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BlackwellPublishingLtdOxford,UKNPHNew Phytologist0028-646X1469-8137©TheAuthors (2009).Journalcompilation©NewPhytologist(2009)293110.1111/j.1469-8137.2009.02931.x June 200900??????CommentaryCommentary Commentary

Commentary

Plant–pathogen interactions:

a view from the evolutionarybasement

The Vermin only teaze and pinchTheir Foes superior by an Inch.So Nat’ralists observe, a FleaHath smaller Fleas that on him prey, And these have smaller Fleas to bite ‘em, And so proceed ad infinitum– Swift. On Poetry: a Rhapsody (1733)

Jonathan Swift’s satiric verses warning aspiring poets of theadverse opinions of critics have much to recommend them asadvice to biologists, struggling to persuade reviewers of thevalue of their work or committees of the ‘impact’ of theirresearch grants. But these lines, in particular, serve to remindus how all organisms (not just poets and biologists) engage ina struggle with pathogens, pests and parasites, and must needsdeploy a variety of defensive strategies with which to repelthem. In this issue of New Phytologist (pp. 432–443), MikkoLehtonen and his colleagues at the University of Helsinkidescribe how the war between plant and pathogen is waged by bryophytes, using the unique tools afforded by the model

moss, Physcomitrella patens.

‘Using the highly efficient gene targeting technology

available in Physcomitrella to create knockout mutant

lines they have demonstrated that these peroxidase genes

form an essential part of the moss defence mechanism.’

It is estimated that 20–40% of crop yield, worldwide, is lostto pathogen attack – principally plant pathogenic fungi – every year, and that this proportion would be even greater were itnot for the intervention of crop-protection strategies. Clearly,plant pathogens pose a threat to agricultural monocultures.However, a glance out of the window reminds us that, left totheir own devices, the plants which dominate our natural

environment ward off these depredations very effectively. With-out a doubt, close observation of plants reveals incidences of pathogenesis, but it also reveals the frequent and characteristicfingerprints of effective defence against pathogens, usually inthe form of the small and sporadic lesions that mark the activity of the hypersensitive response to infections.

Flowering plants deploy highly effective countermeasuresagainst microbial infection that rely on their ability to recognizea potential pathogen and neutralize it through the rapid releaseof a range of fungistatic substances, including reactive oxygenspecies (ROS), phytoalexins and specific antifungal enzymessuch as chitinases. These are allied with programmed death of the infected cell and the modification of the surrounding cell walls to restrict the further passage of infection. The speed with

which this response is mounted is the key to its effectiveness,and has been characterized, genetically, as a specific interactionbetween resistance (R ) genes within the host plant and pathogen-encoded avirulence (avr ) loci. This ‘gene-for-gene’ response isexplained through a molecular recognition between an R -geneproduct – essentially a plant receptor protein – and a fungal avr -specified component to trigger an intracellular signal trans-duction pathway that triggers these events. Both R and avr lociare highly polymorphic, a consequence of the evolutionary ‘arms race’ that develops as host and pathogen compete to survive(Dangl & Jones, 2001).

Among the most prominent features of the plant response

to infection is the ‘oxidative burst’: a rapid release of ROS – inparticular hydrogen peroxide (Bolwell et al ., 2002). Hydrogenperoxide is multifunctional. It can serve directly as an anti-microbial agent, through its antiseptic properties, as well asparticipating in mechanical defence through the generation of papillae (Thordal-Christensen et al ., 1997), the modificationof cell walls (cross-linking and lignification through the incor-poration of phenolic compounds) to restrict fungal spread, thesynthesis of phytoalexins and as a potent intracellular andintercellular signalling compound to activate further responses(Torres et al ., 2006; Almagro et al ., 2009).

By contrast, comparatively little is known about the patho-gens of the ‘lower’ plants, although pathogenic effects of fungal

infection have been reported for a number of mosses (com-prehensively reviewed by Davey & Currah, 2006). However,until recently, little was known of the mechanisms that thebryophytes deploy to resist infection. Because the dominantgametophyte stage of the moss life cycle lacks a protective cuticle,mosses should be particularly susceptible to infection. Add tothis organs that are typically one cell thick, and the consequencesof a successful infection are not difficult to envisage. However,it is clear that the mosses are a very successful taxon. They haveflourished for the past 450 million years, and are the dominant



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form of vegetation in some ecosystems (e.g. polar regions).Comprising c . 10 000 species, the mosses are second only tothe angiosperms in species diversity. It is not surprising there-fore that this group of plants exhibits a robust response toinfection. The wide range of molecular genetic tools, devel-oped by the Physcomitrella research community, now provideresearchers with the resources necessary to undertake a com-

prehensive molecular analysis of moss pathogen responses,and through comparative analysis, to place the existing infor-mation regarding the resistance of flowering plants within anevolutionary framework.

Lehtonen et al . (2009) have isolated naturally occurringfungal bryo-pathogens of a moss species in the field (Raco-mitrium japonicum) and have shown that these are equally pathogenic to Physcomitrella. Having identified secretion of peroxidase as a rapid response to elicitation by the fungal cell- wall-derived compound chitosan, they have identified thegenes encoding this enzyme as a pair of duplicated Class IIIperoxidase genes clustering in a moss-specific phylogenetic

clade. Using the highly efficient gene-targeting technology available in Physcomitrella to create knockout mutant lines,they have demonstrated that these peroxidase genes – thateither use or generate hydrogen peroxide – form an essentialpart of the moss defence mechanism. The questions that arisefrom this are as follows.• How does Physcomitrella – and by analogy other mosses –recognize the presence of the fungal elicitor?• To what extent do the defence responses of mosses resemblethose of higher plants?• What can we learn from comparative studies about theevolution of the plant pathogen response?

In recent years, considerable progress has been made indetermining the molecular features of plant–pathogen resist-ance mechanisms: an enterprise facilitated greatly through theuse of the model angiosperm, Arabidopsis thaliana, and theextensive molecular genetic resources available for this species.Genomic analysis reveals that over 200 R genes are required forresistance, not only to fungal pathogens, but also to infection with bacteria and viruses, as well as to predation by invertebratepests such as nematodes and insects. These genes display com-mon features and are often clustered within the genome, sug-gesting that copy number expansion and diversification has beenan important feature of their evolution (Sterck et al ., 2007).In particular, the presence of leucine-rich repeat (LRR) sequences

as a common feature of R -gene products indicates the basis forspecific recognition of avr-dependent elicitors because thesedomains commonly participate in protein–protein interactionsand in specific ligand-binding (Kobe & Deisenhofer, 1995),and it is these regions of the R-gene products that display sig-nificantly high levels of polymorphism, indicative of the highly active selection operating on these loci (Dangl & Jones, 2001;Bakker et al ., 2006). This combination of gene duplicationand polymorphic variation provides plants with an adaptively flexible means of repelling pathogens.

It is now recognized that plant resistance to pathogens ismultilayered: an initial response to contact with pathogen-specific elicitors (or ‘pathogen-associated molecular patterns’:PAMPs), backed up by a second phase of recognition of pathogen-derived ‘effectors’ with which the pathogen seeks tosuppress the response to an initial recognition event ( Jones &Dangl, 2006; Boller & Felix, 2009). Notwithstanding this

added complexity, the recognition of each of these pathogenicsignals is based on R–avr interactions, and can lead to the acti-vation of hypersensitive cell death and the release of antifungalmicrobial compounds.

The R -gene-mediated pathogen response is clearly essentialfor the health of flowering plants, but how much is knownabout the evolution of this mechanism? Some features of theresponse are clearly ancient. R -gene products themselves shareconsiderable similarity with proteins involved in the mamma-lian programmed cell death pathway (Dangl & Jones, 2001),suggesting that apoptosis is an ancient feature of multicellularorganisms that has been recruited by evolution to provide a

solution to similar problems in different organisms. Most R genes are distinctively modular, the most abundant class com-prising sequences encoding nucleotide-binding (NB) domains,and a domain homologous with the Drosophila Toll and mam-malian interleukin-2 receptors (TIR) that is thought to havean intracellular signalling role. To what extent are these activities widespread among the Plant Kingdom? The development of Physcomitrella for comparative functional genomic studiespromises to shed light on this question.

How then do mosses perceive and respond to pathogenicinfection? Probably by using some of the same mechanismsthat exist in flowering plants: previous studies have demonstratedthat

Physcomitrella will respond to infection with known angio-

sperm pathogens, such as Erwinia and Botrytis , in a manneranalogous to angiosperms (Andersson et al ., 2005; Ponce deLéon et al ., 2007) and pathogen receptor type LRR-containinggenes have been isolated from Physcomitrella (Akita & Valkonen,2002) and also identified in other basal lineages, includingliverworts and charophycean algae (Sasaki et al ., 2007). Withthe publication of reference genomes for the mosses (Phys-comitrella) and lycopods (Selaginella), we can now examine theextent of the gene families encoding LRR-domain genes.

A rapid (and by no means exhaustive) search of these twogenomes reveals over 150 (Physcomitrella) and 110 (Selaginella)LRR-containing genes, respectively. However, compared with

Arabidopsis , only a handful have the characteristic motifs of the abundant flowering-plant TIR–NB–LRR family: in Phys-comitrella, I found only 6 gene models containing TIR motifs, whilst 28 have NB domains; in Selaginella the correspondingnumbers are 2 and 16, respectively. Therefore, it seems that whilst the expansion of LRR repeat genes is widespread amongland plants, the evolutionary acquisition of the signallingdomains may be a feature of the angiosperm radiation. This may underpin taxon-specific differences that have been recorded inthe recognition of specific PAMPs (Qutob et al ., 2006). It will

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be both practical and fruitful to apply the powerful reversegenetics tools afforded by Physcomitrella to investigate thefunctions of those receptors that do exhibit a high degree of similarity with their angiosperm counterparts. Nevertheless,responses elicited by microbial infection in Physcomitrella aresimilar in many ways to those in flowering plants, with therelease of active oxygen species, mobilization of salicylic acid

signalling (Andersson et al ., 2005) and cell death (Ponce deLéon et al ., 2007).

It is tempting to speculate that necessary for the successfultransition of green plants from an aquatic environment tocolonize terrestrial habitats c. 470 million years ago was theevolution of an effective set of defences against airborne patho-gens, and that the expansion and diversification of pathogenreceptor recognition domains (the LRR domains) date from thistime. This is clearly a question that can be addressed throughcomparative genomics, although at present no genome sequencesexist for a taxon representative of the last common ancestor of the land plants.

