The characterization of key physiological traits of medicinal cannabis (Cannabis sativa L.) as a tool for precision breeding.

BACKGROUND: For millennia, drug-type cannabis strains were extensively used for various medicinal, ritual, and inebriant applications. However, cannabis prohibition during the last century led to cultivation and breeding activities being conducted under clandestine conditions, while scientific development of the crop ceased. Recently, the potential of medicinal cannabis has been reacknowledged and the now expanding industry requires optimal and scientifically characterized varieties. However, scientific knowledge that can propel this advancement is sorely lacking. To address this issue, the current study aims to provide a better understanding of key physiological and phenological traits that can facilitate the breeding of advanced cultivars. RESULTS: A diverse population of 121 genotypes of high-THC or balanced THC-CBD ratio was cultivated under a controlled environment facility and 13 plant parameters were measured. No physiological association across genotypes attributed to the same vernacular classification was observed. Floral bud dry weight was found to be positively associated with plant height and stem diameter but not with days to maturation. Furthermore, the heritability of both plant height and days to maturation was relatively high, but for plant height it decreased during the vegetative growth phase. To advance breeding efficacy, a prediction equation for forecasting floral bud dry weight was generated, driven by parameters that can be detected during the vegetative growth phase solely. CONCLUSIONS: Our findings suggest that selection for taller and fast-growing genotypes is likely to lead to an increase in floral bud productivity. It was also found that the final plant height and stem diameter are determined by 5 independent factors that can be used to maximize productivity through cultivation adjustments. The proposed prediction equation can facilitate the selection of prolific genotypes without the completion of a full cultivation cycle. Future studies that will associate genome-wide variation with plants morphological traits and cannabinoid profile will enable precise and accelerated breeding through genomic selection approaches.

A new and improved genome sequence of Cannabis sativa.

Cannabis is a diploid species (2n = 20), the estimated haploid genome sizes of the female and male plants using flow cytometry are 818 and 843 Mb respectively. Although the genome of Cannabis has been sequenced (from hemp, wild and high-THC strains), all assemblies have significant gaps. In addition, there are inconsistencies in the chromosome numbering which limits their use. A new comprehensive draft genome sequence assembly (∼900 Mb) has been generated from the medicinal cannabis strain Cannbio-2, that produces a balanced ratio of cannabidiol and delta-9-tetrahydrocannabinol using long-read sequencing. The assembly was subsequently analysed for completeness by ordering the contigs into chromosome-scale pseudomolecules using a reference genome assembly approach, annotated and compared to other existing reference genome assemblies. The Cannbio-2 genome sequence assembly was found to be the most complete genome sequence available based on nucleotides assembled and BUSCO evaluation in Cannabis sativa with a comprehensive genome annotation. The new draft genome sequence is an advancement in Cannabis genomics permitting pan-genome analysis, genomic selection as well as genome editing.

Generation of a Comprehensive Transcriptome Atlas and Transcriptome Dynamics in Medicinal Cannabis.

Cannabinoids are the main medicinal compounds of interest in the plant Cannabis sativa, that are primarily synthesised in the glandular trichomes; found on female floral buds. The content, composition and yield of secondary metabolites (cannabinoids and terpenoids) is influenced by the plant's genetics and environment. Some initial gene expression experiments have been performed from strains of this plant species that contrasted in cannabinoid production, however the present knowledge about detailed trichome transcriptomics in this species is limited. An extensive transcriptome atlas was generated by RNA sequencing using root, shoot, flower and trichome tissues from a female plant strain (Cannbio-2) and was enhanced with the addition of vegetative and reproductive tissues from a male cannabis plant. Differential gene expression analysis identified genes preferentially expressed in different tissues. Detailed trichomics was performed from extractions specifically from glandular trichomes as well as female floral tissues at varying developmental stages, to identify stage-specific differentially expressed genes. Candidate genes involved in terpene and cannabinoid synthesis were identified and the majority were found to have an abundant expression in trichomes. The comprehensive transcriptome is a significant resource in cannabis for further research of functional genomics to improve the yield of specialised metabolites with high pharmacological value.

