article: Black Sigatoka or black leaf streak disease, caused by the Dothideomycete fungus Pseudocercospora fijiensis (previously: Mycosphaerella fijiensis), is the most significant foliar disease of banana worldwide. Due to the lack of effective host resistance, management of this disease requires frequent fungicide applications, which greatly increase the economic and environmental costs to produce banana. Weekly applications in most banana plantations lead to rapid evolution of fungicide-resistant strains within populations causing disease-control failures throughout the world. Given its extremely high economic importance, two strains of P. fijiensis were sequenced and assembled with the aid of a new genetic linkage map. The 74-Mb genome of P. fijiensis is massively expanded by LTR retrotransposons, making it the largest genome within the Dothideomycetes. Melting-curve assays suggest that the genomes of two closely related members of the Sigatoka disease complex, P. eumusae and P. musae, also are expanded. Electrophoretic karyotyping and analyses of molecular markers in P. fijiensis field populations showed chromosome-length polymorphisms and high genetic diversity. Genetic differentiation was also detected using neutral markers, suggesting strong selection with limited gene flow at the studied geographic scale. Frequencies of fungicide resistance in fungicide-treated plantations were much higher than those in untreated wild-type P. fijiensis populations. A homologue of the Cladosporium fulvum Avr4 effector, PfAvr4, was identified in the P. fijiensis genome. Infiltration of the purified PfAVR4 protein into leaves of the resistant banana variety Calcutta 4 resulted in a hypersensitive-like response. This result suggests that Calcutta 4 could carry an unknown resistance gene recognizing PfAVR4. Besides adding to our understanding of the overall Dothideomycete genome structures, the P. fijiensis genome will aid in developing fungicide treatment schedules to combat this pathogen and in improving the efficiency of banana breeding programs.
  Black Sigatoka or black leaf streak disease (BLSD), caused by the Dothideomycete fungus Pseudocercospora fijiensis (previously: Mycosphaerella fijiensis) [1], is a major threat to global banana production [2]. The disease is part of the Sigatoka complex, which involves two other closely related pathogens in addition to P. fijiensis: P. musae (previously: M. musicola) causal agent of yellow Sigatoka disease; and P. eumusae (previously: M. eumusae) causal agent of the eumusae leaf spot disease. Among the three species, P. fijiensis is the most aggressive and predominant member of the Sigatoka disease complex worldwide. These pathogens occur exclusively on the foliage of bananas and plantains, with continuous sexual and asexual reproduction in nature [1,3–5]. BLSD was first reported in the Sigatoka Valley of the Fiji islands during the 1960s and has since spread to nearly all banana-producing areas worldwide. It can only be managed by intensive fungicide applications, requiring weekly interventions throughout the year in most production areas. Black Sigatoka inflicts huge costs on global banana production, surpassing US $500 million per year [6]. Expenses for fungicide treatments usually represent more than 35% of total production costs [7,8]. Infection with P. fijiensis also results in crop losses and massive indirect costs by inducing early ripening of the fruit, making it unsuitable for sale with concomitant effects on the export trade and the retail sector. Export banana cultivars are sterile, triploid plants that can only be propagated clonally and are grown in huge monocultures of genetically identical individuals. The international banana trade is based solely on a few closely related clones of the Cavendish type, all of which are highly susceptible [6]; disease management, therefore, relies primarily on fungicide applications with enormous environmental impacts [9]. Moreover, the selection pressure on P. fijiensis populations continuously reduces the efficacy of fungicides resulting in control failures and unmanageable levels of disease [2,7]. Therefore, there is an urgent need for scientific discoveries that will lead to the development of better methods for protecting banana crops, both for export fruit production and for small holders around the world who rely on bananas as a staple food [2]. Taxonomically, Pseudocercospora belongs to the order Capnodiales in the class Dothideomycetes, previously known as the Loculoascomycetes [10], which is the largest and most diverse class of ascomycete fungi comprising over 20,000 species. Dothideomycete fungi include endophytes and epiphytes of plants, but also saprobes degrading cellulose and other complex carbohydrates of dead plants, and plant pathogens [11]. The latter cause a range of diseases in various key food, fiber and fuel crops, including Zymoseptoria tritici (septoria tritici blotch of wheat) [12], Venturia inaequalis (apple scab) [13], and Leptosphaeria maculans (blackleg of Brassica crops) [14]. Therefore, genome sequences of several Dothideomycetes have been published [15–22] or are in the process of being completed (http: //genome. jgi. doe. gov/dothideomycetes/dothideomycetes. info. html). The genome sequence of Z. tritici is the reference for all other Dothideomycetes as it is the only one that has been completely finished [21]. The poor experimental amenability of P. fijiensis has significantly hampered progress in understanding its basic biology [9] and the development of research tools. For instance, infection assays are cumbersome due to the need for very specific environmental conditions with respect to temperature, light and relative humidity, and the slow development of the disease that may take up to 50 days until symptoms are expressed [23,24]. Therefore, basic information on pathogenesis is not available and almost nothing is known about the genetic basis of disease resistance in banana germplasm [25,26]. Hence, new tools and research methods are needed to better understand the disease and ensure continued production of the world’s number one fruit, which is a staple food for millions of people in many developing countries. A previous comparative analysis of 18 Dothideomycetes genomes [19] included that of P. fijiensis isolate CIRAD86 for a global analysis of genome organization and evolution. However, P. fijiensis was not the primary focus of that analysis and few specifics were discussed. Here we focus on the genome sequence of P. fijiensis isolate CIRAD86, describe the sequence of a second isolate, CIRAD139, and analyze in detail the species’ genome structure, content and function with a goal of delivering new data that could give clues for global disease management of this devastating banana pathogen.
