Metabolomics of forage plants: A review

REVIEW: PART OF A HIGHLIGHT ON BREEDING STRATEGIESFOR FORAGE AND GRASS IMPROVEMENT

Metabolomics of forage plants: a review

Susanne Rasmussen1,*, Anthony J. Parsons2 and Christopher S. Jones1

1AgResearch Limited, Grasslands Research Centre, Tennent Drive, Palmerston North 4442, New Zealand and2Massey University, Institute of Natural Resources, Palmerston North 4442, New Zealand

* For correspondence. E-mail [email protected]

Received: 1 December 2011 Returned for revision: 22 December 2011 Accepted: 12 January 2012 Published electronically: 19 February 2012

† Background Forage plant breeding is under increasing pressure to deliver new cultivars with improved yield,quality and persistence to the pastoral industry. New innovations in DNA sequencing technologies mean thatquantitative trait loci analysis and marker-assisted selection approaches are becoming faster and cheaper, andare increasingly used in the breeding process with the aim to speed it up and improve its precision. High-through-put phenotyping is currently a major bottle neck and emerging technologies such as metabolomics are beingdeveloped to bridge the gap between genotype and phenotype; metabolomics studies on forages are reviewedin this article.† Scope Major challenges for pasture production arise from the reduced availability of resources, mainly water,nitrogen and phosphorus, and metabolomics studies on metabolic responses to these abiotic stresses in Loliumperenne and Lotus species will be discussed here. Many forage plants can be associated with symbiotic micro-organisms such as legumes with nitrogen fixing rhizobia, grasses and legumes with phosphorus-solubilizingarbuscular mycorrhizal fungi, and cool temperate grasses with fungal anti-herbivorous alkaloid-producingNeotyphodium endophytes and metabolomics studies have shown that these associations can significantlyaffect the metabolic composition of forage plants. The combination of genetics and metabolomics, alsoknown as genetical metabolomics can be a powerful tool to identify genetic regions related to specific metabo-lites or metabolic profiles, but this approach has not been widely adopted for forages yet, and we argue here thatmore studies are needed to improve our chances of success in forage breeding.† Conclusions Metabolomics combined with other ‘-omics’ technologies and genome sequencing can be invalu-able tools for large-scale geno- and phenotyping of breeding populations, although the implementation of theseapproaches in forage breeding programmes still lags behind. The majority of studies using metabolomicsapproaches have been performed with model species or cereals and findings from these studies are not easilytranslated to forage species. To be most effective these approaches should be accompanied by whole-plant physi-ology and proof of concept (modelling) studies. Wider considerations of possible consequences of novel traits onthe fitness of new cultivars and symbiotic associations need also to be taken into account.

Key words: Metabolomics, forage plants, Lolium perenne, drought stress, nutrient stress, Neotyphodium spp.endophytes, Medicago sativa, Lotus spp., arbuscular mycorrhizal fungi, rhizobia, metabolic profiling,genetical metabolomics.

INTRODUCTION

Major forage plants of grazed pastures are the temperate grassesLolium perenne (perennial ryegrass) and L. arundinaceum (tallfescue), and the legumes Trifolium repens (white clover) andMedicago sativa (lucerne, alfalfa). To increase the success ofpasture-based animal production systems, forage breeding hasfocused on traits such as increased pasture production, toleranceand persistence under biotic and abiotic stress, and on improvedforage quality (Humphreys et al., 2006; Parsons et al., 2011a).Reduced opportunities to increase forage production solelythrough on-farm management such as fertilization or defoliationand feed allocation (Clark et al., 2007), as well as pressures toreduce negative environmental impacts (Abberton et al., 2008)require the development of new cultivars with superior agro-nomic traits as rapidly as possible.

Traditional plant breeding is based on phenotypic selectionand subsequent progeny testing commonly followed by

re-selection, which can be a very slow process and requiresoften time-consuming and costly phenotyping. To speed upthe process and to make it more precise quantitative trait loci(QTL) analysis to identify genetic markers which are usedfor marker-assisted selection (MAS) is being developed as anew tool for forage breeding (Zhang et al., 2006; Mouradov,2010), but so far these genotypic markers have been mainlycorrelated to readily observable phenotypes, e.g. seed yield.Many desired traits are directly linked to specific metabolites,e.g. high sugar grasses to fructans (Turner et al., 2006), orinsect resistance to certain secondary metabolites (Clay andSchardl, 2002); targeted analysis of these metabolite classescan be sufficient for selection and QTL analysis, althoughthese methods are usually slow and not amenable for screeningof large populations. However, the link to a desired phenotypecan also be more complex, e.g. in the case of plant growth ordrought tolerance where a complex profile of metabolitesrepresents a chemotype related to the desired characteristics

