Browse Subject Areas

Click through the PLOS taxonomy to find articles in your field.

For more information about PLOS Subject Areas, click here.

  • Loading metrics

Complete Genome Sequence of Sporisorium scitamineum and Biotrophic Interaction Transcriptome with Sugarcane

  • Lucas M. Taniguti ,

    Contributed equally to this work with: Lucas M. Taniguti, Patricia D. C. Schaker

    Affiliation College of Agriculture “Luiz de Queiroz”, University of São Paulo, Av. Pádua Dias 11, PO BOX 9, 13400-970, Piracicaba, São Paulo, Brazil

  • Patricia D. C. Schaker ,

    Contributed equally to this work with: Lucas M. Taniguti, Patricia D. C. Schaker

    Affiliation College of Agriculture “Luiz de Queiroz”, University of São Paulo, Av. Pádua Dias 11, PO BOX 9, 13400-970, Piracicaba, São Paulo, Brazil

  • Juliana Benevenuto ,

    ‡ These authors also contributed equally to this work.

    Affiliation College of Agriculture “Luiz de Queiroz”, University of São Paulo, Av. Pádua Dias 11, PO BOX 9, 13400-970, Piracicaba, São Paulo, Brazil

  • Leila P. Peters ,

    ‡ These authors also contributed equally to this work.

    Affiliation College of Agriculture “Luiz de Queiroz”, University of São Paulo, Av. Pádua Dias 11, PO BOX 9, 13400-970, Piracicaba, São Paulo, Brazil

  • Giselle Carvalho ,

    ‡ These authors also contributed equally to this work.

    Affiliation College of Agriculture “Luiz de Queiroz”, University of São Paulo, Av. Pádua Dias 11, PO BOX 9, 13400-970, Piracicaba, São Paulo, Brazil

  • Alessandra Palhares ,

    ‡ These authors also contributed equally to this work.

    Affiliation College of Agriculture “Luiz de Queiroz”, University of São Paulo, Av. Pádua Dias 11, PO BOX 9, 13400-970, Piracicaba, São Paulo, Brazil

  • Maria C. Quecine,

    Affiliation College of Agriculture “Luiz de Queiroz”, University of São Paulo, Av. Pádua Dias 11, PO BOX 9, 13400-970, Piracicaba, São Paulo, Brazil

  • Filipe R. S. Nunes,

    Affiliation College of Agriculture “Luiz de Queiroz”, University of São Paulo, Av. Pádua Dias 11, PO BOX 9, 13400-970, Piracicaba, São Paulo, Brazil

  • Maria C. P. Kmit,

    Affiliation College of Agriculture “Luiz de Queiroz”, University of São Paulo, Av. Pádua Dias 11, PO BOX 9, 13400-970, Piracicaba, São Paulo, Brazil

  • Alvan Wai,

    Affiliation Department of Microbiology, University of Manitoba, Winnipeg, Manitoba, Canada, R3T 2N2

  • Georg Hausner,

    Affiliation Department of Microbiology, University of Manitoba, Winnipeg, Manitoba, Canada, R3T 2N2

  • Karen S. Aitken,

    Affiliation CSIRO Agriculture, Flagship, Queensland Bioscience Precinct, 306 Carmody Road, St Lucia, QLD, 4067, Australia

  • Paul J. Berkman,

    Affiliation CSIRO Agriculture, Flagship, Queensland Bioscience Precinct, 306 Carmody Road, St Lucia, QLD, 4067, Australia

  • James A. Fraser,

    Affiliation Australian Infectious Diseases Research Centre, School of Chemistry and Molecular Biosciences, The University of Queensland, Brisbane, QLD, Australia

  • Paula M. Moolhuijzen,

    Affiliation Centre for Comparative Genomics, Murdoch University, Perth, Australia

  • Luiz L. Coutinho,

    Affiliation College of Agriculture “Luiz de Queiroz”, University of São Paulo, Av. Pádua Dias 11, PO BOX 9, 13400-970, Piracicaba, São Paulo, Brazil

  • Silvana Creste,

    Affiliation Centro Avançado da Pesquisa Tecnológica do Agronegócio de Cana—IAC/Apta Ribeirão Preto, São Paulo, Brazil

  • Maria L. C. Vieira,

    Affiliation College of Agriculture “Luiz de Queiroz”, University of São Paulo, Av. Pádua Dias 11, PO BOX 9, 13400-970, Piracicaba, São Paulo, Brazil

  • João P. Kitajima,

    Affiliation Mendelics Análise Genômica, Rua Cubatão 86, Cj. 1602, 04013-000, São Paulo, SP, Brazil

  •  [ ... ],
  • Claudia B. Monteiro-Vitorello

    Affiliation College of Agriculture “Luiz de Queiroz”, University of São Paulo, Av. Pádua Dias 11, PO BOX 9, 13400-970, Piracicaba, São Paulo, Brazil

  • [ view all ]
  • [ view less ]

Complete Genome Sequence of Sporisorium scitamineum and Biotrophic Interaction Transcriptome with Sugarcane

  • Lucas M. Taniguti, 
  • Patricia D. C. Schaker, 
  • Juliana Benevenuto, 
  • Leila P. Peters, 
  • Giselle Carvalho, 
  • Alessandra Palhares, 
  • Maria C. Quecine, 
  • Filipe R. S. Nunes, 
  • Maria C. P. Kmit, 
  • Alvan Wai


Sporisorium scitamineum is a biotrophic fungus responsible for the sugarcane smut, a worldwide spread disease. This study provides the complete sequence of individual chromosomes of S. scitamineum from telomere to telomere achieved by a combination of PacBio long reads and Illumina short reads sequence data, as well as a draft sequence of a second fungal strain. Comparative analysis to previous available sequences of another strain detected few polymorphisms among the three genomes. The novel complete sequence described herein allowed us to identify and annotate extended subtelomeric regions, repetitive elements and the mitochondrial DNA sequence. The genome comprises 19,979,571 bases, 6,677 genes encoding proteins, 111 tRNAs and 3 assembled copies of rDNA, out of our estimated number of copies as 130. Chromosomal reorganizations were detected when comparing to sequences of S. reilianum, the closest smut relative, potentially influenced by repeats of transposable elements. Repetitive elements may have also directed the linkage of the two mating-type loci. The fungal transcriptome profiling from in vitro and from interaction with sugarcane at two time points (early infection and whip emergence) revealed that 13.5% of the genes were differentially expressed in planta and particular to each developmental stage. Among them are plant cell wall degrading enzymes, proteases, lipases, chitin modification and lignin degradation enzymes, sugar transporters and transcriptional factors. The fungus also modulates transcription of genes related to surviving against reactive oxygen species and other toxic metabolites produced by the plant. Previously described effectors in smut/plant interactions were detected but some new candidates are proposed. Ten genomic islands harboring some of the candidate genes unique to S. scitamineum were expressed only in planta. RNAseq data was also used to reassure gene predictions.


Sugarcane is an important crop worldwide due to its capability to store large amounts of sucrose in the stem, supplying more than half of the world’s sugar consumption for centuries [1]. Currently, it is also considered the most efficient bioenergy crop for ethanol production [2]. One important factor impairing the increase of sugarcane production is the severity of some diseases affecting the crop [3]. Sporisorium scitamineum, causal agent of the sugarcane smut disease, is a constant concern among producers and breeders, since the disease has been found at low levels in all cultivated areas. There are three distinct phases during the fungal life cycle: haploid yeast-like sporidia, dikaryotic hyphae and diploid teliospores (Fig 1). To infect the host, a combination of two haploid sporidia belonging to opposite mating-types is necessary to form an infective hyphae. Fungal hyphae differentiate appressorium structures to penetrate plant tissues. Sugarcane infected plants show a profound metabolic modification resulting in the development of a whip-like structure from the stalk apex composed of a mixture of plant and fungal tissues. Within these structures millions of dark teliospores develop and are responsible for disseminating the disease [4]. Under appropriate environmental conditions, teliospores germinate promycelia leading to meiosis and production of haploid sporidia that will become infective after the fusion of compatible sporidial cells [5]. Hyphal fusion and sexual cycle are crucial for disease establishment and dissemination. In vitro, S. scitamineum is maintained easily as colonies of yeast-like cells derived of budding sporidia and hyphal colonies, which facilitates genetic studies [6]. The only part of the life cycle restricted to host tissues so far is the development of teliospores. Sugarcane plants are prone to pathogen attack in the early stages of growth, however, whips are observed only after 45 days in more susceptible varieties. Infected sugarcane plants have abnormal grass-like growth, reduced culm diameter, and very fibrous stalks which are poor in sugar content [4].

Fig 1.

(A) Developmental stages in the S. scitamineum life cycle: diploid teliospores (2n); haploid yeast-like sporidia (n) after meiosis (R!); hyphal fusion. (B) Scanning electron micrograph of spores adhered to sugarcane bud surface. (C) Germination of spores on bud scale epidermis and tube-like promycelium formation at 6 hai (hours after inoculation); photomicrograph of tube-like promycelium stained with lactophenol-cotton. (D) Photomicrograph of apressorium formation 48 hai stained with lactophenol-cotton blue; (E) Photomicrograph of S. scitamineum growth on parenchyma cells of bud tissue observed at 120 hr stained with lactophenol-cotton blue. (F) Photomicrograph of S. scitamineum intracellular growth on parenchyma cells of white whip portion; stained with lactophenol-cotton blue. (G) Photomicrograph of black whip portion showing the mature spore liberation. Scale bar = 5 μm

Although little information is available from S. scitamineum biology, more is known about its close relative Ustilago maydis, a smut fungus of corn. Noteworthy in the latter, are a number of genes arranged in groups encoding uncharacterized secreted proteins associated with the control of fungal colonization in host plants [7]. Although among various smut fungi the genomes are similar in size and gene content, disease symptoms related to the formation of fungal sporangial structures and host specificity are unique to each smut species/plant interaction, and therefore comparative analysis may help to uncover genes that trigger specific host responses [8]. This work presents the fully sequenced genome of S. scitamineum SSC39B and a draft of isolates BSES, which enabled us to perform comparative analysis to another genome sequence recently published [9]. The complete sequence of each chromosome of S. scitamineum SSC39B also enabled comparisons regarding genome organization to the closest smut species S. reilianum[10]. Fungal transcriptome profiles during in vitro growth and throughout its life cycle in planta at two time points revealed candidate genes unique to the interaction with sugarcane.

Materials and Methods

Ethics Statement

S. scitamineum SSC39B haploid cells derived from a single mating-type were used for complete genome sequencing. The cells were obtained from a teliospore (SSC39) isolated from a whip developed in the sugarcane susceptible clone IACSP98-2053. The whip was collected from an experimental area of “Centro de Cana—Instituto Agronômico de Campinas” (21°12′04″S; 47°52′20″W), and no specific permissions were required for sampling diseased plants in this location. The isolates BSESs were isolated from a teliospore isolated from a whip developed in a susceptible sugarcane clone Q117. The whip was collected from an experimental field at the Sugar Research Australia pathology farm at Woodford, Australia (26°55′43”S; 152°46′38.3”E), no specific permissions were required for sampling diseased plants in this location.

Strains and sequencing strategies

S. scitamineum haploid cells derived from a single mating-type were used for complete genome sequencing. A single yeast-like colony was isolated and mating-type was assigned as described in Bölker et al. (1992) [11]. The S. scitamineum SSC39B genome was sequenced using the long reads PacBio technology [12]. DNA was extracted using “DNeasy Blood and Tissue Kit” (Qiagen). Five SMRT cells (P5-C3 chemistry) were used in the sequencing process, generating 2.2 Gbp of raw data corresponding to more than 100 fold of sampling depth (738,568 reads with average length of 3,047 bp). Besides PacBio sequencing, paired-end libraries of the same strain were sequenced using Illumina HiSeq 2000. A whole cell DNA library was prepared for sequencing using the kit Nextera DNA Sample Preparation Workflow (Illumina paired-end). A total of 85,465,786 reads of 100 bp in length (approximately 8.5 Gb) corresponding to more than 400 fold of sampling depth were analyzed using FASTQC (ver. 0.10.1) and Seqyclean (ver. 1.8.10) to filter low quality sequences (phred quality below 20).

In addition, an isolate of the opposite mating-type (SSC39A) was partially sequenced using a BAC genomic library that was constructed using the protocol described by Peterson et al. (2000) [13] and the “CopyControlT BAC Cloning Kit” (Epicentre). The genomic library is composed of 2,880 clones with an insert size average of 92 kbp representing 10 X coverage of the genome. Forty-eight BAC clones were selected from pools of 30 plates (96 clones each). Included in this analysis were PCR amplifications for the mating-type genes using the enzyme “GenomiPhi” (GE Healthcare Life Sciences) in combination with following primers for: Locus b (UsibEF 5’ -GCTGGTCCAACATTCTCC- 3’ and UsibER 5’ -CGCTTGCTCTCTGCTTAG- 3’) and Locus a (SSC39AF 5’ -AGATCGGGAAGAAAATG-AGC- 3’ and SSC39AR 5’ -TTGTATCATCGTGGGTCTCTGG- 3’). Sequencing data were generated with Illumina HiSeq technology, also with paired-end reads of 100 bp in length. These reads were used to assemble the mating loci sequence of SSC39A.

