Genome-Wide Prediction of Metabolic Enzymes, Pathways, and Gene Clusters in Plants. Issue 4 (22nd February 2017)

• Record Type: Journal Article
• Authors: Schläpfer, Pascal; Zhang, Peifen; Wang, Chuan; Kim, Taehyong; Banf, Michael; Chae, Lee; Dreher, Kate; Chavali, Arvind K.; Nilo-Poyanco, Ricardo; Bernard, Thomas; Kahn, Daniel; Rhee, Seung Y.
• Is Part Of: Plant physiology. Volume 173:Issue 4(2017)
• Page Start: 2041
• Page End: 2059
• Publication Date: 2017-02-22
• Subjects: Plant physiology -- Periodicals; Botany -- Periodicals; Periodicals; Electronic journals; 571.2
• DOI: 10.1104/pp.16.01942
• Languages: English
• ISSNs: 0032-0889

Abstract

Abstract : A computational pipeline generates high-quality and genome-scale sets of metabolic enzymes, pathways, and gene clusters from plant genomes. Abstract: Plant metabolism underpins many traits of ecological and agronomic importance. Plants produce numerous compounds to cope with their environments but the biosynthetic pathways for most of these compounds have not yet been elucidated. To engineer and improve metabolic traits, we need comprehensive and accurate knowledge of the organization and regulation of plant metabolism at the genome scale. Here, we present a computational pipeline to identify metabolic enzymes, pathways, and gene clusters from a sequenced genome. Using this pipeline, we generated metabolic pathway databases for 22 species and identified metabolic gene clusters from 18 species. This unified resource can be used to conduct a wide array of comparative studies of plant metabolism. Using the resource, we discovered a widespread occurrence of metabolic gene clusters in plants: 11, 969 clusters from 18 species. The prevalence of metabolic gene clusters offers an intriguing possibility of an untapped source for uncovering new metabolite biosynthesis pathways. For example, more than 1, 700 clusters contain enzymes that could generate a specialized metabolite scaffold (signature enzymes) and enzymes that modify the scaffold (tailoring enzymes). In four species with sufficient gene expression data, we identified 43 highly coexpressed clusters that contain signature and tailoring enzymes, of which eight were characterized previously to be functional pathways. Finally, we identified patterns of genome organization that implicate local gene duplication and, to a lesser extent, single gene transposition as having played roles in the evolution of plant metabolic gene clusters.