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Annals of Botany 110: 1281–1290, 2012

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(Tuberosa and Salvi, 2006; Meyer et al., 2007). To unravelthese profiles and to screen large numbers of plant genotypesand populations, metabolomics approaches have been deve-loped to analyse a wide range of metabolite classes simul-taneously and in a high-throughput and untargeted manner(Sumner et al., 2003; Hall, 2006; Fernie and Schauer, 2008;Langridge and Fleury, 2011). Other ‘-omics’ technologiessuch as genomics, transcriptomics or proteomics analyseonly one type of chemical compounds, i.e. DNA, RNA or pro-teins, and require generally only a small number of analyticalplatforms. Metabolomics, on the other hand, is faced with amultitude of chemical structures with physicochemical proper-ties ranging from highly hydrophilic (e.g. sugars) to hydropho-bic (e.g. fatty acids), as well as a large dynamic range frommolar to nanomolar (e.g. some alkaloids) to even lower (e.g.some phytohormones) concentrations. Currently no techno-logy is available which gives a truly ‘holistic’ view of themetabolome, and a combination of several extraction, separ-ation and detection techniques is required to give an overviewof most metabolites present in a sample. The main instrumen-tation used is based on mass spectrometry (MS) coupled to gaschromatography (GC) and/or liquid chromatography (LC), butother technologies such as nuclear magnetic resonance (NMR)or capillary electrophoresis coupled to MS are also used. All ofthese technologies produce very data-rich outputs and requireextensive processing (e.g. noise removal, peak alignment, peakpicking and deconvolution, peak identification) and mining(e.g. multivariate statistics, machine learning, network ana-lysis) techniques to deliver meaningful information whichneeds to be interpreted and utilized in the plant breedingprocess. It is beyond the scope of this review to discussthese techniques in detail and we refer to Hall (2011) andreferences therein for further reading.

Through providing a broad analysis of a plant’s chemicalcomposition, metabolomics approaches can provide a signifi-cant opportunity for plant breeders to assess for traits whichhave previously been considered too difficult or too expensiveto include in breeding programmes. Such traits have requiredthe development of specific targeted analyses or the applica-tion of a significant amount of effort by skilled labour,which would provide a barrier to their routine assessment. Inaddition, as these approaches are implemented more broadlyand integrated with other high-throughput genomic technolo-gies, they will enable plant breeders to assess several ofthese characteristics concurrently. However, setting up the ap-propriate instrumentation and bioinformatics infrastructure stillrequires large financial inputs often beyond the means of smallinstitutes or breeding companies especially in the area offorages. The majority of metabolomics studies so far havetherefore focused on the analysis of model plant species byacademic institutions to develop the technologies, or cerealcrop and vegetable species with larger financial margins forthe breeding industry. For examples of successful implementa-tion of metabolomics, together with other molecular breedingtools in potato, tomato, rice and other fruits and cereals, werefer here to Stewart et al. (2011) and references therein. Incomparison, the use of metabolomics for forage species andits implementation in forage breeding programmes still lagsbehind and we will review here those few studies whichhave analysed the metabolome (or parts of it) in forages.

METABOLOMICS ANALYSIS OF FORAGEPLANT RESPONSES TO ABIOTIC STRESS

Major challenges for pasture production arise from the reducedavailability of three resources, i.e. water, nitrogen (N) andphosphorus (P). Plants have developed an array of adaptationmechanisms to cope with low or fluctuating availability ofthese resources, most of which result in reduced vegetativegrowth. The majority of detailed studies of molecular andmetabolic responses to resource limitation has been performedwith either model (mainly Arabidopsis thaliana) or cereal cropspecies with a major focus for the latter on seed yield.Intensive animal production on pastures, however, requireshigh vegetative plant yield, and much more research on howforage plants respond to low resource supply and how theseresponses might be manipulated is needed.

