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Functional categorization of unique expressed sequence tags obtained from the yeast-like growth phase… Hintz, William; Pinchback, Michael; de la Bastide, Paul; Burgess, Steven; Jacobi, Volker; Hamelin, Richard; Breuil, Colette; Bernier, Louis Aug 24, 2011

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RESEARCH ARTICLE Open AccessFunctional categorization of unique expressedsequence tags obtained from the yeast-likegrowth phase of the elm pathogen Ophiostomanovo-ulmiWilliam Hintz1*, Michael Pinchback1, Paul de la Bastide1, Steven Burgess1, Volker Jacobi2, Richard Hamelin3,Colette Breuil4 and Louis Bernier2AbstractBackground: The highly aggressive pathogenic fungus Ophiostoma novo-ulmi continues to be a serious threat tothe American elm (Ulmus americana) in North America. Extensive studies have been conducted in North Americato understand the mechanisms of virulence of this introduced pathogen and its evolving population structure,with a view to identifying potential strategies for the control of Dutch elm disease. As part of a larger study toexamine the genomes of economically important Ophiostoma spp. and the genetic basis of virulence, we haveconstructed an expressed sequence tag (EST) library using total RNA extracted from the yeast-like growth phase ofO. novo-ulmi (isolate H327).Results: A total of 4,386 readable EST sequences were annotated by determining their closest matches to knownor theoretical sequences in public databases by BLASTX analysis. Searches matched 2,093 sequences to entriesfound in Genbank, including 1,761 matches with known proteins and 332 matches with unknown (hypothetical/predicted) proteins. Known proteins included a collection of 880 unique transcripts which were categorized toobtain a functional profile of the transcriptome and to evaluate physiological function. These assignments yielded20 primary functional categories (FunCat), the largest including Metabolism (FunCat 01, 20.28% of total), Sub-cellular localization (70, 10.23%), Protein synthesis (12, 10.14%), Transcription (11, 8.27%), Biogenesis of cellularcomponents (42, 8.15%), Cellular transport, facilitation and routes (20, 6.08%), Classification unresolved (98, 5.80%),Cell rescue, defence and virulence (32, 5.31%) and the unclassified category, or known sequences of unknownmetabolic function (99, 7.5%). A list of specific transcripts of interest was compiled to initiate an evaluation of theirimpact upon strain virulence in subsequent studies.Conclusions: This is the first large-scale study of the O. novo-ulmi transcriptome. The expression profile obtainedfrom the yeast-like growth phase of this species will facilitate a multigenic approach to gene expression studiesto assess their role in the determination of pathogenicity for this species. The identification and evaluation ofgene targets in such studies will be a prerequisite to the development of biological control strategies for thispathogen.* Correspondence: whintz@uvic.ca1Biology Department, University of Victoria, P.O. Box 3020 STN CSC, Victoria,BC, V8W 3N5, CanadaFull list of author information is available at the end of the articleHintz et al. BMC Genomics 2011, 12:431http://www.biomedcentral.com/1471-2164/12/431© 2011 Hintz et al; licensee BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative CommonsAttribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction inany medium, provided the original work is properly cited.BackgroundThroughout the twentieth century, the American elm(Ulmus americana) has been a favoured urban tree forplanners and landscape architects in many North Amer-ican cities, providing shade along innumerable streetsand boulevards. The elm is a particularly popular choicein northern climates because of its resistance toextremes of weather and harsh urban growing condi-tions, while its abundant crown foliage is large enoughto span a city street [1]. Unfortunately, populations ofthis urban tree have been decimated by Dutch elm dis-ease. The disease in North America can be attributed totwo separate introduction events: the early epidemiccaused by the non-aggressive sub-group O. ulmi and thelater, more severe epidemic, caused by the highly patho-genic aggressive sub-group of O. novo-ulmi, which con-tinues to threaten elm populations of Western Canada.Genomic fingerprinting methods are useful for resol-ving phylogenetic relationships among closely relatedpopulations and species [2] and for the reconstructionof population histories, especially for a species introduc-tion, where there can be rapid population development[3]. Isolates of O. novo-ulmi sampled across Saskatche-wan and Manitoba were analyzed using both nuclearand mitochondrial genetic markers and only limitedgenetic variability was detected. All of the isolates repre-sented the aggressive sub-group and included only twodistinct nuclear and four mitochondrial genotypes [4].The vast majority of isolates were of a single genotype,suggesting that one genetic individual dominated thesample area. Later analysis in the same region comparedisolates collected in 1993 and 2002, using both RAPDmarkers and an evaluation of vegetative compatibility(vc) [5]. It was hypothesized that new vc types woulddevelop quickly after the disease front had passedthrough the region [6,7]. Compatibility tests confirmed asingle vc group, demonstrating that a genetically uni-form population persists in western Canada. In contrast,a much greater diversity of vc types has been documen-ted in the Eurasian aggressive (EAN) race of O. novo-ulmi, as compared to populations of the North Ameri-can aggressive (NAN) race [6]; the EAN and NAN sub-populations of O. novo-ulmi have since been re-designated as subspecies novo-ulmi and americana,respectively [8]. A low diversity of vc types for the amer-icana subspecies appears to be concentrated in thesouthern Great Lakes, which is consistent with its initialdetection in this region; areas colonized more recently,including western Canada, display very limited vc diver-sity [6,8,9]. In areas of Europe experiencing a well estab-lished epidemic of subspecies novo-ulmi that wasinitially characterized by a uniformity of vc types, vege-tative incompatibilities have been reported within six toten years [9]. In contrast, the comparatively low diversityof vc groups observed for the subspecies americana isatypical of an established pathogen epidemic, althoughrapidly expanding pathogen populations