Brent Barrett

Achievements and Challenges in Improving Temperate Perennial Forage Legumes

The expected move towards more sustainable crop-livestock systems implies wider cultivation of perennial forage legumes. Alfalfa (Medicago sativa subsp. sativa) is the main perennial legume in most temperate regions, especially where farm systems rely largely on forage conservation. White clover (Trifolium repens) and red clover (Trifolium pratense) are dominant in specific regions and farm systems. Although breeding progress for disease and insect resistance has been achieved, these crops have shown lower rates of genetic gain for yield than major grain crops, owing to lower breeding investment, longer selection cycles, impossibility to capitalize on harvest index, outbreeding mating systems associated with severe inbreeding depression, and high interaction of genotypes with cropping conditions and crop utilizations. Increasing yield, persistence, adaptation to stressful conditions (drought; salinity; grazing) and compatibility with companion grasses are major breeding targets. We expect genetic gain for yield and other complex traits to accelerate due to progress in genetic resource utilization, genomics resource development, integration of marker-assisted selection with breeding strategies, and trait engineering. The richness in adaptive genes of landraces and natural populations can be fully exploited through an ecological understanding of plant adaptive responses and improved breeding strategies. Useful genetic variation from secondary and tertiary gene pools of Medicago and Trifolium is being increasingly accessed. Genome sequencing projects in alfalfa and white clover will enrich physical, linkage and trait maps. Genome sequences will underpin fine mapping of useful loci and subsequent allele mining, leveraging the synteny of these crops with M. truncatula. Low-cost genome-wide markers generated through genotyping-by-sequencing will make genomic selection for adaptation and forage yield possible for these crops. Genetic markers will also be used for dissecting quantitative traits and developing toolboxes of functional markers for stress tolerance and other traits. Under current regulatory policies, transgenic approaches are likely to be limited to a few breakthrough traits. The key challenge for future applications of genomics technologies is their seamless integration with breeding system logistics and breeding schemes.

Multivariate associations of flavonoid and biomass accumulation in white clover (Trifolium repens) under drought

White clover (Trifolium repens L.) is an important pasture legume in temperate regions, but growth is often strongly reduced under summer drought. Cloned individuals from a full-sib progeny of a pair cross between two phenotypically distinct white clover populations were exposed to water deficit in pots under outdoor conditions for 9 weeks, while control pots were maintained at field capacity. Water deficit decreased leaf water potential by more than 50% overall, but increased the levels of the flavonol glycosides of quercetin (Q) and the ratio of quercetin and kaempferol glycosides (QKR) by 111% and by 90%, respectively. Water deficit reduced dry matter (DM) by 21%, with the most productive genotypes in the controls showing the greatest proportional reduction. The full-sib progeny displayed a significant increase in the root:shoot ratio by 53% under water deficit. Drought-induced changes in plant morphology were associated with changes in Q, but not kaempferol (K) glycosides. The genotypes with high QKR levels reduced their DM production least under water deficit and increased their Q glycoside levels and QKR most. These data show, at the individual genotype level, that increased Q glycoside accumulation in response to water deficit stress can be positively associated with retaining higher levels of DM production.

An integrated genetic linkage map for white clover (Trifolium repens L.) with alignment to Medicago

BackgroundWhite clover (Trifolium repens L.) is a temperate forage legume with an allotetraploid genome (2n=4×=32) estimated at 1093 Mb. Several linkage maps of various sizes, marker sources and completeness are available, however, no integrated map and marker set has explored consistency of linkage analysis among unrelated mapping populations. Such integrative analysis requires tools for homoeologue matching among populations. Development of these tools provides for a consistent framework map of the white clover genome, and facilitates in silico alignment with the model forage legume, Medicago truncatula.ResultsThis is the first report of integration of independent linkage maps in white clover, and adds to the literature on methyl filtered GeneThresher®-derived microsatellite (simple sequence repeat; SSR) markers for linkage mapping. Gene-targeted SSR markers were discovered in a GeneThresher® (TrGT) methyl-filtered database of 364,539 sequences, which yielded 15,647 SSR arrays. Primers were designed for 4,038 arrays and of these, 465 TrGT-SSR markers were used for parental consensus genetic linkage analysis in an F1 mapping population (MP2). This was merged with an EST-SSR consensus genetic map of an independent population (MP1), using markers to match homoeologues and develop a multi-population integrated map of the white clover genome. This integrated map (IM) includes 1109 loci based on 804 SSRs over 1274 cM, covering 97% of the genome at a moderate density of one locus per 1.2 cM. Eighteen candidate genes and one morphological marker were also placed on the IM. Despite being derived from disparate populations and marker sources, the component maps and the derived IM had consistent representations of the white clover genome for marker order and genetic length. In silico analysis at an E-value threshold of 1e-20 revealed substantial co-linearity with the Medicago truncatula genome, and indicates a translocation between T. repens groups 2 and 6 relative to M. truncatula.ConclusionsThis integrated genetic linkage analysis provides a consistent and comprehensive linkage analysis of the white clover genome, with alignment to a model forage legume. Associated marker locus information, particularly the homoeologue-specific markers, offers a new resource for forage legume research to enable genetic analysis and improvement of this forage and grassland species.