Exploitation of data from breeding programs supports rapid implementation of genomic selection for key agronomic traits in perennial ryegrass.

KEY MESSAGE: Exploitation of data from a ryegrass breeding program has enabled rapid development and implementation of genomic selection for sward-based biomass yield with a twofold-to-threefold increase in genetic gain. Genomic selection, which uses genome-wide sequence polymorphism data and quantitative genetics techniques to predict plant performance, has large potential for the improvement in pasture plants. Major factors influencing the accuracy of genomic selection include the size of reference populations, trait heritability values and the genetic diversity of breeding populations. Global diversity of the important forage species perennial ryegrass is high and so would require a large reference population in order to achieve moderate accuracies of genomic selection. However, diversity of germplasm within a breeding program is likely to be lower. In addition, de novo construction and characterisation of reference populations are a logistically complex process. Consequently, historical phenotypic records for seasonal biomass yield and heading date over a 18-year period within a commercial perennial ryegrass breeding program have been accessed, and target populations have been characterised with a high-density transcriptome-based genotyping-by-sequencing assay. Ability to predict observed phenotypic performance in each successive year was assessed by using all synthetic populations from previous years as a reference population. Moderate and high accuracies were achieved for the two traits, respectively, consistent with broad-sense heritability values. The present study represents the first demonstration and validation of genomic selection for seasonal biomass yield within a diverse commercial breeding program across multiple years. These results, supported by previous simulation studies, demonstrate the ability to predict sward-based phenotypic performance early in the process of individual plant selection, so shortening the breeding cycle, increasing the rate of genetic gain and allowing rapid adoption in ryegrass improvement programs.

Genotyping-by-sequencing through transcriptomics: implementation in a range of crop species with varying reproductive habits and ploidy levels.

The application of genomics in crops has the ability to significantly improve genetic gain for agriculture. Many marker-dense tools have been developed, but few have seen broad adoption in plant genomics due to issues of significant variations of genome size, levels of ploidy, single nucleotide polymorphism (SNP) frequency and reproductive habit. When combined with limited breeding activities, small research communities and scant sequence resources, the suitability of popular systems is often suboptimal and routinely fails to effectively balance cost-effectiveness and sample throughput. Genotyping-by-sequencing (GBS) encompasses a range of protocols including resequencing of the transcriptome. This study describes a skim GBS-transcriptomics (GBS-t) approach developed to be broadly applicable, cost-effective and high-throughput while still assaying a significant number of SNP loci. A range of crop species with differing levels of ploidy and degree of inbreeding/outbreeding were chosen, including perennial ryegrass, a diploid outbreeding forage grass; phalaris, a putative segmental allotetraploid outbreeding forage grass; lentil, a diploid inbreeding grain legume; and canola, an allotetraploid partially outbreeding oilseed. GBS-t was validated as a simple and largely automated, cost-effective method which generates sufficient SNPs (from 89 738 to 231 977) with acceptable levels of missing data and even genome coverage from c. 3 million sequence reads per sample. GBS-t is therefore a broadly applicable system suitable for many crops, offering advantages over other systems. The correct choice of subsequent sequence analysis software is important, and the bioinformatics process should be iterative and tailored to the specific challenges posed by ploidy variation and extent of heterozygosity.

Targeted genotyping-by-sequencing permits cost-effective identification and discrimination of pasture grass species and cultivars.

