1. ¹Division of Animal Sciences, National Institute of Agrobiological Sciences, 2 Ikenodai, Tsukuba, Ibaraki, Japan
2. ²Data Mining and Grid Research Team, National Agricultural Research Center, Kannondai, Tsukuba, Ibaraki, Japan

Correspondence: Dr T Hayashi, Division of Animal Sciences, National Institute of Agrobiological Sciences, 2 Ikenodai, Tsukuba, Ibaraki 305-0901, Japan. E-mail: hayatk@affrc.go.jp

Received 18 August 2008; Revised 9 December 2008; Accepted 23 December 2008; Published online 11 February 2009.

Abstract

In some crop species, germplasm collections consisting of a large number of accessions that include traditional landraces, modern cultivars and wild species have recently been established. Such collections are regarded as useful stocks of genes for breeding programs. However, to efficiently utilize these collections for plant breeding, understanding genetic variation in agronomic traits at the QTL level between the accessions is indispensable. One effective way to extract the actual QTL information included in these collections is to perform QTL analysis jointly for multiple families derived from crossing some accessions of the collection with a single reference line such as a standard commercial variety. We developed a Bayesian method for jointly analyzing QTL in such interconnected multiple families derived from a set of inbred lines crossed to the reference line, to detect QTL segregating between any of the inbred lines and the reference line. In this study, we considered multiple recombinant inbred lines, each of which was derived from crossing each of the inbred lines to the reference line. The method was evaluated through the use of simulated data sets for its efficiency in detecting QTL and identifying families segregating at each QTL.