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Comparative transcriptome analysis of Arabidopsis thaliana infested by diamond back moth (Plutella xylostella)… Ehlting, Jürgen; Chowrira, Sunita G; Mattheus, Nathalie; Aeschliman, Dana S; Arimura, Gen-Ichiro; Bohlmann, Jörg Apr 9, 2008

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ralssBioMed CentBMC GenomicsOpen AcceResearch articleComparative transcriptome analysis of Arabidopsis thaliana infested by diamond back moth (Plutella xylostella) larvae reveals signatures of stress response, secondary metabolism, and signallingJürgen Ehlting1,5, Sunita G Chowrira1,2, Nathalie Mattheus1, Dana S Aeschliman4, Gen-Ichiro Arimura1 and Jörg Bohlmann*1,2,3Address: 1Michael Smith Laboratories, University of British Columbia, 2185 East Mall Vancouver, B.C., V6T 1Z4, Canada, 2Department of Botany, University of British Columbia, 6270 University Blvd Vancouver, B.C., V6T 1Z4, Canada, 3Department of Forest Sciences, University of British Columbia, 2424 Main Mall Vancouver, B.C., V6T 1Z4, Canada, 4Department of Statistics, University of British Columbia, 6356 Agricultural Road, Vancouver, B.C., V6T 1Z4, Canada and 5Centre for Forest Biology & Department of Biology, University of Victoria, PO Box 3020 TN CSC, Victoria, B.C., V8W 3N5, CanadaEmail: Jürgen Ehlting - je@uvic.ca; Sunita G Chowrira - chowrira@interchange.ubc.ca; Nathalie Mattheus - natamolius@yahoo.com; Dana S Aeschliman - danaaesch@gmail.com; Gen-Ichiro Arimura - garimura@ice.mpg.de; Jörg Bohlmann* - bohlmann@msl.ubc.ca* Corresponding author    AbstractBackground: Plants are exposed to attack from a large variety of herbivores. Feeding insects can inducesubstantial changes of the host plant transcriptome. Arabidopsis thaliana has been established as a relevant systemfor the discovery of genes associated with response to herbivory, including genes for specialized (i.e. secondary)metabolism as well as genes involved in plant-insect defence signalling.Results: Using a 70-mer oligonulceotide microarray covering 26,090 gene-specific elements, we monitoredchanges of the Arabidopsis leaf transcriptome in response to feeding by diamond back moth (DBM; Plutellaxylostella) larvae. Analysis of samples from a time course of one hour to 24 hours following onset of DBM feedingrevealed almost three thousand (2,881) array elements (including 2,671 genes with AGI annotations) that weredifferentially expressed (>2-fold; p[t-test] < 0.05) of which 1,686 also changed more than twofold in expressionbetween at least two time points of the time course with p(ANOVA) < 0.05. While the majority of thesetranscripts were up-regulated within 8 h upon onset of insect feeding relative to untreated controls, clusteranalysis identified several distinct temporal patterns of transcriptome changes. Many of the DBM-induced genesfall into ontology groups annotated as stress response, secondary metabolism and signalling. Among DBM-inducedgenes associated with plant signal molecules or phytohormones, genes associated with octadecanoid signallingwere clearly overrepresented. We identified a substantial number of differentially expressed genes associatedwith signal transduction in response to DBM feeding, and we compared there expression profiles with those ofpreviously reported transcriptome responses induced by other insect herbivores, specifically Pieris rapae,Frankliniella occidentalis, Bemisia tabaci,Myzus persicae, and Brevicoryne brassicae.Conclusion: Arabidopsis responds to feeding DBM larvae with a drastic reprogramming of the transcriptome,which has considerable overlap with the response induced by other insect herbivores. Based on a meta-analysisof microarray data we identified groups of transcription factors that are either affected by multiple forms of bioticor abiotic stress including DBM feeding or, alternatively, were responsive to DBM herbivory but not to mostPublished: 9 April 2008BMC Genomics 2008, 9:154 doi:10.1186/1471-2164-9-154Received: 17 November 2007Accepted: 9 April 2008This article is available from: http://www.biomedcentral.com/1471-2164/9/154© 2008 Ehlting et al; licensee BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.Page 1 of 20(page number not for citation purposes)other forms of stress.BMC Genomics 2008, 9:154 http://www.biomedcentral.com/1471-2164/9/154BackgroundArabidopsis thaliana has emerged as a useful system forgenomic studies of plant insect-interactions [1-6]. Becauseof the large amount of genomic information available forArabidopsis, it is possible to perform comparisons of geneexpression profiles across many different conditions ortreatments including various forms of interactions withherbivores and pathogens [1,2]. With regard to specificpathways involved in plant defence against insects, theArabidopsis genomic resources have much advanced, forexample, the discovery of genes and proteins of secondarymetabolism (specifically glucosinolate, phenolic, and ter-penoid metabolism) [7-11], as well as genes involved inplant-insect defence signalling [12-14].Previous large-scale gene expression microarray analysesof Arabidopsis-herbivore interactions involved plantsaffected by Pieris rapae (larvae of cabbage white butterfly),Spodoptera littoralis (larvae of mediterranean brocade),Frankliniella occidentalis (western flower thrip), Bemisiatabaci (silverleaf whitefly nymphs), Brevicoryne brassicae(cabbage aphid), and Myzus persicae (green peach aphid)[1-5,15]. These insects represent leave-chewing larvae (P.rapae and S. littoralis) as well as cell-sucking (F. occidenta-lis) or phloem sap-feeding (M. persicae, B. brassicae, B.tabaci) adults with P. rapae and B. brassicae being specialistherbivores adapted to members of the Brassicaceae as theirhosts. The present study complements previous work withan analysis of Arabidopsis rosette leaves fed upon by lar-vae of a different leave-chewing specialist herbivore,Plutella xylostella (diamond back moth – DBM). DBM lar-vae feed on several crucifer plants and are a frequent pestof agricultural crops including cabbage, broccoli, cauli-flower, and rape [16].Overall, our findings from a fully replicated time-coursetranscriptome analysis of Arabidopsis challenged by DBMlarvae identified almost three thousand (2,881 array ele-ments; 2,671 genes with AGI annotations) differentiallyexpressed genes (>2-fold; p[t-test] < 0.05) and several dis-tinct temporal patterns of changes of transcript abun-dance with prominent changes of transcripts associatedwith stress response, secondary metabolism, and signal-ling. In addition, we provide a first comprehensive meta-analysis of array data of herbivore-induced Arabidopsistranscription factors, which identified insect-inducedtranscription factors that are also affected by other formsof biotic or abiotic stress as well as transcription factorsthat appear to be more specific to the insect-inducedresponse.ResultsOverall changes of the Arabidopsis leaf transcriptome in response to DBMArabidopsis rosette leaves (ecotype Ler) were challengedwith feeding DBM larvae (third to fifth instars). For micro-array gene expression profiling, rosette leaves were har-vested after 1 h, 4 h, 8 h, and 24 h of continuous DBMfeeding. For each time point leaves were also harvestedfrom unchallenged control plants. In order to obtainenough plant material for RNA isolation (leave materialbecame limiting in particular at the later time points ofDBM feeding) each treatment and time point consisted offour or five plants grown together in one pot and exposedto a group of seven DBM larvae. For each treatment andcontrol and for each time point two independent biolog-ical replicate experiments were performed and RNAderived from each biological replicate was used for twoseparate array hybridizations each using reversed fluores-cence labels (dye-flip). This experimental design thusresulted in four replicate microarray hybridizations pertime point and treatment with two biological and twotechnical replicates comparing RNA derived from treatedplants with the corresponding control harvested in paral-lel.The microarray used in this study is based on a set of26,090 Arabidopsis gene specific 70-mer oligonucleotides[9]. Upon removal of manually flagged spots, backgroundcorrection, and flooring, on average 12.5 % of all spotswere excluded from further analyses as non-detectible.Signal intensities were used for loess normalizationthereby generating log2-ratios comparing each treatmentwith the corresponding control. For each time point, wefirst used the data from the four replicate arrays to per-form a Student's t-test and to calculate mean expressionratios for each treatment sample relative to the corre-sponding control. In order to assess the type I error rate,we calculated q-values estimating the false discovery ratebased on the parametric p-values obtained from the t-sta-tistic [17]. We then used the four normalized expressionratios from each of five time points (for a total of 20 datapoints) to perform an analysis of variance (ANOVA) andagain estimated the false discovery rate based on the dis-tribution of parametric p-values (Figure 1). Normalizedexpression ratios for all probes on the array as well asresults for all statistical analysis are provided in Addi-tional File 1. As expected, higher p-values from t-statisticsare associated with a higher false discovery rate; for exam-ple, after 8 h of herbivory 4,576 probes were characterizedwith p(t-test) < 0.05, but have a 11% chance to be falselydiscovered (q < 0.110), while only 1,476 probes are char-acterized with p(t-test) < 0.01, and these have only a 6.8%chance to be falsely discovered (Table 1). However, a rel-Page 2 of 20(page number not for citation