Two additional Australian isolates, BSES15 and BSES17, which represent contrasting mating-types, were also sequenced using the Illumina platform. Illumina sequencing generated paired-end 90bp reads on an Illumina GAIIx and 5,588,889 read pairs (1.01 Gbp) and 4,335,980 read pairs (0.78 Gbp) were generated for isolates BSES15 and BSES17 respectively.

Genome Assembly

Given the high coverage of PacBio reads, the HGAP.2 assembler [14] was used with default parameters. The resulting assembly was composed of 59 contigs (19 Mbp) and 11 singletons (88 kbp). A final genome version was built manually with the alignment results, generating 26 final contigs (genome V0). CLC Genomics Workbench V7.01 (CLC Bio) was then used to align all Illumina reads against this assembly. The consensus of the aligned Illumina paired-end reads (parameters: global alignment, minimum of 0.9 read length with minimum 90% identity) against the V0 genome was then saved as the V1 S. scitamineum genome. This assembly was aligned against the S. reilianum genome using cross_match ( The mitochondrial genome was assembled individually (CLC Genomics Workbench V7.01) by using the mitochondrial sequence of S. reilianum as reference. The DNA data of BSES15 and BSES17 was analyzed using the Blue error correcting algorithm [15] and assembled using the Velvet Optimiser algorithm of the Velvet assembler [16] at an optimal k-mer length of 77.

Pulse field gel electrophoresis and hybridization

DNA plugs for pulse-field gel electrophoresis were prepared using CHEF Genomic DNA Plug Kit (Bio-Rad Laboratories Inc.) as described previously [17]. Fragments from 200 to 2200 kbp were separated in contour-clamped homogeneous electric field electrophoresis, conducted in a CHEF II (Bio-Rad Laboratories Inc.) apparatus. Pulse-field electrophoresis was carried out as follows: a 1% agarose gel in 0.5x TBE buffer was held at 14°C by a temperature-controlled cooling unit for 15 h, at 6 V x cm-1, electric current was regulated with the initial pulse = final pulse = 70 s, and a second step for 11 h, 6 V x cm-1 (initial pulse = final pulse = 120 s). Size of bands were estimated by the software Kodak Digital Science 1D 3.0.2, using Pulse Marker 225-2200 kbp (Sigma-Aldrich Corp.). Hybridizations were performed using “AlkPhos” Direct Labeling and Detection System’ (GE). Probes used were sequences of a telomere insert of pTEL13 [18] and a PCR amplicon containing the rDNA internal transcribed spacer region (ITS1, 5.8S and ITS2) of S. scitamineum generated with primers: Hs 5’ -AACACGGTTGCATCGGTTGGGTC- 3’ and Ha 5’ -GCTTCTTGCTCATCCTCACCACCAA- 3’) [19].

Genome and Proteome Annotations

Gene prediction was accomplished by using the U. maydis gene model calculated by the Augustus software [20] integrating the RNAseq paired-end reads (see further below). The tRNAs were identified by the tRNAscan-SE program [21]. Repetitive elements were identified using RECON [22], setting BLASTn to a cutoff of e-value ≤ 1 × 10-10. Only families with more than 15 members with sequences ranging from 500 to 2,500 bp were considered to be repetitive elements. BLASTx searches against UNIREF50 were performed to identify transposable elements containing one of the following PFAM domains: PF00078, PF01498, PF03108, PF03184, PF03221, PF10551, PF13359 [23]. RepeatMasker [24] annotation supplied with our custom library (RECON + RepBase v. 19.11) was used to define repetitive elements.

Telomeric repeats were identified by the Tandem Repeat Database (TRDB) tool [25]. The length and localization of each telomere as well as the subtelomeric predicted genes within the chromosome ends (50 kbp) were manually checked.

Predicted proteins were analyzed using the Blast2Go tool V2.7.2 (BLASTp with cutoff e-value < 1 x 10-5) [26] and Fisher’s exact test was used to detect enrichment of GO terms (p-value ≤ 0.05). The programs SignalP V4.0.1c [27], TMHMM V2.0c [28] and predGPI [29] were used to predict those proteins that are potentially secreted and to define the secretome. The HMMs from dbCAN [30] were used to predict and classify the CAZymes. Reference proteins of the PHI-base (Pathogen-Host Interaction database) [31] were used to obtain experimental evidences to our predicted proteins using BLASTp e-value < 1 x 10-14 and query coverage of more than 80%.

The mitochondrial genome was annotated with the MFannot program combined with RNAweasel [32]. The potential rnl gene and putative ORFs, including intron/exon junctions, were further resolved with ORFfinder and by comparative sequence analysis using the BLAST suite of programs and by aligning intron containing genes with orthologs that lack insertions. Alignments were performed with the MAFFT program [33] with settings that allow for long insertions and short conserved regions and these alignments were manually adjusted with the Genedoc program to narrow intron/exon junctions [34]. Intergenic regions were examined with ORFfinder to identify potential remnants of ORFs, in particular eroded homing endonuclease coding segments.

Comparative genome analysis

Synteny studies between chromosomes of S. reilianum and S. scitamineum were performed using BLASTn (cutoff e-value ≤ 1 x 10-5) combined with Circos [35] to draw the relationships between chromosomes. In addition the complete genome of strain SSC39B was compared to the BSES assembly using cross_match. The scaffolds from the genome assembly of the strain 2014001 (Genbank: JFOL00000000.1) [9] was aligned using MUMmer (V3.0), and BEDTools [36] merging local similarities in a range of 1,500 bp of the genome alignment.

Comparisons of predicted coding sequences among the three strains were performed using BLASTn. Genes particular to the SSC39B were defined by considering either “no hit” or an e-value > 1 x 10-5.

The S. scitamineum SSC39B proteome was compared to all predicted proteins of U. maydis, U. hordei and S. reilianum (MIPS database [37]). OrthoMCL with default parameters was used to determine the orthologous groups among the proteomes [38]. Visualization of the OrthoMCL results was obtained with a four-way-Venn-diagram drawn in R language using the Venn diagram package [39].

Phylogenetic analysis of mating-type protein sequences were performed based on a multiple sequence alignment generated by T-COFFEE [40]. The best amino acids substitution model that fits the data was determined by using the Akaike Information Criterion (AIC) in the software ProtTest v3.2 [41]. Maximum likelihood trees were obtained for each protein considering the heuristic method NNI (Nearest Neighbor Interchange) for searching through treespace and aLRT SH-like (approximate Likelihood-Ratio Test with Shimodaira-Hasegawa-like procedure) for quantifying branch support using PhyML v3.0 [42]. S. scitamineum protein sequences of both mating-types and sequences for close related species available on GenBank were included in the analysis.

Transcriptome assay and analysis

The S. scitamineum SSC39 teliospores (> 90% viability) were mixed with saline solution and used to inoculate sugarcane plants of the smut susceptible variety “RB92-5345”. Single budded sets of 7 month-old plants were surface disinfected, heat treated (52°C for 30 min in water bath, 1 kg of buds/6L of water) and incubated for 16 h at 28°C. Sets were then placed on trays with buds facing upwards, and inoculated using the wound-paste method [43]. Pots were kept in the greenhouse arranged into a completely randomized experimental design. Fungal transcriptome profiles were obtained 5 days after inoculation (DAI) from tissues of the breaking buds and at 200 DAI from the base of the whip-like structure emission (where intense fungal cell division and sporogenesis occurs). For in vitro transcriptome analysis, haploid yeast-like cells of opposite mating-types were grown separately in liquid medium [44] in a orbital shaker for 15 h at 28°C. Cells of both mating-types were mixed prior to RNA extraction. All samples were frozen in liquid nitrogen immediately after collection and stored at -80°C. Three biological replicates were systematically used.

Total RNA extraction from 5 DAI samples was performed using the lithium chloride based method [45, 46]. TRIzol Reagent (Life Technologies, UK) was used for RNA extraction from 200 DAI samples and control cells. DNA was extracted from the same 5 DAI samples to confirm infection before the construction of RNAseq libraries. The rDNA ITS region was amplified with primers Hs and Ha [19] to confirm the presence of S. scitamineum.

Libraries were constructed following Illumina manufacturer’s protocol of the “TruSeq RNA Sample Prep v2 Low Throughput (LT)” kit. Paired-end sequencing was performed on the Illumina platform (HiScanSQ). Reads were analyzed by FASTQC (ver. 0.10.1) and low quality bases (phred ≥ 20), Illumina adapters and poly-A tails were removed using the Seqyclean program (ver. 1.8.10). The RNAseq fungal reads from the 5 DAI and 200 DAI plant materials were recovered from the total reads by mapping to the complete genome of S. scitamineum SSC39B strain using Bowtie2 [47]. RNAseq reads were also aligned to all S. scitamineum coding sequences, using Bowtie2 with default parameters to determine the % of CDSs length coverage.

Differential transcript accumulation among treatments (5 DAI and 200 DAI and controls) was observed using the CLC Genomics Workbench V7.01. Fungal reads were mapped to CDSs of S. scitamineum (100% of nucleotide identity and 98% of coverage). The mapping of at least one read pair in all three replicates was considered to be a positive match. Scaling approach as implemented in the CLC software was used as the normalization method. Baggerley’s test and the false discovery rate (FDR) with a significance level of ≤ 0.01 and Log2FoldChange ≥ 2 or ≤ -2 (treatment/control) were applied to generate a set of differentially expressed genes. Transcripts were considered specific to the interaction with sugarcane if at least one pair of reads mapped to all three replicates of each of the treatments and none to the control. Enrichment test of GO terms were performed with the BLAST2GO tool using the two-side Fisher’s Exact Test (p-value < 0.05).


General Results

PacBio sequencing allowed us to determine the complete sequence of S. scitamineum SSC39B chromosomes. The final assembly comprises 19,979,571 nucleotides distributed in 26 contigs (no gaps within contigs). Telomere motifs were identified for 23 chromosomes longer than 475 kbp in length (Table A in S1 File). The other three contigs (24, 25, 26) have 87,293, 82,225 and 99,152 kbp, respectively, and are also found in the assemblies of 2014001 and BSESs genomes (Figure A in S1 File). The results of PFGE hybridized with telomeric probes (Figure B in S1 File) confirmed the presence of a DNA band of around 100 kbp. Sequence analysis revealed that these contigs are composed of repetitive elements (Figure A in S1 File) and have few predicted genes supported by RNAseq. At this time remains to be established if all of the three assembled contigs are chromosomes of S. scitamineum or if they are misassembles of one or more small chromosomes.

The rDNA cluster was found to be close to the end of chromosome numbered 23 and three copies were assembled. Hybridization data (Figure B in S1 File) together with the coverage of Illumina reads allowed us to estimate that there were 130 copies of rDNA units comprising the rDNA region. Unexpectedly, the length of the chromosome harboring the rDNA sequence varied between the two isolates of the same genetic background but with opposite mating types (Figure B in S1 File). This result was confirmed using hybridizations with probes prepared from two independent regions of the rDNA (data not shown). The rDNA gene cluster is composed of 5,979 bp (18S—5.8 S—28S) and the first copy is located at coordinates 119,074 of chromosome 23. The 5 S rDNA genes are scattered among the chromosomes and 14 copies were identified. Similarly, 111 tRNA genes corresponding to all 20 amino acids were found to be dispersed among the chromosomes (Table B in S1 File).

Assemblies of the BSES15 and BSES17 isolates generated 5,331 contigs. A total of 19,234,547 bp (99%) aligned to the strain SSC39B genome with the following variation: 0.075% substitutions, 0.007% deletions and 0.038% insertions. The comparison between the genome sequences of the SSC39B and 2014001 strains (the last presenting 19,619,026 bp organized in 35 scaffolds [9]) showed that most of the chromosomes assembled are covered. However, the mitochondrial genome was poorly represented in the 2014001 assembly and nuclear genome derived scaffolds do not extend over repetitive regions as well as subtelomeric regions (Fig 2).

Fig 2. Representation of all chromosomes and contigs assembled of the strain SSC39 genome compared to the strain 2014001 scaffolds.

Regions present in the strain 2014001 are shown in green blocks, delimited by black borders. White regions represent sequences unique to the strain SSC39 assembly. The analysis was performed using MUMmer 3 and parameters = -maxmatch -c -L -b -l 500. Red line above the chromosome 2 indicates the region containing the mating-type loci

The S. scitamineum strain SSC39 genome comprises 6,677 protein coding genes, with an average number of introns per gene of 1.94, and 51% of the genes (3,415) have no introns (Table C in S1 File). Most of the CDSs are between 500 and 2,000 kbp in length (3,861) and only a few are larger than 7 kbp (34) (Figure C in S1 File). In general most of the CDSs have an ortholog in the S. reilianum genome (Fig 3).

Fig 3. Syntenic view of two chromosomes of S. reilianum that merged as one in S. scitamineum.

Links represents alignment length of more than 1 kbp obtained by BLASTn (e-value < 1 x 10-5). The first outer circle represents the chromosome and scale is coordinates in base pairs. The second indicates the GC content followed by predicted coding regions of the plus and minus strands. Bars display the % of identity to orthologous in S. reilianum. The most inner circle represents the RNAseq coverage of each chromosome region. Red lines are RNAseq data of S. scitamineum growing in planta and blue lines growing in vitro. Circle images of all chromosomes are available in the Supporting Information S3 File.

