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Background and Aims Clonality is a key life-history strategy promoting on-spot persistence, space occupancy, resprouting after disturbance, and resource storage, sharing and foraging. These functions provided by clonality can be advantageous under different environmental conditions, including resource-paucity and fire-proneness, which define most mediterranean-type open ecosystems, such as southwest Australian shrublands. Studying clonality–environment links in underexplored mediterranean shrublands could therefore deepen our understanding of the role played by this essential strategy in open ecosystems globally. Methods We created a new dataset including 463 species, six traits related to clonal growth organs (CGOs; lignotubers, herbaceous and woody rhizomes, stolons, tubers, stem fragments), and edaphic predictors of soil water availability, nitrogen (N) and phosphorus (P) from 138 plots. Within two shrubland communities, we explored multivariate clonal patterns and how the diversity of CGOs, and abundance-weighted and unweighted proportions .of clonality in plots changed along with the edaphic gradients. Key Results We found clonality in 65 % of species; the most frequent were those with lignotubers (28 %) and herbaceous rhizomes (26 %). In multivariate space, plots clustered into two groups, one distinguished by sandy plots and plants with CGOs, the other by clayey plots and non-clonal species. CGO diversity did not vary along the edaphic gradients (only marginally with water availability). The abundance-weighted proportion of clonal species increased with N and decreased with P and water availability, yet these results were CGO-specific. We revealed almost no relationships for unweighted clonality. Conclusions Clonality is more widespread in shrublands than previously thought, and distinct plant communities are distinguished by specific suites (or lack) of CGOs. We show that weighting belowground traits by aboveground abundance affects the results, with implications for trait-based ecologists using abundance-weighting. We suggest unweighted approaches for belowground organs in open ecosystems until belowground abundance is quantifiable.

Soil microbiota are fundamentally linked to the restoration of degraded ecosystems, as they are central to important ecological functions including the support of plant communities. High throughput sequencing of environmental DNA used to characterise soil microbiota offers promise to monitor ecological progress towards reference states. In post-mining rehabilitation, successful mine closure planning requires specific, measurable, achievable, relevant and time-bound (SMART) completion criteria, such as returning ecological communities to match a target level of similarity to reference sites. We analysed patterns of surface soil bacterial community similarity to reference (9rehabilitation trajectory9) data from three long-term (> 25 year) post-mining rehabilitation chronosequence case studies from south-west Western Australia. We examined the influence of different ecological distance measures, sequence grouping approaches, and eliminating rare taxa on rehabilitation trajectories and predicted recovery times. We also explored the issue of spatial autocorrelation in our rehabilitation trajectory assessments and trialled a first-pass approach for correcting its undue influence. We found considerable variation in bacterial communities among reference sites within each case study minesite, providing valuable context for setting targets and evaluating recovery. Median Bray-Curtis similarities among references within each minesite ranged from 30-36%, based on amplicon sequence variant-level data. Median predicted times for rehabilitated sites to recover to these levels ranged from around 40 to over 100 years. We discuss strengths and limitations of the different approaches and offer recommendations to improve the robustness of this assessment method. Synthesis and applications. We demonstrate a proof-of-concept, complexity-reducing application of soil eDNA sequence-based surveys of bacterial communities in restoration chronosequence studies to quantitatively assess progress towards reference communities and corresponding rehabilitation targets. Our method provides a step towards developing microbiota-based SMART metrics for measuring rehabilitation success in post-mining, and potentially other, restoration contexts. Our approach enables prediction of recovery time, explicitly including uncertainty in assessments, and assists examination of potential barriers to ecological recovery, including biologically-associated variation in soil properties.

The nature of community patterns and environmental drivers in kwongan mediterranean‐type shrubland on nutrient‐poor soils occurring in Western Australia remain poorly examined. We aimed to determine whether (i) classification of the kwongan vegetation of the northern Swan Coastal Plain would be ecologically informative and (ii) which environmental drivers underpin the plant community patterns. The study area was positioned on the northern Swan Coastal Plain, locality of Cooljarloo (30°39′ S, 115°22′ E), situated 170 km north of Perth, Western Australia. Compositional (518 species × 337 releves) and environmental data set (29 variables × 87 releves) describing time since last fire, soil chemical and physical properties, and terrain characteristics were analysed using classification and ordination techniques. OptimClass assisted in the selection of a robust data transformation, resemblance function and clustering algorithm to identify the vegetation patterns. Major ecological drivers of the vegetation patterns were detected using distance‐based redundancy analysis (db‐RDA). Classification revealed major groupings of Wet Heath and Banksia Woodland distinguishable by the high prevalence of myrtyoid and proteoid taxa, respectively. On floristic‐sociological grounds, we recognised four Wet Heath and two Banksia Woodland communities. The Wet Heath was constrained to areas of higher litter depth (db‐RDA axis 1: 9%). Soil chemical and physical properties explained the highest proportion (17%) of the compositional variance, while the terrain‐ and fire‐related variables explained 2% and

