNA Research, doi:10.1093/dnares/dsm020
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© The Author 2007. Kazusa DNA Research Institute.
The online version of this article has been published under an open access model. Users are entitled to use, reproduce, disseminate, or display the open access version of this article for non-commercial purposes provided that: the original authorship is properly and fully attributed; the Journal and Oxford University Press are attributed as the original place of publication with the correct citation details given; if an article is subsequently reproduced or disseminated not in its entirety but only in part or as a derivative work this must be clearly indicated. For commercial re-use, please contact journals.permissions@oxfordjournals.org

Genotype Matrix Mapping: Searching for Quantitative Trait Loci Interactions in Genetic Variation in Complex Traits

Sachiko Isobe1,3,*, Akihiro Nakaya2 and Satoshi Tabata3

1 National Agricultural Research Center for Hokkaido Region, Histujigaoka 1, Toyohira, Sapporo 062-8555, Japan
2 Department of computational Biology, The University of Tokyo, 5-1-5, Kashiwanoha, Kashiwa, Chiba 277-8561, Japan
3 Kazusa DNA Research Institute, Kazusa-Kamatari 2-6-7, Kisarazu, Chiba 292-0818, Japan

Received 25 July 2007 ; accepted 8 October 2007.

In order to reveal quantitative trait loci (QTL) interactions and the relationship between various interactions in complex traits, we have developed a new QTL mapping approach, named genotype matrix mapping (GMM), which searches for QTL interactions in genetic variation. The central approach in GMM is the following. (1) Each tested marker is given a virtual matrix, named a genotype matrix (GM), containing intersecting lines and rows equal to the total allele number for that marker in the population analyzed. (2) QTL interactions are then estimated and compared through virtual networks among the GMs. To evaluate the contribution of marker combinations to a quantitative phenotype, the GMM method divides the samples into two non-overlapping subclasses, S0 and S1; the former contains the samples that have a specific genotype pattern to be evaluated, and the latter contains samples that do not. Based on this division, the F-measure is calculated as an index of significance. With the GMM method, we extracted significant marker combinations consisting of one to three interacting markers. The results indicated there were multiple QTL interactions affecting the phenotype (flowering date). GMM will be a valuable approach to identify QTL interactions in genetic variation of a complex trait within a variety of organisms.

Key words: genotype matrix mapping; QTL interaction; genetic variation

* To whom correspondence should be addressed. Kazusa DNA Research Institute 2-6-7, Kazusa-Kamatari, Kisarazu, Chiba 292-0818, Japan. Tel. +81 438-52-3928. Fax +81 438-52-3934. E-mail: sisobe{at}kazusa.or.jp

Edited by Masahiro Yano


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