It is generally believed that the land plants are derived fromthe Charophycean algae (Karol et al ., 2001), and whilst it is tobe hoped that the genome sequence of either Chara or Coleo-chaete will be determined in the not-too-distant future, atpresent these taxa are currently only the subject of expressedsequence tag (EST) programmes, represented by fewer than500 ESTs available in the NCBI Trace Archive. New sequencingtechnologies will undoubtedly play a part in rectifying thismissing link in the genome databases, and it will clearly be of interest to determine the representation of the LRR gene setin either of these organisms. Until such times, we can only inspect the genome of the unicellular chlorophyte, Chlamydo-

monas reinhardtii , and that of its colonial relative

Volvox carteri .

Each of these organisms contains only a very restricted set of LRR genes (< 20), but these algae diverged from the greenplant lineage approx. 1 billion years ago, and additionally aresingle-celled organisms. It is not unreasonable to suggest thata defence mechanism which operates primarily through theprogrammed death of host cells might not be the most evolu-tionary effective strategy for such organisms. Whatever thefuture holds, it is clear that there is much to be learnt about theacquisition of pathogen defence through the study of basal taxa.

Andrew C. Cuming

Centre for Plant Sciences, Leeds University,Leeds LS2 9JT, UK

(tel +44 113 3433096; email [email protected])

References

Akita M, Valkonen JPT. 2002. A novel gene family in moss (Physcomitrella patens ) shows sequence homology and a phylogenetic relationship with the

TIR-NBS class of plant disease resistance genes. Journal of Molecular Evolution 55: 595–605.

Almagro L, Gomez Ros LV, Belchi-Navarro SB, Bru R, Ros Barcelo A,

Pedreno MA. 2009. Class III peroxidases in plant defence reactions.

Journal of Experimental Botany 60: 377–390. Andersson RA, Akita M, Pirhonen M, Gammelgard E, Valkonen JPT.

2005. Moss-Erwinia pathosystem reveals possible similarities in

pathogenesis and pathogen defense in vascular and nonvascular plants.

Journal of General Plant Pathology 71: 23–28.

Bakker EG, Toomajian C, Kreitman M, Bergelson J. 2006. A genome-wide

survey of R gene polymorphisms. Plant Cell 18: 1803–1818.

Boller T, Felix G. 2009. A renaissance of elicitors: perception of

microbe-associated molecular patterns and danger signals by

pattern-recognition receptors. Annual Review of Plant Biology 60:

379–406.

Bolwell GP, Bindschedler LV, Blee KA, Butt VS, Davies DR, Gardner SL,

Gerrish C, Minibayeva F. 2002. The apoplastic oxidative burst in response

to biotic stress in plants: a three-component system. Journal of Experimental Botany 53: 1367–1376.

Dangl JL, Jones JDG. 2001. Plant pathogens and integrated defenceresponses to infection. Nature 411: 826–833.

Davey ML, Currah RS. 2006. Interactions between mosses (Bryophyta) and

fungi. Canadian Journal of Botany 84: 1509–1519.

Jones JDG, Dangl JL. 2006. The plant immune system. Nature 444:

323–329.

Karol KG, McCourt RM, Cimino MT, Delwiche CF. 2001. The closest

living relatives of land plants. Science 295: 2351–2353.

Kobe B, Deisenhofer J. 1995. Proteins with leucine rich repeats. Current Opinions in Structural Biology 5: 409–416.

Lehtonen MT, Akita M, Kalkkinen N, Ahola-Iivarinen E, Röholm G,

Somervuo P, Thelander M, Valkonen JPT. 2009. Quickly released

peroxidase of moss in defense against fungal invaders. New Phytologist 183: 432–443.

Ponce de Léon I, Oliver JP, Castro A, Gaggero C, Bentacor, Vidal S. 2007.

Erwinia carotovora elicitors and Botrytis cinerea activate defense responsesin Physcomitrella patens . BMC Plant Biology 7: 52.

Qutob D, Kemmerling B, Brunner F, Küfner I, Engelhardt S, Gust AA,

Luberacki B, Seitz HU, Stahl D, Rauhut T et al . 2006. Phytotoxicity and

innate immune responses induced by Nep1-like proteins. Plant Cell 18:

3721–3744.

Sasaki G, Katoh K, Hirose N, Suga H, Kuma K, Miyata T, Su Z-H. 2007.

Multiple receptor-like kinase cDNAs from liverwort Marchantia polymorpha and two charophycean green algae, Closterium ehrenbergii and

Nitella axillaris : extensive gene duplications and gene shufflings in the early

evolution of streptophytes. Gene 401: 135–144.

Sterck L, Rombauts S, Vandepoele K, Rouzé P, Vande Peer Y. 2007. How

many genes are there in plants ( ... and why are they there)? Current Opinion in Plant Biology 10: 199–203.

Thordal-Christensen H, Zhang Z, Wei Y, Collinge DB. 1997. Subcellular

localization of H2O2 in plants. H2O2 accumulation in papillae andhypersensitive response during the barley-powdery mildew interaction.

Plant Journal 11: 1187–1194.

Torres MA, Jones JDG, Dangl JL. 2006. Reactive oxtgen species signaling

in response to pathogens. Plant Physiology 141: 373–378.

Key words: disease resistance, hypersensitive response, peroxidase,

Physcomitrella patens , plant pathogen resistance, R genes.293210.1111/j.1469-8137.2009.02932.x June 200900??????CommentaryCommentary

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Commentary Commentary

The hidden language offlowering plants: floralodours as a key for understanding angiospermevolution?

We live in a world filled with flowering plants and insects, with both groups showing enormous species diversity. However,explaining this diversity has been a major challenge. Onereason suggested for such species diversity is that angiospermshave established mutualistic relationships with different pollinatortypes, leading to co-evolution of both groups (Stebbins, 1970;Thien et al ., 2000). Chemical communication via floralfragrances has been shown to play a central role in attracting

pollinators (Knudsen et al ., 2006), and it is reasonable tohypothesize that floral volatiles played a key role in early angiosperm evolution (Gottsberger, 1988; Thien et al ., 2000).This is supported by observations that strong floral fragrancesare a characteristic feature of many extant taxa from basalangiosperm lineages and that they play an important role forpollinator attraction in most species in these groups (Ervik & Knudsen, 2003; Silberbauer-Gottsberger et al ., 2003).Unfortunately, compared with other plant groups (e.g. orchids)our knowledge on the odour chemistry of basal angiospermlineages is still limited (Knudsen et al ., 2006). Nevertheless,recent publications on the floral odours of basal groups haverevealed interesting insights, for example, into the diversity of floral fragrances (Bernhardt et al ., 2003; Goodrich et al .,2006; Teichert, 2008). The same is true for the paper on floralfragrances of Asimina (pawpaw) and Deeringothamnus species(Annonaceae) by Katherine Goodrich and Robert Raguso inthis issue of New Phytologist (pp. 457–469). First, the dataon 10 species of the North American groups of Annonaceaefill an important gap in our knowledge, as Asimina andDeeringothamnus are the only temperate genera of thisotherwise tropical family (Doyle & Le Thomas, 1997).Second, the fragrances they found, typical fermentation odours,are extremely unusual among angiosperm flowers. Four of the

Asimina species, with wine red-coloured flowers (‘maroon-

phenotype’), emit odours that resemble the scent of decayingorganic matter. The scent blends comprise chemicals that aresimilar to the emissions of baker’s yeast (e.g. acetic acid, ethylacetate, ethanol, 3-methyl-1-butanol; see Goodrich et al ., 2006)but they also contain compounds such as amino acid-derivedaldoximes and nitriles. The scent composition suggests thatthese flowers might attract saprophilous flies and beetles, butmore detailed investigations of the pollination biology of these species are needed. The four Asimina species and the twoDeeringothamnus species with white flowers emit floral volatiles

that indicate a generalist pollination system. The floral scentof D. pulchellus was dominated by sweet-smelling benzenoidcompounds normally found in flowers pollinated by moths.But there are two more striking findings in this paper: the highdiversity of chemicals emitted from the flowers (Goodrich &Raguso detected 272 compounds in 11 species of only twogenera), and the complex spatial and temporal odour patterns

for female and male ontogenetic stages. Their study is also afascinating example illustrating how complex and dynamicfloral odours in basal angiosperms can be.

‘We are starting to understand that plants are quite flexible in

their odour chemistry and that this flexibility is linked with their

evolutionary success.’

Generalist vs specialist modes of pollination inbasal angiosperm groups and the role of beetles

The hypothesis that beetles pollinated the early angiospermsdates back to Faegri & van der Pijl (1979, p. 51) and their‘mess and soil’ pollination mode concept in basal angiospermtaxa – unspecialized (primitive) flowers utilize unspecialized(primitive) insects (beetles) as pollinators. Flowers with a‘mess and soil’ pollination mode often bear many anthers anddeposit large amounts of pollen over the body surface of flower visitors while not offering nectar or lipids as a reward(Faegri & van der Pijl, 1979). It is true that beetles are adominant pollinator group in many magnoliids, including Annonaceae, with up to nine beetle families involved inpollination (Bernhardt, 2000). However, beetles are interestingly not the dominant group of flower visitors in the first threebranches of the angiosperm phylogenetic tree (ANITA grade, with ∼201 species) and it now seems that they represent aderived syndrome in the ANITA-grade plants (Thien et al .,2009). Furthermore, the magnoliids are dominated by beetle

pollination and are regarded as specialized systems whereflowers are specifically adapted to beetle pollinators (Silberbauer-Gottsberger et al ., 2003). According to Thien et al . (2009),the affiliations of ANITA-grade species with their flowervisitors suggest that Diptera are the strongest candidates as thefirst pollinators of early angiosperms.

With more than 2500 species, Annonaceae are one of themost diverse families of the basal groups of flowering plants andthe family has played an important role in discussions of the originand evolution of angiosperms (Doyle & Le Thomas, 1997;




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Gottsberger, 1999). Annonaceae flowers usually contain no nectarbut the flowers provide pollinators with nutritious floral tissues,pollen, and in some species, shelter inside a pollination chamber.In many, particularly night-active, Annonaceae species, thermo-genesis enhances floral odour emission (Gottsberger, 1999). Ithas been estimated that c . 90% of the Annonaceae species studiedso far seem to be adapted to beetle pollination (Teichert, 2008)

with a differentiation into species pollinated by small beetlesand large beetles (Silberbauer-Gottsberger et al ., 2003). Whilemany of the species in the ancestral genera of the family (e.g.

