Fungal Secretome Database: Integrated platform for annotation of fungal secretomes

  • Jaeyoung Choi1, 2, 3,

    Affiliated with

    • Jongsun Park1, 2, 3, 4,

      Affiliated with

      • Donghan Kim1, 2, 3,

        Affiliated with

        • Kyongyong Jung1, 2, 3,

          Affiliated with

          • Seogchan Kang6 and

            Affiliated with

            • Yong-Hwan Lee1, 2, 3, 4, 5Email author

              Affiliated with

              BMC Genomics201011:105

              DOI: 10.1186/1471-2164-11-105

              Received: 16 May 2009

              Accepted: 11 February 2010

              Published: 11 February 2010

              Abstract

              Background

              Fungi secrete various proteins that have diverse functions. Prediction of secretory proteins using only one program is unsatisfactory. To enhance prediction accuracy, we constructed Fungal Secretome Database (FSD).

              Description

              A three-layer hierarchical identification rule based on nine prediction programs was used to identify putative secretory proteins in 158 fungal/oomycete genomes (208,883 proteins, 15.21% of the total proteome). The presence of putative effectors containing known host targeting signals such as RXLX [EDQ] and RXLR was investigated, presenting the degree of bias along with the species. The FSD's user-friendly interface provides summaries of prediction results and diverse web-based analysis functions through Favorite, a personalized repository.

              Conclusions

              The FSD can serve as an integrated platform supporting researches on secretory proteins in the fungal kingdom. All data and functions described in this study can be accessed on the FSD web site at http://​fsd.​snu.​ac.​kr/​.

              Background

              The "secretome" refers to the collection of proteins that contain a signal peptide and are processed via the endoplasmic reticulum and Golgi apparatus before secretion [1]. In organisms from bacteria to humans, secretory proteins are common and perform diverse functions. These functions include immune system [2], roles as neurotransmitters in the nervous system [3], roles as hormones/pheromones [4], acquisition of nutrients [57], building and remodeling of cell walls [8], signaling and environmental sensing [9], and competition with other organisms [1013]. Some secretory proteins in pathogens function as effectors that manipulate and/or destroy host cells with special signatures. In Plasmodium and Phytophthora species, effectors carry the RXLX [EDQ] or RXLR motifs as host targeting signals [1113].

              With the aid of advanced genome sequencing technologies [14], the rapid increase of sequenced fungal genomes offers many opportunities to study the function and evolution of secretory proteins at the genome level [15, 16]. The Comparative Fungal Genomics Platform (CFGP; http://​cfgp.​snu.​ac.​kr/​) [16] now archives 235 genomes from 120 fungal/oomycete species. The accurate prediction of secretory proteins in sequenced genomes is the key to realizing such opportunities.

              The widely used SignalP 3.0 program [17] detected 89.81% of the 2,512 experimentally verified sequences in SPdb [18], a database containing proteins with signal peptides. To improve the accuracy of prediction, we built a hierarchical identification pipeline based on nine prediction programs (Table 1). Through this pipeline, putative secretory proteins, including pathogen effectors, encoded by 158 fungal and oomycete genomes were identified. The Fungal Secretome Database (FSD; http://​fsd.​snu.​ac.​kr/​) was established to support not only the archiving of fungal secretory proteins but also the management and use of the resulting data. The FSD also has a user-friendly web interface and offers several data analysis functions via Favorite, a personalized data repository implemented in the CFGP (http://​cfgp.​snu.​ac.​kr/​)[16].
              Table 1

              List of prediction programs used in FSD

              Prediction Program

              Description

              Ref

              SignalP 3.0

              A program to predict whether a protein has the signal peptidase site I or not

              [17]

              SigCleave

              A program to predict whether a protein has signal peptides or not

              [19]

              SigPred

              A program to predict whether a protein has signal peptides or not

              [20]

              RPSP

              A program to predict whether a protein has signal peptides or not

              [21]

              TMHMM 2.0c

              A program to predict whether a protein has trans-membrane helix(es) or not

              [26]

              TargetP 1.1b

              A program to predict a site where a protein probably resides

              [23]

              PSort II

              A program to predict a site where a protein probably resides

              [22]

              SecretomeP 1.0f

              A program to predict whether a protein is secreted by non-classical pathways or not

              [25]

              predictNLS

              A program to predict whether a protein has nuclear localization signal or not

              [28]

              Construction and content

              Evaluation of the pipeline for predicting secretory proteins

              To evaluate the capabilities of four programs SignalP 3.0 [17], SigCleave [19], SigPred [20], and RPSP [21] for predicting signal peptides, we analyzed the secretory proteins collected in SPdb [18]. SignalP 3.0 identified 89.81% of 2,512 proteins; while adding the other three programs, in combination, 87.50% of the proteins, which were not predicted by SignalP 3.0, were identified. The remaining proteins (1.31% of 2,512 proteins) were investigated by using two programs that predicted subcellular localization: PSort II [22] and TargetP 1.1b [23]. We found that 34.38% of the proteins were predicted to be extracellular proteins, increasing the coverage to 99.16%. For the 1,093 characterized fungal/oomycete secretory proteins (Table 2), the combinatory pipeline raised the prediction coverage from 75.30% to 84.17% in comparison to SignalP 3.0. In addition, 98.14% of 24,921 experimentally unverified sequences in the SPdb were predicted as secretory proteins by the pipeline, while SignalP 3.0 caught 80.22% of them as positive. To assess robustness of the pipeline with non-secretory proteins, we prepared yeast proteins localized in cytosol, endoplasmic reticulum, nucleus, or mitochondrion [24]. When the 1,955 proteins were subjected to the FSD pipeline and SignalP 3.0, the numbers of false positives were almost same (84 and 82, respectively). Together, these results suggest that this ensemble approach could compensate for some of the weaknesses of individual programs, resulting in more robust predictions. Additionally, SecretomeP 1.0f [25], which can predict non-classical secretory proteins, was integrated into the FSD.
              Table 2

              List of references and annotation results of characterized fungal secretory proteins

              Title

              Total Identified Proteins

              Class SP

              Class SP3

              Class SL

              Putative Secretome

              Ref

              Crucial Role of Antioxidant Proteins and Hydrolytic Enzymes in Pathogenicity of Penicillium expansum : Analysis Based on Proteomics Approach (Secretory)

              21

              5

              1

              0

              6

              [43]

              Crucial Role of Antioxidant Proteins and Hydrolytic Enzymes in Pathogenicity of Penicillium expansum : Analysis Based on Proteomics Approach (Non-secretory)

              21

              1

              2

              0

              3

              [43]

              The Phanerochaete chrysosporium secretome: Database predictions and initial mass spectrometry peptide identifications in cellulose-grown medium

              49

              25

              5

              0

              30

              [44]

              An analysis of the Candida albicans genome database for soluble secreted proteins using computer-based prediction algorithms (Secretory)

              46

              28

              19

              2

              49

              [45]

              An analysis of the Candida albicans genome database for soluble secreted proteins using computer-based prediction algorithms (Non-secretory)

              45

              0

              5

              1

              6

              [45]

              The secretome of the maize pathogen Ustilago maydis (Without known functions)

              386

              352

              18

              10

              380

              [46]

              The secretome of the maize pathogen Ustilago maydis (With known functions)

              168

              147

              15

              5

              167

              [46]

              A Catalogue of the Effector Secretome of Plant Pathogenic Oomycetes

              25

              22

              1

              0

              23

              [11]

              Fungal degradation of wood: initial proteomic analysis of extra cellular proteins of Phanerochaete chrysosporium grown on oak substrate

              11

              8

              0

              0

              8

              [47]

              Comparative proteomics of extracellular proteins in vitro and in planta from the pathogenic fungus Fusarium graminearum

              120

              63

              8

              0

              71

              [48]

              Expression analysis of extracellular proteins from Phanerochaete chrysosporium grown on different liquid and solid substrates

              27

              16

              4

              0

              20

              [49]

              Dandruff-associated Malassezia genomes reveal convergent and divergent virulence traits shared with plant and human fungal pathogens

              34

              28

              0

              0

              28

              [50]

              Adaptive Evolution Has Targeted the C-Terminal Domain of the RXLR Effectors of Plant Pathogenic Oomycetes

              79

              79

              0

              0

              79

              [41]

              Genome, transcriptome, and secretome analysis of wood decay fungus Postia placenta supports unique mechanisms of lignocellulose conversion.

              47

              29

              3

              1

              33

              [51]

              Host-Microbe Interactions: Shaping the Evolution of the Plant Immune Response

              14

              12

              0

              1

              13

              [52]

              Total

              1,093

              815

              81

              20

              916

              -

              The FSD contains an identification pipeline that sequentially analyzes proteomes of interest using i) SignalP 3.0; ii) a combination of SigCleave, SigPred, and RPSP to screen those proteins not considered positive by SignalP 3.0; and iii) PSort II and TargetP 1.1b to analyze the negatives from the previous step. Additionally, SecretomeP 1.0f was integrated to provide information related to non-classical secretory proteins. To eliminate potential false positives, we filtered proteins that i) contain more than one transmembrane helix predicted by TMHMM 2.0c [26] and/or ii) the endoplasmic reticulum retention signal ([KRHQSA]- [DENQ]-E-L; classified as false-positive; Figure 1A) [27]. In addition, iii) nuclear proteins predicted by both predictNLS [28] and PSort II [22] and iv) mitochondrial proteins predicted by PSort II [22] as well as TargetP 1.1b [23] were eliminated because two subcellular localizations are not related to secretory proteins.
              http://static-content.springer.com/image/art%3A10.1186%2F1471-2164-11-105/MediaObjects/12864_2009_Article_2699_Fig1_HTML.jpg
              Figure 1

              FSD class definitions and the FSD pipeline. (A) Definitions of four FSD classes. The gray round rectangle indicates the total set of proteins, and the light blue arrows going outside the rectangle show the filtering out processes of the pipeline. The black rectangles show the names of the classes, the yellow arrows indicate expansion of the putative secretome boundary, and the white-bordered blue cross indicates additional information on the putative secretome. (B) Structure of the FSD pipeline. The two parallelograms are input data for the FSD pipeline. The rectangle in the middle indicates the process for identifying putative secretory proteins. The round rectangles indicate the four FSD classes. The gray square on the right represents the thirteen different analysis functions in Favorite.