purposes)atively large number of array probes were associated withhigh p-values (up to at least 0.08), which still contain aBMC Genomics 2008, 9:154 http://www.biomedcentral.com/1471-2164/9/154substantial number of truly differentially expressed genes(Figure 1), as estimated from the higher frequency ofgenes in these p-value bins compared to the frequencyexpected if no genes were differentially expressed (indi-cated by a horizontal line in Figure 1). Thus, by using alow p-value cut-off (0.01), we would reduce the numberof falsely discovered genes, but would also miss a substan-tial number of truly differentially expressed genes. There-fore, assuming that high fold change differences isassociated with a lower likelihood of being false positives,we initially defined as 'differentially expressed' (i.e. geneswith DBM-induced change in transcript abundance) thosegenes for each time point that were associated with a t-testp-value of less than 0.05 (accepting a false discovery rateof up to 0.4) and also displayed a more than two-foldchange between treatment and control. Using this defini-tion, the number of differentially expressed transcripts at(1,246 up- and 559 down-regulated array elements) after8 h of herbivory, with a total of 2,881 transcripts that weredifferentially expressed in at least one time point (Table1). Among these 2,881 transcripts, 1,854 were signifi-cantly up-regulated (designated group A in Additional File1) while 1,007 were significantly down-regulated (groupB) and only 20 were up-regulated at one time point anddown-regulated at another (group C in Additional File 1,Table 1). Relatively few genes were differentially expressedat 1 h after the onset of feeding with increasing numbersof differentially expressed genes until 8 h after DBM feed-ing. Despite ongoing feeding, fewer genes are differen-tially expressed at 24 h after the onset of feeding. At alltime points, much fewer transcripts were down-regulatedthen up-regulated (Table 1). In summary, a total of 2,881probes representing the Arabidopsis leaf transcriptomemet our strict definition of differential expression inresponse to DBM feeding in showing a significant (p[t-test] < 0.05) and more than twofold difference of tran-script abundance between treatment and control for atleast one time point.Temporal patterns of the Arabidopsis leaf transcriptome affected by DBMTo estimate the number of genes that were changing inexpression between at least two time points we performedan analysis of variance (ANOVA), and found 3,111 genesthat changed more than twofold with p(ANOVA) < 0.05(Table 1). However, of these only 1,686 were also differ-entially expressed between treatment and control in atleast one time point. These 1,686 genes, which met ourmost stringent definition of differential expression inresponse to DBM feeding over the 24 hour time course,were placed into nine expression clusters based on theirtemporal patterns of expression profiles identified by K-means clustering (Figure 2; identification of genes belong-ing to each cluster is provided in Additional File 1). While71 genes displayed a rapid transient up-regulation within1 h upon onset of herbivory (Cluster A), a total of 779genes peaked at 8 h (cluster B and cluster C). Anothergroup of differentially expressed genes showed up-regula-tion of transcript abundance mainly at late time-points(cluster D), while 234 genes were up-regulated early dur-ing the treatment and maintained high expression levelsrelative to control plants (cluster E).Similarly, many down-regulated genes displayed transientexpression profiles (cluster G and cluster H), although amajority of down-regulated genes maintained lowerexpression levels over the time course analyzed (cluster I).Interestingly, a portion of genes placed in the down-regu-lated clusters displayed reversed expression ratios at differ-ent time points, e. g. some genes in cluster H wereDistribution of parametric p-values from ANOVAFigure 1Distribution of parametric p-values from ANOVA. For each of the 26,090 probes present on the microarray, normalized expression ratios from four replicate arrays for each of the four time points were used for an analysis of var-iance (ANOVA). Shown is the frequency distribution of the resulting p-values. A horizontal line indicates the estimated NULL distribution separating the number of true positive tests (above the line) from negative tests within a given p-value bin (falsely discovered genes)p-valueFrequency0.0 0.2 0.4 0.6 0.8 1.00500100015002000250012.9% Diff ExpPage 3 of 20(page number not for citation purposes)each time point was found to range from 130 (98 up- and32 down-regulated) after 1 h of DBM feeding to 1,805transiently down-regulated at early time-points but wereup-regulated later in the experiment. Likewise, manyBMC Genomics 2008, 9:154 http://www.biomedcentral.com/1471-2164/9/154genes in cluster I were transiently up-regulated early in thetreatment, but were down-regulated 24 h after the onset ofDBM feeding. In reverse, many genes in cluster F were up-regulated 8 h into the time course, but displayed repressedexpression at the 24 h time point. This cluster also con-tains genes that display a biphasic expression pattern,with repressed expression at early (1 h) and late (24 h)time points.In summary, it is noteworthy that despite continuousinsect feeding over the time period analyzed, a majority(60%) of up-regulated genes displayed a transient patternof change of transcript abundance.Annotation and expression profiles of DBM induced stress-related genesAnnotation against higher level GeneOntology terms atTAIR [18,19] revealed that many of the genes up-regulatedby DBM feeding fall into the functional categories 'trans-port', 'response to abiotic or biotic stimulus (stress)', 'pro-tein metabolism', and 'transcription'. In order to analyzeexpression profiles of stress-related genes in more detail,we retrieved curator annotated TAIR gene lists for the cat-egories 'response to pest, pathogen or parasite' or'response to wounding' as well as for genes associatedwith children terms of these categories. We further limitedthese lists to those genes that have been annotated basedon experimental evidence resulting in 150 stress-relatedgenes after removal of duplicates. Of these, 128 were rep-resented on the microarray and 30 (23%) were differen-tially expressed in response to DBM feeding. Expressiondata for these genes were used for hierarchical cluster anal-Most of these DBM-affected stress-related genes werestrongly up-regulated within 1 to 4 h after the onset ofDBM feeding (Figure 3), and the majority were associatedwith wound response. In contrast, only five genes wereup-regulated only at the 24 h time point, including twopathogenesis-related (PR) genes (PR1/At2g14610 andPRB1/At2g14580) that are associated with salicylic aciddependent pathogen defence. These genes are down-regu-lated early during DBM feeding before being up-regulatedat 24 h. Many of the wound-response genes that arestrongly up-regulated by DBM are involved in octadeca-noid biosynthesis. All known enzymatic steps of the octa-decanoid pathway were represented in the cluster ofDBM-induced genes (Figure 3A). These include the lipox-ygenase LOX2 (At3g45140), two other putative lipoxyge-nases (At1g17420 and At1g72520), the single copy alleneoxid synthase AOS (CYP74A, At5g42650), the alleneoxide cyclases AOC1 (At3g2576), AOC2 (At3g25780),and AOC4 (At1g13280), the 12-oxophytodienoatereductases OPR2 (At1g76690) and OPR3 (At2g06050),and 3-oxo-2-(2'-[Z]-pentenyl)cyclopentane-1-octanoicacid CoA Ligase1 OPCL1 (At1g20510) [20,21]. Othergenes in this group of up-regulated wound-response genesare involved in the shikimate pathway (anthranilate syn-thase, ASB, At1g25220), and tocopherol biosynthesis(tyrosine aminotransferase, TAT, At2g24850) [22,23].We further analyzed expression patterns of genes of sec-ondary metabolite pathways that are known to be affectedby herbivory, namely glucosinolate, phenolic and terpe-noid metabolism (Figure 3B–D). Many transcripts ofthese pathways were differentially expressed upon DBMTable 1: Overall summary of differentially expressed genesp(t-test) < 0.01 p(t-test) < 0.05 p(t-test) < 0.05, FCb>2Treatment genes max. FDRa genes max. FDRa genes, total up down mixed1 h 327 0.589 1350 0.719 130 98 32 -4 h 524 0.307 2019 0.402 532 407 125 -8 h 1476 0.068 4576 0.110 1805 1246 559 -24 h 854 0.173 3124 0.238 1154 658 496 -In at least 1 time point 2830 - 8471 - 2881 1854 1007 20p(ANOVA) < 0.01 p(ANOVA) < 0.05 p(ANOVA) < 0.05, FCc>2Treatment genes max. FDRa genes max. FDRa genesAll 1756 0.084 4093 0.169 3111da the highest expected false discovery rate (FDR); i.e. the maximal q-value observed for the given p(t-test) cut-pointb fold-change between treatment and controlc maximum fold change between treatments [max (treatment/control)/min (treatment/control)]d of these 3111 genes only 1686 genes are also among the group of 2881 genes that are differentiallyexpressed in at least one time point with p(t-test) < 0.05 and FCb > 2Page 4 of 20(page number not for citation purposes)ysis shown with expression maps in Figure 3. feeding. For the glucosinolate pathway, two genesinvolved in the chain elongation of methionin (MAM1BMC Genomics 2008, 9:154 http://www.biomedcentral.com/1471-2164/9/154Page 5 of 20(page number not for citation purposes)Expression profiles based on K-means clusteringFigure 2Expression profiles based on K-means clustering. Mean log2-expression ratios for genes that are differentially expressed in at least one time point (p[t-test] < 0.05 with more than two-fold change of transcript abundance between treatment and control) and which are also changing more than two-fold over