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Nonhost Resistance of Barley to Different FungalPathogens Is Associated with Largely Distinct,Quantitative Transcriptional Responses1[W][OA]

Nina Zellerhoff2,3, Axel Himmelbach2, Wubei Dong4, Stephane Bieri,Ulrich Schaffrath, and Patrick Schweizer*

Institute of Plant Physiology, Rheinisch-Westfalische Technische Hochschule Aachen University, 52056Aachen, Germany (N.Z., U.S.); Leibniz-Institute of Plant Genetics and Crop Plant Research, 06466Gatersleben, Germany (A.H., W.D., P.S.); and BASF Plant Science GmbH, Agrarzentrum Limburgerhof,67117 Limburgerhof, Germany (S.B.)

Nonhost resistance protects plants against attack by the vast majority of potential pathogens, including phytopathogenic fungi.Despite its high biological importance, the molecular architecture of nonhost resistance has remained largely unexplored. Here,we describe the transcriptional responses of one particular genotype of barley (Hordeum vulgare subsp. vulgare ‘Ingrid’) to threedifferent pairs of adapted (host) and nonadapted (nonhost) isolates of fungal pathogens, which belong to the genera Blumeria(powdery mildew), Puccinia (rust), and Magnaporthe (blast). Nonhost resistance against each of these pathogens was associatedwith changes in transcript abundance of distinct sets of nonhost-specific genes, although general (not nonhost-associated)transcriptional responses to the different pathogens overlapped considerably. The powdery mildew- and blast-induceddifferences in transcript abundance between host and nonhost interactions were significantly correlated with differencesbetween a near-isogenic pair of barley lines that carry either theMlowild-type allele or the mutated mlo5 allele, which mediatesbasal resistance to powdery mildew. Moreover, during the interactions of barley with the different host or nonhost pathogens,similar patterns of overrepresented and underrepresented functional categories of genes were found. The results suggest thatnonhost resistance and basal host defense of barley are functionally related and that nonhost resistance to different fungalpathogens is associated with more robust regulation of complex but largely nonoverlapping sets of pathogen-responsive genesinvolved in similar metabolic or signaling pathways.

Nonhost resistance usually is defined as durableresistance of all known genotypes of a plant species toall known races or isolates of a pathogen species.Although this definition does not cover all knowncases of nonhost resistance that can also operate at thesubspecies level, such as formae speciales (f. sp.) ofBlumeria graminis, it reflects a low level of genotypedependence on the efficiency of resistance. Despite itsextreme importance for natural plant populations as

well as its promises for agriculture, nonhost resistanceis only beginning to be better understood and remainswidely unexploited in agricultural practice to date(Ellis, 2006; Schweizer, 2007). The analysis of mutantsof Arabidopsis (Arabidopsis thaliana) has led to theidentification of several genes that contribute to non-host resistance against the barley powdery mildewfungus B. graminis f. sp. hordei (Bgh; Collins et al., 2003;Lipka et al., 2005; Stein et al., 2006). These results led tothe hypothesis of multilayered nonhost resistance inplants, with the plant cell wall being the first and rapidcell death the second line of defense. In wild-typeplants, inappropriate pathogens to which Arabidopsisis a nonhost are usually stopped at the preinvasivestage of penetration. This penetration resistance isassociated with the formation of large cell wall appo-sitions (papillae) enriched in callose, lignin-like mate-rial, and hydrogen peroxide. Upon breaching of thisfirst defense layer, pathogen growth is stopped by ahypersensitive reaction of attacked cells, which isassociated with autofluorescence and a hydrogen per-oxide burst and which leads to cell death (Schweizer,2007). Recently, it has been shown that genes ofArabidopsis identified to play an important role innonhost resistance against powdery mildews alsocontribute to resistance against nonhost rust fungisuch as Phakopsora pachyrhizi (Loehrer et al., 2008).

1 This work was supported by the German Ministry of Educationand Research (PRO-GABI to P.S. and S.B.) and by the Peter undTraudl Engelhorn-Stiftung (grant to N.Z.).

2 These authors contributed equally to the article.3 Present address: Botanical Institute, University of Cologne,

Albertus-Magnus-Platz, 50923 Cologne, Germany.4 Present address: College of Plant Science and Technology,

Huazhong Agricultural University, Wuhan City, Hubei Province,430070 People’s Republic of China.

* Corresponding author; e-mail [email protected] author responsible for distribution of materials integral to the

findings presented in this article in accordance with the policydescribed in the Instructions for Authors (www.plantphysiol.org) is:Patrick Schweizer ([email protected]).

[W] The online version of this article contains Web-only data.[OA] Open Access articles can be viewed online without a sub-

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Plant Physiology�, April 2010, Vol. 152, pp. 2053–2066, www.plantphysiol.org � 2010 American Society of Plant Biologists 2053

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Despite progress made in the model plant Arabidop-sis, one of the main obstacles to a better understandingof the genes and pathways underlying nonhost resis-tance is the lack of genetically tractable systems seg-regating for this type of resistance, which oftenoperates at the species level.

Barley (Hordeum vulgare subsp. vulgare) has beenreported to be a nonhost to the wheat powdery mil-dew (PM) fungus B. graminis f. sp. tritici (Bgt), thewheat leaf rust (Rust) fungus Puccinia triticina (Ptrit),and isolate CD180 (CD) from the genus Magnaporthe(Mag) that is associated with the host Pennisetumspecies (Tosa and Shishiyama, 1984; Hoogkampet al., 1998; Zellerhoff et al., 2006). In all three nonhostsystems, the incompatibility appears to be basedmostly on the first layer of defense (i.e. penetrationresistance; Hoogkamp et al., 1998; Trujillo et al., 2004;Zellerhoff et al., 2006). This highly effective nonhostresistance contrasts sharply with the susceptibility ofmany barley genotypes (such as cv Ingrid selected forthis study) to the corresponding appropriate hostpathogens of the same genera, such as Bgh, Pucciniahordei (Phor), and Magnaporthe oryzae (TH). In thenonhost interactions of barley with inappropriaterust fungi, a better understanding of the genetic basisof nonhost resistance was achieved recently by accu-mulating susceptibility alleles in a series of consecu-tive crosses, which resulted in two barley lines withessentially full susceptibility to nonhost rusts (Atienzaet al., 2004). Segregation analysis of a progeny resultingfrom crosses between “normal” nonhost-resistant par-ents and one of the new nonhost-susceptible lines ledto the identification of a number of quantitative traitloci for nonhost resistance (Jafary et al., 2006). How-ever, the map position of these quantitative trait locivaried greatly depending on (1) the nonhost rustspecies and (2) the genotype of the nonhost-resistantparent. It was concluded, therefore, that nonhost resis-tance, at least to rust fungi, might depend on a complexand functionally redundant set of genes in barley.

Here, we describe the transcriptional responses ofbarley during host/nonhost interactions with three

different fungal pathogens that all share a lifestylewith at least an initial biotrophic phase but that differin the mode of penetration and the leaf tissue they feedfrom. The powdery mildew pathogens Bgh and Bgtexclusively attack epidermal tissue and, in the case ofhost susceptibility, grow on the leaf surface, wherethey sporulate abundantly approximately 5 d afterinitial host contact. The rust fungi Ptrit and Phor exclu-sively attack mesophyll tissue, and compatible isolatesgrow in themesophyll until theybreach the epidermis inorder to release urediniospores. The blast fungi CD andTH first attack the leaf epidermis and, in susceptibleinteractions, invade the underlying mesophyll approx-imately 48 h after initial host contact. While powderymildews and rust are biotropic fungi, blast is consideredas a hemibiotroph. Thus, blast grows on susceptiblehosts in the first penetrated epidermal cell without anysign of cell death, which in turn is caused by the releaseof toxins during mesophyll colonization. The resultsprovide a comparative view of transcriptional eventsthat are associated with nonhost resistance in barley.

RESULTS

Experimental Setup for Transcript Profiling

Three pairs of host-nonhost interactions were usedfor this study (Table I). The time range for the analysiswas selected in order to study the initial phases of theinteractions until the completion of conditioning to-ward accessibility or resistance. All experiments wereplanned in a nonrandomized split-plot design, asshown in Supplemental Figure S1. For the interactionsof barley with Mag and Rust, peeled abaxial epidermisand the entire leaf were used for RNA isolation, respec-tively. For the interaction with PM, peeled epidermisand the remaining leaf tissue containing approximately75% of nonpeeled epidermis were collected separately.

