Ever since its first release in 1999, the free software package for visualization of molecular marker data, graphical genotype (GGT), has been constantly adapted and improved. The GGT package was developed in a plant-breeding context and thus focuses on plant genetic data but was not intended to be limited to plants only. The current version has many options for genetic analysis of populations including diversity analyses and simple association studies. A second release of the GGT package, GGT 2.0 (available through http://www.plantbreeding.wur.nl), is therefore presented in this paper. An overview of existing and new features that are available within GGT 2.0, and a case study in which GGT 2.0 is applied to analyze an existing set of plant genetic data, are presented and discussed.

At the Laboratory of Plant Breeding of Wageningen University, a large amount of pedigree data on current and historic potato cultivars and progenitors has been collected over many years. The sources and reasons for collection of these data are discussed. To allow others to use this data set for their own purposes, we have created a Web-accessible interface that allows querying of these data, e.g., for the ancestry of a cultivar of interest. This Web interface was recently extended and improved to allow users to create reports and dynamically created pedigree-tree images. Availability of this resource and the options provided by the new Web interface are presented.

No abstract

Within the Dutch genomics initiative the "Centre for Biosystems Genomics" (CBSG) a major research eVort is directed at the identiWcation and unraveling of processes and mechanisms aVecting fruit quality in tomato. The basis of this fruit quality program was a diverse set of 94 cultivated tomato cultivars, representing a wide spectrum of phenotypes for quality related traits. This paper describes a diversity study performed on these cultivars, using information of 882 AFLP markers, of which 304 markers had a known map position. The AFLP markers were scored as much as possible in a co-dominant fashion. We investigated genome distribution and coverage for the mapped markers and conclude that it proved diYcult to arrive at a dense and uniformly distributed coverage of the genome with markers. Mapped markers and unmapped markers were used to investigate population structure. A clear substructure was observed which seemed to coincide with a grouping based on fruit size. Finally, we studied amount and decay of linkage disequilibrium (LD) along the chromosomes. LD was observed over considerable (genetic) distances. We discuss the feasibility of markertrait association studies and conclude that the amount of genetic variation in our set of cultivars is limited, but that there exists scope for association studies.

Network analysis of correlations between abundances of metabolites across tomato genotypes can help in unraveling the biological basis of organoleptic variation in tomato. We illustrate how to construct and interpret simple correlations networks using metabolic data collected on a diverse set of tomato genotypes. Various types of correlations are calculated and displayed in the form of networks. Interpretations on the basis of network analyses are compared to interpretations following principal components analysis.