  The genomes of the P. fijiensis isolates were sequenced using either Sanger technology (CIRAD86) or Illumina for resequencing (CIRAD139a). The final assembly size of ~74 Mb consisted of 56 scaffolds with the largest at 11. 8 Mb and an N50 of 50 Kb. Inclusion of a newly made genetic map facilitated assembly of the physical genome (S1 Table). Genetic map construction involved 376 loci that segregated in the progeny of the mapping population, among which 322 (233 DArT, 86 SSR, 3 minisatellite) markers were mapped into 19 linkage groups (Fig 1). The number of loci per linkage group varied from 2 to 35 with an average of 17 and linkage groups 1,2, 8 and 9 contained the largest numbers of markers with 35,29,31 and 26, respectively. Map distances between consecutive markers varied from 0 to 20. 4 cM with the largest gaps between markers on linkage groups 14 and 17, of 6. 1 and 20. 4 cM, respectively (Fig 1). After filtering for EST support, completeness and similarity to other species, 13,107 genes were structurally and functionally annotated. The average gene length in the version 2 assembly is 1,833 nt with 3. 62 exons per gene; 88%, are complete with start and stop codon, 74% have similarity support, and 49% have Pfam domains (S2 Table). Most of the gene models (96%) are located in 12 scaffolds, numbers 1–10,12 and 19. Gene density in these 12 scaffolds varies from 151 to 229 per Mb, but gene density for the remaining scaffolds larger than 0. 5 Mb drops to only 2 to 94 genes per Mb (S1 Table). More detailed information on the assembly, annotation and EST support data can be found in S1 Text.
  The genome of P. fijiensis is the largest among all of the Dothideomycetes sequenced to date; it is 3. 4 times larger than that of the Dothideomycete with the smallest genome, Baudoinia compniacensis, 1. 85 times larger than that of Z. tritici and 1. 2 times larger than that of C. fulvum, which is related to P. fijiensis and also has an expanded genome [18]. Almost all of the increased size is due to the proliferation of LTR retrotransposons, as described here and in another publication [34]. The thermal denaturation results indicate that G+C content heterogeneity is not limited to P. fijiensis, but also occurs in its close relatives within a monophyletic clade of banana pathogens. Based upon the observed similarity of DNA composition between these three banana pathogens, we predict that the genomes of both P. eumusae and P. musae also are expanded and that all three pathogens that often co-occur in nature seem to have a recent common ancestor [4]. The only other member of the Capnodiales known to have a similarly expanded genome is the biotrophic tomato pathogen, C. fulvum [18]. Based on the positions of the species with expanded genomes on the phylogenetic tree (Fig 2), there appear to have been at least two independent expansions in genome size within the Capnodiales, one involving P. fijiensis (and most likely related banana pathogens) and another for C. fulvum. Lack of similarity between the transposable elements in the genomes of P. fijiensis and C. fulvum supports the hypothesis of independent expansions in each genome. The terminal repeats of LTR retrotransposons are identical at the time of insertion and this provides a means to estimate the relative ages of transposable element insertions. This phenomenon has been very useful for estimating transposon insertion times in plants [35,36] but is less useful for fungi where RIP greatly increases the rate of mutations in repetitive sequences. Using this approach in the basidiomycete Laccaria bicolor, three periods of transposon insertion were identified, ranging in age from 0 to 59 million years ago (Mya) [37]. Whether RIP occurs in L. bicolor is not known, but its genome does not contain the genes known to be required for RIP in other fungi [38] and no evidence for RIP was found among transposons in the genomes of other members of the Agaricomycotina [39] so it seems unlikely. Therefore, this approach for estimating the ages of transposon insertions is most likely valid for L. bicolor. A similar analysis of LTRs of transposons in the genome of Z. tritici yielded hypothetical insertion ages ranging from 0 to 5. 7 Mya, with the strong caveat that the times were probably vastly overestimated due to RIP [40]. Even with the bias introduced by RIP, the estimated ages of transposon insertions in the genome of Z. tritici were an order of magnitude younger than those in L. bicolor, indicating that they must have occurred relatively recently. A more accurate approach to estimating transposon age in the presence of RIP would be to exclude the RIP-susceptible sites from analysis [41]. Using this approach, transposon insertions in L. maculans and closely related species in the Pleosporales, another large order of the Dothideomycetes, mostly were relatively recent, within the past four million years [41,42]. For P. fijiensis, the results of a similar analysis clearly suggest a recent, rapid burst of LTR retrotransposon insertions. The young age and high proliferation rate of around 46% of the LTR retrotransposons suggest that P. fijiensis has a highly dynamic genome. Such a recent, high level of activity of retrotransposons can have evolutionary as well as regulatory implications for gene expression that can be better understood using genomic comparisons with other closely related species. Large genome expansions due to amplifications of repetitive elements have been observed in other plant-pathogenic fungi. The published genome sequences and analyses of the powdery mildew fungi Blumeria graminis f. sp. hordei, Erysiphe pisi and Golovinomyces orontii show a marked genome expansion with a massive proliferation of non–LTR retrotransposons and a corresponding decrease in gene content [43]. The missing genes in these obligate biotrophs include enzymes for primary and secondary metabolism, carbohydrate-active enzymes, transporters, and secreted proteins such as effectors. The genome of P. fijiensis also shows a moderate decrease in certain gene families associated with pathogenicity such as PKSs and CWDEs when compared to necrotrophic Dothideomycetes such as P. nodorum or P. tritici-repentis [16]. In a similar way, the hemibiotrophs Z. tritici [17], S. populorum and S. populicola [19,22] also show a marked decrease in CWDEs [19], although not to the extent seen in the powdery mildews. This reduction in Z. tritici is thought to have evolved as a mechanism to evade detection by host defenses during stealth pathogenesis [17]. This hypothesis also could fit the lifestyle of P. fijiensis since it has an even longer biotrophic phase of up to 28 days before necrotic symptoms start to appear so may have a greater need for stealth [23]. However, the association is not perfect because the reduction in CWDEs in Z. tritici is greater, particularly for β glucosidases. Thus, within Ascomycetes there seems to be a correlation between pathogenic lifestyle (biotrophic vs. hemibiotrophic vs. necrotrophic) and diversity of certain gene families such as PKSs and CWDEs. This correlation does not hold up when extended to other fungal groups. For example, rust fungi are obligate biotrophs with greatly expanded