Transcript Profiling

For the study presented here, the in-house-producedbarleyPGRC1 macroarray carrying 10,450 spotted

Table I. Pairs of host/nonhost interactions of fungal pathogens with barley analyzed

Pathogen Genus

(Abbreviation)Pathogen Species (Abbreviation) Host Genus Invaded Shoot Tissue Interaction Type (Reference)

Magnaporthe (Mag) M. grisea (CD)a Pennisetum Epidermis/mesophyll Hemibiotrophic(Zellerhoff et al., 2006)

M. oryzae (TH) Oryza, Hordeum, and other Epidermis/mesophyll Hemibiotrophic(Zellerhoff et al., 2006)

Blumeria (PM) B. graminis f. sp. tritici (Bgt) Triticum Epidermis Biotrophic(Trujillo et al., 2004)

B. graminis f. sp. hordei (Bgh) Hordeum Epidermis Biotrophic(Trujillo et al., 2004)

Puccinia (Rust) P. triticina (Ptrit) Triticum Mesophyll Biotrophic(Hoogkamp et al., 1998)

P. hordei (Phor) Hordeum Mesophyll Biotrophic(Hoogkamp et al., 1998)

aPutative novel Magnaporthe species isolated from Pennisetum (Zellerhoff et al., 2006).

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cDNA features was used (Schweizer, 2008). This arraywas enriched in cDNAs from powdery mildew-attacked epidermis and, therefore, well suited forthe type of experiments presented here. It also con-tains approximately 2,000 spotted unigenes (nonre-dundant EST singletons or contigs) from attackedepidermis that are not represented by a communityresource, the Barley1 genome chip (Close et al., 2004)from Affymetrix. However, the design of the arraydid not cause any bias for signal detection in leafepidermis only and was therefore as well suited forinoculation experiments with PM that grows in theepidermis as for experiments with Rust that growsexclusively in inner leaf tissue (Supplemental Fig. S2).Technical replication experiments, as shown in Sup-plemental Figure S3A, revealed a high degree of datareproducibility. We also hybridized probes frombiological replicates onto different barleyPGRC1macroarray membranes or onto the Barley1 chip(Supplemental Fig. S3, B and C). The correlation ofthe identified gene regulation events induced by Bghattack in barley leaf epidermis was similar in both theintraplatform and the interplatform comparisons.This demonstrates the suitability of the barleyPGRC1array for the detection of gene regulation events uponpathogen attack.Barley plants for inoculation with PM, Mag, or Rust

were grown under different conditions, which wereadapted for each interaction (for details, see “Materialsand Methods”). In order to estimate the influence ofthe different growth chamber or greenhouse environ-ments on the overall transcriptome, a principal com-ponent analysis (PCA) of samples from noninoculatedcontrol plants was performed (Supplemental Fig. S4).This showed that tissue type had the largest effect(PC1 explaining 56% of variation). The epidermalsamples for Mag and PM inoculations clustered to-gether with respect to PC1 (tissue type), whereas theywere separated by PC2. This separation might indicatethe effect of the mock treatment for Mag inoculation(spray with detergent-containing solution). Entire-leafsamples were more similar according to PC2 butshowed some shift along the PC1 axis, although withconsiderable overlap between PM and Rust experi-ments. Because of the shift of entire-leaf control sam-ples along the PC1 axis, we also performed PCA of theregulation factors of transcript abundance of all spot-ted unigenes on the array, not only the ones exhibitingstatistically significant regulation by pathogen inocu-lations. This approach was expected to give a robustestimation of the overall comparability of pathogen-induced transcriptional changes because, per patho-system, approximately 40% of the spotted unigenesshowed a pathogen-induced change in transcriptabundance by a factor of at least 1.5 (data not shown).PCA of the regulation factors showed that PM- andRust-inoculated leaf samples clustered together atspecific time points, indicating comparability of over-all transcriptional responses in the two pathosystems(Supplemental Fig. S5). This conclusion is supported

by the analysis of overlap of significantly regulatedgenes between PM and Rust (see below).

Over all analyzed pathosystems, a total of 1,686spotted features (PCR products) of the barleyPGRC1cDNA array produced differential signals by a factorof at least 2.0 between control and inoculated samples,with a q value of q , 0.05 corresponding to a false-discovery rate of less than 5%. These spotted featurescorrespond to 1,667 unigenes, because some werespotted as duplicates from independent PCRs at dif-ferent positions on the array for control purposes. Atotal of 93 spotted features of the EST library “HO,”which were found to produce signals exclusively inPM-inoculated samples, were eliminated from theanalysis. These were likely to represent fungal tran-scripts, because the HO library was prepared fromPM-inoculated leaf epidermis. The fungal identities ofmost of the 93 removed feature sequences were con-firmed using BLAST (data not shown). The remainingeliminated unigenes did not result in significantBLAST results to sequences from any organism andwere removed because fungal origin could not beexcluded. A complete list of unigenes correspondingto differentially accumulating transcripts upon patho-gen attack can be found in Supplemental Table S1.

PCA of the 1,667 unigenes that correspond to dif-ferentially accumulating transcripts in response topathogen attack revealed a major influence of tissuetype (PC1 explaining 59% of variation) followed bytreatment effects (14% of data variation; Fig. 1). In bothepidermis and entire leaf samples, the correspondinghost/nonhost pairs of interactions induced similarchanges in transcript profiles that resulted in similarshifts of sample mean values along the axes of the twocomponents. In the epidermis, attack by TH or CDinduced fewer transcriptional changes at early timepoints during the (pre)penetration phase of the fun-gus, whereas in entire leaf samples, attack by Rustfungi induced fewer changes at the latest time pointanalyzed (48 h after inoculation), demonstrating thetransient nature of the transcriptional response even inthe susceptible interaction. This suggests that Magproduced fewer pathogen-associated molecular pat-terns (PAMPs) that were perceived by barley duringthe early interaction compared with PM, whereas Phormight have suppressed defense responses efficientlyby effector molecules as soon as first haustoria wereestablished. Similar to our observations, a remarkablylow number of pathogen-regulated genes were ob-served early during the interaction of rice (Oryzasativa) with Mag (99 out of 21,500 analyzed genes;Vergne et al., 2007). Very little information is currentlyavailable for barley-Rust interactions without clearevidence for strong suppression of defense gene ex-pression during compatible interactions (Neu et al.,2003).

Transcriptional changes induced by two pairs ofadapted and nonadapted pathogens were analyzed inthe epidermis and entire leaf, respectively, and werecompared within each pair and between pairs. For this

Nonhost Resistance of Barley

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purpose, the overlap of transcripts fulfilling the statis-tical criterion for differential accumulation (greaterthan 2-fold change in transcript abundance betweencontrol and corresponding treatment with q , 0.05)was compared, as shown in Figure 2. The host andnonhost blast fungi (Mag) induced transcriptionalchanges in barley epidermis that overlapped con-siderably with the responses to PM: approximately15% of PM-regulated and approximately 40% of Mag-regulated genes were responding to attack by bothpathogens (Fig. 2B). An even higher degree of overlap(approximately 42% of Rust-regulated and 70% ofPM-regulated genes) was found in entire leaf samplesresponding to either PM or Rust, despite the factthat the inner leaf tissues, which contributed to ap-proximately 95% of extracted RNA (Zierold et al.,2005), were in direct contact with the Rust fungi butresponded only indirectly to PM, whose developmentis restricted to the epidermis. Thus, the two obligatebiotrophic pathogens PM and Rust affected the barleytranscriptome in a more similar way compared withPM and Mag. In contrast, the overlap of the nonhost-specific transcriptional responses was clearly less be-tween the different pathogens (Fig. 2, gray areas andcolumns).