have previouslybeen reported to exhibit low genetic diversity [10].Factors influencing the development of vc groups andincreased genetic diversity in subspecies novo-ulmi musttherefore be significantly different from those encoun-tered by subspecies americana. There is no clear expla-nation for the limited genetic variability observed in theO. novo-ulmi subspecies americana population in wes-tern Canada. The report of only two nuclear genotypes,and no transitional genotypes, suggests that sexualevents are rare and that its propagation has been predo-minantly by asexual means within the time frame of thisepidemic [4,5]. In a previous study of North Americapopulations of this species, two possible factors contri-buting to low vc diversity were suggested: the infrequentoccurrence of deleterious d-factor viruses in populationsprovide a low level of selection for new vc types and thefrequent predominance of single vc clones on a hostsubstrate does not favour the establishment of novel vctypes [9]. The role of host genetic diversity has not beenevaluated to any extent in studies of Dutch elm diseaseand it should be noted that surveys of elm populationsin western Canada have been conducted primarily inurban environments and may thus have favouredplanted nursery stocks of this species. This may repre-sent a more limited diversity compared to wild U. amer-icana trees.From a perspective of disease management, thegenetic uniformity of the subspecies americana popula-tion could be exploited as a target for the control ofDutch elm disease in western Canada through the useof fungal hypoviruses and related genetic tools to reducepathogen virulence [6]. The presence of double-strandedRNA (dsRNA) viruses in isolates of O. novo-ulmi hasbeen well-documented [5,11,12] and may play a role instrain fitness and the genetic diversity of the pathogen,including the diversity of vc types [9,13,14]. Extensivestudies have been done to understand the mechanismsof virus-determined hypovirulence observed in the cau-sal agent of chestnut blight, Cryphonectria parasitica,and to establish its utility as a method of disease controlfor the North American tree species American chestnut(Castanea dentata)[15-17]. Similarly, the introducedascomycete O. novo-ulmi has become a serious patho-gen of a major tree species and represents a good candi-date for virus-mediated control.Until recently, there has been little work on profilinggene expression in O. novo-ulmi. A study focused onthe transcriptome represents an opportunity for exten-sive gene discovery. The primary benefit of thisapproach is the detection and assessment of genespotentially implicated in pathogenicity and parasiticHintz et al. BMC Genomics 2011, 12:431http://www.biomedcentral.com/1471-2164/12/431Page 2 of 12fitness. Wound pathogens, such as O. novo-ulmi, directlyenter the host through a pre-existing wound. Ophios-toma novo-ulmi is a dimorphic fungus, alternatingbetween a budding yeast-like growth form and a fila-mentous growth form, and this morphology switchappears to have great significance to pathogenicity [18].The yeast phase has been proposed to be involved indissemination of the pathogen from tree to tree by theinsect vector as well as translocation of the infectionwithin the host tree [19]. The mycelial form is requiredto penetrate from one vessel to another and may thusbe considered the invasive form [18]. The yeast - hyphaltransition is regulated by environmental factors andoccurs in the homokaryotic (haploid) state [19]. The cat-aloguing and functional categorization of a library ofexpressed sequence tags (ESTs) from the yeast form ofthis fungus provides a means of identifying genes inte-gral to the first stages of infection. A more completeunderstanding of the genetic basis of pathogenicitycould provide targets for gene regulation, leading tomethods of disease control The recent demonstration oftargeted gene disruption in O. novo-ulmi by RNA inter-ference [20], combined with knowledge about specifictarget genes as detected by EST analysis, makes thisgoal more readily achievable.The Canadian Ophiostoma Genome Project was firstinitiated in 2001 as a collaborative effort with the generalobjective of the large-scale collection and analysis of gen-ome data for species of this genus [21]. Longer-term stu-dies will include the examination of specific genes that aredifferentially expressed, especially those that relate tomechanisms of pathogenicity in these species. The objec-tives of the current study were to (i) construct a low-redundancy EST library using total RNA extracted fromthe yeast-like growth phase of isolate H327 of Ophiostomanovo-ulmi, (ii) annotate the EST information by determin-ing their closest matches to known or theoreticalsequences in public databases, and (iii) categorize theknown EST collection to obtain a functional profile of theO. novo-ulmi genome, as expressed under these conditionsof growth. This work will eventually be assisted by theconstruction of an EST microarray or RNA Seq analysis tofacilitate genome-level studies of gene expression.ResultsSequencing of library and BLASTX analysisAnalysis of novel sequence data typically begins with theassignment of putative identities based on alignmentswith derived proteins in public databases [20]. Recentgenome sequencing projects have resulted in the deposi-tion of hundreds of thousands of theoretical proteins,predicted by analysis of sequenced genomes. Theoreticalproteins frequently match with novel ESTs at a highalignment score, but are of little consequence if they donot assign function or identity to the EST. A protein ofknown function or identity will provide more meaning-ful information, even at a lesser alignment score. Whileautomated alignment and annotation algorithms serveto provide a good approximation of most EST identities,manual scrutiny and annotation is necessary to improvefidelity. With these constraints in mind, we began ananalysis of the expressed sequences of the Dutch elmpathogen O. novo-ulmi.The DNA sequence was determined for 5,760 clonesof a library that was estimated to contain a total of22,000 clones. The proportion of unique sequencesidentified in the entire yeast LMW library graduallydeclined as sequencing progressed, but remained above30% of all sequences read within the final 96-well cellculture plate. This suggests that there still remains a siz-able resource of unique O. novo-ulmi sequences in thecDNA library.Library data is summarized in Table 