time with p(ANOVA) < 0.05 were used for K-means clustering. Each gene within a given cluster is shown with a grey line and the mean expression profile from all genes in a given cluster is indicated with a single blue line. Cluster designation and the number of genes in each cluster are shown above each panel.log 2(DBM/control)log 2(DBM/control)-101231 4 24log 2(DBM/control)time [h] time [h] time [h]A (71 genes) B (154 genes) C (625 genes)D (199 genes) E (234 genes) F (59 genes)G (130 genes) H (38 genes) I (176 genes)8-101231 4 248-1011 4 248-101231 4 248-101231 4 2480341 4 24821-1-1011 4 248-1-2011 4 248-1.5-0.50.51 4 248-2.5BMC Genomics 2008, 9:154 http://www.biomedcentral.com/1471-2164/9/154Page 6 of 20(page number not for citation purposes)Expression profiles of defence related genes and genes of secondary metabolism upon herbivoryFigure 3Expression profiles of defence related genes and genes of secondary metabolism upon herbivory. (A) A list of curator annotated genes involved in response to pathogens or wounding was retrieved from TAIR [18] Thirty of these genes were differentially expressed in response to DBM feeding in at least one time point and mean expression ratios for these genes were used to generate the heatmap. Bright red indicates a more than 5.7-fold higher level of transcript abundance (expression) in herbivore treated plants compared to control plants; bright blue indicates a more than 5.7-fold lower expression. (B) 22 Arabidopsis genes have been characterized as being involved in glucosinolate biosynthesis [32] and eleven of those were found differentially expressed in at least one time point upon DBM herbivory. These genes were used to generate the heatmap shown here. C) Of 78 genes encoding enzymes of the phenylpropanoid pathway and homologs thereof [9], thirteen were found differentially expressed as shown. Note that only CAD1, 4CL3, and 4CL4 are characterized enzymes while all other rep-resent homologs of known phenylpropanoid genes. (D) Of 229 genes annotated to be involved in Arabidopsis isoprenoid metabolism [11], 30 genes (13%) were differentially expressed upon DBM feeding. Shown as a heatmap are selected genes involved in mono-, sesqui,- or diterpene biosynthesis. For details on expression data and gene name abbreviations search Addi-tional File 1 using the locus identifier provided.log2DBMcontrol(        )-2.5 2.51 4 8 24  hDBMLocusNameA: pathogen/wound responseB: glucosinolate biosynthesisC: phenylpropanoid biosynthesisD: terpenoid biosynthesisAt5g24770At3g45140At2g24850At1g17420At1g72520At1g20510At1g72260At5g23570At2g02990At5g20230At4g34710At5g42650At3g25780At3g25760At1g25220At1g76690At1g13280At2g06050At1g01470At2g46370At4g23190At2g14610At2g14580At5g50200At3g04720At5g36970At1g51400At4g36430At1g55490At5g46330VSP2LOX2TAT3LOXputLOXputOPCL1THI2.1SGS3RNS1BCBADC2AOSAOC2AOC1ASBOPR2AOC4OPR3LEA14JAR1CRK11PR1PRB1WR3PR4NHL25PSIIP31LEN1FLS2At5g23020At5g23010At1g16400At5g05260At4g39950At4g31500At2g20610At4g03050At1g52030At1g54030At3g14210MAMLMAM1CYP79F2CYP79A2CYP79B2CYP83B1SUR1AOP3MBPMAGLMAG2At3g02280At1g65060At3g21230At5g38120At1g67990At1g09500At1g76470At5g54160At1g33030At1g76790At4g35160At4g34230At4g37970ATR34CL34CL44CLL8CCOMTL2CCRL3CCRL7COMTCOMTL5COMTL9COMTL14CAD1CADL4At2g02500At3g21500At4g17190At5g47720At1g61120At2g24210At5g23960MCTDXPS1FPPS1AACT1TPS04TPS10TPS21BMC Genomics 2008, 9:154 http://www.biomedcentral.com/1471-2164/9/154and MAML, At5g23020 and At5g23010) were up-regu-lated, while two other members of the MAM gene family[24] were not detectibly differentially expressed. Also up-regulated were cytochrome P450 monooxygenasesinvolved in the biosynthesis of various glucosinolates:CYP79A2 (At5g05260) catalyzing the conversion of phe-nylalanine to the corresponding oxime in benzylglucosi-nolate biosynthesis [25]; CYP79B2 (At4g39950)converting tryptophan and tryptophan analogs to theoxime in indole glucosinolate biosynthesis [26]; CYP79F2(At1g16400) involved in the synthesis of long chainaliphatic glucosinolates [27]; and CYP83B1 (At4g31500)catalyzing the oxidation of indole-3-acetyldoxime inindole glucosinolate biosynthesis [28]. CYP79B2 is alsoinvolved in camalexin and auxin biosynthesis [29,30].DBM feeding further induced the C-S-lyase (SUR1,At2g20610) that converts S-(alkylacetohydroximoyl)-L-cysteines to the corresponding thiohydroximic acids [31].While none of the three myrosinase encoding genespresent in Arabidopsis [32] were differentially expressedat detectable levels, two myrosinase associated proteins(MAG) were affected. Of these MAG2 (At3g14210), whichhas been characterized as a quantitative trait locus(termed epithiospecifier 1; ESM1) controlling the ratio ofnitrile to isothiocyanate production during glucosinolatehydrolysis [33], was suppressed by DBM feeding, whilethe related gene MAGL (At1g54030) was induced.Relatively few genes that have been functionally character-ized to encode enzymes of the phenylpropanoid pathwayare induced by DBM feeding (Figure 3C), but many of thegenes of this pathway just failed the call to be significantlydifferentially expressed at stringent conditions. In con-trast, eight genes with similarity to known phenylpropa-noid genes but otherwise of unknown function weretranscriptionally up-regulated (Figure 3C).Related to terpenoid biosynthesis, two differentiallyexpressed genes encoding enzymes of the methylerythri-tol phosphate pathway, 1-deoxy-D-xylulose 5-phosphatesynthase (DXPS1, At3g21500) and 2-C-methyl-D-erythri-tol 4-phosphate cytidyltransferase (MCT, At2g02500)[11] were down-regulated by DBM feeding. In contrast theonly gene of the mevalonate pathway that was detected asaffected by DBM feeding encodes acetoacetyl-CoA thio-lase (AACT1, At5g47720) and was up-regulated. In addi-tion, a farnesyl diphosphate synthase (FPPS1, At4g17190)and three of the more than thirty Arabidopsis terpene syn-thase genes (TPS04, At1g61120; TPS10, At2g24210;TPS21, At5g23960) [10] were up-regulated by DBM feed-ing (Figure 3D).Expression profiles of phytohormone related genes affected by DBM feedingBased on the relatively large number of transcripts up-reg-ulated by DBM that are associated with biosynthesis ofoctadecanoids (Figure 3), we compared these transcriptsprofiles with those associated with other signalling mole-cules and phytohormones, namely salicylic acid, ethylene,auxin, abscisic acid, brassinosteroids, cytokinin, and gib-berellic acid (Figure 4). For this purpose, we retrievedTAIR gene lists that had been curator annotated to beeither involved in the metabolism of these signalling mol-ecules, to be part of the signal transduction mediated by,or to be responsive to these compounds.We found that genes associated with the signalling mole-cules jasmonate, auxin, and cytokinin were significantlyover-represented among genes up-regulated by DBM feed-ing based on a hypergeometric distribution (p [hyper]< 0.05) (Figure 4). For comparison, while 11% of allprobes on the microarray that are associated with an AGIidentifier were differentially expressed upon DBM feed-ing, 44% of the genes associated with jasmonate biosyn-thesis, signalling, or response were differentially expressedupon DBM feeding, and all were significantly up-regu-lated in at least one time point (Figure 4 and Figure 5). Incontrast, genes associated with the signal compounds sal-icylic acid and ethylene were not more frequently differ-entially expressed than expected for any randomly chosengroup of genes. In contrast to jasmonate-related transcrip-tome signatures, many genes related to salicylic acid andethylene signalling were transiently down-regulated fol-lowed by a late induction during DBM feeding (Figure 4and Figure 5).Genes associated with gibberellic acid, brassinosteroids,and abscisic acid were also not over-represented amongthe differentially expressed genes (Figure 4). However,among those genes that were differentially expressed,most genes associated with abscisic acid were rapidly up-regulated upon herbivory, while genes associated withgibberellic acid were predominantly down-regulated (Fig-ure 4 and Figure 5).In addition to genes associated with jasmonate signalling,genes associated with the hormones auxin and cytokininwere also over-represented in the DBM affected transcrip-tome (Figure 4). While three cytokinin oxidase familymembers involved in cytokinin catabolism were up-regu-lated late in the feeding experiment, several cytokininresponse regulators are transiently down-regulated duringherbivory (Figure 5). Likewise, a large group of auxin-induced genes were transcriptionally down-regulatedstarting at 4 h after the onset of herbivory feeding (FigurePage 7 of 20(page number not for citation purposes)4). However, a smaller group of genes in the same groupdisplayed a reverse expression pattern, as did some genesBMC Genomics 2008, 9:154 http://www.biomedcentral.com/1471-2164/9/154involved in auxin metabolism and the auxin-responsetranscription factor MONOPTEROUS (Figure 5) [34].Overall, our results highlight the importance of jasmonateExpression profiles of genes associated with signal transductionTo gain insights into possible signalling processes elicitedby DBM feeding, we analyzed expression profiles of genesknown or predicted to be involved with signal transduc-tion such as protein kinases, transcription factors, andgenes involved in the 26S proteasome pathway (Figure 6).For these genes we retrieved information for completegene families from PlantsP (protein kinases [35]), AtTFDB(transcription factor families [36]), and PlantsUBQ (26Sproteasome gene families [37]).Of the 902 protein kinases present on the microarray, 98were differentially expressed, 71 were up-regulated, while27 were down-regulated (Additional