Of the total S. scitamineum predicted genes, 6,479 (97%) are supported by mapping the reads produced by RNAseq analysis. A total of 198 have no coverage, but 72 of these have significant matches (BLASTn e-value ≤ 1 x 10-14 and query coverage ≥ 75%) to putative CDSs of U. maydis, S. reilianum or U. hordei genomes. Repetitive elements represented 1.24% of the S. scitamineum genome. Gene Ontology was used to assign GO terms to the set of predicted proteins to improve the organization of the annotation data [26]. GO terms were successfully assigned to 3,682 proteins (55.2%) (Table A in S2 File). As expected, top hit species results (5,078) are with S. reilianum proteins (Figure B in S2 File).

Telomeric and subtelomeric regions

Telomeric arrays of tandem repeats were localized at both ends of all chromosomes, with an average repeat length of 76 bp that range from 32 bp to 140 bp (Table A in S1 File). The subtelomeric gene set comprises 800 predicted genes coding for proteins. Thirty-five helicase genes located in 22 chromosome ends were found, which include 3 predicted telomere-linked RecQ-helicase (TLH) genes, a typical feature of subtelomeric regions. As observed in other fungi, a notable group of genes related to niche adaptation (carbon utilization and catabolism) and pathogenicity were also reported (Table D in S1 File). Yet, some of the uncharacterized genes located near the chromosome ends are potentially associated with interaction with sugarcane (discussed later) (Fig 3).

Chromosomal rearrangements and mating-type analysis

Comparative genomics showed that among the four smut fungi genomes used here S. scitamineum and S. reilianum are the closest, with an average nucleotide identity of 85.4% among all predicted CDSs. Eight S. scitamineum chromosomes display different arrangements with regards to S. reilianum as well as breaking points enriched with transposable elements (Figs. in S3 File). One of such breaking points is a region relevant to the biology of S. scitamineum that links the two mating-type loci referred to as a and b. In S. scitamineum, both loci are located 59 kbp apart on chromosome 2, characteristic of a bipolar mating system [48] (Fig 4). Chromosome 2 of S. scitamineum is homologous to chromosomes 1 and 20 of S. reilianum, which also harbor the mating-type loci b and a, respectively, in a tetrapolar arrangement [49]. Pairwise comparisons of these chromosomes revealed that the breakpoint occurred at the position 825,021 of S. scitamineum chromosome 2 (Fig 4). Within this inter-mating-type loci several remnants of DDE_1 and LINE transposons were noted. In addition, 20% of the sequence in between bases 801,345 and 854,308 is composed of repetitive elements, a much larger percentage when compared to the respective 1.24% of the genome.

Fig 4. Blocks of synteny between chromosome 2 of S. scitamineum and chromosomes 1 and 20 of S. reilianum and schematic representation of the linked mating-type loci in S. scitamineum.

Blue areas correspond to syntenic regions considering BLASTn e-value ≤ 1 x 10-5. Red lines represent the expansion of the region containing the mating type genes in S. scitamineum located at positions 792,295 bp to 863,606 bp of the chromosome 2. The chromosome breakpoint is identified and indicated by a red dot above the sequence. Genes are indicated by gray arrows placed according to transcriptional orientation and the transposons related sequences are highlighted in red. Letters represent functional annotation of encoded proteins: A) c1d1 putative nuclear regulator; B and C) homeodomain transcription factor bE1 and bW1, respectively; D) nat1 putative N-terminal acetyltransferase; E, F, M, N, P, Q and R) Uncharacterized protein; G, J, M and S) Related to transposase; H) sla—cytoskeleton assembly control protein; I) RPN5-26S proteasome regulatory protein; K) hhp1 casein kinase-1; L) related to reverse transcriptase; O) arp2/3—actin related protein 2/3 complex; T) lba1 left border a locus; U) and V) pheromone gene mfa1.2 and mfa1.3, respectively; W) pra1 pheromone receptor gene; X) Rba2—right border a locus; Y) pan1—pantoate-beta-alanine ligase.

The mating-type loci of the SSC39B complete genome sequence are equivalent to MAT1 of U. hordei and a1 of U. maydis, as determined by the similarity to genes of the mating loci (Figure A in S4 File). Based on the percentage of sequence identity, phylogenetic analysis and gene organization comparisons (Figures A and B and Table A in S4 File), the mating-type proteins of close and distantly related smut species differ substantially. BLASTp analysis shows that predicted proteins from whole genome of S. scitamineum have, on average, 82.5, 75.4 and 72.4% of identity with proteins of S. reilianum, U. maydis and U. hordei, respectively. In contrast, their mating-type proteins have lower percentages of identity (Table A in S4 File).

Phylogenetic analysis was performed including other smut mating-type protein sequences extracted from databases and proteins encoded by the opposite mate pair of S. scitamineum obtained by sequencing BAC genomic library inserts (Figure B in S4 File). Proteins encoded by b locus (bE1/bE2 and bW1/bW2) of S. scitamineum (SSC39A and SSC39B) are more close related to each other than to the bE and bW proteins from related species; whereas proteins encoded by its a locus (pra1/pra2 and mfa1.2/mfa1.3/mfa2.1/mfa2.3) cluster preferentially with alleles from others species (Figure A in S4 File). The genomic context indicates that the order and orientation of the genes in the b locus are conserved (Figure B in S4 File). Otherwise for the a locus, these settings vary among species and between alleles of the same species, especially by the presence of rga2 and lga2 genes in the a2-type alleles that are absent in the a1-type (Figure B in S4 File). The a locus of S. scitamineum and S. reilianum also differs from that of U. maydis and U. hordei by the presence of a second pheromone gene, named mfa1.3 in S. scitamineum due to its similarity to the pheromone mfa2.3 from S. reilianum. It is noteworthy that this extra copy of mfa in S. scitamineum lacks the characteristic CAAX motif (C, cysteine; A, aliphatic amino acid; X, any amino acid) at its carboxyl terminus. Pheromone response elements (PREs), with a binding motif “ACAAAGGGA” for transcription factor prf1, were found close to the mating-type genes in S. scitamineum and in the others fungi analyzed, with the exception of Malassezia species (Figure B in S4 File).

The mtDNA Annotation

The mitochondrial genome has 88,018 bp and presents the standard 14 protein coding genes (nad2, nad3, nad4, nad4L, nad5, nad6, cox1, cox2, cox3, cob, atp2, atp6, atp9 and rps3) along with 11 unknown hypothetical ORFs (Table A and B in S5 File). The last nucleotide of the nad2 gene is the first one of the nad3 gene. Among the RNA encoding genes, 22 tRNA genes were detected representing all 20 amino acids, and two tRNAs for each Ser and Met; the rns and rnl genes were also present and finally two potential copies of the rnpB gene were noted. However one copy is interrupted by tRNA(V) and may represent an eroded copy of the gene or a misannotation based on the presence of analogous RNA folds that resemble components of the rnpB encoded RNA molecule. Among the various genes 24 group I introns were noted, of these 23 encoded putative ORFs. The cox1 gene was the most intron rich gene with 11 insertions. Nineteen LAGLIDADG type endonuclease ORFs were noted and among these ORFs four showed evidence of degeneration, i.e. the fragmentation due the presence of premature stop codons. Four intron ORFs belong to the GIY-YIG family of homing endonucleases and two appear to have eroded, as above due to the accumulation of mutations and the presence of premature stop codons. A few eroded freestanding GIY-YIG ORFs were noted in the intergenic regions but these were quite fragmented and thus not annotated. The atp9, cox1, nad1, nad5, and nad6 genes were all followed by duplicated versions that lacked the N-terminal components. Differences between the complete version of the gene and the partial duplicated version fragments of GIY-YIG type ORFs could be detected by programs such as ORFfinder or by BLASTx.

Comparative proteome

A total of 6,475 groups of homologs were described among the four smut species analysed (S. scitamineum, S. reilianum, U. maydis, U. hordei), each one containing at least two proteins (Table A and Figure A in S6 File). The largest intersection was the one comprising the four species, with 5,507 orthologous groups (85.05%), among them, 5,347 containing exactly one ortholog from each proteome. S. scitamineum proteome contains few groups harboring paralogs, thus, most of their genes are single copy (94.3%) (Table 1). The largest paralog family has 61 members related to ATP-dependent DNA helicase (RecQ), some of which identified in close vicinity of telomeres as mentioned previously.

Table 1. Comparative analysis of orthology among four smut fungi obtained by OrthoMCL.

The OrthoMCL analysis resulted in a few unique orthologous clusters for each species that are represented by potentially duplicated genes (Table B in S6 File) and in a higher number of singletons (genes not assigned to any OrthoMCL cluster), which represent single copy genes unique to each species (Table 1). Most of the S. scitamineum unique genes (23 clusters including 89 proteins and 349 singletons) are related to transposable elements and uncharacterized proteins, but RNAseq reads suggest that some of these genes are active at the transcriptional level (Table C in S1 File). Among genes with predicted functions, there are for example, putative effectors related to the Mig1 gene family (g3918_chr10_Ss and g3919_chr10_Ss) and a group of six paralogs related to sterol delta 5,6-desaturase (g2628_chr06_Ss, g3812_chr10_Ss, g4371_chr12_Ss, g6420_chr22_Ss, g6606_chr24_Ss and g6623_chr24_Ss) (Table B in S6 File).


The S. scitamineum genome encodes 527 predicted proteins showing a positive match to signal peptides, of these 342 have no transmembrane domains and 305 are also not anchored by GPI. These proteins were selected to compose the secretome of S. scitamineum. We used the HMMs from dbCAN to identify 54 CAZymes in the secretome, including eight containing carbohydrate binding modules (CBM), 11 carbohydrate esterases (CE), 30 glycoside hydrolases (GH), one glycosyl transferase (GT), one polysaccharide lyase (PL) and six with auxiliary activities (AA) (Table F in S1 File). Nearly 30% of secretome (93 proteins) have at least one GO term assigned according to Blast2GO results (Figure A in S7 File).

The secretome of S. scitamineum is composed of 148 (48.5%) predicted proteins of uncharacterized function. Moreover, 38 of these proteins are considered unique to S. scitamineum by OrthoMCL analysis (Table B in S6 File), wherein 29 proteins are singletons and nine proteins belong to three orthologous clusters.

We analyzed genes of the secretome expressed at 5 DAI and have constructed a heatmap showing the modulation of these genes under the three tested conditions (Fig 5). According to the functional annotation results, they encode hydrolases, peptidases, oxidases and reductases as well as several genes of unknown functions. The modulation of gene expression is particular to each time point during the interaction with sugarcane and to in vitro growth.

Fig 5. Genes encoding secreted proteins and their expression level under all three conditions: in vitro, 5 DAI, 200 DAI as calculated by CLC Genomics Workbench.

Heatmaps were obtained using the function heatmap.2 of the package gplots in R language

Transcriptome Analysis

The data revealed that 56.6%, 41.3% and 54.7% of RNAseq trimmed reads mapped in pairs to S. scitamineum CDSs in vitro, 5 DAI and 200 DAI, respectively (Table A in S8 File). The number of CDSs detected in each experiment was 6,213 (93%) in vitro, 437 (6.5%) at 5 DAI and 6,183 (92.6%) at 200 DAI. The RNAseq data were analyzed based on a combination of expression change threshold of Log2FoldChange (treatment/control) ≥ 2 or ≤ -2 among treatments, and relied on FDR as defined by CLC software. In addition, considering the relatively low number of fungal reads recovered from the assay in planta at 5 DAI, we have analyzed the most expressed genes in a given treatment considering the number of mapping reads per CDS normalized by scaling and CDS length. In this case, only genes mapped by at least one pair of reads in all three replicates were taken into account. We called these genes preferentially expressed (Table B in S8 File). The mapping levels of reads to genes preferentially expressed were between 6 and 10 times higher than the average number of reads mapped per CDS.

The number of preferentially expressed genes encoding secreted proteins is higher in planta (16) than in vitro (3). Among them, only two genes were in common to the two time points analyzed in planta (5 DAI and 200 DAI): the endoglucanase (g3790_chr09_Ss) and an uncharacterized secreted protein (g3890_chr10_Ss). Most of the genes considered preferentially expressed in vitro encode proteins related to energetic metabolism and growth, including an alternative oxidase (g2905_chr06_Ss), which is the most expressed, ATP-ADP carrier protein, elongation factor 1-alfa, polyubiquitin and several ribosomal proteins.

The results of the differentially expressed genes, obtained comparing each treatment in planta to the in vitro control, resulted in 125 genes detected at 5 DAI, of these 119 are up-regulated and six down-regulated in planta (Table C in S8 File). At 200 DAI 907 genes were detected as differentially expressed, of these 641 are up-regulated and 266 down-regulated (Table D in S8 File). GO terms assigned to down-regulated genes at 5 DAI are enriched in members of the mRNA binding functional group, and processes related to carbohydrate metabolism, oxidation-reduction and cellular respiration (Table E in S8 File). Up-regulated genes at 5 DAI are enriched in functions related to transporter activity and molecular/signal transduction (Table C in S8 File). At 200 DAI, the most enriched GO terms among down-regulated genes are oxidoreductase activity and mitochondrion cellular component. Up-regulated genes at 200 DAI are enriched with terms of hydrolase activity acting on glycosyl bonds and carbohydrate metabolic process (Table D in S8 File).