              Following analysis via the pipeline, the resulting putative secretory proteins after removing potential false positives are divided into four classes: i) SP contains all proteins predicted by SignalP 3.0; ii) SP3 contains the proteins predicted by SigPred, SigCleave, or RPSP but not by SignalP 3.0; iii) SL contains the proteins predicted by PSort II and/or TargetP 1.1b but not by the first two steps; and iv) NS contains the proteins predicted by SecretomeP 1.0f but not by SignalP 3.0 (Figure 1A; Table 3).
              Table 3

              Class definitions used in FSD

              Class

              Description*

              Class SP

              Proteins which are predicted by SignalP 3.0

              Class SP3

              Proteins which are predicted by SigPred, SigCleave, or RPSP

              Class SL

              Proteins which are predicted by PSort II or TargetP 1.1b, but are not predicted by SignalP 3.0, SigPred, SigCleave, RPSP, or SecretomeP 1.0f

              Class NS

              Proteins which are predicted by SecretomeP 1.0f, but are not predicted by SignalP 3.0, SigPred, SigCleave, or RPSP

              * Proteins as follows were removed from all four classes described in this table: proteins which i) contain more than one trans-membrane helixes, ii) have ER retention signals, iii) predicted as mitochondrial proteins by PSort II and TargetP 1.1b, and iv) predicted as nuclear proteins by TargetP 1.1b and predictNLS.

              System structure of the FSD

              To improve the expandability and flexibility of the FSD, we adopted a three-layer structure (i.e., data warehouse, analysis pipeline, and user interface) in its design. The data warehouse was established using the standardized genome warehouse managed by the CFGP (http://​cfgp.​snu.​ac.​kr/​)[16] that has been used in various bioinformatics systems [15, 2935]. The pipeline layer was built with a series of Perl programs.

              In addition to the prediction programs described above, ChloroP 1.1 as well as hydropathy plots [36] were included in the FSD to provide additional information on secretory proteins. Whenever new fungal genomes become available, the automated pipeline classifies them based on the predictions of nine programs, thus keeping the FSD current (Figure 1B).

              MySQL 5.0.67 and PHP 5.2.9 were used to maintain database and to develop web-based user interfaces that present complex information intuitively. Web pages were serviced through Apache 2.2.11. Favorite, a personal data repository used in the CFGP (http://​cfgp.​snu.​ac.​kr/​)[16], was integrated to provide thirteen functions for further analyses.

              Utility and Discussion

              Discussion

              Secretory proteins in 158 fungal/oomycete genomes

              To survey the genome-wide distribution of secretory proteins in fungi and oomycetes, we used the pipeline to analyze all predicted proteins encoded by 158 fungal/oomycete genomes. Of the 1,373,444 open reading frames (ORFs) analyzed, 92,926 (6.77%), 103,224 (7.52%), and 12,733 (0.93%) proteins belonged to classes SP, SP3, and SL, respectively (Table 4, 5, and 6). In total, 208,883 ORFs (15.21%) were denoted putative secretory proteins. The proteins belonging to class NS were not included in the putative secretome because they represented more than 40% of whole proteome.
              Table 4

              List and distribution of secretion-associated proteins of the fungal genomes belonging to the subphylum Pezizomycotina archived in FSD

              Species

              Size (Mb)

              # of ORFs

              Class SP

              Class SP3

              Class SL

              Putative Secretome

              Ref

              Fungi (Kingdom) a

                     

                  Ascomycota (Phylum)

                     

              Pezizomycotina (Subphylum)

                     

              Aspergillus clavatus

              27.9

              9,121

              754

              732

              81

              1,567

              [53, 54]

              Aspergillus flavus

              36.8

              12,604

              1,200

              990

              142

              2,332

              [55]

              Aspergillus fumigatus A1163

              29.2

              9,929

              807

              878

              67

              1,752

              [54]

              Aspergillus fumigatus AF293

              29.4

              9,887

              781

              909

              84

              1,774

              [56]

              Aspergillus nidulans

              30.1

              10,568

              922

              877

              96

              1,895

              [57]

              Aspergillus niger ATCC1015

              37.2

              11,200

              860

              883

              88

              1,831

              N

              Aspergillus niger CBS513.88

              34.0

              14,086

              1,142

              1,320

              154

              2,616

              [58]

              Aspergillus oryzae

              37.1

              12,063

              1,060

              1,064

              145

              2,269

              [59]

              Aspergillus terreus

              29.3

              10,406

              934

              916

              81

              1,931

              [53]

              Botrytis cinerea

              42.7

              16,448

              1,163

              1,287

              182

              2,632

              N

              Chaetomium globosum b

              34.9

              11,124

              1,121

              923

              99

              2,143

              N

              Coccidioides immitis H538.4

              27.7

              10,663

              548

              957

              80

              1,585

              N

              Coccidioides immitis RMSCC 2394

              28.8

              10,408

              575

              920

              66

              1,561

              N

              Coccidioides immitis RMSCC 3703

              27.6

              10,465

              539

              892

              65

              1,496

              N

              Coccidioides immitis RS

              28.9

              10,457

              476

              855

              102

              1,433

              [60]

              Coccidioides posadasii RMSCC 3488

              28.1

              9,964

              546

              838

              95

              1,479

              N

              Coccidioides posadasii Silveira

              27.5

              10,125

              558

              869

              91

              1,518

              N

              Cochliobolus heterostrophus C5

              34.9

              9,633

              932

              725

              83

              1,740

              N

              Cryphonectria parasitica

              43.9

              11,184

              1,040

              951

              93

              2,084

              N

              Fusarium graminearum GZ3639c

              15.1

              6,694

              373

              386

              47

              806

              [61]

              Fusarium graminearum MIPS

              36.1

              13,920

              1,370

              1,072

              118

              2,560

              N

              Fusarium graminearum PH-1

              36.6

              13,339

              1,282

              1,004

              118

              2,404

              [61]

              Fusarium oxysporum

              61.4

              17,608

              1,613

              1,297

              147

              3,057

              N

              Fusarium solani

              51.3

              15,707

              1,381

              1,242

              155

              2,778

              [62]

              Fusarium verticillioides

              41.9

              14,199

              1,347

              1,071

              116

              2,534

              N

              Histoplasma capsulatum G186AR

              29.9

              7,454

              357

              578

              96

              1,031

              N

              Histoplasma capsulatum G217B

              41.3

              8,038

              393

              583

              103

              1,079

              N

              Histoplasma capsulatum H143

              39.0

              9,547

              468

              842

              87

              1,397

              N

              Histoplasma capsulatum H88

              37.9

              9,445

              492

              832

              99

              1,423

              N

              Histoplasma capsulatum Nam1

              33.0

              9,349

              398

              736

              79

              1,213

              [60]

              Magnaporthe oryzae

              41.7

              11,069

              1,573

              833

              64

              2,470

              [63]

              Microsporum canis

              23.3

              8,777

              564

              702

              88

              1,354

              N

              Microsporum gypseum

              23.3

              8,876

              629

              669

              52

              1,350

              N

              Mycosphaerella fijiensis

              73.4

              10,327

              770

              778

              81

              1,629

              N

              Mycosphaerella graminicola

              41.9

              11,395

              979

              913

              81

              1,973

              N

              Neosartorya fischeri b

              32.6

              10,403

              959

              818

              84

              1,861

              [54]

              Neurospora crassa

              39.2

              9,842

              817

              788

              61

              1,666

              [64]

              Neurospora crassa MIPS

              34.2

              9,572

              788

              749

              78

              1,615

              N

              Neurospora discretadiscrete

              37.3

              9,948

              823

              800

              88

              1,711

              N

              Neurospora tetrasperma

              37.8

              10,640

              849

              895

              73

              1,817

              N

              Paracoccidioides brasiliensis Pb01

              33.0

              9,136

              402

              808

              71

              1,281

              N

              Paracoccidioides brasiliensis Pb03

              29.1

              9,264

              470

              823

              92

              1,385

              N

              Paracoccidioides brasiliensis Pb18

              30.0

              8,741

              425

              743

              55

              1,223

              N

              Penicillium chrysogenum

              32.2

              12,791

              947

              1,008

              127

              2,082

              [65]

              Penicillium marneffei

              28.6

              10,638

              713

              792

              109

              1,614

              N

              Podospora anserina

              35.7

              10,596

              1,127

              893

              124

              2,144

              [66]

              Pyrenophora tritici-repentis

              38.0

              12,169

              1,228

              912

              123

              2,263

              N

              Sclerotinia sclerotiorum

              38.3

              14,522

              971

              1,109

              147

              2,227

              N

              Sporotrichum thermophile

              38.7

              8,806

              697

              658

              66

              1,421

              N

              Stagonospora nodorum

              37.2

              15,983

              1,511

              1,309

              142

              2,962

              [67]

              Talaromyces stipitatus

              35.7

              13,252

              748

              1,116

              114

              1,978

              N

              Thielavia terrestris

              37.0

              9,815

              877

              855

              67

              1,799

              N

              Trichoderma atroviride

              36.1

              11,100

              907

              935

              86

              1,928

              N

              Trichoderma reesei

              33.5

              9,129

              738

              766

              70

              1,574

              [68]

              Trichoderma virens GV29-8

              38.8

              11,643

              933

              1,009

              93

              2,035

              N

              Trichophyton equinum

              24.2

              8,576

              571

              699

              69

              1,339

              N

              Uncinocarpus reesii

              22.3

              7,798

              485

              626

              64

              1,175

              [60]

              Verticillium albo-atrum VaMs. 102

              32.9

              10,239

              1,074

              815

              73

              1,962

              N

              Verticillium dahliae VdLs. 17

              33.9

              10,575

              1,157

              861

              77

              2,095

              N

              Total

              2,059.4

              641,257

              50,164

              52,111

              5,578

              107,853

              -

              a Taxonomy based on [69]

              b Insufficient exon/intron information

              c Incomplete coverage of genome information

              Table 5

              List and distribution of secretion-associated proteins of the fungal genomes belonging to the subphylum Saccharomycotina and Taphrinomycotina archived in FSD

