# Multi-Omics Approaches to Study Molecular Mechanisms in _Camanabis sativa_
## 5 Conclusions
\begin{table}
\begin{tabular}{c c c} \hline \hline
**Omic Technologies** & **Description** & **Reference** \\ \hline \multicolumn{3}{c}{Study of the cannabis transcriptome.} \\  & Transcriptomic applications & \\ Transcriptomics/RNA-Seq approach & investigated fibers cannabis & [24; 77; 79; 80] \\  & development stages. cannabis & \\  & salt-responsive genes were also & \\  & investigated & \\ \hline Transcriptomics/De novo & Definition of hight quality reference & \\ transcriptome assembly pipeline and & transcriptomes of two cannabis & [65] \\ BLAST2 GO tool & cultivars & \\ \hline \hline \end{tabular}
\end{table} 
Table 2: _Cont._ \begin{table}
\begin{tabular}{c c c} \hline \hline
**Omic Technologies** & **Description** & **Reference** \\ \hline \multicolumn{3}{c}{Matabolomics/GC,} \\ Transcriptomics/RNA-Seq e PCR & & of different cannabinoid synthase & [72; 83; 85] \\ \hline \multicolumn{3}{c}{Metabolomics/HPLC,} \\ Genomics/WGS and GBS & Investigation about cannabis ancestry & [15] \\ \hline \multicolumn{3}{c}{Metabolomics/SPME GC-MS and} \\ LC-MS, Transcriptomics/Rna-Seq & & \\ \hline \multicolumn{3}{c}{Metabolomics/HPLC/GC,} \\ Transcriptomics/RNA-Seq & & \\ \hline \multicolumn{3}{c}{Metabolomics/HPLC,} \\ genomics/WGS, & & \\ \hline \multicolumn{3}{c}{Metabolomics/WRSA-Seq} & \\ \hline \multicolumn{3}{c}{Generomics/SNPs,} \\ Transcriptomics/RNA-sequencing & & \\ \hline \multicolumn{3}{c}{Generomics/RNA-sequencing} \\ Transcriptomics/RNA sequencing & & \\ \hline \multicolumn{3}{c}{Generomics/PacBio,} \\ Transcriptomics/RNA sequencing & & \\ \multicolumn{3}{c}{based on Iso-Seq} & \\ \hline \multicolumn{3}{c}{Genomics/Transcriptomics—} \\ Innovative approaches discussion, & & \\ including GWAS, GS, gen-genomics & & \\ \hline \multicolumn{3}{c}{Metabolomics, genomics and} \\ transcriptomics data are collected and & \multicolumn{3}{c}{“CannabisGDB”, a comprehensive} \\ structured, and available on a web & & multi-omics database & [91] \\ site for researchers & & \\ \hline \multicolumn{3}{c}{Metabolomics, Genomics and} \\ transcriptomics platforms. WGS approach in medical cannabis is & & \\ \hline \multicolumn{3}{c}{Metabolomics/GC,} \\ Genomics/WGS/Linkage mapping & & \\ and & and USO31 cannabis cultivars & \\ \hline \multicolumn{3}{c}{Metabolomics/HPLC,} \\ Genomics/Nanopore technology/Linkage mapping and & & \\ QTL analysis, & & \\ \multicolumn{3}{c}{Cultural} \\ Transcriptomics/RNA-Seq & & \\ \hline \hline \end{tabular}
\end{table} 
Table 3: The multi-omic studies examined in this review. Significant advances in understanding the molecular mechanisms of cannabis have been made in recent years, despite the challenges implementing this interdisciplinary approach. To date, a complete integration of heterogeneous multi-omics data is still extremely challenging and tools to manage and integrate data coming from different omic layers have still to be developed. In this context, the role of publicly available network resources, allowing the access to genomics, genetics, transcriptomics, and metabolomics cannabis data sources, such as the \"CannabisGDB\" data base [91], could become crucial. The benefits of applying these approaches not just to cannabis, but to many other organisms, provide a need to rapidly overcome the current technological limitations. As such, we anticipate that in the near future, these types of studies will become far more widespread, and the full utilisation of these complex datasets will become an attainable goal for many researchers. With changes in legislation and public attitude, the demand for research activity in cannabis is growing rapidly and new, innovative applications are developing. For instance, data provided by omics experiments are being used in parallel with genetic engineering approaches to obtain a better understanding of Cannabis genetics [92].