Among differentially expressed genes up-regulated in planta (5 and/or 200 DAI) 78 encode secreted proteins, some of them are related to host attack, nutrient acquisition and chitin modification. Table 2 summarizes the most relevant proteins detected as differentially expressed.

Table 2. List of selected differentially expressed genes up-regulated in planta. For complete list view Tables C and D in S8 File.

Searching for fungal genes expressed only in planta we found one gene specific to the interaction at 5 DAI (g4078_chr10_Ss), which encodes an uncharacterized protein, not secreted and with no conserved domains detected. Expressed only at 200 DAI are 131 genes: six of them (g5153_chr15_Ss, g5152_chr15_Ss, g5155_chr15_Ss, g3771_chr09_Ss, g4550_chr12_Ss, g3890_chr10_Ss) are also expressed at 5 DAI (Table F in S8 File), 108 encode proteins of unknown function, and 38 encode proteins of the secretome. The GO terms enrichment analysis revealed that extracellular region is the prevalent term. This set of 132 fungal genes is probably related to fungus/host interaction and may contain effectors associated with this singular interaction. Yet, the presence of one gene expressed particularly at 200 DAI encoding a secreted cysteine-protease inhibitor (g2337_chr05_Ss) may be related to the fungal defense against plant proteases. Eight of these genes have homologues in the PHI-base (Table G in S1 File), strengthening its involvement in S. scitamineum pathogenicity. For instance, mutations in U. maydis orthologs of genes g5161_chr15_Ss (PHI:932), g2659_chr06_Ss (PHI:910) and g3271_chr08_Ss (PHI:23) led to reduced virulence, and in the ortholog of g672_chr01_Ss (PHI:907) led to pathogenicity loss of the maize pathogen [7, 50].

The genome context of the genes expressed particularly in planta revealed the presence of ten islands in chromosomes 2, 6, 10, 11, 12, 14, 15 and 16 (Fig 6). Most of the genes are of uncharacterized function and encode secreted proteins ranging in size from 114 to 1257 amino acids. Mig1 related genes are in the chromosome 10 island and genes of the protein family Eff1 effectors are in an island of chromosome 11. Orthologous for 27 (22.9%) of these genes were not found in the genome of S. reilianum, the closest species, as well as in U. maydis and U. hordei, according to OrthoMCL analysis.

Fig 6. Chromosome segments representing the organization of genes in islands (color coded arrows and note colors beneath the bars).

Expression at 200 DAI (heatmap red scale) and in vitro(heat map blue scale) are compared using the normalized number of mapped Illumina paired end reads, represented by the scales under each chromosome island. Gene names are presented at the borders of each segment of the chromosome, numbers represent the coordinates of these islands in kbp and red dots represent singlets as defined by OrthoMCL


The genome of S. scitamineum

The present study describes the successful use of deep coverage sequencing data combining long and short read strategies to achieve the complete sequence from telomere to telomere of each chromosome of the sugarcane smut pathogen S. scitamineum. Comparisons of the three available genomes of S. scitamineum, the SSC39 and BSES strains determined in this work and the published sequence of the strain 2014001 [9] showed few polymorphisms. However, we uncovered new information by revealing repetitive elements, subtelomeric regions and the mitochondrial DNA sequence. We also analyzed the chromosomal arrangement in comparison with the genome of the closest related species S. reilianum. Although, genomes of smut fungi are poor in repetitive elements compared to other fungi, the sequences associated with breaks in synteny between the two genomes revealed the presence of eroded transposable elements. We did not find complete copies of these elements. The genome of S. scitamineum is highly compact but similar to the genome sizes of other smut fungi [51] as well as to the gene predictions described for U. maydis, S. reilianum and U. hordei genomes that shows respective 6,675, 6,902 and 7,111 genes. Both the S. reilianum and U. maydis genomes were described as harboring 1% of transposable elements and S scitamineum harbors 1.24% in contrast to U. hordei that contains 3% of such elements [8].

We defined the location and number of rDNA repeat copies and surprisingly, based on hybridizations, there is a significant variation in chromosome length containing the rDNA cluster between the two mating types of the same genetic background. It has been reported that the copy number of the rDNA genes can vary spontaneously before meiosis [52]. The significance of this difference remains to be studied in S. scitamineum.

Besides the hallmark of telomeric encoded helicases, the subtelomeric sequences harbor genes potentially associated with host adaptation and pathogenicity, a common characteristic among fungi [53, 54]. Although this has not been shown for smut, some of the genes identified were related to sexual cycle, differentiation, sporulation, and to toxin detoxification and resistance. Subtelomeric regions are prone to contain polymorphic regions within genomes of different strains since telomere and subtelomere repeated sequences might favor rearrangements [55, 56]. Investigation of these regions among isolates may offer a better understanding of genetic diversity within fungal populations. Genes encoding proteins of unknown function arranged in clusters were also found within the edges of subtelomeric regions. Some of these regions are indeed associated with host/parasite interactions with sugarcane, since transcriptomic data showed the expression of these genes only in planta.


The S. scitamineum mtDNA was determined to be comprised of 88,018 bp. The largest mitochondrial genome currently reported is from Rhizoctonia solani with 235,849 bp (NC_021436), which is in contrast to the relatively small mtDNA in the fission yeast Schizosaccharomyces pombe, with 19,431 bp (NC_001326). Among the Ustilagionomycotina reported mtDNAs sizes range from 29,999 bp (Jaminaea angkoriensis; KC628747.1) to 90,496 bp (Sporosorium reilanum; FQ311469.1). Very few mitochondrial genomes are available for members of the Ustiloginales (U. maydis, DQ157700.1; Melanopsichium pennsylvanicum, HG529787; and S. reilianum) and sizes range from 5,814 bp to 90,496 bp. Despite the size variation, the gene content among these genomes are very similar and size variability is mostly due to spacers and the presence or absence of introns and intron encoded ORFs [5759].

The S. scitamineum mtDNA contains the 14 core protein coding genes found in all Basidiomycota mitochondrial genomes, encoding hydrophobic subunits of the electron transport chain, components of the ATPase synthase and the 40S ribosomal protein S3 [57]. RNA coding genes included the two ribosomal RNAs (rnl and rns), 22 tRNAs and the rnpB gene, which encodes the RNA component of the RNase P ribonucleoprotein involved in tRNA biogenesis.

Only group I introns were noted and these were located within the following genes: rnl, nad5, cob, nad1, atp9 and the intron-rich cox1 gene encompassing 11 ORF encoding introns. The 11 hypothetical genes (orphans that lack any counterparts in the NCBI database) identified by MFannot do not contain any introns. Mobile introns are characterized by their ability to “home” into cognate alleles that lack introns, therefore these elements tend to insert into conserved sequences which allows for more frequent lateral movement during crosses or during transient hyphal fusion among different species permiting cytoplasmic transfer [60]. The mobility is facilitated by the intron encoded proteins which are named homing endonucleases (HE) and in fungal mitochondrial genomes they can be assigned into two classes: LAGLIDADG and GIY YIG type HEases.

As stated earlier, several examples (atp9, cox1, nad1,nad5 and nad6) were noted in which C-terminus of a gene is duplicated and located downstream of the full length version. These types of duplications were observed for some genes in the mtDNA of Rhizoctonia solani[57]. It might be significant that we have noted that GIY-YIG type ORFs are located between the full length version of the gene and the partial duplicated version. These arrangements could be the result of a GIY-YIG HEG invading the 3’ terminus of a gene thereby displacing the C-terminus coding part of the resident gene. But as it has been seen previously, when freestanding homing endonuclease genes (HEGs) invade genes they can also mobilize a segment that essentially compensates/duplicates the displaced segment [6062]. As HEGs appear to be neutral elements and thus are not subject to selection, they quickly accumulate mutations [63] and thus only a few detectable fragments can now be recorded. In general based on these partial gene duplications associated with GIY-YIG types ORFs and other eroded GIY-YIG ORFs noted in the intergenic spacers it appears HEase activity contributes towards mtDNA size and organization.

Mating-type analysis

Mating genes are crucial factors for disease establishment since a successful mating reaction is needed to form the infective dikaryotic hyphae. Both processes, mating and pathogenicity, are regulated by two loci: a and b[64]. The a locus comprises genes encoding a pheromone-receptor system necessary for cell-cell recognition and hyphal fusion, whereas the b locus comprises two genes encoding subunits of a heterodimeric homeodomain transcription factor regulating the maintenance of the dikaryon. Although considered to be phylogenetically close based on ITS and LSU rDNA analysis [65, 66], the two genera of smut fungi (Ustilago/Sporisorium) show high rates of amino acid substitution per site of the mating-type proteins. The trans-specific polymorphisms in pheromone and receptor genes are supposedly preserved since the last common ancestor of the basidiomycetes and ascomycetes and their reciprocal specificity likely have co-evolved [67]. Although the pheromone and receptor proteins differs among Ustilaginaceae species and seems to be optimized for intraspecific compatibility, interspecific sex up to the stage of plasmogamy can be still observed in vitro, which could have an evolutionary impact on speciation by hybridization events [67].

The genomic context of mating-type genes has been published for several smut fungi [9, 64, 67, 68]. The organization of the b locus genes is conserved among species in opposition to what has been observed for the a locus, even considering compatible mating-types with the same genetic background. S. scitamineum and S. reilianum differ from U. maydis and U. hordei by the presence of a second pheromone gene (mfa) in that locus. However, this extra copy (mfa 1.3) in S. scitamineum lacks the characteristic sequence acting as a signal for post-translational processing. The event involves the isoprenylation and carboxymethylation in the cysteine residue to form a secretable lipopeptide pheromone [69]. In U. maydis, a remnant of a pheromone gene is described for the a2 allele that cannot produce a functional product [67, 70]. Although mfa1.3 gene of S. scitamineum has full coverage of RNAseq reads, additional experiments are required to determine how many different mating-type alleles are in the fungal population and whether both pheromones are functional.

In S. reilianum and U. maydis, the mating-type loci are not linked and segregates independently (tetrapolar system) [68]; in U. hordei and S. scitamineum the a and b loci are linked and segregate as one locus (bipolar system) [9, 71]. Here we present the first completely sequenced intergenic region between the two mating loci among the smut genotypes and the occurrence of transposable elements at this region. In U. hordei, that also has a bipolar mating system, the scaffold that holds the mating-type loci has large stretches of long terminal repeats (LTRs) and transposable elements (TEs) dispersed within an intervening region of about 500 kbp [71]. This region may have been responsible for the evolutionary process that resulted in the fusion of these mating-type loci and the divergence in these chromosomal segments that have led to a suppression of recombination between the alleles [64]. Transcriptome analysis of S. scitamineum during in vitro growth and development in planta showed that mating-type genes are expressed in both conditions. The two mating-types were grown individually in order to obtain the RNAseq data in vitro, which suggests that contact is either not needed to favor gene expression of mating-type genes, or that a very short period of interaction is enough to induce gene expression, since cells were mixed immediately prior centrifugation and RNA extraction. The expression of mating-type genes at the a and b loci are induced by pheromone in U. maydis, that leads to amplification of the pheromone signal during the mating and to increased expression of b genes prior to fusion [72]. A single HMG box transcription factor, PrfI (pheromone response factor I), plays an important role in mediating this interaction between the a and b pathways. Prf1 protein binds specifically to pheromone response elements (PREs), which occur in clusters in the promoter regions in the vicinity of all genes in both loci[72]. Although in different numbers and orientations, PREs have been found close to the mating-type genes in S. scitamineum and other fungi studied, excepting Malassezia species to which so far no sexual cycle has been observed [73]. The pfr1 gene is also expressed in all RNAseq experiments analyzed of S. scitamineum, suggesting that the same kind of regulation of a and b loci occurs in this species.

Plant host-pathogen interaction transcriptome analysis

The combination of genome sequencing and transcriptome profiling is a proven approach to bring insights into pathogen mechanisms to invade host tissues, strategies of acquiring nutrients, avoid plant defense and to provoke disease symptoms. All these events are accomplished by a series of signals inducing a transcriptional reprogramming of fungal metabolism resulting in survival and dissemination within the host.

Our comparative transcriptome profiling showed that approximately 13.5% of S. scitamineum genes were either detected as differentially expressed in planta at 5 or 200 DAI. These genes are related to several metabolic processes important to fungal survival and protection in host tissues. One of these processes involves the chitin modification, mechanism that prevents the generation of elicitor active chitin oligomers which reveals the presence of the pathogen in the plant, triggering defense responses. The deacetylation of surface-exposed chitin into chitosan acts as a molecular disguise strategy [7476]. Deacetylase is one of the most up-regulated gene at 5 DAI, indicating that S. scitamineum uses this strategy to dodge the plant defense in the early phases of fungal establishment. Que and collegues (2014) [77] determined the increase of chitinase gene expression in sugarcane transcriptome profiling of a resistance variety compared to susceptible plants.

The ability to pass through the plant cell wall by secreting a complex of extracellular cell wall degrading enzymes is evident in S. scitamineum. These enzymes are well known in filamentous plant pathogens and are necessary for entry into plant tissues [76, 7881]. However, the amount of these enzymes may vary according to the fungal lifestyle. Biotrophic fungi can have fewer enzymes than hemibiotrophic and necrotrophic fungi [82]. In our study, the number of CAZymes (279) detected in the S. scitamineum genome is similar to other biotrophic fungus [83]. We found a small set of 54 cell wall degrading enzymes, some of which have been identified as up-regulated genes in planta at 5 and 200 DAI, such as those involved in cellulose, pectin and hemicellulose degradation.

