Developing Prediction Models Using Near-Infrared Spectroscopy to Quantify Cannabinoid Content in Cannabis Sativa.

Cannabis is commercially cultivated for both therapeutic and recreational purposes in a growing number of jurisdictions. The main cannabinoids of interest are cannabidiol (CBD) and delta-9 tetrahydrocannabidiol (THC), which have applications in different therapeutic treatments. The rapid, nondestructive determination of cannabinoid levels has been achieved using near-infrared (NIR) spectroscopy coupled to high-quality compound reference data provided by liquid chromatography. However, most of the literature describes prediction models for the decarboxylated cannabinoids, e.g., THC and CBD, rather than naturally occurring analogues, tetrahydrocannabidiolic acid (THCA) and cannabidiolic acid (CBDA). The accurate prediction of these acidic cannabinoids has important implications for quality control for cultivators, manufacturers and regulatory bodies. Using high-quality liquid chromatography-mass spectroscopy (LCMS) data and NIR spectra data, we developed statistical models including principal component analysis (PCA) for data quality control, partial least squares regression (PLS-R) models to predict cannabinoid concentrations for 14 different cannabinoids and partial least squares discriminant analysis (PLS-DA) models to characterise cannabis samples into high-CBDA, high-THCA and even-ratio classes. This analysis employed two spectrometers, a scientific grade benchtop instrument (Bruker MPA II-Multi-Purpose FT-NIR Analyzer) and a handheld instrument (VIAVI MicroNIR Onsite-W). While the models from the benchtop instrument were generally more robust (99.4-100% accuracy prediction), the handheld device also performed well (83.1-100% accuracy prediction) with the added benefits of portability and speed. In addition, two cannabis inflorescence preparation methods were evaluated: finely ground and coarsely ground. The models generated from coarsely ground cannabis provided comparable predictions to that of the finely ground but represent significant timesaving in terms of sample preparation. This study demonstrates that a portable NIR handheld device paired with LCMS quantitative data can provide accurate cannabinoid predictions and potentially be of use for the rapid, high-throughput, nondestructive screening of cannabis material.

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.

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.

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.

Evaluation of endophyte toxin production and its interaction with transgenic perennial ryegrass (Lolium perenne L.) with altered expression of fructosyltransferases.

Alkaloid concentration of perennial ryegrass herbage is affected by endophyte strain and host plant genotype. However, previous studies suggest that associations between host and endophyte also depends on environmental conditions, especially those affecting nutrient reserves and that water-soluble carbohydrate (WSC) concentration of perennial ryegrass plants may influence grass-endophyte associations. In this study a single transgenic event, with altered expression of fructosyltransferase genes to produce high WSC and biomass, has been crossed into a range of cultivar backgrounds with varying Epichloë endophyte strains. The effect of the association between the transgenic trait and alkaloid production was assessed and compared with transgene free control populations. In the vast-majority of comparisons there was no significant difference between alkaloid concentrations of transgenic and non-transgenic plants within the same cultivar and endophyte backgrounds. There was no significant difference between GOI+ (gene of interest positive) and GOI- (gene of interest negative) populations in Janthritrem response. Peramine concentration was not different between GOI+ and GOI- for 10 of the 12 endophytes-cultivar combinations. Cultivar Trojan infected with NEA6 and Alto with SE (standard endophyte) exhibited higher peramine and lolitrem B (only for Alto SE) concentration, in the control GOI- compared with GOI+. Similarly, cultivar Trojan infected with NEA6 and Alto with NEA3 presented higher ergovaline concentration in GOI-. Differences in alkaloid concentration may be attributable to an indirect effect in the modulation of fungal biomass. These results conclude that the presence of this transgenic insertion, does not alter the risk (toxicity) of the endophyte-grass associations. Endophyte-host interactions are complex and further research into associations with high WSC plant should be performed in a case by case basis.

Reference transcriptome assembly and annotation for perennial ryegrass.