Effect of the Nonhost Status on

Transcriptional Responses

In order to identify those transcripts that mightaccumulate differentially during host and correspond-ing nonhost interactions, inoculated samples fromresistant nonhost interactions and the matching inoc-

ulated samples from corresponding susceptible hostinteractions were compared in a pairwise mannerusing the set of 1,667 genes with significantly patho-gen-regulated transcript abundance (see above). Thisresulted in the identification of 70 and 195 differen-tially accumulating transcripts in the epidermis dur-ing host and nonhost Mag and PM interactions,respectively, that met the chosen significance thresh-olds (P , 0.05 and q , 0.1; Supplemental Table S2).During Rust interactions, no significant transcript dif-ferences between host and nonhost interactions werefound, despite the fact that the initial Venn analysissuggested the existence of interaction-specific differ-ences also upon attack by these pathogens (data notshown). Thus, tissue complexity of the whole-leafsamples and the corresponding complex overlap oftissue-specific transcriptional profiles may have pre-vented the identification of significant interaction-specific differences that may be quantitative ratherthan qualitative. This interpretation was confirmed bythe analysis of interaction-specific differences betweenBgh- and Bgt-attacked whole-leaf samples. In contrastto the above-mentioned 195 identified unigenes inepidermis, only four differentially accumulating tran-scripts were identified in whole-leaf samples (data notshown). This demonstrates the importance of usingpeeled epidermis as a method to reduce biologicalcomplexity for the identification of rather subtle effectson the barley transcriptome. Figure 3 shows the resultsof a hierarchical clustering of interaction-specific tran-scripts during the interactions of barley epidermiswith Mag or PM fungi. From this type of analysis, itbecame clear that both nonhost interactions were

Figure 1. PCA of transcript profiles of different plantinoculations and tissues. Mean values from three tofour biological replicates of the 1,667 unigenescorresponding to differentially accumulating tran-scripts upon pathogen attack were used for theanalysis. The clusters of noninoculated samples(from mock-inoculated or nontreated, control plants)are highlighted by gray shading. PC1 and PC2 reflecttissue type and treatment (inoculation), respectively.h, Hours after inoculation. For abbreviations of path-ogens, see Table I.

Zellerhoff et al.




characterized by a stronger up- or down-regulation oftranscript levels compared with corresponding hostinteractions.The observed, more pronounced up- or down-

regulation of transcript levels during nonhost inter-actions in the epidermis was in agreement with thehigher number of statistically significant gene regula-tion events during nonhost interactions with Bgt andCD, as compared with host interactions with Bgh andTH (Fig. 2A). Such quantitative changes can also bedisplayed by calculating the differential index (DI) oftranscript abundance. DI of host versus nonhost inter-actions is defined as

DI ¼ StðIntnonhost 2 InthostÞ=StðIntnonhost þ InthostÞ(where t = time post inoculation and Int = normalizedsignal intensity) and provides an integrative, robust,and normalized measure of differences in the abun-dance of individual transcripts. DI varies between21 and 1, whereas the lowest and highest values areobtained if a transcript is only detected during the host

and nonhost interaction, respectively. Using DI, amajor quantitative effect of the mlo resistance alleleon the host transcriptome of PM-attacked barley epi-dermis was previously described (Zierold et al., 2005).Figure 4 shows that DI of most up-regulated, interac-tion-specific transcripts (Fig. 3; Supplemental Table S2)was positive, which means that they are triggered to ahigher abundance during the nonhost interaction. Onthe other hand, DI was mostly negative in the case ofgenes with down-regulated transcript abundance,which means that the expression of these was re-pressed more strongly during the nonhost interaction.Therefore, attack by the inappropriate Bgt or CDisolates induced higher amplitudes of transcriptionalchanges compared with the corresponding host inter-actions. A selection of unigenes associated with abso-lute DI values larger than 0.2 and 0.3 for Mag and PMinteractions, respectively, is shown in Table II.

The analysis of overlapping gene sets suggestsstrong differences in the transcriptional response todifferent nonhost pathogens (Fig. 2). This, however,does not exclude the possibility that among the geneswith significantly regulated transcript levels in re-sponse to both pathogen genera of a specific compar-ison (inside the thick border lines in Fig. 2A), similarquantitative differences between host and nonhostinteractions exist, which would be reflected in a sim-ilar distribution of DI values. Therefore, we analyzedthe correlation of DI values of PM, Mag, and Rustinteractions. As shown in Table III, there was a highlysignificant positive correlation of DI between PMinteractions in the epidermis and entire leaf samples,suggesting a similar, (non)host-specific response of thedifferent tissues to PM attack. By contrast, no correla-tion of DI values was found by comparing PM-to-Magand PM-to-Rust interactions in the epidermis andentire leaf samples, respectively. In agreement withthis observation, only four of 195 and 70 nonhost-marker transcripts of the PM and Mag interaction,respectively, were overlapping, and these four tran-scripts showed opposite regulation trends (Supple-mental Table S2). In conclusion, the nonhost status ofbarley for the different fungal pathogens was reflectedby clearly distinct signatures of the transcriptionalresponse.

Regulation of Functional Groups of Genes

Are levels of transcripts belonging to specific func-tional groups of genes preferentially up- or down-regulated in response to attack by host or nonhostpathogens? This question was addressed using therecently introduced binning system ofMapMan Barley(Sreenivasulu et al., 2008). Here, only the uppermostlevel of functional categories (superbins) was consid-ered, because otherwise, unigene numbers per binwere too low for x2 analysis. Figure 5 shows thatseveral functional categories were significantly over-represented or underrepresented among the groups ofgenes with pathogen-regulated transcript levels. Over-

Figure 2. Nonhost resistance of barley to fungal pathogens is associ-ated with largely nonoverlapping sets of pathogen-responsive tran-scripts. A, Venn diagram of transcripts differentially regulated duringthe interaction of barley with PM and Mag (left panel) or with PM andRust (right panel). Transcripts regulated by both pathogen genera areshown inside the thick frame. The set of transcripts regulated in anonhost-specific manner by the two genera are highlighted by grayshading. For abbreviations of pathogens, see Table I. B, The overlap oftranscripts (relative to one or the other pathogen as specified below thecolumn) that were generally regulated during interactions with PM andMag in the epidermis or with PM and Rust in entire leaf samples (whitebars) was compared with the overlap found with transcripts regulatedspecifically during nonhost-resistant interactions.





represented among genes with up-regulated transcriptabundance were “Amino acid metabolism,” “Redoxregulation, ascorbate, glutathione,” “Stress,” “Trans-port,” and “Miscellaneous.” Braking down superbinMiscellaneous into specific bins (Supplemental Fig. S6)revealed that more than 75% of the contained unigenesbelong to pathogenesis-related or stress-related multi-gene families. It seems, therefore, that superbin Mis-cellaneous represents the basal response of barley todifferent pathogens. Superbin “Photosynthesis” wasoverrepresented in a highly significant manner amongthe genes with down-regulated transcript levels,suggesting a shift of the leaves away from photosyn-thetic carbon assimilation to defense. One strikingdifference between the different pathogens was thehighly significant overrepresentation of superbin“Lipidmetabolism” inMag-induced transcripts, whereasan overrepresentation of superbin Amino acid metab-olism was seen during PM and Rust interactions.Comparing the transcripts specifically changed in

abundance during nonhost interactions and the onesresponding to both host and nonhost pathogens, wefound no obvious differences in the overrepresenta-tion or underrepresentation of functional categories.However, because numbers of nonhost-specific geneswere generally lower, the statistical power of analysiswas also reduced, thereby providing indicative ratherthan statistically significant results. Despite this limi-tation, two functional categories of genes with down-regulated transcript levels were identified that weresignificantly overrepresented either during host ornonhost Rust interactions. First, “Major CHO metab-olism,” including starch and major carbohydratemetabolic enzymes, was more prominently down-regulated during the nonhost interaction with Ptrit.The significant overrepresentation of Major CHO me-tabolism during the nonhost-resistant Rust interactionis paralleled by the observation that, in Bgt-attackedepidermis, several genes of this functional categoryhad more strongly down-regulated transcript levels

Figure 3. Differentially regulated transcripts be-tween host and nonhost interactions. A hierarchicalclustering of pathogen-regulated transcripts was per-formed that showed a significant (P , 0.05, q , 0.1)quantitative difference of expression in leaf epider-mis between Bgh and Bgt or between TH and CD. Pertime point and treatment, mean values of signalintensities from three to four biological replicateswere calculated, and Pearson correlation with com-plete linkage of log2-transformed, median-centeredmean signal intensities was applied for the clustering.Color code is as follows: blue, down-regulation;yellow, up-regulation.

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(Table II). Second, during the interaction with Phor,genes belonging to “Minor CHO metabolism,” includ-ing biosynthetic enzymes of secondary cell wall build-

ing blocks such as hemicelluloses, were found to besignificantly overrepresented among genes withdown-regulated transcript abundance. Therefore, thisfungus might cause specific repression of the expres-sion of genes encoding biosynthetic enzymes of sec-ondary cell wall or other minor carbohydrates, whichmight facilitate the penetration of mesophyll cells.