genomes due to either the proliferation of LTR retrotransposons similar to P. fijiensis for the wheat stem rust pathogen Puccinia graminis, or to class II DNA transposons for the poplar rust fungus Melampsora larici-populina [44]. However, in both rusts gene numbers were greatly expanded including those for SSPs that may be involved in interactions with their hosts [44]. Thus, evolution of a biotrophic lifestyle has involved very different changes in the genetic architecture of fungal genomes, from the vast reductions in gene content noted in the powdery mildew fungi to huge expansions for the rusts. Hemibiotrophs such as P. fijiensis fall in the middle of the continuum. The one constant is the increased genome size due to transposons, which seems much more common in biotrophic and hemobiotrophic pathogens compared to necrotrophs or saprotrophs. The mechanisms of these transposon expansions remain mostly unknown. The two main unanswered questions revolve around the source of the invading elements and the mechanism by which they proliferate. The most obvious source would be their host plants, but so far there appears to be little evidence that transposons are being transferred from hosts to their pathogens. Biotrophic fungi should be the most suited for acquiring transposons because they are restricted to growing in a very limited ecological niche and have specialized feeding structures to retrieve nutrients from their hosts. For P. fijiensis, a search of the banana genome sequence revealed that transposable elements account for almost half of the Musa sequence with LTR retrotransposons representing the largest part [45,46], so the transposons might have come from banana. If not from the hosts, then they most likely have been acquired from other fungi or pests that are associated with the hosts. Horizontal transfer of genes has been shown in other fungi such as P. nodorum [47] and Fusarium oxysporum f. sp. lycopersici [48] and it could occur for transposons. Horizontal transfer has the potential to broaden host range and pathogenicity of fungal pathogens or even create a new pathogen from a non/pathogenic strain [47,48]. Solving the mystery about the origin of invading transposons is important for understanding the dynamics of fungal genome expansions, and the causal agents of the Sigatoka complex on bananas represent a good model to address such a question. A little more is known about the mechanisms for transposon expansion after they have been acquired. Almost all fungi are capable of Repeat-Induced Point (RIP) mutation, a mechanism for identifying and mutating repetitive sequences [39,41,49–52]. For transposons, the mutations caused by RIP prevent successful translation of the genes coding for transposon movement proteins so they become inactive and can no longer replicate. This provides a very effective defense against transposon expansions in most fungi. In the powdery mildew fungi, the genetic machinery required for RIP was missing [43] and this likely allows unrestricted multiplication of transposons. For the rust fungi, no mechanisms for genome expansion were proposed or tested [44]. For P. fijiensis, rid, the only gene known to be required for RIP, is present and the reading frame appears to be intact. Repetitive sequences in the genome of P. fijiensis show high frequencies of the C to T transitions that are characteristic of RIP, so this phenomenon seems to be active. Because RIP is only active during meiosis, a possible explanation for fungi with extensive asexual phases could be that transposon expansion occurs during asexual reproduction and then is slowed by RIP during rare sexual reproduction. If transposons have expanded enough and RIP is not completely efficient, some intact copies of transposons could remain after meiosis to continue expanding during the next extended asexual phase. This explanation is possible in P. fijiensis; although it has been classically considered to be primarily reproducing by sexual mating, more recent studies suggest that asexual reproduction also plays an important role during epidemics [53,54]. Transposon expansion most likely occurs episodically when RIP or other mechanisms are relaxed, but when and how these episodes occur is currently unknown. In Z. tritici, a different type of genome expansion occurred through the acquisition of a large set of dispensable chromosomes, referred to as the dispensome [17]. The Z. tritici dispensome contains at least eight chromosomes with no known function that appear to have been acquired by horizontal transfer from an unknown donor more than 10,000 years ago [17,55]. Such a large number of dispensable chromosomes with no known effects on fitness so far is unique among fungi. Many potential dispensable chromosomes were identified among the genomic scaffolds of P. fijiensis based on the characteristics of known dispensable chromosomes in Z. tritici. However, dispensability still has not been proven for P. fijiensis. None of the P. fijiensis linkage groups were missing in progeny isolates, one of the hallmarks of dispensable chromosomes in Z. tritici [56]. However, this is not surprising because none of the linkage groups corresponded to any of the putative dispensable scaffolds. If P. fijiensis does contain a dispensome, it is different from that in Z. tritici because there was almost no similarity between the dispensable chromosomes of Z. tritici and any of the scaffolds of P. fijiensis, or vice versa. This raises the intriguing possibility of separate events leading to horizontal transfer of large numbers of chromosomes between species in the Capnodiales and other fungi. Electrophoretic karyotyping of P. fijiensis showed a remarkable level of variability among isolates, even those coming from the same population. This chromosome length and number polymorphism was also described previously in P. fijiensis [57] and in other fungi [58–60]. The mechanisms of such variation include chromosome rearrangements during meiotic recombination and the presence of dispensable chromosomes [61]. From a different perspective, it has been shown that chromosomal reshuffling can drive evolution of virulence in asexual plant-pathogenic fungi [62]; thus both sexual and asexual life cycles could be a source of chromosomal variation. This could constitute a mechanism of adaptation to environmental changes such as selective pressure from chemical fungicides. Field isolates karyotyped in this work were collected in Costa Rica in an area with a high level of fungicide applications. Overall, P. fijiensis chromosomes are larger than those from other Ascomycetes, including its completely sequenced relative Z. tritici [17]. Remarkably, P. fijiensis contains a scaffold larger than 10 Mb, which is at the limit of PFGE resolution. Chromosomes of this size have been observed in other fungi [63–65] but they are not common. Medium-sized chromosomes were not found, similar to previous records for Mexican isolates [57]. Interestingly, the seven smallest main scaffolds, including the smallest calculated core chromosome (0. 61 Mb) and six of the putative dispensable chromosomes did not appear in PFGE, as CIRAD86 did not show a chromosome smaller than 0. 