Metabolic responses to osmotic stress

Extended periods of drought pose a serious challenge toagricultural production systems including pastures. Globalclimate change has been predicted to increase the varianceof climatic parameters, which may lead to unpredictable andmore intense events of drought (Gornall et al., 2010), andmany breeding programmes are directed to develop forageand crop cultivars which survive severe drought better and/orcontinue to be high yielding under moderate drought condi-tions (Wilkins and Humphreys, 2003; Humphreys et al.,2006). Improved survival and/or growth characteristics underdrought can be achieved by plants through a multitude of strat-egies (Orcutt and Nilsen, 2000; Chaves et al., 2003) each in-volving different sets of traits (Ludlow and Muchow, 1990;Richards, 1996, 2006; Collins et al., 2008). Furthermore trade-offs between increased drought adaptation and productivity areto be expected, and these will depend on how well cultivarswith changed strategies cope with a variety of climate scen-arios (Tardieu, 2005; Sambatti and Caylor, 2007). To be suc-cessful in overcoming at least some of these complexproblems requires a much better understanding of plantresponses to drought (and other abiotic stresses) on the mo-lecular level, but only a very few studies have been performedon forages compared with crops (Zhang et al., 2006). Forexample, metabolic and transcript profiling of Loliumperenne exposed to PEG-induced water stress comparedresponses of a susceptible genotype from the cultivar‘Cashel’ to a genotype from an accession classified as‘drought tolerant’ (Foito et al., 2009). The main outcome ofthat study was that a large number of metabolites respondedto water stress with amino acids, fatty acids and phytosterolsgenerally decreasing, while sugars and organic acids increased.Major differences between the two genotypes were related tomuch higher increases in quinic and shikimic acid, phytoster-ols, raffinose and trehalose in the drought-tolerant accession.This general trend of increases in sugars and organic acidsand decreases in amino acids was also found in a comparativemetabolomics study of model and cultivated Lotus speciessubjected to either severe short-term or to moderate long-termdrought (Sanchez et al., 2011b).

Quinic and shikimic acids are precursors for phenylpropa-noids such as flavonols, and studies on Trifolium repens

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subjected to abiotic stresses such as UV irradiation (Hofmannet al., 2001), drought (Hofmann et al., 2003) and cold(Rasmussen et al., 2006; Rasmussen, 2009) showed a strongincrease of flavonols, particularly quercetin conjugates.Cultivars and ecotypes of T. repens with constitutive highlevels of flavonols and anthocyanins had also been shown tobe more UV and drought tolerant (Hofmann et al., 2001,2003), indicating that high levels of phenylpropanoidpathway metabolites might protect plants from abiotic stress(Dixon and Paiva, 1995). However, it has also been shownthat there is no simple correlation between levels of stress-related metabolites and stress tolerance (Ashraf and Foolad,2007; Sanchez et al., 2011), and selection for high-flavonoidclovers has not resulted in more stress-tolerant cultivars sofar. Higher levels of some compatible solutes (e.g. proline,glycine betaine), usually interpreted as an indication ofincreased stress tolerance are in fact observed in some drought-sensitive genotypes of barley and potato (Chen et al., 2007;Vazquez-Robinet et al., 2008; Widodo et al., 2009). Only one-quarter to one-third of metabolite responses were sharedbetween the Lotus model and cultivated species, demonstratingthat findings from studies with model species cannot be simplytranslated to cultivated species (Sanchez et al., 2011b).

Metabolic responses to osmotic stresses are often related tocommon changes in carbon availability, usage and growth(Hummel et al., 2010), but a comparison of metabolicresponses to drought and salt stress in Lotus species showedthat only one-third to one-half of metabolic responses wereconserved, while some metabolites, particularly organicacids, responded in the opposite direction, i.e. were increasedunder drought but decreased under salt stress (Sanchez et al.,2011, 2012). Clearly, more research, particularly on foragecultivars, is needed to identify robust metabolic traits and path-ways conferring drought tolerance to improve chances ofsuccess of current breeding efforts, and this research shouldbe integrated with other -omics data, whole plant physiologyand genetics (Cattivelli et al., 2008; Salekdeh et al., 2009;Roy et al., 2011).

Metabolic responses to nutrients

Plants require large amounts of nitrogen for optimal photo-synthesis and vegetative growth, and green tissues of foragegrasses in highly N-fertilized pastures contain up to 4.5 %total N (Parsons et al., 1991). N is taken up as ammoniumor nitrate from soils, with nitrate being the major form(Crawford and Glass, 1998). Nitrate acts as a signal inducinga range of metabolic enzymes involved in carbon and aminoacid metabolism, while it reduces flavonoid biosynthesis(Lam et al., 1996; Sakakibara et al., 2006; Krouk et al.,2010). A comprehensive study comparing the metabolic com-position of L. perenne plants grown at high-N versus moder-ately low-N supply, resulting in 4 % versus 3 % total Ncontent in blades, showed significant differences in a largenumber of metabolites (Rasmussen et al., 2007, 2008a). Asexpected, strong effects were seen for nitrogenous compoundsof which the majority were much higher at high-N supply.However, major amino acids (e.g. glutamine and aspartate),which represented 85 % of the total free amino acids, weremuch more affected than minor amino acids, which was in

accordance with other studies (Noctor et al., 2002). Nitrate as-similation is strongly linked with photosynthesis and carbonmetabolism (Stitt et al., 2002; Smith and Stitt, 2007) andwas reflected by a shift from carbohydrate to organic acidand lipid biosynthesis (Rasmussen et al., 2008a). This studyalso tested the effects and interactions of resource supplyand infection of Lolium perenne with an endophyticNeotyphodium lolii fungus, which produces alkaloids protect-ing its host from insect herbivory, and one of the major find-ings was that high-N supply resulted in reducedaccumulation of alkaloids produced by this fungus, whichwill be discussed in the section ‘Ryegrass–endophyteassociations’.

