Research Collection

Doctoral Thesis

Mitochondrial genomes of plant pathogenic fungi

Author(s): Torriani, Stefano F.F.

Publication Date: 2008

Permanent Link: https://doi.org/10.3929/ethz-a-005807786

Rights / License: In Copyright - Non-Commercial Use Permitted

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ETH Library

Diss. ETH No. 18123

MITOCHONDRIAL GENOMES OF PLANT PATHOGENIC FUNGI

A dissertation submitted to the SWISS FEDERAL INSTITUTE OF TECHNOLOGY ZURICH For the degree of DOCTOR OF SCIENCE

Presented by STEFANO F. F. TORRIANI Dipl. Natw. ETH

Born 17 January 1980 Citizen of Switzerland

Accepted on recommendation of

Prof. Dr. Bruce A. McDonald, examiner Prof. Dr. Alexander Widmer, co-examiner

2008

Table of contents

SUMMARY 1 RIASSUNTO 3

CHAPTER 1 5 General introduction

CHAPTER 2 25 The mitochondrial genome of Mycosphaerella graminicola

CHAPTER 3 51 The evolutionary history of Mycosphaerella spp. mitochondrial genome

CHAPTER 4 75 The mitochondrial genome of Phaeosphaeria nodorum

CHAPTER 5 123 QoI resistance evolution in European populations of Mycosphaerella graminicola

CHAPTER 6 143 Screening for QoI resistance in a global sample of Rhynchosporium secalis

CHAPTER 7 159 General conclusions

ACKNOWLEDGEMENTS 167 CURRICULUM VITAE 169 PUBBLICATIONS 169

To all those who manage to read from start to finish

Summary

The mitochondrial genomes of plant pathogenic fungi was the leitmotiv of this work that 1) completely annotated the mitochondrial genomes of two wheat-infecting pathogens, Mycosphaerella graminicola and Phaeosphaeria nodorum, 2) inferred the mitochondrial evolutionary history of M. graminicola and 3) studied the evolutionary mechanisms influencing the occurrence and spread of strobilurin (QoI) fungicide resistances. The two obtained mitochondrial genomes were the first analyzed from any species from the class Dothideomycetes, including more than 6000 known species and some of the most economically important plant pathogenic fungi. The fungal mitochondrial genomes displayed some common characteristics interspecifically, including a standard set of genes involved in oxidative phosphorylation, two genes for the large and the small ribosomal subunits and a set of tRNAs genes, which often clustered in groups showing conservation in gene order between organisms in the large Pezizomycotina subphylum of Ascomycota. The mitochondrial tRNA gene order was proposed as an additional criterion in phylogenetic analyses to distinguish between fungal classes. Another distinctive feature of fungal mitochondrial genomes is the variable number of introns. The evolutionary history of the M. graminicola mitochondrial genome was inferred using four sequence loci, dating the divergence from the ancestral Mycosphaerella populations, between 10,000 and 9,000 years ago, coinciding with the domestication of wheat and essentially confirming the analysis based on nuclear markers. The insertion/deletion polymorphisms distinguishing the mitochondrial haplotypes were characterized. A putative gene predicted to encode protein acting as virulence factor proposed to increase the pathogenicity to durum wheat (Triticum turgidum), was identified exclusively in mitochondrial RFLP haplotype 4. To provide better fungicide management strategies the evolutionary mechanisms driving the emergence and spread of resistance need to be studied. QoIs target the protein encoded by the mitochondrial gene cytochrome b. M. graminicola and the barley-infecting pathogen Rhynchosporium secalis were therefore screened for QoI resistance. All 841 tested R. secalis isolates from a global collection were completely sensitive with an estimated naïve resistance frequency less than 0.12%. M. graminicola populations displayed high QoI resistance

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frequencies in Europe, ranging from 30% to 100%. In M. graminicola, selection, parallel genetic adaptation and migration were identified as the principal forces shaping the evolution of fungicide resistances. The same evolutionary pattern of QoI resistance in M, graminicola could be extended to other fungal pathosystems or fungicides having different modes of action.

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Riassunto

Il genoma mitocondriale dei funghi fitopatogeni è stato il filo conduttore di questo lavoro durante il quale: 1) è stato annotato l’intero genoma mitocondriale di due patogeni del frumento Mycosphaerella graminicola e Phaeosphaeria nodorum, 2) è stata dedotta la storia evolutiva di M. graminicola, 3) sono stati investigati i meccanismi evolutivi responsabili dello sviluppo e diffusione della resistenza ai fungicidi analoghi delle strobilurine. I due genomi mitocondriali ottenuti sono i primi analizzati di specie appartenenti alla classe Dothideomycetes, che comprende più di 6,000 specie e alcuni fra i funghi fitopatogeni economicamente più dannosi. I genomi fungini mitocondriali mostrano alcune caratteristiche comuni a livello interspecifico, come l’espressione di un gruppo di geni dedicati alla fosforilazione ossidativa, due geni codificanti per altrettanti RNA ribosomiali (rRNA) e una gamma di RNA di trasporto (tRNA), i quali sovente sono raggruppati in clusters e mostrano una conservazione nell’ordine genico fra gli appartenenti alla suddivisione Pezizomycotina. Questo lavoro propone di usare l’ordine genico dei tRNA mitocondriali quale criterio aggiuntivo in analisi filogenetiche per differenziare classi fungine. Un numero variabile di introni fra un organismo e l’altro è una caratteristica distintiva dei genomi mitocondriali dei funghi. La storia evolutiva del genoma mitocondriale di M. graminicola è stata dedotta usando quattro loci genetici datando la separazione di questa specie dalle popolazioni ancestrali di Mycosphaerella fra 10,000 e 9,000 anni fa, simultaneamente alla domesticazione del frumento; ciò che conferma i risultati di una precedente analisi basata su loci nucleare. Le inserzioni e delezioni di DNA, che distinguono gli aplotipi mitocondriali di M. graminicola, sono state caratterizzate identificando un gene putativo (esclusivo dell’aplotipo 4) che si suppone codifichi un fattore di virulenza in grado di aumentare la patogenicità verso il grano duro (Triticum durum). L’analisi dei meccanismi evolutivi alla base dello sviluppo e diffusione delle resistenze è di fondamentale importanza per fornire migliori strategie di gestione dei fungicidi. M. graminicola e Rhynchosporium secalis, un patogeno dell’orzo, sono stati dunque esaminati alla ricerca d’isolati resistenti ai fungicidi analoghi delle strobilurine che agiscono sul

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citocromo b, codificato da un gene mitocondriale. Tutti gli 841 isolati di R. secalis provenienti dai cinque continenti sono risultati sensibili e la frequenza di resistenza stimata è inferiore a 0.12%. Le popolazioni europee di M. graminicola invece mostrano frequenze di resistenza variabili fra 30-100%. Dall’analisi di M. graminicola si deduce che selezione, adattamento genetico parallelo e migrazione sono le principali forze che modellano l’evoluzione delle resistenze. Questa interpretazione probabilmente può essere estesa ad altri sistemi patologici fungini e a fungicidi aventi modi d’azione differenti da quello dei fungicidi analoghi delle strobilurine.

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CHAPTER 1

General introduction

Chapter 1 General introduction

6 Chapter 1 General introduction

Agriculture and pathogens - Past, Present and Future

About 12,000 years ago humanity began the slow development from a hunter-gatherer to an agricultural society. Archeological and genetic findings support the origin of the agriculture in the Fertile Crescent of the Middle East between 10,000 and 12,000 years ago (Gopher et al. 2002; Salamini et al. 2002). This step, also known as the Neolithic revolution (Childe 1953), was crucial for shaping the human society we know today. Without agriculture the earth would be different, probably characterized by a reduced technology, political organization, no or little urbanization, less pollution and more biodiversity. The wild progenitors of the major Neolithic founder crops e.g. wheat (Triticum spp.), barley (Hordeum vulgare) and pea (Pisum sativum) have been identified in the Middle East (Diamond 1997; Haudry 1997). The continuous selection of desirable morphological traits has driven the slow process of wild grass domestication, creating the crop species we know today (Sharma and Waines 1980; Elias et al. 1996; Taenzler et al. 2002). The first crops were probably composed of species mixtures, but over time Neolithic farmers of the Middle East preferred planting crop species monocultures that subsequently spread to other regions in Europe and Asia (Diamond 1997). The invention of agriculture caused the simultaneous evolution of those pathogens infecting the wild progenitors of the founder crops. With agriculture intensification the landscape was modified, changing from a natural to an agricultural ecosystem, characterized by greater environmental homogeneity, lower species diversity and higher density of more host-specialized pathogens (Stukenbrock and McDonald 2008). The evolution of all three pathogens studied in this work, (Mycospharella graminicola, Phaeosphaeria nodorum and Rhynchosporium secalis) was shaped by human mediated environmental changes that created agricultural ecosystems. Stukenbrock and McDonald (2008) identified the four more likely scenarios for the evolutionary mechanisms by which plant pathogenic fungi have emerged in agricultural ecosystem; 1) host-tracking, when pathogen and host coevolved during host domestication (Stukenbrock et al. 2007), 2) host shifts and jumps, e.g. following the introduction of new crops into new natural ecosystems or from a wild population (Couch et al. 2005), 3) horizontal gene transfer, when a exogenous gene is introduced in a new genome

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(Friesen et al. 2006), 4) interspecific hybridization, when a big part of an exogenous genome is introduced into a new genome (Ioos et al. 2006). As the beginning of agriculture influenced evolution of plant pathogenic fungi, it is reasonable to postulate that present anthropogenic climate changes will affect future evolution of the same organisms. A pioneering study, confirming that current anthropogenically induced environmental changes influenced pathogen evolution, was conducted using archived samples of wheat grain and leaves from the Broadbalk experiment in Rothamsted (1844-2003). This study presented a strong correlation between changes in atmospheric pollution and changes in ratio of plant pathogenic fungi M. graminicola and P. nodorum (Bearchell et al. 2005). Agriculture played, and will play in the future, a fundamental role in sustaining the logarithmic increase of the global human population, which grew from 1.6 to 6.1 billion inhabitants during the 20th century (Lutz and Qiang 2002) and will probably reach 9 billion by 2050 (United Nation 2004). The Food and Agriculture Organization of the United Nations (FAO newsroom 2008) identified the major long-term challenges that world agriculture is facing; among them 1) land and water constraints, 2) low investments in rural infrastructure and agricultural research 3) expensive agricultural inputs relative to farm-gate prices 4) limited adaptation to climate changes. To feed the world population of 2050, the global food production must nearly double. Since population growth will occur mostly in emerging countries and in urban areas, the rural work force will need to be more productive and therefore investments in agriculture renewal are needed. Another future problem for agriculture has its roots in the limited availability of oil, whose price reached a new record of 147.27 US$ per barrel on 11 July 2008. A possible alternative to fossil fuels are the biofuels that may provide up to 25% of the world’s energy needs over the next 20 years (FAO newsroom 2006). As produced today biofuels offer new opportunities to farmers, especially in tropical areas, but simultaneously competition for land between energy production and nutritional purposes will cause future troubles.

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Mitochondrial genome current view

The discovery of mitochondrion could not be credited to a single scientist, however the first descriptions of this small rod-shaped organelle go back to 1840. The name mitochondria was introduced by microbiologist Carl Benda (1857-1933) in 1898 from the Greek mitos “thread” and khondrion “little granule”. Most knowledge about mitochondria arose during research conducted over the last sixty years (Scheffler 2001). Especially from the sixties, when DNA was discovered in mitochondria, sequences accumulate in databases continuously. At present, 1,486 mitochondrial (mt) genomes have been completely sequenced and deposited in the NCBI database, 57 from fungi including 37 from Ascomycota. Fungal mt genome sequencing is in its infancy, since only a few of the 70,000 described fungal species have been studied (Paquin et al. 1997). Mt genomes have proven to be highly useful for research dealing with evolutionary and systematic studies because of their uniparental inheritance, near absence of genetic recombination and uniform background (Chen and Hebert 1999). During evolution of mt genomes, several genes were lost or translocated to the nucleus (Adams et al. 2000), with most mt proteins now encoded by nuclear genes and only subsequently imported into mitochondrion by translocase complexes. Relatively few mt proteins are synthesized directly within the organelle (Hartl et al. 1989; Brennicke et al. 1993). Mt genomes vary widely in size among fungi, ranging from approximately 18 to 109 kb (NCBI database). The main causes are differences in length and organization of intergenic regions and invasion of some mt genes by mobile group I introns, containing homing endonuclease genes of the LAGLIDADG family (Signorovitch et al. 2007). Fungal mtDNAs are generally larger than animal mtDNAs and about an order of magnitude smaller than those of plants (Burger et al. 2003). Other unique characteristics of mt genomes are 1) high A+T content, 2) lack of methylation, 3) conservation in gene function, 4) high copy number 5) alternative genetic code and 6) an independent rate of evolution relative to nuclear genomes (Griffiths 1996; Campbell et al. 1999; Ballard and Whitlock 2004).

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Chemical disease control vs mitochondrial genome

Chemical disease control was routinely applied from the 19th century, though some chemicals, like brine arsenic and copper sulphate, were used even earlier in the treatment of cereal seeds (Russell 2005). From 1824 sulphur was recommended to control powdery mildew and other foliar pathogens (Robertson 1824). More chemicals were released by the end of 19th century, including e.g. Bordeaux mixture and mercuric chloride. After the Second World War, a period of big advances in chemical industry, chemical crop protection industry exploded and from the 1960s a more focused R&D and a rapid market growth characterized it (Russell 2005). Immediately, with the increased use and sometimes overuse of chemical compounds, pathogens developed resistances and industry realized that the situation was having a serious impact so that a major collaboration was established with the formation of Fungicide Resistance Action Committee (FRAC) in the early 1980s. FRAC’s main duty is to coordinate resistance management strategies (Russell 1995). In 2005 the total market value of fungicides approached nine billions dollar (McDougall 2006). Most of the known fungicides targeted nuclear genes, but in 1996 were introduced in the market strobilurins fungicides (QoIs), inhibiting mt respiration in fungi. The discovery of QoIs was inspired by a group of natural fungicidal derivates of ß-methoxyacrylic acid produced by a range of Basidiomycete wood-rotting fungi (Bartlett et al. 2002). A single amino acid substitution (G143A) in mt encoded protein cytochrome b, caused by a single nucleotide polymorphism, is the major mechanism of QoI resistance in most plant pathogenic fungi (Gisi et al. 2002). Other fungi like Alternaria solani (Pasche et al. 2005) or Pyrenophora teres (Sierotzki et al. 2007) have an alternative mutation (F129L), conferring only moderate resistance (FRAC International, Germany). Unknown mechanisms leading to QoI resistance have been seen in Venturia inaequalis (Steinfeld et al. 2001) and Podosphaera fusca (Fernández-Ortuño et al. 2008). Recently, it was postulated that for those fungi having Type 1 intron located directly after G143, the mutation causing G143A change couldn’t occur because it would affect the splicing process, producing a non-functional protein (Grasso et al. 2006). Until now the evolutionary mechanisms behind QoI resistance were not clear, for example was not sure if QoI resistance emerged only once in a distinct mt haplotype, that subsequently spread to other locations by migration, or if it has been fixed

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independently in different genetic and geographic backgrounds by parallel genetic adaptation. Chen et al. (2007) proposed for the grape pathogen Plasmopara viticola the parallel emergence of fungicide resistance, but no literature was found for cereal pathogens. Sales of QoIs exceeded $600 million in 1999 (McDougall 2001). In 1998, only two years after the launch, the first QoI resistance appeared in Blumeria graminis (Sierotzki et al. 2000). In the following years other pathogens became resistant e.g. Pseudoperonospora cubensis in 1999 (Ishii et al. 2001), Pyricularia grisea in 2000 (Vincelli and Dixon 2002), Mycosphaerella graminicola in 2001 (Fraaije et al. 2005). Since no cross-resistance exists between QoIs and other widely used compounds, such as DeMethylation Inhibitors (DMI) or chlorothalonil, disease control and postponement of resistance development could be achieved by combining these chemicals in spray programs.

Mycosphaerella graminicola - The pathogen

Mycosphaerella graminicola (anamorph: Septoria tritici) causes Septoria tritici blotch of wheat and other poaceous hosts worldwide (Eyal 1999). This disease is especially severe in humid and temperate climates e.g. northwestern Europe, causing up to 40% economic loss (Eyal 1981). The taxonomic placement of Mycosphaerella was until recently uncertain and it was usually placed near Dothidea in the Dothideales (Kirk et al. 2001; Goodwin et al. 2004), but recent analyses placed Mycosphaerella in the Capnodiales, a sister group to the Dothideales and Myriangiales (Schoch et al. 2006). Stukenbrock et al. (2007), using nuclear markers, fixed the divergence of M. graminicola from the ancestral populations infecting uncultivated grasses about 10,500 years ago in the Fertile Crescent, proposing the evolutionary scenario of the pathogen domestication along with the host. M. graminicola life cycle presents both sexual and asexual stages, producing respectively ascospores potentially dispersed over several kilometers (Sanderson 1972) and pycnidiospores, normally disseminated by rain splash (Bannon and Cooke 1998). M. graminicola displays high nuclear and low mt diversity (Zhan et al. 2003). High nuclear diversity is produced by combined effect of large effective population sizes (Zhan and McDonald 2004), high gene flow (Boeger et al. 1993; Zhan et al. 2003) and recurring sexual reproduction (Chen and McDonald 1996). The low mt diversity was proposed to result from a selective sweep affecting only the mt

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genome (Zhan et al. 2004). The best way to control Septoria tritici blotch is through fungicides, like DMI or QoIs. DMI have been extensively used for over 20 years, displaying wide variation in the baseline sensitivity (Gisi et al. 1997; Stergiopoulos et al. 2003) with a slow but constant shift towards reduced sensitivity (Gisi et al. 2005; Mavroeidi and Shaw 2005). Genetic analyses of azole-resistant strains indicated a polygenic system for azole resistance (De Waard 1994; Stergiopoulos et al. 2003). QoIs were introduced in 1996 and developed quickly high levels of resistance in M. graminicola (Fraajie et al. 2005).

