Rebecca C. Baillie

Assessment of genetic diversity in Australian canola (Brassica napus L.) cultivars using SSR markers

Australian canola (Brassica napus L.) has been relatively isolated from the global gene pool and limited knowledge is available for genetic variability based on DNA profiling. In the present study, genetic diversity of recent Australian canola cultivars was determined by simple sequence repeat (SSR) marker analysis. In total, 405 individuals from 48 varieties were genotyped with 18 primer pairs, resulting in 112 polymorphic features. The number of polymorphic features amplified by each SSR primer pair varied from 3 to 16. Analysis of molecular variance (AMOVA) detected 53.7% and 46.3% within- and between-cultivar variation, respectively. Intra-cultivar genetic variability differed according to cultivar. The number of polymorphic features per cultivar varied from 35 (Ag-Spectrum) to 72 (Ag-Insignia), while mean sum of squares (MSS) varied from 6.29 (Tornado TT) to 24.76 (Ag-Emblem). Genetic differentiation of cultivars generally reflected pedigree structure and origin by breeding organisation. Clustering and principal coordinate analysis (PCoA) indicated that the individuals were separated into 4 major groups. The genetic diversity information from this study will be useful for future Australian canola breeding programs.

Development and implementation of a multiplexed single nucleotide polymorphism genotyping tool for differentiation of ryegrass species and cultivars

Perennial ryegrass (Lolium perenne L.) and Italian ryegrass (Lolium multiflorum Lam.) are important temperate forage grasses which are closely related, generating fertile interspecific hybrids. All groups are represented by multiple cultivars in the commercial pasture seeds market. Due to the close taxonomic relationship between the two species, differentiation based on morphophysiological criteria is not always readily achievable. In addition, an obligate outbreeding reproductive habit produces high levels of individual heterozygosity and intrapopulation diversity, which presents problems for discrimination between cultivars. Molecular genetic marker polymorphism provides an effective means of addressing these challenges. An iterative process of resequencing from loci distributed across the perennial ryegrass genome was used to identify single nucleotide polymorphism (SNP) markers, which were then validated and formatted in a highly multiplexed (384-plex) assay system. SNP genotyping was then performed across samples of 48–192 individuals from a total of 27 ryegrass cultivars (19 of perennial ryegrass, seven of Italian ryegrass and one hybrid cultivar). SNP markers from perennial ryegrass exhibited a high level of transfer to Italian ryegrass. Data analysis permitted quantification of intra- and inter-species diversity, as well as discrimination between cultivars within each species, including diploid and autotetraploid cultivars of perennial ryegrass. Lower levels of SNP-based diversity were detected in Italian ryegrass than in perennial ryegrass. A neighbour-joining tree based on genetic distance analysis located a hybrid cultivar to an intermediate position between the two species-specific cultivar groups. The resulting catalogue of ryegrass cultivars will provide support for the processes of cultivar accreditation and quality assurance.

Molecular genetic marker-based analysis of species- differentiated phenotypic characters in an interspecific ryegrass mapping population

The genus Lolium (ryegrasses) exhibits substantial variation between species for annual-perennial growth habit. The genetic bases of this trait, and other characters that are differentiated between taxa, have been investigated through molecular genetic marker-based mapping of an interspecific mapping population derived from pair-wise crossing of single genotypes from Lincoln, a long-lived cultivar of perennial ryegrass, and Andrea, a cultivar of annual-type Italian ryegrass. The Andrea1246 and Lincoln1133 parental maps contained 122 loci on eight linkage groups (LGs), and 169 loci on seven LGs, respectively. A total of 10 phenotypic traits were measured, including annuality-perenniality index, date of head emergence, number of spikes per plant, number of spikelets per spike, number of floret per spike, flag leaf length, flag leaf width, spike length, stem length, and extent of regrowth. A total of 31 putative quantitative trait loci (QTLs) were detected. Regions of significance were identified on Andrea1246 LGs 1, 2, 3 and 6. An annuality-perenniality index QTL on LG2 accounted for ~30% of trait-specific phenotypic variance (Vp). In addition, LG2 contained coincident QTLs for the number of spikes per plant and head emergence date traits. The Lincoln1133 genetic map displayed QTL-containing regions of significance on LGs 1, 4, 5 and 7, accounting individually for 10–22% of Vp. QTLs identified in this study provide potential targets for ryegrass breeding in order to improve vegetative yield, persistence and seed yield.

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

Key messageA targeted amplicon-based genotyping-by-sequencing approach has permitted cost-effective and accurate discrimination betweenryegrass species (perennial, Italian and inter-species hybrid), and identification of cultivars based on bulked samples.AbstractPerennial 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.

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

Summary 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 messageExploitation 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.AbstractGenomic 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.