Long‐term studies of vegetation recovery following post‐mining restoration in low‐productivity, high‐stress areas are limited, but essential for understanding underlying ecological processes and evaluating management practices. This study's goal was to describe temporal patterns of recovery (up to 37 years) in vegetation structure, floristic diversity, and composition following post‐mining restoration at two sites, and identify potential drivers of restoration outcomes, in the nutrient‐poor, seasonally dry, species‐rich, fire‐prone kwongan vegetation of southwest Western Australia. Vegetation development is progressing and restoration measures are within range of native reference values, but there is large variation in both patterns observed and restoration outcomes. Several patterns described share similarities with post‐fire recovery of kwongan, and post‐disturbance recovery of other low‐productivity, high‐stress, fire‐prone systems. However, differences in some patterns between sites indicate differences in the underlying mechanisms of recovery. Many management and environmental variables emerge as significant drivers of restoration outcomes but age, fire, and the planting of seedlings account for the largest amount of variation. Adaptive management at both sites appears to be facilitating improved restoration outcomes over time. Using a combination of space‐for‐time, plot level, and linear mixed effects modeling perspectives to examine patterns provides greater insights into restoration recovery than a chronosequence perspective alone. This study will inform restoration practices and outcomes not only in kwongan but in other comparable systems also.

In post-mining rehabilitation, successful mine closure planning requires specific, measurable, achievable, relevant and time-bound (SMART) completion criteria, such as returning ecological communities to match a target level of similarity to reference sites. Soil microbiota are fundamentally linked to the restoration of degraded ecosystems, helping to underpin ecological functions and plant communities. High-throughput sequencing of soil eDNA to characterise these communities offers promise to help monitor and predict ecological progress towards reference states. Here we demonstrate a novel methodology for monitoring and evaluating ecological restoration using three long-term (>25 year) case study post-mining rehabilitation soil eDNA-based bacterial community datasets. Specifically, we developed rehabilitation trajectory assessments based on similarity to reference data from restoration chronosequence datasets. Recognising that numerous alternative options for microbiota data processing have potential to influence these assessments, we comprehensively examined the influence of standard versus compositional data analyses, different ecological distance measures, sequence grouping approaches, eliminating rare taxa, and the potential for excessive spatial autocorrelation to impact on results. Our approach reduces the complexity of information that often overwhelms ecologically-relevant patterns in microbiota studies, and enables prediction of recovery time, with explicit inclusion of uncertainty in assessments. We offer a step change in the development of quantitative microbiota-based SMART metrics for measuring rehabilitation success. Our approach may also have wider applications where restorative processes facilitate the shift of microbiota towards reference states.

An understanding of genetic diversity and the population genetic processes that impact future population viability is vital for the management and recovery of declining populations of threatened species. Styphelia longissima (Ericaceae) is a critically endangered shrub, restricted to a single fragmented population near Eneabba, 250 km north of Perth, Western Australia. For this population, we sought to characterize population genetic variation and its spatial structure, and aspects of the mating portfolio, from which strategies that optimize the conservation of this diversity are identified. A comprehensive survey was carried out and 220 adults, and 106 seedlings from 14 maternal plants, were genotyped using 13 microsatellite markers. Levels of genetic variation and its spatial structure were assessed, and mating system parameters were estimated. Paternity was assigned to the offspring of a subsection of plants, which allowed for the calculation of realized pollen dispersal. Allelic richness and levels of expected heterozygosity were higher than predicted for a small isolated population. Spatial autocorrelation analysis identified fine-scale genetic structure at a scale of 20 m, but no genetic structure was found at larger scales. Mean outcrossing rate (tm = 0.66) reflects self-compatibility and a mixed-mating system. Multiple paternity was low, where 61 % of maternal siblings shared the same sire. Realized pollen dispersal was highly restricted, with 95 % of outcrossing events occurring at 7 m or less, and a mean pollen dispersal distance of 3.8 m. Nearest-neighbour matings were common (55 % of all outcross events), and 97 % of mating events were between the three nearest-neighbours. This study has provided critical baseline data on genetic diversity, mating system and pollen dispersal for future monitoring of S. longissima. Broadly applicable conservation strategies such as implementing a genetic monitoring plan, diluting spatial genetic structure in the natural population, genetically optimizing ex situ collections and incorporating genetic knowledge into translocations will help to manage the future erosion of the high genetic variation detected., Styphelia longissima (Ericaceae) is a critically endangered shrub restricted to a single fragmented population near Eneabba, 250 km north of Perth, Western Australia. Here, 13 microsatellite markers were used to genotype 220 adults and 106 seedlings to assess genetic diversity and structure, mating system parameters and pollen dispersal. The only population of S. longissima was found to be characterised by surprisingly high levels of genetic diversity, with small groups of related individuals within which the vast majority of mating occurs. This study has provided critical baseline data for future monitoring and to inform conservation strategies.