1. Of the 5,760EST clones sequenced, 4,386 gave readable sequenceinformation (~ 76%) and included inserts ranging from133 to 690 bp with an average insert size of 498 bp. Atotal of 2,093 of the 4,386 readable sequences matchedentries described in NCBI and GenBank public data-bases, as determined by BLASTX analysis [22]. Theseincluded 1,761 matches with known proteins and 332matches with unknown (hypothetical/predicted) pro-teins. Matches with known proteins included 880unique transcripts corresponding to 49.97% of the ESTsequences in this category. Applying this same ratio tothe category of unknown proteins would generate anadditional 166 unique transcripts among this group, fora total of 1,046 single matched sequences.A total of 2,293 of the 4,386 readable sequences drewno matches by BLASTX analysis. It may be assumedthat 20% of these clones contained non-authenticsequences, due to the ligation of random fragments ofDNA into vectors during the creation of the EST library,thus reducing the total to 1,835 sequences without amatch. Based on the results for matched readablesequences, it was estimated that approximately 50% ofunmatched EST sequences were unique, thus yieldingan additional 917 sequences that are at present uniden-tified. The total number of unique sequences from allcategories is therefore estimated to be 1,963 (880 knownproteins, 166 unknown proteins and 917 unmatchedsequences). Given that the O. novo-ulmi genome is esti-mated to contain 8,000 - 10,000 genes [23,24], the totalnumber of unique sequences in this library is estimatedto represent about 22% of this genome. Additionalsequencing of EST library clones will add further depthto this analysis.Hintz et al. BMC Genomics 2011, 12:431http://www.biomedcentral.com/1471-2164/12/431Page 3 of 12Functional assignment of ESTsFunctional assignment of expressed sequences requires aconsideration of the metabolic pathway in which a geneproduct is likely to be active. In some instances, the pre-sence of a characteristic functional group or structuraldomain indicates the probable molecular mechanism ofa protein, but offers no insight into the physiologicalfunction that protein serves [25,26]. While the specificmolecular mechanism of a specific protein may beknown, inferences regarding the physiological role ofsimilar proteins can be made based on their conserva-tion of consensus sequences [25]. Sequences involved intarget-ligand interactions are often similar amongrelated proteins and provide a means of deducing theirputative physiological role by comparison with pre-viously categorized proteins bearing similar consensussequences. The 880 matched unique transcripts wereselected as a subset of the 5,760 EST fragments andsubjected to further BLAST analysis to obtain the threehighest scoring alignments. These data were manuallyscrutinized and each EST was manually annotated usingthe FunCat system. A summary of results for the uniquetranscripts is provided in Additional File 1.Functional assignment of O. novo-ulmi yeast LMW ESTsto primary categoriesThe assignment of the O. novo-ulmi Yeast LMW ESTswith known identities (n = 880) into functionally relatedgroups yielded 20 primary functional categories (Table 2).The unclassified category (99, 7.5% of total) representedESTs for which a protein identity could be assigned basedupon an alignment with known sequences, but the meta-bolic function of that sequence remained unknown. Thelargest categories for the functional assignment of ESTs ofknown function included (in order of decreasing impor-tance) Metabolism (01, 20.28%), Protein synthesis (12,10.14%), Sub-cellular localization (70, 10.23%), Biogenesisof cellular components (42, 8.15%) and Transcription (11,8.27%). Individual categories that represented less than1.0% of total assignments included Protein fate (14,0.85%), Protein activity regulation, (18, 0.82%), Cell cycleand DNA processing (10, 0.7%), Transposable elements,viral and plasmid proteins (38, 0.34%), Interaction with theenvironment (36, 0.25%), Cell fate (40, 0.23%) and Celltype differentiation (43, 0.11%).Functional assignment of O. novo-ulmi yeast LMW ESTsto subcategoriesEach of the eight primary functional categories thatrepresented more than 4.5% of all identified ESTs werecategorized to the secondary level within each category(Table 3). The subcategories represented in each groupexhibited a wide variation in both the number detectedand in the proportional distribution among these subca-tegories. FunCat 99 (Unclassified proteins, 7.5%) repre-sented 66 standardized functional assignments of ESTs.The FunCat 01 (Metabolism) was comprised of 178.5standardized functional assignments of identified ESTs,making it the most highly represented functional cate-gory. Within this primary category, eight subcategoriesrelating to metabolism were represented. Expressedsequence tags associated with carbon compound meta-bolism (01.05) were the most highly represented, com-prising 29.83% of FunCat 01. Enzymes implicated in themetabolism of fatty acids (01.06) and amino acids(01.01) were also highly represented, comprising 23.53%and 19.61%, respectively, of these subcategories. Thefunctional assignment of ESTs associated with nucleo-tide metabolism (01.03) were also important (11.76%).The remaining subcategories represented the metabo-lism of nitrogen and sulphur (01.02), phosphate (01.04),vitamins, cofactors and prosthetic groups (01.07), andsecondary metabolism (01.20), each of which comprised5.6% or less of all subcategories.Table 1 Summary of EST sequence analysis for the O.novo-ulmi Yeast LMW library.Parameter NumberTotal ESTs sequenced 5,760Average length of EST (bp) 498Readable sequence data 4,386Sequences matching public databases 2,093Sequences matching known proteins 1,761Sequences matching unknown (hypothetical/predicted) proteins 332Sequences matching known, unique proteins (singletons) 880Sequences matching unknown proteins in public databases that represent singletons (estimated as 50% of unknown proteins) 166Total of singletons matching known and unknown unique proteins 1,046Sequences with no matches in public databases 2,293Sequences with no matches in public databases (less 20% containing non-authentic sequences) 1,835Sequences with no matches in public databases that represent singletons (estimated as 50% of unmatched) 917Total unique sequences from all categories 1,963Hintz et al. BMC Genomics 2011, 12:431http://www.biomedcentral.com/1471-2164/12/431Page 4 of 12A total