KEY MESSAGE: A targeted amplicon-based genotyping-by-sequencing approach has permitted cost-effective and accurate discrimination between ryegrass species (perennial, Italian and inter-species hybrid), and identification of cultivars based on bulked samples. Perennial ryegrass and Italian ryegrass are the most important temperate forage species for global agriculture, and are represented in the commercial pasture seed market by numerous cultivars each composed of multiple highly heterozygous individuals. Previous studies have identified difficulties in the use of morphophysiological criteria to discriminate between these two closely related taxa. Recently, a highly multiplexed single nucleotide polymorphism (SNP)-based genotyping assay has been developed that permits accurate differentiation between both species and cultivars of ryegrasses at the genetic level. This assay has since been further developed into an amplicon-based genotyping-by-sequencing (GBS) approach implemented on a second-generation sequencing platform, allowing accelerated throughput and ca. sixfold reduction in cost. Using the GBS approach, 63 cultivars of perennial, Italian and interspecific hybrid ryegrasses, as well as intergeneric Festulolium hybrids, were genotyped. The genetic relationships between cultivars were interpreted in terms of known breeding histories and indistinct species boundaries within the Lolium genus, as well as suitability of current cultivar registration methodologies. An example of applicability to quality assurance and control (QA/QC) of seed purity is also described. Rapid, low-cost genotypic assays provide new opportunities for breeders to more fully explore genetic diversity within breeding programs, allowing the combination of novel unique genetic backgrounds. Such tools also offer the potential to more accurately define cultivar identities, allowing protection of varieties in the commercial market and supporting processes of cultivar accreditation and quality assurance.

Identification of QTLs for morphological traits influencing waterlogging tolerance in perennial ryegrass (Lolium perenne L.).

Perennial ryegrass is a globally cultivated obligate outbreeding diploid species (2n = 2x = 14) which is subjected to periods of waterlogging stress due to flood irrigation during winter and the lead-up to summer. Reduction of oxygen supply to root systems due to waterlogging produces consequent deleterious effects on plant performance. Framework genetic maps for a large-scale genetic mapping family [F1(NA(x) × AU6)] were constructed containing 91 simple sequence repeat and 24 single nucleotide polymorphism genetic markers. Genetic trait dissection using both control and waterlogging treatments was performed in the glasshouse, a total of 143 maximally recombinant genotypes being selected from the overall sib-ship and replicated threefold in the trial. Analysis was performed for nine quantitative morphological traits measured 8 weeks after stress treatments were applied. A total of 37 quantitative trait loci (QTLs) were identified; 19 on the NA(x) parental genetic map, and 18 on the AU6 parental genetic map. Regions of particular interest were identified on linkage groups (LGs) 4 and 3 of the respective maps, which have been targeted for further analysis by selection of critical recombinants. This first study of genetic control of waterlogging tolerance in ryegrasses has important implications for breeding improvement of abiotic stress adaptation.

Identification of genetic factors influencing salt stress tolerance in white clover (Trifolium repens L.) by QTL analysis.

Allotetraploid (2n = 4x = 32) white clover (Trifolium repens L.) is the most commonly cultivated legume component of temperate pastures, sown in swards with a companion grass species. Genetic control of growth performance of white clover on saline land is highly important for dairy industries, due to increasing soil salinity problems. The objective of this study was to identify quantitative trait loci (QTLs) for salinity tolerance in terms of vegetative growth under stress. Two parental genetic maps consisting of 213 and 159 marker loci and spanning 1,973.0 and 1,837.6 cM, respectively, were constructed using simple sequence repeat (SSR) and single nucleotide polymorphism (SNP) markers from a two-way pseudo-test cross F(1) population derived from pair-crossing of the Haifa(2) and LCL(2) genotypes. A total of 8 unique genomic regions on 8 linkage groups (LGs) of the Haifa(2) parental map and 6 unique regions on 5 LGs in the LCL(2) parental map were associated with plant growth under salt stress and relative growth under stress, as compared to control conditions. The results of this study indicate that salt tolerance in white clover is controlled by multiple QTLs, some at common locations, but each of limited magnitude. Location of these QTLs provides the genetic basis and potential for pyramiding of salt tolerance genes in breeding improvement.