QUESTIONS: The community patterns in kwongan, a mediterranean‐type scrub on nutrient‐poor soils occurring in Western Australia, are poorly understood due to only few, focused studies using disparate sampling designs. We aimed to determine whether (a) classification of the kwongan vegetation of the Eneabba Sandplains leads to an ecologically informative classification scheme, and (b) we could identify environmental drivers underpinning the plant community patterns. LOCATION: Township of Eneabba (29°82′S, 115°27′E), approximately 250 km north of Perth, Western Australia, covering 1,210 km². METHODS: We used a data set consisting of 512 releves, collected following the standard field methodology of the Braun‐Blanquet approach, and accompanied by an extensive set of environmental data consisting of 94 variables representing climate, fire, soil and terrain properties across 189 releves. The data were classified and ordinated by a series of multivariate analyses. OptimClass assisted in the selection of the most robust classification procedure. Distance‐based redundancy analysis (db‐RDA) inferred the major ecological drivers of the vegetation patterns. RESULTS: Numerical classification, nonmetric multidimensional scaling, and syntaxonomic tabular analysis revealed two major community groups (MCG A and B), eight community groups, and 17 communities in the kwongan vegetation of the study area. All vegetation units are characterised in terms of floristic composition and position along major ecological gradients in the studied area. The MCGs separated along a composite gradient of soil‐texture and exchangeable cations. The first two db‐RDA axes explained 21% of the total variance which is very low, considering the high number of environmental variables used. CONCLUSIONS: Our study provides a comprehensive insight into the high variability of vegetation types in hyper‐diverse kwongan scrub at a landscape spatial scale; it is the first syntaxonomic account of the Western Australian kwongan vegetation, presenting a complete tabular comparative analysis. The studied major community groups segregate along a soil‐texture and an exchangeable‐cation content gradient. At a community scale, environmental filtering explained a small fraction of the vegetation–environment relationship. We suggest that the unexplained portion of the vegetation‐environment relationship might be a product of slow‐acting neutral processes in this hyper‐diverse system; this assertion is amenable to rigorous future testing.

Vegetation maps are models of the real vegetation patterns and are considered important tools in conservation and management planning. Maps created through traditional methods can be expensive and time‐consuming, thus, new more efficient approaches are needed. The prediction of vegetation patterns using machine learning shows promise, but many factors may impact on its performance. One important factor is the nature of the vegetation–environment relationship assessed and ecological redundancy. We used two datasets with known ecological redundancy levels (strength of the vegetation–environment relationship) to evaluate the performance of four machine learning (ML) classifiers (classification trees, random forests, support vector machines, and nearest neighbor). These models used climatic and soil variables as environmental predictors with pretreatment of the datasets (principal component analysis and feature selection) and involved three spatial scales. We show that the ML classifiers produced more reliable results in regions where the vegetation–environment relationship is stronger as opposed to regions characterized by redundant vegetation patterns. The pretreatment of datasets and reduction in prediction scale had a substantial influence on the predictive performance of the classifiers. The use of ML classifiers to create potential vegetation maps shows promise as a more efficient way of vegetation modeling. The difference in performance between areas with poorly versus well‐structured vegetation–environment relationships shows that some level of understanding of the ecology of the target region is required prior to their application. Even in areas with poorly structured vegetation–environment relationships, it is possible to improve classifier performance by either pretreating the dataset or reducing the spatial scale of the predictions.