of 39.5 standardized functional assignmentsand seven subcategories were represented within FunCat02 (Energy), with the vast majority of ESTs occurring inthe respiration (02.13) category (60.38%), followed byfermentation (02.16, 11.32%) and energy conversion andregeneration (02.45, 10.69%). The TCA cycle (02.10) wasalso well-represented (9.43%). Those subcategories exhi-biting the least representation within FunCat 02included ESTs classified within metabolism of energyreserves (02.19, 5.03%), electron transport and mem-brane-associated energy conservation (02.11, 2.52%), andthe pentose-phosphate pathway (02.07, 0.63%).Of the eight primary functional categories examined atthe secondary level, FunCat 11 (Transcription) exhibitedthe least complexity, with 72.75 standardized functionalassignments of ESTs in three subcategories, primarilyRNA synthesis (11.02, 86.25%), RNA processing (11.04,11.00%) and RNA modification (11.06, 2.75%).The expression profile for FunCat 12 (Protein synth-esis) had a similar distribution of functional assign-ments, with ribosome biogenesis representing the largestsubcategory (12.01, 77.31%), followed by translation(12.04, 20.45%) and aminoacyl-tRNA synthetases (12.10,2.24%), with a total of 89.25 standardized functionalassignments. Genes in the largest subcategory weredominated by 40S and 60S ribosomal proteins.The assignment of ESTs to subcategories within Fun-Cat 20 (Cellular transport) included 53.5 standardizedfunctional assignments. This category was comprised ofthree subcategories, two of which were highly repre-sented, transport routes (20.09, 49.32%), transportedcompounds (substrates) (20.01, 39.27%) and transportfacilitation (20.03, 11.42%).Within FunCat 32 (Cell rescue, defence and virulence)a total of 46.75 standardized functional assignmentswere made in three subcategories. The assignment ofESTs associated with stress response (32.01) and detoxi-fication (32.07) were almost equally represented at43.32% and 41.18%, respectively, followed by the subca-tegory of disease, virulence and defence (32.05, 15.51%).Those ESTs associated with stress response were repre-sented by inducible gene products sensitive to environ-mental stimuli, such as UV irradiation, desiccation andheat shock.The greatest number of subcategories was observedfor FunCat 42 (Biogenesis of cellular components). Atotal of 71.75 standardized functional assignments weredistributed among ten subcategories. Those ESTs asso-ciated with cytoplasm biogenesis represented the largestsubcategory (42.03, 40.77%) and included a number ofchitin synthase (42.03) proteins, of importance to cellwall biogenesis [27]. The cell wall subcategory was thenext largest group (42.01, 29.97%) and included genescoding for beta-glucanase/beta-glucan synthetase(42.01), stomatin, mucin, and cell wall surface anchorfamily protein. Subcategories with fewer assignmentsincluded mitochondrion (42.16, 9.76%) and cytoskeleton(42.04, 7.67%) biogenesis. The six remaining subcate-gories, totalling 11.84%, included peroxisome (42.19,3.83%), nucleus (42.10, 3.14%), vacuole or lysosome(42.25, 1.74%), extracellular/secretion proteins (42.27,1.39%), plasma membrane (42.02, 1.39%), and endoplas-mic reticulum (42.07, 0.35%) biogenesis. In the peroxi-some subcategory, the Woronin body major protein(42.19) was identified and is known to be important tocellular integrity during growth [28].Table 2 Classification of ESTs by functional category.Classification byfunctional category1RepresentationbyEST fragments2Percent of totalRepresentation301 Metabolism 178.5 20.2802 Energy 39.5 4.4910 Cell cycle and DNA processing 6 0.711 Transcription 72.75 8.2712 Protein synthesis 89.25 10.1414 Protein fate 7.5 0.8516 Protein with binding functionor co-factor requirement12.25 1.3918 Protein activity regulation 7.25 0.8220 Cellular transport, facilitationand routes53.5 6.0832 Cell rescue, defence andvirulence46.75 5.3134 Interaction with the cellularenvironment32 3.6436 Interaction with theenvironment2.16 0.2538 Transposable elements, viraland plasmid proteins3.0 0.3440 Cell fate 2.0 0.2342 Biogenesis of cellularcomponents71.75 8.1543 Cell type differentiation 1.0 0.1170 Subcellular localization 90 10.2373 Cell type localization 30 3.4198 Classification unresolved 51 5.8099 Unclassified proteins 66 7.5Subtotal = 862.25 97.98All remaining categories(each representing < 0.1% oftotal)17.75 2.02Total = 880 100.00Assignment of EST fragments by functional category and the percentrepresentation of each category in the collection of the O. novo-ulmi yeastLMW library.1Based upon the MIPS classification scheme for the functional annotation ofprotein sequences [50].2Classification of known yeast LMW sequences, as determined by BLASTXsearches and homology to sequences of known identity.3Relative percentage of known yeast LMW sequences in each functionalcategory.Hintz et al. BMC Genomics 2011, 12:431http://www.biomedcentral.com/1471-2164/12/431Page 5 of 12The subcategories of FunCat 70 (Subcellular localiza-tion) totalled 90 standardized functional assignments,that were distributed among seven subcategories. Thegreatest proportion of ESTs were associated with cyto-plasm localization (70.03, 30.90%). Other mainsubcategories included ESTs associated with endoplas-mic reticulum localization (70.07, 23.88%) and plasmamembrane/membrane attached subcellular localization(70.02, 20.51%). The subcategories of cell wall (70.01,12.36%) and nucleus (70.10, 11.24%) subcellularTable 3 Distribution of identified ESTs within each of the primary functional categories.Functional Category Functional Subcategory Percentoccurrence01 Metabolism 01.01 amino acid metabolism 19.6101.02 nitrogen and sulfur metabolism 5.6001.03 nucleotide metabolism 11.7601.04 phosphate metabolism 2.1001.05 C-compound and carbohydrate metabolism 29.8301.06 lipid, fatty acid and isoprenoid metabolism 23.5301.07 metabolism of vitamins, cofactors, and prosthetic groups 4.4801.20 secondary metabolism 3.0802 Energy 02.07 pentose-phosphate pathway 0.6302.10 tricarboxylic-acid pathway (citrate, Krebs and TCA cycles) 9.4302.11 elect. trans. and mem.