Developing an integrated genomic selection approach beyond biomass for varietal protection and nutritive traits in perennial ryegrass (Lolium perenne L.).

KEY MESSAGE: Breeding target traits can be broadened to include nutritive value and plant breeder's rights traits in perennial ryegrass by using in-field regression-based spectroscopy phenotyping and genomic selection. Perennial ryegrass breeding has focused on biomass yield, but expansion into a broader set of traits is needed to benefit livestock industries whilst also providing support for intellectual property protection of cultivars. Numerous breeding objectives can be targeted simultaneously with the development of sensor-based phenomics and genomic selection (GS). Of particular interest are nutritive value (NV), which has been difficult and expensive to measure using traditional phenotyping methods, resulting in limited genetic improvement to date, and traits required to obtain varietal protection, known as plant breeder's rights (PBR) traits. In order to assess phenotyping requirements for NV improvement and potential for genetic improvement, in-field reflectance-based spectroscopy was assessed and GS evaluated in a single population for three key NV traits, captured across four timepoints. Using three prediction approaches, the possibility of targeting PBR traits using GS was evaluated for five traits recorded across three years of a breeding program. Prediction accuracy was generally low to moderate for NV traits and moderate to high for PBR traits, with heritability highly correlated with GS accuracy. NV did not show significant or consistent correlation between timepoints highlighting the need to incorporate seasonal NV into selection indexes and the value of being able to regularly monitor NV across seasons. This study has demonstrated the ability to implement GS for both NV and PBR traits in perennial ryegrass, facilitating the expansion of ryegrass breeding targets to agronomically relevant traits while ensuring necessary varietal protection is achieved.

In silico analysis enabling informed design for genome editing in medicinal cannabis; gene families and variant characterisation.

BACKGROUND: Cannabis has been used worldwide for centuries for industrial, recreational and medicinal use, however, to date no successful attempts at editing genes involved in cannabinoid biosynthesis have been reported. This study proposes and develops an in silico best practices approach for the design and implementation of genome editing technologies in cannabis to target all genes involved in cannabinoid biosynthesis. RESULTS: A large dataset of reference genomes was accessed and mined to determine copy number variation and associated SNP variants for optimum target edit sites for genotype independent editing. Copy number variance and highly polymorphic gene sequences exist in the genome making genome editing using CRISPR, Zinc Fingers and TALENs technically difficult. Evaluation of allele or additional gene copies was determined through nucleotide and amino acid alignments with comparative sequence analysis performed. From determined gene copy number and presence of SNPs, multiple online CRISPR design tools were used to design sgRNA targeting every gene, accompanying allele and homologs throughout all involved pathways to create knockouts for further investigation. Universal sgRNA were designed for highly homologous sequences using MultiTargeter and visualised using Sequencher, creating unique sgRNA avoiding SNP and shared nucleotide locations targeting optimal edit sites. CONCLUSIONS: Using this framework, the approach has wider applications to all plant species regardless of ploidy number or highly homologous gene sequences. SIGNIFICANCE STATEMENT: Using this framework, a best-practice approach to genome editing is possible in all plant species, including cannabis, delivering a comprehensive in silico evaluation of the cannabinoid pathway diversity from a large set of whole genome sequences. Identification of SNP variants across all genes could improve genome editing potentially leading to novel applications across multiple disciplines, including agriculture and medicine.

Meta-analysis of GWAS in canola blackleg (Leptosphaeria maculans) disease traits demonstrates increased power from imputed whole-genome sequence.

Blackleg disease causes yield losses in canola (Brassica napus L.). To identify resistance genes and genomic regions, genome-wide association studies (GWAS) of 585 diverse winter and spring canola accessions were performed using imputed whole-genome sequence (WGS) and transcriptome genotype-by-sequencing (GBSt). Blackleg disease phenotypes were collected across three years in six trials. GWAS were performed in several ways and their respective power was judged by the number of significant single nucleotide polymorphisms (SNP), the false discovery rate (FDR), and the percentage of SNP that validated in additional field trials in two subsequent years. WGS GWAS with 1,234,708 million SNP detected a larger number of significant SNP, achieved a lower FDR and a higher validation rate than GBSt with 64,072 SNP. A meta-analysis combining survival and average internal infection resulted in lower FDR but also lower validation rates. The meta-analysis GWAS identified 79 genomic regions (674 SNP) conferring potential resistance to L. maculans. While several GWAS signals localised in regions of known Rlm genes, fifty-three new potential resistance regions were detected. Seventeen regions had underlying genes with putative functions related to disease defence or stress response in Arabidopsis thaliana. This study provides insight into the genetic architecture and potential molecular mechanisms underlying canola L. maculans resistance.

