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

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 ma...

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Bibliographic Details
Published inBioinformatics Vol. 32; no. 8; pp. 1138 - 1143
Main Authors Wolf, Thomas, Shelest, Vladimir, Nath, Neetika, Shelest, Ekaterina
Format Journal Article
LanguageEnglish
Published England Oxford University Press 15.04.2016
Subjects
Anchors
Bioinformatics
Clusters
Eukaryota
Genes
Genomes
Islands
Metabolites
Multigene Family
Original Papers
Peptide Synthases - genetics
Polyketide Synthases - genetics
Searching
Software
Online AccessGet full text
ISSN1367-4803
1367-4811
1460-2059
DOI10.1093/bioinformatics/btv713

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Summary: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.
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Associate Editor: Alfonso Valencia
ISSN:1367-4803
1367-4811
1460-2059
DOI:10.1093/bioinformatics/btv713