-associated energy conservation 2.5202.13 respiration 60.3802.16 fermentation 11.3202.19 metabolism of energy reserves (e.g. glycogen, trehalose) 5.0302.45 energy conversion and regeneration 10.6911 Transcription 11.02 RNA synthesis 86.2511.04 RNA processing 11.0011.06 RNA modification 2.7512 Protein synthesis 12.01 ribosome biogenesis 77.3112.04 translation 20.4512.10 aminoacyl-tRNA-synthetases 2.2420 Cellular transport, transport facilitation and transport routes 20.01 transported compounds (substrates) 39.2720.03 transport facilitation 11.4220.09 transport routes 49.3232 Cellular rescue, defense and virulence 32.01 stress response 43.3232.05 disease, virulence and defense 15.5132.07 detoxification 41.1842 Biogenesis of cellular components 42.01 cell wall 29.9742.02 eukaryotic plasma membrane 1.3942.03 cytoplasm 40.7742.04 cytoskeleton 7.6742.07 endoplasmic reticulum 0.3542.10 nucleus 3.1442.16 mitochondrion 9.7642.19 peroxisome 3.8342.25 vacuole or lysosome 1.7442.27 extracellular/secretion proteins 1.3970 Subcellular localization 70.01 cell wall 12.3670.02 eukaryotic plasma membrane/membrane attached 20.5170.03 cytoplasm 30.9070.04 cytoskeleton 1.1270.07 endoplasmic reticulum 23.8870.10 nucleus 11.2470.25 vacuole or lysosome 1.12Hintz et al. BMC Genomics 2011, 12:431http://www.biomedcentral.com/1471-2164/12/431Page 6 of 12localization were also prominent, followed by genes cod-ing for vacuole or lysosome (70.25) and cytoskeleton(70.04) localization that both comprised 1.12% of allassignments in each category.The O. novo-ulmi unique transcript collection wasreviewed and we identified a number of expressed genesthat may be placed in these gene families of importanceto ascomycetous pathogens (Table 4). Genes of interestincluded those relevant to cell wall biogenesis, pathogendefense mechanisms during infection and the host infec-tion process.DiscussionUnderstanding pathogenicity in O. novo-ulmiThe construction of an EST library provides an initialgene expression profile for the yeast phase of a highlyaggressive strain of the elm pathogen O. novo-ulmi. ThisEST library will be the first step in elucidating the com-plex mechanisms determining fungal pathogenicity,through the study of multiple candidate genes that arepotentially implicated in the infection process. Histori-cally, studies of pathogenicity were limited to one or asmall number of candidate loci. With the creation of anEST library and the eventual use of microarray analysisto evaluate the expression of many genes under definedconditions, it will be possible to study whole organismgene expression as it relates to pathogenicity. The multi-genic character of fungal pathogenicity can thence bemore effectively assessed by this approach. Past effortsfocused on single genes have attained limited successand have only confirmed the complex nature of fungalpathogenicity in O. novo-ulmi [29]. Information gainedfrom future studies will be of benefit to understandingthe elm pathogen, as well as other fungal pathogens ofwoody plant species.Comparision with other Ophiostoma speciesThe EST library will also serve as a comparative data-base for other studies underway in the Ophiostoma Gen-ome Project for other growth states O. novo-ulmi andfor other species of the genus Ophiostoma that targetdifferent hosts [30-34]. Associated data from the currentproject includes a total of 561 EST fragments (GenbankAcc: EG355614.1 to EG356175.1) from libraries thatselected for perithecial (Onu-Per, 128 EST’s), synnema-tal (Onu-Syn, 181), mycelium grown at 15°C (Onu-t15,156) and mycelium grown at 31°C (Onu-t31, 96) growthphases [35]. The comparison of expressed sequences fordifferent life phases will facilitate our preliminary analy-sis of differentially expressed genes in O. novo-ulmi andTable 4 Transcripts detected in O.novo-ulmi that occur in gene families described for other ascomycetous pathogensand may function in determining virulence and fitness.Assigned protein identity No. ofcopiesFunCatnumberPutative function Species occurrence ofgene locus (citation)Trichothecene C-15 hydroxylase 1 01.06 Mycotoxin pathway FG, FS[51,52]Isochorismatase family hydrolase 2 99 Response to plant defence mechanisms MG, BC, SS, SN, AF[FGI, 53]Woronin body major protein 3 42.19 Cellular integrity(seal septal pores in response to stress,important during host infection)MG, filamentousascomycetes[FGI, 54]Tetraspanin 2 99 Transmembrane protein implicated inpenetration of host tissueBC, MG, CL[FGI, 55]Cox17p, involved in copper metabolism andassembly of cytochrome oxidase1 02.13; 70.10;34.01Cellular respiration (cytochrome C oxidasecopper chaperone)BC, MG, SS, SN, AN(FGI)Beta-glucanase/beta-glucan synthetase1 01.05, 42.01 Cell wall biogenesis BC, SS, SN, AN, FS[FGI, 56]Copper-zinc superoxide dismutase 5 11.01; 11.07 Antioxidant defenses (conversion ofsuperoxide radicals)CN, PM[57]Glutathione peroxidase paralogue 1 11.07 Antioxidant defenses (reduction of lipidhydroperoxides)BC, MG, SS, SN, CG[FGI, 58]Chitin synthase(including type A, C, 3, class IV and class V)12 01.05, 34.11,42.03, 73.01Cell wall biogenesis AN, AF, CGr, MG, PB[27]Histidine kinase 1 14.07, 30.05 Global gene regulation BD, HC[41]Glucan synthase 1 01.05 Cell wall biogenesis BD, HC, PB[58]Species acronyms: AN = Aspergillus nidulans, AF = Aspergillus flavus, BC = Botrytis cinerea, BD = Blastomyces dermatitidis, CGl = Chaetomium globosum, CGr =Colletotrichum graminicola, CL = Colletotrichum lindemuthianum, CN = Cryptococcus neoformans, FG = Fusarium graminearum (anamorph of Gibberella zeae), FS =Fusarium spp., HC = Histoplasma capsulatum, MG = Magnaporthe grisea, PB = Paracoccidioides braziliensis, PM = Penicillium marneffei, SN = Stagonospora nodorum,SS = Sclerotinia sclerotiorum. FGI = Fungal Genome Initiative, Broad Institute http://www.broad.mit.edu/annotation/fungi/fgi/index.htmlHintz et al. BMC Genomics 2011, 12:431http://www.biomedcentral.com/1471-2164/12/431Page 7 of 12provide direction for future studies of genes relevant topathogenesis. Existing EST projects for other Ophios-toma species include the sap-staining fungi Ophiostomapiliferum (Fungal Genomics Project, Concordia Univer-sity, web address: https://fungalgenomics.concordia.ca/fungi/Opil.php), Grosmannia clavigera (formerly Ophios-toma clavigerum) [30,36,37] and Ophiostoma floccosum(Farrell et al., pers. com.)The search for proteins associated with the pathogeniclife phase of Ophiostoma spp. has produced various stra-tegies designed to favour the expression of the relevantgene families. The use of suppressive subtractive hybri-dization PCR for the screening of genes differentiallyexpressed in yeast and mycelia forms of the sap-stainfungus Ophiostoma piceae has demonstrated one strat-egy for the identification of genes involved in morphol-ogy switching [31]. More recently, an EST library wascreated