RNA-Seq methodology has been used to generate a comprehensive transcriptome sequence resource for perennial ryegrass, an important temperate pasture grass species. A total of 931 547 255 reads were obtained from libraries corresponding to 19 distinct tissue samples, including both vegetative and reproductive stages of development. Assembly of data generated a final filtered reference set of 48 713 contigs and scaffolds. The transcriptome resource will support whole genome sequence assembly, comparative genomics, implementation of genotyping-by-sequencing (GBS) methods based on transcript sampling, and identification of candidate genes for multiple biological functions.

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.

Generation and Characterisation of a Reference Transcriptome for Lentil (Lens culinaris Medik.).

RNA-Seq using second-generation sequencing technologies permits generation of a reference unigene set for a given species, in the absence of a well-annotated genome sequence, supporting functional genomics studies, gene characterisation and detailed expression analysis for specific morphophysiological or environmental stress response traits. A reference unigene set for lentil has been developed, consisting of 58,986 contigs and scaffolds with an N50 length of 1719 bp. Comparison to gene complements from related species, reference protein databases, previously published lentil transcriptomes and a draft genome sequence validated the current dataset in terms of degree of completeness and utility. A large proportion (98%) of unigenes were expressed in more than one tissue, at varying levels. Candidate genes associated with mechanisms of tolerance to both boron toxicity and time of flowering were identified, which can eventually be used for the development of gene-based markers. This study has provided a comprehensive, assembled and annotated reference gene set for lentil that can be used for multiple applications, permitting identification of genes for pathway-specific expression analysis, genetic modification approaches, development of resources for genotypic analysis, and assistance in the annotation of a future lentil genome sequence.

A simple method for semi-random DNA amplicon fragmentation using the methylation-dependent restriction enzyme MspJI.

BACKGROUND: Fragmentation at random nucleotide locations is an essential process for preparation of DNA libraries to be used on massively parallel short-read DNA sequencing platforms. Although instruments for physical shearing, such as the Covaris S2 focused-ultrasonicator system, and products for enzymatic shearing, such as the Nextera technology and NEBNext dsDNA Fragmentase kit, are commercially available, a simple and inexpensive method is desirable for high-throughput sequencing library preparation. MspJI is a recently characterised restriction enzyme which recognises the sequence motif CNNR (where R = G or A) when the first base is modified to 5-methylcytosine or 5-hydroxymethylcytosine. RESULTS: A semi-random enzymatic DNA amplicon fragmentation method was developed based on the unique cleavage properties of MspJI. In this method, random incorporation of 5-methyl-2'-deoxycytidine-5'-triphosphate is achieved through DNA amplification with DNA polymerase, followed by DNA digestion with MspJI. Due to the recognition sequence of the enzyme, DNA amplicons are fragmented in a relatively sequence-independent manner. The size range of the resulting fragments was capable of control through optimisation of 5-methyl-2'-deoxycytidine-5'-triphosphate concentration in the reaction mixture. A library suitable for sequencing using the Illumina MiSeq platform was prepared and processed using the proposed method. Alignment of generated short reads to a reference sequence demonstrated a relatively high level of random fragmentation. CONCLUSIONS: The proposed method may be performed with standard laboratory equipment. Although the uniformity of coverage was slightly inferior to the Covaris physical shearing procedure, due to efficiencies of cost and labour, the method may be more suitable than existing approaches for implementation in large-scale sequencing activities, such as bacterial artificial chromosome (BAC)-based genome sequence assembly, pan-genomic studies and locus-targeted genotyping-by-sequencing.

Improving the analysis of low heritability complex traits for enhanced genetic gain in potato.