Anaxagorea) are pollinated by small beetles, pollination by largebeetles is a specialized condition within the family and wasprobably acquired late in its evolution (Gottsberger, 1999;Silberbauer-Gottsberger et al ., 2003). However, other pollinatorgroups interacting with Annonaceae, such as thrips, flies,cockroaches and perfume-collecting euglossine bees (Gotts-berger, 1999; Silberbauer-Gottsberger et al ., 2003; Teichert,2008 and references therein), also provide evidence for otherspecialized pollination systems within the Annonaceae.

Differentiation of Annonaceae pollinationsystems in odour space

Before the present study carried out by Goodrich & Raguso,floral fragrances of only a few, mostly Neotropical, Annonaceaehad been analyzed (Jürgenset al ., 2000; Teichert, 2008; Teichertet al ., 2008). Based on the floral scent data of six Annonaceaespecies with small beetle pollination syndrome, which emit a wide range of different compounds in different compoundclasses, Jürgens et al . (2000) wondered whether the flowerscent reflects the opportunistic behavior of the flower visitors.It is possible that Nitidulidae beetles, which normally live on,and eat, rotten bark and fruits, are attracted by a wide rangeof compounds that all might be indicative of fruits and/orrotten bark (Jürgens et al ., 2000).

Although there are only limited data available on the floralvolatiles of Annonaceae, visualization of the combined datasets in odour space gives some evidence that different pollina-tion types are represented by clearly separated odour clusters(Fig. 1). The analysis was based on nine different genera of the Annonaceae (21 species), including the data of Goodrich &Raguso (this issue of New Phytologist ), Jürgens et al . (2000),Teichert et al . (2008), Teichert (2008) and unpublished data(A. Jürgens & G. Gottsberger). The analysis revealed that floral

fragrances reflect both phylogenetic constraints/relationshipsand the pollination biology of the species (Fig. 1), also showingthat unrelated species, associated with similar pollinator types,occupy the same odour space.

For species with sweet fruity odour blends, a green–yellow colouration, and relatively small pollination chambers that aremainly pollinated by small beetles ( Anaxagorea, Duguetia,Guatteria, Rollinia and Xylopia; Silberbauer-Gottsberger et al .,2003), the odour space is relatively large. These species prob-ably represent different chemical strategies by using hydrocarbon

esters ( Anaxagorea, Guatteria), naphthalene (Rollinia), benzenoidcompounds ( Xylopia), or monoterpenoids (Duguetia, Rollinia)to attract small beetles. Furthermore, the differences in odourchemistry might also reflect the taxonomic heterogeneity of the pollinating beetles. Although mainly pollinated by Nitidu-lidae, other beetles could play a role as additional pollinators(e.g. Staphylinidae, Chrysomelidae) and, in Xylopia aromatica,

thrips also seem to play an important role. However, these areall subsumed under the ‘small beetle pollination syndrome’.

Close to the small beetle pollination syndrome we find Annona glabra, a species pollinated by relatively small Chryso-melidae or Curculionidae beetles (Gottsberger, 1999) whereGoodrich & Raguso found 3-pentanyl acetate and severalmonoterpenoids as major scent compounds. The spicy floralodour of Unonopsis stipitata shows similarities in the odourcomposition with that of A. glabra and emits many of thesame monoterpenoids. However, U. stipitata is pollinated by perfume-collecting male euglossine bees and its scent is dom-inated by several monoterpenoids, particularly trans-carvone

oxide, which was only present in this species (Teichert, 2008).Interestingly, trans-carvone oxide has been found severaltimes in euglossine-pollinated plants of other unrelated plantfamilies (e.g. orchids) and it has been suggested that thiscompound might be the key attractant for euglossine bees(Whitten et al ., 1986).

The Asimina and Deeringothamnus species analyzed by Goodrich & Raguso form a cluster separate from the othergenera. Within this cluster we find a chemical differentiationof Asimina flowers with the ‘maroon-phenotype’, emittingfermented/decaying scents (suggesting a mimicry-based pol-lination strategy), from another cluster with flowers of the‘white-phenotype’, emitting pleasant scents (suggesting honestsignaling and a reward-based pollination strategy) (Fig. 1). Itis known that fermenting odours elicit strong physiologicaland behavioral responses in fruit flies and some beetles(Stensmyr et al ., 2003) and it seems likely that scent is mainly responsible for pollinator attraction in Asimina species withyeasty scent.

Floral fragrances as a key innovation promotingpollinator shifts and diversification in floweringplants

Stebbins (1970) wrote that ‘more specialized vectors are

attracted to flowers by a variety of stimuli, of which scent may be even more important than either shape or colour’. Advancesin our understanding of floral volatiles and their role inpollination have been enormous in the last 20 yr with theemergence of technological breakthroughs for floral volatileanalysis. In 1993, Knudsen et al . compiled floral scent data on441 species, and listed 700 compounds; in a recent update,Knudsen et al . (2006) listed 991 species and 1791 compounds. A rough calculation shows that the average number of new (identified) compounds per species has increased from 1.6 (in




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1993) to 1.8 (in 2006). Part of the increase can be attributedto the development of more sensitive technologies for samplingplant volatiles and better ways of compound identification(e.g. via database systems). Nevertheless, it seems that a plateauregarding the chemical diversity of angiosperm flowers has notyet been reached. Odour diversity of the Annonaceae speciesinvestigated so far seems to be relatively high compared withthat of all angiosperms listed in Knudsen et al . (2006). The Annonaceae analyzed so far, representing 2.2% (22 species of 991) of the angiosperms, comprise 8.4% (150 compounds of 1791, not including the many unidentified compounds listed

by Goodrich & Raguso) of the total odour diversity found inflowering plants.

A key question for the coming decade will be whetherangiosperm diversification is correlated with a potential forrapid changes in the floral scent composition. We are startingto understand that plants are quite flexible in their odourchemistry and that this flexibility is linked with their evolu-tionary success. The scent composition of flowers can be very complex, sometimes containing > 50 compounds per sample.In some cases, single key odour signals (like trans-carvone

oxide in Unonopsis stipitata) might be responsible for attract-ing specific pollinators (Teichert et al ., 2008); however, thecommon situation in most flowering plants is that severalcompounds together attract a diverse array of different flowervisitors. Not all are necessarily effective pollinators and otherfloral features often function as filters. In the Annonaceae,other factors, such as the size of the pollination chamber, floralcolour and the reward system, need to be considered to under-stand the evolution of this group. In situations with multipleflower visitors and multiple volatiles emitted from a flower,compound X might be an attractant for pollinator A only,

whereas compound Z might be an attractant for pollinator A plus B (or B only), etc. Thus, floral scent can be seen as a multi-channel signal, and small evolutionary changes in the scentcomposition might open (or close) signal channels for flowervisitors that might affect the plant’s fitness. Furthermore,insects are often opportunistic in their behavior, and theinsect, as a signal receiver, may respond to a range of differentchemicals. In such a scenario different chemical strategies may evolve, attracting the same type of pollinator but exploitingdifferent aspects of its olfactory spectrum.

Fig. 1 Visualization of floral fragrance similarities and (hypothesized) pollinators of 21 Annonaceae species. Nonmetric multidimensional scalingwas based on Bray–Curtis similarities of 150 identified scent components. Asimina and Deeringothamnus species (triangles) and Annona glabra are from Goodrich & Raguso (2009) (open circle) (this issue of New Phytologist ). The ‘maroon-phenotype’ of Asimina flowers (closed triangles)and the ‘white-phenotype’ (open triangles) are indicated. Unonopsis stipitata and Anaxagorea prinoides are from Teichert et al. (2008) andTeichert (2008); Anaxagorea brevipes, A. dolichocarpa, Xylopia aromatica, X. benthamii, Rollinia insignis and R. mucosaare from Jürgens et al.(2000); Guatteria foliosa and Duguetia asterotricha are from A. Jürgens & G. Gottsberger (unpublished data). The two-dimensional stress valueis 0.15; ANOSIM Global R = 0.776; P < 0.01.




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Acknowledgements

I would like to thank Karl Duffy, Steve Johnson, AdamShuttleworth and Taina Witt for valuable comments anddiscussion on the manuscript.

Andreas Jürgens

School of Biological and Conservation Sciences,University of KwaZulu-Natal, P. Bag X01 Scottsville,

Pietermaritzburg 3209, South Africa(tel +27 (0)33 2605657; email [email protected])

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UK: Pergamon Press.

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in Asimina and Deeringothamnus (Annonaceae). New Phytologist 183:

457–469.

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( Asimina triloba : Annonaceae). International Journal of Plant Sciences 167:

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Taxon 37: 630–643.

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distribution of floral scent. The Botanical Review 72: 1–120.

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volatile compounds isolated by head-space techniques. Phytochemistry 33:253–280.

Silberbauer-Gottsberger I, Gottsberger G, Webber AC. 2003.

Morphological and functional flower characteristics of New and Old

World Annonaceae with respect to their mode of pollination. Taxon 52:

701–718.

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angiosperms. I: pollination mechanisms. Annual Review of Ecology and Systematics 1: 307–326.

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Novel natural ligands for Drosophila olfactory receptor neurons. Journal of Experimental Biology 206: 715–724.

Teichert H. 2008. Pollination biology of cantharophilous and melittophilous Annonaceae and Cyclanthaceae in French Guiana . PhD thesis, University of

Ulm, Ulm, Germany.

Teichert H, Dötterl S, Zimma B, Ayasse M, Gottsberger G. 2008.Perfume-collecting male euglossine bees as pollinators of a basal

angiosperm: the case of Unonopsis stipitata (Annonaceae). Plant Biology 11:

29–37.