8 Mb. The total number of chromosomes separated by PFGE is at least 11, and probably up to 15 when possible co-migrating bands are counted separately, in addition to the five unresolved largest scaffolds. The availability of a genome sequence enables the identification of genes that might be involved in pathogenicity, including those encoding putative effector proteins. Fungal effectors are proteins that aid pathogenicity, usually by subduing host defenses. However, these same proteins affecting pathogenicity also can be recognized by the host resistance proteins, triggering a defense response and making them advantageous or disadvantageous to the pathogen depending on the host genotype. Bioinformatic analysis of the P. fijiensis genome identified many putative effectors, including one that appears to be a homolog of the Avr4 effector in the related Dothideomycete, C. fulvum [31]. The P. fijiensis putative Avr4 homolog PfAvr4 was on scaffold 4 adjacent to repeats of 617 and 2765 bp and a 6-kb AT-rich block with a GC content of 39. 3%, similar to known effectors in other fungi, which often are in AT-rich regions [41,55]. Other genes in this region of the P. fijiensis genome were different from those in Z. tritici and C. fulvum, indicating little synteny among genes around the PfAvr4 homologs in related species. Previous research showed that PfAvr4 is a functional homolog of the CfAvr4 virulence factor in C. fulvum, and that, despite a low amino acid identity of only 42%, it could be recognized by the Cf4 resistance protein to stimulate an HR in tomato [32]. However, whether PfAvr4 could be recognized by banana cultivars had not been tested until now. The response of the banana varieties to the PfAVR4 protein strongly suggests that it acts as an avirulence factor that is recognized by a resistant banana accession where it elicits an HR-like necrosis. Most probably this protein has a function similar to that of its homolog in C. fulvum where it is an effector that facilitates disease in susceptible cultivars of tomato and can be recognized by the Cf4 receptor in a resistant tomato cultivar to elicit the HR [31]. To our knowledge, this is the first fungal effector known to induce a cultivar-specific, HR-like necrosis in banana, suggesting that M. acuminata ssp. burmannicoides var. Calcutta 4 most likely has a functional R gene that recognizes PfAVR4, and which appears to be a functional homologue of Cf4 in tomato. Additional experiments are needed to thoroughly test the hypothesis that var. Calcutta 4 contains an HR-inducing resistance gene effective against P. fijiensis. These could include analysis of progeny from controlled crosses between var. Calcutta 4 and a susceptible banana to test for co-segregation of necrosis induced by PfAVR4 and resistance to P. fijiensis, or deletion of PfAvr4 to test whether the resulting mutant becomes virulent to var. Calcutta 4. However, these experiments would be challenging due to experimental limitations in this pathosystem: crosses in banana frequently suffer from segregation distortions due to the occurrence of translocations and functional analyses in P. fijiensis are not routine. The banana var. Calcutta 4 has been a source of resistance against fungi, bacteria and nematodes in Musa breeding programs [66,67]. It is one of the most resistant accessions in field evaluations against P. fijiensis populations from around the world, with the exception of some isolates from the Pacific islands and Papua New Guinea [68], which are considered as the center of origin of the disease [5]. In addition, var. Calcutta 4 has shown resistance to crude extracts from P. fijiensis [69,70]. The identification of PfAvr4 as a likely avirulence factor in var. Calcutta 4 provides a major advance for banana breeding programs aiming at increasing the level of resistance against black Sigatoka. Purified effector proteins can be used to identify other resistance genes and to facilitate rapid selection of resistant progeny from segregating populations. The current selection process in resistance breeding is inadequate as it exclusively relies on field evaluations, and is slow because black Sigatoka has a latent period of a month or longer and the banana cycling time, depending on the species, is approximately 10–15 months. Similar experiences slowed down resistance breeding in wheat to Z. tritici until the elucidation of its mating system showed single-gene inheritance of pathogenicity factors that facilitated more precise isolate characterizations and subsequent R-gene discovery [17,71–74]. Other potential genes involved in pathogenicity are discussed in supporting S2Text. QoIs represent a class of fungicides that initially showed impressive efficacy against many plant pathogens [75]. However, resistance evolved rapidly and soon rendered the compound of little use in multiple pathosystems [76]. Diagnostic primers for the mitochondrial cytb gene showed that P. fijiensis is no exception, as the three commercial and frequently sprayed plantations were nearly or completely fixed for resistance. This is a remarkable shift compared to analyses performed during 2000–2003 when only part of the population was resistant [77]. Interestingly, the San Carlos population, which was not sprayed with fungicides, is still entirely sensitive. This result suggests limited genetic exchange between these populations that are separated by about 100 km. Nevertheless, even limited gene flow could have an impact on untreated areas. Because the selection pressure exerted by strobilurins is quite strong, the resistance frequency rapidly increases from a low number of resistant individuals to widespread resistance soon after fungicides are used, particularly since these compounds do not prevent sexual reproduction [78]. This prompted us to process the P. fijiensis genome sequence with a bioinformatics pipeline to develop VNTR markers for rapid PCR-based population analyses to compare with a priori neutral markers. Nonetheless, some genetic differentiation occurs between the populations as already described earlier in Costa Rica using microsatellite markers [79]. However, because populations have not yet reached mutation–drift equilibrium, gene flow could not be estimated using classical genetic models based on genetic differentiation [79]. Fortunately, new indirect [80] and direct [53] methods have been recently used to provide estimates of dispersal in P. fijiensis that could be integrated in theoretical and spatially explicit models to predict spatial patterns of fungicide resistance evolution under different management strategies. The availability of the CIRAD86 genome sequence and the resequence data of CIRAD139 for P. fijiensis will blunt its continued threat to global production by facilitating the development of resistant cultivars in banana breeding programs. The rapid development of fungicide resistance and extreme variability of the P. fijiensis genome among isolates coupled with a high level of sexual reproduction make this pathogen highly adaptable to changing environmental conditions. Diversifying and increasing the level of host resistance in banana may be the only way to slow the devastation caused by this fungus in the future.