Premise of the study: Microsatellite markers were developed for population genetic analysis in the rare shrub Styphelia longissima (Ericaceae). Methods and Results: We generated ca. 2.5 million sequence reads using a Personal Genome Machine semiconductor sequencer. Using the QDD pipeline, we designed primers for >12,000 sequences with PCR product lengths of 80–480 bp. From these, 30 primer pairs were selected and screened using PCR; of these, 16 loci were found to be polymorphic, four loci were monomorphic, and 10 loci did not amplify reliably for S. longissima. For a sample of 57 plants from the only known population, the number of alleles observed for these 16 loci ranged from two to 21 and expected heterozygosity ranged from 0.49 to 0.91. These markers were also amplified in Astroloma xerophyllum, a closely related species. Conclusions: These markers will be used to characterize population genetic variation, spatial genetic structure, mating system parameters, and dispersal to aid in the management and conservation of the rare shrub S. longissima.

The concepts of traits, plant functional types (PFT), and functional communities are effective tools for the study of complex phenomena such as plant community assembly. Here, we (1) suggest a procedure formalising the classification of response traits to construct a PFT system; (2) integrate the PFT, and species compositional data to formally define functional communities; and, (3) identify environmental drivers that underpin the functional-community patterns. A species–trait data set featuring species pooled from two study sites (Eneabba and Cooljarloo, Western Australia), both supporting kwongan vegetation (sclerophyllous scrub and woodland communities), was subjected to classification to define PFTs. Species of both study sites were replaced with the newly derived PFTs and projected cover abundance-weighted means calculated for every plot. Functional communities were defined by classifications of the abundance-weighted PFT data in the respective sites. Distance-based redundancy analysis (using the abundance-weighted community and environmental data) was used to infer drivers of the functional community patterns for each site. A classification based on trait data assisted in reducing trait-space complexity in the studied vegetation and revealed 26 PFTs shared across the study sites. In total, seven functional communities were identified. We demonstrate a putative functional-community pattern-driving effect of soil-texture (clay—sand) gradients at Eneabba (42% of the total inertia explained) and that of water repellence at Cooljarloo (36%). Synthesis. This paper presents a procedure formalising the classification of multiple response traits leading to the delineation of PFTs and functional communities. This step captures plant responses to stresses and disturbance characteristic of kwongan vegetation, including low nutrient status, water stress, and fire (a landscape-level disturbance factor). Our study is the first to introduce a formal procedure assisting their formal recognition. Our results support the role of short-term abiotic drivers structuring the formation of fine-scale functional community patterns in a complex, species-rich vegetation of Western Australia.

Assignment or exclusion of an individual to specific populations or cultivars based on molecular genetic markers provides an attractive approach for varietal identification at the individual level in cross-pollinated plant species. The objectives of this study were (i) to explore the molecular diversity and relationships between Australasian perennial ryegrass (Lolium perenne L.) populations; (ii) to investigate accuracy of assignment of individuals to different types of populations including ecotypic, nonrestricted- and restricted-based cultivars; and (iii) to determine the effect of variable number of SSR loci and different statistical analysis methods on assignment accuracy. Eight forage perennial ryegrass populations comprising 48 individual plants per population were genotyped with 29 simple sequence repeat (SSR) marker loci. The number of alleles per locus ranged from 3.72 to 6.76. The mean observed heterozygosity varied from 0.419 to 0.538. Various genetic distance estimates and clustering methods obtained results consistent with breeding history. Genetic variation among (8.7%) and within populations (91.3%) was significant. Accuracy of individual assignment differed by population type, and it was higher (>90%) for restricted-based cultivars than for ecotypic and nonrestricted-based populations. These results indicate that SSR marker profiles can be effectively used to assign individuals for outbreeding populations such as perennial ryegrass. The approach used in this study may be useful for ryegrass germplasm management issues such as cultivar identification at the individual level.

To test the hypothesis that resistance in Phytophthora cinnamomi to control by the fungicide phosphite (phosphonate) would arise in sites with prolonged use of phosphite, 30 P. cinnamomi isolates were collected from a range of sites with different phosphite-use histories, including phosphite-treated and untreated avocado orchards, and phosphite-treated and untreated native vegetation sites. The colonizing ability of these isolates was tested by different inoculation methods against a range of host tissues, treated and untreated with phosphite, including mycelial stem inoculation on clonally propagated Leucadendron sp., mycelial root inoculation of lupin seedlings and zoospore inoculation of Eucalyptus sieberi cotyledons. Isolates from avocado orchards with a long history of phosphite use were, on average, more extensive colonizers of the phosphite-treated Leucadendron sp., lupin seedling roots and Eucalyptus sieberi cotyledons. These isolates did not colonize untreated plant tissue (Leucadendron sp.) more extensively than isolates from sites with no history of phosphite use and no isolates were resistant to control by phosphite. Analysis of all isolates with microsatellite markers revealed the majority were from a single clonal lineage. Selection for decreased sensitivity to phosphite in planta has taken place within asexual clonal lineages of P. cinnamomi in sites with prolonged use of phosphite.