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Key words: angiosperm, diversification, evolution, floral fragrances,

pollination.287210.1111/j.1469-8137.2009.02872.xApril200900??????LetterLetters

Letters

Letters

Ussing’s conundrum and the

search for transportmechanisms in plants

Plant transport physiologists have developed a range of modelsdescribing the movement of ions across cell membranes.However, while substantial progress has been made towardsproviding precise descriptions of the mechanisms underlyingthese fluxes, important instances remain in which the prevailingmodels cannot account for repeated observations, particularly

in terms of energy transformations. As we shall show, dis-agreements with experimental findings may entail a revisionof the proposed models, similarly to what has been required

in animal transport studies (Ussing, 1994; see below). Wepresent, as a key example, the futile cycling of sodium undertoxic conditions (see Britto & Kronzucker, 2006, and discussedlater), and show that unidirectional flux magnitudes measuredby several groups, including our own, cannot be explainedenergetically by current models. We attempt to explainthese observations by proposing alternative mechanisms of Na+

transport across the root-cell plasma membrane.The influx/efflux cycle of Na+ in plants has been attributed

to the sophisticated activity of distinct transport proteins in

© The Authors (2009) New Phytologist (2009) 183: 243–246 Journal compilation © New Phytologist (2009) www.newphytologist.org



Letters Forum244

the plasma membrane (see Fig. 1 in Malagoli et al ., 2008). According to this widely accepted view, the majority of Na+

influx into the plant cell occurs via nonselective cation channels(NSCCs; other possible Na+ influx transporters includepartially specific potassium channels and HKT transporters),

while Na+

efflux is thought to be mediated by a Na+

/H+

exchanger, possibly SOS1 (Amtmann & Sanders, 1999; Munns& Tester, 2008).

The consensus view of the thermodynamic conditionsoccuring during salinity stress is that: (1) root cytosolic Na+

activity ( ) is substantially lower than external (in oneof the few studies that measured cytosolic directly, it wasfound to be as high as 28 mM, against an external of 150 mM (Carden et al ., 2003)); and (2) the chemical potentialdifference for Na+ across the plasma membrane is amplifiedgreatly by the electrical potential difference (approx. −80 mV in Carden et al ., 2003), as per the Nernst equation. A steepelectrochemical potential gradient results, favoring passive influxof Na+ into the cell, and an active efflux, powered by the elec-trochemical H+ gradient generated by plasma-membrane proton ATPases. To estimate the energy required to drive the Na+

fluxing proposed in this model, it is useful to consider that, inmany cases, it appears to be almost purely cyclical; that is,relatively little Na+ accumulates in the plant compared withthe large amount that initially enters, and ultimately exits, thesystem. Evidence for cyclic Na+ transport includes the loss, within 1 h, of 90% of 22Na+ absorbed in 10 min by corn roots(Cheeseman, 1982); the precipitous decline in apparent 24Na+

influx within 5 min of labeling intact Suaeda maritima roots(Lazof & Cheeseman, 1986; also see Britto & Kronzucker,

2006); the rapid (< 5 min) saturation of 22Na+ in roots of Ara-bidopsis (Essah et al ., 2003); and efflux : influx ratios of 0.86–0.90 in rice (Malagoli et al ., 2008), 0.92–0.95 in Puccinelliatenuiflora and wheat (Wang et al ., 2009), and 0.95 in barley (Kronzucker et al ., 2006).

Thus, the active (efflux) component of this cycle is nearly equal to the passive (influx) component, and therefore influxmeasurements, which are more commonly found in the liter-ature and more straightforward to interpret, can be used toapproximate efflux, with only a slight overestimate (in fact,

the influx component may also entail an energy cost, despitebeing in the thermodynamically passive direction, because itinvolves an electrogenic uniport that must be counteracted by proton pumping; Na+ efflux cannot accomplish this, if it isindeed electroneutral, because of the exchange with H+). The

required energy can then be predicted, in terms of O2 consumedper Na+ transported, on the basis of the following stoichio-metric series that draws upon models of transport energization:a 1:1 stoichiometry for Na+/H+ antiport (Shi et al ., 2000;Pardo et al ., 2006; Yeo, 2007); a second 1:1 stoichiometry between H+ pumping and ATP hydrolysis (Briskin & Reynolds-Niesman, 1991; Palmgren, 2001); and a third stoichiometry,of 5:1, between ATP synthesized and O2 consumed in respi-ration (i.e. ‘phosphorylation efficiency’ or P : O2 ratio; Poorteret al ., 1991; Scheurwater, 1999; Kurimoto et al ., 2004). Tosummarize, for every O2 consumed in respiration, five Na+ ionsare extruded from the cell via Na+/H+ exchange. Energy demands will be even greater as a result of simultaneous Cl− transportand other transport steps within the plant, such as across thetonoplast, or from root to shoot (see the analysis by Yeo, 1983).

The problem with this analysis becomes evident upon exam-ining actual Na+ flux magnitudes measured in plants andcomparing them with O2 normally consumed in respiration.Table 1 predicts the O2-consumption rates theoretically asso-ciated with Na+ fluxes from a number of studies, based on thepreceding analysis; in every case, these values are extremely high and almost certainly exceed the root’s respiratory budget.For example, maximal root respiration was only approx. 30 µmolof O2 g (root FW)−1 h−1 (assuming, conservatively, a fresh root weight : dry root weight ratio of 10) in a study of 24 wild

plant species (Poorter et al ., 1991), and was even less in a study of six crop species (Rao & Ito, 1998). These values fall farshort of the predicted value in three of the four cases presentedin Table 1. In the fourth case (Malagoli et al ., 2008), measuredrespiration rates of only 11 µmol g (root FW)−1 h−1 were com-pared directly with Na+ efflux; again, they were only half of what would be required to account for the flux.

Clearly, because there are other demands on respiration (e.g.for growth, maintenance and the fluxes of other ions), thesepredicted values are in excess of what can be provided to power

aNa+ a

Na+

aNa+

aNa+

Table 1 Na+ fluxes from four studies, with predicted respiratory requirement

SpeciesNa+ flux (µmol g(root FW)−1 h−1)

Respiratory requirement(O2 consumption, µmol g(root FW)−1 h−1) Reference

Spergularia maritima 600 120 Lazof & Cheeseman (1986)Arabidopsis thaliana 300* 60 Essah et al. (2003)

Oryza sativa (japonica rice) 240* 48 Horie et al. (2007)Oryza sativa (indica rice) 107 21 Malagoli et al. (2008)

The asterisk (*) indicates influx measurements that are slightly higher than efflux; respiratory requirements are also therefore slightly higher thanactive efflux would require.

New Phytologist (2009) 183: 243–246 © The Authors (2009)www.newphytologist.org Journal compilation © New Phytologist (2009)



Letters Forum 245

such large fluxes, according to the proposed mechanisms of transport and energy transduction. We have termed this lack of correspondence ‘Ussing’s conundrum’ because it representsthe same problem faced half a century ago by Hans Ussing, apioneer of tracer-flux research (Ussing, 1947, 1994) and theco-originator of the Ussing–Teorell flux-ratio equation. Ussinghad compared theoretically active chloride fluxes and respira-

tion rates in frog epithelia, to find that the available energy wasinsufficient to account for the observed flux. He thus proposedan alternative transport mechanism, in which the flux of oneionic species in the ‘uphill’ direction is energetically coupled tothe flux of the same (or similar) ion in the ‘downhill’ direction.This concept of ‘exchange diffusion’ would later be developedinto modern ideas of ionic symport and antiport (Maloney,1994).

The discrepancy that emerges in Table 1 is scarcely lessenedif the Ussing–Teorell equation is applied to sodium fluxes. Theenergy calculations would then be based only upon the degreeto which the total flux in the active (efflux) direction exceeds

the maximum free-diffusion flux in that direction, which is afunction of cytosolic electrochemical (Dainty, 1962; White,2003). In practice, this diffusive flux can be calculated in rela-tion to influx, and to the external activity, according to theUssing–Teorell equation:

Eqn 1

(a simplified version, where φoc and φco represent influx andefflux, and a c and a o represent cytosolic and external electro-chemical activities, respectively; Teorell, 1949; Ussing, 1947;also see White, 2003, for critique). Applying values formembrane electrical potential (∼ −80 mV) and cytosolic(≤ 28 mM), both measured by Carden et al . (2003), at anexternal of 150 mM, we can calculate the electrochemicalactivity ratio (inside : outside) to be c . 28:3400 (derived firstfrom the activity ratio 28:150, which is then increased by c .22-fold as a result of the −80 mV electrical potential, accordingto the Nernst equation; see Nobel, 2005). This indicates thatvery little (< 1% of the magnitude of influx) of the efflux canbe accounted for by passive diffusion. Moreover, this quantity is further reduced by the likelihood that the proposed channel-mediated entry of Na+ is via a long pore, which exponentially

reduces the back flux through the channel (Hodgkin &Keynes, 1955; Hille, 1992).

Thus, like Ussing, we may be required to revise (if notabandon) one or more aspects of the proposed flux-energizationmodel. In Ussing’s case, the concept of energetically coupledexchange diffusion was developed to address this concern(Ussing, 1994). Although few examples of ions exchanging with others of the same ionic species exist in the plant literature(Laties, 1959; cf. Horemans et al ., 1998; Britto & Kronzucker,2003), it is not impossible that the futile cycling of Na+ occurs

by this means, perhaps via an antiporter, evolved for anotherfunction, with low selectivity for monovalent cations. Thispossibility could be investigated by testing for trans-stimulation.Since the time of Ussing’s original conundrum, the broaderconcept of ionic symport and antiport has encompassed theexchange of similar, as well as dissimilar, ions (Maloney, 1994);in the case of sodium efflux, there may be many possibilities

that have been overlooked (e.g. Na+/Cl− symport; Colmenero-Flores et al ., 2007). Indeed, the possibility that sodium exitsthe cell via processes other than Na+/H+ antiport, at least insome species, was suggested in a study of 16 crop plant species(Mennen et al ., 1990). Interestingly, much of the ground work that established Na+/H+ antiport as a leading model for Na+

efflux was conducted under low-Na+ conditions (Colombo et al .,1979; Jacoby & Teomy, 1988; Mennen et al ., 1990), whereenergetic considerations are, by comparison to the presentdiscussion, trivial. In addition, the stoichiometries of ATPhydrolysis and proton pumping may not be uniform (Baun-sgaard et al ., 1996; Low & Rausch, 1996; Morsomme et al .,

1996).More radical solutions may also have to be considered. For

instance, it may be that Na+ is not extruded via the plasmamembrane by transport proteins, but is secreted via mem-brane vesicles, as has been suggested for Na+ transport (Lazof & Cheeseman, 1986; Flowers & Colmer, 2008, and referencestherein), and more recently shown for photoassimilate (Etxe-berria et al ., 2007) and Mn2+ (Peiter et al ., 2007) transport. A still more unconventional proposal is that the majority of apparent ion fluxes exceeding the cell’s respiratory capacity arenot across the plasma membrane at all, but result from themisinterpretation of tracer accumulating in extracellular spaces,particularly in leaves, as has been demonstrated to some degreein rice plants (Flowers et al ., 1991; Gong et al ., 2006).