  Pseudocercospora fijiensis isolate CIRAD86 (mat1-1 mating type, originating from Cameroon in 1988) was chosen for sequencing because it is the epitype for the species, has been the subject of intensive analyses previously and is one parent of an existing mapping population [81]. CIRAD139a (mat1-2, originating from Colombia in 1990) was used for resequencing. CIRAD86 is maintained at the CBS-KNAW Fungal Biodiversity Centre (CBS 120258). Mycelia for DNA extraction were grown in 1L Erlenmeyer flasks containing 200 mL of PDB (potato dextrose broth; Becton Dickinson, NJ, USA) shaken at 120 rpm at 28°C. Mycelial mats produced during culture were filtered to remove the broth and lyophilized. Samples containing 50 mg of lyophilized mycelia were placed in 2 mL tubes and ground with a Hybaid Ribolyser (model n° FP120HY-230) for 10 s at 2500 rpm with a tungsten-carbide bead. DNA was extracted from the ground mycelia using the Wizard Magnetic DNA Purification system (Promega, Netherlands) for food according to instructions provided by the manufacturer. Whole-genome shotgun sequencing and assembly of the P. fijiensis genome were done using Sanger sequencing of three different-sized libraries (3- and 8-kb plasmids, and 40-kb fosmids) as described previously for Z. tritici [17] and other species [82]. The initial version 1 assembly was improved by aligning the physical scaffolds to a genetic linkage map constructed using Joinmap V 4. 0 software [83] to analyze the segregation data for 322 markers that were scored on 135 progeny of the cross between isolates CIRAD86 and CIRAD 139A [81]. For each molecular locus, a goodness-of-fit analysis was performed to test for deviation from the expected 1: 1 segregation ratio at a 1% significance level. Linkage groups were established using a minimum LOD score of 9. 0 and final mapping was achieved by combining two or more linkage groups belonging to the same chromosome. The order of the markers on each chromosome was determined using a minimum LOD score of 1. 0, recombination threshold of 0. 4, jump of 5. 0, ripple value of 1 (default) and Haldane’s mapping function as parameters. In cases of uncertainty, some markers were removed and the order was recalculated until a more stable order was achieved. Three methods were used to identify the P. fijiensis repetitive sequences. Repeated sequences in the genome were identified de novo using RECON [84] and the k-mer based method RepeatScout [85]. A custom set of repeats and the RepBase Update library of 234 fungal repeats [86] were then used to mask the P. fijiensis genome using RepeatMasker (http: //www. repeatmasker. org/) [87]. Repeat families with 10 or more elements identified by RepeatScout were annotated and classified into categories based on the presence of protein domains (BLAST [88]). Structural features including Long Terminal Repeats (LTRs) and Terminal Inverted Repeats (TIRs) were verified using the EMBOSS [89] software package. Sequences with no known proteins or structural features were grouped into the unclassified category. Identification and annotation of protein-coding genes were performed using the JGI Annotation Pipeline, which takes multiple inputs (scaffolds, ESTs, and known genes), runs several analytical tools for gene prediction and annotation, and deposits the results in the JGI fungal genome portal MycoCosm (http: //jgi. doe. gov/fungi) [90] for further analysis and manual curation. Several gene-prediction programs falling into three general categories were used to annotate the repeat-masked assembly as described by Ohm et al. [19]. The resulting set of putative genes was then filtered for the best models based on EST and similarity support to produce a non-redundant representative set. This representative set of filtered gene models from the automated annotation pipeline was subject to further analysis and manual curation as described by Goodwin et al. for Z. tritici [17] and by Ohm et al. [82] for more recently sequenced species. Measures of model quality included proportions of the models complete with start and stop codons (88% of models), those that were consistent with ESTs (30% of models) and those supported by similarity with proteins from the NCBI NR database (74% of models) as summarized in S8 Table. Functional annotations for all predicted gene models were made using SignalP [91], TMHMM [92], InterProScan [93], and BLASTp [88] against the nr, SwissProt (http: //www. expasy. org/sprot/), KEGG [94] and KOG [95] databases as described by Ohm et al. [19]. Multigene families were predicted with the Markov clustering algorithm (MCL) [96] to cluster the proteins using BLASTp alignment scores between proteins as a similarity metric. Functional annotations are summarized in S9 Table. Manual curation of the automated annotations was performed using the web-based interactive editing tools of the JGI Genome Portal to assess predicted gene structures, assign gene functions, and report supporting evidence. Gene models predicted by the JGI annotation pipeline were also analyzed using the program Blast2GO [97] with an E-value of < 10−6. Blast2GO assigns GO terms based on the BLAST definitions. Comparisons between groups of genes for enrichment of GO terms were done by using Fisher’s exact test implemented in the Blast2GO program. Potential secreted proteins were identified with a python script made to run all gene models through SignalP 3. 