Phosphorus is the second most important mineral nutrientessential for plant growth and low-P availability severelylimits crop and pasture growth (Vance et al., 2003). P fertiliza-tion is becoming increasingly expensive as natural resources ofphosphate rock are dwindling (Gilbert, 2009; Vance, 2001).Phosphate deprivation results in a complex re-programmingof metabolism, and plants have evolved four major adaptationstrategies involving changes in root morphology, improved Puptake, increased P recycling and improved P economy(Vance et al., 2003; Morcuende et al., 2007; Muller et al.,2007; Nilsson et al., 2010). A transcriptomic and metabolicprofiling study on early response mechanisms of L. perenneto P starvation revealed an enhanced uptake of sulfur and mo-bilization of glycerol 3-phosphate, which is indicative of a re-modelling of membranes from phosphor lipids (to release P) tosulfolipids (Byrne et al., 2011) as was seen in A. thaliana aswell (Misson et al., 2005). Other effects were a genotype-specific reduction of sugars, amino acids, fatty acids andorganic acids in leaves while sugars and some fatty acidswere increased, indicating effects on photosynthesis(Hammond and White, 2008; Byrne et al., 2011). Improved ef-ficiency of P use can be achieved by activating glycolyticbypasses (Theodorou and Plaxton, 1993) and Byrne et al.(2011) presented evidence that this strategy can be employedby L. perenne. A high level of transcripts coding for cellulosesynthases accompanied with reduced expression of xylanaseswas interpreted by the authors as indicative of remodellingof cell walls; however, it is unclear how P deficiency andcell wall biosynthesis are interconnected (Byrne et al., 2011).

Plants have evolved additional strategies to cope with a lownutrient supply, i.e. legumes can form symbiotic associationswith dinitrogen-fixing rhizobial bacteria, while both grassesand legumes can also form associations with arbuscularmycorrhizal fungi (AMF) to improve P solubilization anduptake. Metabolomics studies of these associations will bereviewed in the following sections.

METABOLOMICS ANALYSIS OF SYMBIOTICFORAGE PLANT ASSOCIATIONS

Like many other plants, forages form a wide variety of associa-tions with endosymbiotic heterotrophic microbes. One of themost important is the association of legumes such asT. repens (white clover) and M. sativa (alfalfa, lucerne) withrhizobia as these provide pastures with additional nitrogenthrough fixation of atmospheric dinitrogen (N2) gas (Grahamand Vance 2000, 2003). Common to both forage grasses and

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legumes are associations with AMF which facilitate the solu-bilization and utilization of immobilized soil phosphorus(Read and Perez-Moreno, 2003; Cappellazzo et al., 2008;Smith and Read, 2008). A symbiotic association specific to cool-temperate grasses such as L. perenne and L. arundinaceum is theinfection with fungal Neotyphodium/Epichloe spp. endophyteswhich provide their host plants with anti-herbivorous alkaloids(Leuchtmann, 1992; Clay and Schardl, 2002; Christensenet al., 2008). In all cases the heterotrophic microorganismsdepend on carbon and energy provided by their autotrophichost plants. How a mutualistic co-operation (both partnersbenefit) between the symbiotic partners is maintained over thecourse of evolution and especially how the partners preventeach other from ‘cheating’ (only one partner benefits) is stilldebated, but control of metabolite/nutrient exchange betweenthe partners seems to play an important role (Kiers andDenison, 2008; Ryan et al., 2008; Draper et al., 2011).Metabolomics approaches have been used to study the effectsof these associations on metabolic composition of the wholesymbiotum or specialized cell structures like arbuscules andnodules, and will be discussed in the following section.

