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BackgroundThe raised demand of cannabis as a medicinal plant in recent years led to an increased interest in understanding the biosynthetic routes of cannabis metabolites. Since there is no established protocol to generate stable gene knockouts in cannabis, the use of a virus-induced gene silencing (VIGS) method, resulting in a gene knockdown, to study gene functions is desirable.ResultsFor this, a computational approach was employed to analyze the Cannabis sativa L. transcriptomic and genomic resources. Reporter genes expected to give rise to easily scorable phenotypes upon silencing, i.e. the phytoene desaturase (PDS) and magnesium chelatase subunit I (ChlI), were identified in C. sativa. Subsequently, the targets of specific small interfering RNAs (siRNAs) and silencing fragments were predicted and tested in a post-transcriptional gene silencing (PTGS) approach. Here we show for the first time a gene knockdown in C. sativa using the Cotton leaf crumple virus (CLCrV) in a silencing vector system. Plants transiently transformed with the Agrobacterium tumefaciens strain AGL1, carrying the VIGS-vectors, showed the desired phenotypes, spotted bleaching of the leaves. The successful knockdown of the genes was additionally validated by quantitative PCR resulting in reduced expression of transcripts from 70 to 73% for ChlI and PDS, respectively. This is accompanied with the reduction of the chlorophyll a and carotenoid content, respectively. In summary, the data clearly demonstrate the potential for functional gene studies in cannabis using the CLCrV-based vector system.ConclusionsThe applied VIGS-method can be used for reverse genetic studies in C. sativa to identify unknown gene functions. This will gain deeper inside into unknown biosynthetic routes and will help to close the gap between available genomic data and biochemical information of this important medicinal plant.

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The liverwort Radula marginata belongs to the bryophyte division of land plants and is a prospective alternate source of cannabinoid-like compounds. However, mechanistic insights into the molecular pathways directing the synthesis of these cannabinoid-like compounds have been hindered due to the lack of genetic information. This prompted us to do deep sequencing, de novo assembly and annotation of R. marginata transcriptome, which resulted in the identification and validation of the genes for cannabinoid biosynthetic pathway. In total, we have identified 11,421 putative genes encoding 1,554 enzymes from 145 biosynthetic pathways. Interestingly, we have identified all the upstream genes of the central precursor of cannabinoid biosynthesis, cannabigerolic acid (CBGA), including its two first intermediates, stilbene acid (SA) and geranyl diphosphate (GPP). Expression of all these genes was validated using quantitative real-time PCR. We have characterized the protein structure of stilbene synthase (STS), which is considered as a homolog of olivetolic acid in R. marginata. Moreover, the metabolomics approach enabled us to identify CBGA-analogous compounds using electrospray ionization mass spectrometry (ESI-MS/MS) and gas chromatography mass spectrometry (GC-MS). Transcriptomic analysis revealed 1085 transcription factors (TF) from 39 families. Comparative analysis showed that six TF families have been uniquely predicted in R. marginata. In addition, the bioinformatics analysis predicted a large number of simple sequence repeats (SSRs) and non-coding RNAs (ncRNAs). Our results collectively provide mechanistic insights into the putative precursor genes for the biosynthesis of cannabinoid-like compounds and a novel transcriptomic resource for R. marginata. The large-scale transcriptomic resource generated in this study would further serve as a reference transcriptome to explore the Radulaceae family.