Acknowledgements

We wish to thank Eduardo Blumwald for helpful discussions,and the Canada Research Chair Program and the NaturalSciences and Engineering Research Council of Canada forfunding this work.

Dev T. Britto and Herbert J. Kronzucker*

University of Toronto, 1265 Military Trail, Toronto,Ontario, Canada, M1C 1A4

(*Author for correspondence:tel +1 416 287 7436; email [email protected])

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Baunsgaard L, Venema K, Axelsen KB, Villalba JM, Welling A,

Wollenweber B, Palmgren MG. 1996. Modified plant plasma membrane

aNa+

φ

φoc

co

o

c

=a

a

aNa+

aNa+




Letters Forum246

H+-ATPase with improved transport coupling efficiency identified by

mutant selection in yeast. Plant Journal 10: 451–58.

Briskin DP, Reynolds-Niesman I. 1991. Determination of H+/ATP

stoichiometry for the plasma membrane H+-ATPase from red beet (Betavulgaris L.) storage tissue. Plant Physiology 95: 242–250.

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provides evidence for the cytosolic origin of tracer in the compartmental

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Britto DT, Kronzucker HJ. 2006. Futile cycling at the plasma membrane: A hallmark of low-affinity nutrient transport. Trends in Plant Science 11:

529–534.

Carden DE, Walker DJ, Flowers TJ, Miller AJ. 2003. Single-cell

measurements of the contributions. Plant Physiology 131: 676–683.

Cheeseman JM. 1982. Pump-leak sodium fluxes in low-salt corn roots.

Journal of Membrane Biology 70: 157–164.

Colmenero-Flores JM, Martinez G, Gamba G, Vazquez N, Iglesias DJ,

Brumos J, Talon M. 2007. Identification and functional characterization

of cation-chloride cotransporters in plants. Plant Journal 50: 278–292.

Colombo R, Bonetti A, Lado P. 1979. Promoting effect of fusicoccin on Na+

efflux in barley roots: evidence for a Na+-H+ antiport. Plant, Cell & Environment 2: 281–285.

Dainty J. 1962. Ion transport and electrical potentials in plant cells. Annual Review of Plant Biology 13: 379–402.

Essah PA, Davenport RJ, Tester M. 2003. Sodium influx and accumulationin Arabidopsis thaliana. Plant Physiology 133: 307–318.

Etxeberria E, Gonzalez P, Pozueta J. 2007. Mannitol enhanced fluid-phase

endocytosis in storage parenchyma cells of celery ( Apium graveolens )petioles. American Journal of Botany 96: 1041–1045.

Flowers TJ, Colmer TD. 2008. Salinity tolerance in halophytes. NewPhytologist 179: 945–963.

Flowers TJ, Hajibagheri MA, Yeo AR. 1991. Ion accumulation in the cell

walls of rice plants growing under saline conditions – evidence for the

Oertli hypothesis. Plant, Cell & Environment 14: 319–325.

Gong HJ, Randall DP, Flowers TJ. 2006. Silicon deposition in the root

reduces sodium uptake in rice (Oryza sativa L.) seedlings by reducing

bypass flow. Plant, Cell & Environment 29: 1970–1979.

Hille B. 1992. Ionic channels of excitable membranes , 2nd edn. Sunderland,

MA, USA: Sinauer.

Hodgkin AL, Keynes RD. 1955. The potassium permeability of a giantnerve fibre. Journal of Physiology 128: 61–88.

Horemans N, Asard H, Van Gestelen P, Caubergs RJ. 1998. Facilitated

diffusion drives transport of oxidised ascorbate molecules into purified

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Horie T, Costa A, Kim TH, Han MJ, Horie R, Leung HY, Miyao A,

Hirochika H, An G, Schroeder JI. 2007. Rice OSHKT2;1 transporter

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Kronzucker HJ, Szczerba MW, Moazami-Goudarzi M, Britto DT. 2006.

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Lambers H. 1999. Relatively large nitrate efflux can account for the high

specific respiratory costs for nitrate transport in slow-growing grass species.

Plant and Soil 215: 123–134.Shi HZ, Ishitani M, Kim CS, Zhu JK. 2000. The Arabidopsis thalianasalt

tolerance gene SOS1 encodes a putative Na+/H+ antiporter. Proceedings of the National Academy of Sciences, USA 97: 6896–6901.

Teorell T. 1949. Membrane electrophoresis in relation to bioelectrical

polarization effects. Archives des Sciences Physiologiques 3:

205–219.

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muscle. Nature 160: 262–263.

Ussing HH. 1994. Does active transport exist? Journal of Membrane Biology 137: 91–98.

Wang C-M, Zhang J-L, Liu X-S, Li Z, Wu G-Q, Cai J-Y, Flowers TJ, Wang

S-M. 2009. Puccinellia tenuiflora maintains a low Na+ level under salinity

by limiting unidirectional Na+ influx resulting in a high selectivity for K +

over Na+. Plant, Cell & Environment (in press; DOI: 10.1111/j.1365-

3040.2009.01942.x) White PJ. 2003. Ion transport. In: Thomas B, Murphy DJ, Murray BG, eds.

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sodium transport, transport energetics, Ussing–Teorell equation.288110.1111/j.1469-8137.2009.02881.xMay200900??????LetterLetter

Letter Letter

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Questions about floral(dis)integration

Successful pollen dispersal requires complex interactions forpollen to be loaded from flowers onto a pollen vector and then

be deposited on stigmas as the vector subsequently encountersother flowers. These interactions involve many floral andinflorescence traits, so that coordination of their functionsshould promote pollen dispersal, leading to the hypothesisthat angiosperm flowers are functionally integrated organs(reviewed by Armbruster et al ., 2004). Several specializedpollination systems, such as heterostyly, secondary pollenpresentation, and the fusion of anther(s) and stigma(s) intothe orchid column and asclepiad gynostegium, provide obviousexamples of floral integration, but what is the evidence forgeneral integration? This question has been examined foralmost 50 years (Berg, 1960), but with inconsistent results

(reviewed by Armbruster et al ., 2004; see Ashman & Majetic,2006, for results based on genetic correlations), and variationin the extent of floral integration within angiosperms remainspoorly understood. In this context, the recent article by Ordano et al . (2008) in New Phytologist , reporting a survey of 55 studies of floral integration, is of particular interest. Basedon this survey, they concluded that ‘flowering plants havelower floral integration ... than expected by a randomly generated distribution’ (page 1189), a finding clearly at odds with the integration hypothesis. However, certain aspects of Ordano et al .’s analysis seem inappropriate and I demonstratehere that correction of this problem leads instead to strongevidence that flowers are usually integrated.

The studies surveyed by Ordano et al . (2008) used thepopulation variance of eigenvalues, V (λ ), from principal-components analyses of floral traits as an index of floralintegration. In such an analysis, all eigenvalues will equal one when the m traits are uncorrelated (not integrated), resultingin a minimum variance of zero; whereas, if all traits are perfectly,positively correlated (highly integrated), the first eigenvalue would equal m, the number of variables, and the remainingeigenvalues would equal zero, resulting in the maximum possiblevariance (which coincidentally equals m numerically). Togenerate their random ‘null’ distribution, Ordano et al .calculated the integration index for simulated samples based

on trait correlations ‘randomly chosen from a uniform prob-ability distribution’ (page 1186) and found that the average‘expected’ integration index was 32.7% (SD = 8.5%) of themaximum possible. Use of a uniform distribution proposesthat when traits are uncorrelated strong correlations occur asoften as weak correlations, owing solely to sampling error. Forproduct–moment correlations, which are used in most studiesof floral integration, such a uniform distribution is appropriateonly for samples of four observations (Stuart & Ord, 1987).By contrast, the null distribution of product–moment corre-

lations approaches a normal distribution as the sample sizeincreases (Stuart & Ord, 1987), so strong correlations shouldoccur rarely for studies with reasonable samples when the null

hypothesis is true. As a result of their use of a uniform distri-bution of correlations, Ordano et al .’s simulations shouldgenerally have overestimated the expected integration indexfor randomly associated traits.

I illustrate this problem with the results from two sets of 1000 simulations for n = 30 observations of m = 5 traits: oneusing a uniform distribution of correlation coefficients; andthe other based on the null distribution of product–momentcorrelation coefficients. The mean integration index forsimulations based on uniform correlations is 26.7% of the

Fig. 1 Frequency distributions of (a) 1000 simulated integration

indices based on trait correlations drawn randomly from a uniformdistribution (white bars), as modeled by Ordanoet al. (2008), or fromthe distribution of product–moment correlation coefficients (greybars), and (b) observed integration indices for 36 species(summarized by Ordano et al., 2008). The vertical dashed linesindicate the mean for each distribution. For (a) each simulated samplerepresented 30 observations of five variables and the true populationcorrelation for both parent distributions was 0: variation resultedsolely from sampling error.




Letters Forum248

maximum possible (Fig. 1a, white histogram) and of themagnitude of the results of Ordano et al ., which were basedon varying numbers of traits and observations. By contrast,the mean integration index based on the null distribution of product–moment correlations was an order of magnitudesmaller, at 2.76% of the maximum (Fig. 1a, grey histogram).This outcome is consistent with the prediction of 100(m – 1)/

mn = 2.67%, based on the expected variance of eigenvaluesfor product–moment correlations when the null hypothesis istrue (Wagner, 1984; also see Chevrud et al ., 1989: note thatthis expectation approaches an asymptotic maximum of 100/n as the number of traits considered increases).