Associations of forage legumes with rhizobia

Mineral soil nitrogen is a major limiting factor for pasture-based animal production requiring the application of nitrogenfertilizers to intensive production systems. Global marketprizes for these fertilizers have steadily increased over thepast decades due to high energy consumption in the productionprocess, and environmental impacts due to nitrate leaching andnitrous oxide emissions from pastures have renewed an interestin biological nitrogen fixation by legumes. Major foragelegumes in pastoral systems are Trifolium and Lotus species,and alfalfa (lucerne) which are either grown in mixed swardswith forage grasses for grazing or as monocultures for hayand silage production. Rhizobial bacteria infect legume rootsand form nodular structures which are able to fix otherwise in-accessible atmospheric N2. The establishment of successfulnodulation and active N-fixation depends on a complex signal-ling pathway which involves metabolite (e.g. isoflavonoids,phytohormones, lectins) -based communication between thetwo partners (Matamoros et al., 2006; Gibson et al., 2008;Oldroyd and Downie, 2008; Ding and Oldroyd, 2009).

Primary metabolism undergoes major changes during thetransition from nodule-free root tissues to functional nodulesand it has been proposed that malate is the major source forcarbon and energy for nodule-inhabiting bacteroids (Vanceet al., 1994; Schulze, 2004). An induction of genes relatedto sucrose degradation, glycolysis, phosphoenolpyruvate carb-oxylation and malate synthesis increasing malate production inthe host plant has been demonstrated by transcriptomic ana-lyses (Hohnjec et al., 1999; Colebatch et al., 2002, 2004;Kouchi et al., 2004; Manthey et al., 2004; Barsch et al.,2006). Only a few studies have used metabolic profiling or meta-bolomics to analyse these metabolic changes in forage plantsor their close relatives, and these have focused on nodules ofMesorhizobium loti-infected L. japonicus (Colebatch et al.,2004; Desbrosses et al., 2005) and Sinorhizobium meliloti-infected M. sativa (Barsch et al., 2006) using mainly GC–MS.A recent study of soybean root hairs using GC–MS and

ultra-performance LC–quadrupole time-of-flight–MS identifieda total of 2610 metabolites of which 166 were significantly regu-lated at very early stages of infection with Bradyrhizobium japo-nicum (Brechenmacher et al., 2010). In support of models basedon transcriptome analyses these studies revealed an increase insome sugars, glycolytic and citric acid cycle pathway intermedi-ates, malate, polyols, polyamines and most amino acids, espe-cially asparagine and glutamine, in nodules. Precursors forphenylpropanoid-derived plant defence and signalling com-pounds such as shikimate and quinate as well as (iso)flavonoidswere also reported. Interestingly, biosynthesis of the branched-chain amino acids leucine, isoleucine and valine is stronglydown-regulated in nodules (Barnett et al., 2004; Capela et al.,2006; Pessi et al., 2007), and it was shown that these aminoacids need to be supplied to the bacteroids by the host plant,indicating a crucial mechanism for regulatory control ofnodule metabolism by the host (Prell et al., 2009).

Overall, these metabolic changes are indicators of stress andit has been suggested that nodules experience two major stressconditions, i.e. hypoxia and phosphorous limitation (Colebatchet al., 2004). Hypoxia could be a consequence of the lowoxygen concentrations in nodules required for nitrogenase ac-tivity (Batut and Boistard, 1994; Fischer, 1996). P deficiency,on the other hand, seems to be caused by bacteroids acting as asignificant P sink (Hernandez et al., 2009), which might be acritical factor for the relatively high P requirements of legumescompared with grasses in pastoral systems.

Associations of forage plants with AMF

Phosphorus is the second major limiting factor for product-ivity in pastoral systems and, due to dwindling reserves and in-creasing costs of natural P fertilizers, solutions are needed toincrease available soil P. Arbuscular mycorrhizal (from theGreek words for ‘fungus’ and ‘root’) fungi (AMF) play a crit-ical role in the acquisition of inorganic phosphorus from insol-uble P sources in soils and transfer to their hosts (Read andPerez-Moreno, 2003; Cappellazzo et al., 2008; Smith andRead, 2008). Like rhizobial bacteria, AMF are also hetero-trophic and completely dependent on carbon and energysupply by the host. Up to 20 % of fixed carbon can be trans-ferred to AMF, contributing considerably to the carbon seques-tration capacity of soils (Bago et al., 2000; Zhu and Miller,2003).

