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Nucleic Acids Res. 2017 Jul 3;45(W1):W55-W63. doi: 10.1093/nar/gkx305.

plantiSMASH: automated identification, annotation and expression analysis of plant biosynthetic gene clusters.

Author information

1
Bioinformatics Group, Wageningen University, 6708 PB Wageningen, The Netherlands.
2
Teknik Informatika, Universitas Lampung, Jln. Sumantri Brojonegoro No. 01, Lampung 35141, Indonesia.
3
The Novo Nordisk Foundation Center for Biosustainability, Technical University of Denmark, 2800 Kgs. Lyngby, Denmark.
4
Department of Metabolic Biology, John Innes Centre, Norwich Research Park, Norwich NR4 7UH, UK.

Abstract

Plant specialized metabolites are chemically highly diverse, play key roles in host-microbe interactions, have important nutritional value in crops and are frequently applied as medicines. It has recently become clear that plant biosynthetic pathway-encoding genes are sometimes densely clustered in specific genomic loci: biosynthetic gene clusters (BGCs). Here, we introduce plantiSMASH, a versatile online analysis platform that automates the identification of candidate plant BGCs. Moreover, it allows integration of transcriptomic data to prioritize candidate BGCs based on the coexpression patterns of predicted biosynthetic enzyme-coding genes, and facilitates comparative genomic analysis to study the evolutionary conservation of each cluster. Applied on 48 high-quality plant genomes, plantiSMASH identifies a rich diversity of candidate plant BGCs. These results will guide further experimental exploration of the nature and dynamics of gene clustering in plant metabolism. Moreover, spurred by the continuing decrease in costs of plant genome sequencing, they will allow genome mining technologies to be applied to plant natural product discovery. The plantiSMASH web server, precalculated results and source code are freely available from http://plantismash.secondarymetabolites.org.

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