In light of these results, the average integration index of 21.5% (SD = 15.4%), observed for 36 plant species in 16families in the survey of Ordano et al . (Fig. 1b), indicates, incontrast to their conclusion, that flowers are much more highly integrated than expected based on random trait correlations.Indeed, over 80% of the observed integration indices exceedthe maximum null simulation based on product–moment

correlations (compare grey histograms in Fig. 1a,b), indicatingthat floral integration is the rule, rather than the exception.Thus, rather than questioning whether flowers are integrated,attention should now focus on the causes of the extensivevariation in integration (Fig. 1b) and its reproductiveconsequences.

Lawrence D. Harder

Department of Biological Sciences, University of Calgary,Calgary, Alberta, Canada T2N 1N4

(Author for correspondence: tel +1 403 2206489;email [email protected])

References

Armbruster WS, Pélabon C, Hansen TF, Mulder CPH. 2004.

Floral integration, modularity, and precision: distinguishing complex

adaptations from genetic constraints. In: Pigliucci M, Preston K, eds.

Phenotypic integration: studying the ecology and evolution of complex phenotypes . New York, NY, USA: Oxford University Press,

23–49.

Ashman T-L, Majetic CJ. 2006. Genetic constraints on floral evolution: a

review and evaluation of patterns. Heredity 96: 343–352.

Berg RL. 1960. The ecological significance of correlation pleiades.Evolution

14: 171–180.

Chevrud JM, Wagner GP, Dow MM. 1989. Methods for the comparative

analysis of variation patterns. Systematic Zoology 38: 201–213.Ordano M, Fornoni J, Boege K, Domínguez CA. 2008. The adaptive value

of phenotypic floral integration. New Phytologist 179: 1183–1192.

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quantitative character variation. Journal of Mathematical Biology 21:

77–95.

Key words: eigenvalue variance, floral integration, floral morphology, null

distribution, pollination.291110.1111/j.1469-8137.2009.02911.xMay 200900??????LetterLetter

Letter Letter

Phenotypic integration:between zero and how muchis too much

The hypothesis that flowers constitute mechanical devicesdesigned by natural selection to ensure pollen donation/reception through the concerted action of a suite of correlated(integrated) traits is an appealing and broadly accepted idea(Bell, 1985). Two questions derive from this hypothesis. Thefirst is whether flowers are, in fact, integrated modules. Moststudies evaluating this question have found significant levelsof floral integration and a marked heterogeneity amongspecies (Armbruster et al ., 1999, 2004; Pérez et al ., 2007;Pérez-Barrales et al ., 2007; Ordano et al ., 2008). Thus, theavailable evidence already indicates that flowers are indeedintegrated (Ordano et al ., 2008). A different, but equally

relevant, question is whether or not flowers exhibit relatively high levels of phenotypic integration. Because in most plantspecies flower functioning depends on the interaction betweenfloral and pollinator morphologies, it has been suggested thatflowers should have relatively high levels of phenotypicintegration (Stebbins, 1950, 1970; Faegri & van der Pijl, 1966).Obviously, responses to these two questions require differentapproaches and rely on distinct biological reasons.

In his letter to New Phytologist , Harder (2009; this issue,pp. 247–248) argues that our conclusion that floweringplants have lower floral integration than expected by arandomly generated distribution (Ordano etal ., 2008, p. 1189)is flawed because of the inappropriateness of our analysis.He further concluded that: ‘floral integration is the rule, ratherthan the exception’. While we agree with his general conclusionregarding the ubiquity of floral integration, we believe that hiscriticism is based on confusing the two questions presentedabove. Accordingly, the disagreement presented by Harder(2009) merits a thorough discussion of these two questions.In doing so, we attempt to clarify possible sources of mis-interpretation in the paper by Ordano et al . (2008).

Question 1. Are flowers integrated?

Since the seminal work of Berg (1960), evidence has

accumulated supporting the expectation that flowers areintegrated modules (Armbruster et al ., 1999, 2004; Pérezet al ., 2007; Pérez-Barrales et al ., 2007; Ordano et al ., 2008),a pattern observed for other functional modules in animaltaxa (Wagner et al ., 2007; Pavlicev et al ., 2009). By using theobserved distribution of integration values reported by Ordanoet al . (2008), and the statistical approach developed by Wagner (1984) and Cheverud et al . (1989), Harder’s analysesconfirmed that flowers are significantly integrated. The nullhypothesis used by Harder (2009) is that of no correlation among




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characters, and thus any integration level above the expectedvalue, given by the sampling error E (V (λ )) = ( M − 1)/N , wouldindicate that a correlation matrix is significantly integrated(Cheverud et al ., 1989). Because the average integration valueobserved among flowering plants was 21.5% (Ordano et al .,2008), and the expected value obtained by Harder (2009) wasonly 2.76%, the null hypothesis is readily rejected (sampling

error obtained from an approximated normal distribution of product–moment correlation coefficients). Accordingly, Harder’sexercise (2009) just confirmed previous results supporting theexpectation that flowers express significant levels of phenotypicintegration. Moreover, we agree that the use of a uniformdistribution of product–moment correlation coefficients todetermine whether a given level of integration is significantly different from zero is not a valid procedure. So far, theseresults add to the mounting evidence showing that flowers,and many other functional modules in several organisms,express significant levels of integration.

Question 2. Do flowers have high levels of floralintegration?

Harder’s (2009) test evaluates whether a group of traits areindeed integrated, but it does not tell us if the magnitude of integration is low or high. In addition to the presence/absencequestion, one could also ask whether the special case of plant–pollinator interactions really favoured the evolution of highlevels of phenotypic integration. The natural history of plantsand pollinators is full of examples showing that efficientpollen transfer depends on the interaction between flower andpollinator morphologies (Faegri & van der Pijl, 1966; Fenster

et al ., 2004). Accordingly, answering if flowers are highly

integrated modules requires a different null hypothesis fromthat used for testing question 1. In this sense, Ordano et al .(2008) looked for the appropriate null distribution that shouldbe used to determine whether an observed level of integration was relatively low or high. To this end, Ordano et al . (2008)built an expected distribution of integration values based onrandomly generated correlation matrices. These matrices, inturn, were obtained from randomly sampling product–momentcorrelation coefficients (ranging from −1 to 1). This procedureensures that low, intermediate and high values have the sameprobability of being selected. Integration values were thencalculated for each matrix (Wagner, 1984) and were used to

build the expected distribution of integration. Such a distributionis centred on the average expected (significant) value of integration for a random association of independent correlationcoefficients. Consequently, testing question 2 would determine whether a given integration value corresponds to a lower levelor a higher level than that expected by chance. In fact, theexpected distribution of integration values obtained by Ordanoet al . (2008) can be used for any other functional module todetermine what level of integration can be considered as low or high. A couple of examples suggests that there is a huge

variation in the magnitude of integration. For instance,integration levels as high as 77.16% have been found for the wing in the northern goshawk ( Accipiter gentilis ; Pavlicev et al ., 2009), while that of the fruit of Prunus persica is 21.79%(Badenes et al ., 1998). Other modules, like the facial skull of papionins, can range from 33.33% in Papio cynocephalus to18.33% in Macaca nemestrina (Cheverud, 1989). Thus, the

low level of integration found among flowering plants may not be an exception.

Overall, we agree with Harder (2009) in that floral integra-tion is the rule. Having taken this position, we must also takeanother. Demonstrating that flowers are integrated organsdoes not mean that they are highly integrated. The analyses inOrdano et al . (2008) were intended to test question 2 andconcluded that flowers have relatively low levels of floralintegration, rejecting the expectation that flowers are highly integrated organs. Thus, besides understanding the causes of variation in the levels of floral integration, floral evolutionary biologists could go forward in exploring why flowers are

apparently little integrated (Fornoni et al ., 2008).

Juan Fornoni1, Mariano Ordano2, Karina Boege1

and César A. Domínguez 1*

1Departamento de Ecología Evolutiva, Instituto de Ecología,Universidad Nacional Autónoma de México, Apartado Postal

70-275, C.P. 04510, México Distrito Federal, México;2Centro de Investigaciones sobre Regulación de Poblaciones

de Organismos Nocivos (CIRPON), Fundación MiguelLillo, Pasaje Caseros 1050, T4001MVD, San Miguel de

Tucumán, Tucumán, Argentina (*Author for correspondence:tel +52 55 5622 9039; email: [email protected])

References

Armbruster WS, Di Stilio VS, Tuxill JD, Flores TC, Velásquez-Runk JL.

1999. Covariance and decoupling of floral and vegetative traits in nine

neotropical plants: a re-evaluation of Berg’s correlation pleiades concept.

American Journal of Botany 86: 39–55.

Armbruster WS, Pélabon C, Hansen TF, Mulder CPH. 2004.

Floral integration, modularity, and accuracy: distinguishing complex

adaptations from genetic constraints. In: Pigliucci M, Preston K, eds.

Phenotypic integration: studying the ecology and evolution of complex phenotypes . New York, NY, USA: Oxford University Press, 23–49.

Badenes ML, Martínez-Calvo J, Llacer G. 1998. Estudio comparativo

de la calidad de los frutos de 26 cultivares de melocotonero de origennorteamericano y dos variedades población de origen español.

Investigación Agraria, Producción y Protección Vegetales (INIA España) 13:

57–70.

Bell GB. 1985. On the function of flowers. Proceedings of the Royal Society of London B 224: 223–265.

Berg RL. 1960. The ecological significance of correlation pleiades.Evolution

14: 171–180.

Cheverud JM. 1989. A comparative analysis of morphological variation

patterns in the Papionins. Evolution 43: 1737–1747.

Cheverud JM, Wagner GP, Dow MM. 1989. Methods for the comparative

analysis of variation patterns. Systematics Zoology 38: 201–213.




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Faegri K, van der Pijl L. 1966. The principles of pollination ecology . Oxford,

UK: Pergamon Press.

Fenster CB, Armbruster WS, Wilson P, Thomson JD, Dudash MR. 2004.

Pollination syndromes and floral specialization. Annual Review of Ecology,Evolution and Systematics 35: 375–403.

Fornoni J, Boege K, Domínguez CA, Ordano M. 2008. How little is too

little? The adaptive value of floral integration. Communicative & Integrative Biology 1: 56–58.

Harder LD. 2009. Questions about floral (dis)integration. New Phytologist 183: 247–248.

Ordano M, Fornoni J, Boege K, Domínguez CA. 2008. The adaptive

value of phenotypic floral integration. New Phytologist 179:

1183–1192.