Genetic map construction and QTL mapping of resistance to blackleg (Leptosphaeria maculans) disease in Australian canola (Brassica napus L.) cultivars.

Genetic map construction and identification of quantitative trait loci (QTLs) for blackleg resistance were performed for four mapping populations derived from five different canola source cultivars. Three of the populations were generated from crosses between single genotypes from the blackleg-resistant cultivars Caiman, Camberra and (AV)Sapphire and the blackleg-susceptible cultivar Westar(10). The fourth population was derived from a cross between genotypes from two blackleg resistant varieties (Rainbow and (AV)Sapphire). Different types of DNA-based markers were designed and characterised from a collection of 20,000 EST sequences generated from multiple Brassica species, including a new set of 445 EST-SSR markers of high value to the international community. Multiple molecular genetic marker systems were used to construct linkage maps with locus numbers varying between 219 and 468, and coverage ranging from 1173 to 1800 cM. The proportion of polymorphic markers assigned to map locations varied from 70 to 89% across the four populations. Publicly available simple sequence repeat markers were used to assign linkage groups to reference nomenclature, and a sub-set of mapped markers were also screened on the Tapidor x Ningyou (T x N) reference population to assist this process. QTL analysis was performed based on percentage survival at low and high disease pressure sites. Multiple QTLs were identified across the four mapping populations, accounting for 13-33% of phenotypic variance (V (p)). QTL-linked marker data are suitable for implementation in breeding for disease resistance in Australian canola cultivars. However, the likelihood of shifts in pathogen race structure across different geographical locations may have implications for the long-term durability of such associations.

Assessment of low-coverage nanopore long read sequencing for SNP genotyping in doubled haploid canola (Brassica napus L.).

Despite the high accuracy of short read sequencing (SRS), there are still issues with attaining accurate single nucleotide polymorphism (SNP) genotypes at low sequencing coverage and in highly duplicated genomes due to misalignment. Long read sequencing (LRS) systems, including the Oxford Nanopore Technologies (ONT) minION, have become popular options for de novo genome assembly and structural variant characterisation. The current high error rate often requires substantial post-sequencing correction and would appear to prevent the adoption of this system for SNP genotyping, but nanopore sequencing errors are largely random. Using low coverage ONT minION sequencing for genotyping of pre-validated SNP loci was examined in 9 canola doubled haploids. The minION genotypes were compared to the Illumina sequences to determine the extent and nature of genotype discrepancies between the two systems. The significant increase in read length improved alignment to the genome and the absence of classical SRS biases results in a more even representation of the genome. Sequencing errors are present, primarily in the form of heterozygous genotypes, which can be removed in completely homozygous backgrounds but requires more advanced bioinformatics in heterozygous genomes. Developments in this technology are promising for routine genotyping in the future.

Validation of Genotyping by Sequencing Using Transcriptomics for Diversity and Application of Genomic Selection in Tetraploid Potato.

Potato is an important food crop due to its increasing consumption, and as a result, there is demand for varieties with improved production. However, the current status of breeding for improved varieties is a long process which relies heavily on phenotypic evaluation and dated molecular techniques and has little emphasis on modern genotyping approaches. Evaluation and selection before a cultivar is commercialized typically takes 10-15 years. Molecular markers have been developed for disease and pest resistance, resulting in initial marker-assisted selection in breeding. This study has evaluated and implemented a high-throughput transcriptome sequencing method for dense marker discovery in potato for the application of genomic selection. An Australian relevant collection of commercial cultivars was selected, and identification and distribution of high quality SNPs were examined using standard bioinformatic pipelines and a custom approach for the prediction of allelic dosage. As a result, a large number of SNP markers were identified and filtered to generate a high-quality subset that was then combined with historic phenotypic data to assess the approach for genomic selection. Genomic selection potential was predicted for highly heritable traits and the approach demonstrated advantages over the previously used technologies in terms of markers identified as well as costs incurred. The high-quality SNP list also provided acceptable genome coverage which demonstrates its applicability for much larger future studies. This SNP list was also annotated to provide an indication of function and will serve as a resource for the community in future studies. Genome wide marker tools will provide significant benefits for potato breeding efforts and the application of genomic selection will greatly enhance genetic progress.