              Species

              Size (Mb)

              # of ORFs

              Class SP

              Class SP3

              Class SL

              Putative Secretome

              Ref

              Fungi (Kingdom) a

                     

                  Ascomycota (Phylum)

                     

              Saccharomycotina (Subphylum)

                     

              Candida albicans SC5314

              14.3

              6,185

              321

              405

              87

              813

              [70, 71]

              Candida albicans WO-1

              14.5

              6,160

              310

              385

              78

              773

              [72]

              Candida dubliniensis b

              14.5

              6,027

              308

              340

              71

              719

              N

              Candida glabrata CBS138

              12.3

              5,165

              231

              290

              49

              570

              [73]

              Candida guilliermondii

              10.6

              5,920

              279

              400

              63

              742

              [72]

              Candida lusitaniae

              12.1

              5,941

              310

              482

              50

              842

              [72]

              Candida parapsilosis

              13.1

              5,733

              308

              321

              83

              712

              [72]

              Candida tropicalis

              14.6

              6,258

              360

              373

              76

              809

              [72, 74]

              Debaryomyces hansenii

              12.2

              6,354

              254

              357

              74

              685

              [73]

              Eremothecium gossypii

              8.8

              4,717

              204

              333

              35

              572

              [75]

              Kluyveromyces lactis

              10.7

              5,327

              248

              304

              60

              612

              [73]

              Kluyveromyces polysporus

              14.7

              5,367

              219

              276

              58

              553

              [76]

              Kluyveromyces waltii

              10.9

              4,935

              187

              280

              41

              508

              [77]

              Lodderomyces elongisporus

              15.5

              5,802

              253

              351

              50

              654

              [72]

              Pichia stipitis

              15.4

              5,839

              263

              374

              58

              695

              [78]

              Saccharomyces bayanus 623-6C YM4911

              11.9

              4,966

              200

              275

              44

              519

              [79]

              Saccharomyces bayanus MCYC 623

              11.5

              9,385

              663

              767

              141

              1571

              [80]

              Saccharomyces castellii

              11.4

              4,677

              177

              240

              46

              463

              [79]

              Saccharomyces cerevisiae 273614N

              12.5

              5,354

              223

              261

              51

              535

              [81]

              Saccharomyces cerevisiae 322134S

              12.5

              5,382

              224

              290

              53

              567

              [81]

              Saccharomyces cerevisiae 378604X

              12.5

              5,400

              232

              267

              53

              552

              [81]

              Saccharomyces cerevisiae AWRI1631

              11.2

              5,451

              220

              364

              63

              647

              N

              Saccharomyces cerevisiae BC187

              12.5

              5,332

              226

              263

              47

              536

              [81]

              Saccharomyces cerevisiae DBVPG1106

              12.5

              5,318

              225

              253

              52

              530

              [81]

              Saccharomyces cerevisiae DBVPG1373

              12.4

              5,349

              229

              260

              48

              537

              [81]

              Saccharomyces cerevisiae DBVPG1788

              12.4

              5,347

              227

              263

              46

              536

              [81]

              Saccharomyces cerevisiae DBVPG1853

              12.5

              5,359

              224

              265

              51

              540

              [81]

              Saccharomyces cerevisiae DBVPG6040

              12.6

              5,364

              221

              271

              50

              542

              [81]

              Saccharomyces cerevisiae DBVPG6044

              12.5

              5,890

              224

              268

              48

              540

              [81]

              Saccharomyces cerevisiae DBVPG6765

              12.2

              5,377

              230

              263

              48

              541

              [81]

              Saccharomyces cerevisiae K11

              12.5

              5,375

              228

              270

              52

              550

              [81]

              Saccharomyces cerevisiae L_1374

              12.4

              5,346

              225

              264

              55

              544

              [81]

              Saccharomyces cerevisiae L_1528

              12.4

              5,346

              227

              258

              48

              533

              [81]

              Saccharomyces cerevisiae M22

              10.8

              6,755

              249

              399

              62

              710

              [82]

              Saccharomyces cerevisiae NCYC110

              12.5

              5,408

              226

              264

              57

              547

              [81]

              Saccharomyces cerevisiae NCYC361

              12.6

              5,360

              228

              261

              49

              538

              [81]

              Saccharomyces cerevisiae RM11-1a

              11.7

              5,696

              264

              283

              63

              610

              N

              Saccharomyces cerevisiae S288C

              12.2

              6,692

              394

              425

              99

              918

              [83]

              Saccharomyces cerevisiae SK1

              12.4

              5,433

              233

              269

              55

              557

              [81]

              Saccharomyces cerevisiae UWOPS03_461_4

              12.6

              5,329

              218

              268

              51

              537

              [81]

              Saccharomyces cerevisiae UWOPS05_217_3

              12.6

              5,350

              217

              264

              47

              528

              [81]

              Saccharomyces cerevisiae UWOPS05_227_2

              12.6

              5,334

              220

              266

              51

              537

              [81]

              Saccharomyces cerevisiae UWOPS83_787_3

              12.6

              5,392

              225

              269

              51

              545

              [81]

              Saccharomyces cerevisiae UWOPS87_2421

              12.6

              5,368

              226

              266

              56

              548

              [81]

              Saccharomyces cerevisiae W303

              12.4

              5,467

              237

              271

              52

              560

              [81]

              Saccharomyces cerevisiae Y12

              12.6

              5,370

              223

              268

              57

              548

              [81]

              Saccharomyces cerevisiae Y55

              12.3

              5,415

              239

              262

              60

              561

              [81]

              Saccharomyces cerevisiae Y9

              12.6

              5,377

              223

              271

              49

              543

              [81]

              Saccharomyces cerevisiae YIIc17_E5

              12.5

              5,376

              227

              265

              47

              539

              [81]

              Saccharomyces cerevisiae YJM789

              12.0

              5,903

              293

              303

              59

              655

              [84]

              Saccharomyces cerevisiae YJM975

              12.4

              5,341

              223

              255

              45

              523

              [81]

              Saccharomyces cerevisiae YJM978

              12.4

              5,353

              224

              258

              47

              529

              [81]

              Saccharomyces cerevisiae YJM981

              12.5

              5,351

              224

              256

              54

              534

              [81]

              Saccharomyces cerevisiae YPS128

              12.4

              5,364

              230

              269

              54

              553

              [81]

              Saccharomyces cerevisiae YPS163

              10.7

              6,648

              229

              368

              67

              664

              [82]

              Saccharomyces cerevisiae YPS606

              12.5

              5,354

              224

              270

              51

              545

              [81]

              Saccharomyces cerevisiae YS2

              12.6

              5,383

              221

              254

              50

              525

              [81]

              Saccharomyces cerevisiae YS4

              12.5

              5,398

              215

              267

              54

              536

              [81]

              Saccharomyces cerevisiae YS9

              12.6

              5,373

              226

              265

              51

              542

              [81]

              Saccharomyces kluyveri

              11.0

              2,968

              120

              180

              29

              329

              [79]

              Saccharomyces kudriavzevii

              11.2

              3,768

              187

              195

              28

              410

              [79]

              Saccharomyces mikatae

              11.5

              9,016

              575

              630

              154

              1359

              [80]

              Saccharomyces mikatae WashU

              10.8

              3,100

              161

              154

              24

              339

              [79]

              Saccharomyces paradoxus

              11.9

              8,939

              581

              615

              138

              1334

              [80]

              Yarrowia lipolytica

              20.5

              6,524

              409

              464

              75

              948

              [73]

              Taphrinomycotina (Subphylum)

                     

              Pneumocystis carinii b, c

              6.3

              4,020

              129

              333

              35

              497

              N

              Schizosaccharomyces japonicus

              11.3

              5,172

              207

              312

              25

              544

              N

              Schizosaccharomyces octosporus

              11.2

              4,925

              190

              263

              26

              479

              N

              Schizosaccharomyces pombe

              12.6

              5,058

              192

              288

              36

              516

              [85]

              Total

              853.1

              383,828

              17,389

              21,403

              3,937

              42,729

              -

              a Taxonomy based on [69]

              b Insufficient exon/intron information

              c Incomplete coverage of genome information

              Table 6

              List and distribution of secretion-associated proteins of the fungal genomes belonging to the phyla Basidiomycota, Chytridiomycota, and Microsporidia, the subphylum Mucoromycotina, and the phylum Peronosporomycota (oomycetes) archived in FSD

              Species

              Size (Mb)

              # of ORFs

              Class SP

              Class SP3

              Class SL

              Putative Secretome

              Ref

              Fungi (Kingdom) a

                     

                  Basidiomycota (Phylum)

                     

              Agricomycotina (Subphylum)

                     

              Coprinus cinereus

              36.3

              13,410

              1,189

              1,032

              119

              2,340

              N

              Cryptococcus neoformans Serotype A

              18.9

              6,980

              377

              549

              56

              982

              N

              Cryptococcus neoformans Serotype B

              19.0

              6,870

              331

              529

              44

              904

              N

              Cryptococcus neoformans Serotype D B-3501A

              18.5

              6,431

              342

              523

              39

              904

              [86]

              Cryptococcus neoformans Serotype D JEC21

              19.1

              6,475

              344

              541

              38

              923

              [86]

              Laccaria bicolour

              64.9

              20,614

              1,190

              2,024

              256

              3,470

              [87]

              Moniliophthora perniciosa

              26.7

              13,560

              843

              1,127

              126

              2,096

              N

              Phanerochaete chrysosporium

              35.1

              10,048

              793

              933

              83

              1,809

              [88]

              Pleurotus ostreatus

              34.3

              11,603

              1,039

              1,058

              106

              2,203

              N

              Postia placenta

              90.9

              17,173

              1,057

              1,808

              202

              3,067

              [51]

              Schizophyllum commune

              38.5

              13,181

              975

              1,175

              119

              2,269

              N

              Pucciniomycotina (Subphylum)

                     

              Melampsora laricis-populina

              21.9

              16,694

              1305

              1483

              233

              3,021

              N

              Puccinia graminis

              88.7

              20,567

              1,931

              2,020

              230

              4,181

              N

              Sporobolomyces roseus

              21.2

              5,536

              187

              592

              43

              822

              N

              Ustilaginomycotina (Subphylum)