Phaeosphaeria nodorum - The pathogen

Phaeosphaeria (syn. Leptosphaeria) nodorum [anamorph: Stagonospora (syn. Septoria) nodorum] causes the economically important disease Stagonospora nodorum leaf and glume blotch disease on wheat. P. nodorum is the major foliar pathogen in Western Australia and north central and north eastern North America (Solomon et al. 2006) as it was in Europe until the 1970s before being replaced by M. graminicola (Bearchell et al. 2005). P. nodorum is a filamentous fungus from the Dothiodeomycetes class that includes the causal pathogens of many economically important plant diseases e.g. Leptosphaeria maculans, Cochliobolus heterostrophus and Ascochyta blight of several legumes (Winka and Eriksson 1997). Many plant pathogens of the Dothiomycetes produce host specific toxins (Wolpert et al. 2002). In P. nodorum, proteinaceous host specific toxins were shown to be important virulence determinants (Liu et al. 2004a and 2004b), like ToxA that has been horizontally transferred into Pyrenophora tritici repentis, causing the emergence of a new disease of wheat called yellow or tan spot in 1941 (Friesen et al. 2006). As M. graminicola, P. nodorum displays in both sexual and asexual stages, with ascospores being blown over considerable distances and pycnidiospores dispersed over short distances (Griffiths and Hann 1976; Brennan et al. 1985; Arseniuk et al. 1998). The infection epidemiology is polycyclic with repeated cycles of both sexual and asexual infection (Bathgate and Loughman 2001; McDonald unpublished). P. nodorum is dispersed over long distances also by seed borne dispersal (Shah et al. 1995; Bennett et al. 2005). Seed transmission is important but easily controlled by fungicides. Epidemiology and population genetic evidence indicates that the pathogen undergoes sexual

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reproduction in the field regularly and that, as M. graminicola, gene flow is global (Stukenbrock et al. 2006). The migration among populations probably has not been symmetrical, but rather reflects the historical movement of the host. P. nodorum is mainly controlled, as M. graminicola, with DMI and QoIs. Cultural practices could reduce the severity of the infections often in a minor way (Eyal 1999).

Rhynchosporium secalis - The pathogen

Rhynchosporium secalis causes a necrotic disease known as scald or leaf blotch on barley, rye and various other poaceous hosts, especially on species of Agropyron, Bromus, Hordeum and Lolium (Caldwell 1937; Shipton et al. 1974; Zaffarano et al. 2008). Scald is a worldwide problem and in region with humid and cool temperature it can cause yield losses of 35-40% (Shipton et al. 1974; Khan 1986). R. secalis produces two-celled conidia with a typical beak (from here the name of the species, since beak in Greek is Rhyncos). No sexual spore has been found for the genus Rhynchosporium, however high levels of genetic variability similar to that of sexual reproducing fungi were identified (Goodwin et al. 1993; McDonald et al. 1999; Salamati et al. 2000). The presence of both mating types at equal frequency in the field is a further suggestion for the occurrence of a cryptic teleomorph (Linde et al. 2003). R. secalis is mainly controlled through cultural practices like crop rotation, treatment of seeds or resistant cultivars; fungicides remain a valid alternative. Many resistance genes to barley scald were described (Webster and Jackson 1980; Reitan et al. 2002). Fungicides are largely applied in Europe for example by the end of the 1980s about 90% of winter barley crop was treated at least once (Oerke et al. 1994). Fungicides display different efficacy ranging from high resistance frequencies for benzimidazol carbamates (MBC) and DMI (Kendall et al. 1993; Locke and Phillips 1995) to the complete sensitivity to QoIs (FRAC International, Germany). Barley and rye originated in the Fertile Crescent approximately 10,000 to 12,000 years ago (Badr et al. 2000), but Zaffarano et al. (2006) showed that the center of diversity did not coincide with center of origin of barley. Center of pathogen diversity was found to be Scandinavia. This result was confirmed using the avirulence gene NIP1 (Brunner et al. 2007). Zaffarano et al. (2008) confirmed the emergence

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of R. secalis most likely between 1,200 and 3,600 years ago, following the introduction of barley in to northern Europe through a host shift.

The present study - chapter by chapter

The present nearly four years study, was planned to provide new insights into the mt genomes of plant pathogenic fungi. The mt genomes of P. nodorum (EU053989) and M. graminicola (EU090238) were completely sequenced, annotated and released. This effort represents about the 5% of all mtDNAs sequenced from ascomycetes, until 2008 globally. The evolutionary history of the mt genome in Mycosphaerella populations infecting bread wheat, durum wheat and wild grasses was elucidated. Finally the QoI resistance evolution was studied in M. graminicola and R. secalis, showing that 1) in M. graminicola recurring mutations introduced the QoI resistant allele into different genetic and geographic backgrounds and that 2) R. secalis remains sensitive to QoIs with a naïve resistant allele frequency predicted from a global collection of samples to be lower than 0.12%.

Chapter 1 gives an introduction about 1) history and evolution of agriculture, 2) present knowledge of mt genomes, 3) correlation between mtDNAs and QoI resistance and 4) general introduction about plant pathogenic fungi M. graminicola, P.nodorum and R. secalis.

Chapter 2 shows the intraspecific comparison and annotation of the completely sequenced mt genome sequences from two isolates of M. graminicola and an estimation of the intraspecific mt diversity based on three mt loci among 37 isolates sampled globally.

Chapter 3 infers the evolutionary history of the mt genome of Mycosphaerella populations infecting Triticum durum, Triticum aestivum, Lolium multiflorum, Dactylis glomerata and Agropyron repens and characterizes the insertions/deletions polymorphisms associated with the main mtRFLP types, with particular attention to a 3 kb insertion found exclusively in RFLP type 4, which was proposed to increase the parasitic fitness on T. durum.

14 Chapter 1 General introduction

Chapter 4 presents the P. nodorum genome sequence. My contribution to this publication was limited to the characterization and annotation of mt genome.

Chapter 5 clarifies the evolutionary mechanisms behind the rapid emergence and spread of QoI-resistant isolates of M. graminicola in Europe, by testing two hypothesis 1) QoI resistance occurred only once and subsequently spread to other regions or 2) QoI resistance occurred independently in several different genetic and geographic backgrounds.

Chapter 6 characterizes the mt gene cytochrome b of R. secalis, describes the intraspecific and interspecific sequence diversity, presents the diagnostic tools needed to detect the most common allele associated with QoI resistance and screens a global collection of 841 isolates for QoI resistance.

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References

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Brunner PC, Schurch S, McDonald BA. 2007. The origin and colonization history of the barley scald pathogen Rhynchosporium secalis. J Evol Biol. 20:1311-1322. Burger G, Gray MW, Lang BF. 2003. Mitochondrial genomes: anything goes. TRENDS Genet. 19:709-716. Caldwell RM. 1937. Rhynchosporium scald of barley, rye, and other grasses. J Agr Res. 55:175-197. Campbell A, Mrazek J, Karlin S. 1999. Genome signature comparisons among prokaryote, plasmid, and mitochondrial DNA. Proc Natl Acad Sci USA 96:9184-9189. Chen WJ, Delmotte F, Richard-Cervera S, Douence L, Greif C and Corio-Costet MF. 2007. At least two origins of fungicide resistance in grapevine downy mildew populations. Appl Environ Microb. 73:5162-5172. Chen JZ, Hebert PDN. 1999. Intra-individual sequence diversity and hierarchical approach to the study of mitochondrial DNA mutations. Mutat Res. 434:205-217. Chen RS, McDonald BA. 1996. Sexual reproduction plays a major role in the genetic structure of populations of the fungus Mycosphaerella graminicola. Genetics 142:1119- 1127. Childe VG. 1953. New light on the most ancient Near East. New York: Praeger. Couch BC, Fudal I, Lebrun MH, Tharreau D, Valent B, van Kim P, Kohn LM. 2005. Origins of host-specific populations of the blast pathogen Magnaporthe oryzae in crop domestication with subsequent expansion of pandemic clones on rice and weeds of rice. Genetics 170:613-630. De Waard MA. 1994. Resistance to fungicides which inhibit sterol 14-a-demethilation, an historical perspective. In Heaney S, Slawson D, Hollomon DW, Smith M, Russell PE, Parry DW. eds, Fungicide resistance. 3-10. BCPC Surrey, UK. Diamond J. 1997. Guns, Germs, and Steel: the Fates of Human Societies. New York: Norton. Elias EM, Steiger DK, Cantrell RG. 1996. Evaluation of lines derived from wild emmer chromosome substitutions. II. Agronomic traits. Crop Sci. 36:228-233. Eyal Z. 1981. Integrated control of Septoria diseases of wheat. Plant Dis. 65:763-768. Eyal Z. 1999. The septoria tritici and stagonospora nodorum blotch disease of wheat. Eur J Plant Pathol. 105:629-641. FAO newsroom 2006. FAO sees major shift to bioenergy. 25 April 2006.

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FAO newsroom 2008. Record harvest but troubles loom ahead. 6 November 2008. Fernandez-Ortuno D, Torés JA, de Vicente A, Pérez-García A. 2008. Field resistance to QoI fungicides in Podosphaera fusca is not supported by typical mutations in the mitochondrial cytochrome b gene. Pest Manag Sci. 64:694-702. Fraaije BA, Burnett FJ, Clark WS, Motteram J, Lucas JA. 2005. Resistance development to QoI inhibitors in populations of Mycosphaerella graminicola in the UK. In: Dehne HW, Gisi U, Kuck KH, Russell PE, Lyr H. eds, Modern Fungicides and Antifungal Compounds IV. 63-71 BCPC, Alton, UK. Friesen TL, Stukenbrock EH, Liu ZH, Meinhardt S, Ling H, Faris JD, Rasmussen JB, Solomon PS, McDonald BA, Oliver RP. 2006. Emergence of a new disease as a result of interspecific virulence gene transfer. Nat Genet. 38:953-956. Gisi U, Hermann D, Ohl L, Steden C. 1997. Sensitivity profiles of Mycosphaerella graminicola and Phytophthora infestans populations to different classes of fungicides. Pestic Sci. 51:290-298. Gisi U, Pavic L, Stanger C, Hugelshofer U, Sierotzki H. 2005. Dynamics of Mycosphaerella graminicola populations in response to selection by different fungicides. In: Dehne HW, Gisi U, Kuck KH, Russell PE, Lyr H. eds, Modern Fungicides and Antifungal Compounds IV. 73-80 BCPC, Alton, UK. Gisi U, Sierotzki H, Cook A, McCaffery A. 2002. Mechanisms influencing the evolution of resistance to Qo inhibitor fungicides. Pest Manag Sci. 58:859-867. Goodwin SB, Waalwijk C, Kema GHJ. 2004. Genetics and genomics of Mycosphaerella graminicola: a model for the Dothideales. In: Arora DK, Khachatourians GG, eds, Applied Mycology & Biotechnology. Volume 4. Fungal Genomics Elsevier Science B.V., Amsterdam, pp. 315-330. Goodwin SB, Maroof MAS, Allard RW, Webster RK. 1993. Isozyme variation within and among populations of Rhynchosporium secalis in Europe, Australia and the United States. Mycol Res. 97:49-58. Gopher A, Abbo S, Lev-Yadun ST. 2002. The ‘when’, the ‘where’ and the ‘why’ of the Neolithic revolution in the Levant. Doc Praehist. 28:49-62.

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Grasso V, Palermo S, Sierotzki H, Garibaldi A, Gisi U. 2006. Cytochrome b gene structure and consequences for resistance to Qo inhibitor fungicides in plant pathogens. Pest Manag Sci. 62:465-472. Griffiths AJF. 1996. Mitochondrial inheritance in filamentous fungi. J Genet. 75:403-414. Griffiths DC, Hann CAO. 1976. Dispersal of Septoria nodorum spores and spread of glume blotch of wheat in the field. Transactions of the British Micological Society 67:413-418. Hartl FU, Pfanner N, Nicholson DW, Neupert W. 1989. Mitochondrial protein import. Biochim Biophys Acta 988:1-45. Haudry A, Cenci A, Ravel C, Bataillon T, Brunel D, Poncet C, Hochu I, Poirier S, Santoni S, Glémin S, David J. 2007. Grinding up wheat: a massive loss of nucleotide diversity since domestication. Mol Biol Evol. 24:1506-1517. Ioos R, Andrieux A, Marcais B, Frey P. 2006. Genetic characterization of the natural hybrid species Phytophthora alni as inferred from nuclear and mitochondrial DNA analyses. Fungal Genet Biol. 43:511-529. Ishii H, Fraaije BA, Sugiyama T, Noguchi K, Nishimura K, Takeda T, Amano T, Hollomon DW. 2001. Occurrence and molecular characterization of strobilurin resistance in cucumber powdery mildew and downy mildew. Phytopathology 91:1166-1171. Kendall SJ, Hollomon DW, Cooke LR, Jones DR. 1993. Changes in sensitivity to DMI fungicides in Rhynchosporium secalis. Crop Prot. 12:357-362. Khan TN. 1986. Effects of fungicide treatments on scald (Rhynchosporium secalis (Oud)

Davis) infection and yield of barley in western-Australia. Aus J Exp Agr. 26:231-235. Kirk PM, Cannon PF, David JC, Stalpers JA. 2001. Ainsworth & Bisby´s Dictionary of the Fungi. 9th eds, CAB International, Wallingford, UK. Linde CC, Zala M, Ceccarelli S, McDonald BA. 2003. Further evidence for sexual reproduction in Rhynchosporium secalis based on distribution and frequency of mating- type alleles. Fungal Genet Biol. 40:115-125. Liu ZH, Faris JD, Meinhardt SW, Ali S, Rasmussen JB, Friesen TL. 2004a. Genetic and physical mapping of a gene conditioning sensitivity in wheat to a partially purified host- selective toxin produced by Stagonospora nodorum. Phytopathology 94:1056-1060.

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Liu ZH, Friesen TL, Rasmussen JB, Ali S, Meinhardt SW, Faris JD. 2004b. Quantitative trait loci analysis and mapping of seedling resistance to Stagonospora nodorum leaf blotch in wheat. Phytopathology 94:1061-1067. Locke T, Phillips AN. 1995. The occurrence of carbendazim resistance in Rhyncosporium secalis on winter barley in England and Wales in 1992 and 1993. Plant Pathol. 44:294- 300. Lutz W, Qiang R. 2002. Determinants of human population growth. Phil Trans R Soc Lond B. 357:1197-1210. McDonald BA, Zhan J, Burdon JJ. 1999. Genetic structure of Rhynchosporium secalis in Australia. Phytopathology 89:639-645. McDougall P. 2001. Crop protection and agricultural biotechnology consultants, Report 249, July 2001. McDougall P. 2006. Phillips McDougall Agriservice Report. Pathhead, Midlothian, Scotland, UK. Oerke EC, Dehne HW, Schönbeck F, Weber A. 1994. Crop Production and Crop Protection. 297-364, Elsevier, Amsterdam, the Netherlands. Paquin B, Laforest MJ, Forget L, Roewer I, Wang Z, Longcore J, Lang BF. 1997. The fungal mitochondrial genome project: evolution of fungal mitochondrial genomes and their gene expression. Curr Genet. 31:380-395. Pasche JS, Piche LM, Gudmestad NC. 2005. Effect of the F129L mutation in Alternaria solani on fungicides affecting mitochondrial respiration. Plant Dis. 89:269-278. Reitan L, Grønnerød S, Ristad TP, Salamati S, Skinnes H, Waugh R, Bjørnstad Å. 2002. Characterization of resistance genes against scald (Rhynchosporium secalis (Oudem.) J.J. Davis) in barley (Hordeum vulgare L.) lines from central Norway, by means of genetic markers and pathotype tests. Euphytica 123:31-39. Robertson J. 1824. Transaction of the London Horticultural Society 5:175. Russell PE. 1995. Fungicide resistance: occurrence and management. J Agr Sci. 124:317- 323. Russell PE. 2005. A century of fungicide evolution. J Agr Sci. 143:11-25.