The symbiotic association between perennial ryegrass (Lolium perenne L.) and the fungal endophyte Neotyphodium lolii is associated with host-specific adaptations, particularly in response to abiotic and biotic stresses. Knowledge of the origin of the symbiosis and the contribution of endophyte genotype to host phenotypic variation is currently limited. Simple sequence repeat (SSR) markers were used to assess endophyte genetic diversity in a globally distributed collection of perennial ryegrass accessions. Consistent in planta detection was achieved with 18 of 22 SSR markers (primer pairs). Endophytes representing as many as four different taxa were detected in 42 accessions from 20 different countries, N. lolii being predominant. A total of 33 unique N. lolii genotypes were discriminated, of which 29 clustered into three major groups with limited within-group variation. The three major N. lolii groups were associated with distinct perennial ryegrass chloroplast haplotypes. The alkaloid profiles of accessions were apparently associated with the presence of specific N. lolii genotypes. Genotypic analysis provides a powerful method for genetic dissection of the grass-endophyte interaction and prediction of phenotypic variation based on genotypic variation.

Development of accurate high-throughput molecular marker systems such as SNPs permits evaluation and selection of favourable gene variants to accelerate elite varietal production. SNP discovery in perennial ryegrass has been based on PCR amplification and sequencing of multiple amplicons designed to scan all components of the transcriptional unit. Full-length genes (with complete intron-exon structure and promoter information) corresponding to well-defined biochemical functions such as lignin biosynthesis and oligosaccharide metabolism are ideal for complete SNP haplotype determination. Multiple SNPs at regular intervals across the transcriptional unit were detected within and between the heterozygous parents and validated in the progeny of the F (1)(NA(6) x AU(6)) genetic mapping family. Haplotype structures in the parental genotypes were defined and haplotypic abundance, structure and variation were assessed in diverse germplasm sources. Decay of LD to r (2) values of c. 0.2 typically occurs over 500-3,000 bp, comparable with gene length and with little apparent variation between diverse, ecotypic and varietal population sub-groups. Similar patterns were revealed as limited blocks of intragenic LD. The results are compatible with the reproductive biology of perennial ryegrass and the effects of large ancestral population size. This analysis provides crucial information to validate strategies for correlation of haplotypic diversity and phenotypic variation through association mapping.

Microsatellites were evaluated as genetic markers for the mitochondrial genome (mtDNA) of Phytophthora cinnamomi for population studies. Two (A)n microsatellite loci were cloned from the mtDNA of P. cinnamomi. Amplification products from these loci showed little polymorphism among Phytophthora isolates due to their location in coding regions of mtDNA. A further three (A)n microsatellite loci obtained from the complete mtDNA sequence of P. infestans were also not highly polymorphic, although located in non-coding mtDNA. The presence of the (A)n microsatellites was not conserved in the genus Phytophthora. Unlike those of the chloroplast genome of plants, (A)n microsatellite loci of mtDNA do not have potential as highly polymorphic markers in Phytophthora.

Crown rust fungus, Puccinia coronata f.sp. lolii is an obligate biotrophic pathogen of ryegrasses which causes significant reductions of herbage yield, palatability and digestibility. Genetic diversity in virulence has been reported in all the major temperate regions of the world and is therefore a major problem for pasture and turf breeders developing varieties with durable resistance for crown rust. Knowledge of the genetic variation present both within and between Australasian crown rust populations is essential for the efficient production of resistant varieties. A total of 11 efficient simple sequence repeat (SSR) markers developed from a urediniospore-derived expressed sequence tag (EST) resource have been used for Australasian intraspecific genetic diversity analysis. Seventy-two single pustule samples comprising three main populations from both North and South Islands of New Zealand and from south-eastern Australia were genotyped. The analysis identified 59 distinct genotypes, high levels of genetic diversity being detected both within and between populations. All methods of analysis detected no significant difference between isolates from the North and South Islands of New Zealand (p > 0.05), and high intrapopulation diversity between Victorian isolates. However high population differentiation (p < 0.001) was detected between Victorian isolates and those from the South Island (PhiPT [estimate of genetic variability = 0.101) and especially the North Islands (PhiPT = 0.162) of New Zealand. Genetic dissection of crown rust population structure within Australasia will inform the magnitude of gene pyramiding required for the development of varieties with durable resistance.