In summary, during the interactions of barley withdifferent pairs of host or nonhost pathogens, com-mon metabolic or signaling pathways appeared to beactivated or inactivated, without a clear differencebetween generally pathogen-responsive and nonhost-specific sets of genes.

DISCUSSION

This is a comparative study to describe the tran-scriptional responses of a particular barley genotype tothree pairs of host/nonhost pathogens causing theimportant diseases of powdery mildew, rust, and blaston cereals. Although the barleyPGRC1 cDNA arrayused for this purpose represents not more than ap-proximately 25% of the estimated complexity of thebarley transcriptome, its complexity was sufficient fora comparative and statistical analysis of global trendsof gene expression between the different pathosys-tems. Moreover, the barleyPGRC1 array carries ap-proximately 2,000 unique sequences not representedby the Barley1 genome chip (Affymetrix) and wasfound to be specifically well suited for studying plant-pathogen interactions in epidermal tissue (Gjettinget al., 2007).

When comparing gene expression within each host/nonhost pair of pathogens by PCA and by pairwiseanalysis, it became clear that barley did not activatefundamentally different responses depending on thehost or nonhost status of the interactions (Figs. 1 and3). Rather, a complex quantitative difference of thetranscriptional response was revealed using DI as asensitive measure for differences of transcript abun-dance between inoculated samples from host andnonhost interactions (Fig. 4). However, during PMand Mag interactions, 195 and 70 unigenes possesseddifferent transcript abundance when comparing sam-ples from Bgh- versus Bgt-inoculated and TH- versusCD-inoculated epidermis, respectively (Table II; Sup-plemental Table S2). Unigenes of these subsets associ-ated with absolute DI values larger than 0.2 and 0.3 forMag and PM interactions, respectively, are brieflydiscussed here. Four of the most prominently accu-mulating marker transcripts for the nonhost interac-tion with CD encode lipid transfer proteins, furthersupporting an important, defense-related role of thisprotein family in barley (Molina and Garcia-Olmedo,1997) that is also impacting malt quality and plays arole as a major food allergen (Broekaert et al., 1997;Breiteneder and Mills, 2005; Stanislava, 2007). Amongthe genes with more strongly down-regulated tran-script levels during CD interaction are four chloro-

Figure 4. Stronger regulation of transcript abundance in nonhost-resistant interactions. Distribution of the DI for the interaction-specificmarker transcripts identified in barley epidermis (according to Supple-mental Table S2) is shown. The transcripts were grouped according tothe regulons highlighted in Figure 3. DI values of genes with up-regulated or down-regulated transcript abundance (black or whitesymbols, respectively) were sorted in decreasing order. Positive DIvalues of genes with up-regulated transcript abundance indicate astronger transcript accumulation during nonhost interactions, whereasnegative DI values of genes with down-regulated transcript abundancereflect stronger repression of gene expression during nonhost interac-tions. Absolute DI values of 0.2 and 0.3 correspond to 1.5- and 2-foldaverage differences, respectively, of transcript abundance between hostor nonhost interactions.





phyll a/b-binding proteins. Because barley epidermisis known to be mostly devoid of chlorophyll (exceptfor stomatal cells), these signals might represent minorcontamination of the epidermal samples by adheringmesophyll cells, detected due to the very high abun-

dance of the corresponding transcripts. This assump-tion is supported by the finding that transcript levelsof three of the four genes encoding chlorophyll a/b-binding proteins were also down-regulated upon PMattack in entire leaf samples (data not shown). There-

Table II. Selection of transcripts showing most differential accumulation between host andnonhost interactions

Clone

IdentifieraFungus Regulation DIb Descriptionc E Value

HO02B01 Mag Up 0.333 Lipid transfer protein CW18 3E-44HK03J16 Mag Up 0.287 Lipid transfer protein CW18 2E-44HO07G08 Mag Up 0.259 Cytochrome P450 4E-57HK05F10 Mag Up 0.252 Lipid transfer protein LTP4.1 2E-41HT02A21 Mag Up 0.241 No matchHK06L05 Mag Up 0.241 No matchHY06N01 Mag Up 0.233 DNA mismatch repair

protein MUS12E-90

HF01C09 Mag Up 0.229 Hypothetical 4E-18HS02P06 Mag Up 0.229 Lipid transfer protein LTP4.3 2E-36HT01F03 Mag Up 0.229 Ascorbate peroxidase 6E-98HK05P10 Mag Up 0.219 No matchHV01H13 Mag Up 0.204 (2R)-Phospho-3-sulfolactate

synthase-like2E-42

HE01E12 Mag Down 20.200 Chlorophyll a/b binding protein 1E-66HG01I24 Mag Down 20.219 Chlorophyll a/b binding protein 6E-83HG01J16 Mag Down 20.227 Glycolate oxidase 2E-58HO01P12 Mag Down 20.230 Translation elongation factor 1 2E-51HO14N05 Mag Down 20.235 Hypothetical 8E-48HO03H17 Mag Down 20.237 Hypothetical 6E-74HE01N10 Mag Down 20.263 Chlorophyll a/b binding protein 3E-95HO04A04 Mag Down 20.264 Cytochrome P450 8E-82HP01O18 Mag Down 20.277 Chlorophyll a/b binding protein 1E-15HO04K12 PM Up 0.746 Hypothetical 1E-25HO02D11 PM Up 0.653 Protein kinase 1E-15HO14L23 PM Up 0.586 Hypothetical 1E-48HO01P09 PM Up 0.559 Actin-related protein 3 4E-84HO03N06 PM Up 0.521 No matchHO07E03 PM Up 0.519 Polyubiquitin 9E-92HD03B05 PM Up 0.395 No matchHO14N21 PM Up 0.378 Heat shock 70 1E-81HH01C09 PM Up 0.327 Anthranilate

phosphoribosyltransferase1E-103

HO11G24 PM Up 0.305 Regulatory protein 4E-89HD02J12 PM Up 0.304 No matchHF02G02 PM Up 0.303 Suppressor-like protein 1E-35HM02P05 PM Down 20.301 CBL-interacting protein kinase 3E-69HW04K16 PM Down 20.303 Hexokinase 1E-22HM02B07 PM Down 20.307 Vacuolar H+-transporting

ATP synthase2E-83

HK03O23 PM Down 20.329 Ribosomal protein 4E-14HT01J17 PM Down 20.333 No matchHI02A12 PM Down 20.333 Drought-inducible protein 1OS 1E-29HV01H05 PM Down 20.334 Cathepsin B 1E-123HM03K01 PM Down 20.349 6-Phosphogluconolactonase 5E-45HT01D06 PM Down 20.351 Suc synthase 1E-127HI04I23 PM Down 20.412 No match

aSelection of unigenes with significantly up- or down-regulated transcript abundance upon pathogenattack that also exhibited significant differences between host and nonhost interactions. bUnigenesassociated with an absolute DI value larger than 0.2 and 0.3 duringMag and PM interactions, respectively,were selected. cBased on BLASTX against the NRpep database (National Center for BiotechnologyInformation).

Zellerhoff et al.




fore, photosynthesis in leaf mesophyll might be morestrongly suppressed during the nonhost interactionwith CD than during the compatible interaction withTH, which points at a role of a senescence-relateddefense program (Buchanan-Wollaston et al., 2003).During the nonhost interaction with Bgt, many tran-scripts encoding unknown or hypothetical proteinsaccumulatedmore strongly. In addition, genes with up-regulated transcript abundance encoding polyubiquitin,an actin-related protein, as well as anthranilate phos-phoribosyltransferase were markers of nonhost resis-tance, in agreement with suggested functions ofprotein ubiquitination, actin reorganization, and aro-matic amino acid synthesis in basal defense of barleyto PM (Dong et al., 2006; Miklis et al., 2007; Hu et al.,2009). Among the marker genes of nonhost resistanceto Bgt with down-regulated transcript abundancewere three genes of major carbohydrate metabolismencoding Suc synthase, 6-phosphogluconolactonase,and a mitochondrial hexokinase. This might indicateselective reduction of cellular homeostasis, whichshifts cells to a predisposition to execute a programmedcell death upon further stimuli. Indeed, in the caseof mitochondrial hexokinase, silencing was recentlyshown to induce programmed cell death in tobacco(Nicotiana tabacum; Kim et al., 2006). The relevanceof the individual barley genes belonging to the host/nonhost-specific regulons remains to be further exam-ined by direct functional assays or by genetic approaches.In the barley-PM system, a single-cell transient assay forgene silencing is available to test corresponding hypoth-eses in high throughput (Douchkov et al., 2005). In theMag pathosystem, different approaches, such as virus-induced gene silencing, TILLING, and stable RNAinterference, would be required in order to directly ad-dress gene function (Holzberg et al., 2002; Himmelbachet al., 2007; Weil, 2009).When comparing gene sets with significantly altered