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Salamati S, Zhan J, Burdon JJ, McDonald BA. 2000. The genetic structure of field populations of Rhynchosporium secalis from three continents suggests moderate gene flow and regular recombination. Phytopathology 902:901-908. Salamini F, Ozkan H, Brandolini A, Schafer-Pregl R, Martin W. 2002. Genetics and geography of wild cereal domestication in the Near East. Nat Rev Genet. 3:429-441. Sanderson FR. 1972. A Mycosphaerella species as the ascogenous state of Septoria tritici Rob. and Desm. New Zeal J Bot. 10:707-710. Scheffler IE. 2001. A century of mitochondrial research: achievements and perspectives. Mitochondrion 1:3-31. Schoch CL, Shoemaker RA, Seifert KA, Hambleton S, Spatafora JW, Crous PW. 2006. A multigene phylogeny of the Dothideomycetes using four nuclear loci. Mycologia 98:1041-1052. Shah DA, Bergstrom GC, Ueng PP. 1995. Initiation of Septoria nodorum blotch epidemics in winter wheat by seedborne Stagonospora nodorum. Phytopathology 85:452.457. Sharma HC, Waines JG. 1980. Inheritance of tough rachis in crosses of Triticum monococcum and T. boeoticum. J Hered. 71:214-216. Shipton WA, Boyd WJR, Ali SM. 1974. Scald of barley. Rev Plant Pathol. 53:840-861. Sierotzki H, Frey R, Wullschleger J, Palermo S, Karlin S, Godwin J, Gisi U. 2007. Cytochrome b gene sequence and structure of Pyrenophora teres and P. tritici-repentis and implications for QoI resistance. Pest Manag Sci. 63:225-233. Sierotzki H, Wullschleger J, Gisi U. 2000. Point mutation in cytochrome b gene conferring resistance to strobilurin fungicides in Erysiphe graminis f. sp tritici field isolates. Pestic Biochem and Phys. 68:107-112. Signorovitch AY, Buss LW, Dellaporta SL. 2007. Comparative genomics of large mitochondria in placozoans. PLOS Genetics 3:e13. Solomon PS, Lowe RGT, Tan K-C, Waters ODC, Oliver RP. 2006. Stagonospora nodorum: cause of stagonospora nodorum blotch of wheat. Mol Plant Pathol. 7:147-156. Steinfeld U, Sierotzki H, Parisi S, Poirey S, Gisi U. 2001. Sensitivity of mitochondrial respiration to different inhibitors in Venturia inaequalis. Pest Manag Sci. 57:787-796.

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Stergiopoulos I, van Nistelrooy JGM, Kema GHJ, De Waard MA. 2003. Multiple mechanisms account for variation in base-line sensitivity to azole fungicides in field isolates of Mycosphaerella graminicola. Pest Manag Sci. 59:1333-1343. Stukenbrock EH, Banke S, Javan-Nikkhah M, McDonald BA. 2007. Origin and domestication of the fungal wheat pathogen Mycosphaerella graminicola via sympatric speciation. Mol Biol Evol. 24:398-411. Stukenbrock EH, Banke S, McDonald BA. 2006. Global migration patterns in the fungal wheat pathogen Phaeosphaeria nodorum. Mol Ecol. 15:2895-2904. Stukenbrock EH, McDonald BA. 2008 The origin of plant pathogens in agro-ecosystems. Annu Rev Phytopathol. 46:75-100. Taenzler B, Esposti RF, Vaccino P, Brandolini A, Effgen S, Heun M, Schäfer-Pregl R, Borghi B, Salamini F. 2002. Molecular linkage map of Einkorn wheat: mapping of storage-protein and soft-glume genes and bread-making quality QTLs. Genet Res Camb. 80:131-143. United Nations (Population Division). 2004. World population to 2300. ST/ESA/SER.A/236, New York, USA. Vincelli P, Dixon E. 2002. Resistance to Q(o)I (strobilurin-like) fungicides in isolates of Pyricularia grisea from perennial ryegrass. Plant Dis. 86:235-240. Webster RK, Jackson LF. 1980. Sources of resistance in barley to Rhynchosporium secalis. Plant Dis. 64:88-90. Winka K, Eriksson OE. 1997. Supraordinal taxa of Ascomycota. Myconet. 1:1-16. Wolpert TJ, Dunkle LD, Ciuffetti LM. 2002. Host-selective toxins and avirulence determinants: What's in a name? Annu Rev Phytopathol 40:251-285. Zaffarano PL, McDonald BA, Linde CC. 2008. Rapid speciation following recent host shifts in the plant pathogenic fungus Rhynchosporium. Evolution 62:1418-1436. Zaffarano PL, McDonald BA, Zala M, Linde CC. 2006. Global hierarchical gene diversity analysis suggests the Fertile Crescent is not the center of origin of the barley scald pathogen Rhynchosporium secalis. Phytopathology 96:941-950. Zhan J, McDonald BA. 2004. The interaction among evolutionary forces in the pathogenic fungus Mycosphaerella graminicola. Fungal Genet Biol. 41:590-599.

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Zhan J, Pettway RE, McDonald BA. 2003. The global genetic structure of the wheat pathogen Mycosphaerella graminicola is characterized by high nuclear diversity, low mitochondrial diversity, regular recombination and gene flow. Fungal Genet Biol. 38:286-297.

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CHAPTER 2

The mitochondrial gemome of Mycosphaerella graminicola

Stefano FF Torriani, Stephen B Goodwin, Gert HJ Kema, Jasmyn L Pangilinan, Bruce A. McDonald. 2008. Intraspecific comparison and annotation of two complete mitochondrial genome sequences from the plant pathogenic fungus Mycosphaerella graminicola. Fungal Genetics and Biology 45:628-637.

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Abstract

The mitochondrial genomes of two isolates of the wheat pathogen Mycosphaerella graminicola were sequenced completely and compared to identify polymorphic regions. This organism is of interest because it is phylogenetically distant from other fungi with sequenced mitochondrial genomes and it has shown discordant patterns of nuclear and mitochondrial diversity. The mitochondrial genome of M. graminicola is a circular molecule of approximately 43,960 bp containing the typical genes coding for 14 proteins related to oxidative phosphorylation, one RNA polymerase, two rRNA genes and a set of 27 tRNAs. The mitochondrial DNA of M. graminicola lacks the gene encoding the putative ribosomal protein (rps5-like), commonly found in fungal mitochondrial genomes. Most of the tRNA genes were clustered with a gene order conserved with many other ascomycetes. A sample of thirty-five additional strains representing the known global mt diversity was partially sequenced to measure overall mitochondrial variability within the species. Little variation was found, confirming previous RFLP-based findings of low mitochondrial diversity. The mitochondrial sequence of M. graminicola is the first reported from the family Mycosphaerellaceae or the order Capnodiales. The sequence also provides a tool to better understand the development of fungicide resistance and the conflicting pattern of high nuclear and low mitochondrial diversity in global populations of this fungus.

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Introduction

Mycosphaerella graminicola (anamorph Septoria tritici) is the causal agent of Septoria tritici blotch of wheat and other poaceous hosts, and occurs worldwide across a wide range of climates (Eyal 1999). The life cycle of M. graminicola includes both sexual and asexual stages. The sexual stage permits genetic recombination and produces airborne ascospores with the potential to be dispersed over several kilometers (Sanderson 1972), whereas the asexual phase (S. tritici) produces pycnidiospores disseminated over limited distances from plant to plant via rain splash (Bannon and Cooke 1998). In most fungi studied to date there is concordance between genetic variation in the mitochondrial (mt) and nuclear genomes (Zhan et al. 2004; Sommerhalder et al. 2007), with some fungi having high levels of mt and nuclear diversity (Liu et al. 1996; Kudla et al. 2002) and others having low mt and nuclear genetic variability (Kurdyla et al. 1995; Xia et al. 2000). However, the pattern of variability in M. graminicola is different; a comparison of RFLP markers in nuclear and mt genomes showed a pattern of high nuclear and low mt diversity in populations around the world (Zhan et al. 2003). Over 1300 nuclear RFLP genotypes were found among 1673 isolates, with an average of 18 alleles per nuclear RFLP locus. In contrast, only seven mtDNA haplotypes were found globally, with the two most common representing 93% of the world population. The high nuclear diversity is thought to be the consequence of high gene flow (Boeger et al. 1993), coupled with large effective population sizes (Zhan and McDonald 2004) and recurring sexual reproduction (Chen and McDonald 1996; Kema et al. 1996; Hunter et al. 1999). Zhan et al. (2004) suggested a selective sweep to explain the low diversity found in the mtDNA. Selective sweeps may be common in mt genomes because all of the genes are linked in one molecule so that selection on one gene can affect the frequency of all genes through hitchhiking. Mt genomes have proven to be highly useful for research in evolutionary biology and systematics because of their uniparental inheritance, the near absence of genetic recombination, and uniform genetic backgrounds (Chen and Hebert 1999). The evolution of mtDNAs has been characterized by extensive loss and translocation of genes to the nucleus (Adams et al. 2000) since their origin by endosymbiosis of a bacterial ancestor (John and Whatley 1975). The result of this process is that most mt proteins are encoded by nuclear

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genes whose products are imported into the mitochondrion by translocase complexes, leaving relatively few mt proteins that are synthesized directly within the organelle (Hartl et al. 1989; Brennicke et al. 1993). Mt genomes are characterized by high A + T content, lack of methylation, conservation in gene function, and high copy number (Campbell et al. 1999), and they can evolve at their own rate relative to the nuclear genomes of the organisms in which they occur (Ballard and Whitlock 2004). The size and topology of the mt genome, the number and nature of the proteins it encodes, and even the genetic code itself can vary greatly among species (Gray et al. 1999). Fungal mtDNAs are generally an order of magnitude smaller than those of plants but larger than animal mtDNAs (Burger et al. 2003) and usually contain 14 genes encoding hydrophobic subunits of respiratory chain complexes, as well as genes for the large (rnl) and small (rns) ribosomal subunits and a set of tRNAs (Gray et al. 1999). The coding percent ranges between 40 and 60% in the Pezizomycotina. Among fungi, mt genomes vary widely in size, from approximately 18 to 109 kb (NCBI database). The variability of mt genome size among species is strongly influenced by differences in length and organization of intergenic regions, as well as by differences in intron content (from 0 to 30) and size (ranging from 0.15 and 4 kb). Burger et al. (2003) showed that there is no correlation between mtDNA size and gene content. The taxonomic placement of Mycosphaerella within the class Dothideomycetes until recently was uncertain, and it usually was placed near Dothidea in the Dothideales (Kirk et al. 2001; Goodwin et al. 2004). However, recent analyses of a multigene phylogeny showed that Mycosphaerella belongs in the Capnodiales, a sister group to the Dothideales and Myriangiales (Schoch et al. 2006). Though the mt genome of Stagonospora nodorum, another member of the Dothideomycetes, was recently published (Hane et al. 2007), no mt genomes have been published from Mycosphaerella or any species in the Capnodiales, Dothideales, or Myriangiales. The goals of this research were to obtain and annotate the first complete mitochondrial genome sequence from the Mycosphaerella branch of the fungal evolutionary tree, and to test a previous hypothesis of low mitochondrial diversity within global populations of M. graminicola. Complete sequences of the mtDNA genomes from two isolates of M. graminicola (one from North America and one from Europe) plus sequences at three

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mitochondrial loci for 35 additional isolates representing most of the known global diversity were compared, first to quantify the overall mtDNA sequence diversity in M. graminicola and second to compare it with earlier findings of low diversity based on RFLP analysis. An interspecific analysis of the tRNA genes flanking rnl of species in the Pezizomycotina revealed a consensus in tRNA gene content and order.

Materials and methods

Fungal strains, DNA extraction, and library construction. Strain IPO323 was isolated from a naturally infected leaf of the soft white wheat cultivar Arminda collected in Brabant, the Netherlands during 1981 (Kema and Van Silfhout 1997). Fungal mycelia were produced on liquid shake cultures, harvested, stored and prepared for DNA extraction as described in Kema et al. (2002). Fungal spores and mycelia were ground with a Hybaid Ribolyser (model FP120HY-230) for 10 s at 2,500 rpm with two tungsten carbide beads, and total genomic DNA was extracted using the Promega Wizard Magnetic DNA Purification System for Food as described by the manufacturer except with only 50 mg of lyophilised fungal material and 500 µl of lysis buffer. Plasmid libraries with insert sizes of 3 and 8 kb were created at the U.S. Department of Energy’s Joint Genome Institute (JGI) and sequenced to 4× genomic sequence coverage (~150,000 clones each). Strain STBB1 was isolated from a wheat field 5 km southwest of College Station, Texas, USA, during 1989. The entire mt genome of this isolate was purified from total DNA by cesium chloride (CsCl) ultracentrifugation as described by Garber and Yoder (1983), with a CsCl density of 1.6 g/ml. A library was constructed by digesting the purified mtDNA to completion using the restriction enzyme HindIII, ligating the fragments into the plasmid vector pUC18 and cloning in Escherichia coli strain DH5α.

DNA sequencing and assembly. Shotgun sequencing of the nuclear and mt genomes of isolate IPO323 was through the Community Sequencing Program of the JGI (www.jgi.doe.gov/CSP/) by analysis of libraries with insert sizes averaging 3, 8 and 40 kb. The mt genome was assembled from ~7,680 sequencing reads from 10 plates of the 3-kb library using phrap (http://www.phrap.org/) with its standard parameters. This corresponds to

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roughly 5-6 Mb of sequence. Approximately 5.5% of the reads (~260 kb) represented mtDNA so the initial sequence was assembled at a depth of about 6×. The average depth of coverage for the entire project was 8.9× and was released publicly (http://genome.jgi- psf.org/Mycgr1/Mycgr1.home.html) during November 2006. The mtDNA library obtained from isolate STBB1 was sequenced using the BigDyeTM Terminator v3.0 Cycle Sequencing kit and the primer walking strategy. The sequencing reactions were in a total volume of 10 µl using 20-40 ng of plasmid DNA, 10 pmol of primers and 2 µl of BigDye reaction mix, previously diluted 1:4. The cycling profile was 10 s denaturation at 95°C, 5 s annealing at 50°C and 4 min extension at 60°C for 100 cycles. The sequencing reactions were purified through Sephadex G-50 DNA Grade F (Amersham Biosciences, Switzerland) before being loaded into an ABI 3100 automated sequencer (Applied Biosystems). The sequences were aligned and analyzed with the Sequencher version 4.2 software package (Gene Codes Corporation, Ann Arbor, MI) using the genetic code of Pezizomycotina that diverged from the standard nuclear code for the codon TGA, which was read as Trp and not as Stop. Sequencing of the isolate STBB1 mt library generated approximately 75% of the entire mtDNA genome. Gaps in the STBB1 sequence were filled by aligning the sequenced HindIII fragments to the complete mtDNA sequence of isolate IPO323 and designing pairs of primers to amplify the missing regions in STBB1. The amplicons were sequenced as described above to obtain the entire mt genome of isolate STBB1.

Sequence annotation. The mtDNA sequence of M. graminicola was screened for similarity with those from other organisms in the NCBI database using the BlastN tool. Sequences showing matches with protein-coding genes of other organisms were subsequently compared using the BlastX tool (Altschul et al. 1990). The mt sequences of strains IPO323 and STBB1 were aligned using the Sequencher program and screened manually for polymorphisms including transitions, transversions, insertions and deletions (indels). The genes coding for ribosomal RNAs were determined by comparison with sequences from other fungi. The tRNAs were defined by tRNAscan-SE v1.21 (Lowe and Eddy 1997) and by comparison with the NCBI database. Expression of mt genes was tested by blast searches against databases of EST sequences (Kema et al. 2003; Soanes and Talbot 2006; Goodwin et

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al. 2007). Repetitive elements, including minisatellites, simple-sequence repeats (SSRs) and mononucleotide repeats were identified using the online program Perfect Microsatellite Repeat Finder (http://sgdp.iop.kcl.ac.uk/nikammar/repeatfinder.html).

Intraspecific comparison and haplotype network. Three mtDNA loci, named Mg1, Mg2 and Mg3, were used to assess the overall mt diversity within the species. These loci were located in different regions of the mtDNA and were chosen because they displayed different degrees of polymorphism in the comparison between STBB1 and IPO323. Mg1 was located within orf1 and had no polymorphism. Mg2 included a portion of orf4 and had several polymorphisms including single-nucleotide polymorphisms (SNPs), indels and homopolymers of various lengths. Mg3 included the region with tRNA-Gly, tRNA-Asp, tRNA- Ser and tRNA-Trp and had two polymorphic microsatellites and one homopolymer. Thirty- five isolates (Table 1) belonging to four RFLP haplotypes (Zhan et al. 2003) and originating from five continents were amplified using primers: Mg1F (5’-CCG GTC CCT CTA ATA GTT CTG G-3’) and Mg1R (5’-TAA TCC GCC ATT ACT TCT CAG G-3’); Mg2F (5’-GGT TCC AAT GGG TTT AAT GCT A-3’) and Mg2R (5’- TGG GTG TAG CTA GAA ACC CTT C-3’); Mg3F (5’-AAG CTA CGC CTA TGG CTA ACA C-3’) and Mg3R (5’-AGG TAA GAC GCA CGC ATT TC-3’). Each PCR reaction contained 5-10 ng of DNA in a 20-µl reaction volume containing 10 pmol of each primer, 100 µM of each nucleotide, 2 µl of 10x

PCR buffer (1x PCR buffer: 10 mM KCl, 10 mM (NH4)2SO4, 20 mM Tris-HCl, 2 mM

MgSO4, 0.1% Triton X-100 [pH 8.8]) and 1 U of Taq DNA Polymerase (New England Biolabs). The PCR amplifications were carried out under the following conditions: initial denaturation at 96°C for 2 min, followed by 35 cycles of 96°C for 1 min, 56°C for 1 min, and 72°C for 1 min, with a final extension at 72°C for 5 min. The PCR products were sequenced using the primers Mg1F, Mg2F and Mg3R, generating a total of 1,339 bp (338 bp for Mg1, 333 bp for Mg2 and 668 bp for Mg3). Sequencing reactions were performed as described previously for STBB1. The program SNAP Workbench (Price and Carbone 2005) was used to collapse the sequences into haplotypes and DnaSP (Rozas et al. 2003) was used to test for recombination within and among the tested loci. The software package TCS version 1.21 (Clement et al. 2000) was used to infer intraspecific evolution of the M. graminicola mtDNA.