Development of accurate high-throughput molecular marker systems such as SNPs permits evaluation and selection of favourable gene variants to accelerate elite varietal production. SNP discovery in perennial ryegrass has been based on PCR amplification and sequencing of multiple amplicons designed to scan all components of the transcriptional unit.

The genetic structure of populations of Phytophthora cinnamomi, a pathogen of an enormous variety of woody plants, was investigated using microsatellites. Three intensively sampled disease sites in southwest Australia were analyzed along with a large culture collection of Austra-lian isolates and some isolates from elsewhere in the world. The mutation in the four microsatellite loci analyzed revealed spatial patterns at the disease sites that correlated with the age of the infestation. Only three clonal lineages were identified in Australian populations and these same clonal lineages were present in worldwide populations, where it is suggested that a limited number of clonal lineages have spread in most regions. No evidence for sexual reproduction between these clonal lineages in Australia has been found even though the pathogen has the opportunity. Instead, mitotic recombination is frequent within the clonal lineages. The implications of this are discussed.

The key components for implementation of functionally associated genetic markers in perennial ryegrass and white clover breeding have been established. They include: generation of substantial genomic sequence resources; methods for functional analysis and verification of candidate gene status, including transcriptomics and transgenesis; efficient methods for in silico and in vitro discovery and validation of gene-associated SNP loci; evaluation of intra- and inter-population diversity; estimation of SNP haplotype complexity and LD; development of robust protocols for phenotypic analysis of key agronomic traits; design and implementation of experiments for haplotype-phenotype correlation; and development of efficient strategies for gene-based marker deployment in existing germplasm improvement programmes. These processes are mature for perennial ryegrass, and despite the added complexities of genetic architecture in white clover, optimized methods for SNP discovery should be equally effective for the latter species. The strategies are also suitable for other agronomically important temperate forage species, such as the grasses Italian ryegrass, tall fescue (Festuca arundinacea), meadow fescue (Festuca pratensis), cocksfoot (Dactylis glomerata) and timothy (Phleum pratense), as well as the legumes red clover (Trifolium pratense) and lucerne (Medicago sativa).

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.

White clover (Trifolium repens L.) is an important temperate pasture legume that plays a key role as a companion to grass species, such as perennial ryegrass (Lolium perenne L.). Due to the outbreeding nature of white clover, cultivars are highly heterogeneous. Genetic diversity was assessed using 16 elite cultivars from Europe, North and South America, Australia, and New Zealand. Fifteen simple sequence repeat markers that detect single, codominant polymorphic genetic loci were selected for the study. The genetic relationships among individuals were compared using phenetic clustering, and those among cultivars were compared using nonmetric multidimensional scaling. Intrapopula tion variability exceeded interpopulation variability, with substantial overlap among populations and weak interpopula tion differentiation. No obvious or significant differentiation was observed on the basis of morphology or geographic origin of the cultivars. The number of parental genotypes used to derive each cultivar was not a major determinant of genome-wide genetic diversity. The outcomes of this assessment of genetic variation in elite white clover germplasm pools have important implications for the feasibility of molecular marker-based cultivar discrimination, and will be used to assist the design of linkage disequilibrium mapping strategies for marker-trait association.Key words: white clover, allotetraploid, genetic diversity, polymorphism, simple sequence repeat, cluster analysis, nonmetric multidimensional scaling.

