# Multi-Omics Approaches to Study Molecular Mechanisms in _Camanabis sativa_
## 3 Genomic and Transcriptomic Cannabis Profiles
It is worth noticing that genetic improvement of the alkyl side chain could help the development of new chemical chemotypes for pharmaceutical use. Furthermore, a GWAS approach has been applied to study the genetic architecture of flowering time and sex determination in hemp by using a panel of over 100 hemp accessions and a large set of SNP markers [69]. Several key genes and transcription factors involved in regulating phytohormones levels, like gibberellic acid, were identified in sex determination loci. These QTLs were proved to be responsible for the development of male flowers in female plants, being behind sex determination in monecious plants and its stability over time [69]. However, despite the advancement of the latest cannabis resources, the understanding of the genetic variation underlying complex agronomic traits of interest is still limited [19]. Although other recent investigations have been carried out, the development of efficient NGS tools and the construction of high-density genetic cannabis maps are necessary to improve the QTL mapping quality [62; 63]. Genomic selection (GS) methods, which rely on genome-wide marker information to forecast the breeding impact of genotypes, could be a relevant approach to reach this aim. GS has been recently used in breeding other crop species, including rice and canola [70; 71]. In both investigations, a multi-omics approach was applied to enhance agronomically important breeding traits including yield, grain weight and hybrid performance, underlining the advantages of combining omics datasets for GS analysis. In rice, the genomics predictions using genomic and metabolomic datasets showed better results than single omics approaches [70]. In canola, both SNPs and transcripts resulted reliable to predict hybrid performance using the most effective genomic unbiased prediction models. Compared to models just relying on pure genetic markers, those taking into account transcriptome data seem to be related to a significantly higher prediction accuracy, suggesting that transcripts contain relevant information beyond just genomic data [71]. The overall results reached to date are promising and open new perspectives for the genetic enhancement of complex traits regulated by a large number of genes. In the future, when further information become available and statistical models and phenotyping accuracy improve, these findings could also be applied to cannabis traits. Regarding terpene synthase genes, the CsTPS family in the 'JL' reference genomes was characterised [72]. Copy number gains in _CsTPS17_ were observed in several cannabis cultivars, and _CsTPS17_ was identified as potentially involved in myrcene or limonene synthase [25]. In the same study, a copy number analysis in the 'JL' genome revealed a unique amplification of Gibberellic Acid Insensitive genes (GAI), which are known to be involved in plant growth. However, further investigations are required to better understand the contribution to yield of these genes. Pathogen response genes, like those belonging to the Mildew Locus O (MLO) family, correlated with resistance to powdery mildew (PM), and the Thaumatin-Like Protein (TPLs) family, correlated with a wide range of pathogen resistance traits in plants including cannabis, were studied [25]. Specifically, the analysis confirmed extensive CNVs in cannabinoid synthesis and over 80 genes associated with resistance to _Golovinomyces chicoracearum_. Results also showed that plants with low THCA concentrations have a lower resistance to this pathogen. The antifungal response activity (against _Fusarium oxysporum_) of _CsTLP1_ was confirmed as well [25]. Gene expression investigations have been crucial for a better understanding of cannabinoid metabolic pathways [73]. A comparison of the transcriptomes of drug and fiber cannabis revealed that expression of the genes involved in the cannabinoid pathway is enhanced in drug cannabis [23], confirming that positive transcriptional regulators of the cannabinoid biosynthetic genes are more active in this variety.