                     

              Malassezia globosa

              9.0

              4,286

              211

              378

              37

              626

              [50]

              Ustilago maydis 521

              19.7

              6,689

              789

              583

              10

              1382

              [89]

              Ustilago maydis FB1

              19.3

              6,950

              481

              717

              34

              1232

              [89]

              Ustilago maydis MIPS

              19.7

              6,787

              574

              687

              34

              1295

              N

              Chytridiomycota (Phylum)

                     

              Batrachochytrium dendrobatidis JAM81

              24.3

              8,732

              806

              750

              108

              1,664

              N

              Batrachochytrium dendrobatidis JEL423

              23.9

              8,818

              650

              785

              91

              1,526

              N

              Mucoromycotina (Subphylum incertae sedis )

                     

              Mucor circinelloides

              36.6

              10,930

              580

              623

              83

              1286

              N

              Phycomyces blakesleeanus

              55.9

              14,792

              642

              1,085

              221

              1,948

              N

              Rhizopus oryzae

              46.1

              17,482

              750

              994

              202

              1,946

              [90]

              Microsporidia (Phylum)

                     

              Antonospora locustae b

              6.1

              2,606

              166

              208

              62

              436

              N

              Encephalitozoon cuniculi

              2.5

              1,996

              90

              135

              34

              259

              [91]

              Alveolata (Kingdom)

                     

              Apicomplexa (Phylum)

                     

              Plasmodium berghei

              18.0

              12,175

              844

              554

              569

              1,967

              N

              Plasmodium chabaudi

              16.9

              15,007

              1,027

              643

              661

              2,331

              N

              Plasmodium falciparum 3D7

              21.0

              5,387

              212

              283

              267

              762

              [92]

              Plasmodium knowlesi

              23.5

              5,103

              305

              280

              81

              666

              N

              Stramenopila (Kingdom)

                     

              Peronosporomycota (Phylum)

                     

              Hyaloperonospora parasitica

              83.6

              14,789

              868

              1,235

              132

              2,235

              N

              Phytophthora capsici

              107.8

              17,414

              1,485

              1,179

              136

              2,800

              N

              Phytophthora infestans b

              228.5

              22,658

              1,668

              1,923

              153

              3,744

              [93]

              Phytophthora ramorum

              66.7

              15,743

              1,670

              1,372

              91

              3,133

              [94]

              Phytophthora sojae

              86.0

              19,027

              2,040

              1,662

              96

              3,798

              [94]

              Total

              1,449.1

              386,513

              27,761

              31,470

              4,796

              64,027

              -

              a Taxonomy based on [69]

              b Insufficient exon/intron information

              c Incomplete coverage of genome information

              To determine the phylum-level distribution of classes SP, SP3, and SL within fungi, we investigated the proportions of the three classes among subphyla (Figure 2). Class SP3 was the largest, class SP was a little smaller, and the class SL was much smaller; this was consistent over every subphylum. Only in Plasmodium species, oomycetes, and the kingdom Metazoa class SP was dominant. Class SL did not exceeded 2.10% of the whole genome, except in Plasmodium species (4.52%). Plasmodium species also showed the lowest variance among the three classes, which may reflect signal peptide-independent types of secretory proteins such as vacuolar transport signals (VTSs) [12]. These results may be partially affected by the composition of the training data for each prediction program and inherent features of each algorithm.
              http://static-content.springer.com/image/art%3A10.1186%2F1471-2164-11-105/MediaObjects/12864_2009_Article_2699_Fig2_HTML.jpg
              Figure 2

              Distribution of three classes at the phylum/subphylum level. The average ratios of the classes to the total ORFs at the subphylum and phylum levels are described. The orange circular arc represents the fungal kingdom, and the four light blue round boxes represent phyla or kingdoms. Inside the chart, the blue line represents the ratio of class SP; the red line, class SP3; and the green line, class SL.

              The phylum Basidiomycota had a larger proportion of secretory proteins (17.90%) than other fungal taxonomy such as the subphylum Mucoromycotina (11.99%) and the phyla Ascomycota (12.87%) and Microsporidia (15.10%). Within the phylum Ascomycota, the subphylum Pezizomycotina showed a higher portion of class SP (7.82%) than the subphyla Saccharomycotina and Taphrinomycotina (4.57% and 3.74%, respectively). When considered that subphylum Pezizomycotina contains many pathogenic fungi (47 of 59) compared with subphylum Saccharomycotina (11 of 65), the abundance of secretory proteins in the subphylum Pezizomycotina suggests that pathogens may have larger secretome than saprophytes in general. In fact, Magnaporthe oryzae and Neurospora crassa, a closely related pair of pathogen and non-pathogen supported by recent phylogenomic studies [3739], contain 22.31% and 16.93% of secretory proteins, respectively. Moreover, the same tendency was found in comparison with 158 fungal/oomycete genomes archived in the FSD (pathogens and saprophytes showed 14.06% and 11.70%, respectively).

              Effectors encoded by fungal/oomycete and Plasmodium genomes

              Phytophthora species, a group that includes many important plant pathogens, uses a RXLR signal to secrete effectors to host cells [40]. RXLR effectors were tightly co-located with signal peptides predicted by the SignalP 3.0 with high confidence values (HMM and NN for 0.93 and 0.65, respectively) [41]. With the same conditions, we identified 734 putative RXLR effectors from three Phytophthora species, similar to a previous study [42]. However, 153 fungal genomes showed that only 0.04% of the total proteome contained this motif, suggesting that the use of RXLR for secretion is oomycete-specific.

              The motivation of finding the RXLR pattern in oomycetes was the RXLX [EDQ] motif of the VTS in the malaria pathogen, Plasmodium falciparum. Once P. falciparum invades the human erythrocyte, it secretes the proteins that carry the pentameric VTS of the RXLX [EDQ] motif from the parasitophorus vacuole to the host cytoplasm [12, 13]. To determine how many VTSs could be detected by our pipeline, we investigated 217 proteins of P. falciparum [13]. Of these, 115 proteins (53.00%) were classified as secretory proteins, defined in the FSD by the RXLX [EDQ] motif. Comparing our result to that predicted by SignalP 3.0 alone (41 out of 217), we found that our pipeline demonstrated high fidelity in detecting proteins containing VTSs.

              In class SP, the proportions of proteins possessing the RXLX [EDQ] but not the RXLR motif were 96.75%, 56.18%, and 93.21% in fungi, oomycetes, and Plasmodium species, respectively (Figure 3A). There were similar proportions of the RXLX [EDQ] motif in classes SP3 and SL across the three groups (Figure 3B and 3C). Taken together, these data show that the RXLR motif, with signal peptides predicted by SignalP 3.0, is oomycete-specific [41]. It is interesting that fungal genomes have significantly higher numbers of the RXLX [EDQ] motif than Plasmodium species (t-test based on amino acid frequency in each genome; P = 2.2e-16), suggesting that the RXLX [EDQ] motif may be one of fungal-specific signatures of effectors.
              http://static-content.springer.com/image/art%3A10.1186%2F1471-2164-11-105/MediaObjects/12864_2009_Article_2699_Fig3_HTML.jpg
              Figure 3

              Composition of RXLR/RXLX [EDQ] pattern in fungi, oomycetes, andPlasmodiumspecies. Composition of the RXLX [EDQ] (blue) and the RXLR (red) under class SP (A), class SP3 (B), and class SL (C) with the relative ratio in fungi, oomycetes, and Plasmodium species, respectively.

              Utility

              FSD web interfaces

              To support the browsing of the global patterns of archived data, the FSD prepares diverse charts and tables. For example, intersections of prediction results are summarized in a chart for each genome (Figure 4). Despite of the many programs, all prediction results for each protein are displayed on one page, allowing users to browse them easily (Figure 5).
              http://static-content.springer.com/image/art%3A10.1186%2F1471-2164-11-105/MediaObjects/12864_2009_Article_2699_Fig4_HTML.jpg
              Figure 4

              Screenshot of genome-level analysis functions for an example fungal genome. This screenshot shows the ORF numbers and ratios of each class through the pie chart in the left and the table in the right. The numbers in the table provide links to the list of putative secretory proteins belonging to each group. This figure shows the result from M. oryzae.

              http://static-content.springer.com/image/art%3A10.1186%2F1471-2164-11-105/MediaObjects/12864_2009_Article_2699_Fig5_HTML.jpg
              Figure 5

              One page summary for a protein. The web page shows a one page summary of amino acid sequence, exon structure, and genome context via the SNUGB [15], along with 12 predictions, including signal peptides and subcellular localization.

              The SNUGB interface (http://​genomebrowser.​snu.​ac.​kr/​)[15] provides several fields: i) signal peptides predicted by four different programs; ii) effector patterns, such as RXLR and RXLX [EDQ]; iii) nucleotide localization signals predicted by predictNLS; iv) transmembrane helixes predicted by TMHMM 2.0c; and v) hydropathy plots (Figure 6). The users can readily compare secretome-related information with diverse genomic contexts.
              http://static-content.springer.com/image/art%3A10.1186%2F1471-2164-11-105/MediaObjects/12864_2009_Article_2699_Fig6_HTML.jpg
              Figure 6

              SNU Genome Browser implemented in the FSD. The SNUGB (http://​genomebrowser.​snu.​ac.​kr/​)[15] displays i) four types of signal peptides predicted by SignalP 3.0, SigCleave, SigPred, and RPSP, ii) amino acid patterns, iii) nucleotide localization signals predicted by predictNLS, iv) transmembrane helixes predicted by TMHMM 2.0c, and v) hydropathy plots.