transcript levels between the different pathosystems,we found a much higher overlap of genes that weregenerally pathogen responsive compared with thosewhose transcript levels only changed during nonhost-resistant interactions (Fig. 2). The lower overlap ofsignificantly regulated transcript levels during non-host interactions was in agreement with the low orabsent correlation between DI values of the genes that

were responding to the different host/nonhost pairs ofpathogens (Table III). This phenomenon becomes veryclear when comparing the overlap of genes betweenPM and Rust in entire leaf samples: more than 70% ofgenes responding to PM were also responding to Rustfungi, but only 14% of Bgt-responsive genes were alsoresponding to Ptrit inoculation. Thus, the nonhoststatus of one barley genotype to three different path-ogens was reflected by largely nonoverlapping, quan-titative transcriptional responses.

We also addressed the question of which transcriptssignificantly changed in abundance during all threecompatible host interactions. This revealed six and 24transcripts with down- and up-regulated levels, re-spectively (Supplemental Table S3). While most of thegenes with down-regulated transcript abundance werenot assigned to a known function, the up-regulatedgroup included members involved in sugar, aminoacid, and phosphate mobilization and transport pro-cesses, whichmight indicate cooption of the correspond-ing genes by the successful host pathogens for nutrientuptake. In addition, transcripts of jasmonate and eth-ylene biosynthesis genes and of pathogenesis-relatedgenes such as peroxidases, glutathione S-transferase,and proteinase inhibitors were induced, reflecting ageneral stress response of the colonized tissue.

Using the MapMan tool of barley (Sreenivasuluet al., 2008), we analyzed meta-trends of the transcrip-tional response in the different host/nonhost pairs ofinteractions and found a number of significantly over-represented or underrepresented functional transcriptcategories. This revealed an astonishingly similar pat-tern of activated or repressed pathways or cellularresponses in barley responding to the different path-ogens, irrespective of their genus or host/nonhoststatus. One of the most pronounced, overrepresentedcategories of genes with up-regulated transcript levelsencoded for proteins of amino acid metabolism. Break-ing down of the superbin revealed that most of theencoded enzymes were involved in amino acid syn-thesis and that about 50% of those were synthesizingaromatic or sulfur-containing amino acids (data notshown). This probably reflects the fact that shikimate-derived amino acids such as Trp and Phe are impor-tant precursors of defensive compounds such as indolealkaloids, monolignols, and lignin-like materials andconfirms previous reports on transcript profiling andgene silencing in Bgh-attacked barley (Matsuo et al.,2001; Caldo et al., 2004; Hu et al., 2009). The enhancednumber of genes with up-regulated transcript abun-dance encoding Met and Cys may reflect an enhancedrequirement of attacked tissues for activated methylgroups as cofactors for biosynthetic pathways and/orreduced sulfhydryl groups in order to control cellularredox status. Interestingly, amino acid metabolismappears not to be stimulated in Mag-attacked barley.This might suggest that papilla formation and cellwall lignification are not the most abundant defensemechanisms in Mag-attacked barley, although fluores-cent papillae occurred frequently at penetration sites

Table III. Dissimilarity of transcript profiles of barley duringdifferent host/nonhost pairs of interactions

Comparison r a P b nc

DI Mag epidermisversus DI PM epidermis

0.141 0.1508 105

DI PM epidermisversus DI PM leaf

0.410 ,0.0001 245

DI PM leafversus DI Rust leaf

0.075 0.136 393

aPearson r. bTwo-sided test for significant deviation of slope fromzero. cNumber of unigenes corresponding to differentially accu-mulating transcripts in both interactions to be compared.





(Zellerhoff et al., 2006). Instead, a strong overrepre-sentation of accumulating transcripts involved in lipidmetabolism was characteristic for this interaction,thereby separating the barley-Mag from the two otherinteractions and providing a first clue to the higherimportance of lipid(-like) molecules in stress signalingor defense of barley epidermis attacked by blast fungicompared with PM. Several of the correspondingtranscripts encode lipid transfer proteins (Supplemen-tal Table S1), which might indicate that lipid metabo-lism is a key step in basal defense of plants against thispathogen. Moreover, signaling by cutin monomers ascuticle breakdown products might be important, be-cause Cutinase2 has been shown to be involved invirulence of the fungus and because cutin monomerswere found to induce genes in rice encoding lipidtransfer proteins that enhanced resistance in trans-genic rice to Mag upon overexpression (Patkar andChattoo, 2006; Skamnioti and Gurr, 2007; Kim et al.,2008c). Perception of cutin monomers by several plantspecies including barley has been reported previously

(Schweizer et al., 1996a, 1996b; Park et al., 2008).Noteworthy, analysis with a reporter gene constructfused to the promoter of a LTP1 gene in rice has shownthat its expression is restricted to the lesion, suggestiona role of LTPs in the establishment of a physical barrier(Guiderdoni et al., 2002). Genes with up-regulatedtranscript abundance of superbin “RNA” were under-represented, and this effect was statistically significantin entire leaf samples. Most transcripts within thissuperbin encode transcription factors, suggesting thatmost relevant transcription factors are regulated post-translationally in pathogen-attacked barley.

Upon pathogen attack, host plants perceive PAMPs,leading to the initiation of a PAMP-triggered immu-nity response (Jones and Dangl, 2006). Pathogen ef-fectors have been found to subsequently quench thisresponse, thereby reestablishing host susceptibility. Inseveral plants including barley, Mlo genes have beenidentified as negative regulators of PAMP-triggeredimmunity, and nonfunctional alleles of Mlo causeenhanced PAMP-triggered immunity, resulting in

Figure 5. Different pathogens induce similar changes in signaling or metabolic pathways. Statistical significance of theoverrepresentation or underrepresentation of regulated transcripts belonging to a specific functional transcript category wascalculated relative to the entire cDNA array (x2 test). Superbin nomenclature was taken from Sreenivasulu et al. (2008). Pink andred bars indicate genes with up-regulated transcript abundance; light and dark green bars indicate genes with down-regulatedtranscript abundance. Statistical significance is indicated with asterisks: * P , 0.05, ** P , 0.005, *** P , 0.0005. AA, Aminoacid; Asc, ascorbate; CHO, carbohydrate; epi, epidermis; Gluth, glutathione; n.a., not analyzed; OPP, oxidative pentosephosphate; PR, pathogenesis related. For abbreviations of pathogens, see Table I.

Zellerhoff et al.




strong and durable resistance (Buschges et al., 1997;Consonni et al., 2006). Several lines of evidence pointto a functional link of strong PAMP-triggered hostimmunity against Bgh mediated by recessive mlo al-leles and nonhost resistance to inappropriate PMisolates (Trujillo et al., 2004; Humphry et al., 2006;Schweizer, 2007). These observations support the hy-pothesis that, in many cases, nonhost resistance isactually a manifestation of PAMP-triggered immunity,which is inefficiently suppressed by nonhost patho-gens because these secrete nonadapted effectors thatwere specifically shaped during coevolution to fittargets of their corresponding host. Accordingly, non-host resistance based on this mechanism is expectedto be robust and durable. We tested the hypothesisthat nonhost resistance shares similarity with PAMP-triggered immunity by performing transcript profilingexperiments in a near-isogenic pair of barley differingin the allelic status of theMlo gene (Ingrid [Mlo] versusIngrid BC mlo5) and by comparing the distribution ofDI values between pathogen-regulated transcript setsin barley exhibiting either nonhost resistance or strongPAMP-triggered immunity mediated by themlo5 allele(for 684 transcripts differentially regulated by Bghin the epidermis of Ingrid BC mlo5, see SupplementalTable S1). As shown in Table IV, there was indeed ahighly significant correlation between DI values ofthe PM-responsive transcriptome of nonhost resistantplants and near-isogenic host plants differing in theabsence/presence of the mlo5 resistance gene. Thissupports the view that nonhost resistance to PMin barley is mechanistically related to mlo-mediatedhost resistance. Interestingly, a highly significant cor-relation of DI values was also found between mlo-mediated resistance to PM and nonhost resistance tothe blast fungus CD. Therefore, nonhost resistanceagainst at least two fungal pathogens may be generallyregarded as a manifestation of PAMP-triggered im-munity in barley. Since there was no correlation of DIvalues between mlo-mediated PM resistance and non-host resistance to the rust Ptrit, it seems that the impactof the mlo allele on effective defense is restricted toepidermal tissue.

