Identification of SSR markers associated with height using pool-based genome-wide association mapping in sorghum

Sorghum has been proposed as a potential energy crop. However, it has been traditionally bred for grain yield and forage quality, not traits related to bioenergy production. To develop tools for genetic improvement of bioenergy-related traits such as height, genetic markers associated with these traits have first to be identified. Association mapping has been extensively used in humans and in some crop plants for this purpose. However, genome-wide association mapping using the whole association panel is costly and time-consuming. A variation of this method called pool-based genome-wide association mapping has been extensively used in humans. In this variation, pools of individuals with contrasting phenotypes, instead of the whole panel, are screened with genetic markers and polymorphic markers are confirmed by screening the individuals in the pools. Here, we identified several new simple sequence repeats (SSR) markers associated with height using this pool-based genome-wide association mapping in sorghum. After screening the tall and short pools of sorghum accessions from the sorghum Mini Core collection developed at the International Crops Research Institute for the Semi-Arid Tropics with 703 SSR markers, we have identified four markers that are closely associated with sorghum height on chromosomes 2, 6, and 9. Comparison with published maps indicates that all four markers are clustered with markers previously mapped to height or height-related traits and with candidate genes involved in regulating plant height such as FtsZ, Ugt, and GA 2-oxidase. The mapping method can be applied to other crop plants for which a high-throughput genome-wide association mapping platform is not yet available

Simcluster: clustering enumeration gene expression data on the simplex space

Transcript enumeration methods such as SAGE, MPSS, and sequencing-by-synthesis EST "digital northern", are important high-throughput techniques for digital gene expression measurement. As other counting or voting processes, these measurements constitute compositional data exhibiting properties particular to the simplex space where the summation of the components is constrained. These properties are not present on regular Euclidean spaces, on which hybridization-based microarray data is often modeled. Therefore, pattern recognition methods commonly used for microarray data analysis may be non-informative for the data generated by transcript enumeration techniques since they ignore certain fundamental properties of this space.

Here we present a software tool, Simcluster, designed to perform clustering analysis for data on the simplex space. We present Simcluster as a stand-alone command-line C package and as a user-friendly on-line tool. Both versions are available at: http://xerad.systemsbiology.net/simcluster.

Simcluster is designed in accordance with a well-established mathematical framework for compositional data analysis, which provides principled procedures for dealing with the simplex space, and is thus applicable in a number of contexts, including enumeration-based gene expression data

Recent results on parallel link resolution

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Knowledge-Intensive Gathering and Integration of Statistical Information on European Fisheries

Gathering, maintenance, integration and presentation of statistics are major activities of the Dutch Agricultural Economics Research Institute LEI. In this paper we explore how knowledge and agent technology can be exploited to support the information gathering and integration process. In particular, the methods used by the institute’s experts in the domain of Fishery Economics are analyzed. Also, the design and implementation of a prototype system for intelligent information gathering and integration are discussed. The model covers not only the actual integration, but also the processes for identification of the type of information needed by the client, and the gathering of source information