Surpassing the cell barrier, pathogens have to breakdown proteins, sugars, lipids and nucleic acids [84]. Nineteen enzymes associated with digestion of proteins were detected among the secreted proteins. The transcriptome revealed that genes related to proteases were also up-regulated in planta. The fungal proteases may inhibit the activity of plant pathogenesis-related protein [8587]. Another defense strategy potentially used by the fungus is the secretion of a cysteine-protease inhibitor to minimize the plant response, since the plant proteolytic machinery plays important roles in defense against pathogens [88].

Enzymes that target lipids, including lipases, triacyglycerol lipase and phospholipase were also found to have genes up-regulated at both time points analyzed. Lipases and phospholipases have been proposed to be essential not only for human pathogen virulence [89], but also for pathogens interacting with plants [90]. Eleven putative lipases were found in U. maydis potentially related to pathogenicity [91]. Lipase activities were associated with the fungal filamentous growth in vitro in the presence of lipids and also responsive to the known mating signaling pathways of the corn pathogen [91].

S. scitamineum seems to use another pathogen protective strategy to survive within sugarcane by the ability to detoxify the environment. Plants secrete various antimicrobial compounds into the apoplast to restrict pathogen growth. Examples are steroidal glycoalkaloids, such as saponin, and plant derived reactive oxygen species (ROS), which accumulate upon MAMP (microbe-associated molecular patterns) perception [92]. One of these detoxifying enzymes possibly used by S. scitamineum is related to pisatin demethylase, which was found up-regulated at 200 DAI. The pea pathogen Fusarium oxysporum f. sp. pisi is able to detoxify the phytoalexin pisatin, a substrate-inducible cytochrome P450, produced as a plant defense response [93]. Other genes related to cytochrome P450 and benzoate 4-monooxygenase are up-regulated at 200 DAI, which may indicate the need of detoxification in planta. These enzymes produce phenolic derivatives that are channeled to the b-ketoadipate pathway for aromatic compound degradation [94, 95]. Superoxide dismutase and catalases are also highly relevant to pathogenic fungal protection in planta[96, 97]. It has been reported that sugarcane resistant varieties produce an oxidative burst response upon smut infection [98]. These enzymes are involved in oxidative stress response against host superoxide radical (O2-) and hydrogen peroxide (H2O2), respectively. Their importance in the initial penetration is well documented [9, 99], but expression in the final stages (200 DAI) of smut sugarcane colonization in sugarcane may provide an additional protection against oxidative stress.

Of the differentially expressed genes at 5 DAI, nine have homologues in the PHI-base. Noteworthy are three up-regulated genes that code for sugar/glucose transporter and maltose permease, which in U. maydis mutants shows reduced virulence [100]. Among the differentially expressed genes at 200 DAI, 33 have homologues in the PHI-base. These genes are related to sugar, nicotinic acid, peptide transporters and the secreted proteins beta-glucosidase, lipase and aspartic protease. The sugar transporter coded by g1034_chr02_Ss is an ortholog of the U. maydis plasma membrane-localized sucrose transporter (Srt1), which is sucrose specific, and allows the direct utilization of sucrose without the production of extracellular monosaccharides known to elicit plant immune responses [100]. The presence of invertase is also indicative that sucrose breakdown is relevant for sporulation and whip development, leading support to the decrease of sucrose content in later stages of disease development [6]. The biotrophic interaction of S. scitamineum and sugarcane leads to increased invertase gene expression also by the plant, which is potentially to limit the sugar access to the pathogen, however the fungus present various sugar transporters that can increase the range of sugars and ways of intake this carbon source [101]. These mechanisms are probably among the ones that make this pathosystem very particular. Among other sugar transporter-encoding genes we found three quinate permease genes (g72_chr01_Ss; g1719_chr03_Ss and g2935_chr06_Ss) that were differentially expressed at 200 DAI. Quinate can serve as source of carbon to M. oryzae in early stages of rice infection [102]. M oryzae modulates expression of common genes related to the conversion between quinate and shikimate pathways by increasing quinate availability and decreasing products of the shikimate pathway, such as defensive phenylpropanoids. It is known that early sugarcane infection with S. scitamineum triggers expression of phenylpropanoid as a means of protection against fungal infection [77, 103]. In sugarcane it remains to be established whether quinate is available in the later stages of interaction, although these quinate assimilation genes up-regulated could be related to shunt of plant phenylpropanoid metabolism during smut whip emergence.

Laccase genes were also found to be differentially expressed in the fungus upon infection in sugarcane, revealing the potential of S. scitamineum for breaking down lignified tissues. Laccase is a polyphenol oxidase that catalyzes the reduction of O2 to H2O using a range of phenolic compounds as hydrogen donors, including lignin [104], that is the second most abundant constituent of the vascular plants cell wall, acting in cellulose protection towards hydrolytic microbial attack [105]. Sugarcane is known to respond to the presence of smut by modulating the expression of genes related to lignin pathways [98, 106, 107].

Our detailed annotation of the S. scitamineum genome revealed the presence of three genes encoding laccases. One of them, part of the described secretome, is encoded by the gene g1208_chr02_Ss, which is up-regulated in both 5 and 200 DAI, with values of Log2FoldChange of 6.56 and 7.59, respectively. Secreted laccases are related to lignin breakdown [108] and has great potential to be studied in numerous biotechnological applications, including those related to second generation of biofuels [97, 109, 110]. However, laccases can also be involved in various fungal physiological processes, for instance, the development of fruiting bodies [111] and spore pigmentation [112]. The transcriptome analysis results showed another laccase up-regulated at 200 DAI, which is not secreted (g4962_chr14_Ss, Log2FoldChange = 5.49). In this case this gene is possibly involved with pigment biosynthesis, since this stage of fungal development is characterized by intensive teliospore differentiation. Polyketide synthases encoding genes related to secondary metabolite production such as those involved in pigment biosynthesis were also found up-regulated at 200 DAI.

During the co-evolution of fungal plant pathogens and their hosts there has been a seesawing interplay between pathogen virulence and host resistance. Thus, to facilitate infection, plant pathogens secrete numerous effector proteins into the plant apoplast or cytosol [113]. Besides the strategies used to defend itself from plant immune system, S. scitamineum seems to have an arsenal of effectors that can potentially manipulate host metabolism [9, 114, 115]. S. scitamineum SSC39B secretome includes 70 proteins candidates for effectors, 51 annotated as either hypothetical or conserved hypothetical proteins. A similar number of candidates (43) was reported to occur in the 2014001 S. scitamineum strain [9]. Additionally, the authors used RT-qPCR analysis to reveal that 47% of these candidate genes were expressed in S. scitamineum in the early stages of the infection [9].

The transcriptomic data provided us with indications of S. scitamineum effectors that are transcriptionally active. Among them are the known effectors chorismate mutase, and salicylate hydroxylase [116], both involved in attenuating plant salicylic acid level reported in U. maydis[117], and Pep1 of U. maydis[118], an apoplastic inhibitor of host peroxidases [9, 119, 120]. As probable novel effectors used by S. scitamineum during sugarcane interaction we can highlight three genes (g2_chr01_Ss, g3890_chr10, and g1513_chr03_Ss) among the preferentially expressed in plant at 5 DAI, which encode to small secreted proteins of 236, 135 and 215 amino acids respectively. These genes have no identifiable conserved domains or any particular sequence feature. At 200 DAI the uncharacterized secreted proteins encoded by the highly expressed genes g3870_chr10_Ss, g488_chr01_Ss and g5684_chr17_Ss, are rich in glycine residues. In M. oryzae, members of the pwl gene family codify to small glycine-rich secreted proteins acting as Avrs conferring host specificity [121, 122].

A potential pathogenicity factor of the S. scitamineum is the most highly expressed genes of the secretome at 5 DAI (g3970_chr10_Ss). The encoded protein sequence presents several repeated motifs, such as “PQPQDGQ” residues represented seven times close to the N-terminal region and “PYGDKPNGDAENSDS” repeated eight times towards the C-terminal region. Its homologous in U. maydis, um03274, is expressed only in plant and not in axenic cultures [123] and in S. scitamineum the expression of this gene is low during in vitro growth. Sequences rich in proline and glutamine residues were found in the human fungal pathogen Candida albicans, where the 10-amino-acid long N-terminal repeat in the Hwp1p adhesin allows covalent cross-linking to host cells [124, 125]. All these genes of undetermined functions from S. scitamineum secretome, which are among the most expressed in plant, are good targets for experimental analyses to elucidate potential involvement in fungal growth and disease development.

In order to provide deeper analysis of S. scitamineum transcriptional profiles, we searched for the distribution of genes specifically expressed in planta, which allowed for the identification of 10 putative pathogenicity islands, a characteristic widespread in fungal pathogen genomes, which can harbor probable effectors. In the U. maydis, for instance were found 12 islands of genes encoding small secreted proteins with unknown function; most of them are co-regulated and induced in infected tissues, and deletion of individual islands can alter the pathogen virulence, leading in some cases to a complete lack of symptoms [7]. The evidence that some of them are only present in the S. scitamineum genome suggests its involvement in the sugarcane specificity, which is an important trait underlying the interaction of smuts with their hosts, but still poorly understood at the molecular level. Despite being phylogenetically close, the smut fungi infect different members of the Poaceae, and vary in their mode of plant colonization and symptom development. Searching for species-specific genes is a promising strategy to identify genes involved in host-specific adaptations [51, 126]. An important feature found in four of the predicted islands (chromosomes 2, 6, 10 and 11) is the presence of repetitive elements, that have been viewed as drivers of genome evolution by promoting genome rearrangements and possible gene regulation [127], and this can be related to the smut fungus adaptability towards sugarcane colonization.


The de novo complete genome assembly allowed us the determination of subtelomeric regions, mating-type loci, repetitive elements and the sequence and annotation of mtDNA of S. scitamineum. The mtDNA with 88 kb in length is within the size range expected for members of the Ustiloginales and the genome is rich in potential mobile introns with some evidence that duplications may have been generated by the activity of intron encoded homing endonucleases. Comparisons to other smut genome sequences revealed that chromosomal reorganizations related to the mating loci and details of the sequences linking both loci may be used in further evolutionary studies. The combination of transcriptomic data obtained in different phases of the fungal life cycle disclosed modulation of gene expression revealing that S. scitamineum uses common strategies to survive within sugarcane but also uncovered novelties that are associated to the specific interaction with sugarcane. The onset of infection is similar to those of other smut interactions. For instance, orthologues of U. maydis known virulence factors were found to be expressed in S. scitamineum during infection phase by means of attenuation of the salicylate mediated defense response. New candidate effectors have been identified and are organized in 10 genomic islands which are expressed only in planta, some of which S. scitamineum specific. Plant cell wall degrading enzymes, proteases and lipases are up-regulated potentially associated to the entry of the pathogen. Fungal defense responses were also a common strategy regarding the interaction with sugarcane. The fungus accumulates a series of transcripts encoding proteins to survive ROS and other toxins potentially produced by the plant. To avoid recognition by the host plant S. scitamineum probably uses chitin modifications. During the development of the whip and sporogenesis the presence of transcripts related to detoxification of plant metabolites as well as ROS are evident. The fungus metabolism shifts to the accumulation of sugar transporters and invertase transcripts, to use sucrose directly and/or sucrose monomers derivatives. Increased laccase activities both extracellular and non-secreted were detected. Laccases are regarded as potentially involved in lignin degradation and to pigment biosynthesis. This study suggests a new promising research aiming at the biotechnological use of S.scitamineum as well as provides valuable targets for experimental studies to confirm pathogen genes involved parasite/host interaction, with perspectives for applications in disease management and sugarcane breeding.

Database accession number

The complete genome sequence of the S. scitamineum SSC39B has been submitted at DDBJ/EMBL/GenBank under the BioProject number: PRJNA275631

The reads used in the RNAseq analysis has been submitted at DDBJ/EMBL/GenBank under the BioProject number: PRJNA275890

The complete genome sequence of the S. scitamineum BSES15 and BSES17 has been submitted the BioProject number: PRJEB5169

Supporting Information

S1 File. General analysis of S. scitamineum genome (Excel file format).

Chromosomes size, coordinates of telomeric regions and pattern found by Tandem Repeat Database (Table A). Circos of the alignment between the tree small contigs and the other chromosomes (a) and between other strains of S. scitamineum (Figure A). Pulse Field Gel Hibridizations (Figure B). Predicted tRNAs obtained by using tRNAscan-SE (Table B). Genes coordinates, best hit of each S. scitamineum protein against Uniref50, presence of signal peptide, transmembrane domain, GPI anchor site and RNAseq length coverage and BLASTp against proteins of S. reilianum Table C). Gene length distribution in S. scitamineum genome (Figure C). Annotation of subtelomeric genes (Table D). Repetitive elements detected using RECON for de novo identification, REPBASE and RepeatMasker (Table E). dbCAN domains on CAZymes (Table F). Alignments against the reference proteins from PHI-base (Table G).



S2 File. Blast2GO analysis (Excel file format).