for the lodgepole pine pathogen G. clavigera,using selective media to favour the detection of fungalgenes expressed in the presence of oleoresin, one of thekey host tree defense mechanisms against fungal patho-gens [30]. This study described 5,974 EST fragments(2,600 unique transcripts) and their preliminary func-tional analysis was generally focused on those genesimplicated in fungal growth within the host and patho-genicity. Similarly, an EST library for O. piliferum wasconstructed by culturing the fungus on different carbonsources to obtain a total of 9,589 EST fragments (Tsang,Storms and Butler, unpublished); this species has beenconsidered for industrial applications, including the bio-pulping process [38]. Useful insights into gene familieslinked to virulence and growth within the host for O.novo-ulmi could be obtained by reviewing the EST datafor G. clavigera and O. piliferum. Molecular mechanismsunderlying Dutch elm disease were recently studied withthe construction of an interaction cDNA library, bymeans of suppression subtractive hybridization fromelm callus tissue following inoculation with O. novo-ulmi. Fifty three up-regulated Elm host-specific uniquetranscripts were identified, including genes coding forknown classes of pathogenesis-related proteins [39].Strategies for detecting genes that influence virulence inO. novo-ulmiThe NCBI public database for submitted fungal ESTsequences includes a total of 2,909,255 entries for 216species, with 1,931,468 entries for 134 species of asco-mycetes alone (November 2010). Among the ascomyce-tous species, there are a number of phytopathogens thathave been the subject of genome sequencing projects,many of which are available in public databases [40]. Inour efforts to indentify unique fungal genes relevant topathogenicity, two general strategies have been followedin studies of O. novo-ulmi. We have considered otherphytopathogenic ascomycete species as the most rele-vant group of organisms that may share common genesof importance to the host infection process, as well asdimorphic species of ascomycete pathogens thatundergo radical changes in morphology upon host infec-tion. A comparison of gene inventories for filamentouspathogenic and non-pathogenic ascomycetes identified aset of gene families that appear to have increased indiversity over evolutionary history and may play a rolein pathogenicity [26]. Genes seen in phytopathogenicfungi are not necessarily unique to pathogen species,but have developed a greater diversity of related genesfor specialized functions of a pathogenic lifestyle, whencompared to homologues that are found in non-patho-genic species [26]. These specialized functions caninclude the production of secondary metabolites (myco-toxins, melanin, hydrophobins), the ability to use a vari-ety of nutritional substrates, phenotypic plasticity(infection structures, dimorphism) and complex signal-ling pathways relevant to the infection process (hostrecognition, host defence systems, regulation ofmorphogenesis).Ophiostoma novo-ulmi exhibits mycelial and yeast-likegrowth phases at different stages of growth and infec-tion of the host elm. Possession of a variable growthphase is shared with some important human pathogenicfungi, where specific cues from the host species willinduce the change in morphology. A multigenicapproach has been pursued with these ascomycetepathogens and has begun to provide some importantfindings regarding the regulation of specific pathogenloci and the infection process [41,42]. A considerationof these genes in the screening of O. novo-ulmi librarymay therefore provide useful information. Histidinekinases in Blastomyces dermatitidis and Histoplasmacapsulatum appear to act as global regulators in thesedimorphic, human pathogenic ascomycetes, functioningin a two-component signalling system to regulatedimorphism and virulence. They directly influence thetransition from mycelial to yeast phase in the body of ahost and have been demonstrated to regulate theexpression of several yeast-phase specific genes [41]. Asingle histidine kinase was identified in the EST library(FunCat 14.07, 30.05), providing a potential gene targetfor further evaluation. Also in B. dermatitidis, H. capsu-latum and Paracoccidioides braziliensis the gene alpha-(1,3)-glucan synthase and several other loci are consid-ered yeast-phase specific virulence genes, as they are up-regulated with the switch to the pathogenic yeast format 37°C in the host [42]. In the species H. capsulatum,this is one of the genes regulated by a histidine kinase.The O. novo-ulmi library also contains glucan synthase(FunCat 01.05) and related genes that code for polysac-charides and other cell wall components.Hintz et al. BMC Genomics 2011, 12:431http://www.biomedcentral.com/1471-2164/12/431Page 8 of 12A number of candidate virulence factors are underconsideration for human pathogenic fungi and includemelanin compounds, oxidative and nitrosative stressdefense mechanisms, cell adhesion compounds, specificsecreted products, arginine catabolism, cell surface com-position, and those genes that are preferentiallyexpressed in the parasitic yeast phase [42]. Since thetransition of these dimorphic fungi from a mycelial to ayeast phase is required for virulence, this latter categoryhas received much attention. For genomic studies of thespecies of H. capsulatum and P. brasiliensis, a largenumber of differentially expressed genes have been iden-tified (500 and 328 genes, respectively) with the transi-tion to the pathogenic yeast phase [43-45]. These genesfall into a number of functional categories and have pro-vided a valuable resource for current studies of phase-specific gene expression in these species. Further studyof the current yeast EST database created for O. novo-ulmi and its comparison to the EST library constructedfor the mycelia growth phase of this species shouldallow the detection of phase-specific gene expression.This will ultimately be done by the functional compari-son of identified transcripts in each library and anassessment of their variability in gene expressionthrough microarray analysis or RNA Seq analysis.The development of control measures for O. novo-ulmiThe multigenic approach to assessing gene expression inO. novo-ulmi will also serve the future objective of iden-tifying gene targets that play a key role in the determi-nation of pathogenicity for this species. Such genes willbe further studied to assess their potential as targets