The obvious relation of the nonhost response ofbarley to mlo-mediated resistance led to the model ofselective suppression of host responses shown inFigure 6. In this model, compatible isolates of hostpathogens selectively suppress the part of the PAMP-triggered immunity regulon via different effector mol-ecules, which during coevolution turned out to becritical for the success or failure of the parasitic inter-action. In consequence, those genes that are under hostpathogen-specific suppression define the sets of tran-scripts with more strongly regulated levels duringnonhost interactions. In accordance with our observa-tions, these transcript sets are predicted to be largelynonoverlapping. Several effectors, such as AvrBS3 andXopD, may directly bind to target promoters affectingexpression of the corresponding genes (Kay et al.,2007; Kim et al., 2008a). The complexity and mostlyquantitative nature of the nonhost-specific transcrip-tional response, therefore, might be due to ratherpleiotropic, indirect effector action. Good candidatesfor genes mediating such indirect effects are severalWRKY transcription factors that were found to repressbasal defense in barley and Arabidopsis (Eckey et al.,2004; Shen et al., 2007; Kim et al., 2008b). Despite thefact that the nonhost-specific regulons were largelynonoverlapping between the different host/nonhostinteractions of barley, we observed a similar distribu-tion of overrepresented or underrepresented func-tional categories between nonhost-specific regulons

Table IV. Significant correlation of transcriptional changes of barleybetween different host/nonhost pairs of pathogens and mlo-mediatedresistance against Bgh

Comparison r a P b nc

DI PM epidermisversus DI Bgh epidermis mlo5

0.486 ,0.0001 366

DI PM leafversus DI Bgh leaf mlo5

0.463 ,0.0001 302

DI Mag epidermisversus DI Bgh epidermis mlo5

0.394 ,0.0001 121

DI Rust leafversus DI Bgh leaf mlo5

20.077 0.1353 374

aPearson r. bTwo-sided test for significant deviation of slope fromzero. cNumber of unigenes corresponding to differentially accu-mulating transcripts in both interactions to be compared.

Figure 6. Model of selective suppression of host defense genes bydifferent pathogens. The observed small overlap of the nonhost-specificpart of the transcriptional response of barley may be due to pathogen-specific suppression of basal defense, which is also under negativecontrol by the Mlo gene, by the different adapted host pathogens.Despite differences in the sets of regulated transcripts responding todifferent adapted or nonadapted pathogens, pathways and cellularresponses triggered by all types of pathogens were converging intosimilar defense reactions.





and generally pathogen-responsive transcripts acrosstwo or even three pathosystems. Therefore, the com-patible pathogens did address similar, probably im-portant pathways of defense by effector molecules inorder to establish host susceptibility, although theysuppressed the accumulation of different sets of tran-scripts involved in such pathways.

MATERIALS AND METHODS

Plant and Fungal Material

For all inoculation experiments, 7- to 10-d-old barley (Hordeum vulgare

subsp. vulgare ‘Ingrid’ Mlo) seedlings were used. In addition, for PM inocu-

lation, 7-d-old seedlings of experimental line ‘Ingrid BCmlo5’ (Buschges et al.,

1997) were used.

For PM inoculation, plants were routinely grown in compost soil from IPK

nursery without fertilization in a growth chamber at 20�C with 60% to 70%

relative humidity and a 16-h photoperiod (216 mmol m22 s21). Blumeria

graminis f. sp. hordei, strain CH4.8 carrying AvrMla9, was cultivated by weekly

inoculation of 7-d-old seedlings of barley cv Golden Promise.

ForMag inoculation, plants were routinely grown in commercial soil ED73

(Balster Einheitserdewerk) without fertilization in a growth chamber at 18�Cwith 50% to 60% relative humidity and a 16-h photoperiod (207 mmol m22 s21).

Mag isolate TH6772 of the host plant rice (Oryza sativa) was received from the

Institute of Biochemistry, Facility of Agriculture, TamagawaUniversity. Isolate

CD180 of Pennisetum was kindly provided by D. Tharreau (Centre de

Cooperation Internationale en Recherche Agronomique pour le Development).

Both Magnaporthe isolates were alternately grown on rice leaf agar (water

extract of 50 g L21 rice leaves, 10 g L21 water-soluble starch, 2 g L21 yeast extract

[Gerbu], and 15 g L21 agar-agar), HSA agar (oat flake starch agar, water extract

of 10 g L21 water-soluble starch, 2 g L21 Faex medicinales [yeast extract;

Gerbu]), and potato dextrose agar (Becton Dickinson). Isolates were incubated

at 24�C under black light (310–360 nm) for 2 weeks under a 16-h-day/8-h-night

regime.

For Rust inoculation, plants were grown in commercial soil (Floradur B

fein; Floragard) with additions of approximately 25% sand and perlite in a

greenhouse cabinet at 26�Cwith average 70% humidity in the light and at 19�Cwith average 70% humidity in the dark with a photoperiod of 16 h. Natural

daylight was supplemented with artificial light as soon as the external light

intensity dropped below 6,000 lux. Approximately 25 seeds each of cv Ingrid

barley were grown in pots (11 cm diameter) until 10 d old and fertilized using

a 1:1,000 dilution of Kamasol grun 10+4+7 (Compo). The Puccinia hordei isolate

I80 that is fully virulent on cv Ingrid was obtained from the Julius Kuhn

Institute and propagated on barley cv Astrid. Puccinia triticina (field isolate

collected by BASF near Limburgerhof, Germany) was propagated on wheat

(Triticum aestivum) cv Monopol.

Experimental Design

All inoculation experiments were set up as split-split-plot experiments

(treatment 3 fungal isolate or treatment 3 host genotype [Mlo/mlo5]). All

plots of one experiment were inoculated at the same time and harvested at the

times indicated.

Plant Inoculations

Plants of cv Ingrid or near-isogenic line Ingrid BC mlo5 (Buschges et al.,

1997) were inoculated with PM conidia by shaking inoculated plants over test

plants in a settling tower of approximately 603 603 60 cm. Inoculations were

done 1 to 2 h after the onset of light at an average density of 10 conidia mm22

leaf area. Control plants were left nontreated. Control and inoculated plants

were incubated at a constant temperature of 20�C and natural daylight (no

direct sunlight) until RNA extraction.

For inoculations with Mag, conidia of both isolates were harvested from

2-week-old agar plates by rinsing with distilled water and filtering through

three layers of gauze. The resulting spore suspension was diluted 1:1 (v/v)

with the spraying solution (0.1% [w/v] gelatin, 0.05% [v/v] Tween 20) to a

final concentration of 200,000 conidia mL21. Primary leaves of 7-d-old plants

were spray inoculated and incubated in a dark moist chamber at 26�C and

100% relative humidity. Mock-treated plants were sprayed in parallel with the

same solution containing no spores.

Plants were inoculated with Rust uredospores that had previously been

dehydrated for at least 4 d. Plants were dry inoculated with spores (1 g m22)

using an automated inoculation device. After application of spores, the plants

were dusted with water and moved for 24 h to a dark room with 23�C/20�Cday/night and 95% humidity. Mock-treated plants were only dusted with

water. Afterward, plants were maintained as described for the generation of

plant material.

Tissue Sampling and RNA Extraction

For transcript profiling experiments with PM and Mag, abaxial epidermis

of primary leaves from control and inoculated plants was stripped 6, 12, and

24 h post inoculation and immediately frozen in liquid N2. Epidermis of all

four samples to be harvested per time point (two treatments times two isolates

or genotypes) was stripped in parallel in order to exclude genes that are under

circadian regulation. For transcript profiling experiments with PM, the

remaining leaves with approximately 50% of the adaxial epidermis and the

entire abaxial epidermis still attached were also frozen in liquid nitrogen, in

order to compare transcript regulation events of the epidermis and the entire

leaf. The removal of approximately 25% of epidermis from leaves was

considered to be negligible; therefore, no discrimination between nonpeeled

leaf samples of the Rust experiments and partially peeled samples of the PM

experiments was made. For transcript profiling experiments with Rust, entire

leaves were sampled at 12, 24, and 48 h after inoculation and immediately

frozen in liquid nitrogen.