White Clover Seed Yield: A Case Study in Marker-Assisted Selection

Genetic gain from phenotypic selection in open-pollinated forage species is constrained by the inability to accurately use phenotype to estimate genotype, prior to parent selection for polycrossing. The use of marker-assisted selection (MAS) offers the potential to accelerate genetic gain by partially overcoming this constraint. White clover (Trifolium repens L., 2n = 4x = 32) is an open-pollinated, high-quality, perennial forage legume with complex inheritance of traits underpinning pasture persistence, seed production, animal productivity, and animal health. Our legume improvement programme has utilised seed production in white clover as a case study in the application of MAS in outbred forage species, using microsatellite markers linked to quantitative trait loci (QTL) of moderate resolution. The QTL SY03-D2 on the distal end of group D2, was used to explore marker:trait associations in 12 breeding pools, leading to opportunities to conduct reselection experiments, and to monitor response to genotypic selection criteria in experimental polycrosses. Each breeding pool was sampled with 90 or more individuals grown out in an unreplicated field trial to assess seed yield traits, as per standard practice in our cultivar development programme. DNA samples were tested with up to three microsatellite markers associated with the QTL. Significant (p < 0.01) marker:trait associations were observed in 8 of the 12 breeding pools, with the most informative polymorphisms accounting for differences of 30–69% in the mean seed yield values within breeding pools. These data suggest that value can be realised from the current investment in genomics for MAS in white clover, given QTL of moderate resolution, and widely used marker platforms such as microsatellites.

Effect of grass species and fungal endophyte on soil nitrification potential

This experiment tested the impact of grass species and fungal endophyte status and strain on soil nitrification. Three C3 grass–endophyte combinations were tested: Festuca arundinacea–Neotyphodium coenophialum; F. pratensis–N. uncinatum; Lolium perenne–N. lolii, and included different strains of endophyte and endophyte-free grasses. Three C4 species— Brachiaria decumbens, Paspalum dilatatum and Pennisetum clandestinum—of unknown Acremonium endophyte status, were also tested. Plants were grown for 6 weeks without fertiliser in pots in a field soil (Mollic Psammaquent), then rhizosphere soil was sampled and incubated at 27 °C with and without (NH4)2SO4. The –N production was measured weekly. The presence of plants significantly increased the nitrification rate compared with bare soil. There were significant differences (P=0.02) among plant species. In all cases, endophyte presence increased nitrification in soil samples (P<0.001) relative to endophyte-free within a species.

Genetic mapping of a root-knot nematode resistance locus in Trifolium

Parasitic nematodes damage white clover (Trifolium repens) roots, negatively impacting forage yield and persistence. No single gene resistance to nematodes has been identified in white clover. Trifolium semipilosum (2n = 2x = 16) genotypes exhibiting either complete resistance or susceptibility to infection by the clover root-knot nematode (CRKN), Meloidogyne trifoliophila, were identified. F1 progeny (n = 92) of a pair-cross between ‘TsR’, a plant heterozygous for the resistance phenotype and ‘TsS’, a plant homozygous for the susceptible phenotype, were challenged with infective CRKN juveniles and evaluated subsequently for root galling. Segregation analysis indicated the resistance phenotype may be conferred by a single dominant allele at a locus (designated TRKR, Trifolium Root-knot Resistance) subject to segregation distortion. TsR, TsS, and bulked resistant and bulked susceptible F1 progeny (n = 12/bulk) were screened using T. repens microsatellite (SSR) markers. Three SSRs revealed polymorphism in TsR and the resistant bulk, of which prs090 and prs247 map to loci on T. repens linkage group D2. Progeny were genotyped with these three SSRs and 23 additional SSRs from T. repens groups D1 and D2. Linkage analysis in both TsR and TsS demonstrated macro-synteny between T. repens group D homoeologues and the T. semipilosum linkage group (designated DTs) containing the TRKR locus. Significant segregation distortion was detected in TsR, and recombination in the central region of the T. semipilosum linkage group was suppressed relative to T. repens in both parents. These data demonstrate the opportunities and challenges for comparative mapping in Trifolium and characterisation of loci conferring resistance to plant-parasitic nematodes.