Effective mosquito and arbovirus surveillance using metabarcoding.

Effective vector and arbovirus surveillance requires timely and accurate screening techniques that can be easily upscaled. Next-generation sequencing (NGS) is a high-throughput technology that has the potential to modernize vector surveillance. When combined with DNA barcoding, it is termed 'metabarcoding.' The aim of our study was to establish a metabarcoding protocol to characterize pools of mosquitoes and screen them for virus. Pools contained 100 morphologically identified individuals, including one Ross River virus (RRV) infected mosquito, with three species present at different proportions: 1, 5, 94%. Nucleic acid extracted from both crude homogenate and supernatant was used to amplify a 269-bp section of the mitochondrial cytochrome c oxidase subunit I (COI) locus. Additionally, a 67-bp region of the RRV E2 gene was amplified from synthesized cDNA to screen for RRV. Amplicon sequencing was performed using an Illumina MiSeq, and bioinformatic analysis was performed using a DNA barcode database of Victorian mosquitoes. Metabarcoding successfully detected all mosquito species and RRV in every positive sample tested. The limits of species detection were also examined by screening a pool of 1000 individuals, successfully identifying the species and RRV from a single mosquito. The primers used for amplification, number of PCR cycles and total number of individuals present all have effects on the quantification of species in mixed bulk samples. Based on the results, a number of recommendations for future metabarcoding studies are presented. Overall, metabarcoding shows great promise for providing a new alternative approach to screening large insect surveillance trap catches.

Discovery and genetic mapping of single nucleotide polymorphisms in candidate genes for pathogen defence response in perennial ryegrass (Lolium perenne L.).

Susceptibility to foliar pathogens commonly causes significant reductions in productivity of the important temperate forage perennial ryegrass. Breeding for durable disease resistance involves not only the deployment of major genes but also the additive effects of minor genes. An approach based on in vitro single nucleotide polymorphism (SNP) discovery in candidate defence response (DR) genes has been used to develop potential diagnostic genetic markers. SNPs were predicted, validated and mapped for representatives of the pathogenesis-related (PR) protein-encoding and reactive oxygen species (ROS)-generating gene classes. The F(1)(NA(6) x AU(6)) two-way pseudo-test cross population was used for SNP genetic mapping and detection of quantitative trait loci (QTLs) in response to a crown rust field infection. Novel resistance QTLs were coincident with mapped DR gene SNPs. QTLs on LG3 and LG7 also coincided with both herbage quality QTLs and candidate genes for lignin biosynthesis. Multiple DR gene SNP loci additionally co-located with QTLs for grey leaf spot, bacterial wilt and crown rust resistance from other published studies. Further functional validation of DR gene SNP loci using methods such as fine-mapping and association genetics will improve the efficiency of parental selection based on superior allele content.

Validation of in silico-predicted genic SNPs in white clover (Trifolium repens L.), an outbreeding allopolyploid species.

White clover (Trifolium repens L.) is an obligate outbreeding allotetraploid forage legume. Gene-associated SNPs provide the optimum genetic system for improvement of such crop species. An EST resource obtained from multiple cDNA libraries constructed from numerous genotypes of a single cultivar has been used for in silico SNP discovery and validation. A total of 58 from 236 selected sequence clusters (24.5%) were fully validated as containing polymorphic SNPs by genotypic analysis across the parents and progeny of several two-way pseudo-testcross mapping families. The clusters include genes belonging to a broad range of predicted functional categories. Polymorphic SNP-containing ESTs have also been used for comparative genomic analysis by comparison with whole genome data from model legume species, as well as Arabidopsis thaliana. A total of 29 (50%) of the 58 clusters detected putative ortholoci with known chromosomal locations in Medicago truncatula, which is closely related to white clover within the Trifolieae tribe of the Fabaceae. This analysis provides access to translational data from model species. The efficiency of in silico SNP discovery in white clover is limited by paralogous and homoeologous gene duplication effects, which are resolved unambiguously by the transmission test. This approach will also be applicable to other agronomically important cross-pollinating allopolyploid plant species.

Individual and multi-environment combined analyses identify QTLs for morphogenetic and reproductive development traits in white clover (Trifolium repens L.).