Total RNA of the inoculations with Mag (first three experiments), PM (all

experiments), and Rust (all experiments) was extracted using the acid guani-

dinium thiocyanate/phenol/chloroform method (Chomczynski and Sacchi,

1987). The fourth experiment of the Mag inoculation was extracted using the

hot phenol method (Dudler and Hertig, 1992).

Transcript Profiling

The design and production of the barleyPGRC1 10K cDNA arrays have

been described elsewhere (Schweizer, 2008). The array contains a total of

10,450 spotted PCR fragments corresponding to 10,297 unigenes. The labeling

and hybridization of barley cDNA probes by [33P]dCTP was performed as

described (Zierold et al., 2005). Radioactive signals on nylon membranes were

detected using a Fuji BAS3000 phosphor imager.

Transcriptome Data Analysis

Spots were detected and signals were quantified using the AIDA Image

Analyzer 4.08 and ArrayVision 8.0 software packages, respectively. For

background subtraction, dynamic definition of background spots was used

by selecting four spots producing the lowest signals per subarray and by

subtracting the mean intensity of those four spots from all spots of the

corresponding subarray. The rationale behind this background subtraction

was the presence of four empty spots per subarray that, however, did not

always produce the lowest signals, due to sporadic overshining from neigh-

boring spots with extremely strong hybridization signals. Spot intensity

values were normalized by median centering of the signal distribution per

array hybridization (Sreenivasulu et al., 2002). Spotted unigenes producing

signals above 2.03 local background in less than three to four hybridizations

per analyzed plant-pathogen combination (corresponding to three to four

biological replicates) were excluded from the analysis. Pathogen-regulated

transcripts per plant-pathogen combination were identified by paired, static-

match analysis and correction for multiple testing using the EDGE software

(Storey and Tibshirani, 2003; http://faculty.washington.edu/jstorey/edge/).

The significance thresholds for true positives and false discoveries were set to

P , 0.05 and q , 0.05, respectively. Pathogen-regulated transcripts were

subjected to PCA and hierarchical clustering using the MeV version 4.0

software (The Institute for Genomic Research). Settings for PCA were as

follows: log2 transformation of signal intensities or regulation factors, mean

centering of samples, 10 neighbors for KNN imputation. Settings for hierar-

chical clustering were as follows: log2 transformation of signal intensities,

median centering of transcript abundance signals, Pearson’s correlation,

complete linkage. For the analysis of transcript patterns between host and

corresponding nonhost interactions (Bgh versus Bgt, TH versus CD, Phor

Zellerhoff et al.




versus Ptrit), the set of 1,667 unigenes corresponding to differentially accu-

mulating transcripts was subjected to a second pairwise, static-match analysis

as specified above with significance thresholds of P , 0.05 and q , 0.1.

The entire transcript profiling data from this article have been deposited

in the ArrayExpress database and are available under experiment identifiers

E-IPKG-4 to E-IPKG-9.

Supplemental Data

The following materials are available in the online version of this article.

Supplemental Figure S1. Schematic summary of the experimental design.

Supplemental Figure S2. Distribution of the ratio of signal intensities

obtained from hybridization of epidermal versus whole-leaf mRNA

samples.

Supplemental Figure S3. Reproducibility of macroarray experiments.

Supplemental Figure S4. PCA of all transcript-derived signals on the

barleyPGRC1 array hybridized with noninoculated control samples.

Supplemental Figure S5. PCA of regulation factors (inoculated with PM

or Rust/control) of all spotted unigenes in leaf samples.

Supplemental Figure S6. Breakdown of the functional transcript category

“miscellaneous” from the MapMan binning file.

Supplemental Table S1. Summary data of all regulated genes during host

or nonhost interactions or during interaction of Bghwith Ingrid BCmlo5.

Supplemental Table S2. Unigenes with significantly different transcript

abundances between matching host-nonhost pairs of interactions in

barley epidermis.

Supplemental Table S3. Summary of genes regulated robustly during all

analyzed host interactions.

ACKNOWLEDGMENTS

The technical assistance of Ines Walde and Tanja Kempf is acknowledged.

We thank Dr. Matthias Lange for MAGE-ML export of array primary data to

ArrayExpress.

Received November 30, 2009; accepted February 11, 2010; published February

19, 2010.

LITERATURE CITED

Atienza SG, Jafary H, Niks RE (2004) Accumulation of genes for suscep-

tibility to Rust fungi for which barley is nearly a nonhost results in two

barley lines with extreme multiple susceptibility. Planta 220: 71–79

Breiteneder H, Mills C (2005) Nonspecific lipid-transfer proteins in plant

foods and pollens: an important allergen class. Curr Opin Allergy Clin

Immunol 5: 275–279

Broekaert WF, Cammue BPA, DeBolle MFC, Thevissen K, DeSamblanx

GW, Osborn RW (1997) Antimicrobial peptides from plants. Crit Rev

Plant Sci 16: 297–323

Buchanan-Wollaston V, Earl S, Harrison E, Mathas E, Navabpour S, Page

T, Pink D (2003) The molecular analysis of leaf senescence: a genomics

approach. Plant Biotechnol J 1: 3–22

Buschges R, Hollricher K, Panstruga R, Simons G, Wolter M, Frijters A,

van Daelen R, van der Lee T, Diergarde P, Groenendijk J, et al (1997)

The barley Mlo gene: a novel control element of plant pathogen

resistance. Cell 88: 695–705

Caldo RA, Nettleton D, Wise RP (2004) Interaction-dependent gene

expression in Mla-specified response to barley powdery mildew. Plant

Cell 16: 2514–2528

Chomczynski P, Sacchi N (1987) Single-step method of RNA isolation by

acid guanidinium thiocyanate-phenol-chloroform extraction. Anal Bio-

chem 162: 156–159

Close TJ, Wanamaker SI, Caldo RA, Turner SM, Ashlock DA, Dickerson

JA, Wing RA, Muehlbauer GJ, Kleinhofs A, Wise RP (2004) A new

resource for cereal genomics: 22K barley GeneChip comes of age. Plant

Physiol 134: 960–968

Collins NC, Thordal-Christensen H, Lipka V, Bau S, Kombrink E, Qiu JL,

Huckelhoven R, Stein M, Freialdenhoven A, Somerville SC, et al

(2003) SNARE-protein-mediated disease resistance at the plant cell wall.

Nature 425: 973–977

Consonni C, Humphry ME, Hartmann HA, Livaja M, Durner J, Westphal

L, Vogel J, Lipka V, Kemmerling B, Schulze-Lefert P, et al (2006)

Conserved requirement for a plant host cell protein in powdery mildew

pathogenesis. Nat Genet 38: 716–720

DongWB, Nowara D, Schweizer P (2006) Protein polyubiquitination plays

a role in basal host resistance of barley. Plant Cell 18: 3321–3331

Douchkov D, Nowara D, Zierold U, Schweizer P (2005) A high-through-

put gene-silencing system for the functional assessment of defense-

related genes in barley epidermal cells. Mol Plant Microbe Interact 18:

755–761

Dudler R, Hertig C (1992) Structure of an mdr-like gene from Arabidopsis

thaliana: evolutionary implications. J Biol Chem 267: 5882–5888

Eckey C, Korell M, Leib K, Biedenkopf D, Jansen C, Langen G, Kogel KH

(2004) Identification of powdery mildew-induced barley genes by

cDNA-AFLP: functional assessment of an early expressed MAP kinase.