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This program applies a statistical parsimony method to infer unrooted cladograms based on Templeton’s 95% parsimony connection limit (Templeton et al. 1992).

Table 1. Mycosphaerella graminicola isolates included in the analysis of mtDNA variation. Haplotype Isolate RFLPa Sequenceb SNPc Hostd Year Location Source AU49 1 1 1 BW 1993 Australia B Ballantyne AU54 1 1 1 BW 1993 Australia B Ballantyne AU58 1 1 1 BW 1993 Australia B Ballantyne CH9B12A 1 4 1 BW 1999 Switzerland BA McDonald AU59 1 11 1 BW 1993 Australia B Ballantyne OR402 1 12 1 BW 1990 Oregon J Boeger, BA McDonald, M Schmitt CH9B12C 1 7 3 BW 1999 Switzerland BA McDonald IN11 1 7 3 BW 1993 Indiana G Shaner IN12 1 7 3 BW 1993 Indiana G Shaner IN13 1 7 3 BW 1993 Indiana G Shaner OR389 1 7 3 BW 1990 Oregon J Boeger, BA McDonald, M Schmitt OR409 1 7 3 BW 1990 Oregon J Boeger, BA McDonald, M Schmitt CH9C1A 1 8 3 BW 1999 Switzerland BA McDonald IN1 1 10 3 BW 1993 Indiana G Shaner IN9 1 10 3 BW 1993 Indiana G Shaner CH9B5A 2 5 1 BW 1999 Switzerland BA McDonald CH9B9A 2 5 1 BW 1999 Switzerland BA McDonald GEA2a.2 2 5 1 BW 1992 Germany R Huang, G Koch IPO323 2 5 1 BW 1981 Netherlands GHJ Kema CH9B7B 2 6 1 BW 1999 Switzerland BA McDonald GEE2b.2 2 6 1 BW 1992 Germany R Huang, G Koch GEE3a.2 2 6 1 BW 1992 Germany R Huang, G Koch U17 2 6 1 BW 1981 Netherlands GHJ Kema GEE1a.2 2 14 1 BW 1992 Germany R Huang, G Koch OR428 2 7 3 BW 1990 Oregon J Boeger, BA McDonald, M Schmitt STBB1 2 9 3 BW 1989 Texas BA McDonald AU57 3 11 1 BW 1993 Australia B Ballantyne AU70 3 11 1 BW 1993 Australia B Ballantyne AU72 3 11 1 BW 1993 Australia B Ballantyne MX156 3 13 1 BW 1993 Mexico L Gilchrist MX160 3 13 1 BW 1993 Mexico L Gilchrist MX163 3 13 1 BW 1993 Mexico L Gilchrist MX167 3 13 1 BW 1993 Mexico L Gilchrist MX169 3 13 1 BW 1993 Mexico L Gilchrist U2 4 2 2 DW 1991 Syria GHJ Kema U7 4 2 2 DW 1991 Tunisia GHJ Kema U6 4 3 2 DW 1991 Tunisia GHJ Kema aRFLP haplotypes are groups of isolates having identical RFLP patterns following Zhan et al. (2003) bSequence haplotypes are groups of isolates having identical concatenated sequences for mitochondrial loci Mg1, Mg2 and Mg3 cSNP haplotypes are groups of isolates having the identical concatenated sequence for Mg1, Mg2 and Mg3 after removing all indels dBW = bread wheat, DW = durum wheat

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Results

Gene content and genome organization. The mt genome of M. graminicola is a circular molecule of approximately 43,960 bp containing 15 protein-coding genes, the large (rnl) and small (rns) ribosomal subunits, 27 tRNAs and eight putative open reading frames (orfs1-8) of unknown function (Fig. 1; Table 2). The protein-coding genes included three ATP synthase subunits (atp6, atp8 and atp9), the three cytochrome oxidase subunits I, II and III (cox1-3), cytochrome b (cytb), seven nicotinamide adenine dinucleotide ubiquinone oxidoreductase subunits (nad1-6, nad4L) and a DNA-directed RNA polymerase (RNA-Pol). These genes were transcribed in two contiguous segments of opposite direction (Fig. 1). A putative ribosomal protein (rps5-like) commonly found within rnl of ascomycetes was missing (Fig. 1; Table 2). To test whether this gene could have been transferred to the nuclear genome, blastp and tblastn searches were performed on the 8.9× draft genomic sequence of M. graminicola. The blastp searches identified no matching proteins among the list of annotated genes. However, the tblastn searches identified matches at better than e-5 on scaffold 5 to rps5-like proteins from Phaeosphaeria nodorum (e-9) and Penicillium marneffei (e-7), but not to those from the Sordariomycetes Hypocrea jecorina or Verticillium dahliae. Therefore, this gene most likely occurs in the nuclear rather than the mitochondrial genome of M. graminicola. The eight putative orfs of unknown function are predicted to produce proteins containing from 126 to 481 amino acids. The 3’ terminus of orf3 overlapped with orf2 for 52 nucleotides. The exact function of these putative proteins remains to be determined, but the TMHMM2 method (Krogh et al. 2001) predicted orf2 to encode a non-membrane protein, whereas the other orfs were predicted to encode proteins having from one (orf5 and orf8) to ten (orf7) transmembrane domains. Expressed sequence tag (EST) databases (Kema et al. 2003; Soanes and Talbot 2006; Goodwin et al. 2007) provided evidence for the transcription of orf5, orf6 and orf8. Putative protein-coding genes covered 51.8% of the genome (including 15.9% composed of putative orfs), while 4.5 and 11.5% corresponded to tRNA genes and both rnl and rns, respectively. These values were similar to those reported for other ascomycetes (Table 2). Overall, the M. graminicola mtDNA was 34.5% A, 33.5% T, 16.3% G and 15.7% C. MtDNA

34 Chapter 2 mtDNA of M. graminicola

AT-content was 68% with coding and non-coding parts of the genome having, on average, the same AT-percentage.

Figure 1. Circular map of the mitochondrial genome of Mycosphaerella graminicola. Black blocks, grey blocks, hatched blocks and bars show, respectively, protein-coding, orfs, rRNA and tRNA genes. Arrows indicate the direction of transcription.

35 Chapter 2 mtDNA of M. graminicola

a Table 2. A comparison of the principal features of some completely sequenced fungal mt genomes Size A + T Coding Percent Accession Species (kb) content genesb Orfs codingc RNAsd number Aspergillus niger 31.1 74% 14 2 47%* 27 DQ207726 Aspergillus tubingensis 33.6 74% 14 2 43%* 27 DQ217399 Penicillium marneffei 35.5 76% 15 10 63%* 30 AY347307 Epidermophyton floccosum 30.9 77% 15 5 67%* 27 AY916130 Mycosphaerella graminicola 43.9 68% 15 8 52%* 29 EU090238 Lecanicillium muscarium 24.5 73% 15 0 58% 27 AF487277 Verticillium dahliae 27.2 73% 15 0 53% 27 DQ351941 Fusarium oxysporum 34.5 69% 15 1 44% 27 AY945289 Metarhizium anisopliae 24.7 72% 15 0 59% 26 AY884128 a All fungi in this list have mt genomes with circular topologies b If present the fifteenth gene is rps5 except for M. graminicola that has a RNA-pol c Asterisks mark the genomes in which orfs were considered as coding genes in the calculation of percent coding d All fungi in this list have two genes encoding for the large and small ribosomal subunit

Codon usage and tRNA genes. As expected given the transmembrane location of most mt proteins, the three most frequent codons were TTA (377 counts), ATA (371 counts) and TTT (270 counts) encoding Leu, Ile and Phe, respectively. These amino acids have hydrophobic side chains commonly found in transmembrane helices. These three codons accounted for 19.3% of all codons in the mt genome. One codon was not used at all (CGA, Arg) and eight codons (CGC, TGG, TGC, CGG, CTC, GGC, GTC, CCG) were under represented, being used from one to ten times each. All 15 protein-coding genes started with the canonical translation initiation codon ATG. The preferred stop codon was TAA, present in 11 protein-coding genes; the alternative stop codon was TAG. Codon usage of the orfs was similar to that of the protein-coding loci. The 27 tRNAs encoded by the mt genome of M. graminicola could carry all 20 amino acids (Fig. 1). Two tRNA isoacceptors were identified for serine and leucine, three for arginine and four for methionine. Among the 27 tRNAs, only tRNA-Val occurred singly. The remaining 26 tRNA genes were grouped into five clusters, composed of 12, 5, 4, 3 and 2 tRNA genes (Fig. 1). As in other filamentous fungi, several tRNA genes flanked the rnl gene (Table 3; Tambor et al. 2006). In M. graminicola, these tRNA genes had an order similar to that of Eurotiomycetes and generally followed a conserved pattern found in other fungi (Table 3; Ghikas et al. 2006). Surprisingly, M. graminicola did not possess the TEM-tRNA genes at the beginning of the 3’ tRNA gene consensus, in contrast to both Eurotiomycetes and Sordariomycetes, suggesting an independent rearrangement in this species. The

36 Chapter 2 mtDNA of M. graminicola

secondary structures of tRNA-Phe and tRNA-Thr diverged from the expected cloverleaf form as they contained nine instead of the canonical seven nucleotides in the anticodon loop

Figure 2. A linearized map showing polymorphisms between the mt genomes of Mycosphaerella graminicola isolates STBB1 and IPO323. Protein coding genes are presented as dark-grey blocks, orfs as light-grey blocks and ribosomal subunit as hatched blocks. The polymorphisms occurring between the mt genomes of isolates STBB1 and IPO323 are transversions (triangles), transitions (circles), microsatellites (plus signs), a frameshift (diamond), and a 17-bp-long indel (square). Arrows under genes indicate the direction of transcription and the small black dots close to the genes show mononucleotide repeats longer than 7 bases. The tRNAs are not presented to simplify the figure. Mg1, Mg2 and Mg3 were the three regions used to assess the total intraspecific mt diversity.

Repetitive elements and comparative genomics. One 27-mer minisatellite repeated three times (located between the nad4 and nad4L genes), 186 SSRs and 51 mononucleotide repeats larger than seven nucleotides (mainly located in non-coding regions), were found in the mt genome of M. graminicola. The total nucleotide diversity between IPO323 and STBB1 was 0.16%. The two M. graminicola isolates differed by only 23 base substitutions, including fourteen transversions and nine transitions. These changes represented 0.05% of the entire mt genome. Twenty-two additional mutations were found between IPO323 and STBB1:18 were mononucleotide repeats of different lengths (9 poly-A and 9 poly-T), two were tetra- (AAAT) or penta- nucleotide microsatellite repeats (ATTTA), one was a frameshift mutation and the last was a 17-base deletion (Fig. 2). The nucleotide diversity among the global sample of 35 isolates was 35% greater than that between only IPO323 and STBB1 for the same three mitochondrial loci (Mg1, Mg2 and Mg3). Mg2 was the most variable locus, having 3 SNPs, a 17-bp indel, a polymorphic microsatellite with 2 alleles, and a mononucleotide repeat with 3 alleles. Mg1 had the fewest mutations, with two SNPs that were exclusive to isolates

37 Chapter 2 mtDNA of M. graminicola

collected from durum wheat (Triticum turgidum). Mg3 had a mononucleotide repeat with 2 alleles and 2 microsatellites, respectively with 2 and 4 alleles. All microsatellite alleles were due to differences in the number of repeats. The concatenated sequences of Mg1, Mg2, and Mg3 from all 37 isolates identified 14 haplotypes. If all mutations other than SNPs were excluded from the analysis, only three haplotypes were found (Table 1). If the increase of 35% in nucleotide diversity detected for the Mg loci is extrapolated to the total genome, it results in a value of 0.22% for mitochondrial nucleotide diversity in a global sample of 37

isolates representing most of the known mt variants. A haplotype network was inferred from all three Mg loci using the concatenated alignments (Fig. 3). The haplotype network did not show a clear pattern of geographical association; although isolates from North America were in the top half and all of those at the bottom were from Europe. Some frequent haplotypes such as H5, H6, and H7 included isolates of mixed origin, while others (H1, H11 and H13) were geographically limited. The M. graminicola haplotypes originating from durum wheat (Triticum turgidum ssp. durum) were distinguished from those originating from bread wheat (T. aestivum) by three SNPs. The two sequenced haplotypes (H5 and H9) represented different parts of the network. No evidence for recombination was found in the mtDNA of M. graminicola using the DnaSP program.

Table 3. Comparison of tRNAa gene clusters flanking the rnl gene in several ascomycetesa Class Accession Species 5'-upstream regionb,c rnl 3'-downstream regionb,c number A. niger Eurotiomycetes KGDS1WIS2P rnl TEVM1M2L1AFL2QM3H DQ207726 A. tubingensis Eurotiomycetes KGDS1WIS2P rnl TEVM1M2L1AF2QLM3H DQ217399 2 1 2 1 2 1 2 3 P. marneffei Eurotiomycetes RKG1G DS WIS P rnl TEVM M L AFL QM H AY347307 E. floccosum Eurotiomycetes KGDS1IWS2P rnl TEVM1M2L1AFL2QM3H AY916130 M. graminicola Dothideomycetes GDS1WIS2P rnl M1L1EAFL2YQM2HRM3 EU090238 L. muscarium Sordariomycetes GVISW*P rnl TE1M1M2L1E2FKL2QHM3 AF487277 V. dahliae Sordariomycetes KGDS*VW*R*P1*P2 rnl TE1M1M2L1AFL2QHM3 DQ351941 F. oxysporum Sordariomycetes VISWP rnl TEM1M2L1AFKL2QHM3 AY945289 M. anisopliae Sordariomycetes YDS1N*G*LIS2W rnl TE M1M2L1AFKL2QHM3 AY884128 a The tRNA gene order of listed organisms is based on Genbank sequences b The underlined tRNA genes showed rearrangement if compared to the consensus (bold) c Capital letters refer to tRNA genes for: R=arginine, K=lysine, G=glycine, D=aspartic acid, S=serine, W=tryptophan, I=isoleucine, P=proline, T=threonine, E=glutamic acid, V=valine, L=leucine, A=alanine, F=phenylalanine, Q=glutamine, H=histidine, Y=tyrosine, N=asparagine * Asterisk indicates where functional genes interrupt the tRNA genes sequence 123 The numbers indicate the presence of more tRNA genes for the same amino acid in the consensus sequences

38 Chapter 2 mtDNA of M. graminicola

Discussion

The mt genomes of two strains of the plant pathogenic fungus M. graminicola originating from different continents (Europe and North America) were sequenced completely, annotated and compared to identify polymorphisms. Both isolates had mt genomes belonging to RFLP haplotype 2 (Zhan et al. 2003; Table 1). The mtDNA of M. graminicola was circular and A+T biased like those of most other fungi (Table 2). These two M. graminicola sequences represent the first complete mt genomes of any species in the genus Mycosphaerella or from the branch of the fungal evolutionary tree that includes the Capnodiales, Dothideales, or Myriangiales (Schoch et al. 2006). Mycosphaerella and its related asexual genera (e.g., Cercospora, Septoria) comprise one of the largest and most economically important groups of pathogenic fungi (Goodwin et al. 2001) with several thousand species infecting virtually every major family of plants (Corlett 1991). Species of Mycosphaerella are not closely related to model fungi or those with completely sequenced mt genomes, so represent a previously unsampled branch of the fungal evolutionary tree. The mtDNA of M. graminicola contains genes for 14 inner mt membrane proteins involved in electron transport and coupled oxidative phosphorylation, as well as rnl, rns and RNA-Pol genes (Fig. 1). Except for presence of the RNA-Pol gene and absence of a gene encoding a putative ribosomal protein (rps5-like), this is the standard set of mtDNA-encoded genes found in other fungi. The rps5-like gene is found commonly in mt genomes of different fungal species and it was postulated that mtDNA-encoded rps5 was present in the common ancestor of fungal and animal mtDNAs (Bullerwell et al. 2000). As M. graminicola is one of the few ascomycetes known to be lacking rps5, the absence of this gene could indicate an independent loss in this species. A possible homolog of this gene was identified on scaffold 5 of the 8.9× draft genomic sequence of M. graminicola, so it may have been transferred to the nuclear genome rather than having been lost. Genes in the M. graminicola mtDNA had no introns, a finding that contrasts with other fungal mtDNAs that possess large introns containing intron-encoded proteins, as found in Podospora anserina (Cummings et al. 1990) and Penicillium marneffei (Woo et al. 2003). Eight orfs, with no obvious homology to any other sequenced genes present in the GenBank database, were found in the mt genome of M. graminicola. The functions of these putative