White clover (Trifolium repens L.) is a key component legume of temperate pasture agriculture and an important target for molecular marker-assisted plant breeding. A genetic map of white clover has been used to assess genetic control of agronomically important traits that vary in the F2(I.4RxI.5J) mapping family. Phenotypic analysis was performed for a range of vegetative morphogenesis traits (such as leaf area, internode length, plant height and plant spread) and reproductive morphogenesis and development traits (such as flowering date, floral intensity and seed yield), with both spatial and temporal replication. A multi-environment combined analysis (combined analysis) has been performed for traits assessed across multiple experimental datasets in order to identify consistent genetic effects. Quantitative trait locus (QTLs) were detected for the majority of traits, and the locations and magnitudes of QTL effects were compared between individual and combined analyses. This molecular genetic dissection of agronomic traits in white clover provides the basis for equivalent studies in more complex populations, design of marker-assisted selection strategies and comparative genetics with model legume species. Selection for QTLs derived from the combined analysis will permit robust improvement of phenotypic traits over different environments.

Molecular cloning and genetic mapping of perennial ryegrass casein protein kinase 2 alpha-subunit genes.

The alpha-subunit of the casein protein kinase CK2 has been implicated in both light-regulated and circadian rhythm-controlled plant gene expression, including control of the flowering time. Two putative CK2alpha genes of perennial ryegrass (Lolium perenne L.) have been obtained from a cDNA library constructed with mRNA isolated from cold-acclimated crown tissue. The genomic organisation of the two genes was determined by Southern hybridisation analysis. Primer designs to the Lpck2a-1 and Lpck2a-2 cDNA sequences permitted the amplification of genomic products containing large intron sequences. Amplicon sequence analysis detected single nucleotide polymorphisms (SNPs) within the p150/112 reference mapping population. Validated SNPs, within diagnostic restriction enzyme sites, were used to design cleaved amplified polymorphic sequence (CAPS) assays. The Lpck2a-1 CAPS marker was assigned to perennial ryegrass linkage group (LG) 4 and the Lpck2a-2 CAPS marker was assigned to LG2. The location of the Lpck2a-1 gene locus supports the previous conclusion of conserved synteny between perennial ryegrass LG4, the Triticeae homoeologous group 5L chromosomes and the corresponding segment of rice chromosome 3. Allelic variation at the Lpck2a-1 and Lpck2a-2 gene loci was correlated with phenotypic variation for heading date and winter survival, respectively. SNP polymorphism may be used for the further study of the role of CK2alpha genes in the initiation of reproductive development and winter hardiness in grasses.

QTL analysis and comparative genomics of herbage quality traits in perennial ryegrass (Lolium perenne L.).

Genetic control of herbage quality variation was assessed through the use of the molecular marker-based reference genetic map of perennial ryegrass (Lolium perenne L.). The restriction fragment length polymorphism (RFLP), amplified fragment length polymorphism (AFLP) and genomic DNA-derived simple sequence repeat-based (SSR) framework marker set was enhanced, with RFLP loci corresponding to genes for key enzymes involved in lignin biosynthesis and fructan metabolism. Quality traits such as crude protein (CP) content, estimated in vivo dry matter digestibility (IVVDMD), neutral detergent fibre content (NDF), estimated metabolisable energy (EstME) and water soluble carbohydrate (WSC) content were measured by near infrared reflectance spectroscopy (NIRS) analysis of herbage harvests. Quantitative trait locus (QTL) analysis was performed using single-marker regression, simple interval mapping and composite interval mapping approaches, detecting a total of 42 QTLs from six different sampling experiments varying by developmental stage (anthesis or vegetative growth), location or year. Coincident QTLs were detected on linkage groups (LGs) 3, 5 and 7. The region on LG3 was associated with variation for all measured traits across various experimental datasets. The region on LG7 was associated with variation for all traits except CP, and is located in the vicinity of the lignin biosynthesis gene loci xlpomt1 (caffeic acid-O-methyltransferase), xlpccr1 (cinnamoyl CoA-reductase) and xlpssrcad 2.1 (cinnamyl alcohol dehydrogenase). Comparative genomics analysis of these gene classes with wheat (Triticum aestivum L.) provides evidence for conservation of gene order over evolutionary time and the basis for cross-specific genetic information transfer. The identification of co-location between QTLs and functionally associated genetic markers is critical for the implementation of marker-assisted selection programs and for linkage disequilibrium studies, which will enable future improvement strategies for perennial ryegrass.