Protein annotation of S. scitamineum genome using Blast2GO (Table A). Distribution of GO terms of predicted S. scitamineum proteins (Table B). List of best hit species of predicted protein sequences of S. scitamineum as defined by Blast2GO analysis (Table C).



S3 File. Chromosomes comparison of S. scitamineum SSC39 and S. reilianum (Zip with figures).

Figures produced using Circos software to illustrate chromosomes alignments between these two close related species.



S4 File. Mating-type analysis (PDF file format).

Percentage of identity of mating-type proteins and the average of predicted proteins from whole genome between S. scitamineum and others smut fungi (Table A). Unrooted consensus phylogenetic tree for the mating-type proteins from smut related species (Figure A). Genomic context of mating-type genes from smut related species (Figure B).



S5 File. Mitochondrial genome analysis (Excel file format).

Table with mitochondrial gene annotations and manual curation (Table A). Feature table of the mitochondria (Table B).



S6 File. OrthoMCL analysis (Excel file format).

Co-orthologs groups with their respective members (Table A). Four-way-Venn-diagram showing the distribution of orthologous protein clusters among smuts species (Figure A). Unique orthologs groups and theirs predicted functions (Table B). Singletons identifiers (proteins not assigned to any OrthoMCL cluster) (Table C). Single-copy genes in each group of orthologs (Table D). Putative effectors unique of S. scitamineum (differentially or exclusively) expressedin planta (Table E).



S7 File. Gene Ontology analysis of S. scitamineum secretome (PDF file format).

Graphs with GO terms enriched in the S. scitamineum secretome (Figure A).



S8 File. Transcriptome data analysis (Excel file format).

Number of reads mapped in transcriptome analysis obtained with CLC Genomics Workbench analysis (100% identity, 98% coverage) (Table A). Genes preferentially expressed in vitro, 5 DAI and 200 DAI. Expression values were defined by normalization using scaling approach and CDS size (Table B). Genes differentially expressed at 5 DAI in comparison with transcriptional profiles obtained in YM culture medium fungal axenic growth. Were considered differentially expressed genes those with FDR ≤ 0.01 in Baggerley’s test and Log2(Fold Change) ≤ -2 or ≥ 2 (Table C). Genes differentially expressed at 200 DAI as assumed in 5 DAI analysis (Table D). GO terms enrichment of differentially expressed genes using p-value ≤ 0.05 performed in Blast2GO software (Table E). Genes expressed exclusively in plant in comparison with genes expressed during axenic growth in YM medium (Table F).




The authors thank the sequencing facility Center of Functional Genomics and Center of Research Support in Electron Microscopy Applied to Agriculture (NAP/MEPA), University of São Paulo, Campus “Luiz de Queiroz”.

Author Contributions

Conceived and designed the experiments: CBMV JPK. Performed the experiments: ACP MCPK FRSN MCQ. Analyzed the data: LMT PDCS JB LPP GC KSA PJB JAF PMM GH AW JPK CBMV. Contributed reagents/materials/analysis tools: LLC SC. Wrote the paper: LMT PDCS JB LPP GC KSA GH JPK CBMV. Provided expertise and editing: JPK MLCV MCQ.