forbiological control strategies. One of the main criteria inthe identification of such gene targets will be to confirmthat the modification of gene expression at the chosenlocus will only induce changes in the fungal species andnot in the host, or in other non-target species. As a pre-cursor to this assessment, it will be necessary to compilea prioritized list of possible gene targets identified fol-lowing the functional characterization of the ESTlibrary. A preliminary list of genes has been assembledin the current study and their evaluation can be assistedby the concurrent evaluation of whole organism geneexpression made possible by microarray analysis.The screening of candidate genes is best done by RNAinterference (RNAi) as a means of down-regulating theexpression of these gene targets. This approach hasbeen used to successfully characterize the role of alpha-(1,3)-glucan synthase (AGS1) in the pathogenicity of H.capsulatum [42], for the down-regulation of the polyke-tide synthase (PKS1) gene of the melanin pathway inOphiostoma piceae and Ophiostoma. floccosum [46] and,more recently, for the evaluation of gene expression bythe endopolygalacturonase (epg1) gene, a pathogenicityfactor in O. novo-ulmi [20]. This proven method of generegulation will provide a means of effectively screeningmultiple candidate genes from the EST library. Trans-formed wild type strains of O. novo-ulmi with modifiedexpression of selected genes can now be more easilyscreened in bioassays to assess the impact of targetedRNAi upon strain pathogenicity.ConclusionsThe creation of an EST library for O. novo-ulmi hasprovided an opportunity for gene discovery and thefunctional analysis of gene expression in this importantplant pathogen. This library will also provide usefulinformation for the study of other Ophiostoma spp. ofeconomic importance. A number of genes that mayinfluence virulence and fitness in O. novo-ulmi havebeen identified and these will be the focus of subsequentstudies to evaluate their role in host infection. Promisinggene targets will be assessed using an RNAi strategy toestablish their importance to pathogenicity. These find-ings will determine the approach of future biologicalcontrol research to control Dutch elm disease inCanada. This research will be complemented by wholegenome expression studies for O. novo-ulmi and relatedspecies.MethodsFungal strains and culture conditionsOphiostoma novo-ulmi strain H327, representing a highlyaggressive pathogen [47], was selected for RNA extrac-tions. Dimorphic O. novo-ulmi can be grown as either amycelial or a yeast-like form, depending on culture con-ditions. Stock cultures were maintained on solid Ophios-toma complete medium (CM) plates at 23°C [48]. For thegeneration of yeast-like cultures, 1 cm2 agar plugs werecut from the edge of an actively growing colony, inocu-lated into a 50 ml volume of liquid CM contained in 125ml Erlenmeyer flasks [48] and then incubated for 4 daysat 23°C with agitation (250 rpm). Yeast cells were subse-quently obtained by filtering the liquid culture through 3layers of sterile miracloth (Calbiotech, La Jolla, CA) andpelleted by centrifugation (700 g) for 15 min.Poly(A) mRNA extraction and purificationThe extraction and purification of poly(A) RNA was per-formed using a MicroPoly(A)Pure mRNA PurificationKit (Ambion/Applied Biosystems, Streetsville, ON,Canada). Total RNA was extracted from 210 mg wetweight of yeast cells and the poly (A) RNA was purifiedby oligo(dT) cellulose spun-column chromatography.The poly (A) RNA was resuspended in 20 μl of RNAase-free sterile, distilled water for storage at -80°C. Spectro-photometric analysis determined the RNA concentrationto be 853 ng/μl, with a purity ratio (A260/A280) of 1.452.Hintz et al. BMC Genomics 2011, 12:431http://www.biomedcentral.com/1471-2164/12/431Page 9 of 12Complementary DNA synthesisFor construction of the yeast O. novo-ulmi cDNAlibrary, the pBluescript II XR cDNA Library Construc-tion kit (Stratagene, La Jolla, CA, USA) was used for thefirst and second round of cDNA synthesis, cDNA termi-nus blunting, EcoRI adapter ligation and adapter phos-phorylation. First-strand synthesis was performed at 42°C for 1 hour with 9.20 μg of the yeast-like mRNA. Sam-ples were cooled on ice for 5 min, prior to secondstrand synthesis at 16°C for 2.5 hours. The terminusblunting reaction was stopped after 30 min by extractionwith 200 μl phenol:chloroform (1:1, v/v). The cDNAwith blunt termini were precipitated overnight at -20°C,following the addition of two volumes of 95% ethanoland 0.1 volume of 3 M sodium acetate. The mixturewas then centrifuged (13,000 g) for 20 min at 4°C, thesupernatant aspirated, the pellet dried by lyophilizationand re-suspended in a 9 μl volume containing the EcoRIadapters (Stratagene). The adapters were ligated to theblunt cDNA termini, following the addition of 1 μl 10 ×ligase buffer, 1 μl 10 mM rATP, 4 units T4 DNA ligaseand incubation overnight at 8°C. The ligated EcoRIadapters were phosphorylated with 10 units of T4 poly-nucleotide kinase and digested with 120 units XhoI at37°C for 2 hours. The cDNA was ethanol precipitatedovernight at -20°C, centrifuged at 13,000 g for 15 min at4°C and the pellet was re-suspended in 10 μl ElutionBuffer (Qiagen, Mississauga, ON, Canada).cDNA size fractionation, ligation and transformationThe synthesized cDNA was size fractionated by electro-phoresis on a 1% agarose gel in nuclease-free TAE buf-fer at 80 V for 1 hour, stained with ethidium bromideand visualized under UV light. The cDNA correspond-ing to low molecular weight (LMW, 400 - 2,000 bp) andhigh molecular weight (HMW, 2,000 - 5,000 bp) cate-gories was excised and isolated using the Qiaquick GelExtraction kit (Qiagen). Fractionated cDNA was elutedwith 50 μl Elution Buffer. Spectrophotometric analysisof the isolated yeast HMW and LMW cDNA samplesindicated concentrations of 2.8 ng/μl and 3.9 ng/μl,respectively. Fractionated LMW cDNA was ligated intothe pBluescript II SK vector (pBluescript II XR cDNALibrary Construction kit, Stratagene). Ligation reactionscontained 10 ng fractionated cDNA, 20 ng vector, and 2units of T4 DNA ligase in 1 × ligase buffer with 1 mMrATP (pH 7.5), in a final volume of 5.0 μl that was incu-bated at 12°C for 24 hours. The resulting constructswere employed to transform ultracompetent E. coliDH12S cells by electroporation, using 1 mm gap cuv-ettes (Bio-Rad, Mississauga, ON, Canada) in a BTXElectro Cell Manipulator 600 (settings: 1.30V; 2.5 