Pavlicev M, Cheverud JM, Wagner GP. 2009. Measuring morphological

integration using eigenvalue variance. Evolutionary Biology 36: 157–170.

Pérez F, Arroyo MTK, Medel R. 2007. Phylogenetic analysis of

floral integration in Schizanthus (Solanaceae): does pollination truly

integrate corolla traits? Journal of Evolutionary Biology 20:

1730–1738.

Pérez-Barrales R, Arroyo J, Armbruster WS. 2007. Diffferences in

pollinator faunas may generate geographic differences in floral

morphology and integration in Narcissus papyraceus (Amaryllidaceae).

Oikos 116: 1904–1918.

Stebbins GL. 1950. Variation and evolution in plants . New York, NY, USA:

Columbia University Press.

Stebbins GL. 1970. Adaptive radiation of reproductive characteristics in

angiosperms, I: pollination mechanisms. Annual Review of Ecology and

Systematics 1: 307–326. Wagner GP. 1984. On the eigenvalue distribution of genetic and phenotypic

dispersion matrices: evidence for a nonrandom organization of

quantitative character variation. Journal of Mathematical Biology 21:

77–95.

Wagner GP, Pavlicev M, Cheverud JM. 2007. The road to modularity.

Nature Review Genetics 8: 921–931.

Key words: correlation matrix, floral morphology, modularity, phenotyic

evolution, phenotypic integration.290610.1111/j.1469-8137.2009.02906.xMay200900??????MeetingReportMeetings

Meetings

Meetings

Gearing up for comparativegenomics: analyses of thefungal classDothideomycetes

Dothideomycetes Comparative Genomicssession: 25th Fungal Genetics Conference, PacificGrove, CA, USA, March 2009

The Fungal Genetics Conferences, held biannually on thegrounds of the Asilomar Conference Center in Pacific Grove,CA, USA, are the premier gatherings for fungal geneticists world-wide. This year’s conference, the 25th (http://www.fgsc.net/25thFGC/FGC25.htm), provided four very full daysof talks, workshops and posters for almost 1000 participants.Fungi exceed every other kingdom of Eukaryotes in the numberof genomic sequences completed or in progress. With this rich

resource of available sequences, the focus is now switching fromanalyses of single genomes to comparative analyses acrossmultiple genomes as a way to understand fungal biology andthe interactions of fungi with plants.

Fungi in the class Dothideomycetes are leading the way,and a full concurrent session was devoted to DothideomycetesComparative Genomics. This subject was chosen because theDothideomycetes is one of the largest and most importantgroups of fungi that collectively infect almost every majormonocot and dicot crop, whether for food, feed, fiber or fuel.

In addition to plant pathogens, the class includes fungi withan unparalleled ecological, life history and metabolic diversity.Dothideomycetes are present on every continent, including Antarctica (Selbmann et al ., 2005), and are important toecosystem health and global carbon cycling as saprophytes anddegraders of plant biomass. Many are lichenized (Del Pradoet al ., 2006) or are otherwise tolerant of environmental extremes

including heat, cold and humidity (Ewaze et al ., 2007). Someproduce enzymes that help degrade rocks while others cancapture and metabolize ethanol vapors (Tribe et al ., 2006). A few are pathogens of humans or livestock. Cladosporium her-barum and Alternaria alternataare ubiquitous colonizers of dead plant biomass that play an important role in globalcarbon cycling, but in addition they are the two most commonly detected human allergens and a leading cause of asthma(Gioulekas et al ., 2004). Thus, Dothideomycetes are extremely important to human as well as plant health.

With seven Dothideomycetes genomes sequenced from theorders Capnodiales and Pleosporales (Table 1) and more onthe way, a critical mass for comparative analysis has been

achieved. The purpose of the Dothideomycetes ComparativeGenomics session was to highlight recent progress on com-parative analyses of this group. Talks were selected fromsubmitted abstracts because they presented new tools for high-throughput functional analysis that could be applied to othersequenced genomes, or used a comparative genomics approachto reveal new insights into the biology of these fungi. MostDothideomycetes are plant pathogens, and understandinghow they interact with their plant hosts was a major focus of the session.

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Genetic analysis of Cochliobolus sativus

Shaobin Zhong (North Dakota State University, Fargo, ND,USA) began the session with a talk on new tools for genomicanalyses of Cochliobolus sativus (asexual stage: Bipolaris soro-kiniana), a pathogen that causes kernel blight, root rot andseedling blight of barley (Hordeum vulgare ), wheat (Triticum

aestivum) and other grasses. It also causes spot blotch, a very important foliar disease in the northern USA and in tropicalenvironments of Southeast Asia. Genetic and genomic toolsare being developed for unraveling the pathogenicity of thisfungus, which is highly specialized into several races onbarley. Genetic mapping and pulsed-field gel electrophoresisidentified the genomic locations for single factors controllingthe virulence of the fungus in barley and wheat, which arenow being pursued through map-based cloning strategies.Techniques for transformation and RNA-mediated genesilencing were developed for functional analyses that will helpto pin down the virulence factors once a genomic sequence

becomes available. This is an up-and-coming system withgreat potential for elucidating host–pathogen interactions inthe Dothideomycetes.

Tools for functional analysis in the Pleosporales

Salim Bourras (INRA-Bioger, Versailes, France) moved thefocus to high-throughput tools for functional analysis of Leptosphaeria maculans , the black leg fungus of canola (Brassicanapus ) and other Brassicaceous crops. This fungus alternatesnecrotrophic and biotrophic growth within a field season.The genome sequence has approximately 12 000 genes buttheir density varies with position between gene-poor, AT-richregions (with 1 gene per 29 kb) and GC-equilibrated isochorescontaining one gene approximately every 2.4 kb. To assignfunction to these genes, Agrobacterium tumefaciens -mediatedtransformation (ATMT) was developed to generate a large

mutant library. The number of targeted genes was 279, of which 169 have an assigned function. Forty-three genes wererecovered that potentially were involved in pathogenicity.The program will be extended and validated with similar largeinsertional-mutant libraries that are available for the rice blastpathogen, Magnaporthe oryzae , and should help to elucidate themechanisms by which L. maculans interacts with its Brassica hosts.

High-throughput mutant generation by ATMT was furtherelaborated by Carrie Smith (Oklahoma State University, Still- water, OK, USA) working on Phoma medicaginis , a pathogenthat causes a defoliating leaf spot of alfalfa ( Medicago sativa)in large areas of the USA and also infects the model legume

Medicago truncatula. This fungus is asexual and readily formsconidia in pycnidia on artificial media as well as on host plants. ATMT was used to generate an insertional-mutant library andidentify genes involved in pathogenicity. Over 1000 mutants were generated (0.03% efficiency) and 10 were selected foran in-depth analysis. Several mutants with insertions in hypo-thetical proteins had obvious, visible phenotypes such as cracked

pycnidia or lack of melanization. One mutant had fluffy, whitehyphae that produced no pycnidia or conidia, while one withan insertion in a poly-A RNA polymerase gene produced smalland few pycnidia and had reduced pathogenicity. This gene was similar to caffeine-induced death (Cid) genes in Schizosac-charomyces pombe . Homologs were identified in the Dothideo-mycetes Stagonospora nodorum and Pyrenophora tritici-repentis . With a sequenced host genome and an efficient T-DNA taggingsystem, P. medicaginis is poised to become an important organismfor the analysis of Dothideomycetes–host interactions.

Tools for comparative genomics analysis

The development of tools for comparative analysis has laggedbehind the accumulation of genomic sequence data. To addressthis problem, The Joint Genome Institute ( JGI) of the USDepartment of Energy (DOE) has pioneered a unique approach

Table 1 Sequence resources available currently for comparative analyses of Dothideomycetes genomes

Species Order CoverageGenomesize (Mb) Resources

Alternaria brassicicola Pleosporales 6.4× 30.3 Washington University (http://genome.wustl.edu/genome.cgi?GENOME=Alternaria%20brassicicola)

JGI (jgi.doe.gov/Abrassicicola)Cochliobolus heterostrophus Pleosporales 10.0× 34.9 JGI (http://jgi.doe.gov/Cochliobolus) Mycosphaerella fijiensis Capnodiales 7.1× 73.4 JGI (http://jgi.doe.gov/Mfijiensis) Mycosphaerella graminicola Capnodiales Finished 39.7 JGI (http://jgi.doe.gov/Mgraminicola)Pyrenophora tritici-repentis Pleosporales 6.9× 37.8 Broad (http://www.broad.mit.edu/annotation/genome/

pyrenophora_tritici_repentis.3/Info.html)JGI (http://jgi.doe.gov/Ptritici_repentis)

Stagonospora nodorum Pleosporales > 10× 37.2 Broad (http://www.broad.mit.edu/annotation/genome/stagonospora_nodorum.2/Home.html)JGI (http://jgi.doe.gov/Snodorum)

JGI, The Joint Genome Institute.

No claim to original US government works New Phytologist (2009) 183: 250–254 Journal compilation © New Phytologist (2009) www.newphytologist.org

http://genome.wustl.edu/

http://jgi.doe.gov/Cochliobolus

http://jgi.doe.gov/Mfijiensis

http://jgi.doe.gov/Mgraminicola

http://www.broad.mit.edu/annotation/genome/pyrenophora_tritici_repentis.3/Info.html

http://jgi.doe.gov/Ptritici_repentis

http://www.broad.mit.edu/annotation/genome/stagonospora_nodorum.2/Home.html

http://jgi.doe.gov/Snodorum

http://jgi.doe.gov/Snodorum

http://www.broad.mit.edu/annotation/genome/stagonospora_nodorum.2/Home.html

http://jgi.doe.gov/Ptritici_repentis

http://www.broad.mit.edu/annotation/genome/pyrenophora_tritici_repentis.3/Info.html

http://jgi.doe.gov/Mgraminicola

http://jgi.doe.gov/Mfijiensis

http://jgi.doe.gov/Cochliobolus

http://genome.wustl.edu/



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to software development by asking communities of users torequest new tools that are directly needed to further theirresearch. Andrea Aerts (DOE-JGI, Walnut Creek, CA, USA)presented the JGI annotation pipeline for Dothideomycetesgenomes. To support the JGI mission of community anno-tation, six Dothideomycetes genomes (Table 1) are currently available on their web portal, including three that were sequenced

outside JGI and, in addition, they have organized on-siteannotation jamborees to facilitate whole-genome annotation.The annotation pipeline comprises repeat masking, datamapping, gene prediction, annotation and validation, andculminates in public release of the data. Functional categoriesaccording to GO (Gene Ontology), KOG (euKaryotic OrthologousGroups) and KEGG (Kyoto Encyclopedia of Genes andGenomes) assignments can be browsed for each genome, whichprovides an excellent tool for comparative genomics analyses.Side-by-side analysis of all six genomes facilitates rapid andefficient comparisons, and it is simple to switch from onespecies to another. An overview of all browsers, synteny, VISTA

(http://genome.lbl.gov/vista/index.shtml) conservation andprotein cluster viewers was provided, demonstrating theexcellent support that the JGI provides to the Dothideomycetescommunity. VISTA conservation tracks for all Dothideo-mycetes genomes and the synteny viewer allow syntenicrelationships to be identified and analyzed efficiently. The DotPlot viewer readily showed the differences between essentialand dispensable chromosomes of the Mycosphaerella graminicolagenome. These new tools provide an excellent resource forthe Dothideomycetes research community and also should beuseful for comparative genomics analyses in other organisms,including plants.