The causative organism of crown rust in ryegrasses (Puccinia coronata f.sp. lolii) is an obligate biotroph that causes significant economic losses within the temperate grazing industries of dairy, meat, and wool production. This study reports on the development, transferability, and utility of gene-associated simple sequence repeat (SSR) molecular markers for crown rust. Analysis of 1100 expressed sequence tag (EST) sequences from a urediniospore-derived cDNA library detected 55 SSR loci. The majority of EST-SSR arrays contained perfect trinucleotide repeats with consistently low repeat numbers, and the motifs (ACC)n and (CAT)n were most commonly represented. DNA extraction from single pustules, in conjunction with multiple displacement amplification, provided the basis for PCR-based screening to evalu- ate genetic marker performance. An example of the identification of intraspecific genetic diversity was obtained from the analysis of 16 P. coronata isolates originating from the United Kingdom, Australia, New Zealand, and Japan. A subset of 12 robust EST-SSR markers was informative for determination of pathogen diversity within and between these localities. It was also demonstrated that crown rust EST-SSR markers were capable of cross-amplification in closely related fungal taxa (Puccinia spp.) and filamentous fungi within the Ascomycota. Resume : L'agent causal de la rouille couronnee chez les ray-grass (P. coronata f. sp. lolii) est un biotrophe obliga- toire qui occasionne des pertes economiques importantes dans les zones temperees de production fourragere pour les fins de production de lait, de viande et de laine. Cette etude rapporte le developpement, la transportabilite et l'utilite de marqueurs microsatellites (SSR) associes a des genes chez la rouille couronnee. L'analyse de 1 100 etiquettes de sequences exprimees (EST) issus d'une banque d'ADNc provenant d'uredospores a decele 55 SSR. La plupart de ces EST-SSR contenaient des repetitions trinucleotidiques parfaites dont le nombre de repetitions etait constamment faible et chez lesquelles les motifs (ACC)n et (CAT)n etaient les plus communs. L'extraction d'ADN de pustules individuels, en conjonction avec une amplification a deplacement multiple (MDA), a rendu possible un crible PCR pour evaluer la performance des marqueurs genetiques. Un exemple de detection de diversite genetique intraspecifique a ete obtenu en analysant 16 isolats du P. coronata provenant du Royaume-Uni, de l'Australie, de la Nouvelle-Zelande et du Japon. Un sous-ensemble de 12 marqueurs EST-SSR robustes s'est avere utilisable chez des taxons fongiques proches (Puccinia spp.) ainsi que chez des champignons filamenteux appartenant aux ascomycetes. Mots cles : Puccinia coronata, microsatellite, etiquette de sequence exprimee, uredospore, diversite genetique, pathogene.

Asexual fungal endophytes of the genus Epichloë form mutually beneficial associations with cool-season pasture grasses such as ryegrasses (Lolium spp.). Alkaloid production by the fungus confers both beneficial (deterrence of invertebrate herbivory) and detrimental (toxicity to mammalian livestock) attributes. A few novel strains with desirable metabolite profiles have been advanced into commercial production by inoculation of perennial ryegrass cultivars. In the present study, an integrated process for discovery of novel endophytes based on exploitation of genotypic information has been designed and implemented. A survey of genetic diversity was performed on a large-scale, customised germplasm collection (containing 244 accessions) in order to identify previously uncharacterised endophyte genotypes. Preliminary qualitative metabolic profiling in the endogenous genetic background permitted elimination of undesirable combinations, and definition of a subset of priority candidates. A novel method was developed for inoculation of endophytes into meristem-culture-derived callus tissue of single genotypes from multiple perennial ryegrass cultivars, in order to allow isogenic comparisons with respect to both host and endophyte genotype. Beneficial toxin profiles were confirmed for associations formed with the grass genotypic panel, and semi-quantitative metabolite analysis provided evidence for genotype-specific effects of both host and genotype on levels of alkaloid production. Vegetative stability was also assessed over both shorter and longer terms. A final set of three prioritised candidates was obtained, two of which (belonging to the known taxa E. festucae var. lolii and LpTG-2) produce the alkaloids ergovaline and peramine. The third candidate endophyte, belonging to a putative novel taxon, solely produces representatives of an additional alkaloid class, the epoxy-janthitrems.

We report the development of four microsatellite loci into genetic markers for the diploid oomycete plant pathogen Phytophthora cinnamomi and that (AC)(n) and (AG)(n) microsatellites are significantly less frequent than in plant and mammal genomes. A minisatellite motif 14 bp long was also discovered. The four microsatellite loci were used to analyze sexual progeny from four separate crosses of P. cinnamomi. A large proportion of non-Mendelian inheritance was observed across all loci in all four crosses, including inheritance of more than two alleles at a locus and noninheritance of alleles from either parent at a locus. The aberrant inheritance is best explained by nondisjunction at meiosis in both the A1 parent and the A2 trisomic parents, resulting in aneuploid progeny. Two loci on the putative trisomic chromosome showed linkage and no loci were linked to mating type. One aneuploid offspring was shown to have lost alleles at two loci following subculture over 4 years, indicating that aneuploid progeny may not be mitotically stable.