              The personalized virtual space, Favorite, supports in-depth analyses in the FSD

              The FSD allows users to collect proteins of interest and save them into the Favorite, which provides thirteen functions: i) classes distribution of proteins; ii) comparisons of predicted signal peptides generated by the four programs; iii) distributions and lists of proteins with predicted signal peptide cleavage sites; iv) compositions of amino acids near the cleavage sites; v) analyses of subcellular localization predictions; vi) lists and ratios of proteins that have chloroplast transit peptides, as determined by ChloroP 1.1; vii) analyses of proteins detected by SecretomeP 1.0f; viii) lists and distribution charts of proteins with trans-membrane helices, as predicted by TMHMM 2.0c; ix) hydropathy plots for proteins; x) analyses of proteins believed to be targeted to the nucleus of a host cell supported by predictNLS; xi) distributions and lists of proteins with a specific amino acid patterns; xii) lists of functional domains predicted by InterPro Scan; xiii) domain architecture of InterPro Scan (Figure 7). From these result pages, users can collect and store proteins in Favorite again, for further analyses. Additionally, Favorites created in the FSD can be shared with the CFGP (http://​cfgp.​snu.​ac.​kr/​)[16], permitting users to use the 22 bioinformatics tools provided in the CFGP web site.
              http://static-content.springer.com/image/art%3A10.1186%2F1471-2164-11-105/MediaObjects/12864_2009_Article_2699_Fig7_HTML.jpg
              Figure 7

              Thirteen analysis functions in the Favorite browser. Six different pages of analyses, connected to the Favorite browser, are displayed. "Prediction distribution" provides a list of predicted secretory proteins with their proportion to all proteins. "Class distribution" shows the composition of the classes, with the protein numbers belonging to each class. "Frequency/Position distribution" gives a bar or pie graph and numerical values linking to proteins listed for each item. "Hydropathy plots" draws the two graphs with window sizes of 11 and 19. "Amino acid distribution" presents consensus amino acids around the cleavage sites. "Functional domain distribution" lists the domains and their architecture diagrams based on InterPro terms.

              Conclusions

              Given the availability of large number of fungal genomes and diverse prediction programs for secretory proteins, a three-layer classification rule was established and implemented in a web-based database, the FSD. With the aid of an automated pipeline, the FSD classifies putative secretory proteins from 158 fungal/oomycetes genomes into four different classes, three of which are defined as the putative secretome. The proportion of fungal secretory proteins and host targeting signals varies considerably by species. It is interesting that fungal genomes have high proportions of the RXLX [EDQ] motif, characterized as host targeting signal in Plasmodium species. Summaries of the complex prediction results from twelve programs help users to readily access to the information provided by the FSD. Favorite, a personalized virtual space in the CFGP, serves thirteen different analysis tools for further in-depth analyses. Moreover, 22 bioinformatics tools provided by the CFGP can be utilized via the Favorite. Given these features, the FSD can serve as an integrated environment for studying secretory proteins in the fungal kingdom.

              Availability and requirements

              All data and functions described in this paper can be freely accessed through the FSD web site at http://​fsd.​snu.​ac.​kr/​.

              Declarations

              Acknowledgements

              This work was supported by the National Research Foundation of Korea grants (2009-0063340 and 2009-0080161) and grants from the Biogreen21 (20080401-034-044-009-01-00), the TDPAF (309015-04-SB020), and the Crop Functional Genomics Center (2009K001198). JC is grateful for the graduate fellowship through the Brain Korea 21 Program.

              Authors’ Affiliations

              (1)
              Fungal Bioinformatics Laboratory, Seoul National University
              (2)
              Department of Agricultural Biotechnology, Seoul National University
              (3)
              Center for Fungal Pathogenesis, Seoul National University
              (4)
              Center for Fungal Genetic Resources, Seoul National University
              (5)
              Center for Agricultural Biomaterials, Seoul National University
              (6)
              Department of Plant Pathology, The Pennsylvania State University