39 Chapter 2 mtDNA of M. graminicola

genes remain unclear, although some of them may represent highly diverged versions of known mtDNA-encoded genes, no longer recognizable by identity searches (Gray et al. 1998). EST databases provided evidence for transcription of orf5, orf6 and orf8, indicating that they may be expressed. Interestingly, these three orfs were the only ones of the eight that were located adjacent to tRNA genes, so possibly they may be transcribed along with the tRNAs but not translated. All tRNA secondary structures had the expected cloverleaf form, but particularly interesting were tRNA-Thr (UGU as anticodon) and tRNA-Phe (GAA as anticodon) because they had nine nucleotides in the anticodon loop instead of the canonical seven. This rare tRNA structure was described previously in Metarhizium anisopliae for tRNA-Thr and tRNA- Glu (Ghikas et al. 2006), and in Verticillium dahliae for tRNA-Thr, tRNA-Glu, tRNA-Arg and tRNA-Ser (Pantou et al. 2006). Nuclear genomes, including that of M. graminicola (Goodwin et al. 2007), possess SSRs that are known to be highly variable in terms of motif repeat number and distribution (Toth et al. 2000; Katti et al. 2001;). This study presents a similar picture for the mt genome of M. graminicola. SSRs and mononucleotide repeats may play a significant role in the regulation and evolution of the entire molecule. In nuclear genomes it was demonstrated that these highly variable tracts, if placed in promoter regions, could influence transcriptional activity (Kashi et al. 1997) and could play an important role in creating and maintaining quantitative genetic variation (Tautz et al. 1986; Kashi et al. 1997). In the mtDNA of M. graminicola, mononucleotide repeats became less common in coding regions as their length increased. Because most long mononucleotide repeats are located 5’-upstream of ATG start codons (Fig. 2), we hypothesize that they might play a role in regulating transcription. These tracts could be protein binding signals and, more precisely, upstream promoter elements, as demonstrated previously in nuclear genomes (Kashi et al. 1997). The intraspecific mt diversity was first assessed by comparing the total genome sequences of two isolates (STBB1 and IPO323), giving a nucleotide diversity of 0.16%. In order to assess species-wide variation, another 35 isolates were chosen, originating from five continents and belonging to four of the seven known RFLP haplotypes (Table 1). Using these additional isolates, the total mtDNA variation in M. graminicola was estimated to range from 0.16 to 0.22%, falling within the lower range of published intraspecific nucleotide diversities.

40 Chapter 2 mtDNA of M. graminicola

Figure 3. Phylogenetic relationships among Mycosphaerella graminicola mtDNA haplotypes inferred using a parsimony haplotype network. Haplotypes are presented as ovals with sizes proportional to the haplotype frequencies. Haplotypes containing isolates originating from durum wheat (Triticum turgidum ssp. durum) are grey. Open circles are hypothetical missing intermediate haplotypes. The completely sequenced haplotypes, H5 (IPO323) and H9 (STBB1), are indicated with bold text.

41 Chapter 2 mtDNA of M. graminicola

The nucleotide diversity would decrease to 0.12% if the 17-bp indel was excluded. This 17- bp indel appears to be a recent mutation that occurred during the 1970s (Torriani SFF, unpublished), suggesting that the M. graminicola mtDNA may be increasing in diversity following the hypothesized selective sweep (Zhan et al. 2003). Other examples of low intraspecific mtDNA nucleotide diversity based on complete mtDNA sequences were 0.2% for the olive fly Bactrocera oleae (Nardi et al. 2003) and 0.36% for Drosophila simulans (Ballard 2000). These results support earlier findings of low mt diversity in M. graminicola obtained by RFLP analysis (Zhan et al. 2003). While the haplotypic diversity based on sequences was higher than that found using RFLPs, the total nucleotide diversity remains the lowest reported to date in fungi. The greater number of haplotypes found through sequencing reflects the higher resolution of this method, especially the ability to resolve small indels that are missed by RFLP analysis (Fig. 3). In fact, if indels were removed from the sequence analysis and only SNPs were considered, only three mt haplotypes were found, but they did not always correspond with the RFLP data (Table 1). For example, isolates with RFLP haplotypes 1 and 2 were the most polymorphic and could have SNP haplotypes 1 or 3. Isolates with RFLP haplotype 3 always had SNP haplotype 1. It was interesting that isolates of M. graminicola adapted to durum wheat had unique RFLP and SNP haplotypes 4 and 2, respectively (Table 1). The nonrandom association between mitochondrial RFLP haplotypes and host species, presumably caused by natural selection operating on the mt genome, was noted previously in M. graminicola (Zhan et al. 2004) and other fungi (Gomes et al. 2000; Demanche et al. 2001). The intraspecific haplotype network (Fig. 3) that included all mutational events also distinguished between haplotypes originating from bread wheat and durum wheat. The contrasting genetic diversity among mt and nuclear genomes in M. graminicola (Zhan et al. 2003 and 2004) raises intriguing questions about the mechanisms leading to this phenomenon. At least two hypotheses can be proposed to account for the observed low levels of mt variation, including a lower mutation rate in the mt genome or a selective sweep. A comparison among the three yeast species Saccharomyces cerevisiae, Kluyveromyces lactis, and Candida glabrata showed that the frequency of nucleotide changes is higher in nuclear than in mt genomes (Clark-Walker 1991), which is the opposite of mammals where nuclear genes evolve slower than mt genes (Saccone et al. 2000). On the other hand, the low level of

42 Chapter 2 mtDNA of M. graminicola

polymorphism in the M. graminicola mtDNAs may have been generated through fixation of an advantageous mt mutation during a selective sweep. The selection of a favored mt haplotype leading to low levels of polymorphism was suggested in the oomycete Phytophthora infestans (Gavino and Fry 2002). The analysis of intraspecific diversity in the largely conserved mt genome of M. graminicola provides the basis for developing new tools essential to clarify the conflicting patterns of nuclear and mt diversity and to understand its cause. For example, the polymorphic microsatellites differed in numbers of 4- or 5-base repeats, making them amenable to agarose gel assays. These polymorphisms have already been used to analyze paternity in crosses (Ware 2006) and are now being used to analyze the evolution of resistance to strobilurin fungicides in M. graminicola (Chapter 5).

Acknowledgments

We gratefully acknowledge Marcello Zala for technical support and Charles Crane for bioinformatics analyses. DNA sequencing of isolate IPO323 was performed at the Department of Energy's Joint Genome Institute through the Community Sequencing Program (www.jgi.doe.gov/csp/). All sequencing data are public and may be accessed through http://www.jgi.doe.gov/Mgraminicola. This project was supported by the Swiss National Science Foundation (grant 3100A0-104145) and by USDA CRIS project 3602-22000-013- 00D.

43 Chapter 2 mtDNA of M. graminicola

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Kema GHJ, Verstappen ECP, Todorova M, Waalwijk C. 1996. Successful crosses and molecular tetrad and progeny analyses demonstrate heterothallism in Mycosphaerella graminicola. Curr Genet. 30:251-258. Kema GHJ, Verstappen E, van der Lee T, Mendes O, Sandbrink H, Klein-Lankhorst R, Zwiers L, Csukai M, Baker K, Waalwijk C. 2003. Gene hunting in Mycosphaerella graminicola. Proceedings of the 22nd Fungal Genetics Conference, Asilomar, California, USA Page 252. Kirk PM, Cannon PF, David JC, Stalpers JA. 2001. Ainsworth & Bisby´s Dictionary of the Fungi. 9th Ed., CAB International, Wallingford, UK. Krogh A, Larsson B, von Heijne G, Sonnhammer ELL. 2001. Predicting transmembrane protein topology with a hidden Markov model: Application to complete genomes. J Mol Biol. 305:567-580. Kudla J, Albertazzi FJ, Blazevic D, Hermann M, Bock R. 2002. Loss of the mitochondrial cox2 intron 1 in a family of monocotyledonous plants and utilization of the mitochondrial intron sequence for the construction of a nuclear intron. Mol Genet Genomics 267:223- 230. Kurdyla TM, Guthrie PAI, McDonald BA, Appel DN. 1995. RFLPs in mitochondrial and nuclear DNA indicate low levels of genetic diversity in the oak wilt pathogen Ceratocystis fagacearum. Curr Genet. 27:373-378. Lowe TM, Eddy SR. 1997. tRNAscan-SE: A program for improved detection of transfer RNA genes in genomic sequence. Nucleic Acids Res. 25:955-964. Liu YC, Cortesi P, Double ML, MacDonald WL, Milgroom MG. 1996. Diversity and multilocus genetic structure in populations of Cryphonectria parasitica. Phytopathology 86:1344-1351. Nardi F, Carapelli A, Dallai R, Frati F. 2003. The mitochondrial genome of the olive fly Bactrocera oleae: two haplotypes from distant geographical locations. Insect Mol Biol. 12:605-611. Pantou MP, Kouvelis VN, Typas MA. 2006. The complete mitochondrial genome of the vascular wilt fungus Verticillium dahliae: a novel gene order for Verticillium and a diagnostic tool for species identification. Curr Genet. 50:125-136.

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Price EW, Carbone I. 2005. SNAP: workbench management tool for evolutionary population genetic analysis. Bioinformatics 21:402-404. Rozas J, Sanchez-DelBarrio JC, Messeguer X, Rozas R. 2003. DnaSP, DNA polymorphism analyses by the coalescent and other methods. Bioinformatics 19:2496-2497. Saccone C, Gissi C, Lanave C, Larizza A, Pesole G, Reyes A. 2000. Evolution of the mitochondrial genetic system: an overview. Gene 261:153-159. Sanderson FR. 1972. A Mycosphaerella species as the ascogenous state of Septoria tritici Rob. and Desm. New Zeal J Bot. 10:707-710. Schoch CL, Shoemaker RA, Seifert KA, Hambleton S, Spatafora JW, Crous PW. 2006. A multigene phylogeny of the Dothideomycetes using four nuclear loci. Mycologia 98:1041-1052. Soanes DM, Talbot NJ. 2006. Comparative genomic analysis of phytopathogenic fungi using expressed sequence tag (EST) collections. Mol Plant Pathol. 7:61-70. Sommerhalder RJ, McDonald BA, Zhan J. 2007. Concordant evolution of mitochondrial and nuclear genomes in the wheat pathogen Phaeosphaeria nodorum. Fungal Genet Biol. 44: 764-772. Tambor JHM, Guedes RF, Nobrega MP, Nobrega FG. 2006. The complete DNA sequence of the mitochondrial genome of the dermatophyte fungus Epidermophyton floccosum. Curr Genet. 49:302-308. Tautz D, Trick M, Dover G. 1986. Cryptic simplicity in DNA is a major source of genetic variation. Nature 322:652-656. Templeton AR, Crandall KA, Sing CF. 1992. A cladistic analysis of the phenotypic associations with haplotypes inferred from restriction endonuclease mapping and DNA sequence data. III. Cladogram estimation. Genetics 132:619-633. Toth G, Gaspari Z, Jurka J. 2000. Microsatellites in different eukaryotic genomes: survey and analysis. Genome Res. 10:967-981. Ware SB. 2006. Aspects of sexual reproduction in Mycosphaerella species on wheat and barley: genetic studies on specificity, mapping, and fungicide resistance. Ph.D. thesis, Wageningen University, the Netherlands. Woo PCY, Zhen HJ, Cai JJ, Yu J, Lau SKP, Wang J, Teng JLL, Wong SSY, Tse RH, Chen R, Yang HM, Liu B, Yuen KY. 2003. The mitochondrial genome of the thermal

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dimorphic fungus Penicillium marneffei is more closely related to those of molds than yeasts. FEBS Lett. 555:469-477. Xia JQ, Correll JC, Lee FN, Ross WJ, Rhoads DD. 2000. Regional population diversity of Pyricularia grisea in Arkansas and influence of host selection. Plant Dis. 84:877-884. Zhan J, Kema GHJ, McDonald BA, 2004. Evidence for natural selection in the mitochondrial genome of Mycosphaerella graminicola. Phytopathology 94:261-267. Zhan J, McDonald BA. 2004. The interaction among evolutionary forces in the pathogenic fungus Mycosphaerella graminicola. Fungal Genet Biol. 41:590-599. Zhan J, Pettway RE, McDonald BA. 2003. The global genetic structure of the wheat pathogen Mycosphaerella graminicola is characterized by high nuclear diversity, low mitochondrial diversity, regular recombination and gene flow. Fungal Genet Biol. 38:286-297.

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50

CHAPTER 3

The evolutionary history of Mycosphaerella spp. mitochondrial genome

Stefano FF Torriani, Patrick C Brunner, Bruce A. McDonald. 2009. Evolutionary history of the mitochondrial genome in Mycosphaerella populations infecting bread wheat, durum wheat, and wild grasses. To be submitted.

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Abstract

Plant pathogens emerge in agro-ecosystems following different evolutionary mechanisms over different time scales. Previous analysis based on nuclear loci indicated that Mycosphaerella graminicola diverged from an ancestral population adapted to wild grasses during the process of wheat domestication approximately 10,500 years ago. Here we present a coalescence analysis based on four mitochondrial loci (total of 1338 bp) that dates the origin of M. graminicola to approximately 10,000 years before present, further supporting the hypothesis that Neolithic farmers shaped the evolution of the pathogen during the development of wheat agriculture. The previously proposed non-random association between mitochondrial genome haplotypes of M. graminicola and host-specific populations infecting bread wheat (Triticum aestivum) or durum wheat (Triticum durum) was reconsidered after the annotation of a 1935 bp putative gene exclusive to a mitochondrial DNA haplotype found at a higher frequency on durum wheat. The putative protein was predicted to have ligase activity. Ligases can act as virulence factors by manipulating host cellular pathways to overcome plant innate immunity. This could explain the increased pathogenicity on durum wheat of those mitochondrial haplotypes possessing this newly identified gene. Since this putative ligase gene could not be detected in M. graminicola ancestors we propose that it was introduced through horizontal gene transfer from a yet unknown donor organism.

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Introduction

Archeological (Childe 1953; Moore et al. 2000; Gopher et al. 2002) and genetic findings (Salamini et al. 2002) place the origins of agriculture in the Fertile Crescent of the Middle East between 10,000 and 12,000 years ago. The wild progenitors of the major Neolithic founder crops including wheat (Triticum spp.), barley (Hordeum vulgare) and pea (Pisum sativum) have been identified in this region (Diamond 1997; Haudry et al. 2007). The domestication of wild grasses was a slow process reflecting the gradual transition from a hunter-gatherer to an agriculture-based society. The continuous selection of desired morphological traits, like increased seed size, stiffness of the ear rachis and the ease of release of the seed, altered the wild progenitors into the crop species known today (Sharma and Waines 1980; Elias et al. 1996; Taenzler et al. 2002). Agricultural practices also modified the physical and biotic environment by altering natural ecosystems characterized by greater environmental heterogeneity, higher species diversity and lower host density into agro-ecosystems with greater environmental homogeneity, lower species diversity and higher host density (Stukenbrock and McDonald 2008). Natural ecosystems favor the evolution of generalist pathogens able to infect several host species. In contrast, agro-ecosystems characterized by extensive monoculture favor the evolution of host-specialized pathogens that have higher virulence (Anderson and May 1982). Agriculture played a significant role in selecting and spreading globally a number of pathogen species. At least four evolutionary mechanisms have been proposed by which pathogens emerged in agro-ecosystems over different time scales (Stukenbrock and McDonald 2008): 1) pathogen domestication along with the host (e.g. Mycosphaerella graminicola; Stukenbrock et al. 2007), 2) host shifts and host jumps (e.g. Magnaporthe oryzae; Couch et al. 2005), 3) horizontal gene transfer (e.g. Pyrenophora tritici-repentis; Friesen et al. 2006), and 4) hybridization (e.g. Phytophthora cambivora; Ioos et al. 2006). The impact of agricultural practices on the emergence of new pathogens can be inferred by dating the divergence time between pathogens on cultivated crops and their progenitors on wild plants. Up until now, very few studies have followed this approach, with a focus on plant pathogenic fungi and always using nuclear markers (Couch et al. 2005; Stukenbrock et al. 2007; Munkacsi et al. 2008; Zaffarano et al. 2008). These studies confirmed that the origins of some fungal plant pathogens, including M. graminicola and M.