KEY MESSAGE: Best linear unbiased prediction (BLUP), which uses pedigree to estimate breeding values, can result in increased genetic gains for low heritability traits in autotetraploid potato. Conventional potato breeding strategies, based on outcrossing followed by phenotypic recurrent selection over a number of generations, can result in slow but steady improvements of traits with moderate to high heritability. However, faster gains, particularly for low heritability traits, could be made by selection on estimated breeding values (EBVs) calculated using more complete pedigree information in best linear unbiased prediction (BLUP) analysis. One complication in applying BLUP predictions of breeding value to potato breeding programs is the autotetraploid inheritance pattern of this species. Here we have used a large pedigree, dating back to 1908, to estimate heritability for nine key traits for potato breeding, modelling autotetraploid inheritance. We estimate the proportion of double reduction in potatoes from our data, and across traits, to be in the order of 10 %. Estimates of heritability ranged from 0.21 for breeder's visual preference, 0.58 for tuber yield, to 0.83 for plant maturity. Using the accuracies of the EBVs determined by cross generational validation, we model the genetic gain that could be achieved by selection of genotypes for breeding on BLUP EBVs and demonstrate that gains can be greater than in conventional schemes.

EST-SNP discovery and dense genetic mapping in lentil (Lens culinaris Medik.) enable candidate gene selection for boron tolerance.

Large-scale SNP discovery and dense genetic mapping in a lentil intraspecific cross permitted identification of a single chromosomal region controlling tolerance to boron toxicity, an important breeding objective. Lentil (Lens culinaris Medik.) is a highly nutritious food legume crop that is cultivated world-wide. Until recently, lentil has been considered a genomic 'orphan' crop, limiting the feasibility of marker-assisted selection strategies in breeding programs. The present study reports on the identification of single-nucleotide polymorphisms (SNPs) from transcriptome sequencing data, utilisation of expressed sequence tag (EST)-derived simple sequence repeat (SSR) and SNP markers for construction of a gene-based genetic linkage map, and identification of markers in close linkage to major QTLs for tolerance to boron (B) toxicity. A total of 2,956 high-quality SNP markers were identified from a lentil EST database. Sub-sets of 546 SSRs and 768 SNPs were further used for genetic mapping of an intraspecific mapping population (Cassab × ILL2024) that exhibits segregation for B tolerance. Comparative analysis of the lentil linkage map with the sequenced genomes of Medicago truncatula Gaertn., soybean (Glycine max [L.] Merr.) and Lotus japonicus L. indicated blocks of conserved macrosynteny, as well as a number of rearrangements. A single genomic region was found to be associated with variation for B tolerance in lentil, based on evaluation performed over 2 years. Comparison of flanking markers to genome sequences of model species (M. truncatula, soybean and Arabidopsis thaliana) identified candidate genes that are functionally associated with B tolerance, and could potentially be used for diagnostic marker development in lentil.

Improving breeding efficiency in potato using molecular and quantitative genetics.

KEY MESSAGE: Potatoes are highly heterozygous and the conventional breeding of superior germplasm is challenging, but use of a combination of MAS and EBVs can accelerate genetic gain. Cultivated potatoes are highly heterozygous due to their outbreeding nature, and suffer acute inbreeding depression. Modern potato cultivars also exhibit tetrasomic inheritance. Due to this genetic heterogeneity, the large number of target traits and the specific requirements of commercial cultivars, potato breeding is challenging. A conventional breeding strategy applies phenotypic recurrent selection over a number of generations, a process which can take over 10 years. Recently, major advances in genetics and molecular biology have provided breeders with molecular tools to accelerate gains for some traits. Marker-assisted selection (MAS) can be effectively used for the identification of major genes and quantitative trait loci that exhibit large effects. There are also a number of complex traits of interest, such as yield, that are influenced by a large number of genes of individual small effect where MAS will be difficult to deploy. Progeny testing and the use of pedigree in the analysis can provide effective identification of the superior genetic factors that underpin these complex traits. Recently, it has been shown that estimated breeding values (EBVs) can be developed for complex potato traits. Using a combination of MAS and EBVs for simple and complex traits can lead to a significant reduction in the length of the breeding cycle for the identification of superior germplasm.