              References

              1. Lippincott-Schwartz J, Roberts TH, Hirschberg K: Secretory protein trafficking and organelle dynamics in living cells. Annu Rev Cell Dev Biol 2000, 16: 557–589.PubMedView Article
              2. Abbas KA, Lichtman HA, Pillai S: Cellular and Molecular Immunilogy. 6th edition. Saunders; 2006.
              3. Cho WJ, Jeremic A, Rognlien KT, Zhvania MG, Lazrishvili I, Tamar B, Jena BP: Structure, isolation, composition and reconstitution of the neuronal fusion pore. Cell Biol Int 2004, 28 (10) : 699–708.PubMedView Article
              4. Cho SJ, Jeftinija K, Glavaski A, Jeftinija S, Jena BP, Anderson LL: Structure and dynamics of the fusion pores in live GH-secreting cells revealed using atomic force microscopy. Endocrinology 2002, 143 (3) : 1144–1148.PubMedView Article
              5. Suarez MB, Sanz L, Chamorro MI, Rey M, Gonzalez FJ, Llobell A, Monte E: Proteomic analysis of secreted proteins from Trichoderma harzianum : Identification of a fungal cell wall-induced aspartic protease. Fungal Genet Biol 2005, 42 (11) : 924–934.PubMedView Article
              6. Van den Wymelenberg A, Minges P, Sabat G, Martinez D, Aerts A, Salamov A, Grigoriev I, Shapiro H, Putnam N, Belinky P, Dosoretz C, Gaskell J, Kersten P, Cullen D: Computational analysis of the Phanerochaete chrysosporium v2.0 genome database and mass spectrometry identification of peptides in ligninolytic cultures reveal complex mixtures of secreted proteins. Fungal Genet Biol 2006, 43 (5) : 343–356.View Article
              7. Vinzant TB, Adney WS, Decker SR, Baker JO, Kinter MT, Sherman NE, Fox JW, Himmel ME: Fingerprinting Trichoderma reesei hydrolases in a commercial cellulase preparation. Appl Biochem Biotechnol 2001, 91–93: 99–107.PubMedView Article
              8. Lesage G, Bussey H: Cell wall assembly in Saccharomyces cerevisiae . Microbiol Mol Biol Rev 2006, 70 (2) : 317–343.PubMedView Article
              9. Waters CM, Bassler BL: Quorum sensing: cell-to-cell communication in bacteria. Annu Rev Cell Dev Biol 2005, 21: 319–346.PubMedView Article
              10. Cornelis GR, Van Gijsegem F: Assembly and function of type III secretory systems. Annu Rev Microbiol 2000, 54: 735–774.PubMedView Article
              11. Kamoun S: A catalogue of the effector secretome of plant pathogenic oomycetes. Annu Rev Phytopathol 2006, 44: 41–60.PubMedView Article
              12. Hiller NL, Bhattacharjee S, van Ooij C, Liolios K, Harrison T, Lopez-Estrano C, Haldar K: A host-targeting signal in virulence proteins reveals a secretome in malarial infection. Science 2004, 306 (5703) : 1934–1937.PubMedView Article
              13. Marti M, Good RT, Rug M, Knuepfer E, Cowman AF: Targeting malaria virulence and remodeling proteins to the host erythrocyte. Science 2004, 306 (5703) : 1930–1933.PubMedView Article
              14. Bouws H, Wattenberg A, Zorn H: Fungal secretomes--nature's toolbox for white biotechnology. Appl Microbiol Biotechnol 2008, 80 (3) : 381–388.PubMedView Article
              15. Jung K, Park J, Choi J, Park B, Kim S, Ahn K, Choi J, Choi D, Kang S, Lee Y-H: SNUGB: a versatile genome browser supporting comparative and functional fungal genomics. BMC Genomics 2008, 9: 585.View Article
              16. Park J, Park B, Jung K, Jang S, Yu K, Choi J, Kong S, Kim S, Kim H, Kim JF, Blair JE, Lee K, Kang S, Lee YH: CFGP: a web-based, comparative fungal genomics platform. Nucleic Acids Res 2008, 36: D562–571.PubMedView Article
              17. Bendtsen JD, Nielsen H, von Heijne G, Brunak S: Improved prediction of signal peptides: SignalP 3.0. J Mol Biol 2004, 340 (4) : 783–795.PubMedView Article
              18. Choo KH, Tan TW, Ranganathan S: SPdb--a signal peptide database. BMC Bioinformatics 2005, 6: 249.PubMedView Article
              19. Rice P, Longden I, Bleasby A: EMBOSS: the European Molecular Biology Open Software Suite. Trends Genet 2000, 16 (6) : 276–277.PubMedView Article
              20. Bradford JR: Protein Design for Biopharmaceutical Development at GlaxoSmithKline: In silico Methods for Prediction of Signal Peptides and their Cleavage Sites, and Linear Epitopes. MRes thesis, The University of Leeds, Department of Biological Sciences 2001.
              21. Plewczynski D, Slabinski L, Ginalski K, Rychlewski L: Prediction of signal peptides in protein sequences by neural networks. Acta Biochim Pol 2008, 55 (2) : 261–267.PubMed
              22. Horton P, Park KJ, Obayashi T, Fujita N, Harada H, Adams-Collier CJ, Nakai K: WoLF PSORT: protein localization predictor. Nucleic Acids Res 2007, 35 (Web Server issue) : W585–587.PubMedView Article
              23. Emanuelsson O, Nielsen H, Brunak S, von Heijne G: Predicting subcellular localization of proteins based on their N-terminal amino acid sequence. J Mol Biol 2000, 300 (4) : 1005–1016.PubMedView Article
              24. Kumar A, Agarwal S, Heyman JA, Matson S, Heidtman M, Piccirillo S, Umansky L, Drawid A, Jansen R, Liu Y, Cheung KH, Miller P, Gerstein M, Roeder GS, Snyder M: Subcellular localization of the yeast proteome. Genes Dev 2002, 16 (6) : 707–719.PubMedView Article
              25. Bendtsen JD, Jensen LJ, Blom N, Von Heijne G, Brunak S: Feature-based prediction of non-classical and leaderless protein secretion. Protein Eng Des Sel 2004, 17 (4) : 349–356.PubMedView Article
              26. Sonnhammer EL, von Heijne G, Krogh A: A hidden Markov model for predicting transmembrane helices in protein sequences. Proc Int Conf Intell Syst Mol Biol 1998, 6: 175–182.PubMed
              27. Raykhel I, Alanen H, Salo K, Jurvansuu J, Nguyen VD, Latva-Ranta M, Ruddock L: A molecular specificity code for the three mammalian KDEL receptors. J Cell Biol 2007, 179 (6) : 1193–1204.PubMedView Article
              28. Cokol M, Nair R, Rost B: Finding nuclear localization signals. EMBO Rep 2000, 1 (5) : 411–415.PubMedView Article
              29. Park J, Park J, Jang S, Kim S, Kong S, Choi J, Ahn K, Kim J, Lee S, Kim S, Park B, Jung K, Kim S, Kang S, Lee YH: FTFD: an informatics pipeline supporting phylogenomic analysis of fungal transcription factors. Bioinformatics 2008, 24 (7) : 1024–1025.PubMedView Article
              30. Jeon J, Park SY, Chi MH, Choi J, Park J, Rho HS, Kim S, Goh J, Yoo S, Choi J, Park JY, Yi M, Yang S, Kwon MJ, Han SS, Kim BR, Khang CH, Park B, Lim SE, Jung K, Kong S, Karunakaran M, Oh HS, Kim H, Kim S, Park J, Kang S, Choi WB, Kang S, Lee YH: Genome-wide functional analysis of pathogenicity genes in the rice blast fungus. Nat Genet 2007, 39 (4) : 561–565.PubMedView Article
              31. Park J, Lee S, Choi J, Ahn K, Park B, Park J, Kang S, Lee YH: Fungal Cytochrome P450 Database. BMC Genomics 2008, 9 (1) : 402.PubMedView Article
              32. Choi J, Park J, Jeon J, Chi MH, Goh J, Yoo SY, Park J, Jung K, Kim H, Park SY, Rho HS, Kim S, Kim BR, Han SS, Kang S, Lee YH: Genome-wide analysis of T-DNA integration into the chromosomes of Magnaporthe oryzae . Mol Microbiol 2007, 66 (2) : 371–382.PubMedView Article
              33. Lee W, Park J, Choi J, Jung K, Park B, Kim D, Lee J, Ahn K, Song W, Kang S, Lee YH, Lee S: IMGD: an Integrated Platform Supporting Comparative Genomics and Phylogenetics of Insect Mitochondrial Genomes. BMC Genomics 2009, 10: 148.PubMedView Article
              34. Park J, Park B, Veeraraghavan N, Jung K, Lee YH, Blair J, Geiser DM, Isard S, Mansfield MA, Nikolaeva E, Park SY, Russo J, Kim SH, Greene M, Ivors KL, Balci Y, Peiman M, Erwin DC, Coffey MD, Rossman A, Farr D, Cline E, Crünwald NJ, Luster DG, Schrandt J, Martin F, Ribeiro OK, Makalowska I, Kang S: Phytophthora Database: A Forensic Database Supporting the Identification and Monitoring of Phytophthora . Plant disease 2008, 92 (6) : 966–972.View Article
              35. Xi H, Park J, Ding G, Lee YH, Li Y: SysPIMP: the web-based systematical platform for identifying human disease-related mutated sequences from mass spectrometry. Nucleic Acids Res 2009, 37: D913–920.PubMedView Article
              36. Kyte J, Doolittle RF: A simple method for displaying the hydropathic character of a protein. J Mol Biol 1982, 157 (1) : 105–132.PubMedView Article
              37. Fitzpatrick DA, Logue ME, Stajich JE, Butler G: A fungal phylogeny based on 42 complete genomes derived from supertree and combined gene analysis. BMC Evol Biol 2006, 6: 99.PubMedView Article
              38. Wang H, Xu Z, Gao L, Hao B: A fungal phylogeny based on 82 complete genomes using the composition vector method. BMC Evol Biol 2009, 9: 195.PubMedView Article
              39. Soanes DM, Alam I, Cornell M, Wong HM, Hedeler C, Paton NW, Rattray M, Hubbard SJ, Oliver SG, Talbot NJ: Comparative genome analysis of filamentous fungi reveals gene family expansions associated with fungal pathogenesis. PLoS One 2008, 3 (6) : e2300.PubMedView Article
              40. Whisson SC, Boevink PC, Moleleki L, Avrova AO, Morales JG, Gilroy EM, Armstrong MR, Grouffaud S, van West P, Chapman S, Hein I, Toth IK, Pritchard L, Birch PR: A translocation signal for delivery of oomycete effector proteins into host plant cells. Nature 2007, 450 (7166) : 115–118.PubMedView Article
              41. Win J, Morgan W, Bos J, Krasileva KV, Cano LM, Chaparro-Garcia A, Ammar R, Staskawicz BJ, Kamoun S: Adaptive evolution has targeted the C-terminal domain of the RXLR effectors of plant pathogenic oomycetes. Plant Cell 2007, 19 (8) : 2349–2369.PubMedView Article
              42. Jiang RH, Tripathy S, Govers F, Tyler BM: RXLR effector reservoir in two Phytophthora species is dominated by a single rapidly evolving superfamily with more than 700 members. Proc Natl Acad Sci USA 2008, 105 (12) : 4874–4879.PubMedView Article
              43. Qin G, Tian S, Chan Z, Li B: Crucial role of antioxidant proteins and hydrolytic enzymes in pathogenicity of Penicillium expansum : analysis based on proteomics approach. Mol Cell Proteomics 2007, 6 (3) : 425–438.PubMed