Plant Mol Biol 55: 1–15

Ellis J (2006) Insights into nonhost disease resistance: can they assist

disease control in agriculture? Plant Cell 18: 523–528

Gjetting T, Hagedorn PH, Schweizer P, Thordal-Christensen H, Carver

TLW, Lyngkjaer MF (2007) Single-cell transcript profiling of barley

attacked by the powdery mildew fungus. Mol Plant Microbe Interact 20:

235–246

Guiderdoni E, Cordero MJ, Vignols F, Garcia-Garrido JM, Lescot M,

Tharreau D, Meynard D, Ferriere N, Notteghem JL, Delseny M (2002)

Inducibility by pathogen attack and developmental regulation of the

rice Ltp1 gene. Plant Mol Biol 49: 683–699

Himmelbach A, Zierold U, Hensel G, Riechen J, Douchkov D, Schweizer

P, Kumlehn J (2007) A set of modular binary vectors for transformation

of cereals. Plant Physiol 145: 1192–1200

Holzberg S, Brosio P, Gross C, Pogue GP (2002) Barley stripe mosaic virus-

induced gene silencing in a monocot plant. Plant J 30: 315–327

Hoogkamp TJH, Chen WQ, Niks RE (1998) Specificity of prehaustorial

resistance to Puccinia hordei and to two inappropriate Rust fungi in

barley. Phytopathology 88: 856–861

Hu PS, Meng Y, Wise RP (2009) Functional contribution of chorismate

synthase, anthranilate synthase, and chorismate mutase to penetration

resistance in barley-powdery mildew interactions. Mol Plant Microbe

Interact 22: 311–320

Humphry M, Consonni C, Panstruga R (2006) mlo-based powdery mildew

immunity: silver bullet or simply non-host resistance? Mol Plant Pathol

7: 605–610

Jafary H, Szabo LJ, Niks RE (2006) Innate nonhost immunity in barley to

different heterologous Rust fungi is controlled by sets of resistance

genes with different and overlapping specificities. Mol Plant Microbe

Interact 19: 1270–1279

Jones JDG, Dangl JL (2006) The plant immune system. Nature 444: 323–329

Kay S, Hahn S, Marois E, Hause G, Bonas U (2007) A bacterial effector acts

as a plant transcription factor and induces a cell size regulator. Science

318: 648–651

Kim JG, Taylor KW, Hotson A, Keegan M, Schmelz EA, Mudgett MB

(2008a) XopD SUMO protease affects host transcription, promotes

pathogen growth, and delays symptom development in Xanthomonas-

infected tomato leaves. Plant Cell 20: 1915–1929

Kim KC, Lai ZB, Fan BF, Chen ZX (2008b) Arabidopsis WRKY38 and

WRKY62 transcription factors interact with histone deacetylase 19 in

basal defense. Plant Cell 20: 2357–2371

Kim M, Lim JH, Ahn CS, Park K, Kim GT, Kim WT, Pai HS (2006)

Mitochondria-associated hexokinases play a role in the control of pro-

grammed cell death in Nicotiana benthamiana. Plant Cell 18: 2341–2355

Kim TH, Park JH, Kim MC, Cho SH (2008c) Cutin monomer induces

expression of the rice OsLTP5 lipid transfer protein gene. J Plant Physiol

165: 345–349

Lipka V, Dittgen J, Bednarek P, Bhat R, Wiermer M, Stein M, Landtag J,

Brandt W, Rosahl S, Scheel D, et al (2005) Pre- and postinvasion

defenses both contribute to nonhost resistance in Arabidopsis. Science

310: 1180–1183

Loehrer M, Langenbach C, Goellner K, Conrath U, Schaffrath U (2008)





Characterization of nonhost resistance of Arabidopsis to the Asian

soybean Rust. Mol Plant Microbe Interact 21: 1421–1430

Matsuo H, Taniguchi K, Hiramoto T, Yamada T, Ichinose Y, Toyoda K,

Takeda K, Shiraishi T (2001) Gramine increase associated with rapid

and transient systemic resistance in barley seedlings induced by me-

chanical and biological stresses. Plant Cell Physiol 42: 1103–1111

Miklis M, Consonni C, Bhat RA, Lipka V, Schulze-Lefert P, Panstruga R

(2007) Barley MLO modulates actin-dependent and actin-independent

antifungal defense pathways at the cell periphery. Plant Physiol 144:

1132–1143

Molina A, Garcia-Olmedo F (1997) Enhanced tolerance to bacterial path-

ogens caused by the transgenic expression of barley lipid transfer

protein LTP2. Plant J 12: 669–675

Neu C, Keller B, Feuillet C (2003) Cytological and molecular analysis of the

Hordeum vulgare-Puccinia triticina nonhost interaction. Mol Plant

Microbe Interact 16: 626–633

Park JH, SuhMC, Kim TH, KimMC, Cho SH (2008) Expression of glycine-

rich protein genes, AtGRP5 and AtGRP23, induced by the cutin mono-

mer 16-hydroxypalmitic acid in Arabidopsis thaliana. Plant Physiol

Biochem 46: 1015–1018

Patkar RN, Chattoo BB (2006) Transgenic indica rice expressing ns-LTP-

Like protein shows enhanced resistance to both fungal and bacterial

pathogens. Mol Breed 17: 159–171

Schweizer P (2007) Nonhost resistance of plants to powdery mildew: new

opportunities to unravel the mystery. Physiol Mol Plant Pathol 70: 3–7

Schweizer P (2008) Tissue-specific expression of a defence-related perox-

idase in transgenic wheat potentiates cell death in pathogen-attacked

leaf epidermis. Mol Plant Pathol 9: 45–57

Schweizer P, Felix G, Buchala A, Mueller C, Metraux JP (1996a) Percep-

tion of free cutin monomers by plant cells. Plant J 10: 331–341

Schweizer P, Jeanguenat A, Whitacre D, Metraux JP, Mosinger E (1996b)

Induction of resistance in barley against Erysiphe graminis f.sp. hordei

by free cutin monomers. Physiol Mol Plant Pathol 49: 103–120

Shen QH, Saijo Y, Mauch S, Biskup C, Bieri S, Keller B, Seki H, Ulker B,

Somssich IE, Schulze-Lefert P (2007) Nuclear activity of MLA immune

receptors links isolate-specific and basal disease-resistance responses.

Science 315: 1098–1103

Skamnioti P, Gurr SJ (2007) Magnaporthe grisea cutinase2 mediates appres-

sorium differentiation and host penetration and is required for full

virulence. Plant Cell 19: 2674–2689

Sreenivasulu N, Altschmied L, Panitz R, Hahnel U, Michalek W,

Weschke W, Wobus U (2002) Identification of genes specifically ex-

pressed in maternal and filial tissues of barley caryopses: a cDNA array

analysis. Mol Genet Genomics 266: 758–767

Sreenivasulu N, Usadel B, Winter A, Radchuk V, Scholz U, Stein N,

Weschke W, Strickert M, Close TJ, Stitt M, et al (2008) Barley grain

maturation and germination: metabolic pathway and regulatory net-

work commonalities and differences highlighted by new MapMan/

PageMan profiling tools. Plant Physiol 146: 1738–1758

Stanislava G (2007) Barley grain non-specific lipid-transfer proteins (ns-

LTPs) in beer production and quality. J Inst Brew 113: 310–324

Stein M, Dittgen J, Sanchez-Rodriguez C, Hou BH, Molina A, Schulze-

Lefert P, Lipka V, Somerville S (2006) Arabidopsis PEN3/PDR8, an ATP

binding cassette transporter, contributes to nonhost resistance to inap-

propriate pathogens that enter by direct penetration. Plant Cell 18:

731–746

Storey JD, Tibshirani R (2003) Statistical significance for genomewide

studies. Proc Natl Acad Sci USA 100: 9440–9445

Tosa Y, Shishiyama J (1984) Defense reactions of barley cultivars to an

inappropriate forma-specialis of the powdery mildew fungus of gra-

mineous plants. Can J Bot 62: 2114–2117

Trujillo M, Troeger M, Niks RE, Kogel KH, Huckelhoven R (2004)

Mechanistic and genetic overlap of barley host and non-host resistance

to Blumeria graminis. Mol Plant Pathol 5: 389–396

Vergne E, Ballini E, Marques S, Mammar BS, Droc G, Gaillard S, Bourot

S, DeRose R, Tharreau D, Notteghem JL, et al (2007) Early and specific

gene expression triggered by rice resistance gene Pi33 in response to

infection by ACE1 avirulent blast fungus. New Phytol 174: 159–171

Weil CF (2009) TILLING in grass species. Plant Physiol 149: 158–164

Zellerhoff N, Jarosch B, Groenewald JZ, Crous PW, Schaffrath U (2006)

Nonhost resistance of barley is successfully manifested against Magna-

porthe grisea and a closely related Pennisetum-infecting lineage but

is overcome by Magnaporthe oryzae. Mol Plant Microbe Interact 19:

1014–1022

Zierold U, Scholz U, Schweizer P (2005) Transcriptome analysis of mlo-

mediated resistance in the epidermis of barley. Mol Plant Pathol 6:

139–151

Zellerhoff et al.




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