CASSIS and SMIPS: promoter-based prediction of secondary metabolite gene clusters in eukaryotic genomes

Abstract:

MOTIVATION: Secondary metabolites (SM) are structurally diverse natural products of high pharmaceutical importance. Genes involved in their biosynthesis are often organized in clusters, i.e., are co-localized and co-expressed. In silico cluster prediction in eukaryotic genomes remains problematic mainly due to the high variability of the clusters' content and lack of other distinguishing sequence features. RESULTS: We present Cluster Assignment by Islands of Sites (CASSIS), a method for SM cluster prediction in eukaryotic genomes, and Secondary Metabolites by InterProScan (SMIPS), a tool for genome-wide detection of SM key enzymes ('anchor' genes): polyketide synthases, non-ribosomal peptide synthetases and dimethylallyl tryptophan synthases. Unlike other tools based on protein similarity, CASSIS exploits the idea of co-regulation of the cluster genes, which assumes the existence of common regulatory patterns in the cluster promoters. The method searches for 'islands' of enriched cluster-specific motifs in the vicinity of anchor genes. It was validated in a series of cross-validation experiments and showed high sensitivity and specificity. AVAILABILITY AND IMPLEMENTATION: CASSIS and SMIPS are freely available at https://sbi.hki-jena.de/cassis CONTACT: thomas.wolf@leibniz-hki.de or ekaterina.shelest@leibniz-hki.de SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

SEEK ID: https://data.chembiosys.de/publications/22

PubMed ID: 26656005

Projects: INF

Journal: Bioinformatics

Citation:

Date Published: 9th Dec 2015

Authors: T. Wolf, V. Shelest, N. Nath, Ekaterina Shelest

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Created: 5th Oct 2016 at 06:42

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