Chromosome-level genome assembly of Ophiorrhiza pumila reveals the evolution of camptothecin biosynthesis

Abstract

Plant genomes remain highly fragmented and are often characterized by hundreds to thousands of assembly gaps. Here, we report chromosome-level reference and phased genome assembly of Ophiorrhiza pumila, a camptothecin-producing medicinal plant, through an ordered multi-scaffolding and experimental validation approach. With 21 assembly gaps and a contig N50 of 18.49 Mb, Ophiorrhiza genome is one of the most complete plant genomes assembled to date. We also report 273 nitrogen-containing metabolites, including diverse monoterpene indole alkaloids (MIAs). A comparative genomics approach identifies strictosidine biogenesis as the origin of MIA evolution. The emergence of strictosidine biosynthesis-catalyzing enzymes precede downstream enzymes’ evolution post γ whole-genome triplication, which occurred approximately 110 Mya in O. pumila, and before the whole-genome duplication in Camptotheca acuminata identified here. Combining comparative genome analysis, multi-omics analysis, and metabolic gene-cluster analysis, we propose a working model for MIA evolution, and a pangenome for MIA biosynthesis, which will help in establishing a sustainable supply of camptothecin.

Genome-wide Survey of the GATA Gene Family in Camptothecin-producing Plant Ophiorrhiza Pumila

“…CPT has been isolated from different plant species. CPT-producing weedy plant Ophiorrhiza pumila has brought about widespread attention, and the whole genome of O. pumila has been sequenced [29]. Recently, metabolic engineering has been applied in O. pumila to elevate CPT content.…”

“…GATA TFs from O. pumila (OpGATAs) have not been extensively studied. In this study, GATA family TFs distributed in O. pumila were we systematically characterized [29]. Based on phylogenetic relationship and expression pattern combined with co-expression analysis, candidate GATA genes regulating CPT biosynthesis were predicted.…”

The emerging role of biosynthetic gene clusters in plant defense and plant interactions

“…Clustering of specialized biosynthetic pathways, many of which have evolved relatively recently in evolutionary time, implies that they are under particular selective pressures and are therefore likely to underlie important traits that enhance fitness (e.g., by providing resistance to pests and pathogens). Genomic factors that may contribute to the formation, regulation, and evolution of BGCs include transposable element-mediated recombination [ 37 ], chromosomal inversion [ 38 ], gene shuffling [ 39 , 40 ], whole genome duplications [ 41 , 42 ], copy number variations of genes within BGCs [ 43 ], chromatin modification [ 44 , 45 ], and chromosomal 3D structure [ 46 ].…”

Gene-Metabolite Network Analysis Revealed Tissue-Specific Accumulation of Therapeutic Metabolites in Mallotus japonicus

“…The availability of genomic resources is the prerequisite to evaluate molecular components involved in specialized metabolites biosynthesis. While the number of plant species with chromosome-scale genome assemblies has significantly increased in the last few years, the sequenced genomes are still dominated by crops, and relatively fewer medicinal plants have obtained the high-quality genome status so far [13,29]. The scarcity of genomic resources for medicinal plants has hindered the prospect of developing a sustainable alternative to produce pharmacological metabolites of plant origin.…”

“…We, therefore, hypothesized that the transcript modules correlated with the MetM7 metabolite module would include functional genes most likely associated with the biosynthesis of rutin and associated metabolites. Several studies have highlighted the importance of integrating transcriptome and metabolome datasets in identifying functional genes [29,38,[54][55][56][57][58]. Therefore, using a similar strategy in M. japonicus, we performed a correlation analysis between metabolite and transcript modules and identified the transcript modules TransM9 and TransM4, sharing a high correlation (R 2 > 0.7) with the MetM7 metabolite module.…”