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oryzae, coincided with the agricultural domestication of their host plant. M. graminicola emerged as a new pathogen adapted to wheat from an ancestral population infecting wild grasses in the Middle East during the process of wheat domestication around 10,500 years ago (Stukenbrock et al. 2007). The new pathogen was first distributed throughout Europe, during the spread of wheat cultivation approximately 5000-8000 years ago (McDonald et al. 1999; Banke et al. 2004). More recently (500 and 150 years ago, respectively), European colonists introduced it together with its host into the Americas and Australia (Banke and McDonald 2005). M. graminicola is one of the most important foliar pathogens of wheat and occurs globally across a wide range of climates (Polley and Thomas 1991; Eyal 1999). The life cycle includes both sexual and asexual stages, with the sexual ascospores having the potential to be blown over several kilometers (Sanderson 1972) and the asexual pycnidiospores disseminated over limited distances, mainly via rain-splash (Bannon and Cooke 1998). Disease management relies on breeding for resistance, fungicide applications and cultural practices (Parker and Lovell 2001; Russell 2005; Loyce et al. 2008). M. graminicola is characterized by high nuclear and low mitochondrial (mt) diversity in populations around the world (Zhan et al. 2003). High gene flow (Boeger et al. 1993), large effective population sizes (Zhan and McDonald 2004) and recurring sexual reproduction result in high observed nuclear diversity (Chen and McDonald 1996; Hunter et al. 1999). In contrast, Zhan et al. (2003) identified only seven mtRFLP haplotypes among a global collection of 1673 isolates, with the two most frequent (type 1 and type 3) characterizing approximately 93% of the isolates. Restriction mapping showed that differences among mtRFLP haplotypes were mainly insertion or deletion polymorphisms (indels). MtRFLP type 1 differed from mtRFLP type 2 by a 1.7 kb insertion, whereas mtRFLP type 4 differed from mtRFLP type 1 by a 3 kb insertion within the 1.7 kb insertion (Zhan et al. 2004). Torriani et al. (2008) completely sequenced two mtRFLP type 2 genomes and estimated, using thirty-five globally selected samples from four different mtRFLP types, an intraspecific nucleotide diversity of 0.22% for M. graminicola, which is one of the lowest values reported until now in any organism. A selective sweep affecting only the mt genome was proposed to explain the high nuclear and low mt diversity (Zhan et al. 2004). Previous studies revealed a nonrandom association between both mtRFLP (Zhan et al. 2004) or mt sequence haplotypes (Torriani et al. 2008)

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and host species of origin. MtRFLP type 4 isolates were collected only from durum wheat (Triticum turgidum) and never detected on isolates from bread wheat (Triticum aestivum). Because only minor genetic differences were found in the nuclear genome between populations collected from durum- and bread wheat, it was hypothesized that natural selection acted on host-specific (i.e. durum- wheat-adapted) mt haplotypes such as mtRFLP type 4 (Zhan et al. 2004). The first aim of this study was to infer the evolutionary history of M. graminicola using sequence data from four mt loci. Pathogen populations closely related to M. graminicola, collected from wild grasses at the center of origin (Stukenbrock et al. 2007), were added to the analyses to obtain a more complete picture. The second goal was to characterize the indel polymorphisms distinguishing the different mtRFLP types and in particular a 3 kb insertion exclusive to mtRFLP haplotype 4 proposed to increase the parasitic fitness on durum wheat.

Materials and methods

Fungal Isolates. M. graminicola isolates collected from locations in Asia, Europe, Africa, North and South America were obtained from infected leaves sampled from both bread and durum wheat. Closely related fungal pathogens in the genus Mycosphaerella were collected from uncultivated grasses of three different genera, Agropyron repens, Dactylis glomerata and Lolium multiflorum in the northwestern Iranian province Ardabil. Additionally, we included four isolates of Septoria passerinii, a closely related barley pathogen collected from H. vulgare (Table 1). Pathogen isolation and DNA extraction were performed as previously described (Linde et al. 2002; Zhan et al. 2003 and 2004). Most of the populations were previously described using nuclear (McDonald et al. 1999; Linde et al. 2002; Banke et al. 2004; Stukenbrock et al. 2007) and mt markers (Zhan et al. 2003 and 2004; Torriani et al. 2008 and 2009).

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Table 1. Pathogen populations included in this study Sampling Pathogen Isolates Population Location Continent Host Plant Year strategy1 Collectors Mycosphaerella Spp. 2 Iran 1 Ardabil Asia Lolium multiflorum 2004 Random Javan-Nikkhah M (S1 and S2) 2 Iran 2 Ardabil Asia Dactylis glomerata 2004 Random Javan-Nikkhah M 6 Iran 3 Ardabil Asia Lolium multiflorum 2004 Random Javan-Nikkhah M 4 Iran 4 Ardabil Asia Agropyron repens 2004 Random Javan-Nikkhah M 3 Iran 5 Ardabil Asia Lolium multiflorum 2004 Random Javan-Nikkhah M Mycosphaerella 20 Israel Sa'ad Asia Triticum aestivum 1992 Transect Yarden O graminicola 1 Syria Syria Asia Triticum turgidum 1995 Random Kema GHJ 18 Iran Mehran Asia Triticum aestivum 2001 Random Javan-Nikkhah M 8 England England Europe Triticum aestivum 1992 Transect Shaw C, Pjils C 9 Denmark Abed Europe Triticum aestivum 1994 Hierarchy Rasmussen M 8 Switzerland Hubersdorf Europe Triticum aestivum 1999 Hierarchy McDonald BA 6 United States 1 Oregon America Triticum aestivum 1990 Hierarchy Boeger J2 5 United States 2 Indiana America Triticum aestivum 1993 Hierarchy Shaner G 8 Uruguay Colonia America Triticum aestivum 1993 Hierarchy Diaz de Ackermann R 5 Algeria 1 Algeria Africa Triticum turgidum 1992-94 Random Kema GHJ 1 Algeria 2 Algeria Africa Triticum aestivum 1992-94 Random Kema GHJ 2 Tunisia 1 Tunisia Africa Triticum turgidum 1992-94 Random Kema GHJ 10 Tunisia 2 Tunisia Africa Triticum aestivum 2008 Mixed Boukef S 21 Tunisia 3 Tunisia Africa Triticum turgidum 2008 Mixed Boukef S Septoria passerinii 4 United States 3 N. Dakota America Hordeum vulgare 1995 Random Long D

1 Mixed sampling strategy included both isolates collected randomly and hierarchical. 2 and McDonald BA, Schmitt M

Polymerase Chain Reaction and Sequencing. Amplifications of the previously described mtDNA loci Mg1, Mg2 and Mg3 (Torriani et al. 2008 and 2009) from Mycosphaerella spp. isolates collected from uncultivated grasses were unsuccessful. Therefore, other mtDNA regions were screened to develop four new mtDNA loci, Mg4, Mg5, Mg6 and Mg7. Mg4 partially amplified nad5, Mg5 amplified the large ribosomal subunit (rnl), while Mg6 and Mg7 were located 3’downstream of rnl in a region containing tRNA- genes with a gene order found to be conserved interspecifically (Tambor et al. 2006; Torriani et al. 2008). All isolates were amplified using the following primers: Mg4F (5’-AAC ACT AAG TCT GTC ACG TAT CTG-3’) and Mg4R (5’-CCC TTC ATG ACA GGT TTC TAC TC-3’); Mg5F (5’-TTA ATC TAT TCA GTT ATA ATT C-3’) and Mg5R (AGT CGT ACC CTT CAT GAT TCC T-3’); Mg6F (5’-GAG CTA GCA CCG TTC TTA TAA ATG’-3) and Mg6R (5’- AAA GAT CGG TGA GCC GTT AC-3’); Mg7F (5’-AAA CGG AGG TAA CGG CTC AC-3’) and Mg7R (5’- GAT TAT CTT GTG GGC ATT GGT C-3’). PCR reactions were carried out in 20 µl volumes containing 2 µl of 10x PCR buffer (1x PCR buffer: 10 mM

KCl, 10 mM (NH4)2SO4, 20 mM Tris-HCl, 2 mM MgSO4, 0.1% Triton X-100, [pH 8.8]), 0.1

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mM of each dNTP, 10 pmol of each primer, 1 U of Taq DNA Polymerase (New England Biolabs, England) and 4 µl of genomic DNA (5 to 10 ng final DNA concentration). Thermal cycling conditions included initial denaturation at 96°C for 2 min followed by 35 cycles of 96°C for 1 min, 53°C for 90 sec, 72°C for 1 min. Finally, a 5 min PCR extension was carried out at 72°C. The PCR products were sequenced using the primers Mg4R, Mg5F, Mg6F and Mg7F. A total of 1338 bp was sequenced from each isolate, 483 bp for Mg4, 318 bp for Mg5, 156 bp for Mg6 and 381 bp for Mg7. Sequencing reactions were performed using the ABI PRISM BigDye Terminator v3.0 ready reaction cycle sequencing kit (Applied Biosystems, Foster City, CA). Sequencing reactions were in a final volume of 10 µl using 10 pmol of primer, 2 µl BigDye reaction mix, previously diluted 1:4 and 4 µl of purified PCR products. The cycling profile was: 10 sec denaturation at 95°C, 5 sec annealing at 50°C and 4 min extension at 60°C for 100 cycles. All sequences were aligned and edited manually with Sequencer 4.5 (Gene Codes Corporation, Ann Arbor, MI) using the Pezizomycotina genetic code that diverged from the standard nuclear code for codon TGA, which was read as Trp and not as Stop.

Mt RFLP polymorphism analysis. The M. graminicola mt genomic region including the indel polymorphisms characterizing the different mtRFLP haplotypes was identified by comparing Southern blots described in Zhan el al. (2003) and the recently released complete mtDNA sequence (EU090238; Torriani et al. 2008). Primers Mgvar1F and Mgvar1R (Table 2) were used to amplify the mt indel polymorphic region (Fig. 1) from three mtRFLP types (type 1, type 2 and type 4). MtRFLP types 1 and 3 were identical at this locus so only type 1 was analyzed. The reactions were in a total volume of 25 µl containing 2.5 µl of 10x long

PCR buffer with 15 mM MgCl2, 0.2 mM of each dNTP, 10 pmol of each primer, 1 U of long PCR enzyme mix (containing a Taq DNA Polymerase and a second thermostable polymerase that exhibits 3’-5’ exonuclease activity; Fermentas, Switzerland) and 5 µl of genomic DNA (5 to 15 ng final DNA concentration). The thermal cycling conditions were: initial denaturation at 94°C for 2 min followed by 10 cycles of 15 sec denaturation at 94°C, 30 sec annealing at 60°C, 5 min extension at 68°C and 20 cycles with same profile but with 15 sec more extension. Finally, a 10 min PCR extension was carried out at 68°C. The obtained PCR amplicons were completely sequenced by primer walking using primers listed in Table 2. The

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open reading frame unique to mtRFLP type 4 (mtRFLP4-ORF) was translated and screened for similarity using the BlastP tool provided by the NCBI database (Altschul et al. 1990) and tested for the presence of transmembrane domains with the TMHMM2 method (Krogh et al. 2001). The program ProtFun 2.2 (Jensen et al. 2002) was used to assess the putative function of mtRFLP4-ORF encoded protein. ProtFun 2.2 produces ab initio prediction of protein functions from amino acid sequences using a large number of other feature prediction servers, most of them available online on the homepage of the Technical University of Denmark (http://www.cbs.dtu.dk). All isolates were tested for the presence/absence of mtRFLP4-ORF by multiplex PCR using the Mg-loci settings described above and two pairs of primers, Mgvar6F and Mgvar6R specific for mtRFLP4-ORF and Mg5F and Mg5R as a control for the method. The amplicons were 397 bp and 562 bp, respectively.

Table 2. 5’-3’ sequence of primers used for sequencing the indels characterizing the mtDNA RFLP types of Mycosphaerella graminicola. Primer name Sequence (5'-3') Size (bp) RFLP-typesa Mgvar1F ATACTAGCACTGGCTCCGTTTC 22 1, 2, 3, 4 Mgvar2F AACGCCCTTACTACAAGACGTG 22 1, 3, 4 Mgvar3F CCTAATTCCTTGTATTCCCTTTCC 24 4 Mgvar4F TGTATTACACTGAGATGCGTTGC 23 4 Mgvar5F AGGAGAACTTCGCAAGAATAGC 22 4 Mgvar6F TGACGTAATCAATCATCTGAGG 22 4 Mgvar1R ATACCCACACCTTTACCCAGAG 22 1, 2, 3, 4 Mgvar2R GGTGGTGCAGAATTTCCATTAG 22 1, 3, 4 Mgvar3R TGAGCAACATCTCTAGGACGAG 22 1, 3, 4 Mgvar4R TTCATCGCAAGAGATAGCAAAC 22 1, 3, 4 Mgvar5R AAGGTCCTCGACCAAACCTATC 22 4 Mgvar6R CAGGTGGGACAGTGTCATGTAG 22 4 a The mitochondrial RFLP-haplotypes that the primer can bind (only type 1-4 are considered)

Haplotype Network. To determine the phylogenetic relationships among the Mycosphaerella populations collected from T. aestivum, T. durum, L. multiflorum, D. glomerata and A. repens, the concatenated sequences of Mg4, Mg5, Mg6 and Mg7 were analyzed using the program TCS 1.21 (Clement et al. 2000). All indels and infinite site violations were removed prior to using the program SNAP Workbench (Price and Carbone 2005). TCS 1.21 infers an unrooted cladogram (Fig. 2) applying a statistical parsimony method based on Templeton’s 95% parsimony connection limit (Templeton et al. 1992).

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Coalescent analysis. The ancestral history of the mt genome in Mycosphaerella populations infecting bread wheat, durum wheat and wild grasses was inferred by coalescent- based genealogy using SNAP Workbench (Price and Carbone 2005). The concatenated (Mg4, Mg5, Mg6 and Mg7) DNA sequences were collapsed into haplotypes using the program SNAP map (Aylor et al. 2006) by excluding indels and removing infinite site violations. To detect incompatibility among segregating sites, an incompatibility matrix was generated in SNAP Clade and SNAP Matrix (Markwordt et al. 2004), and conflicting sites were removed manually. The M. graminicola populations were considered as one panmictic population because of the high gene flow operating between geographic populations in this species (Boeger et al. 1993; Zhan et al. 2003). The coalescent analysis was run using four subdivided lineages, including S. passerinii, M. graminicola and the Mycosphaerella populations S1 and S2 adapted to uncultivated grasses, as described in Stukenbrock et al. (2007). A migration matrix was generated with the program MIGRATE (Beerli and Felsenstein 2001) and used as the backward migration matrix for ancestral inference, using population subdivision in the program GENETREE (Griffiths and Tavaré 1994) as implemented in the SNAP workbench. The genealogy with the highest root probability was determined by performing 500,000 simulations of the coalescent with five different starting random number seeds. The tree with highest root probability was selected showing the distribution of mutations along the branches of the pathogen populations (Fig. 3). To compare dates of divergence with previously published data, the relative coalescence time scale was calibrated at the separation of S. passerini from Mycosphaerella spp. by assuming a divergence time of 68,500 years bp, as reported in Stukenbrock et al. (2007) using nuclear markers. The nuclear coalescence time was calculated using mutation rates from six loci and 360 individuals (Stukenbrock et al. 2007).

Results

One hundred twenty-two M. graminicola isolates from four continents, collected from T. aestivum (93) and T. durum (29), seventeen from Mycosphaerella spp. adapted to uncultivated grasses L. multiflorum (11), D. glomerata (2) and A. repens (4) as well as four S.

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passerinii isolates from H. vulgare were successfully sequenced and included in the analysis (Table 1).

Figure 1. Characterization of the indels distinguishing between the mitochondrial RFLP haplotypes. Orf3 and nad2 gene flank the indel polymorphic region respectively on the left and on the right (dark gray). The diagram encloses a 6 kb long mitochondrial region. If compared with type 2, type 1 and type 4 present respectively insertions of 1777 bp and 4788 bp. Type 4 presents an uninterrupted ORF of 2607 bp, containing the type-4 specific putative gene (1935 bp, dark gray) and a region of 200 bp with cox1 homology (black block 1). Black blocks 2 and 3 had homology with nad2 gene. Vertical soft gray bars (A, B, C) represent three highly conserved regions in type 4 sequence. The two-hatched horizontal bars represent a prolonged homology found only in conserved regions A and C. The two-pointed blocks are an additional homology. The lines above the diagram are the 50 longer repeated sequences found using the program REPuter.

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Haplotype Network. The parsimony haplotype network was inferred from the compatible sequence alignment of the four sequenced loci (Mg4-Mg7) excluding indels and infinite violation sites. The 143 isolates collapsed into six distinct haplotypes, two for both M. graminicola and S2 (S2a, S2b), and one each for S1 and S. passerinii (Fig. 2). Four major evolutionary groups were identified; S. passerinii, M. graminicola, S1 and S2, consistent with previous results based on nuclear sequences (Stukenbrock et al. 2007). The number of mutational events between S. passerinii and S2 was 31, between S1 and M. graminicola nine and between S2 and M. graminicola three. The most frequent M. graminicola haplotype, representing more than 99% of all isolates, included samples collected from both durum and bread wheat, with all isolates sampled from durum wheat collapsing into this haplotype. The haplotype network showed that S1 could infect three different hosts (L. multiflorum, D. glomerata and A. repens), whereas S2 was restricted to L. multiflorum (Fig. 2).

Figure 2. Parsimony haplotype network for the concatenated loci (Mg4, Mg5, Mg6 and Mg7). Haplotypes are presented as circle with sizes proportional to the haplotype frequencies; numbers in parenthesis refer to isolates enclosed in that haplotype. Different colors indicate the hosts from which the isolates were sampled. Dots are hypothetical missing intermediate haplotypes.