0 [98] and subsequently filtered for proteins that had no transmembrane domains, no signal anchor motifs, were fewer than 300 amino acids in length and had at least four cysteine residues. The gene models that fulfilled these criteria were considered as potential SSPs. For re-sequencing of isolate CIRAD 139A, a paired-end library was made using the standard Illumina library prep protocol with NEB reagents. Average insert size of the library was 272 base pairs. Sequencing was done on an Illumina GAIIx in one lane of a 54-cycle paired-end run using 36-cycle version 5 SBS Kits. The flow cell was built using a version 4 paired-end cluster generation kit. Eventually, 37 million reads were obtained for a total yield of 4 gigabases. Paired reads were aligned to the P. fijiensis v2 Assembly reference scaffolds using GSNAP (2010-03-09 release), allowing up to 3 mismatches or 1 indel and with end trimming enabled. Uniquely aligned reads were then used to call variant sites using the Alpheus pipeline, requiring that a variant have support from at least two reads with an average quality of bases of at least phred 10 and at least 80% of the reads covering the site calling that variant. Nonsynonymous SNP differences were assessed against the coding regions in the P. fijiensis v2 Frozen Gene Catalog 20100402. To survey the non-synonymous SNPs in the annotated protein set of CIRAD86, a simple analysis of functional bias in variant proteins was conducted using a ranking comparison approach. All genes were ranked based on their non-synonymous SNP count (normalized for coding sequence length) and two selected gene sets were compared with the whole-genome set. The two sets used for comparison were the 1500 most-variant proteins (Set V) and the 1500 least-variant proteins (Set C), taken from the list of genes ranked by non-synonymous SNP count. The annotation files for the P. fijiensis v2 Frozen Gene Catalog 20100402 were used as the source of GO terms for the genes. The ranked frequency of occurrence of GO terms in the gene annotations for the whole genome was compared with those for Sets C and V. For each repetitive element family, a subset of elements with lengths within 50% of the longest element was aligned using clustalX [99]. These alignments were submitted to RIPCAL [28] to determine the dinucleotide bias observed in repetitive elements. RIPCAL estimates' RIP dominance' for each dinucleotide containing a cytosine. It is the ratio of a given dinucleotide (e. g. , CA) to the sum of the other three dinucleotides (CG/CC/CT). To test for isochores in the P. fijiensis genome, a contiguous stretch of sequence with an arbitrarily chosen average GC content of less than 45% was categorized as an AT block. Custom python scripts were used to calculate the percent GC across the genome, to generate AT blocks and to calculate the average percent GC across the AT blocks and those fewer than 500 bp apart were merged into blocks of at least 1 kb in length, which were retained and analyzed for their composition and distribution of repetitive sequences and genes. To estimate and compare the amount of RIP between the AT-rich blocks and the rest of the genome, a custom python script was written using a 500-bp sliding window with a step size of 100 bp. The amount of RIP was calculated as an index (CpA+TpG) / (ApC+GpT) and estimated separately for each of the AT-rich versus AT-poor regions in the genome. The RIP index measures the depletion of the RIP targets CpA and TpG; thus, lower values of (CpA+TpG) / (ApC+GpT) are indicative of a higher degree of RIP [28]. To estimate the ages of transposon insertions, LTR retrotransposons were identified and annotated using the LTRharvest [100] and LTRdigest [101] modules in GenomeTools [102]. LTR sequences from these elements were aligned using ClustalW [99] and manually curated to estimate the numbers of mutations that had accumulated over time. All transition mutations were ignored in this analysis to remove the bias caused by RIP. Age of the LTR retrotransposons was calculated using the average rate of 1. 09 × 10−9 substitutions/site/year as proposed for fungal sequences [103]. To test whether the transposons in the P. fijiensis genome were unique, a comparison was made to transposable elements (TEs) in the genome of C. fulvum, the only other sequenced fungus in the Capnodiales with an expanded genome. RepeatMasker [85] was used to mask the C. fulvum genome using the repeat database from the P. fijiensis genome. The resulting file was parsed using the 80: 80 rule of Wicker et al. [27], i. e. , 80% identity across 80% length to identify repeats in common between the two genomes. Another run was done at a 70: 70 cutoff to allow for greater divergence generated by RIP. The CIRAD86 strain was grown in three culture media for production of cDNA libraries: yeast-glucose broth as a rich medium (10 g of yeast extract and 30 g of glucose per liter); minimal nutrient medium (1 g of KH2PO4,1 g of KNO3,0. 5 g of MgSO4·7H2O, 0. 5 g of KCl, 0. 2 g of glucose, 0. 2 g of sucrose per liter); and minimal nutrient medium without a nitrogen source (as above but without KNO3). Fungal mycelia were grown in each medium at 25°C for 10 days with a photoperiod of 12 hours using cool-white fluorescent light on a rotary shaker at 100 rpm. Mycelia derived from all three in vitro conditions were harvested by filtration and ground in liquid nitrogen. The RNA was isolated by the trizol method with the RNeasy kit (Qiagen, Netherlands) with 2 g of starting material. RNA quality and quantity were assessed by spectrophotometer and by gel electrophoresis according to standard procedures. For cDNA library construction, first-strand cDNA synthesis was done using polyA+ RNA, reverse transcriptase (SuperScriptII (Invitrogen, CA, USA) ) and an oligo dT-NotI primer (5' GACTAGTTCTAGATCGCGAGCGGCCGCCCT15VN 3' ). Second-strand synthesis was done by E. coli DNA ligase, polymerase I and RNaseH before end repair with T4 DNA polymerase. The SalI adaptor (5' TCGACCCACGCGTCCG and 5' CGGACGCGTGGG) was ligated to the cDNA and digested with NotI before selecting the size range by gel electrophoresis. Sizes were 0. 6–2 kb and 2–10 kb. The cDNA of P. fijiensis grown in yeast-glucose medium was divided into libraries CBBT and CBHU (0. 6-2kb) and CBHT (2-10kb). The cDNA from culture on minimal nutrient medium was divided into libraries CBBW and CBHX (0. 6-2kb) and CBBU and CBHW (2-10kb), and for the libraries of culture on minimal nutrient medium without nitrogen source, cDNA was divided into libraries CBBX and CBHY (0. 