              44. Wymelenberg AV, Sabat G, Martinez D, Rajangam AS, Teeri TT, Gaskell J, Kersten PJ, Cullen D: The Phanerochaete chrysosporium secretome: database predictions and initial mass spectrometry peptide identifications in cellulose-grown medium. J Biotechnol 2005, 118 (1) : 17–34.PubMedView Article
              45. Lee SA, Wormsley S, Kamoun S, Lee AF, Joiner K, Wong B: An analysis of the Candida albicans genome database for soluble secreted proteins using computer-based prediction algorithms. Yeast 2003, 20 (7) : 595–610.PubMedView Article
              46. Mueller O, Kahmann R, Aguilar G, Trejo-Aguilar B, Wu A, de Vries RP: The secretome of the maize pathogen Ustilago maydis . Fungal Genet Biol 2008, 45 (Suppl 1) : S63–70.PubMedView Article
              47. Abbas A, Koc H, Liu F, Tien M: Fungal degradation of wood: initial proteomic analysis of extracellular proteins of Phanerochaete chrysosporium grown on oak substrate. Curr Genet 2005, 47 (1) : 49–56.PubMedView Article
              48. Paper JM, Scott-Craig JS, Adhikari ND, Cuomo CA, Walton JD: Comparative proteomics of extracellular proteins in vitro and in planta from the pathogenic fungus Fusarium graminearum . Proteomics 2007, 7 (17) : 3171–3183.PubMedView Article
              49. Sato S, Liu F, Koc H, Tien M: Expression analysis of extracellular proteins from Phanerochaete chrysosporium grown on different liquid and solid substrates. Microbiology 2007, 153 (Pt 9) : 3023–3033.PubMedView Article
              50. Xu J, Saunders CW, Hu P, Grant RA, Boekhout T, Kuramae EE, Kronstad JW, Deangelis YM, Reeder NL, Johnstone KR, Leland M, Fieno AM, Begley WM, Sun Y, Lacey MP, Chaudhary T, Keough T, Chu L, Sears R, Yuan B, Dawson TL Jr: Dandruff-associated Malassezia genomes reveal convergent and divergent virulence traits shared with plant and human fungal pathogens. Proc Natl Acad Sci USA 2007, 104 (47) : 18730–18735.PubMedView Article
              51. Martinez D, Challacombe J, Morgenstern I, Hibbett D, Schmoll M, Kubicek CP, Ferreira P, Ruiz-Duenas FJ, Martinez AT, Kersten P, Hammel KE, Vanden Wymelenberg A, Gaskell J, Lindquist E, Sabat G, Bondurant SS, Larrondo LF, Canessa P, Vicuna R, Yadav J, Doddapaneni H, Subramanian V, Pisabarro AG, Lavin JL, Oguiza JA, Master E, Henrissat B, Coutinho PM, Harris P, Magnuson JK, et al.: Genome, transcriptome, and secretome analysis of wood decay fungus Postia placenta supports unique mechanisms of lignocellulose conversion. Proc Natl Acad Sci USA 2009, 106 (6) : 1954–1959.PubMedView Article
              52. Chisholm ST, Coaker G, Day B, Staskawicz BJ: Host-microbe interactions: shaping the evolution of the plant immune response. Cell 2006, 124 (4) : 803–814.PubMedView Article
              53. Wortman JR, Fedorova N, Crabtree J, Joardar V, Maiti R, Haas BJ, Amedeo P, Lee E, Angiuoli SV, Jiang B, Anderson MJ, Denning DW, White OR, Nierman WC: Whole genome comparison of the A. fumigatus family. Med Mycol 2006, 44 (6) : 3–7.View Article
              54. Fedorova ND, Khaldi N, Joardar VS, Maiti R, Amedeo P, Anderson MJ, Crabtree J, Silva JC, Badger JH, Albarraq A, Angiuoli S, Bussey H, Bowyer P, Cotty PJ, Dyer PS, Egan A, Galens K, Fraser-Liggett CM, Haas BJ, Inman JM, Kent R, Lemieux S, Malavazi I, Orvis J, Roemer T, Ronning CM, Sundaram JP, Sutton G, Turner G, Venter JC, et al.: Genomic islands in the pathogenic filamentous fungus Aspergillus fumigatus . PLoS Genet 2008, 4 (4) : e1000046.PubMedView Article
              55. Payne GA, Nierman WC, Wortman JR, Pritchard BL, Brown D, Dean RA, Bhatnagar D, Cleveland TE, Machida M, Yu J: Whole genome comparision of A. flavus and A. oryzae . Med Mycol 2006, 44 (6) : 9–11.View Article
              56. Nierman WC, Pain A, Anderson MJ, Wortman JR, Kim HS, Arroyo J, Berriman M, Abe K, Archer DB, Bermejo C, Bennett J, Bowyer P, Chen D, Collins M, Coulsen R, Davies R, Dyer PS, Farman M, Fedorova N, Fedorova N, Feldblyum TV, Fischer R, Fosker N, Fraser A, Garcia JL, Garcia MJ, Goble A, Goldman GH, Gomi K, Griffith-Jones S, et al.: Genomic sequence of the pathogenic and allergenic filamentous fungus Aspergillus fumigatus . Nature 2005, 438 (7071) : 1151–1156.PubMedView Article
              57. Galagan JE, Calvo SE, Cuomo C, Ma LJ, Wortman JR, Batzoglou S, Lee SI, Basturkmen M, Spevak CC, Clutterbuck J, Kapitonov V, Jurka J, Scazzocchio C, Farman M, Butler J, Purcell S, Harris S, Braus GH, Draht O, Busch S, D'Enfert C, Bouchier C, Goldman GH, Bell-Pedersen D, Griffiths-Jones S, Doonan JH, Yu J, Vienken K, Pain A, Freitag M, et al.: Sequencing of Aspergillus nidulans and comparative analysis with A. fumigatus and A. oryzae . Nature 2005, 438 (7071) : 1105–1115.PubMedView Article
              58. Pel HJ, de Winde JH, Archer DB, Dyer PS, Hofmann G, Schaap PJ, Turner G, de Vries RP, Albang R, Albermann K, Andersen MR, Bendtsen JD, Benen JA, van den Berg M, Breestraat S, Caddick MX, Contreras R, Cornell M, Coutinho PM, Danchin EG, Debets AJ, Dekker P, van Dijck PW, van Dijk A, Dijkhuizen L, Driessen AJ, d'Enfert C, Geysens S, Goosen C, Groot GS, et al.: Genome sequencing and analysis of the versatile cell factory Aspergillus niger CBS 513.88. Nat Biotechnol 2007, 25 (2) : 221–231.PubMedView Article
              59. Machida M, Asai K, Sano M, Tanaka T, Kumagai T, Terai G, Kusumoto K, Arima T, Akita O, Kashiwagi Y, Abe K, Gomi K, Horiuchi H, Kitamoto K, Kobayashi T, Takeuchi M, Denning DW, Galagan JE, Nierman WC, Yu J, Archer DB, Bennett JW, Bhatnagar D, Cleveland TE, Fedorova ND, Gotoh O, Horikawa H, Hosoyama A, Ichinomiya M, Igarashi R, et al.: Genome sequencing and analysis of Aspergillus oryzae . Nature 2005, 438 (7071) : 1157–1161.PubMedView Article
              60. Sharpton TJ, Stajich JE, Rounsley SD, Gardner MJ, Wortman JR, Jordar VS, Maiti R, Kodira CD, Neafsey DE, Zeng Q, Hung CY, McMahan C, Muszewska A, Grynberg M, Mandel MA, Kellner EM, Barker BM, Galgiani JN, Orbach MJ, Kirkland TN, Cole GT, Henn MR, Birren BW, Taylor JW: Comparative genomic analyses of the human fungal pathogens Coccidioides and their relatives. Genome Res 2009, 19 (10) : 1722–1731.PubMedView Article
              61. Cuomo CA, Guldener U, Xu JR, Trail F, Turgeon BG, Di Pietro A, Walton JD, Ma LJ, Baker SE, Rep M, Adam G, Antoniw J, Baldwin T, Calvo S, Chang YL, Decaprio D, Gale LR, Gnerre S, Goswami RS, Hammond-Kosack K, Harris LJ, Hilburn K, Kennell JC, Kroken S, Magnuson JK, Mannhaupt G, Mauceli E, Mewes HW, Mitterbauer R, Muehlbauer G, et al.: The Fusarium graminearum genome reveals a link between localized polymorphism and pathogen specialization. Science 2007, 317 (5843) : 1400–1402.PubMedView Article
              62. Coleman JJ, Rounsley SD, Rodriguez-Carres M, Kuo A, Wasmann CC, Grimwood J, Schmutz J, Taga M, White GJ, Zhou S, Schwartz DC, Freitag M, Ma LJ, Danchin EG, Henrissat B, Coutinho PM, Nelson DR, Straney D, Napoli CA, Barker BM, Gribskov M, Rep M, Kroken S, Molnar I, Rensing C, Kennell JC, Zamora J, Farman ML, Selker EU, Salamov A, et al.: The genome of Nectria haematococca : contribution of supernumerary chromosomes to gene expansion. PLoS Genet 2009, 5 (8) : e1000618.PubMedView Article
              63. Dean RA, Talbot NJ, Ebbole DJ, Farman ML, Mitchell TK, Orbach MJ, Thon M, Kulkarni R, Xu JR, Pan H, Read ND, Lee YH, Carbone I, Brown D, Oh YY, Donofrio N, Jeong JS, Soanes DM, Djonovic S, Kolomiets E, Rehmeyer C, Li W, Harding M, Kim S, Lebrun MH, Bohnert H, Coughlan S, Butler J, Calvo S, Ma LJ, et al.: The genome sequence of the rice blast fungus Magnaporthe grisea . Nature 2005, 434 (7036) : 980–986.PubMedView Article
              64. Galagan JE, Calvo SE, Borkovich KA, Selker EU, Read ND, Jaffe D, FitzHugh W, Ma LJ, Smirnov S, Purcell S, Rehman B, Elkins T, Engels R, Wang S, Nielsen CB, Butler J, Endrizzi M, Qui D, Ianakiev P, Bell-Pedersen D, Nelson MA, Werner-Washburne M, Selitrennikoff CP, Kinsey JA, Braun EL, Zelter A, Schulte U, Kothe GO, Jedd G, Mewes W, et al.: The genome sequence of the filamentous fungus Neurospora crassa . Nature 2003, 422 (6934) : 859–868.PubMedView Article
              65. van den Berg MA, Albang R, Albermann K, Badger JH, Daran JM, Driessen AJ, Garcia-Estrada C, Fedorova ND, Harris DM, Heijne WH, Joardar V, Kiel JA, Kovalchuk A, Martin JF, Nierman WC, Nijland JG, Pronk JT, Roubos JA, van der Klei IJ, van Peij NN, Veenhuis M, von Dohren H, Wagner C, Wortman J, Bovenberg RA: Genome sequencing and analysis of the filamentous fungus Penicillium chrysogenum . Nat Biotechnol 2008, 26 (10) : 1161–1168.PubMedView Article
              66. Espagne E, Lespinet O, Malagnac F, Da Silva C, Jaillon O, Porcel BM, Couloux A, Aury JM, Segurens B, Poulain J, Anthouard V, Grossetete S, Khalili H, Coppin E, Dequard-Chablat M, Picard M, Contamine V, Arnaise S, Bourdais A, Berteaux-Lecellier V, Gautheret D, de Vries RP, Battaglia E, Coutinho PM, Danchin EG, Henrissat B, Khoury RE, Sainsard-Chanet A, Boivin A, Pinan-Lucarre B, et al.: The genome sequence of the model ascomycete fungus Podospora anserina . Genome Biol 2008, 9 (5) : R77.PubMedView Article
              67. Hane JK, Lowe RG, Solomon PS, Tan KC, Schoch CL, Spatafora JW, Crous PW, Kodira C, Birren BW, Galagan JE, Torriani SF, McDonald BA, Oliver RP: Dothideomycete Plant Interactions Illuminated by Genome Sequencing and EST Analysis of the Wheat Pathogen Stagonospora nodorum . Plant Cell 2007, 19 (11) : 3347–3368.PubMedView Article
              68. Martinez D, Berka RM, Henrissat B, Saloheimo M, Arvas M, Baker SE, Chapman J, Chertkov O, Coutinho PM, Cullen D, Danchin EG, Grigoriev IV, Harris P, Jackson M, Kubicek CP, Han CS, Ho I, Larrondo LF, de Leon AL, Magnuson JK, Merino S, Misra M, Nelson B, Putnam N, Robbertse B, Salamov AA, Schmoll M, Terry A, Thayer N, Westerholm-Parvinen A, et al.: Genome sequencing and analysis of the biomass-degrading fungus Trichoderma reesei (syn. Hypocrea jecorina ). Nat Biotechnol 2008, 26 (5) : 553–560.PubMedView Article
