Abstract
The natural diversity of plant metabolism has long been a source for human medicines. One group of plant-derived compounds, the monoterpene indole alkaloids (MIAs), includes well-documented therapeutic agents used in the treatment of cancer (vinblastine, vincristine, camptothecin), hypertension (reserpine, ajmalicine), malaria (quinine), and as analgesics (7-hydroxymitragynine). Our understanding of the biochemical pathways that synthesize these commercially relevant compounds is incomplete due in part to a lack of molecular, genetic, and genomic resources for the identification of the genes involved in these specialized metabolic pathways. To address these limitations, we generated large-scale transcriptome sequence and expression profiles for three species of Asterids that produce medicinally important MIAs: Camptotheca acuminata, Catharanthus roseus, and Rauvolfia serpentina. Using next generation sequencing technology, we sampled the transcriptomes of these species across a diverse set of developmental tissues, and in the case of C. roseus, in cultured cells and roots following elicitor treatment. Through an iterative assembly process, we generated robust transcriptome assemblies for all three species with a substantial number of the assembled transcripts being full or near-full length. The majority of transcripts had a related sequence in either UniRef100, the Arabidopsis thaliana predicted proteome, or the Pfam protein domain database; however, we also identified transcripts that lacked similarity with entries in either database and thereby lack a known function. Representation of known genes within the MIA biosynthetic pathway was robust. As a diverse set of tissues and treatments were surveyed, expression abundances of transcripts in the three species could be estimated to reveal transcripts associated with development and response to elicitor treatment. Together, these transcriptomes and expression abundance matrices provide a rich resource for understanding plant specialized metabolism, and promotes realization of innovative production systems for plant-derived pharmaceuticals.
Highlights
Plants, and natural products derived from them, have been used medicinally for millennia
The longest transcript isoform generated from each Oases-generated contig was selected to be the representative transcript and an artificial molecule was constructed using custom Perl scripts for C. roseus and R. serpentina by concatenating the representative transcripts together
The second and final de novo assembly for C. roseus and R. serpentina was generated by combining reads from the normalized library with reads that failed to align to the pseudomolecule from the single non-normalized experimental tissue/treatment libraries and using these in a second and final assembly with Oases [14]
Summary
Natural products derived from them, have been used medicinally for millennia. Cannabis sativa is one striking exception, as extensive (but illicit) efforts have increased the concentration of its major active compound, delta 9-tetrahydrocannabinol, from less than 1.5% in the early 1980s to over 13% in more recent samples [3] This ,10-fold increase suggests that much potential remains locked in the genomes of other medicinal plants and is waiting to be exploited. A further complication is the inability to apply powerful genetic approaches to most medicinal plants–approaches that have had great success in unraveling other complicated biological processes To circumvent these barriers, we recently participated in the Medicinal Plant Genomics Consortium, an effort to use next-generation sequencing to create public databases for the transcriptomes of 14 medicinal plants (http://medicinalplantgenomics.msu.edu/). The availability of these data allows investigators to freely access information about known biosynthetic genes that are in plants of high pharmacological importance and, importantly, provide the information needed to identify potential genes for the remaining unknown biosynthetic steps for target compounds
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