  1. 1. Verheye W. Growth and production of sugarcane. In: H VW, B BM, editors. Soils, plant growth and crop production. vol. 2. Encyclopedia of Life Support Systems; 2010.
  2. 2. Waclawovsky AJ, Sato PM, Lembke CG, Moore PH, Souza GM. Sugarcane for bioenergy production: an assessment of yield and regulation of sucrose content. Plant Biotechnology Journal. 2010;8(3):263–276. Available from: doi: 10.1111/j.1467-7652.2009.00491.x. pmid:20388126
  3. 3. Santos ASS. Doenças causadas por fungos e bactérias em cana-de-açúcar. IX Reunião itinerante de fitossanidade do instituto biológico. 2003;p. 11–17.
  4. 4. Comstock JC, Lentini RS. Sugarcane Smut Disease. In: Rice RW, editor. Florida Sugarcane Handbook. InTech; 2005. p. 107–128.
  5. 5. Alexander K, Ramakrishnan K. Infection of the bud, establishment in the host and production of whips in sugarcane smut (Ustilago scitaminea syd) of sugarcane. Proceedings. Congress of the International Society of Sugar Cane Technologists. 1980;.
  6. 6. Sundar AR, Barnabas EL, Malathi P, Viswanathan R. A Mini-Review on Smut Disease of Sugarcane Caused by Sporisorium scitamineum. In: Mworia JK, editor. Botany. InTech; 2012. p. 107–128.
  7. 7. Kämper J, Kahmann R, Bölker M, Ma LJ, Brefort T, Saville BJ, et al. Insights from the genome of the biotrophic fungal plant pathogen Ustilago maydis. Nature. 2006;444:97–101. doi: 10.1038/nature05248. pmid:17080091
  8. 8. Sharma R, Mishra B, Runge F, Thines M. Gene loss rather than gene gain is associated with a host jump from monocots to dicots in the Smut Fungus Melanopsichium pennsylvanicum. Genome Biology and Evolution. 2014;6(8):2034–2049. doi: 10.1093/gbe/evu148. pmid:25062916
  9. 9. Que Y, Xu L, Wu Q, Liu Y, Ling H, Liu Y, et al. Genome sequencing of Sporisorium scitamineum provides insights into the pathogenic mechanisms of sugarcane smut. BMC Genomics. 2014;15(1):996. Available from: doi: 10.1186/1471-2164-15-996. pmid:25406499
  10. 10. Schirawski J, Mannhaupt G, Münch K, Brefort T, Schipper K, Doehlemann G, et al. Pathogenicity Determinants in Smut Fungi Revealed by Genome Comparison. Science. 2010;330(6010):1546–1548. Available from: doi: 10.1126/science.1195330. pmid:21148393
  11. 11. Bölker M, Urban M, Kahmann R. The a mating type locus of U. maydis specifies cell signaling components. Cell. 1992;68(3):441–450. Available from: doi: 10.1016/0092-8674(92)90182-C. pmid:1310895
  12. 12. Eid J, Fehr A, Gray J, Luong K, Lyle J, Otto G, et al. Real-time DNA sequencing from single polymerase molecules. Science. 2009 Jan;323(5910):133–138. Available from: doi: 10.1126/science.1162986. pmid:19023044
  13. 13. Peterson DG, Tomkins JP, Frisch DA, Wing RA, Paterson AH. Construction of plant bacterial artificial chromosome (BAC) libraries: an illustrated guide. University of Georgia, Room 162: Journal of agricultural Genomics; 2000.
  14. 14. Chin CS, Alexander DH, Marks P, Klammer AA, Drake J, Heiner C, et al. Nonhybrid, finished microbial genome assemblies from long-read SMRT sequencing data. Nature Methods. 2013;10:563–569. doi: 10.1038/nmeth.2474. pmid:23644548
  15. 15. Greenfield P, Duesing K, Papanicolaou A, Bauer DC. Blue: correcting sequencing errors using consensus and context. Bioinformatics. 2014;30(19):2723–2732. Available from: doi: 10.1093/bioinformatics/btu368. pmid:24919879
  16. 16. Zerbino DR, Birney E. Velvet: Algorithms for de novo short read assembly using de Bruijn graphs. Genome Research. 2008;18(5):821–829. Available from: doi: 10.1101/gr.074492.107. pmid:18349386
  17. 17. McCluskey K. Identification and Characterization of Chromosome Length Polymorphisms Among Strains Representing Fourteen Races of Ustilago hordei. Molecular Plant-Microbe Interaction. 1990;3(6):366–37. doi: 10.1094/MPMI-3-366.
  18. 18. Levis C, Giraud T, Dutertre M, Fortini D, Brygoo Y. Telomeric DNA of Botrytis cinerea: a useful tool for strain identification. FEMS Microbiology Letters. 1997;157:267–272. doi: 10.1111/j.1574-6968.1997.tb12783.x. pmid:9435107
  19. 19. Bueno CRNC. Infecção por Sporisorium scitamineum em cana-de-açúcar: influência de variáveis ambientais e desenvolvimento de método para diagnose precoce. University of São Paulo; 2010. Available:
  20. 20. Stanke M, Morgenstern B. AUGUSTUS: a web server for gene prediction in eukaryotes that allows user-defined constraints. Nucleic Acids Research. 2005;33(suppl 2):W465–W467. Available from: doi: 10.1093/nar/gki458. pmid:15980513
  21. 21. Schattner P, Brooks AN, Lowe TM. The tRNAscan-SE, snoscan and snoGPS web servers for the detection of tRNAs and snoRNAs. Nucleic Acids Research. 2005;33(suppl 2):W686–W689. Available from: doi: 10.1093/nar/gki366. pmid:15980563
  22. 22. Bao Z, Eddy SR. Automated de novo Identification of Repeat Sequence Families in Sequenced Genomes. Genome Research. 2002;12:1269–1276. doi: 10.1101/gr.88502. pmid:12176934
  23. 23. Finn RD, Bateman A, Clements J, Coggill P, Eberhardt RY, Eddy SR, et al. Pfam: the protein families database. Nucleic Acids Research. 2014;42(D1):D222–D230. Available from: doi: 10.1093/nar/gkt1223. pmid:24288371
  24. 24. Smit AFA, Hubley R, Green P. RepeatMasker Open-3.0; 1996–2010. Available from:
  25. 25. Gelfand Y, Rodriguez A, Benson G. TRDB—The Tandem Repeats Database. Nucleic Acids Research. 2007;35(suppl 1):D80–D87. Available from: doi: 10.1093/nar/gkl1013. pmid:17175540
  26. 26. Conesa A, Gotz S. Blast2GO: A Comprehensive Suite for Functional Analysis in Plant Genomics. International Journal of Plant Genomics. 2008;2008. doi: 10.1155/2008/619832
  27. 27. Petersen TNN, Brunak S, von Heijne G, Nielsen H. SignalP 4.0: discriminating signal peptides from transmembrane regions. Nature Methods. 2011 Oct;8(10):785–786. Available from: doi: 10.1038/nmeth.1701. pmid:21959131
  28. 28. Krogh A, Larsson B, von Heijne G, Sonnhammer ELL. Predicting Transmembrane Protein Topology with a Hidden Markov Model: Application to Complete Genomes. Jornal of Molecular Biology. 2001;305:567–580. doi: 10.1006/jmbi.2000.4315.
  29. 29. Pierleoni A, Luigi Martelli P, Casadio R. PredGPI: a GPI-anchor predictor. BMC Bioinformatics. 2008;9(1). Available from: doi: 10.1186/1471-2105-9-392. pmid:18811934
  30. 30. Yin Y, Mao X, Yang J, Chen X, Mao F, Xu Y. dbCAN: a web resource for automated carbohydrate-active enzyme annotation. Nucleic Acids Research. 2012;40(W1):W445–W451. Available from: doi: 10.1093/nar/gks479. pmid:22645317
  31. 31. Winnenburg R, Urban M, Beacham A, Baldwin TK, Holland S, Lindeberg M, et al. PHI-base update: additions to the pathogen–host interaction database. Nucleic Acids Research. 2008;36(suppl 1):D572–D576. Available from: doi: 10.1093/nar/gkm858. pmid:17942425
  32. 32. Lang BF, Laforest MJ, Burger G. Mitochondrial introns: a critical view. Trends in Genetics. 2007;23(3):119–125. Available from: doi: 10.1016/j.tig.2007.01.006. pmid:17280737
  33. 33. Katoh K, Standley DM. MAFFT Multiple Sequence Alignment Software Version 7: Improvements in Performance and Usability. Molecular Biology and Evolution. 2013;30(4):772–780. Available from: doi: 10.1093/molbev/mst010. pmid:23329690
  34. 34. Nicholas KB, Nicholas HB, Deerfield DW. GeneDoc: analysis and visualization of genetic variation. EMBNEW NEWS. 1997;4:14.
  35. 35. Krzywinski MI, Schein JE, Birol I, Connors J, Gascoyne R, Horsman D, et al. Circos: An information aesthetic for comparative genomics. Genome Research. 2009 Jun;19(9):1639–1645. Available from: doi: 10.1101/gr.092759.109. pmid:19541911
  36. 36. Quinlan AR, Hall IM. BEDTools: a flexible suite of utilities for comparing genomic features. Bioinformatics. 2010;26(6):841–842. Available from: doi: 10.1093/bioinformatics/btq033. pmid:20110278
  37. 37. Mewes HW, Ruepp A, Theis F, Rattei T, Walter M, Frishman D, et al. MIPS: curated databases and comprehensive secondary data resources in 2010. Nucleic Acids Research. 2011;39(suppl 1):D220–D224. Available from: doi: 10.1093/nar/gkq1157. pmid:21109531
  38. 38. Li L, Stoeckert CJ, Roos DS. OrthoMCL: Identification of Ortholog Groups for Eukaryotic Genomes. Genome Research. 2003 Sep;13(9):2178–2189. Available from: doi: 10.1101/gr.1224503. pmid:12952885
  39. 39. Chen H, Boutros P. VennDiagram: a package for the generation of highly-customizable Venn and Euler diagrams in R. BMC Bioinformatics. 2011;12(1):35. Available from: doi: 10.1186/1471-2105-12-35. pmid:21269502
  40. 40. Notredame C, Higgins DG, Heringa J. T-Coffee: A novel method for fast and accurate multiple sequence alignment. Journal of Molecular Biology. 2000;302(1):205–17. doi: 10.1006/jmbi.2000.4042. pmid:10964570
  41. 41. Darriba D, Taboada GL, Doallo R, Posada D. ProtTest 3: fast selection of best-fit models of protein evolution. Bioinformatics. 2011 Apr;27(8):1164–1165. doi: 10.1093/bioinformatics/btr088. pmid:21335321
  42. 42. Guindon S, Dufayard JF, Lefort V, Anisimova M, Hordijk W, Gascuel O. New Algorithms and Methods to Estimate Maximum-Likelihood Phylogenies: Assessing the Performance of PhyML 3.0. Systematic Biology. 2010;59(3):307–321. Available from: doi: 10.1093/sysbio/syq010. pmid:20525638
  43. 43. Co O, Ngugi K, Nzioki H, Githiri SM. Evaluation of smut inoculation techniques in sugarcane seedlings. Sugar Tech. 2008;10(4):341–345. Available from: doi: 10.1007/s12355-008-0060-7.
  44. 44. Singh N, Somai BM, Pillay D. In vitro screening of sugarcane to evaluate smut susceptibility. Plant Cell, Tissue and Organ Culture. 2005;80(3):259–266. Available from: doi: 10.1007/s11240-004-1017-5.
  45. 45. Gasic K, Hernandez A, Korban S. RNA extraction from different apple tissues rich in polyphenols and polysaccharides for cDNA library construction. Plant Molecular Biology Reporter. 2004;22(4):437–438. Available from: doi: 10.1007/BF02772687.
  46. 46. de Oliveira JFNC. Caracterização fisiológica e perfil de expressão gênica de cultivares de cana-de-açúcar (Saccharum spp) contrastantes para o deficit hídrico. University of São Paulo; 2013. Available:
  47. 47. Langmead B, Salzberg SL. Fast gapped-read alignment with Bowtie 2. Nature Methods. 2012 Mar;9(4):357–359. Available from: doi: 10.1038/nmeth.1923. pmid:22388286
  48. 48. Bakkeren G, Kronstad JW. Linkage of mating-type loci distinguishes bipolar from tetrapolar mating in basidiomycetous smut fungi. Proceedings of the National Academy of Sciences. 1994;91(15):7085–7089. doi: 10.1073/pnas.91.15.7085.
  49. 49. Schirawski J, Mannhaupt G, Munch K, Brefort T, Schipper K, Doehlemann G, et al. Pathogenicity Determinants in Smut Fungi Revealed by Genome Comparison. Science. 2010 12;330:1546–1548. doi: 10.1126/science.1195330. pmid:21148393
  50. 50. Gold S, Duncan G, Barrett K, Kronstad J. cAMP regulates morphogenesis in the fungal pathogen Ustilago maydis. Genes and Development. 1994;8(23):2805–2816. Available from: doi: 10.1101/gad.8.23.2805. pmid:7995519
  51. 51. Wollenberg T, Schirawski J. Comparative Genomics of Plant Fungal Pathogens: The Ustilago-Sporisorium Paradigm. PLoS Pathogen. 2014 07;10(7):e1004218. Available from: doi: 10.1371/journal.ppat.1004218.
  52. 52. Barry JD. The relative significance of mechanisms of antigenic variation in African trypanosomes. Parasitology Today. 1997;13(6):212–218. Available from: doi: 10.1016/S0169-4758(97)01039-9. pmid:15275073
  53. 53. Verstrepen KJ, Reynolds TB, Fink GR. Origins of variation in the fungal cell surface. Nature Reviews Microbiology. 2004;2:533–540. doi: 10.1038/nrmicro927. pmid:15197389
  54. 54. Farman M. Telomeres in the rice blast fungus Magnaporthe oryzae: the world of the end as we know it. FEMS Microbiology Letters. 2007;273(2):125–32. doi: 10.1111/j.1574-6968.2007.00812.x. pmid:17610516
  55. 55. Rehmeyer C, Li W, Kusaba M, Kim YS, Brown D, Staben C, et al. Organization of chromosome ends in the rice blast fungus, Magnaporthe oryzae. Nucleic Acids Research. 2006;34(17):4685–4701. Available from: doi: 10.1093/nar/gkl588. pmid:16963777
  56. 56. Wu C, Kim YS, Smith KM, Li W, Hood HM, Staben C, et al. Characterization of Chromosome Ends in the Filamentous Fungus Neurospora crassa. Genetics. 2009;181(3):1129–1145. Available from: doi: 10.1534/genetics.107.084392. pmid:19104079
  57. 57. Losada L, Pakala SB, Fedorova ND, Joardar V, Shabalina SA, Hostetler J, et al. Mobile elements and mitochondrial genome expansion in the soil fungus and potato pathogen Rhizoctonia solani AG-3. FEMS Microbiology Letters. 2014;352(2):165–173. doi: 10.1111/1574-6968.12387. pmid:24461055
  58. 58. Hegedusova E, Brejova B, Tomaska L, Sipiczki M, Nosek J. Mitochondrial genome of the basidiomycetous yeast Jaminaea angkorensis. Current Genetics. 2014;60(1):49–59. Available from: doi: 10.1007/s00294-013-0410-1. pmid:24071901
  59. 59. Salavirta H, Oksanen I, Kuuskeri J, Mäkelä M, Laine P, Paulin L, et al. Mitochondrial Genome of Phlebia radiata Is the Second Largest (156 kbp) among Fungi and Features Signs of Genome Flexibility and Recent Recombination Events. PLoS ONE. 2014 05;9(5):e97141. Available from: doi: 10.1371/journal.pone.0097141. pmid:24824642
  60. 60. Hausner G. Introns, Mobile Elements, and Plasmids. In: Bullerwell CE, editor. Organelle Genetics. Springer Berlin Heidelberg; 2012. p. 329–357. Available from:
  61. 61. Paquin B, Laforest MJ, Lang BF. Interspecific transfer of mitochondrial genes in fungi and creation of a homologous hybrid gene. Proceedings of the National Academy of Sciences. 1994;91(25):11807–11810. Available from: doi: 10.1073/pnas.91.25.11807.
  62. 62. Sethuraman J, Majer A, Iranpour M, Hausner G. Molecular Evolution of the mtDNA Encoded rps3 Gene Among Filamentous Ascomycetes Fungi with an Emphasis on the Ophiostomatoid Fungi. Journal of Molecular Evolution. 2009;69(4):372–385. Available from: doi: 10.1007/s00239-009-9291-9. pmid:19826748
  63. 63. Goddard MR, Burt A. Recurrent invasion and extinction of a selfish gene. Proceedings of the National Academy of Sciences. 1999;96(24):13880–13885. Available from: doi: 10.1073/pnas.96.24.13880.
  64. 64. Bakkeren G, Kämper J, Schirawski J. Sex in smut fungi: Structure, function and evolution of mating-type complexes. Fungal Genetics and Biology. 2008;45(0):S15–S21. Available from: doi: 10.1016/j.fgb.2008.04.005. pmid:18501648
  65. 65. Stoll M, Piepenbring M, Begerow D, Oberwinkler F. Molecular phylogeny of Ustilago and Sporisorium species (Basidiomycota, Ustilaginales) based on internal transcribed spacer (ITS) sequences. Canadian Journal of Botany. 2003;81(9):976–984. Available from: doi: 10.1139/b03-094.
  66. 66. Stoll M, Begerow D, Oberwinkler F. Molecular phylogeny of Ustilago, Sporisorium, and related taxa based on combined analyses of rDNA sequences. Mycological Research. 2005;109(3):342–56. doi: 10.1017/S0953756204002229. pmid:15912952
  67. 67. Kellner R, Vollmeister E, Feldbrügge M, Begerow D. Interspecific Sex in Grass Smuts and the Genetic Diversity of Their Pheromone-Receptor System. PLoS Genetics. 2011 12;7(12):e1002436. Available from: doi: 10.1371/journal.pgen.1002436. pmid:22242007
  68. 68. Schirawski J, Heinze B, Wagenknecht M, Kahmann R. Mating Type Loci of Sporisorium reilianum: Novel Pattern with Three a and Multiple b Specificities. Eukaryotic Cell. 2005;4(8):1317–1327. Available from: doi: 10.1128/EC.4.8.1317-1327.2005. pmid:16087737