              69. Hibbett DS, Binder M, Bischoff JF, Blackwell M, Cannon PF, Eriksson OE, Huhndorf S, James T, Kirk PM, Lucking R, Thorsten Lumbsch H, Lutzoni F, Matheny PB, McLaughlin DJ, Powell MJ, Redhead S, Schoch CL, Spatafora JW, Stalpers JA, Vilgalys R, Aime MC, Aptroot A, Bauer R, Begerow D, Benny GL, Castlebury LA, Crous PW, Dai YC, Gams W, Geiser DM, et al.: A higher-level phylogenetic classification of the Fungi. Mycol Res 2007, 111 (Pt 5) : 509–547.PubMedView Article
              70. Jones T, Federspiel NA, Chibana H, Dungan J, Kalman S, Magee BB, Newport G, Thorstenson YR, Agabian N, Magee PT, Davis RW, Scherer S: The diploid genome sequence of Candida albicans . Proc Natl Acad Sci USA 2004, 101 (19) : 7329–7334.PubMedView Article
              71. van het Hoog M, Rast TJ, Martchenko M, Grindle S, Dignard D, Hogues H, Cuomo C, Berriman M, Scherer S, Magee BB, Whiteway M, Chibana H, Nantel A, Magee PT: Assembly of the Candida albicans genome into sixteen supercontigs aligned on the eight chromosomes. Genome Biol 2007, 8 (4) : R52.View Article
              72. Butler G, Rasmussen MD, Lin MF, Santos MA, Sakthikumar S, Munro CA, Rheinbay E, Grabherr M, Forche A, Reedy JL, Agrafioti I, Arnaud MB, Bates S, Brown AJ, Brunke S, Costanzo MC, Fitzpatrick DA, de Groot PW, Harris D, Hoyer LL, Hube B, Klis FM, Kodira C, Lennard N, Logue ME, Martin R, Neiman AM, Nikolaou E, Quail MA, Quinn J, et al.: Evolution of pathogenicity and sexual reproduction in eight Candida genomes. Nature 2009, 459 (7247) : 657–662.PubMedView Article
              73. Dujon B, Sherman D, Fischer G, Durrens P, Casaregola S, Lafontaine I, De Montigny J, Marck C, Neuveglise C, Talla E, Goffard N, Frangeul L, Aigle M, Anthouard V, Babour A, Barbe V, Barnay S, Blanchin S, Beckerich JM, Beyne E, Bleykasten C, Boisrame A, Boyer J, Cattolico L, Confanioleri F, De Daruvar A, Despons L, Fabre E, Fairhead C, Ferry-Dumazet H, et al.: Genome evolution in yeasts. Nature 2004, 430 (6995) : 35–44.PubMedView Article
              74. Blandin G, Ozier-Kalogeropoulos O, Wincker P, Artiguenave F, Dujon B: Genomic exploration of the hemiascomycetous yeasts: 16. Candida tropicalis . FEBS Lett 2000, 487 (1) : 91–94.PubMedView Article
              75. Dietrich FS, Voegeli S, Brachat S, Lerch A, Gates K, Steiner S, Mohr C, Pohlmann R, Luedi P, Choi S, Wing RA, Flavier A, Gaffney TD, Philippsen P: The Ashbya gossypii genome as a tool for mapping the ancient Saccharomyces cerevisiae genome. Science 2004, 304 (5668) : 304–307.PubMedView Article
              76. Scannell DR, Frank AC, Conant GC, Byrne KP, Woolfit M, Wolfe KH: Independent sorting-out of thousands of duplicated gene pairs in two yeast species descended from a whole-genome duplication. Proc Natl Acad Sci USA 2007, 104 (20) : 8397–8402.PubMedView Article
              77. Kellis M, Birren BW, Lander ES: Proof and evolutionary analysis of ancient genome duplication in the yeast Saccharomyces cerevisiae . Nature 2004, 428 (6983) : 617–624.PubMedView Article
              78. Jeffries TW, Grigoriev IV, Grimwood J, Laplaza JM, Aerts A, Salamov A, Schmutz J, Lindquist E, Dehal P, Shapiro H, Jin YS, Passoth V, Richardson PM: Genome sequence of the lignocellulose-bioconverting and xylose-fermenting yeast Pichia stipitis . Nat Biotechnol 2007, 25 (3) : 319–326.PubMedView Article
              79. Cliften P, Sudarsanam P, Desikan A, Fulton L, Fulton B, Majors J, Waterston R, Cohen BA, Johnston M: Finding functional features in Saccharomyces genomes by phylogenetic footprinting. Science 2003, 301 (5629) : 71–76.PubMedView Article
              80. Kellis M, Patterson N, Endrizzi M, Birren B, Lander ES: Sequencing and comparison of yeast species to identify genes and regulatory elements. Nature 2003, 423 (6937) : 241–254.PubMedView Article
              81. Liti G, Carter DM, Moses AM, Warringer J, Parts L, James SA, Davey RP, Roberts IN, Burt A, Koufopanou V, Tsai IJ, Bergman CM, Bensasson D, O'Kelly MJ, van Oudenaarden A, Barton DB, Bailes E, Nguyen AN, Jones M, Quail MA, Goodhead I, Sims S, Smith F, Blomberg A, Durbin R, Louis EJ: Population genomics of domestic and wild yeasts. Nature 2009, 458 (7236) : 337–341.PubMedView Article
              82. Doniger SW, Kim HS, Swain D, Corcuera D, Williams M, Yang SP, Fay JC: A catalog of neutral and deleterious polymorphism in yeast. PLoS Genet 2008, 4 (8) : e1000183.PubMedView Article
              83. Goffeau A, Barrell BG, Bussey H, Davis RW, Dujon B, Feldmann H, Galibert F, Hoheisel JD, Jacq C, Johnston M, Louis EJ, Mewes HW, Murakami Y, Philippsen P, Tettelin H, Oliver SG: Life with 6000 genes. Science 1996, 274 (5287) : 563–547.View Article
              84. Gu Z, David L, Petrov D, Jones T, Davis RW, Steinmetz LM: Elevated evolutionary rates in the laboratory strain of Saccharomyces cerevisiae . Proc Natl Acad Sci USA 2005, 102 (4) : 1092–1097.PubMedView Article
              85. Wood V, Gwilliam R, Rajandream MA, Lyne M, Lyne R, Stewart A, Sgouros J, Peat N, Hayles J, Baker S, Basham D, Bowman S, Brooks K, Brown D, Brown S, Chillingworth T, Churcher C, Collins M, Connor R, Cronin A, Davis P, Feltwell T, Fraser A, Gentles S, Goble A, Hamlin N, Harris D, Hidalgo J, Hodgson G, Holroyd S, et al.: The genome sequence of Schizosaccharomyces pombe . Nature 2002, 415 (6874) : 871–880.PubMedView Article
              86. Loftus BJ, Fung E, Roncaglia P, Rowley D, Amedeo P, Bruno D, Vamathevan J, Miranda M, Anderson IJ, Fraser JA, Allen JE, Bosdet IE, Brent MR, Chiu R, Doering TL, Donlin MJ, D'Souza CA, Fox DS, Grinberg V, Fu J, Fukushima M, Haas BJ, Huang JC, Janbon G, Jones SJ, Koo HL, Krzywinski MI, Kwon-Chung JK, Lengeler KB, Maiti R, et al.: The genome of the basidiomycetous yeast and human pathogen Cryptococcus neoformans . Science 2005, 307 (5713) : 1321–1324.PubMedView Article
              87. Martin F, Aerts A, Ahren D, Brun A, Danchin EG, Duchaussoy F, Gibon J, Kohler A, Lindquist E, Pereda V, Salamov A, Shapiro HJ, Wuyts J, Blaudez D, Buee M, Brokstein P, Canback B, Cohen D, Courty PE, Coutinho PM, Delaruelle C, Detter JC, Deveau A, DiFazio S, Duplessis S, Fraissinet-Tachet L, Lucic E, Frey-Klett P, Fourrey C, Feussner I, et al.: The genome of Laccaria bicolor provides insights into mycorrhizal symbiosis. Nature 2008, 452 (7183) : 88–92.PubMedView Article
              88. Martinez D, Larrondo LF, Putnam N, Gelpke MD, Huang K, Chapman J, Helfenbein KG, Ramaiya P, Detter JC, Larimer F, Coutinho PM, Henrissat B, Berka R, Cullen D, Rokhsar D: Genome sequence of the lignocellulose degrading fungus Phanerochaete chrysosporium strain RP78. Nat Biotechnol 2004, 22 (6) : 695–700.PubMedView Article
              89. Kamper J, Kahmann R, Bolker M, Ma LJ, Brefort T, Saville BJ, Banuett F, Kronstad JW, Gold SE, Muller O, Perlin MH, Wosten HA, de Vries R, Ruiz-Herrera J, Reynaga-Pena CG, Snetselaar K, McCann M, Perez-Martin J, Feldbrugge M, Basse CW, Steinberg G, Ibeas JI, Holloman W, Guzman P, Farman M, Stajich JE, Sentandreu R, Gonzalez-Prieto JM, Kennell JC, Molina L, et al.: Insights from the genome of the biotrophic fungal plant pathogen Ustilago maydis . Nature 2006, 444 (7115) : 97–101.PubMedView Article
              90. Ma LJ, Ibrahim AS, Skory C, Grabherr MG, Burger G, Butler M, Elias M, Idnurm A, Lang BF, Sone T, Abe A, Calvo SE, Corrochano LM, Engels R, Fu J, Hansberg W, Kim JM, Kodira CD, Koehrsen MJ, Liu B, Miranda-Saavedra D, O'Leary S, Ortiz-Castellanos L, Poulter R, Rodriguez-Romero J, Ruiz-Herrera J, Shen YQ, Zeng Q, Galagan J, Birren BW, et al.: Genomic analysis of the basal lineage fungus Rhizopus oryzae reveals a whole-genome duplication. PLoS Genet 2009, 5 (7) : e1000549.PubMedView Article
              91. Katinka MD, Duprat S, Cornillot E, Metenier G, Thomarat F, Prensier G, Barbe V, Peyretaillade E, Brottier P, Wincker P, Delbac F, El Alaoui H, Peyret P, Saurin W, Gouy M, Weissenbach J, Vivares CP: Genome sequence and gene compaction of the eukaryote parasite Encephalitozoon cuniculi . Nature 2001, 414 (6862) : 450–453.PubMedView Article
              92. Gardner MJ, Hall N, Fung E, White O, Berriman M, Hyman RW, Carlton JM, Pain A, Nelson KE, Bowman S, Paulsen IT, James K, Eisen JA, Rutherford K, Salzberg SL, Craig A, Kyes S, Chan MS, Nene V, Shallom SJ, Suh B, Peterson J, Angiuoli S, Pertea M, Allen J, Selengut J, Haft D, Mather MW, Vaidya AB, Martin DM, et al.: Genome sequence of the human malaria parasite Plasmodium falciparum . Nature 2002, 419 (6906) : 498–511.PubMedView Article
              93. Haas BJ, Kamoun S, Zody MC, Jiang RH, Handsaker RE, Cano LM, Grabherr M, Kodira CD, Raffaele S, Torto-Alalibo T, Bozkurt TO, Ah-Fong AM, Alvarado L, Anderson VL, Armstrong MR, Avrova A, Baxter L, Beynon J, Boevink PC, Bollmann SR, Bos JI, Bulone V, Cai G, Cakir C, Carrington JC, Chawner M, Conti L, Costanzo S, Ewan R, Fahlgren N, et al.: Genome sequence and analysis of the Irish potato famine pathogen Phytophthora infestans . Nature 2009, 461 (7262) : 393–398.PubMedView Article
              94. Tyler BM, Tripathy S, Zhang X, Dehal P, Jiang RH, Aerts A, Arredondo FD, Baxter L, Bensasson D, Beynon JL, Chapman J, Damasceno CM, Dorrance AE, Dou D, Dickerman AW, Dubchak IL, Garbelotto M, Gijzen M, Gordon SG, Govers F, Grunwald NJ, Huang W, Ivors KL, Jones RW, Kamoun S, Krampis K, Lamour KH, Lee MK, McDonald WH, Medina M, et al.: Phytophthora genome sequences uncover evolutionary origins and mechanisms of pathogenesis. Science 2006, 313 (5791) : 1261–1266.PubMedView Article

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              This article is published under license to 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.