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Coalescent analysis. The Program Genetree was used to provide coalescent-based genealogies to differentiate between ancestral and descendent populations and to infer the evolution of polymorphisms among haplotypes (Fig. 3). The analysis included 48 informative polymorphic sites, which gave good resolution identifying the same six clades obtained in the parsimony haplotype network (Fig. 2). A transversion from adenine to guanine separated S2 from S1 and, more recently, a transition from thymine to cytosine separated S1 from M. graminicola (mutation numbers 25 and 1 respectively in Fig. 3). The S2 clade separated earlier than S1 from M. graminicola. S1 was the clade that accumulated the most mutations after the split from M. graminicola. S. passerinii separated at the deepest point in the genealogy, suggesting a more ancient divergence from the other three Mycosphaerella clades. One isolate from Denmark didn’t cluster with other M. graminicola isolates in the same clade. After converting the coalescence time to real time by calibrating the separation between S. passerini and Mycosphaerella spp. at 68,500 years ago (Stukenbrock et al. 2007), we found that S2 diverged approximately 22,000 years ago and M. graminicola emerged as a new pathogen about 10,000 years BP.

MtRFLP haplotype analysis. The indel polymorphic region of M. graminicola mtDNA characterizing the different mtRFLP haplotypes (Zhan et al. 2003 and 2004) was amplified, sequenced and analyzed for three different mtRFLP types, in order to include more than 90% of the global mtRFLP haplotypic diversity (Zhan et al. 2003). The amplifications resulting from mtRFLP types 1, 2 and 4 were respectively 2,495 bp, 719 bp and 5,506 bp in size. MtRFLP types 1 had an insertion of 1,776 bp compared to type 2; type 4 differed from type 1 by a 3,011 bp insertion (Fig. 1). The MtRFLP type 4 carried a unique insertion containing a 2,607 bp ORF displaying two stretches of 175 bp and 200 bp, showing homology respectively to nad2 (93% identity, e-value of 9e-66; black block 1 in Fig. 1) and cox1 (99% identity, e-value of 6e-98; black block 2 in Fig. 1). The mtRFLP type 4 insertion also had 122 nucleotides with nad2 similarity (85% identity, e-value of 1e-30; black block 3 in Fig. 1), repeated within a longer nad2-homologous stretch (639 bp, 93% identity and e-value of 0; black block 4 in Fig. 1) present in both mtRFLP type 1 and type 4, but absent in mtRFLP type 2 (Fig 1). Within the mtRFLP type 4 insertion a putative gene of 1,935 nucleotides was identified, composed of 32% A, 33% T, 19% G and 16% C, with an AT-content of 65%. The

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translation of the putative gene gave rise to a 644 amino acid protein with no specific match against NCBI database sequences, but with a theoretical isoelectric point of 5.15 and an estimated molecular weight of 74 KDa. The predicted protein displays three putative transmembrane domains at positions 22-44, 29-81 and 97-119, five putative N-glycosylated sites, one putative O-glycosylated site, 37 putative phosphorylation sites and it was hypothesized to follow the secretory pathway. Based on the amino acid sequence, the protein was predicted to have a ligase function. A region approximately 435 bp long was found repeated three times (A-, B-, C-repeats; soft grey bars Fig. 1) in mtRFLP type 4, always flanking a putative indel insertion/excision site. MtRFLP types 1 and 2 had two and one copies of this repeat, respectively. The A-, B- and C-repeats had a total nucleotide diversity of 16%. The A- and C-repeats showed a 153 bp extended homology not found in the B-repeat (91% identity, e-value of 2e-50; hatched horizontal bars Fig. 1). All isolates were screened for the presence of mtRFLP4-ORF using a multiplex PCR approach. MtRFLP4-ORF was not found in Mycosphaerella isolates sampled from the uncultivated grasses (A. repens, D. glomerata, L. multiflorum), nor in S. passerinii collected from H. vulgare. 29% of the tested M. graminicola isolates possessed the mtRFLP4-ORF, including 93% of isolates sampled from durum wheat and 9% from bread wheat. All mtRFLP4-ORF containing isolates from bread wheat were limited to a single North African population (Tunisia 2, Table 1), where it occurred at a frequency of 80%. Samples containing mtRFLP4-ORF were found in all populations of T. turgidum.

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Figure 3. Coalescent-based genealogy of the combined mitochondrial loci Mg4, Mg5, Mg6, Mg7 showing the distribution of mutations in Mycospharella graminicola, Mycosphaerella S1 and S2 and Septoria passerinii. The split between M. graminicola and S1 was fixed at 10,500 (Stukenbrock et al. 2007) and used to convert the coalescence scale to real time. The number of isolates represented in each branch is shown below the tree. Time scale is given on the right from the past (top) to the present (bottom).

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Discussion

Here we report the first analysis of the evolutionary history of the M. graminicola mt genome. Earlier studies considered the low mtDNA variability and the nonrandom association between mtRFLP haplotypes and host species (Zhan et al. 2003 and 2004; Torriani et al. 2008). The obtained mt coalescence analyses provided an overview of the divergence of Mycosphaerella populations since the split from S. passerinii, dated to approximately 68,500 years ago. Mt coalescence supported nuclear analyses showing S. passerinii branching at the deepest point of the coalescence, indicating that the separation between the wheat pathogen M. graminicola and barley pathogen S. passerinii took place before the domestication of their hosts. Mitochondrial and nuclear coalescence analyses provided congruent results, indicating that both genomes shared the same evolutionary history and reinforcing the hypothesis that M. graminicola emerged as a new pathogen during the process of wheat domestication about 10,000 years ago in the Fertile Crescent from an ancestral species able to infect several uncultivated hosts. Many archeological studies have reported on the profound changes in Mesopotamia and other Neolithic cultures after the beginning of agriculture and the related intensive selection and cultivation of selected crop genotypes (Moore et al. 2000; Gopher et al. 2002). By selecting plants for agricultural purposes Neolithic farmers not only altered the natural environment by creating agro- ecosystems, they also changed host-pathogen interactions (Stukenbrock and McDonald 2008), shaping the evolution of pathogen populations and giving rise to “modern” plant pathogen species, such as M. graminicola. Other pathogens thought to have been domesticated along with their hosts are M. oryzae on rice (Couch et al. 2005), Phytophthora infestans on potatoes (Gomez-Alpizar et al. 2007) and Ustilago maydis on maize (Munkacsi et al. 2008). For the first time we identified M. graminicola isolates from bread wheat belonging to mtRFLP type 4. In previous surveys mtRFLP type 4 isolates were found only infecting durum wheat (Zhan et al. 2004; Torriani et al. 2008). All mtRFLP type 4 isolates from bread wheat belonged to the same Tunisian population. Tunisian cereal production is characterized by a significantly higher production of durum wheat than bread wheat (Ben Salem et al. 1995). MtRFLP type 4 isolates could have increased in frequency through selection in durum

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wheat fields, possibly due to higher pathogenicity on durum wheat conferred by mtRFLP4- ORF, and subsequently spread into surrounding fields of bread wheat. Even though other mtRFLP types may have higher fitness on bread wheat, the higher number of mtRFLP type 4 spores produced in the more common durum wheat fields may have allowed this haplotype to become locally more frequent on bread wheat. Durum wheat has been grown on a large scale for a long time in Tunisia. Since both wild relatives and domesticated wheat co-occur (Medini et al. 2005), the introduction of the mtRFLP4-ORF into the mt genome of M. graminicola could have taken place in this region. The coalescent analysis was not able to distinguish mtRFLP4-ORF containing isolates from the others. Additionally, the mtRFLP4- ORF was not found in S1 and S2, indicating the absence of this putative gene in M. graminicola ancestors and suggesting a recent insertion event. Since horizontal gene transfer (HGT; also known as lateral gene transfer) has already been demonstrated to promote the development of new functions or increased virulence in recipient lineages (De la Cruz and Davies 2000; Friesen et al. 2006; Keeling and Palmer 2008), we hypothesize that HGT may have introduced mtRFLP4-ORF into M. graminicola mtDNA. HGTs often take place among prokaryotes; leading to the acquisition of genes conferring antibiotic resistance (De la Cruz and Davies 2000). Prokaryote to eukaryote transfers have also been found, e.g. an ancestor of Saccharomyces cerevisiae received a gene encoding the enzyme dihydroorotate dehydrogenase making the yeast facultatively anaerobic (Hall et al. 2005). Recently, Friesen et al. (2006) demonstrated that a gene (ToxA) encoding a critical virulence factor was laterally transferred from one fungal species to another, showing that HGT can occur between fungi. HGT can introduce exogenous genetic material through symbiotic relationship between prokaryotes and eukaryotes or by viral transfection (Gogarten 2003). A third possible mechanism (specific to fungi) involves conidial anastomosis tubes forming between two fungal species that regularly come into close contact (Friesen et al. 2006). Because no similarity was found with any NCBI deposited sequences, a possible donor could not be identified, even though the high A+T content of mtRFLP4-ORF (65%) suggests a mt origin, since this is one of the distinctive feature of these genomes (Campbell et al. 1999). The presence of the three 435 bp long repeats (A-, B-, C-repeat) flanking the insertion/excision sites of indels, characterizing the different mtRFLP types, indicates that the RFLP polymorphism at this locus was produced by two mutational events (Fig. 1).

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MtRFLP4-ORF was predicted to have ligase function, a result that if confirmed would find support in the literature. It was already noticed that different pathogen virulence factors having ligase activity can enable pathogens to manipulate the proteasome-mediated degradation of proteins in their hosts to promote disease by removing specific host proteins (Huang et al. 2004, Angot et al. 2007; Speth et al. 2007). We postulate that the increased pathogenicity of mtRFLP type 4 isolates to durum wheat could be due to the introgression of the mtRFLP4-ORF that encodes a protein acting as a virulence factor.

Acknowledgments

We gratefully acknowledge Marcello Zala for technical support and Stephen Goodwin for generously providing isolates from Septoria passerinii. This project was supported by the Swiss National Science Foundation (grant 3100A0-104145). DNA sequencing was conducted using the facilities of the Genetic Diversity Center at ETH Zurich.

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References

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74

CHAPTER 4

The mitochondrial genome of Phaeosphaeria nodorum

Torriani’s contribution to the publication “Hane et al. (2007)” was the complete annotation of the mitochondrial genome and related analysis.

James K Hane, Rohan GT Lowe, Peter S Solomon, Kar-Chun Tan, Conrad L Schoch, Joseph W Spatafora, Pedro W Crous, Chinappa Kodira, Bruce W Birren, Stefano FF Torriani, Bruce A McDonald, Richard P Oliver. 2007. Dothideomycete-Plant interactions illuminated by genome sequencing and EST analysis of the wheat pathogen Stagonospora nodorum. The Plant Cell 19:3347-3368.

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Abstract

Stagonospora nodorum is a major necrotrophic fungal pathogen of wheat (Triticum aestivum), and a member of the Dothideomycetes, a large fungal taxon that include many important plant pathogens affecting major crop plant families. Here, we report the acquisition and initial analysis of a draft genome sequence for this fungus. The assembly comprises 37,164,227 bp of nuclear DNA contained in 107 scaffolds. The circular mitochondrial genome comprises 49850 bp encoding 46 genes including four that are intron-encoded. The nuclear genome assembly contains 26 classes of repetitive DNA comprising 4.5% of the genome. Some of the repeats show evidence of repeat-induced point mutations consistent with a frequent sexual cycle. ESTs and gene prediction models support a minimum of 10,762 nuclear genes. Extensive orthology was found between the polyketide synthase family in S. nodorum and Cochliobolus heterostrophus, suggesting an ancient origin and conserved functions for these genes. A striking feature of the gene catalogue was the large number of genes predicted to encode secreted proteins; the majority has no meaningful similarity to any other known genes. It is likely that genes for host-specific toxins, in addition to ToxA, will be found amongst this group. ESTs obtained from axenic mycelium grown on oleate (chosen to mimic early infection) and late-stage lesions sporulating on wheat leaves were obtained. Statistical analysis shows that transcripts encoding proteins involved in protein synthesis and in the production of extracellular proteases, cellulases and xylanases predominate in the infection library. This suggests that the fungus is dependant on the degradation of wheat macromolecular constituents to provide the carbon skeletons and energy for the synthesis of proteins and other components destined for the developing pycnidiospores.

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Introduction

Stagonospora (syn. Septoria) nodorum (Berk.) Castell. & Germano [teleomorph Phaeosphaeria (syn. Leptosphaeria) nodorum (Müll.) Hedjar] is a major pathogen of wheat (Triticum aestivum) in most wheat-growing areas of the world. It is the major cause of losses due to foliar pathogens in Western Australia and north central and north eastern North America (Solomon et al. 2006a) and until the 1970s, it was the major foliar necrotrophic pathogen in Europe (Bearchell et al. 2005). Infection begins when spores (ascospores or asexual pycnidiospores) land on leaf tissue (Bathgate and Loughman 2001; Solomon et al. 2006b). The spores rapidly germinate to produce hyphae which invade the leaf, utilising hyphopodia to gain entry to epidermal cells or by growing directly through stomata (Solomon et al. 2006b). The hyphae rapidly colonise the leaves and begin to produce pycnidia in 7-10 days. The infection has been divided into three metabolic phases (Solomon et al. 2003a). The first phase is penetration of the host epidermis and is fuelled predominantly by lipid stores in the spores (Solomon et al. 2004a); the second is proliferation throughout the interior of the leaf, involves toxin release (Liu et al. 2006) and uses host-derived simple carbohydrate sources (Solomon et al. 2004a); the final phase produces the new spores, but so far the metabolic requirements for pycnidiation are unclear. The infection epidemiology follows a polycyclic pattern with repeated cycles of both asexual (Bathgate and Loughman 2001) and sexual (McDonald unpublished data) infection throughout the growing season. New rounds of infection are initiated by rain-splash of pycnidiospores and wind dispersal of ascospores. Eventually, wheat heads become infected, causing the glume blotch symptom. In Mediterranean climates, the fungus over-summers in senescent straw and stubble. Seed transmission can be important but is readily controlled by fungicides. Infected stubble harbours the pseudothecia that produce airborne (Bathgate and Loughman 2001), heterothallic (Bennett et al. 2003) ascospores to reinitiate the infection in the following growing season. Epidemiological and population genetic evidence suggest the fungus undergoes meiosis in the field regularly and that gene flow is global (Stukenbrock et al. 2006). S. nodorum is a member of the Dothideomycetes class of filamentous fungi. This is a newly recognised major class that broadly replaced the long-recognized loculoascomycetes

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(Winka and Eriksson 1997) and includes the causal organisms of many economically important plant diseases; notable examples are black leg (Leptosphaeria maculans), southern corn leaf blight (Cochliobolus heterostrophus), barley net blotch (Pyrenophora teres), apple scab (Venturia inaequalis), black sigatoka of banana (Mycosphaerella fijiensis), wheat leaf blotch (M. graminicola), tomato leaf mould (Passalora [syn. Cladosporium] fulva) and Ascochyta blight of many legume species (Ascochyta spp.). The taxon also includes large numbers of saprobic species occurring on substrates ranging from dung to plant debris, a few species associated with animals and several lichenized species (Del Prado et al. 2006). Many plant pathogens in this group produce host-specific toxins (Wolpert et al. 2002). These molecules interact with specific host factors to produce disease symptoms only in selected genotypes of specific plant hosts. Well-known examples are found in Alternaria Alternata, Cochliobolus heterostrophus and P. tritici-repentis, while species in the genera Mycosphaerella, Corynespora and Stemphylium are also thought to produce host-specific toxins (Agrios 2005). Proteinaceous host-specific toxins have recently been shown to be important virulence determinants in S. nodorum (Liu et al. 2004a and 2004b) including one whose gene is thought to have been interspecifically transferred to the wheat tan spot pathogen, P. tritici-repentis (Friesen et al. 2006). Only one example of a host-specific toxin has been identified outside of the Dothideomycetes (Wolpert et al. 2002). Non-host specific toxins produced by species in this group include cercosporin (Cercospora) and solanopyrone (Ascochyta) but are also produced by many other fungal taxa (Agrios 2005). S. nodorum is an experimentally tractable organism, which is easily handled in defined media, was one of the first fungal pathogens to be genetically manipulated (Cooley et al. 1988) and has been a model for fungicide development (Dancer et al. 1999). Molecular analysis of pathogenicity determinants is aided by facile tools for gene ablation and rapid in vitro phenotypic screens and thus far, a small number of genes required for pathogenicity have been identified (Cutler et al. 1998; Cooley et al. 1999; Bailey et al. 2000; Bindschedler et al. 2003; Solomon et al. 2003b, 2004a, 2004b; Solomon and Oliver 2004; Solomon et al. 2005 and 2006a). It has thus emerged as a model for dothideomycete pathology. Whole genome sequences have been described for a handful of fungal saprobes and pathogens (Galagan et al. 2003; Jones et al. 2004; Dean et al. 2005; Galagan et al. 2005; Kamper et al. 2006). Here, we present an initial analysis of the genome sequence of S.

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nodorum, the first dothideomycete genome sequence to be publicly released. Gene expression studies using EST libraries from axenic mycelium and heavily infected wheat leaves complement the genome sequence and provide the first broad-based analysis of the genomic basis of infection by S. nodorum.

