PLoS ONE (Jan 2015)
Large-Scale Evolutionary Analysis of Genes and Supergene Clusters from Terpenoid Modular Pathways Provides Insights into Metabolic Diversification in Flowering Plants.
Abstract
An important component of plant evolution is the plethora of pathways producing more than 200,000 biochemically diverse specialized metabolites with pharmacological, nutritional and ecological significance. To unravel dynamics underlying metabolic diversification, it is critical to determine lineage-specific gene family expansion in a phylogenomics framework. However, robust functional annotation is often only available for core enzymes catalyzing committed reaction steps within few model systems. In a genome informatics approach, we extracted information from early-draft gene-space assemblies and non-redundant transcriptomes to identify protein families involved in isoprenoid biosynthesis. Isoprenoids comprise terpenoids with various roles in plant-environment interaction, such as pollinator attraction or pathogen defense. Combining lines of evidence provided by synteny, sequence homology and Hidden-Markov-Modelling, we screened 17 genomes including 12 major crops and found evidence for 1,904 proteins associated with terpenoid biosynthesis. Our terpenoid genes set contains evidence for 840 core terpene-synthases and 338 triterpene-specific synthases. We further identified 190 prenyltransferases, 39 isopentenyl-diphosphate isomerases as well as 278 and 219 proteins involved in mevalonate and methylerithrol pathways, respectively. Assessing the impact of gene and genome duplication to lineage-specific terpenoid pathway expansion, we illustrated key events underlying terpenoid metabolic diversification within 250 million years of flowering plant radiation. By quantifying Angiosperm-wide versatility and phylogenetic relationships of pleiotropic gene families in terpenoid modular pathways, our analysis offers significant insight into evolutionary dynamics underlying diversification of plant secondary metabolism. Furthermore, our data provide a blueprint for future efforts to identify and more rapidly clone terpenoid biosynthetic genes from any plant species.