File 2). Fourteenkinases were differentially expressed in at least two timepoints (Figure 6). Most genes in this group code for recep-tor-like kinases such as leucin rich repeat (LRR) and pep-tido-glucan (LysM) binding domain containing kinases.In addition, two mitogen activated protein kinase kinasekinases (MAPKKK) were transcriptionally up-regulated:ANP2 (At3g46160) is a MAPKKK protein related to Nico-tiana protein kinase 1 (NPK1) which may negatively regu-late stress responses [38]; and Raf27 (At4g18950)contains an ankyrin domain but has not been furthercharacterized. A calcium-dependent protein kinase,At2g3036 (CIPK11, SnRK3.22) which is a member of aplant specific protein kinase family that specifically inter-acts with the calcium sensor protein CalcineurinB-like[39], was also up-regulated by DBM feeding. Finally, twoAGC kinases (protein kinases A, G, and C), which belongto a family of effectors of the intracellular second messen-gers cAMP, cGMP, phospholipids, and Ca2+ [40], were up-regulated upon herbivory.Among the 1,409 transcription factors represented on thearray, 173 were differentially expressed in at least one timepoint, with 118 being up-regulated and 53 down-regu-lated, while two displayed a mixed expression (AdditionalFile 2). Thirty five transcription factors were differentiallyexpressed in at least two time points, ten of which weredown-regulated and 25 were up-regulated (Figure 6).Among the ten down-regulated transcription factors, basichelix loop helix (bHLH) and homeodomaine binding(HB) proteins of the HD-ZIP II class form the dominantgroup. Transcription factors that were up-regulated byDBM feeding predominantly belong to AP2-EREBP, MYB,and NAC type factors (Figure 6). Notably, three MYB andthree AP2-EREBP factors were up-regulated rapidly within1 h after the onset of DBM feeding and stayed up-regu-lated. Expression of all five AP-EREBP transcription factorsfound to be DBM-induced by microarray analysis alsoshowed highly similar expression profiles when validatedDifferential expression of genes associated with signalling mol culesFigu  4Differential expression of genes associated with sig-nalling molecules. Based on curator annotated Gene Ontology categories at TAIR, A. thaliana genes were identi-fied that are (i) involved in the metabolism of, (ii) are part of the signal transduction mediated by, or (iii) are responsive to signalling compounds (i.e., ABA: abscicic acid; AUX: auxin; BS: brassinosteroid; CYT: cytokinin; ETH: ethylene; GA: gib-erellic acid; JA: jasmonates; SA: salicylic acid). Fractions of genes that are differentially expressed upon DBM herbivory (in % of the genes in each category) in at least one time point (p[t-test] < 0.05, fold-change > 2) are shown. The fraction of down-regulated genes is shown in dark grey, the fraction with mixed expression over the time course in medium grey, and the fraction of up-regulated genes in light grey. Stars indi-cate that the frequency of differentially expressed genes in the given functional group is significantly higher (p[hyper] < 0.05) than the frequency observed in the set of all genes rep-resented on the microarray.ABA AUX BS CYT ETH GA JA SAdifferentially expressed [%]upmixdown***Page 8 of 20(page number not for citation purposes)in herbivore induced signalling, and may also suggestroles for cytokinin and auxin as well.by qRT-PCR (Figure 7). Although several AP2-EREBP typetranscription factors have been associated with regulatingBMC Genomics 2008, 9:154 http://www.biomedcentral.com/1471-2164/9/154stress responses, to date none of the transcription factorsidentified here has been characterized in detail. Amongthe DBM-induced MYB transcription factors, onlyMYB34/ATR1 has previously been characterized as a pos-itive regulator of indole glucosinolate biosynthesis [41],which is consistent with results that most of its targetgenes were up-regulated by DBM feeding (Figure 3, Addi-tional File 2).Targeted protein degradation via the ubiquitin/26S-pro-teasome pathway is another important regulatory process[42]. Among the 1,403 Arabidopsis genes annotated to beinvolved in this pathway, 1,230 are present on the arrayand 82 were differentially expressed upon DBM feeding(Additional File 2). Among these are a 75 putative E3-ubiquitin-protein-ligases that were affected by DBM, inaddition to five differentially expressed 26S-proteasometwo were down-regulated). Figure 6 shows the expressionprofile of ten different E3-ubiquitin-protein-ligases thatwere differentially expressed in at least two time points. Insummary, we identified a large number of signal transduc-tion components affected by DBM feeding. In particular,members of the AP2-EREBP family of transcription factorsstand out as being rapidly induced by herbivory suggest-ing roles for this family in DBM induced signal transduc-tion networks.DiscussionInfestation by feeding DBM larvae induces substantialoverall changes in the Arabidopsis leaf transcriptome,with 1,854 array elements representing 1,664 annotatedgenes that were significantly induced and 1,007 elementsrepresenting 913 annotated genes that were repressed sig-nificantly. Despite continuous feeding the majority of dif-Expression profiles of hormone related genes affected by DBM feedingFigure 5Expression profiles of hormone related genes affected by DBM feeding. Based on curator annotated Gene Ontology categories at TAIR, A. thaliana genes were identified that are (i) involved in the metabolism of, (ii) are part of the signal trans-duction mediated by, or (iii) are responsive to signalling compounds (i.e., ABA: abscicic acid; AUX: auxin; BS: brassinosteroid; CYT: cytokinin; ETH: ethylene; GA: gibberellic acid; JA: jasmonate; SA: salicylic acid). Shown as a heatmap are genes in these categories that are differentially expressed upon herbivory in at least one time point (p[t-test] < 0.05, fold-change > 2). Bright Red indicates a more than 5.7-fold higher transcript abunance in herbivore treated plants compared to control plants; bright blue indicates a more than 5.7 fold lower expression. AGI information and gene names are given on the right, for detailed information on each gene see Additional File 2.1 4 8 24 hDBMAt3g03840At4g34760At4g34770At4g34790At4g34810At4g38840At4g38860At5g18010At5g18050At5g18080At5g19140log2DBMcontrol(        )-3 3At1g77330 ACOAt4g37770 ACS8At2g25450At2g30840At3g04720 PR4At1g55880At2g22810At2g14580 PRB1abscisic acidauxinbrassinosteroidjasmonic acidsalicylic acidAt3g50410 OBP1At5g36970 NHL25At1g55490 LEN1At2g14610 PR1At2g14580 ATPRB1At4g18350 NCED1At5g63980 FRY1At1g20450 LTI29At2g33380 RD20At4g24960 HVA22DAt4g34710 ADC2At5g59320 LTP3At3g43600 AAO2At5g45820 PKS18gibberellic acidcytokininAt2g46370 JAR1At1g13280 AOC4At1g76680 OPR1At3g25760 AOC1At3g25780 AOC2At3g45140 LOX2At5g42650 AOSAt1g20510 OPCL1At1g17420 LOXputAt1g72520 LOXputAt1g76690 OPR2At2g06050 OPR3At2g24850 TAT3At4g34710 ADC2At2g14580 ATPRB1At1g02400 GA2OXAt2g30810At1g14920 GAIAt3g51060 STY1At5g15230 GASA4At1g74670At2g18420At5g54510 DFL1At1g44350 ILL6At3g02875 ILR1At5g54140 ILL3At2g20610 SUR1At4g31500 CYP83B1At1g15050 IAA34At1g19850   MPAt3g23050 IAA7At3g50410 OBP1At2g21200At2g23170At2g45210At2g46370At3g12830At4g12410At4g22620At5g03310At5g13360At1g70940 PIN3At2g01420At2g06850 EXGT-A1At3g15540 IAA19At4g28640 IAA11At4g32280 IAA29At1g17345At1g28130At1g29420At1g29430At1g29440At1g29450At1g29460At1g72430At2g18010At2g21220At2g22810At3g03830At1g75080 BZR1ethyleneAt2g19500 CKX2At4g29740 CKX4At1g70510 KNAT2At3g63440At1g59940 ARR3At2g40670 ARR16At3g48100 ARR5auxin (cont’d)1 4 8 24 hDBM1 4 8 24 hDBMPage 9 of 20(page number not for citation purposes)components, a single ubiquitin-like gene and a E2-ubiq-uitin activating enzyme (UBC10, At5g53300) (the latterferentially expressed genes displayed a transientexpression profile with a maximum transcript abundanceBMC Genomics 2008, 9:154 http://www.biomedcentral.com/1471-2164/9/154Page 10 of 20(page number not for citation purposes)Gene expression profiles of genes associated with signal transduction componentsFigur  6Gene expression profiles of genes associated with signal transduction components. Gene information was retrieved from PlantsP (protein kinase families), AtTFDB (transcription factor families), and PlantsUBQ (26S proteasome gene families). 902 protein kinases were present on the array used for DBM herbivory profiling, of which 14 were differentially expressed in at least two time points. 