6-2kb). The size-selected inserts were cloned into the pCMVSPORT6 vector (Invitrogen) and digested with SalI and NotI. Ligated vectors were transformed into ElectroMAX T1 DH10B cells (Invitrogen). Sequence reads from cDNA libraries were trimmed of vector, linker, adapter, poly-A/T, and other artifact sequences with the Cross-match software. Internally developed software at the JGI-DOE identified short patterns and low-quality regions (Q15). The longest high-quality region of each read was counted as an EST. Clustering of ESTs was performed based on pairwise alignments generated using the Malign software, a modified version of the Smith–Waterman algorithm [104], which was developed at the JGI for use in whole-genome shotgun assembly. ESTs sharing an alignment of at least 98% identity with 150-bp overlap were assigned to the same cluster. For each cluster of EST sequences, a consensus sequence was generated by running the Phrap software [105,106]. Plantlets of M. acuminata ssp. burmannicoides var. Calcutta 4 (recognized as a resistant standard for BLSD) were multiplied and rooted in vitro, whereas Cavendish “Grand Naine” tissue culture plants were hardened for three to four weeks in a greenhouse environment. Subsequently, all plantlets were grown for three months (small plants), and some plants of var. Calcutta 4 and “Grand Naine” were grown for eight months (large plants) in a controlled-environment greenhouse compartment at 25°C with a relative humidity of >80% and 16 hours of light per day. Plants of tomato (Lycopersicum esculentum) cv. Moneymaker (MM), which has no known Cf resistance genes (Cf0), or an isogenic line previously transformed with the Cf4 resistance gene were grown under greenhouse conditions as described by Stergiopoulos et al. [32] during 3–4 weeks. The mature protein from the P. fijiensis putative effector gene PfAvr4 was produced heterologously by culturing Pichia pastoris isolate GS115 in a fermentor as described previously [107]. Following production in the fermentor, the protein was further purified from excess liquid medium and smaller proteins by filtration through a 3-kDa membrane (Amicon Ultra-15 Centrifugal filter unit, Millipore, USA). Infiltration of the complete fermentor product or purified PfAVR4 protein into banana and tomato leaves was done by injection with a 1-mL syringe with no needle. Infiltrations on banana leaves were done at the original concentration and a six-fold higher concentration. For tomato, all infiltration materials were diluted fifty or seventy-five times prior to infiltration. Samples of the fermentor medium and water were infiltrated separately as negative controls for all plants. At each infiltration point, the observed water soaking of tissue was marked with a permanent marker. Observations were recorded with an Olympus C-8080 digital camera at four and 10 days post infiltration (dpi) on banana leaves, and at 6 dpi for tomato plants. Protein preparation and controls were infiltrated in at least two banana leaves from each genotype in small and large sizes, with at least 3 repetitions per leaf. Infiltrations in tomato plants were performed in at least 4 leaves with one repetition. The thermal denaturation method of Marmur and Doty [108], performed basically as described by Smith et al. [109], was used to estimate G+C contents of DNA from P. fijiensis isolate CIRAD86 (CBS120258) plus that from the closely related banana pathogens P. musae (isolate UQ430; CBS121371) and P. eumusae (isolate CBS122457) as well as the previously sequenced Z. tritici isolate IPO323 (CBS115943) [17]. Genomic DNA was isolated from cultures grown in PD broth at 25°C on a rotary shaker (150 rpm) following the procedure described by Raeder and Broda [110] and was dissolved in 0. 1X SSC. Melting curves were obtained on a Perkin-Elmer λ25 spectrophotometer equipped with a thermal programmer. The G+C contents were calculated from the Tm values (melting/transition temperature) derived from the peaks of the first derivatives of the melting curves [111]. DNA from Candida parapsilosis isolate CBS604 (Tm in 0. 1 x SSC, 70. 6°C) [3] was used as a calibration control. Determinations were performed at least twice for each isolate. Phylogenetic analysis showing the placement of species within the Capnodiales with expanded genomes was done using Internal Transcribed Spacer regions (ITS). DNA sequences were downloaded from GenBank with the following accession numbers: AF181692 for Z. tritici, EU514233 for P. eumusae, EU514265 for P. musae and EU514248 for P. fijiensis or obtained from genome data available at the Fungal Genome portal at JGI. Sequence alignment was done using MUSCLE [112] and the phylogenetic tree was generated with MEGA 6. 0 [113] using a Maximum Likelihood statistical method and the Tamura 3-parameter substitution model. Support for the nodes of the tree was estimated by bootstrapping with 1000 replications. Isolates of P. fijiensis grown for 3 weeks in PD broth at 28°C, 150 rpm, were blended and grown for 48 hrs in the same medium at 20% strength amended with 1 μM tricyclazole. Decanted culture was washed with 1 M sorbitol, and added to 40 mL of OM buffer (1. 2 M MgSO4,10 mM K phosphate, pH 5. 8 with 700 mg of glucanase (Sigma, Germany), 256 mg of yatalase (Takara, Japan), 7500 U of β-glucuronidase (Sigma) and 0. 8 g of driselase (Sigma) ) in a ratio of ~1: 3 (mycelium: buffer). The enzymatic treatment was incubated at 33°C and shaken at 50 rpm for 4. 5 hrs. Protoplasts were filtered through a plastic mesh of 30 μm and washed 3 times with 1 M sorbitol in sterile conditions. When the concentration was at least 1 × 108 per mL, protoplasts were embedded in low-melting point (SeaKem Gold) agarose at a final concentration of 0. 5%. Agarose plugs were treated with proteinase K as described previously [114], washed with cold 50 mM EDTA, and kept in the same solution at 4°C until used. Chromosomes of P. fijiensis were separated in a CHEF DR-II system (Bio-Rad, Netherlands). Small chromosomal bands were discriminated as described before [57] using the chromosomes of Saccharomyces cerevisiae (Bio-Rad) as a high molecular weight (HMW) standard. Large chromosomes were separated in a 0. 8% low-melting point (SeaKem Gold) agarose gel, with 0. 