Successful infection and arbuscule formation requires acomplex re-programming of root cells which is strikinglysimilar to that seen in nodule formation (Akiyama andHayashi, 2006; Besserer et al., 2006; Oldroyd et al., 2009;Soto et al., 2010; Draper et al., 2011; Gaude et al., 2012).Metabolomics studies of AMF associations are very rare andmost of the current knowledge of metabolite exchange and me-tabolism is based on detailed studies employing labelled iso-topes and NMR spectroscopy (Bago et al., 2000, 2001;Pfeffer et al., 2001). In the developed symbiosis, carbon istranslocated as hexoses to the arbuscules and intraradicalfungal hyphae and subsequently metabolized to trehalose,glycogen and lipids. Lipids are translocated to the extraradicalhyphae where they are used for fungal growth and mainten-ance. Extraradical hyphae can take up P from the soil inthe form of inorganic phosphate and translocate it as


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polyphosphate to the intraradical hyphae and arbuscules, andeventually to plant cells (Shachar-Hill et al., 1995; Javotet al., 2007). Metabolic profiling of Glomus intraradices-infected M. truncatula (a model legume closely related toM. sativa) roots revealed levels of some amino acids, fattyacids, isoflavonoids and tyrosol in arbuscular relative to unin-fected root tissue (Schliemann et al., 2008). This study alsoidentified the fungal-specific metabolites trehalose,D11-unsaturated fatty acids, sterols and apocarotenoids.Interestingly, trehalose was also identified as a rhizobium-specific metabolite in the above-mentioned study onB. japonicum-infected root hairs in soybean (Brechenmacheret al., 2010).

Ryegrass–endophyte associations

Cool temperate forage grasses such as L. perenne andL. arundinaceum can also be infected by clavicipitaceousfungal endophytes which reside exclusively in the apoplasticspaces of above-ground plant parts and do not form any kindof specialized symbiotic compartments (Leuchtmann, 1992;Clay and Schardl, 2002; Christensen et al., 2008). These endo-phytes produce a variety of alkaloids which have anti-herbivorous activities and protect the host plants fromgrazing mammals, insects and other invertebrates (Bushet al., 1997; Lane et al., 2000; Schardl et al., 2004). Unlikefor rhizobia and mycorrhiza, not much is known about signal-ling processes between endophytes and their hosts, but a rolefor reactive oxygen species and possibly iron for the regulationof fungal growth in planta has been demonstrated (Tanakaet al., 2006, 2008; Koulman et al., 2012). Transcriptomic ana-lyses of host plant responses to endophyte infection have beenhampered by the lack of available genome sequences;however, the genome sequences of several Epichloe strainshave recently been made publicly available (http://www.endophyte.uky.edu/). A study using high-throughput mRNAsequencing showed that disruption of a fungal kinase leadsto dramatic changes in gene expression profiles associatedwith proliferative fungal growth, early plant senescence anddown-regulation of fungal secondary metabolites, indicatinga shift of the nature of the association from mutualistic topathogenic (Eaton et al., 2010).

Neotyphodium/Epichloe spp. endophytes are completely de-pendent on micro- and macronutrient supply by their hostplants, but very little is known about the mechanisms of ex-change of metabolites, and no specific sugar or amino acidtransporters have been functionally characterized so far(Draper et al., 2011). Targeted and untargeted metabolomicsanalyses comparing infected with uninfected plants show asignificant decrease in nitrogenous compounds (e.g. nitrate, as-paragine, proline, proteins) and some fibre components with aconcomitant increase in soluble carbohydrates and organicacids such as malate, quinate, shikimate and phenylpropanoids(Cao et al., 2008; Rasmussen et al., 2008a, 2009a). The effectson sugars, specific organic acids and stress-related metabolitesseems to be a common feature of all three symbiotic associa-tions discussed here, and are in fact common to most bio-trophic, including pathogenic interactions (Draper et al.,2011).

Some of the alkaloids produced by grass endophytes such aslolitrems and ergovaline are toxic to grazing livestock(Gallagher et al., 1984; Lyons et al., 1986; Strickland et al.,1996), and a range of fungal genes and gene clusters respon-sible for alkaloid biosynthesis have been identified (Spieringet al., 2002; Tanaka et al., 2005; Young et al., 2006;Fleetwood et al., 2007). Major efforts are under way to iden-tify novel endophytic strains with beneficial metabolic profiles,and high-throughput analytic methods employing direct infu-sion MS proved to be useful for rapid screening of largenumbers of infected seeds and plants (Koulman et al., 2007)and identified a previously unknown class of cyclic oligopep-tides produced by endophytes (Cao et al., 2008). Moreover, astudy testing the effects of nitrogen supply, high-sugar rye-grass cultivars and strains of endophytes differing in their al-kaloid profile revealed that several additional metabolitesapart from alkaloids and particular combinations of thesewere relevant for insect responses to infected plants(Rasmussen et al., 2008b). The above studies also demon-strated that endophyte alkaloid production and endophyte con-centrations depended strongly on the ryegrass cultivar(Rasmussen et al., 2007, 2008a; Liu et al., 2011), supportingthe findings that the host-plant genotype regulates fungalgrowth (Easton et al., 2002), and a genetical metabolomicsstudy described in the following section identified severalQTL in the ryegrass genome relevant to these traits(Koulman et al., 2009).