35 transcription factors were differentially expressed in at least two time points among the 1,409 genes represented on the array used. Expression profiles of these genes are displayed as heatmaps: Bright red indi-cates a more than 5.7-fold higher expression in herbivore treated plants compared to control plants; bright blue indicates a more than 5.7-fold lower expression. Grey indicates missing data. AGI information and sub-family names are given on the right. Gene names are indicated in brackets were applicable. For detailed information on each gene see Additional File 2. The left panel shows results obtained upon DBM treatment (this study). To the right previously published results for the same genes obtained with large scale expression profiling experiments upon herbivory with P. rapae, F. occidentalis, and M. persicae are given (aCATMA array platform [3]; bAffymetrix ATH1 array platform [1])(         )treatmentcontrollog2-3 0 3 KinasesTrancription FactorsUbiquitin LigasesMAPKKK (RAF27)LRR-RLKSnRK (CIPK11)AGC (AGC2-1)RLCKAGC (NDR5)LRR-RLKLRR-RLK (SRF5)RLCKMAPKKK (ANP2)LysM-RLKL-RLKLysM-RLKRLCKMYB (MYB15)AP2-EREBPAP2-EREBPAP2-EREBP (RAP2.6)NAC (ANAC019)AP2-EREBPNAC (ANAC055)WRKY (WRKY40)NAC (ANAC046)NAC (ANAC062)C2H2 (ZFP1)MYB (MYB34, ATR1)MYB (MYB95)WRKY (WRKY60)bZIP (bZIP7)bHLH (PIF3, PAP3)AP2-EREBPC2H2C2H2 (JAG)bHLH (bHLH121)MYB (MYB54)C3HMADS (AGL99)CCAAT-HAP2HBBPC (BPC1)HB (HAT4, AtHB-2)ARR-BbHLH (bHLH060)HB (HAT3)GRAS (GAI)HB (HAT1)bHLH (bHLH058, BEE2)bHLH (bHLH064)HCa-RINGEHCa-RINGUbox-RINGC2-RINGA3v-RINGB7B4D2-RING12 24P. rapaeP. xylostella   (DBM) 1 4 8 24 24 48 48 72M. persicae5F. occidentalisha b b b b b bgroup IIIgroup IIgroup Igroup IIIgroup IIgroup Igroup IIIgroup IIgroup IBMC Genomics 2008, 9:154 http://www.biomedcentral.com/1471-2164/9/154Page 11 of 20(page number not for citation purposes)Comparison of qRT-PCR and microarray expression data for AP2-EREBP genesFigure 7Comparison of qRT-PCR and microarray expression data for AP2-EREBP genes. The five AP2-EREBP genes found up-regulated in the microarray data (see Figure 6) and two AP2-EREBP genes that were not significantly differentially expressed as detected on the microarray were tested for RNA abundance using quantitative real time RT-PCR. As an internal standard, expression levels of At5g62700 (TUB, tubulin) was used to determine relative expression levels in each sample (ΔCT values). Shown in green are the ΔΔCT values comparing ΔCT values of DBM treated samples with untreated control samples at 1 h, 4 h, 8 h, 12 h, and 24 h of continuous feeding (right scale bar). For comparison, normalized log2-expression ratios found using the microarray platform are given in blue (left scale).At2g20880 - AP2-EREBP1 4 8 12 24h53210402010030RT-PCR [ΔΔCT (sample/control)]4At5g13330 - AP2-EREBP1 4 8 12 24h2102103array [log 2(sample/control)]At4g34410 - AP2-EREBP1 4 8 12 24h4321015963012array [log 2(sample/control)]At3g57600 - AP2-EREBP1 4 8 12 24h210-1-230-2-32RT-PCR [ΔΔCT (sample/control)]At3g57600 - AP2-EREBP1 4 8 12 24harray [log 2(sample/control)]210-1-23.00-1.5-3.01.5RT-PCR [ΔΔCT (sample/control)]1 4 8 12 24h32050302010040RT-PCR [ΔΔCT (sample/control)]1At1g43160 - AP2-EREBP1 4 8 12 24h2102015105025array [log 2(sample/control)]At1g28370 - AP2-EREBP (ERF11)time [h](negative control)(negative control)arrayRT-PCR1-1time [h]BMC Genomics 2008, 9:154 http://www.biomedcentral.com/1471-2164/9/154level at 8 h after onset of feeding and were down to theirinitial transcript level after 24 h (clusters B and C, Figure2). It is not known what proportion of the inducedchanges of the transcriptome result in any downstreamchanges; and it is possible that some defence responsesonly require a transient burst at the level of the transcrip-tome to become effective and a large part of the initialresponse could return to the pre-attack steady-state levelof gene expression. Repressor proteins, such as therecently discovered JAZ proteins involved in the media-tion of jasmomate signalling [13,14], may be involved inshaping such rapid and transient responses.Although only a few plant species have been studied forthe impact of insect attack on large-scale transcriptomechanges, their diversity ranges from relatively short-livedherbaceous plants to long-lived trees, includingangiosperms and gymnosperms. Results obtained withthese systems support the general notion that insect feed-ing induces massive changes of the host plant transcrip-tome [1-6,43,44]. A few general patterns have emergedfrom these studies suggesting that herbivory can results indown-regulation of primary metabolic processes while atthe same time activating defence related processes includ-ing secondary defence metabolism. These findings arewell supported by our analysis of the Arabidopsis tran-scriptome affected by DBM feeding. In addition, the mas-sive reprogramming of primary and secondary metabolicprocesses as part of the insect-induced defence responseinvolves rapid changes in signalling and other regulatoryprocesses. The present study establishes a signature ofDBM-induced changes of the signalling transcriptome ofArabidopsis leaves.In order to more broadly identify common patterns of thetranscriptome response of Arabidopsis to different herbiv-ores, we compared data obtained in this study with otherlarge scale expression analyses that used different arrayplatforms to study the transcriptome responses inducedby P. rapae [1,3,5], S. littoralis [5], F. occidentalis [1], B.tabaci [2], M. persica [1,15], and B. brassicae [15] (Figure 8;see figure legend for details on the platforms used and thetime points analysed). Despite the large differences in thebiological materials and the different array platforms used(in particular the coverage of the array platforms variedgreatly), which precludes complete comparisons, a sub-stantial overlap in the groups of up- or down-regulatedgenes was apparent (Figure 8). The highest relative degreeof overlap of the DBM-affected transcriptome was foundwith the effect of S. littoralis, as DBM a leaf chewing cater-pillar, with 47% (41 genes) of differentially expressedgenes common on both platforms being induced by bothS. littoralis and DBM. Similarly, between 32% and 40%in our analysis with DBM agreed in their general induc-tion (Figure 8). Both P. rapae and DBM are leaf chewingcaterpillar specialized to the Brassicacea. Overall lowerdegrees of relative overlap in the group of induced geneswere found when the response induced by DBM was com-pared with the responses induced by cell-sucking thrips, F.occidentalis, or the phloem sap-feeding herbivores M. per-sicae, B. tabaci, and B. brassica with 11% to 31% of inducedgenes found in common. In this comparison, the highestrelative degree of overlap was found with the aphid B.brassica, which is as DBM a specialist herbivore. Togetherthese comparisons suggest that herbivores with a similarmode of feeding may induce a more similar transcriptomeresponse in the host.Surprisingly, in the meta-analysis of all microarray datarepresented in this comparative Arabidopsis-herbivorytranscriptome study (Figure 8 and Additional File 3), wefound only one gene being up-regulated in nine of the tenexperiments compared: The cytochrome P450 monooxy-genase CYP79B2, which catalyzes the conversion of tryp-tophan to indole-3-acetaldoxime, the precursor of indoleglucosinolates, camalexin, and also auxin [26,29,30,45].Six additional genes were found up-regulated in eight ofthe ten experiments, including three other genes related totryptophan metabolism and glucosinolate biosynthesis aswell as the jasmonate inducible tyrosine aminotransferaseTAT, which is involved in tocopherol biosynthesis[22,46]. An additional 40 genes were found induced in atleast six of the experiments compared (Additional File 3),and almost half of these (18 genes) were found in theGeneOntology category 'response to stress' includinggenes encoding enzymes of the shikimate pathway (inparticular the tryptophan branch), phenylpropanoidmetabolism, glucosinolate bioynthesis, glutathionemetabolism, and chlorophyll degradation (AdditionalFile 3). Genes encoding functions in the octadecanoidpathway were also found induced in most of the individ-ual datasets of this comparative Arabidopsis-herbivorytranscriptome meta-analysis. The role of octadecanoids inmediating herbivore-induced responses is well estab-lished, and it has been estimated that up to 80% of all her-bivore-induced Arabidopsis genes are octadecanoidregulated [5].Our analysis of the DBM-induced response in Arabidopsisagrees with the central role of ocatdecanoids since jas-monate related genes were significantly over-representedin the set of DBM-induced genes. While auxin and cytoki-nin related genes also appear to be involved in differentaspects of the responses to DBM, in contrast to the jas-monate related genes, a substantial portion of the cytoki-nin and auxin related genes were down-regulated (FiguresPage 12 of 20(page number not for citation purposes)(56 to 204 genes) of those genes that are in common tothe respective platforms used in studies with P. rapae and4 and 5). Cytokinin and auxin are important in the con-trol of plant morphogenesis and frequently act antagonis-BMC Genomics 2008, 9:154 http://www.biomedcentral.com/1471-2164/9/154Page 13 of 20(page number not for citation purposes)Venn diagrams comparing the DBM induced transcriptome changes with the response to other herbivoresFigure 8Venn diagrams comparing the DBM induced transcriptome changes with the response to other herbivores. The number of induced (up-regulated, left column) and repressed (down-regulated, right column) genes upon DBM feeding (indicated by blue circles) was compared with the response to other herbivory treatments that have previously been published [1-3,5,15]. Circle areas are drawn to scale to the number of genes found differentially expressed (DE). Given with absolute numbers and in percent is the fraction of differentially expressed genes that is regulated in the same overall manner in the two datasets of comparison (overlapping area), or that is affected only by DBM or only by the other herbivore. In A to G the frac-tion of differentially expressed genes found in a given experiment that is not present on the other array is shaded in lighter col-ours. For H and I the necessary microarray platform information for a detailed comparison are unpublished. If more than one time point or more than one ecotype were used, a gene was defined as DE if it was up- or down-regulated in at least one of the different treatments with the same herbivore using the same array platform. A) Herbivore: Piris rapae; Arabidopsis ecotype: Col; time point: 5 h; definition of DE: p(t-test) < 0.05 & foldchange > 2 (replicates: n = 7); platform: CATMA array, unique AGI loci: 15,722 [3]. B) P. rapae; Col; 12 h or 24 h; DE: 'present' in at least one array & foldchange > 2 (n = 1); Affymetrix ATH1, unique loci: 21,833 [1]. C) P. rapae; Col; 3 h to 5 h, 24 h local, or 24 