5% TBE buffer at 11°C, and 50 V for 195 hrs with switching times from 4800 to 1800 sec, and 24 hrs from 1800 to 1300 sec, followed by 20 hrs at 60 V from 1300 to 800 sec, and finally 27 hrs of 800 to 600 sec at 80 V. HMW standards were Schizosaccharomyces pombe and Hansenula wingei chromosomes (BioRad). Agarose gels were stained with SYBRGold (Invitrogen) and destained in water for 30 and 20 min, respectively, observed under a UV transilluminator and recorded with an Eagle Eye II (Stratagene) still video system. Two tools, Circos [115] and MUMmer [116], were used for structural analysis of the P. fijiensis genome. A nucleotide-based similarity search was done between the masked P. fijiensis and Z. tritici genomes and visualized using Circos [115], whereas protein comparisons between the masked genomes were done using Promer [116]. Proteins with greater than 60% identity were reported. Proteins in P. fijiensis and Z. tritici with at least 50% amino-acid identity and match length were grouped as orthologs using OrthoMCL [117] and synteny blocks were determined using Orthocluster [118]. The Z. tritici protein dataset also was compared to two other phylogenetically distant Dothideomycetes in the order Pleosporales, P. nodorum and P. tritici-repentis. To analyze the frequencies of molecular marker alleles and fungicide resistance within populations, four farms in Costa Rica were sampled during 2008 (S8 Fig). San Pablo, Zent, and Cartagena are located in Limón province, where bananas are grown at high density on large plantations and diseases are controlled by using chemical fungicides. These farms are located in the main Costa Rica banana production area with approximate sizes of 285,342 and 64 ha, respectively. A fourth farm, San Carlos (0. 5 ha), is located in Alajuela province and is isolated geographically from the principal banana-production area. Leaf tissue was collected from ten banana plants from each farm. Ascospores were discharged from the pseudothecia onto water agar [119] and single ascospores were transferred immediately to 15 x 100-mm petri dishes filled with potato dextrose agar (PDA). Between eight to ten ascospores from each sample point were placed on each dish of PDA. After 4 days colonies were transferred to Mycophil agar (Becton Dickinson Microbiology Systems, Cockeysville, MD) and incubated for 15 days at 25°C under continuous fluorescent light for colony growth and conidial production. Eventually, 649 isolates were collected and analyzed for phenotypic and molecular variability. To obtain DNA for population genetics analyses, mycelia of 190 isolates from each of the three commercial plantations and of 95 isolates from the San Carlos population were harvested and lyophilized for 24 hours. Genomic DNA was extracted using the Wizard Magnetic DNA Purification System for Food Kit (Promega, Madison, WI, USA) according to the manufacturer’s instructions and 2 μL per sample were quantified using a NanoDrop ND-1000 Spectrophotometer (NanoDrop Technologies, Wilmington, DE, USA). Mating type (mat) PCR assays [120] were performed in a 50-μL total volume containing 50 ng of template genomic DNA, 2 mM MgCl2,600 μM dNTPs, 5 μM of each primer, and 0. 4 U of Taq DNA polymerase (Roche, Mannhein, Germany). Temperature cycling was carried out with the following program: 94°C for 2 min, 40 cycles of 94°C for 1 min, 70°C for 30 s and 72°C for 1 min, and a final elongation period of 10 min at 72°C. Analysis of VNTR markers was done as reported previously [121]. For genotyping strobilurin resistance, primers were developed on the basis of the G143A mutation in the cytb gene [122] to identify sensitive and resistant P. fijiensis field strains (S10 Table) in 20-μL aliquots containing 50 ng of template genomic DNA, 2 mM MgCl2,600 μM dNTPs, 5 μM of each primer and 0. 4 U of Taq DNA polymerase (Roche, Mannhein, Germany). Temperature cycling was conducted with the following program: 94°C for two min, 40 cycles of 94°C for one min, 70°C for 30 s and 72°C for one min, and a final elongation period of 10 min at 72°C. Amplicons were separated by electrophoresis using 1% (for mat and cytb assays) or 3% (for VNTRs) agarose gels containing 0. 3 μg/mL ethidium bromide, in 0. 5× TBE buffer at 120 V for approximately 1 h (for mat and cytb assays) or 5 h (for VNTRs) and were visualized and photographed using a UV transilluminator and Eagle Eye II (Stratagene) still video system. To analyze the data, frequencies of the two mating types within each population and in the overall sample were tested for deviation from a 1: 1 ratio with χ2 tests. A molecular multilocus haplotype was constructed for each isolate by combining the allelic data at all five VNTR loci. Gene diversity within each population (HS) in total and by locus was calculated using GenAlEx 6. 4 [123]. Total diversity over the entire sample (HT), mean gene diversity within populations (HS), genetic differentiation among populations (GST) and the corrected, standardized measure of genetic differentiation (G”ST) were calculated using GENODIVE Beta version 2. 0 [124]. In all cases, HT and HS refer to the unbiased estimates as developed by Nei [125]. Pairwise estimates of G”ST and of Jost’s differentiation (D) [126] also were calculated with GENODIVE. Multilocus haplotype diversity was calculated with multilocus (http: //www. bio. ic. ac. uk/evolve/software/).
summary: Black Sigatoka or black leaf streak disease, caused by the ascomycete fungus Pseudocercospora fijiensis, inflicts huge costs on banana producers, due to crop losses and expenses for disease control. The global banana export trade relies on Cavendish clones that are highly susceptible to P. fijiensis. Sustainable production of the world’s number one fruit requires a better understanding of host resistance and sophisticated management of fungicide resistance in the pathogen. In the P. fijiensis genome sequence we identified an effector that induced an HR-like necrosis on a resistant banana accession but not on a susceptible cultivar. If validated, this assay may be useful for identifying resistance in banana breeding programs. We also used the genomic sequence to develop highly polymorphic molecular markers for analyzing P. fijiensis field populations and identified a strong enrichment (nearly 100%) for fungicide resistance markers in fungicide-treated banana plantations compared to untreated wild-type populations. This rapid evolution of fungicide resistance poses an immediate threat to sustainable banana production.
keywords: medicine and health sciences
  bananas
  pathology and laboratory medicine
  fungal genetics
  pathogens
  microbiology
  fungi
  genetic elements
  crops
  plants
  fungal pathogens
  mycology
  crop science
  chromosome biology
  medical microbiology
  microbial pathogens
  comparative genomics
  fruits
  agriculture
  fungal genomics
  cell biology
  genetics
  transposable elements
  biology and life sciences
  genomics
  mobile genetic elements
  computational biology
  organisms
  chromosomes
title: Combating a Global Threat to a Clonal Crop: Banana Black Sigatoka Pathogen Pseudocercospora fijiensis (Synonym Mycosphaerella fijiensis) Genomes Reveal Clues for Disease Control