kVresistance; capacitance timing = out; 129 Ω). The titerof the transformed bacterial cells was determined bydilution plating on 2YT plates (16 g/L tryptone, 10 g/Lyeast extract, 5 g/L NaCl, adjusted to pH 7.0 with 2NNaOH) amended with 50 μg/ml ampicillin (Sigma-Aldrich, Oakville, ON, Canada), 100 μg/ml X-galactose(Sigma), and 31 mg/ml isopropyl b-D-1-thiogalactopyra-noside (Sigma). Bacterial titer plates were incubatedovernight at 37°C, counted and stored at 4°C for sub-culturing. Plate counts indicated that the yeast LMWlibrary contained approximately 22,000 clones. The pri-mary stock culture of each library was stored at -80°Cin 50 μl aliquots to avoid freeze-thaw cycling duringsub-culturing.DNA sequencing and annotation of ESTsClones from the primary yeast LMW cDNA library wereprepared for sequencing by plating on 2YT amendedwith 50 μg/ml ampicillin, at a density of approximately200 colonies/plate. Discrete colonies were transferred to96-well cell culture plates (Corning, Lowell, MA, USA)containing 200 μl 2YT amended with 50 μg/ml ampicil-lin. Cell culture plates were sealed with foil tape (Corn-ing) and incubated overnight at 37°C without shaking. Atotal of 5,760 clones of the LMW cDNA library weresubmitted for sequencing and BLASTX analysis.Downstream processing of the LMW yeast-like O.novo-ulmi cDNA library began with the comparison ofEST fragments to nucleotide sequences already sub-mitted to public databases. In preparation for sequencecomparisons, the vector DNA was edited from authenticO. novo-ulmi sequences. Putative identities were assignedto each clone using the heuristic BLASTX algorithm [22],which compares a nucleotide query sequence, translatedinto all 6 reading frames, against the NCBI Genbank pub-lic database. A low-complexity filter was applied to querysequences to remove regions of low-complexity, such asproline-rich regions, or repeats of common acidic orbasic residues. The removal of these low-complexityregions increased the fidelity of alignments, and enrichedthe data for biological significance [49], rather than statis-tical significance alone.Database construction and assignment of functionalcategories to ESTsFor a list of unique ESTs retrieving hits from publicdatabases, see the Additional File 1 - Alphabetized listof 880 ESTs determined to be unique transcripts withmatches to known proteins in the GenBank database).All sequences have been deposited into GenBank’s ESTdatabase (Accession numbers JG459238 - JG463623).The Munich Information Centre for ProteinSequences (MIPS, now the Institute for Bioinformatics,Neuherberg, Germany) developed the Functional Catalo-gue (FunCat) as a stand-alone information managementframework and it has become a standard tool forHintz et al. BMC Genomics 2011, 12:431http://www.biomedcentral.com/1471-2164/12/431Page 10 of 12bioinformatics studies [25,50]. FunCat is a hierarchicallystructured, scalable classification system enabling thefunctional assignment of proteins from any genomeaccording to their physiological role, or metabolicpathway.A transcription profile was created for the O. novo-ulmi Yeast LMW library using transcripts whichmatched sequences characterized in other organisms.These were subjected to further BLAST analysis toobtain the three highest scoring alignments and thisinformation was manually scrutinized to determine themost meaningful annotation for each EST within theFunCat scheme. It is important to note that many pro-teins are associated with more than one metabolic path-way and many pathways influence more than one aspectof metabolism. Consequently, the assignment of a singlefunctional category to a protein can be both restrictiveand inaccurate. Many multifunctional proteins are justi-fiably included in numerous functional categories. Thiscan result in a small number of proteins generating avery large number of functional assignments. In order tostandardize FunCat scores for the Yeast LMW ESTlibrary and accommodate multifunctional proteins, weassigned each protein a total of 1.00 units of metabolicfunction, such that multifunctional proteins wereassigned a value less than one, as dictated by the num-ber of functional categories they encompassed [meta-bolic function = x(1/x), where × = number of functionalcategories included and 1/x = proportion of metabolicfunction assigned to each category].Additional materialAdditional file 1: Identified genes and FunCat assignments.xls (excelspreadsheet).AcknowledgementsResearch support to WH, CB and LB from the Natural Sciences andEngineering Research Council of Canada (NSERC) Discovery and StrategicGrant programs is gratefully acknowledged. We would like to thank Dr. BenKoop at the University of Victoria for providing access to his sequencingfacility and for the construction of an EST database. We also thank JongLeong for his assistance in submitting the sequences to Genbank.Author details1Biology Department, University of Victoria, P.O. Box 3020 STN CSC, Victoria,BC, V8W 3N5, Canada. 2Centre d’étude de la forêt (CEF), Faculté de foresterieet de géomatique, Université Laval, Québec (Québec) G1K 7P4, Canada.3Service canadien des forêts, Ressources naturelles Canada, Centre deforesterie des Laurentides, 1055 du PEPS, P.O. Box 3800, Québec (Québec)G1V 4C7 Canada. 4Department of Wood Science, University of BritishColumbia, Vancouver, British Columbia, V6T 1Z4 Canada.Authors’ contributionsWH was the supervisor for the project, conducted data analysis anddatabase creation and was responsible for the preparation and submissionof the manuscript. CB and LB were co-Principal Investigators on this projectand assisted with data analysis as well as providing input to the manuscript.The experimental work was conducted by SB, MP and PB. Additional dataanalysis and revision of the manuscript was done by VJ and RH. All authorshave read and approved the final manuscript.Received: 5 April 2011 Accepted: 24 August 2011Published: 24 August 2011References1. Hubbes M: The American elm and Dutch elm disease. Forest Chron 1999,75:265-273.2. Taylor J: Fungal evolutionary biology and mitochondrial DNA. Exp Mycol1986, 10:259-269.3. Avise JC: Gene trees and organismal histories: a phylogenetic approachto population biology. Evolution 1989, 43:1192-1208.4. Hintz WE, Jeng RS, Yang DQ, Hubbes MM, Horgen PA: A genetic survey ofthe pathogenic fungus Ophiostoma ulmi across a Dutch elm diseasefront in western Canada. Genome 1993, 36(3):418-426.5. 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