Assessment of genetic variation within a global collection of lentil (Lens culinaris Medik.) cultivars and landraces using SNP markers.

BACKGROUND: Lentil is a self-pollinated annual diploid (2n = 2× = 14) crop with a restricted history of genetic improvement through breeding, particularly when compared to cereal crops. This limited breeding has probably contributed to the narrow genetic base of local cultivars, and a corresponding potential to continue yield increases and stability. Therefore, knowledge of genetic variation and relationships between populations is important for understanding of available genetic variability and its potential for use in breeding programs. Single nucleotide polymorphism (SNP) markers provide a method for rapid automated genotyping and subsequent data analysis over large numbers of samples, allowing assessment of genetic relationships between genotypes. RESULTS: In order to investigate levels of genetic diversity within lentil germplasm, 505 cultivars and landraces were genotyped with 384 genome-wide distributed SNP markers, of which 266 (69.2%) obtained successful amplification and detected polymorphisms. Gene diversity and PIC values varied between 0.108-0.5 and 0.102-0.375, with averages of 0.419 and 0.328, respectively. On the basis of clarity and interest to lentil breeders, the genetic structure of the germplasm collection was analysed separately for cultivars and landraces. A neighbour-joining (NJ) dendrogram was constructed for commercial cultivars, in which lentil cultivars were sorted into three major groups (G-I, G-II and G-III). These results were further supported by principal coordinate analysis (PCoA) and STRUCTURE, from which three clear clusters were defined based on differences in geographical location. In the case of landraces, a weak correlation between geographical origin and genetic relationships was observed. The landraces from the Mediterranean region, predominantly Greece and Turkey, revealed very high levels of genetic diversity. CONCLUSIONS: Lentil cultivars revealed clear clustering based on geographical origin, but much more limited correlation between geographic origin and genetic diversity was observed for landraces. These results suggest that selection of divergent parental genotypes for breeding should be made actively on the basis of systematic assessment of genetic distance between genotypes, rather than passively based on geographical distance.

SNP marker discovery, linkage map construction and identification of QTLs for enhanced salinity tolerance in field pea (Pisum sativum L.).

BACKGROUND: Field pea (Pisum sativum L.) is a self-pollinating, diploid, cool-season food legume. Crop production is constrained by multiple biotic and abiotic stress factors, including salinity, that cause reduced growth and yield. Recent advances in genomics have permitted the development of low-cost high-throughput genotyping systems, allowing the construction of saturated genetic linkage maps for identification of quantitative trait loci (QTLs) associated with traits of interest. Genetic markers in close linkage with the relevant genomic regions may then be implemented in varietal improvement programs. RESULTS: In this study, single nucleotide polymorphism (SNP) markers associated with expressed sequence tags (ESTs) were developed and used to generate comprehensive linkage maps for field pea. From a set of 36,188 variant nucleotide positions detected through in silico analysis, 768 were selected for genotyping of a recombinant inbred line (RIL) population. A total of 705 SNPs (91.7%) successfully detected segregating polymorphisms. In addition to SNPs, genomic and EST-derived simple sequence repeats (SSRs) were assigned to the genetic map in order to obtain an evenly distributed genome-wide coverage. Sequences associated with the mapped molecular markers were used for comparative genomic analysis with other legume species. Higher levels of conserved synteny were observed with the genomes of Medicago truncatula Gaertn. and chickpea (Cicer arietinum L.) than with soybean (Glycine max [L.] Merr.), Lotus japonicus L. and pigeon pea (Cajanus cajan [L.] Millsp.). Parents and RIL progeny were screened at the seedling growth stage for responses to salinity stress, imposed by addition of NaCl in the watering solution at a concentration of 18 dS m-1. Salinity-induced symptoms showed normal distribution, and the severity of the symptoms increased over time. QTLs for salinity tolerance were identified on linkage groups Ps III and VII, with flanking SNP markers suitable for selection of resistant cultivars. Comparison of sequences underpinning these SNP markers to the M. truncatula genome defined genomic regions containing candidate genes associated with saline stress tolerance. CONCLUSION: The SNP assays and associated genetic linkage maps developed in this study permitted identification of salinity tolerance QTLs and candidate genes. This constitutes an important set of tools for marker-assisted selection (MAS) programs aimed at performance enhancement of field pea cultivars.