  69. 69. Caldwell GA, Naider F, Becker JM. Fungal lipopeptide mating pheromones: a model system for the study of protein prenylation. Microbiological Reviews. 1995;59(3):406–22. Available from: pmid:7565412
  70. 70. Urban M, Kahmann R, Bölker M. The biallelica mating type locus of Ustilago maydis: remnants of an additional pheromone gene indicate evolution from a multiallelic ancestor. Molecular and General Genetics MGG. 1996;250(4):414–420. Available from: doi: 10.1007/BF02174029. pmid:8602158
  71. 71. Laurie JD, Ali S, Linning R, Mannhaupt G, Wong P, Guldener U, et al. Genome Comparison of Barley and Maize Smut Fungi Reveals Targeted Loss of RNA Silencing Components and Species-Specific Presence of Transposable Elements. The Plant Cell. 2012 05;24:1733–1745. doi: 10.1105/tpc.112.097261. pmid:22623492
  72. 72. Hartmann HA, Kahmann R, Bölker M. The pheromone response factor coordinates filamentous growth and pathogenicity in Ustilago maydis. EMBO Journal. 1996;15(7):1632–1641. pmid:8612587
  73. 73. Saunders CW, Scheynius A, Heitman J. Malassezia Fungi Are Specialized to Live on Skin and Associated with Dandruff, Eczema, and Other Skin Diseases. PLoS Pathogens. 2012 06;8(6):e1002701. Available from: doi: 10.1371/journal.ppat.1002701. pmid:22737067
  74. 74. Nampally M, Moerschbacher BM, Kolkenbrock S. Fusion of a Novel Genetically Engineered Chitosan Affinity Protein and Green Fluorescent Protein for Specific Detection of Chitosan In Vitro and In Situ. Applied and Environmental Microbiology. 2012;78(9):3114–3119. Available from: doi: 10.1128/AEM.07506-11. pmid:22367086
  75. 75. Leroch M, Kleber A, Silva E, Coenen T, Koppenhöfer D, Shmaryahu A, et al. Transcriptome Profiling of Botrytis cinerea Conidial Germination Reveals Upregulation of Infection-Related Genes during the Prepenetration Stage. Eukaryotic Cell. 2013;12(4):614–626. Available from: doi: 10.1128/EC.00295-12. pmid:23417562
  76. 76. Meinhardt L, Costa GG, Thomazella D, Teixeira PJ, Carazzolle M, Schuster S, et al. Genome and secretome analysis of the hemibiotrophic fungal pathogen, Moniliophthora roreri, which causes frosty pod rot disease of cacao: mechanisms of the biotrophic and necrotrophic phases. BMC Genomics. 2014;15(1):164. Available from: doi: 10.1186/1471-2164-15-164. pmid:24571091
  77. 77. Que Y, Su Y, Guo J, Wu Q, Xu L. A Global View of Transcriptome Dynamics during Sporisorium scitamineum Challenge in Sugarcane by RNA-seq. PLoS ONE. 2014 08;9(8):e106476. Available from: doi: 10.1371/journal.pone.0106476. pmid:25171065
  78. 78. Raffaele S, Win J, Cano L, Kamoun S. Analyses of genome architecture and gene expression reveal novel candidate virulence factors in the secretome of Phytophthora infestans. BMC Genomics. 2010;11(1):637. Available from: doi: 10.1186/1471-2164-11-637. pmid:21080964
  79. 79. Mueller O, Kahmann R, Aguilar G, Trejo-Aguilar B, Wu A, de Vries RP. The secretome of the maize pathogen Ustilago maydis. Fungal Genetics and Biology. 2008;45, Supplement 1(0):S63–S70. Thematic Issue: Ustilago maydis. Available from: doi: 10.1016/j.fgb.2008.03.012. pmid:18456523
  80. 80. Kawahara Y, Oono Y, Kanamori H, Matsumoto T, Itoh T, Minami E. Simultaneous RNA-Seq Analysis of a Mixed Transcriptome of Rice and Blast Fungus Interaction. PLoS ONE. 2012 11;7(11):e49423. Available from: doi: 10.1371/journal.pone.0049423. pmid:23139845
  81. 81. jGarnica DP, Upadhyaya NM, Dodds PN, Rathjen JP. Strategies for Wheat Stripe Rust Pathogenicity Identified by Transcriptome Sequencing. PLoS ONE. 2013 06;8(6):e67150. Available from: doi: 10.1371/journal.pone.0067150.
  82. 82. O’Connell RJ, Thon MR, Hacquard S, Amyotte SG, Kleemann J, Torres MF, et al. Lifestyle transitions in plant pathogenic Colletotrichum fungi deciphered by genome and transcriptome analyses. Nature Genetics. 2012;44(1):1060–1065. doi: 10.1038/ng.2372. pmid:22885923
  83. 83. Zhao Z, Liu H, Wang C, Xu JR. Comparative analysis of fungal genomes reveals different plant cell wall degrading capacity in fungi. BMC Genomics. 2013;14(1):274. Available from: doi: 10.1186/1471-2164-14-274. pmid:23617724
  84. 84. Brown NA, Antoniw J, Hammond-Kosack KE. The Predicted Secretome of the Plant Pathogenic Fungus Fusarium graminearum: A Refined Comparative Analysis. PLoS ONE. 2012 04;7(4):e33731. Available from: doi: 10.1371/journal.pone.0033731. pmid:22493673
  85. 85. Tian M, Huitema E, da Cunha L, Torto-Alalibo T, Kamoun S. A Kazal-like Extracellular Serine Protease Inhibitor from Phytophthora infestans Targets the Tomato Pathogenesis-related Protease P69B. Journal of Biological Chemistry. 2004;279(25):26370–26377. Available from: doi: 10.1074/jbc.M400941200. pmid:15096512
  86. 86. Fernandes I, Alves A, Correia A, Devreese B, Esteves AC. Secretome analysis identifies potential virulence factors of Diplodia corticola, a fungal pathogen involved in cork oak (Quercus suber) decline. Fungal Biology. 2014;118(5–6):516–523. Available from: doi: 10.1016/j.funbio.2014.04.006. pmid:24863480
  87. 87. Espino JJ, Gutiérrez-Sánchez G, Brito N, Shah P, Orlando R, González C. The Botrytis cinerea early secretome. Proteomics. 2010;10(16):3020–3034. Available from: doi: 10.1002/pmic.201000037. pmid:20564262
  88. 88. Tian M, Win J, Song J, van der Hoorn R, van der Knaap E, Kamoun S. A Phytophthora infestans Cystatin-Like Protein Targets a Novel Tomato Papain-Like Apoplastic Protease. Plant Physiology. 2007;143(1):364–377. doi: 10.1104/pp.106.090050. pmid:17085509
  89. 89. Cafarchia C, Otranto D. Association between Phospholipase Production by Malassezia pachydermatis and Skin Lesions. Journal of Clinical Microbiology. 2004;42(10):4868–4869. doi: 10.1128/JCM.42.10.4868-4869.2004. pmid:15472366
  90. 90. Voigt CA, Schäfer W, Salomon S. A secreted lipase of Fusarium graminearum is a virulence factor required for infection of cereals. The Plant Journal. 2005;42(3):364–375. Available from: doi: 10.1111/j.1365-313X.2005.02377.x. pmid:15842622
  91. 91. Klose J, De Sá MM, Kronstad JW. Lipid-induced filamentous growth in Ustilago maydis. Molecular Microbiology. 2004;52(3):823–835. Available from: doi: 10.1111/j.1365-2958.2004.04019.x. pmid:15101987
  92. 92. Ökmen B, Doehlemann G. Inside plant: biotrophic strategies to modulate host immunity and metabolism. Current Opinion in Plant Biology. 2014;20(0):19–25. SI: Biotic interactions. Available from: pmid:24780462
  93. 93. Coleman JJ, Wasmann CC, Usami T, White GJ, Temporini ED, McCluskey K, et al. Characterization of the Gene Encoding Pisatin Demethylase (FoPDA1) in Fusarium oxysporum. APS Journals. 2011;24(12):1482–1491. doi: 10.1094/mpmi-05-11-0119
  94. 94. Harwood CS, Parales RE. The ß-ketoadipate pathway and the biology of self-identity. Annual Review of Microbiology. 1996;50(1):553–590. Available from: doi: 10.1146/annurev.micro.50.1.553. pmid:8905091
  95. 95. Podobnik B, Stojan J, Lah L, Krasevec N, Seliskar M, Rizner TL, et al. CYP53A15 of Cochliobolus lunatus, a Target for Natural Antifungal Compounds. Journal of Medicinal Chemistry. 2008;51(12):3480–3486. Available from: doi: 10.1021/jm800030e. pmid:18505250
  96. 96. Roetzer A, Gabaldón T, Schüller C. From Saccharomyces cerevisiae to Candida glabrata in a few easy steps: important adaptations for an opportunistic pathogen. FEMS Microbiology Letters. 2011;314(1):1–9. doi: 10.1111/j.1574-6968.2010.02102.x. pmid:20846362
  97. 97. Mayer AM, Staples RC. Laccase: new functions for an old enzyme. Phytochemistry. 2002;60(6):551–565. Available from: doi: 10.1016/S0031-9422(02)00171-1. pmid:12126701
  98. 98. LaO M, Arencibia A, Carmona E, Acevedo R, Rodríguez E, León O, et al. Differential expression analysis by cDNA-AFLP of Saccharum spp. after inoculation with the host pathogen Sporisorium scitamineum. Plant Cell Reports. 2008;27(6):1103–1111. Available from: doi: 10.1007/s00299-008-0524-y. pmid:18379790
  99. 99. Weßling R, Schmidt SM, Micali CO, Knaust F, Reinhardt R, Neumann U, et al. Transcriptome analysis of enriched Golovinomyces orontii haustoria by deep 454 pyrosequencing. Fungal Genetics and Biology. 2012;49(6):470–482. Available from: doi: 10.1016/j.fgb.2012.04.001. pmid:22521876
  100. 100. Wahl R, Wippel K, Goos S, Kämper J, Sauer N. A Novel High-Affinity Sucrose Transporter Is Required for Virulence of the Plant Pathogen Ustilago maydis. PLoS Biology. 2010 02;8(2):e1000303. Available from: doi: 10.1371/journal.pbio.1000303. pmid:20161717
  101. 101. Doidy J, Grace E, Kühn C, Simon-Plas F, Casieri L, Wipf D. Sugar transporters in plants and in their interactions with fungi. Trends in Plant Science. 2012;17(7):413–422. doi: 10.1016/j.tplants.2012.03.009. pmid:22513109
  102. 102. Soanes DM, Chakrabarti A, Paszkiewicz KH, Dawe AL, Talbot NJ. Genome-wide Transcriptional Profiling of Appressorium Development by the Rice Blast Fungus Magnaporthe oryzae. PLoS Pathogens. 2012 02;8(2):e1002514. Available from: doi: 10.1371/journal.ppat.1002514. pmid:22346750
  103. 103. Thokoane L, Rutherford R. cDNA-AFLP differential display of sugarcane (Saccharum spp., hybrids) genes induced by challenge with the fungal pathogen Ustilago scitaminea (sugarcane smut). In: Proceedings of the South African Sugar Technologists’ Association. vol. 75; 2001. p. 104–107.
  104. 104. Thurston CF. The structure and function of fungal laccases. Microbiology. 1994;140(1):19–26. Available from: doi: 10.1099/13500872-140-1-19.
  105. 105. Ruiz-Dueñas FJ, Martínez AT. Microbial degradation of lignin: how a bulky recalcitrant polymer is efficiently recycled in nature and how we can take advantage of this. Microbial Biotechnology. 2009;2(2):164–177. Available from: doi: 10.1111/j.1751-7915.2008.00078.x. pmid:21261911
  106. 106. You-Xiong Q, Jian-Wei L, Xian-Xian S, Li-Ping X, Ru-Kai C. Differential Gene Expression in Sugarcane in Response to Challenge by Fungal Pathogen Ustilago scitaminea Revealed by cDNA-AFLP. Journal of Biomedicine and Biotechnology. 2011;2011:10. doi: 10.1155/2011/160934.
  107. 107. Santiago R, Quintana J, Rodríguez S, Díaz EM, Legaz ME, Vicente C. An elicitor isolated from smut teliospores Sporisorium scitamineum enhances lignin deposition on the cell wall of both sclerenchyma and xylem in sugarcane leaves. Pakistan Journal of Botany. 2010;42(4):2867–2881.
  108. 108. Baldrian P. Fungal laccases—occurrence and properties. FEMS Microbiology Reviews. 2006;30(2):215–242. Available from: doi: 10.1111/j.1574-4976.2005.00010.x. pmid:16472305
  109. 109. Singh Arora D, Kumar Sharma R. Ligninolytic Fungal Laccases and Their Biotechnological Applications. Applied Biochemistry and Biotechnology. 2010;160(6):1760–1788. Available from: doi: 10.1007/s12010-009-8676-y. pmid:19513857
  110. 110. Madhavi V, Lele SS. Laccase: properties and applications. BioResources. 2009;4(4):1694–1717. Available from: 1694_Madhavi_Lele_Laccase_Props_Applications_Rev.
  111. 111. Leatham GF, Stahmann MA. Studies on the Laccase of Lentinus edodes: Specificity, Localization and Association with the Development of Fruiting Bodies. Journal of General Microbiology. 1981;125(1):147–157. Available from:
  112. 112. Clutterbuck AJ. Absence of Laccase from Yellow-spored Mutants of Aspergillus nidulans. Journal of General Microbiology. 1972;70(3):423–435. Available from: doi: 10.1099/00221287-70-3-423. pmid:4624671
  113. 113. Koeck M, Hardham AR, Dodds PN. The role of effectors of biotrophic and hemibiotrophic fungi in infection. Cellular Microbiology. 2011;13(12):1849–1857. Available from: doi: 10.1111/j.1462-5822.2011.01665.x. pmid:21848815
  114. 114. Stergiopoulos I, de Wit PJGM. Fungal Effector Proteins. Annual Review of Phytopathology. 2009;47(1):233–263. doi: 10.1146/annurev.phyto.112408.132637. pmid:19400631
  115. 115. Soyer JL, El Ghalid M, Glaser N, Ollivier B, Linglin J, Grandaubert J, et al. Epigenetic Control of Effector Gene Expression in the Plant Pathogenic Fungus Leptosphaeria maculans. PLoS Genetics. 2014 03;10(3):e1004227. Available from: doi: 10.1371/journal.pgen.1004227. pmid:24603691
  116. 116. Rabe F, Ajami-Rashidi Z, Doehlemann G, Kahmann R, Djamei A. Degradation of the plant defence hormone salicylic acid by the biotrophic fungus Ustilago maydis. Molecular Microbiology. 2013;89(1):179–188. Available from: doi: 10.1111/mmi.12269. pmid:23692401
  117. 117. Djamei A, Schipper K, Rabe F, Ghosh A, Vincon V, Kahnt J, et al. Metabolic priming by a secreted fungal effector. Nature. 2011;478(7369):395–398. doi: 10.1038/nature10454. pmid:21976020
  118. 118. Doehlemann G, van der Linde K, Aßmann D, Schwammbach D, Hof A, Mohanty A, et al. Pep1, a Secreted Effector Protein of Ustilago maydis, Is Required for Successful Invasion of Plant Cells. PLoS Pathogens. 2009 02;5(2):e1000290. Available from: doi: 10.1371/journal.ppat.1000290. pmid:19197359
  119. 119. Hemetsberger C, Herrberger C, Zechmann B, Hillmer M, Doehlemann G. The Ustilago maydis Effector Pep1 Suppresses Plant Immunity by Inhibition of Host Peroxidase Activity. PLoS Pathogens. 2012 05;8(5):e1002684. Available from: doi: 10.1371/journal.ppat.1002684. pmid:22589719
  120. 120. Hemetsberger C, Mueller AN, Matei A, Herrberger C, Hensel G, Kumlehn J, et al. The fungal core effector Pep1 is conserved across smuts of dicots and monocots. The New Phytologist. 2015;206(3):1116–1126. doi: 10.1111/nph.13304. pmid:25628012
  121. 121. Kang S, Sweigard J, Valent B. The PWL host specificity gene family in the blast fungus Magnaporthe grisea. Molecular Plant-Microbe Interaction. 1995;8(6):939–48. doi: 10.1094/MPMI-8-0939.
  122. 122. Sweigard JA, Carroll AM, Kang S, Farrall L, Chumley FG, Valent B. Identification, cloning, and characterization of PWL2, a gene for host species specificity in the rice blast fungus. Plant Cell. 1995;7(8):1221–1233. doi: 10.1105/tpc.7.8.1221. pmid:7549480
  123. 123. Donaldson ME, Meng S, Gagarinova A, Babu M, Lambie SC, Swiadek AA, et al. Investigating the Ustilago maydis/Zea mays pathosystem: Transcriptional responses and novel functional aspects of a fungal calcineurin regulatory B subunit. Fungal Genetics and Biology. 2013;58–59(0):91–04. Available from: doi: 10.1016/j.fgb.2013.08.006. pmid:23973481
  124. 124. Levdansky E, Sharon H, Osherov N. Coding fungal tandem repeats as generators of fungal diversity. Fungal Biology Reviews. 2008;22(3–4):85–96. Available from: doi: 10.1016/j.fbr.2008.08.001.
  125. 125. Padovan ACB, Chaves GM, Colombo AL, Briones MRS. A novel allele of HWP1, isolated from a clinical strain of Candida albicans with defective hyphal growth and biofilm formation, has deletions of Gln/Pro and Ser/Thr repeats involved in cellular adhesion. Medical Mycology. 2009;47(8):824–835. Available from: doi: 10.3109/13693780802669574. pmid:19184714
  126. 126. Feldbrügge M, Kellner R, Schipper K. The biotechnological use and potential of plant pathogenic smut fungi. Applied Microbiology and Biotechnology. 2013;97(8):3253–3265. Available from: doi: 10.1007/s00253-013-4777-1. pmid:23455565
  127. 127. Schmidt SM, Panstruga R. Pathogenomics of fungal plant parasites: what have we learnt about pathogenesis? Current Opinion in Plant Biology. 2011;14(4):392–399. Biotic interactions. Available from: doi: 10.1016/j.pbi.2011.03.006. pmid:21458359