GENETICAL METABOLOMICS AND FORAGEBREEDING

The combination of genetics and metabolomics, also known asgenetical metabolomics has been successfully used in modeland crop species to identify genetic regions related to specificmetabolites or metabolic profiles (for reviews, see Keurentjeset al., 2006; Keurentjes, 2009; Kliebenstein, 2009; Fernie andKlee, 2011). An untargeted metabolomics and QTL analysis of2000 mass peaks detected in a recombinant inbred line ofArabidopsis thaliana allowed the reconstruction of the gluco-sinolate pathway, confirmed that at least two QTL contributeto variation in aliphatic glucosinolates, and uncovered newbiosynthetic steps related to flavonol glycosides (Keurentjeset al., 2006). Other studies of this type identified QTL forflavour volatile emissions in tomato (Schauer et al., 2006;Tieman et al., 2006) and flavonols in poplar (Morreel et al.,2006).

Only a very few studies have been published on geneticalmetabolomics in forage plants and we will discuss two exam-ples here. A targeted metabolic profiling approach has beenused to identify QTL related to high sugar content in bladesof L. perenne (Turner et al., 2006). Grasses with highersugar levels in blades have been bred to increase energysupply to the rumen microorganisms, decreasing N lossesfrom rumen protein degradation and increasing N supplied tothe ruminant, thereby reducing N losses in urine and nitrousoxide emissions from pastures (Miller et al., 2001; Wilkinsand Lovatt, 2003; Edwards et al., 2007; Parsons et al.,2011a, b). Temperate grasses accumulate water-soluble fruc-tans, i.e. polymeric chains of fructose attached to a core mol-ecule of sucrose, which are an alternative reserve carbohydrate


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to starch (Pavis et al., 2001). Biosynthesis and accumulation offructans show marked seasonal variation (Pollock and Jones,1979), and mobilization of fructans plays an important rolefor re-growth after defoliation (Morvand-Bertrand et al.,2001). Fructan metabolism is very complex and considerableinteractions of the expression of the high sugar trait in high-sugar grass cultivars with temperature, duration of re-growthafter defoliation, nutrient supply, flowering and associationwith symbiotic microorganisms has been shown (Pollock andCairns, 1991; Parsons et al., 2004; Rasmussen et al., 2007,2009b; Liu et al., 2011). Turner et al. (2006) mappedfructan, sucrose, glucose and fructose contents in L. perenneleaves and tiller bases using an F2 mapping family from ahigh water-soluble carbohydrate (WSC) × low WSC cross intwo seasons (spring and autumn) over 4 years. Despite highvariability of the traits and considerable environmental vari-ation, significant genetic effects were detected and the broad-sense heritability was moderate to high. The metabolic QTL(mQTL) explained between 8 % and 59 % of the total pheno-typic variation with the largest effects for fructan and totalWSC QTL near the top of chromosome 6. However, a largeproportion of the total phenotypic variation was unexplainedby QTL, and many QTL were identified in only 1 year prob-ably reflecting the strong impact of environmental conditionson the expression of the trait (Kamoshita et al., 2002). A sub-sequent study analysing relationships between growth anddrought-stress QTL with fructan QTL (Turner et al., 2008)showed that correlation between growth and fructan contentwas low to negative suggesting that growth is likely to berelated to a not very well-defined inherent plant growth cap-acity rather than to carbohydrate storage. Recently developedLC–MS-based methods for the rapid analysis of polymericfructans up to DP 100 (degree of polymerization) revealedthat high sugar grasses mainly differed in large polymeric fruc-tans (Harrison et al., 2009, 2011, 2012). These high-DP fruc-tans are difficult to separate and quantify with the analyticalmethods commonly used for fructan analysis and MS analysismight reveal additional and larger QTL for high sugar grasses.

An untargeted direct infusion MS/MS analysis of metabo-lites in clonal replicates of 200 genotypes of an endophyte-infected L. perenne F1 mapping population from a pair crossbetween two heterozygous genotypes in two consecutiveyears identified 22 ions with one or more reproducible QTLacross the 2 years (Koulman et al., 2009). QTL were detectedfor the fungal alkaloid peramine and for an unknown fungalcyclic oligopeptide identified in a previous study (Cao et al.,2008), clearly showing that fungal metabolite production isat least partially regulated by the host genome and suggestingthat marker-assisted selection might be an option for breedingof endophyte–host associations with a particular metabolicmake-up. A large number of ions with QTL were unknownsand would need more targeted LC-MS/MS analyticalmethods and purification for compound identification. Twoof the unknowns were subsequently isolated and shown to bethe plant pyrrolizidine alkaloids thesinine-rhamnoside and athesinine-rhamnoside-hexoside which had not been describedpreviously in Poaceae (Koulman et al., 2008). Some pyrrolizi-dine alkaloids have been associated with insect-deterringactivities (Frolich et al., 2006), and the finding that thesinineaccumulated in most of the ryegrass cultivars tested lead the

authors to speculate that breeders have inadvertently bred forthis metabolic trait (Koulman et al., 2008). This clearlyshows that untargeted metabolomics is very powerful indetecting unknown metabolic consequences of breeding.