The Cannabis Plant as a Complex System: Interrelationships between Cannabinoid Compositions, Morphological, Physiological and Phenological Traits.

Maintaining specific and reproducible cannabinoid compositions (type and quantity) is essential for the production of cannabis-based remedies that are therapeutically effective. The current study investigates factors that determine the plant's cannabinoid profile and examines interrelationships between plant features (growth rate, phenology and biomass), inflorescence morphology (size, shape and distribution) and cannabinoid content. An examination of differences in cannabinoid profile within genotypes revealed that across the cultivation facility, cannabinoids' qualitative traits (ratios between cannabinoid quantities) remain fairly stable, while quantitative traits (the absolute amount of Δ9-tetrahydrocannabinol (THC), cannabidiol (CBD), cannabichromene (CBC), cannabigerol (CBG), Δ9-tetrahydrocannabivarin (THCV) and cannabidivarin (CBDV)) can significantly vary. The calculated broad-sense heritability values imply that cannabinoid composition will have a strong response to selection in comparison to the morphological and phenological traits of the plant and its inflorescences. Moreover, it is proposed that selection in favour of a vigorous growth rate, high-stature plants and wide inflorescences is expected to increase overall cannabinoid production. Finally, a range of physiological and phenological features was utilised for generating a successful model for the prediction of cannabinoid production. The holistic approach presented in the current study provides a better understanding of the interaction between the key features of the cannabis plant and facilitates the production of advanced plant-based medicinal substances.

Fine-scale genomic tracking of Ross River virus using nanopore sequencing.

BACKGROUND: Ross River virus (RRV) is Australia's most common and widespread mosquito-transmitted arbovirus and is of significant public health concern. With increasing anthropogenic impacts on wildlife and mosquito populations, it is important that we understand how RRV circulates in its endemic hotspots to determine where public health efforts should be directed. Current surveillance methods are effective in locating the virus but do not provide data on the circulation of the virus and its strains within the environment. This study examined the ability to identify single nucleotide polymorphisms (SNPs) within the variable E2/E3 region by generating full-length haplotypes from a range of mosquito trap-derived samples. METHODS: A novel tiled primer amplification workflow for amplifying RRV was developed with analysis using Oxford Nanopore Technology's MinION and a custom ARTIC/InterARTIC bioinformatic protocol. By creating a range of amplicons across the whole genome, fine-scale SNP analysis was enabled by specifically targeting the variable region that was amplified as a single fragment and established haplotypes that informed spatial-temporal variation of RRV in the study site in Victoria. RESULTS: A bioinformatic and laboratory pipeline was successfully designed and implemented on mosquito whole trap homogenates. Resulting data showed that genotyping could be conducted in real time and that whole trap consensus of the viruses (with major SNPs) could be determined in a timely manner. Minor variants were successfully detected from the variable E2/E3 region of RRV, which allowed haplotype determination within complex mosquito homogenate samples. CONCLUSIONS: The novel bioinformatic and wet laboratory methods developed here will enable fast detection and characterisation of RRV isolates. The concepts presented in this body of work are transferable to other viruses that exist as quasispecies in samples. The ability to detect minor SNPs, and thus haplotype strains, is critically important for understanding the epidemiology of viruses their natural environment.

Genome-wide SNP identification in multiple morphotypes of allohexaploid tall fescue (Festuca arundinacea Schreb).