Development of Genomic Selection for Perennial Ryegrass

Mixed-species pasture based on perennial ryegrass (Lolium perenne) and white clover (Trifolium repens) is the foundation for profitable production from temperate grasslands. In theory, genomic selection (GS) offers an opportunity to lift the rate of genetic gain in these species. Critical research questions include to what extent theoretical expectations for GS can be realized in practice, and understanding the genetic and economic implications of GS in breeding programs and on farm. We describe a limited experiment to derive and cross-validate genomic estimated breeding values (GEBVs) from 211 perennial ryegrass plants evaluated for plant herbage dry weight (DW) and days-to-heading (DTH), using field phenotypic data and up to 10,885 markers typed via genotyping-by-sequencing (GBS). Using Ridge Regression-BLUP and Random Forest regression, cross validation prediction accuracies ranged from r = 0.16–0.34 (DW) and r = 0.52–0.56 (DTH). Accuracy was not influenced by marker density, but there was an interaction between statistical model and trait. The data indicate that, in these elite breeding populations, low marker densities in a limited training population dataset may be viable for generation of GEBVs in perennial ryegrass. Variance attributable to population structure, rather than linkage disequilibrium, is likely the primary basis of GEBV accuracy in this study. Generation of a training set of increased size, scope and greater relevance for key economic traits is outlined in the context of developing a GS capability with an Australasian focus.

Using non-targeted direct analysis in real time-mass spectrometry (DART-MS) to discriminate seeds based on endogenous or exogenous chemicals.

Forage seeds are a highly traded agricultural commodity, and therefore, quality control and assurance is high priority. In this study, we have used direct analysis in real time-mass spectrometry (DART-MS) as a tool to discriminate forage seeds based on their non-targeted chemical profiles. In the first experiment, two lots of perennial ryegrass (Lolium perenne L.) seed were discriminated based on exogenous residues of N-(3, 4-dichlorophenyl)-N,N-dimethylurea (DiuronTM), a herbicide. In a separate experiment, washed and unwashed seeds of the forage legumes white clover (Trifolium repens L.) and alfalfa (Medicago sativa L.) were discriminated based on the presence or absence of oxylipins, a class of endogenous antimicrobial compounds. Unwashed seeds confer toxicity towards symbiotic, nitrogen-fixing rhizobia which are routinely coated on legume seeds before planting, resulting in reduced rhizobial count. This is the first report of automatic introduction of intact seeds in the DART ion source and detecting oxylipins using DART-MS. Apart from providing scope to investigate legume-rhizobia symbiosis further in the context of oxylipins, the results presented here will enable future studies aimed at classification of seeds based on chemicals bound to the seed coat, thereby offering an efficient screening device for industry.

Untargeted Metabotyping Lolium perenne Reveals Population-Level Variation in Plant Flavonoids and Alkaloids

Metabolomics provides a powerful platform to characterize plants at the biochemical level, allowing a search for underlying genes and associations with higher level complex traits such as yield and nutritional value. Efficient and reliable methods to characterize metabolic variation in economically important species are considered of high value to the evaluation and prioritization of germplasm and breeding lines. In this investigation, a large-scale metabolomic survey was performed on a collection of diverse perennial ryegrass (Lolium perenne L.) plants. A total of 2,708 data files, derived from liquid chromatography coupled to high resolution mass spectrometry (LCMS), were selected to assess the effectiveness and efficiency of applying high throughput metabolomics to survey chemical diversity in plant populations. The data set was generated from 23 ryegrass populations, with 3–25 genotypes per population, and five clonal replicates per genotype. We demonstrate an integrated approach to rapidly mine and analyze metabolic variation from this large, multi-batch LCMS data set. After performing quality control, statistical data mining and peak annotation, a wide range of variation for flavonoid glycosides and plant alkaloids was discovered among the populations. Structural variation of flavonoids occurs both in aglycone structures and acetylated/malonylated/feruloylated sugar moieties. The discovery of comprehensive metabolic variation among the plant populations offers opportunities to probe into the genetic basis of the variation, and provides a valuable resource to gain insight into biochemical functions and to relate metabolic variation with higher level traits in the species.

QuLinePlus: extending plant breeding strategy and genetic model simulation to cross-pollinated populations—case studies in forage breeding

Plant breeders are supported by a range of tools that assist them to make decisions about the conduct or design of plant breeding programs. Simulations are a strategic tool that enables the breeder to integrate the multiple components of a breeding program into a number of proposed scenarios that are compared by a range of statistics measuring the efficiency of the proposed systems. A simulation study for the trait growth score compared two major strategies for breeding forage species, among half-sib family selection and among and within half-sib family selection. These scenarios highlighted new features of the QuLine program, now called QuLinePlus, incorporated to enable the software platform to be used to simulate breeding programs for cross-pollinated species. Each strategy was compared across three levels of half-sib family mean heritability (0.1, 0.5, and 0.9), across three sizes of the initial parental population (10, 50, and 100), and across three genetic effects models (fully additive model, a mixture of additive, partial and over dominance model, and a mixture of partial dominance and over dominance model). Among and within half-sib selection performed better than among half-sib selection for all scenarios. The new tools introduced into QuLinePlus should serve to accurately compare among methods and provide direction on how to achieve specific goals in the improvement of plant breeding programs for cross breeding species.