h distal; DE: p(t-test) < 0.05 & foldchange > 2 (n = 5); plat-form: cDNA array, unique AGI loci: 7,200 [5]. D) Spodoptera littoralis; Col; 3 h to 5 h; DE: p(t-test) < 0.05 & foldchange > 2 (n = 5); platform: cDNA array [5]. E) Frankliniella occidentalis; Col; 12 h or 24 h; DE: 'present' in at least one array & foldchange > 2 (n = 1); platform: Affymetrix ATH1 [1]. F) Bemisia tabaci; Col; 21d; DE: SAM q < 3.917% & foldchange > 2 (n = 2); platform: Affymetrix ATH1 [2]. G) Myzus persicae; Col; 48 h or 72 h DE: 'present' in at least one array & foldchange > 2 (n = 1); platform: Affymetrix ATH1 [1]. H) M. persicae; Ws, Cvi, or Ler; 1d; DE: q(t-test) < 0.05 & foldchange > 2 (n = 4); oligo-array, unique AGI loci: 2,158 [15]. I) Brevicoryne brassicae; Ws, Cvi, or Ler; 1d; DE: q(t-test) < 0.05 & foldchange > 2 (n = 4); oligo-array [15]. Data for all pairwise comparisons as well as the numbers for multiple intersects are given in Additional File 3. This table also contains information on all genes being called DE in at least one experiment.116826482%18%22%232F. occidentalis91878%13661100412784%89% 16%11%12510S. littoralis4641 53%9%47%4571341>99%1<1%100%P. rapae436875688% 61%12%39%11821257133999%31%100%1260 22614889%60%11%40% P. rapae256347619999%50%1%50%8143P. rapae1228 43420486%68%14%32%232137362395293%82%7%18%3125M. persicae1225163420786% 89%14%11%232 23683103510587%91% 13%9%12591610 14154 116 89716M. persicae1614 11150 100 89815B. brassicae up-regulated  down-regulatedP. xylostella (DBM) P. xylostella (DBM)134994%23256487%56836%13%B. tabaci71041790%84%125627810%16%1182chewing specialistchewing generalistcell sucking generalistphloem feeding generalistphloem feeding specialistABCDEFGHIBMC Genomics 2008, 9:154 http://www.biomedcentral.com/1471-2164/9/154tically [47-49]. Cytokinin is known to promote celldivision, delays leaf senescence and may have a role inreallocation of resources from source to sink tissues [50].In previous studies, auxin levels were found to bedecreased in tobacco and maize after wounding or uponherbivore infestation [51,52], and external application ofauxin decreased wound responses including productionof jasmonate [53] and proteinase inhibitor gene expres-sion [51]. Auxin related genes were also found to bedown-regulated in wounded Arabidopsis plants [54].Thus, auxin- and jasmonate-dependent processes may besubject to opposite regulation in the plant response towounding or herbivory. In support of this notion, wefound that many of the stress-related signal transductioncomponents induced upon DBM herbivory are alsoinduced by methyl jasmonate, but are repressed by auxin(Figure 9).In the present study we identified a large number of tran-scripts that are affected by DBM feeding and are broadlyassociated with signal transduction components (exam-ples are highlighted in Figure 6 and the complete data setMeta-analysis of DBM-affected signalling elementsFigure 9Meta-analysis of DBM-affected signalling elements. Expression data (normalized intensities) based on publicly available Affymetrix microarray hybridization data were retrieved from the Genevestigator database [55]. All probe sets called absent were set to the mean intensity of these undetectable probe sets for each gene. If replicate experiments were performed the mean intensity of all replicates was calculated. Expression ratios for all treatment experiments were generated using the corre-sponding control experiments and the log2 transformed ratios were used to generate a heatmap. Each column represents one experiment; each row represents one of the candidate genes as indicated to the right. Bright Red indicates a more than 5.7 fold higher expression in treated plants compared to control plants; bright blue indicates a more than 5.7 fold lower expression.  AGC (AGC2-1)MAPKKK (RAF27)LRR-RLKSnRK (CIPK11)RLCKRLCKLRR-RLK (SRF5)RLKL-RLKMAPKKK (ANP2)LysM-RLKLRR-RLKRLCKMYB (MYB15)AP2-EREBPAP2-EREBPNAC (ANAC019)NAC (ANAC055)WRKY (WRKY40)NAC (ANAC046)NAC (ANAC062)C2H2 (ZFP1)WRKY (WRKY60)AP2-EREBPbHLH ( PIF3, PAP3)AP2-EREBPAP2-EREBPC2H2MYB (MYB34, ATR1)MYB (MYB95)CCAAT-HAP2C3HMYB (MYB54)bHLH (bHLH121)C2H2 (JAG)MADS (AGL99)HBBPC (BPC1)HB (HAT4, AtHB-2)ARR-BbHLH (bHLH060)HB (HAT3)GRAS (GAI)HB (HAT1)bHLH ( BEE2)bHLH (bHLH064)HCa-RINGEUbox-RINGC2-RINGA3HCa-RINGv-RINGProtein KinasesTranscription Factors26S-Proteasome (Ubiquitin ligases)P. xylostella (DBM)bacterial    pathogens (local)bacterial    pathogens (sytemic)fungal pathogensoomycetal pathogenselicitorscold stressosmotic stresssalt stressdrought stressgenotoxic stresswoundingUV stressoxidative stressheat stresslight stressmetal and toxic stressauxincytokiningiberrelinabscisic acidsalicylic acidjasmonateethylenebrasinosteroidgroupIIIIIIIIIIIIIIIherbivoreslog2treatmentcontrol(           )-3        3        Page 14 of 20(page number not for citation purposes)Brief descriptions of the experimental treatments are given on top. Details on each experiment are given in Additional File 4.BMC Genomics 2008, 9:154 http://www.biomedcentral.com/1471-2164/9/154is provided in Additional File 2). Transcriptome patternsassociated with signalling in insect attack have not beenwell established. In other plant species this is largely dueto the smaller array platforms commonly available thatmay not include many transcription factors or other sig-nalling features. Also, lack of relevant reference datasetssuch as those obtained from array analyses of other stresstreatments in the same plant species make meta-analysesof signalling transcriptomes currently a difficult task formost plant species, except for Arabidopsis. We establisheda first meta-analysis of DBM-induced regulatory proteins(protein kinases, transcription factors, ubiquitin ligases)to integrate results obtained in the present microarrayanalysis of DBM-induced Arabidopsis leaves with previ-ously published Arabidopsis microarray data from vari-ous treatments related to biotic and abiotic stress response(Figure 9, Additional File 4). Specifically, we selectedmicroarray data from a total of 295 Arabidopsis samplestreated with a wide range of biotic and abiotic stresses,phytohormones and biological elicitors, or other chemi-cals (Figure 9, Additional File 4). The data analyzed in thiscomparison are based on the Affymetrix ATH1 platform,were retrieved from the 'Genevestigator' database [55],and were processed as described in Additional File 4.Based on this meta-analysis, the DBM-affected transcrip-tion factors and other signalling components identified inour experiments can be divided into two large classes: (i)those that are responsive to a wide range of differentforms of biotic and abiotic stress [Figure 9, group I(induced) and group III (repressed)]; and (ii) those thatare not effected by most other treatments of this compar-ison (Figure 9 and Additional File 4, group II).Signalling components in group-I and group-III thus con-stitute candidates involved generally in stress perceptionand transduction. Group-I and group-III transcription fac-tors include all DBM-affected AP2-EREBP genes, thebHLH PIF1, WRKY80, WRKY40, the C2H2 At5g04340,MYB15, and all DBM-effected NAC type transcription fac-tors. Most of these genes were also found to be induced byother herbivores, although with notable exceptions (Fig-ure 6). For example, the AP2-EREBP At2g2088 is rapidlyand strongly induced by DBM feeding, but appears unaf-fected by the other herbivore treatments, while treatmentswith some bacterial or fungal pathogens, drought, andabscisic acid lead to transiently induced expression (Addi-tional File 4).Signalling components in group-II appear to be specific toDBM treatment, as they were not found induced in mostother stress treatment (Figure 9). However, lack of induc-tion in other treatments needs to be interpreted cau-tiously, since different expression profiling platforms werewere also found induced upon herbivory with P. rapaeand M. persicae, respectively (Figure 6) but were foundinduced in only three and five, respectively, of the other297 stress treatments (Figure 9 and Additional File 4). JAGhad previously been shown to be necessary for the devel-opment and shaping of lateral organs such as leaves [56].Taken together, we identified a large set of signal transduc-tion components that likely orchestrate a rapid and gen-eral response to a wide range of external stresses, but alsoa large set of signaling components that may mediateresponses more specific to plant-herbivore responses.Very few of the protein kinases, transcription factors andubiquitin ligases that are affected by DBM feeding (Figure9, Additional File 4) have well characterized functions. Anotable exception is the transcription factor MYB34/ATR1(At5g60890), which encodes a positive regulator ofindole glucosinolate biosynthesis. ATR1 has previouslybeen implied in insect-induced signalling [41] and isinduced in particular late into the DBM feeding experi-ment. ATR1 was also found induced upon herbivory by P.rapae [3], but appears repressed upon treatment with F.occidentalis and M. persicae [1] (Figure 6). Three additionaltranscription factors, the two AP2-EREBP RAP2.6(At1g43160) and At2g20880 as well as MYB15(At3g23250), were previously identified as induced bywounding, methyl jasmonate, various pathogens, andseveral forms of abiotic stress [57].ConclusionThe Arabidopsis transcriptome changes substantially inresponse to leaf feeding DBM larvae. Major DBM inducedchanges are involved in specialized (secondary) defencemetabolism and in signalling. The DBM induced responseshows considerable overlap with the response induced byother insect herbivores. A first large-scale meta-analysis ofArabidopsis microarray data obtained for a large numberof biotic and