BACKGROUND: Single nucleotide polymorphisms (SNPs) provide essential tools for the advancement of research in plant genomics, and the development of SNP resources for many species has been accelerated by the capabilities of second-generation sequencing technologies. The current study aimed to develop and use a novel bioinformatic pipeline to generate a comprehensive collection of SNP markers within the agriculturally important pasture grass tall fescue; an outbreeding allopolyploid species displaying three distinct morphotypes: Continental, Mediterranean and rhizomatous. RESULTS: A bioinformatic pipeline was developed that successfully identified SNPs within genotypes from distinct tall fescue morphotypes, following the sequencing of 414 polymerase chain reaction (PCR) - generated amplicons using 454 GS FLX technology. Equivalent amplicon sets were derived from representative genotypes of each morphotype, including six Continental, five Mediterranean and one rhizomatous. A total of 8,584 and 2,292 SNPs were identified with high confidence within the Continental and Mediterranean morphotypes respectively. The success of the bioinformatic approach was demonstrated through validation (at a rate of 70%) of a subset of 141 SNPs using both SNaPshot™ and GoldenGate™ assay chemistries. Furthermore, the quantitative genotyping capability of the GoldenGate™ assay revealed that approximately 30% of the putative SNPs were accessible to co-dominant scoring, despite the hexaploid genome structure. The sub-genome-specific origin of each SNP validated from Continental tall fescue was predicted using a phylogenetic approach based on comparison with orthologous sequences from predicted progenitor species. CONCLUSIONS: Using the appropriate bioinformatic approach, amplicon resequencing based on 454 GS FLX technology is an effective method for the identification of polymorphic SNPs within the genomes of Continental and Mediterranean tall fescue. The GoldenGate™ assay is capable of high-throughput co-dominant SNP allele detection, and minimises the problems associated with SNP genotyping in a polyploid by effectively reducing the complexity to a diploid system. This SNP collection may now be refined and used in applications such as cultivar identification, genetic linkage map construction, genome-wide association studies and genomic selection in tall fescue. The bioinformatic pipeline described here represents an effective general method for SNP discovery within outbreeding allopolyploid species.

Transcriptome sequencing of field pea and faba bean for discovery and validation of SSR genetic markers.

BACKGROUND: Field pea (Pisum sativum L.) and faba bean (Vicia faba L.) are cool-season grain legume species that provide rich sources of food for humans and fodder for livestock. To date, both species have been relative 'genomic orphans' due to limited availability of genetic and genomic information. A significant enrichment of genomic resources is consequently required in order to understand the genetic architecture of important agronomic traits, and to support germplasm enhancement, genetic diversity, population structure and demographic studies. RESULTS: cDNA samples obtained from various tissue types of specific field pea and faba bean genotypes were sequenced using 454 Roche GS FLX Titanium technology. A total of 720,324 and 304,680 reads for field pea and faba bean, respectively, were de novo assembled to generate sets of 70,682 and 60,440 unigenes. Consensus sequences were compared against the genome of the model legume species Medicago truncatula Gaertn., as well as that of the more distantly related, but better-characterised genome of Arabidopsis thaliana L.. In comparison to M. truncatula coding sequences, 11,737 and 10,179 unique hits were obtained from field pea and faba bean. Totals of 22,057 field pea and 18,052 faba bean unigenes were subsequently annotated from GenBank. Comparison to the genome of soybean (Glycine max L.) resulted in 19,451 unique hits for field pea and 16,497 unique hits for faba bean, corresponding to c. 35% and 30% of the known gene space, respectively. Simple sequence repeat (SSR)-containing expressed sequence tags (ESTs) were identified from consensus sequences, and totals of 2,397 and 802 primer pairs were designed for field pea and faba bean. Subsets of 96 EST-SSR markers were screened for validation across modest panels of field pea and faba bean cultivars, as well as related non-domesticated species. For field pea, 86 primer pairs successfully obtained amplification products from one or more template genotypes, of which 59% revealed polymorphism between 6 genotypes. In the case of faba bean, 81 primer pairs displayed successful amplification, of which 48% detected polymorphism. CONCLUSIONS: The generation of EST datasets for field pea and faba bean has permitted effective unigene identification and functional sequence annotation. EST-SSR loci were detected at incidences of 14-17%, permitting design of comprehensive sets of primer pairs. The subsets from these primer pairs proved highly useful for polymorphism detection within Pisum and Vicia germplasm.