Effectors shared among species

Several talks were related to the finished genome of the septoriatritici blotch fungus of wheat, Mycosphaerella graminicola, orthe draft sequence of its close relative, the banana black Sigatoka (or leaf streak) pathogen, Mycosphaerella fijiensis .Ioannis Stergiopoulos (Wageningen University, The Netherlands)reported on a comparative study between M. fijiensis andCladosporium fulvum (syn.: Passalora fulva), a nonobligate,biotrophic pathogen of tomato (Solanum lycopersicum) andreference organism for host–pathogen interactions. To date,10 effectors have been identified from C. fulvum. All are

small, cysteine-rich proteins that are secreted into the apoplastand whose recognition in tomato is mediated by cognate Cf (for C. fulvum) resistance proteins. Although demonstratedfor only a few, all of the effector proteins are assumed to bevirulence factors (Stergiopoulos & De Wit, 2009). So far nohomologs of the C. fulvum effectors had been identified inother fungi, and thus they were considered to be speciesspecific. However, a careful search in the genome sequence of

M. fijiensis , based on a combination of comparative genomicsand structural analysis, identified putative homologs for

at least three of the C. fulvum effectors, two of which arealso present in M. graminicola and other Dothideomycetes.Based on these findings, the current hypothesis is that closely related pathogens share some effectors that are most probably inherited from a common ancestor and are adapted tospecific host plants. This is the first report on effectorsshared among pathogens of such widely divergent hosts,

suggesting that similar strategies might have been employedby related plant pathogens that infect unrelated host plants.These results have led to a new model for effectoromics, in which related Dothideomycetes fungi share a set of commoneffectors that facilitate colonization of many different hostspecies, but have diverged for other effectors that enable hostspecialization.

Mycosphaerella graminicola to the fore

Sarrah Ben M’Barek (Plant Research International, Wageningen,The Netherlands) presented the current status of the M. grami-

nicola sequence analysis, the first finished genome of afilamentous fungus. High-density linkage mapping with over2000 sequenced markers enabled a perfect alignment of thegenetic map with the genome sequence over all 21 chromo-somes. Genome plasticity in this fungus was evident frompolymorphisms in chromosome length and number. Meiosis,in contrast to mitosis, frequently generates chromosome numberpolymorphisms (CNPs), particularly for chromosomes 14–21. These chromosomes are missing frequently in progeny with no visible effect on viability or virulence and appear tobe dispensable (Wittenberg et al ., in press). Comparativegenomic hybridizations using a NimbleGen (Roche NimbleGenInc., Madison, WI, USA) whole-genome array confirmed theorigin of CNPs. The dispensable chromosomes are smaller,have lower gene densities, have a higher density of transposonsand contain many unclassified genes that could code for novelproteins. They also contain a high number of redundantcopies of genes that are unique on the essential chromosomes.For example, extra copies of tubulin genes on the dispensablechromosomes appeared to be pseudogenes compared withthose on the essential chromosomes. The JGI browsers(described by Andrea Aerts) enabled high-resolution self-synteny analyses showing that the dispensable chromosomesare a mosaic of redundant blocks of virtually all other chro-mosomes. However, the synteny with other Dothideomycetes

such as Stagonospora nodorum and M. fijiensis is extremely low. The presence of eight dispensable chromosomes is uniquefor fungi. However, their function is unknown and will be thesubject of future analyses.

Braham Dhillon (Purdue University, West Lafayette, IN,USA) continued analyses of the M. graminicola genome withresearch on the amplification and apparent inactivation of agene for cytosine methylation. Analysis of the repetitive frac-tion of the genome identified a family of 28 repeats, 23 of which contained a region similar to a DNA methyltransferase

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(DNMT) gene. All copies except for one were located near thetelomeres, with the remaining copy on chromosome 6. TheDNMT gene was single copy in nine other fungal genomesand, based on syntenic relationships identified by a compar-ative analysis with the genome sequence of M. fijiensis , thecopy on chromosome 6 probably was the original beforeamplification. Interestingly, all copies of the DNMT gene,

including the putative original on chromosome 6, showedevidence of repeat-induced point mutation (RIP), a mecha-nism in fungi for inactivating transposons by introducing stopcodons into reading frames. Tests for methylation showedthat M. graminicola lacks cytosine methylation, even thoughit was present in close relatives. Accidental amplification followedby RIP appears to be a novel mechanism for inactivation of single-copy genes in fungi.

In the final talk of the session, Eva Stukenbrock (University of Aarhus, Aarhus, Denmark) reported on the putative geneticbasis of speciation in Mycosphaerella based on comparativegenomics. A previous analysis of sequence data had shown very

recent divergence times among M. graminicola, two undescribednew species from wild grasses in Iran and the somewhat moredistantly related barley pathogen, Septoria passerinii (Stuken-brock et al ., 2007). Therefore, genomic comparisons with

M. graminicola could reveal evolutionary changes that occurredduring speciation. Resequencing one of these related speciesrevealed two haplotypes in the mitochondrial sequences, indi-cating the first possible report of heteroplasmy in the Dothide-omycetes. The nuclear genome sequence was very similar andshowed a high degree of synteny with the essential chromo-somes 1–13 of the finished genome of M. graminicola. Incontrast, synteny with the dispensable chromosomes 14–21 was considerably lower. Regions of repetitive DNA correlated well with nonaligned DNA except for the eight dispensablechromosomes of M. graminicola, probably as a result of their higher content of transposons. A browser developed forcomparative genomics showed a significant difference in theratio of substitutions in both coding and noncoding DNA of the essential and dispensable chromosomes, suggesting thatthey have different evolutionary patterns. In particular, the ratioof nonsynonymous to synonymous substitutions (dN/dS) was markedly higher on the dispensable chromosomes, givinga strong indication of possible directional selection.

Perspectives As more genomes are sequenced, the potential power of comparative analyses increases. Being able to search completegenomes for homologs of interesting genes has revealed new insights into the evolution of effectors and the genes ondispensable chromosomes, and has also revealed a potentially new mode of inactivation of an otherwise single-copy gene.Estimates of selection on all genes in an organism will identify those that are under directional selection and might be involvedin host–pathogen interactions and speciation. The power of

these analyses to illuminate host–pathogen interactions willincrease greatly once genome sequences also are available forthe host plants. The future of comparative genomics isincreasingly bright. The recent session on DothideomycetesComparative Genomics provided a first small hint of what isto come as more fungal and plant genomes are sequenced.

Acknowledgements

We thank Francine Govers and Jay Dunlap for programmingthe Dothideomycetes Comparative Genomics session of the25th Fungal Genetics Conference, and Andrea Aerts, SarrahBen M’Barek, Salim Bourras, Braham Dhillon, Carrie Smith,Ioannis Stergiopoulos, Eva Stukenbrock, and Shaobin Zhongfor speaking at the session and for verifying a previous draft of this report.

Stephen B. Goodwin1* and Gerrit H. J. Kema 2

1USDA-ARS, Crop Production and Pest Control ResearchUnit, Department of Botany and Plant Pathology, 915 West

State Street, Purdue University, West Lafayette, IN 47907-2054, USA; 2Plant Research International B.V., Wageningen

University and Research Centre, P.O. Box 16, 6700 AA Wageningen, The Netherlands (*Author for correspondence:tel +1 (765) 494-4635; email [email protected] or

[email protected])

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Molecular data place Trypetheliaceae in Dothideomycetes. Mycological

Research 110: 511–520.Ewaze JO, Summerbell RC, Scott JA. 2007. Physiological studies of the

warehouse staining fungus, Baudoinia compniacensis . Mycological Research 111: 1422–1430.

Gioulekas D, Damialis A, Papakosta D, Spieksma F, Giouleka P, Patakas

D. 2004. Allergenic fungi spore records (15 years) and sensitization in

patients with respiratory allergy in Thessaloniki-Greece. Journal of Investigational Allergology & Clinical Immunology 14: 225–231.

Selbmann L, de Hoog GS, Mazzaglia A, Friedmann EI, Onofri S. 2005.

Fungi at the edge of life: cryptoendolithic black fungi from Antarctic

desert. Studies in Mycology 51: 1–32.

Stergiopoulos I, De Wit PJGM. 2009. Fungal effector proteins. Annual Review of Phytopathology 47: 233–263.

Stukenbrock EH, Banke S, Javan-Nikkhah M, McDonald BA. 2007.

Origin and domestication of the fungal wheat pathogen Mycosphaerella

graminicola via sympatric speciation. Molecular Biology and Evolution 24:398–411.

Tribe HT, Thines E, Weber RWS. 2006. Moulds that should be better

known: the wine cellar mould, Racodium cellare Persoon. Mycologist 20:

171–175.

Wittenberg AHJ, van der Lee TAJ, Ben M’Barek S, Ware SB, Goodwin SB,

Kilian A, Visser RGF, Kema GHJ, Schouten HJ. (in press). Meiosis drives

extraordinary genome plasticity in the haploid fungal plant pathogen

Mycosphaerella graminicola. PLoS One .

Keywords: comparative, Dothideomycetes, fungi, genetics, genomics, host–

pathogen interactions, tools.

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