Another promising area for implementing metabolomicsinto forage breeding is the development of MS-based analysisof grass-fibre composition. Low digestibility (or degradationrate) of grass cell walls can negatively affect feed intake andfibre chemical composition has been targeted in some foragebreeding programmes (Casler et al., 2008). The measurementof in sacco or in vivo degradation rates of plant material is ex-pensive and not useful for screening individual plants in abreeding programme. Analysis of plant cell-wall compositionand the correlation of concentrations of extracted wall com-pounds such as etherified hydroxycinnamic acids with degrad-ation rates has therefore been proposed as an alternativeapproach (Lam et al., 2003). However, cell walls in grassesare a complex of insoluble polyphenolic lignin tightly linkedto hemicellulose and cellulose by esterified and etherifiedhydroxycinnamic acids. Current extraction and detectionmethods for these fibres are difficult to use, time-consumingand costly, which has hampered the development of new cul-tivars with improved digestibility characteristics. Recently, amore mild extraction method with subsequent chromatograph-ic separation of larger complexes of lignin, polysaccharidesand hydroxycinnamic acids and detection by MS has beendescribed (Faville et al., 2010). This method is amenable tohigh-throughput analysis of large sample sets, and relativelyhigh correlation (up to 0.63) with in sacco degradation rateswas seen for some of the unidentified cell-wall polymers.These compounds also showed considerable genotypic vari-ation and might be very useful as metabolic markers infuture forage breeding programmes. A study of seasonalchanges in metabolic composition of 21 grass and legume cul-tivars using NMR also revealed high correlation of sugar con-centrations, fibres and in vitro organic matter digestibility withthe NMR fingerprints, mainly due to differences in spectral in-tensities of malic acid, choline and glucose (Bertram et al.,2010). These studies highlight that metabolomics-basedapproaches deliver high-throughput detection and selectionmethods for forage genotypes with improved feed qualityand can help overcome some of the current limitations offorage breeding programmes.

CONCLUSIONS

Meeting current and future demands of the pastoral industryfor new forage cultivars with superior agronomic charac-teristics to increase animal production and reduce environmen-tal impacts will be a challenge for plant breeders. Newtechnologies such as genome sequencing, transcriptomicsand metabolomics can be very powerful tools for large-scalegeno- and phenotyping, and for improving our understandingof complex traits and our ability to manipulate them.Particularly the combination of genetics and metabolomicstechnologies is a very promising, albeit under-developed tech-nique for forage breeding. The plant metabolome is verycomplex and the development of metabolomics approachesis still in its early stages and requires currently expensive ana-lytical instrumentation and extensive bioinformatics


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infrastructure. This has resulted in slow uptake of these tech-nologies by forage breeders and a lack of examples of success-ful implementation in forage breeding programmes so far.

Much of the knowledge of the traits discussed in this reviewcomes from studies on model species or cultivated cereals.These plants are most often inbreeding annuals with floweringand seed setting as a major strategy for survival of the popula-tion. Forage species, on the other hand, are mostly outbreedingperennials which have evolved long-term strategies for sur-vival and propagation of vegetative material often involvingextended phenotypes, i.e. associations with symbiotic micro-organisms. Furthermore, the harvested component of forageplants in grazed pastures is vegetative photosyntheticallyactive tissue, the only source of new carbon for plant growthand so pasture production. Hence, yield is a trade-offbetween removing leaves to feed grazing animals while sus-taining enough leaf material to photosynthesize, and improve-ments in ‘yield’ are very difficult to achieve and sustain forgrazed forage plants. These special features have limited thesuccess of translational approaches from model species andmore research on major forage species is urgently needed toassist forage breeding in overcoming current limitations ofpasture-based production systems. To be most effective,these techniques need to be accompanied by whole-plantphysiology, proof of concept (modelling) studies related tothe efficacy of specific traits, and wider considerations of pos-sible consequences of new traits, particularly on fitness of newpopulations.

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Metabolomics of forage plants: A review