Molecular characterisation and interpretation of genetic diversity within globally distributed germplasm collections of tall fescue (Festuca arundinacea Schreb.) and meadow fescue (F. pratensis Huds.).

Allohexaploid tall fescue (Festuca arundinacea Schreb. syn. Lolium arundinaceum [Schreb.] Darbysh.) is an agriculturally important grass cultivated for pasture and turf world-wide. Genetic improvement of tall fescue could benefit from the use of non-domesticated germplasm to diversify breeding populations through the incorporation of novel and superior allele content. However, such potential germplasm must first be characterised, as three major morphotypes (Continental, Mediterranean and rhizomatous) with varying degrees of hybrid interfertility are commonly described within this species. As hexaploid tall fescue is also a member of a polyploid species complex that contains tetraploid, octoploid and decaploid taxa, it is also possible that germplasm collections may have inadvertently sampled some of these sub-species. In this study, 1,040 accessions from the publicly available United States Department of Agriculture tall fescue and meadow fescue germplasm collections were investigated. Sequence of the chloroplast genome-located matK gene and the nuclear ribosomal DNA internal transcribed spacer (rDNA ITS) permitted attribution of accessions to the three previously known morphotypes and also revealed the presence of tall fescue sub-species of varying ploidy levels, as well as other closely related species. The majority of accessions were, however, identified as Continental hexaploid tall fescue. Analysis using 34 simple sequence repeat markers was able to further investigate the level of genetic diversity within each hexaploid tall fescue morphotype group. At least two genetically distinct sub-groups of Continental hexaploid tall fescue were identified which are probably associated with palaeogeographic range expansion of this morphotype. This work has comprehensively characterised a large and complex germplasm collection and has identified genetically diverse accessions which may potentially contribute valuable alleles at agronomic loci for tall fescue cultivar improvement programs.

Quantitative Trait Locus (QTL) meta-analysis and comparative genomics for candidate gene prediction in perennial ryegrass (Lolium perenne L.).

BACKGROUND: In crop species, QTL analysis is commonly used for identification of factors contributing to variation of agronomically important traits. As an important pasture species, a large number of QTLs have been reported for perennial ryegrass based on analysis of biparental mapping populations. Further characterisation of those QTLs is, however, essential for utilisation in varietal improvement programs. RESULTS: A bibliographic survey of perennial ryegrass trait-dissection studies identified a total of 560 QTLs from previously published papers, of which 189, 270 and 101 were classified as morphology-, physiology- and resistance/tolerance-related loci, respectively. The collected dataset permitted a subsequent meta-QTL study and implementation of a cross-species candidate gene identification approach. A meta-QTL analysis based on use of the BioMercator software was performed to identify two consensus regions for pathogen resistance traits. Genes that are candidates for causal polymorphism underpinning perennial ryegrass QTLs were identified through in silico comparative mapping using rice databases, and 7 genes were assigned to the p150/112 reference map. Markers linked to the LpDGL1, LpPh1 and LpPIPK1 genes were located close to plant size, leaf extension time and heading date-related QTLs, respectively, suggesting that these genes may be functionally associated with important agronomic traits in perennial ryegrass. CONCLUSIONS: Functional markers are valuable for QTL meta-analysis and comparative genomics. Enrichment of such genetic markers may permit further detailed characterisation of QTLs. The outcomes of QTL meta-analysis and comparative genomics studies may be useful for accelerated development of novel perennial ryegrass cultivars with desirable traits.