Due to the complex genetic architecture of perennial ryegrass, based on an obligate outbreeding reproductive habit, association-mapping approaches to genetic dissection offer the potential for effective identification of genetic marker–trait linkages. Associations with genes for agronomic characters, such as components of herbage nutritive quality, may then be utilised for accelerated cultivar improvement using advanced molecular breeding practices. The objective of the present study was to evaluate the presence of such associations for a broad range of candidate genes involved in pathways of cell wall biosynthesis and carbohydrate metabolism. An association-mapping panel composed from a broad range of non-domesticated and varietal sources was assembled and assessed for genome-wide sequence polymorphism. Removal of significant population structure obtained a diverse meta-population (220 genotypes) suitable for association studies. The meta-population was established with replication as a spaced-plant field trial. All plants were genotyped with a cohort of candidate gene-derived single nucleotide polymorphism (SNP) markers. Herbage samples were harvested at both vegetative and reproductive stages and were measured for a range of herbage quality traits using near infrared reflectance spectroscopy. Significant associations were identified for ~50% of the genes, accounting for small but significant components of phenotypic variance. The identities of genes with associated SNPs were largely consistent with detailed knowledge of ryegrass biology, and they are interpreted in terms of known biochemical and physiological processes. Magnitudes of effect of observed marker–trait gene association were small, indicating that future activities should focus on genome-wide association studies in order to identify the majority of causal mutations for complex traits such as forage quality.

The products of RAPD-PCR amplification of Phytophthora cinnamomi DNA were separated by electrophoresis in agarose. Parallel Southern blots of the gels were hybridized with nick translated DNA from different species of Phytophthora. Fragments that hybridized specifically to P. cinnamomi DNA were identified. These fragments were purified and cloned into pUC18. Their specificity for P. cinnamomi was confirmed.

Genetic analysis of host resistance to the crown rust pathogen of ryegrasses has traditionally involved the use of composite urediniospore collections, which may contain multiple genotypes and virulence races. Consequently, discrimination between major gene responses to alternative races and quantitative resistance has proved challenging for disease trait-dissection studies.Amethod of propagation on detached leaves has been used to derive genetically homogenised crown rust pathogen lines from bulked spore collections obtained from five distinct Australian locations. Spores from individual pustules were repeatedly reinoculated onto fresh leaves. Amplicon complexity was assessed at the conclusion of each cycle using crown rust pathogen expressed sequence tag (EST)-derived simple sequence repeat (SSR) primer pairs. The mean number of amplification products per isolate declined over successive rounds of reinfection. The number of rounds of sequential infection required for decay to stable levels was dependent on the diversity present within the bulked spore collection. Large-scale propagation of the putative homogenised populations developed in the present study may provide inoculum for infection studies to allow quantitative trait loci mapping of specific gene-for-gene responses. The methodology has significant applications for the pyramiding of resistance genes specific to diverse crown rust pathogen genotypes during cultivar development and for pathotyping of existing elite germplasm. This approach is also applicable to other Puccinia species.

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.

Alkaloids produced by the perennial ryegrass pasture and turf grass endophyte Neotyphodium lolii confer both beneficial (insect feeding deterrence) and deleterious (mammalian herbivore toxicoses) effects. Novel endophyte strains with altered and desirable in planta metabolic profiles have been introduced into cultivars by inoculation. The potentially severe effects of contamination with standard toxic endophytes provide an important incentive for quality control during varietal development. Genotyping with expressed sequence tag (EST)-derived simple sequence repeat (SSR) markers in order to monitor endophyte content was evaluated in this study. The NEA2 endophyte, described as producing low levels of lolitrem B and moderate quantities of ergovaline and peramine, has been deployed in the cultivar (cv.) Tolosa and transferred to other proprietary varieties by crossing or controlled inoculation. In planta genotypic analysis of cv. Tolosa-derived plants revealed the presence of 2 distinct NEA2 genotypes (A and B). Variable proportions of NEA2 A and B were observed at different stages of cultivar multiplication, and NEA2 B was present in inoculated varieties. Several accessions also revealed the presence of a third genotype (C), identical to standard toxic types. Alkaloid measurement in plants containing individual A and B endophytes identified distinct profiles which collectively account for the average NEA2 profile. The C variant is apparently a contaminant arising from seed or adventitious seedlings during varietal multiplication or incomplete removal of endophyte from seed before inoculation. SSR-based genotyping provides an efficient means to continuously assess endophyte prevalence and identity in pasture grass breeding programs.