In Silico Identification and Comparative Synteny of Biosynthetic Gene Clusters in Plants

Biosynthetic gene clusters (BGCs) are often encoding specialized metabolic pathways in plants, yet effective methods for the comparison across multiple species are still evolving. In this protocol, we present a bioinformatics approach combining plantiSMASH and MCScan for the identification, annotation, and comparative analysis of BGCs in plant genomes. The methodology involves using plantiSMASH to predict and annotate potential BGCs, followed by the use of MCScan to perform syntenic analysis, enabling the exploration of the conservation and evolutionary dynamics of BGCs across different plant species. Here, we provide a step-by-step guide for installing and configuring the necessary software, preparing genomic data, and executing the analysis. This methodology, integrated with transcriptomic and metabolomic data, can be used to verify the functional relevance of the identified BGCs in specific biosynthetic pathways. It is applicable to a broad range of plant species and serves as a framework for the discovery and characterization of BGCs. The described methodology can significantly enhance research in plant genomics and metabolic engineering by offering new insights into the organization and function of BGCs.