abiotic interactions revealed groups of tran-scription factors and other signalling components that aresimilarly affected by multiple forms of biotic or abioticstress including DBM feeding or, alternatively, appearmore specifically responsive to DBM herbivory.MethodsPlant and insect materialsArabidopsis thaliana plants (ecotype Landsberg erecta) weregrown in plastic pots (10 cm wide × 8 cm tall) containingTerra-lite Redi-earth (W.R. Grace and Co., Ajax, Ontario,Canada). Each pot contained four or five plants, whichwere grown in a growth chamber at 20°C constant tem-perature, 8 hr/16 hr Light/Dark photoperiod at 50–60%ambient humidity, for 8 to 9 weeks. Short day conditionsprevented the onset of flowering and the plants were thusPage 15 of 20(page number not for citation purposes)used. The transcription factors JAG (At1g68480) andbHLH121 (At3g19860), which are members of group II,maintained in growth stage 1 (leaf production) with 13 to15 rosette leaves larger than 1 mm (stage 1.13 to 1.14).BMC Genomics 2008, 9:154 http://www.biomedcentral.com/1471-2164/9/154Diamondback moth (DBM, Plutella xylostella) larvae wereprovided by Dr. Murray Isman (Faculty of Agricultural Sci-ences, University of British Columbia, Vancouver, Can-ada) and maintained on cabbage (Brassica oleracea) plantsin a climate-controlled room at 25°C, 12 hr photoperiodwith 50%-60% relative humidity. Two days before expos-ing A. thaliana plants to herbivore treatment, plants weretransferred to a climate-controlled room (22°C, 50–60%humidity, 12 hr photoperiod). For insect treatment, sevenDBM larvae (third to fifth instars) were placed on a groupof four or five plants until time of harvest, for each timepoint separately. As control, Arabidopsis plants weremaintained under the same condition except withoutexposure to DBM larvae. Rosette leaves from DBM-exposed and control plants were harvested at 1 h, 4 h, 8 h,12 h and 24 h after onset of herbivory. For each treatmentgroup and time point, all rosette leaves were harvestedfrom the four or five plants per treatment group and flashfrozen in liquid nitrogen.Microarrays, RNA isolation, cDNA labelling, and microarray hybridizationThe design and production of the A. thaliana 26,090 ele-ment 70-mer oligonucleotide microarray was previouslydescribed with oligonucleotides designed in collabora-tion with and purchased from Operon (Huntsville AL,USA) [9]. All procedures for RNA isolation, RNA labellingand microarray hybridization were performed asdescribed [9]. Microarray experiments involved two inde-pendent biological replicates for each time point andtreatment with each replicate consisting of four or fiveplants to provide enough plant material for RNA isola-tion. In addition, microarray hybridizations for each timepoint and treatment were performed with two technicalreplicates (dye-flip labelling) for each of the biologicalreplicates for a total of four dual channel microarrayhybridizations per time point comparing treatment withcontrol.Microarray data analysisMicroarrays were scanned with a ScanArray Express (Per-kin Elmer, Woodbridge ON, Canada) scanner with laserpower set to 95% and photo-multiplier-tube set to 54 to64. We identified and quantified hybridization signalsusing ImaGene software (BioDiscovery, Marina Del ReyCA, USA). Grids were manually placed and spot findingwas performed using the 'Auto adjust' spot functionrepeated three times. Spot finding was subsequently veri-fied by visual inspection and manually adjusted whennecessary. Poor spots were manually flagged (flag 1) andwere not used in further data analyses. For all analyses, themedian pixel intensities for each spot were used. Allmicroarray expression data were submitted to the GEOR and Bioconducter [59]. For background correction, wedefined the mean of the lowest 10% of spot intensitiesfrom a particular subgrid as the background for that sub-grid. This mean was subtracted from each spot in the sub-grid. Signal intensities that did not exceed the backgroundplus 3 standard deviations thereof were defined as notdetectable and were excluded from further analyses. Wenormalized using loess curves [60]. For each array ele-ment, we first used the data from the four replicate arrayhybridizations (two biological replicates each with twotechnical replicates) for each time point and treatment toperform a paired Student's t-test using the Welch approx-imation to degrees of freedom. Subsequently, an analysisof variance (ANOVA) using data from all experimentalsamples (four normalized log2-expression ratios per timepoint for a total of 20 data points) was performed for eachelement. In order to assess the type I error rate, we calcu-lated q-values estimating the false discovery rate based onthe parametric p-values [17]. Genes were first placed intoone of three expression groups: Group A) up-regulatedgenes displaying a significant (p[t-test] < 0.05) and morethan twofold higher signal in insect treated leaves com-pared to control leaves in at least one time point; GroupB) down-regulated genes displaying a significant (p <0.05) and more than twofold lower signal in insect treatedcompared to control plants in at least one time point; andGroup C) genes with mixed expression using the samedefinition as in A and B. For clustering, mean log2-expres-sion ratios for genes identified as differentially expressed(DE) in at least one time point were used. To derive at areliable dataset, we defined genes as DE only if they metall of the following criteria: (1) significant (p[t-test] <0.05) and more than twofold difference of transcriptabundance between treatment and control for at least onetime point, and (2) change of expression of more thantwofold between at least two time points of the treatmenttime course with p(ANOVA) < 0.05. K-means clustering ofDE genes was performed using Genesis v1.5 [61] definingnine clusters with a maximum of 50 iterations. The nor-malized expression ratios and the results for all statisticalanalyses are summarized in Additional File 1.Analyses of genes of interestGene lists containing selected genes of interests wereretrieved from 'The Arabidopsis Resource Informationdatabase' (TAIR) [18] or from published gene family com-pilations. Lists of genes involved in "response to pathogensor wounding" were retrieved from TAIR (status December2004). We selected genes placed in the GeneOntology(GO) categories "involved in" the "biological process""response to pest, pathogen, or parasite" and/or "response towounding". Because of the large number of genes ofuncharacterized functions associated with the GO-terms,Page 16 of 20(page number not for citation purposes)database [58] under the accessions series GSE10681. Fur-ther analyses were performed using customized scripts forwe only selected genes if they were also curator annotatedbased on experimental evidence by TAIR. Children termsBMC Genomics 2008, 9:154 http://www.biomedcentral.com/1471-2164/9/154of these GO categories were also included in the selectionof these genes. Lists of complete gene families involved in"Arabidopsis secondary metabolism of glucosinolates, phenyl-propanoids, or terpenoids" were compiled based on pub-lished surveys of the Arabidopsis genome [9-11,32].Complete lists of putative "protein kinases, transcription fac-tors", and genes involved in the "26S proteasome pathway"were retrieved from the PlantsP (protein kinase families[35]), AtTFDB (transcription factor families [36]), andPlantsUBQ (26S proteasome gene families [37]) data-bases, respectively. For analysis of genes associated with"phytohormones or signalling compounds", curator annotatedgenes placed in the GO terms "involved in the metabolismof", "involved in the signalling mediated by", or "involved inthe response to" the phytohormones or signalling mole-cules "auxin", "abscisic acid", "brassinosteroid", "cytokinin","ethylene", "gibberellic acid", "jasmonic acid", and "salicylicacid" were retrieved from TAIR. Each of these gene listswas filtered to avoid multiple entries per list of the samegene.Expression data for members of these gene lists that werefound differentially expressed in our experiments accord-ing to the DE definition described above were visualizedas heatmaps using Genesis v1.5 [61]. To assess if any ofthe groups of genes associated with phytohormones orsignalling compounds was significantly overrepresentedin the insect-effected Arabidopsis transcriptome, the fre-quency of differentially expressed genes associated witheach of the different phytohormones or signalling com-pounds in the groups A, B, and C (see above) was com-pared to the frequency of all genes associated with thesecategories represented on the microarray using a hyperge-ometric distribution. Phytohormone or signalling com-pound GO groups were defined as significantly over-represented in the group of differentially expressed genes,when p[hyper] < 0.01.Quantitative real time RT-PCR (qRT-PCR)Total RNA (15 μg) was digested with 15U DNAse in 1 ×buffer (Invitrogen, Carlsbad CA, USA) for 15 min at roomtemperature. The reaction was stopped with EDTA (2.3mM final concentration) and heat-inactivation (65°C, 10min). RNA was precipitated with a 1/10 volume of 3 Msodium acetate and 2.5 volumes of ethanol at -20°C over-night, and subsequently pelleted at 20,000 × g for 30 minat 4°C. The precipitate was washed with 70% ethanol,centrifuged, and resuspended in RNAse free water to anapproximate concentration of 1 μg/μl. Actual RNA con-centration was determined spectrophotometrically.DNAse-treated total RNA (10 μg) of was used for reversetranscription with 0.27 μM T17VN primer, 0.15 mMdNTPs, 40 U RNAseOut, and 400 U SuperscriptII (Invitro-was heated to 65°C for 5 min and for primer annealingcooled