ABSTRACT
MOTIVATION: The genome of the social amoeba Dictyostelium discoideum contains an unusually large number of polyketide synthase (PKS) genes. An analysis of the genes is a first step towards understanding the biological roles of their products and exploiting novel products. RESULTS: A total of 45 Type I iterative PKS genes were found, 5 of which are probably pseudogenes. Catalytic domains that are homologous with known PKS sequences as well as possible novel domains were identified. The genes often occurred in clusters of 2-5 genes, where members of the cluster had very similar sequences. The D.discoideum PKS genes formed a clade distinct from fungal and bacterial genes. All nine genes examined by RT-PCR were expressed, although at different developmental stages. The promoters of PKS genes were much more divergent than the structural genes, although we have identified motifs that are unique to some PKS gene promoters.
Subject(s)
Chromosome Mapping/methods , Dictyostelium/physiology , Multigene Family/physiology , Polyketide Synthases/chemistry , Polyketide Synthases/physiology , Sequence Analysis, Protein/methods , Amino Acid Sequence , Animals , Biological Products/metabolism , Molecular Sequence Data , Protein Structure, Tertiary , Sequence Homology, Amino AcidABSTRACT
This paper describes a new technique for clustering short time series coming from gene expression data. The technique is based on the labelling of the time series through temporal trend abstractions and a consequent clustering of the series on the basis of their labels. Clustering is performed at three different levels of aggregation of the original time series, so that the results are organized and visualized as a three-levels hierarchical tree. Results on simulated and on yeast data are shown. The technique appears robust and efficient and the results obtained are easy to be interpreted.