to 42°C. Following an incubation at 42°C for 2.5h, the RNA was degraded with 8μl 1 M sodium hydroxidefor 15 min at 65°C, neutralized with 8 μl 1 M hydrochlo-ric acid and buffered with 4 μl 1 M Tris-pH 7.5. Synthe-sized cDNA was purified using the Quiagen (Hilden,Germany) PCR-purification kit prior to quantitative PCRreaction using the ABI TaqMan system. The Custom Taq-Man Gene Expression Assays (consisting of gene-specificTaqMan® MGB probe and primer sets, supplied as 20×stocks) used for quantitative real time PCR were from theApplied Biosystems (Foster City CA, USA) Custom Oligo-nucleotide Synthesis Service. The gene-specific probe andprimer sets were designed using the Primer Express soft-ware from Applied Biosystems. Oligonucleotidesequences of all primer pairs and the respective probes aregiven in Additional File 5. Multiplex PCR reaction in trip-licate (20 μl) containing cDNA equivalent to 100 ng RNAwere performed in 96-well plates with the Opticon 2 (Bio-Rad, Hercules CA, USA) using 1 μl of the 20× Custom Taq-Man Gene Expression Assay (consisting 900 μmole ofprimer/250 μmole FAM-labeled probe, final concentra-tion) for each of the genes analyzed; 2 μl primer pair andprobe combination (300 μmole of primer/125 μmole ofVIC-labeled probe) of the endogenous control (β-tubu-lin); 10 μl of 2× TaqMan Universal PCR Master Mix (con-taining all necessary components for fast reaction set-upfor 5' nuclease reactions, including AmpliTaq Gold DNApolymerase, and AmpErase UNG). After an initial hold at50°C for 2 min for the activation of AmpErase UNG, anddenaturing at 95°C for 10 min, 40 cycles at 95°C for 15sec and 60°C for 1 min, followed by fluorescence readingwere performed. Data analysis was done according to aprotocol by Applied Biosystems. Briefly, the baseline wasset such that the amplification curve growth began at acycle number that was greater than the highest baselinenumber. The threshold value was set within the exponen-tial phase of the logarithmic scale amplification plot. Rel-ative quantification of gene expression was calculatedfrom the threshold cycle (CT) values for each replicate wellon the reaction plate. Relative gene expression levels werecalculated manually from the exported results file. Briefly,the VIC CT values were subtracted from the FAM CT valuesto calculate ΔCT for the control and samples at each of thetime points for each of the transcription factors [ΔCT = CT(FAM) - CT (VIC)]. The ΔCT values for the triplicate wells of theControl samples at each time point for each of the tran-scription factor were averaged to obtain the mean ΔCT(Control). The mean ΔCT (Control) for a gene at a particulartime point was then subtracted from the ΔCT values of thisgene at that time point to calculate its ΔΔCT (Sample) [ΔΔCT(Sample) = ΔCT (Sample) - mean ΔCT (Control)]. The ΔΔCT (Sample)values were then averaged for the triplicate wells of eachPage 17 of 20(page number not for citation purposes)gen) in 10 mM DTT and 1 × first strand buffer in a totalvolume of 40 μl. Prior to addition of enzymes the solutiongene at each time point to normalize the target mRNAquantity to the internal control (β-Tubulin). The AverageBMC Genomics 2008, 9:154 http://www.biomedcentral.com/1471-2164/9/154ΔΔCT (Sample) for each sample was then used to calculatethe relative quantification values [2-mean ΔΔCT].Authors' contributionsJE performed and directed experiments, analyzed micro-array data, and performed database analyses. SGC per-formed qRT-PCR experiments and analyzed data. NMassisted with microarray hybridizations. DSA supportedstatistical analyses. GIA performed herbivore treatments.JB conceived the study, directed experiments, and ana-lyzed data. JE and JB wrote the manuscript. All authorsread and approved the final manuscript.Additional materialAcknowledgementsWe gratefully acknowledge financial support (to JB) from the Natural Sci-ence and Engineering Research Council (NSERC) of Canada, Genome Can-ada, and Genome British Columbia. JB is a UBC Distinguished University Scholar and NSERC E.W.R. Steacie Memorial Fellow.References1. De Vos M, Van Oosten VR, Van Poecke RMP, Van Pelt JA, Pozo MJ,Mueller MJ, Buchala AJ, Metraux JP, van Loon LC, Dicke M, PieterseAdditional file 1Normalized expression data of all non-control elements upon herbiv-ory with DBM. Arabidopsis Ler plants were challenged with P. xylostella (DBM) larvae for 1 h, 4 h, 8 h, and 24 h. Untreated control tissues were harvested in parallel. The experiment was repeated twice (biological rep-licates) and RNA from each treatment/control sample pair was used twice (dye-flip replicates) for hybridisation of a printed 70-mer oligonucleotide microarray containing 26,090 non control elements. Given for all non-control elements are information on the genes recognized (columns A to D), the normalized expression ratios for each hybridization (columns Y to AN), the mean ratios from the four replicates (columns L to O), clustering results (columns H and I), and the results of statistical analysis as indi-cated (columns F, G, J, K, P to W). Ratio considered significant (p[t-test] < 0.05 & foldchange > 2) are indicated in red (induced) or blue (repressed).Click here for file[http://www.biomedcentral.com/content/supplementary/1471-2164-9-154-S1.xls]Additional file 2Expression data of genes related to signalling components. Sheet a: Expression data of hormone related genes affected by DBM feeding. Based on curator annotated Gene Ontology categories at TAIR (colums D and U), A. thaliana genes were identified that are (i) involved in the metab-olism of, (ii) are part of the signal transduction mediated by, or (iii) are responsive to signalling compounds (i.e., abscicic acid; auxin; brassinos-teroid; cytokinin; ethylene; gibberellic acid; jasmonate; salicylic acid). Shown are genes in these categories that are differentially expressed upon herbivory in at least one time point (p[t-test] < 0.05, fold-change > 2). Sheet b: Expression data of DBM responsive signal transduction compo-nents (protein kinases, transcription factors, and 26S proteasome compo-nents). Complete gene family information were retrieved from PlantsP (protein kinases [34]), AtTFDB (transcription factor families [35]), and PlantsUBQ (26S proteasome gene families [36]). Shown are expression data for genes found differentially expressed (p[t-test] < 0.05 and more than twofold change) in at least one time point.Click here for file[http://www.biomedcentral.com/content/supplementary/1471-2164-9-154-S2.xls]Additional file 3Venn analysis of differentially expressed genes. To the left the number of communalities in the set of differentially expressed genes comparing DBM responses with previously published large scale transcriptome anal-yses. References are given in the title of each experiment. a and b denote the sets being intersected, with b being the last set to be intersected. First pairwise intersects are shown, then thresome intersects, etc. This compar-ison is based on a summary of experimental sets, i.e. a gene was counted as differentially expressed (DE) if at least one sample in a given experi-mental series was considered DE (see Figure 8 for definitions of DE). A list of all genes being considered as DE is given to the right. First, the max-imum fold change in any of the indicated samples is given; ratios are given only if at least one treatment was called DE. Second, ratios for all time points in each experiment are given; ratios are shown only if the gene was called DE. Sheet a: induced genes; sheet b: repressed genes.Click here for file[http://www.biomedcentral.com/content/supplementary/1471-2164-9-154-S3.xls]Additional file 4Meta-analysis of DBM-affected signalling component. Expression data (normalized intensities) based on publicly available Affymetrix micro-array hybridization data were downloaded from the Genevestigator data-base [54]. All probe sets called absent were set to the mean intensity of these undetectable probe sets for each gene. If replicate experiments were performed the mean intensity of all replicates was calculated. Expression ratios for all stress related and hormone treatment experiments available were generated using the corresponding control experiments and the log2 transformed ratios were used to generate a heatmap. On top of each col-umn the name, description, and the Affymetrix probeset used are indi-cated. Brief descriptions of each experiment and, in brackets, the experiment ID from the Genevestigator database are given. Expression ratios are colour coded, with bright yellow indicates a more than 8 fold higher expression in treated plants compared to control plants; bright blue indicates a more than 8 fold lower expression. Note that the data have been transposed relative to Figure 9 in order to fit the limitations of the spreadsheet.Click here for file[http://www.biomedcentral.com/content/supplementary/1471-2164-9-154-S4.xls]Additional file 5Oligonucleotide primers used for qRT-PCR. Sequence information for oligonucleotide primers and probes used for RT-PCR of EREBP transcrip-tion factors.Click here for file[http://www.biomedcentral.com/content/supplementary/1471-2164-9-154-S5.pdf]Page 18 of 20(page number not for citation purposes)CMJ: Signal signature and transcriptome changes of Arabi-dopsis during pathogen and insect attack.  Mol Plant Microbe In2005, 18:923-937.BMC Genomics 2008, 9:154 http://www.biomedcentral.com/1471-2164/9/1542. Kempema LA, Cui XP, Holzer FM, Walling LL: Arabidopsis tran-scriptome changes in response to phloem-feeding silverleafwhitefly nymphs. Similarities and distinctions in responses toaphids.  Plant Physiol 2007, 143:849-865.3. 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