Materials and Methods

Fungal Strains. Stagonospora nodorum strain SN15 (Solomon et al. 2003b) was used for both genome and EST libraries and has been deposited at the Fungal Genetics Stock Center. The genome sequence was obtained as described (http://www.broad.mit.edu/annotation/ genome/ stagonospora_nodorum/Assembly.html). The sequences are available for download from GenBank under accession number AAGI00000000.

Phylogenetic Analysis. A combined matrix of 41 taxa was generated from DNA sequences obtained from two ribosomal (nuclear large and small subunit [nuc-LSU and nuc- SSU]) and three protein genes (elongation factor 1 a [EF-1α] and the largest and second largest subunits of RNA polymerase II [RPB1 and RPB2]). Data were obtained from the Assembling the Fungal Tree of Life (AFTOL; www.aftol.org) and GenBank sequence databases, which aligned in ClustalX (Thompson et al. 1997) and manually improved where necessary. After introns and ambiguously aligned characters were excluded, 6694 bp were used in the final analyses. In some cases, genes were missing (see Supplemental Table 3 and Supplemental Data Set 3 online). The resulting data were combined and delimited into 11 partitions, including nuc-SSU, nuc-LSU, and the first, second, and third codon positions of EF-1α, RPB1, and RPB2, with unique models applied to each partition. Metropolis coupled Markov chain Monte Carlo analyses were conducted using MrBayes 3.1.2 (Huelsenbeck and Ronquist 2001) with a six-parameter model of evolution (generalized time reversible) (Rodriguez et al. 1990) and gamma distribution approximated with four categories and a proportion of invariable sites. Trees were sampled every 100th generation for 5,000,000 generations. Three runs were completed to ensure that stationarity was reached, and 5000 trees were discarded as “burn in” for each. Posterior probabilities were determined by calculating a 50% majority-rule consensus tree of 45,000 trees from a single run. Maximum

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likelihood bootstrap proportions were calculated by doing 1000 replicates in RAxML-VI- HPC (Stamatakis, 2006) with the GTRCAT model approximation and 25 rate categories with the same data partitions as for the Bayesian runs.

Repetitive Elements. Repetitive elements were identified de novo using RepeatScout v1.0.0 (Price et al. 2005) with a minimum threshold of 10 matches and a minimum repeat length of 200 bp. Newly generated repeats were aligned to the genome assembly via BLASTN v2.0 (Altschul et al. 1990). Hits were discarded if sequence identity fell below 35% or alignment length was less than 200 bp. For each repeat, the number of filtered hits was counted, and repeats were discarded if the number of hits to the assembly was less than 10. Prototype repeat regions were defined by identification of sequence similarities among themselves via BLASTN and deletion of redundant repeat sequence. Regions of the genome assembly that matched to a repeat were aligned using MUSCLE v3.6 (Edgar 2004). To identify repeat type and function, repeats were compared with the nonredundant sequence database hosted by NCBI via BLASTN/BLASTX, and subrepeat regions within repeats were also analyzed. Tandem repeats were identified using Tandem Repeat Finder (Benson 1999), direct repeats were identified via MegaBLAST (Zhang et al. 2000), and inverted repeats were identified using both MegaBLAST and eINVERTED (Rice et al. 2000). Putative telomeric regions were predicted by considering scaffold ends containing successive repetitive elements without interspersed predicted protein coding genes. The occurrence of repeat classes within these regions was counted and compared with occurrences throughout the genome. Where less than 85% of the repeats were found to be at nongenic scaffold end regions, these classes were classified as telomeric repeats. The scaffold ends were predicted to be physical telomeres if they contained three or more telomeric repeats. To analyze and compare the prevalence of RIP mutation, we developed a program to compare RIP mutations between multiple sequences (Hane and Oliver, unpublished data). RIPCAL compares the aligned sequences against a designated model sequence (in this case the trimmed de novo repeats) and was configured to calculate RIP (Dean et al. 2005).

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Gene Content. An automated genome annotation was initially created using the Calhoun annotation system. A combination of gene prediction programs, FGENESH, FGENESH+, and GENEID, and 317 manually curated transcripts were used. GENEWISE was used with non-species specific parameters to predict genes from proteins identified by BLASTX. To refine the initial genome annotation, a further 10,752 EST reads were obtained from an EST library from oleate-grown mycelium and 10,751 from S. nodorum infected wheat. These EST sequences were screened against a library of wheat ESTs, trimmed for vector sequence manually, for poly(A) tail sequence using TrimEST (Rice et al. 2000), screened for unusable sequences of poor quality, filtered for remaining sequence equal or bigger than 50 bp, and aligned to the genome assembly using Sim4 (Florea et al. 1998). ESTs with multiple genomic locations were assigned their optimum location based on percent identity, total alignment length, and best location of the EST mated pair. Gene models were manually annotated according to optimum EST alignments using Apollo (Lewis et al. 2002). Genes that were fully supported by EST data were used to train the gene prediction program UNVEIL (Majoros et al. 2003). Second-round gene annotations were created by combining gene predictions with EST data, with EST data replacing predicted gene models, and UNVEIL predictions preferred over first-round predictions. Genes with coding regions smaller than 50 amino acids were discarded. The numerical identifiers assigned during the first-round predictions have been retained. New gene models were assigned loci from 20,000 onwards. Updated loci (UNVEIL and EST supported) have been given the numerical suffix 2 (e.g., SNOG_16571.2). The 5354 unsupported genes have retained the numerical identifiers and suffix 1. Where genic regions lack EST support, only the coding sequence is reported. ESTs not aligned to the assembly by Sim4 were compared with the unassembled reads via BLASTN. EST with matches to unassembled reads with an e-value of less than 1e-10 were clustered into contigs using cap3 (Huang and Madan 1999). The assembled ESTs were tested for single open reading frames using getORF (Rice et al. 2000), and possible genes were determined by BLASTP (Altschul et al. 1990) to protein databases at NCBI. One new gene (STAG_20208.1) was identified by this method. We have chosen not to alter genes where gene models conflicted with homologs except where colinearity evidence confirms orthology (Figure 4). Updated files of gene and protein sequences are available from R. Oliver ([email protected]).

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Proteins were assigned putative functional classes by searching for relevant PFAM (Bateman et al. 1999) domains (Bateman et al. 2004) with HMMER v2.0 (Eddy, 1998) (see Supplemental Data Set 2 and Supplemental Table 2 online). Putative gene ontology was assigned via BLASTP with BLAST2GO (Conesa et al. 2005). Due to the relatively poor identification of certain PKS and NRPS domains using resources like PFAM (Bateman et al. 2004) and CD-SEARCH (Marchler-Bauer and Bryant 2004; Marchler-Bauer et al. 2005), PKS and NRPS domains and their modular organization were further elucidated with online tools available at NRPS-PKS (Yadav et al. 2003; Ansari et al. 2004). Subcellular localization and secretion was predicted via WoLF PSORT (Horton et al. 2007).

EST Library Construction. For the construction of the in planta cDNA library, wheat (Triticum aestivum) cv Amery was infected with S. nodorum SN15 as a whole plant spray and processed as a latent period assay (Solomon et al. 2006b). Necrotic tissue was excised from the leaves at 10, 11, and 12 DAI for RNA isolation. RNA was isolated by the Trizol method (Sigma-Aldrich). Material for the oleate library was generated as follows: minimal medium(100 mL) + sucrose (0.5% [w/v]) was inoculated with S. nodorum SN15 pycnidiospores (2.75 x 107) and incubated at 22°C with shaking (130 rpm) for 4 d. Mycelia was harvested, washed, and added to 100 mL of minimal media, including 0.05% (v/v) Tween 80 and 0.2% (w/v) oleate as the carbon source. The culture was incubated as before for 30 h before being harvested, washed, snap frozen in liquid nitrogen, and freeze-dried in a Maxi Dry Lyo (Heto Holten). mRNA was extracted using the Messagemaker mRNA purification-cloning kit (Gibco/Invitrogen) according to manufacturer’s instructions. A total of 2.3 mg of mRNA was used as template for reverse transcription to cDNA. The in planta cDNA library was constructed using the SMART cDNA library construction kit (Clontech), and the oleate library was constructed in pSPORT1 (Gibco/Invitrogen). All manipulations were performed according to the manufacturer’s instructions. Phage DNA was packaged using the GigapackIII Gold phage packaging system (Stratagene) according to the manufacturer’s instructions. Phages were grown, amplified, and mass-excised to bacterial clones according to the provided protocols. The final libraries were both estimated to contain about 500,000 clones.

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Quantitative PCR. Total RNA (1µg) was reverse transcribed to cDNA using iScript reverse transcriptase premix (Bio-Rad) according to the manufacturer’s instructions. RNA from three biological replicates was pooled for a single cDNA synthesis. cDNA reactions were used as PCR template at 1:50 dilution for in vitro-grown SN15 samples and at 1:5 dilution for in planta-grown SN15 samples. Quantitative PCR reactions consisted of 10 µL of iQ SYBR green supermix (Bio-Rad), forward and reverse primers (each at 1.2 µM), and 5 µL of template DNA in a 20 µL reaction. Reactions were incubated in a Rotor-Gene 3000 thermocycler (Corbett Research). Cycling conditions were 3 min/95°C and then 35 cycles of 10s/95°C, 20s/57°C, and 20s/72°. Amplicon fluorescence from template of unknown concentration was compared with that from genomic DNA standards of 25, 2.5, 0.25, and 0.025 ng/reaction. All reactions were performed with two technical replicates. Data were analyzed using the Rotorgene software version 6.0 (Corbett Research). Primer sequences are listed in Supplemental Table 4 online.

Accession Number. Sequence data from this article can be found in the GenBank/EMBL data libraries under accession number AAGI00000000.

Results

Acquisition and analysis of the genome sequence. The genome sequence was obtained using a whole-genome shotgun approach. Approximately 10x sequence coverage was obtained as paired-end reads from plasmids of 4 kb and 10 kb plus 40-kb fosmids. Reads were assembled using Arachne (Jaffe et al. 2003) forming 496 contigs totalling 37,071 kb. The contig N50 was 179 kb, meaning an average base in the assembly lies within a contig of at least 179 kb. Greater than 98% of the bases in the assembly have a consensus quality score larger or equal of 40, corresponding to the standard error rate of fully finished sequence. The contigs are connected in 109 scaffolds spanning 37,202 kb with a scaffold N50 of 1.05 Mb. More than 50% of the genome is contained in the 13 largest scaffolds. Within the scaffolds, only ~140 kb is estimated to lie within sequence gaps. Thus in terms of representation, contiguity and sequence accuracy, the draft assembly is of high quality. The mitochondrial genome comprises a circle of 49,850 bp (Genbank accession number EU053989). It replaces

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two of the auto-assembled; 52 and 65. The nuclear genome is therefore assembled in 107 scaffolds of total length 37,164,227 bp. General features of the assembly are described in Table 1. As detailed below, the genomic sequencing was complemented by sequencing EST libraries. One library was constructed from axenically-grown mycelium and after removing vector, polyA sequences, poor quality sequences and sequences smaller than 100 bp, there were 7750 remaining ESTs. Of these, 97.6% mapped to the genome assembly via Sim4 and 1.4% mapped to unassembled reads. This indicates that the assembly has achieved good coverage of the genome. In all, seven EST contigs and 13 singletons clustered to the unassembled reads.

Table 1. The assembly of the S. nodorum nuclear genome sequence

Scaffold count 107 Scaffold median length/bp 32,376 Total/bp 37,164,227 Scaffold mean length/bp 347,329 Coverage ~10 x Gaps/number 387 G + C % 50.3 % Total length of gaps/bp 146,025 Scaffold minimum length/bp 2005 Max length of gap/bp 11,204 Scaffold maximum length/bp 2,531,949 Median length of gap/bp 325

Analysis of Repetitive elements. Repetitive elements were identified de novo, by identifying sequence elements that existed in 10 or more copies, were greater than 200 bp, and exhibited more than 65% sequence identity. The analysis revealed the presence of 25 repeat classes. Table 2 lists the general features of the repeats (see Supplemental Data Set 1 online). Only three, Molly, Pixie and Elsa, had been detected earlier (Genbank accession numbers AJ277502, AJ277503, and AJ277966, respectively). Molly, Pixie, X15 and R37 show sequence characteristics of inverted terminal repeat-containing transposons, while Elsa, R9 and X11 appear to be retrotransposons. Repetitive elements were found individually throughout the genome but were often found in clusters spanning several kilobases. Telomere-associated repeats were identified by searching for examples of the canonical telomere repeat TTAGGG at the termini of auto-assembled scaffolds. Physically-linked repetitive sequences were then analysed for association with the TTAGGG sequence repeats. Between 19 and 38 copies of telomere-associated repeats were found in the assembly.

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Repeat-induced point (RIP) mutation is a fungal-specific genome-cleansing process that detects repeated DNA at meiosis and introduces C to T mutations into the copies (Cambareri et al. 1989). Using the parameters defined for Magnaporthe grisea (Dean et al. 2005) we identified RIP-like characteristics in several of the repeat classes (Table 2; Supplementary Data Set 1 online). The transposons Molly and Elsa were the most clearly affected classes. None of the telomere-associated repeats displayed RIP characteristics.

Mitochondrial Genome. The mitochondrial genome of S. nodorum assembled as a circular molecule of approximately 49,850 bp, with an overall G + C content of 29.4%. It contains the typical genes encoding 12 inner mitochondrial membrane proteins involved in electron transport and coupled oxidative phosphorylation (nad1-6 and nad4L, cytb, cox1-3, atp6), the 5S ribosomal protein, three open reading frames (ORFs) of unknown function, and genes for the large and small ribosomal RNAs (rnl and rns) (Fig. 1). The genes were coded on both DNA strands. The 27 tRNAs can carry all 20 canonical amino acids. All tRNA secondary structures showed the expected cloverleaf form, but tRNA-Thr and tRNA-Phe had 9 nucleotides in the anticodon loop instead of the typical seven, and tRNA-Arg2 had 11 nucleotides in its anticodon loop.

Gene content. The initial gene prediction process identified 16,957 gene models of which 16,586 were located on the 107 nuclear scaffolds. A revised gene prediction procedure, using new ESTs (see below) and 795 fully supported and manually annotated gene models, identified 10,762 version 2 nuclear gene models. Of these, 617 genes corresponded to a merging of version 1 genes; in 50 cases, three prior gene models were merged and in one case, four genes were merged. ESTs that aligned to unassembled reads identified one supported gene (SNOG_20000.2). A total of 5,354 version 1 gene models were not supported but did not conflict with second-round predictions. We therefore conclude that S. nodorum contains a minimum of 10,762 nuclear genes of which all but 125 are supported by two gene prediction procedures and 2,696 are supported by direct experimental evidence via EST alignment. These genes have the identification format SNOG_xxxxx.2, were compared with the Genbank nonredundant protein NCBI database. Informative (not hypothetical, predicted, putative or unknown) BLASTP (Altschul et al. 1990) hits with e-

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values less than 1x10-6 were found for 7,116 genes (See Supplementary Data Set2 online). It is estimated that at least 46.6% of the nuclear genome is transcribed and 38.8% is translated. The 5,354 gene models without support from the reannotation have unaltered accession numbers as SNOG_xxxxx.1 and are retained for further possible validation and analysis. As 952 of these unsupported gene models have BLASTP hits with e-values less than 1x10-6, we predict that some will be validated as new evidence comes to hand.

Figure 1. The Structure of the Mitochondrial Genome. Black segments are exons, hatched segments are rRNA genes, and white segments are introns. The direction of transcription is indicated with the arrows.

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Table 2. Features of repetitive element classes found in the nuclear genome

Full Length Occupied Percentage Repeat Name Class Count (bp) (bp) of Genome RIPa Subtelomeric R22 Telomeric repeat 23 678 12565 0.03 NO X15 Telomeric repeat/transposon or remnant 37 6231 89126 0.24 NO X26 Telomeric repeat 38 4628 77020 0.21 NO X35 Telomeric repeat 19 1157 14393 0.04 NO X48 Telomeric repeat 22 265 5631 0.02 NO

Ribosomal Y1 rDNA repeat 113 9358 401890 1.08 NO

Other Elsa Transposon 17 5240 34287 0.09 YES Molly Transposon 40 1862 50453 0.14 YES Pixie Transposon 28 1845 39148 0.11 NO R10 Unknown 59 1241 44018 0.12 NO R25 Unknown 23 3320 44860 0.12 NO R31 Unknown 23 3031 40267 0.11 NO R37 Transposon or remnant 98 1603 104915 0.28 NO R38 Unknown 25 358 8556 0.02 NO R39 Unknown 29 2050 35758 0.10 NO R51 Unknown 39 833 25538 0.07 NO R8 Unknown 48 9143 275643 0.74 NO R9 Transposon or remnant 72 4108 163739 0.44 NO X0 Unknown 76 3862 145268 0.39 NO X11 Transposon or remnant 36 8555 128638 0.35 NO X12 Unknown 29 2263 25369 0.07 NO X23 Unknown 29 685 11679 0.03 NO X28 Unknown 30 1784 32002 0.09 NO X3 Unknown 213 9364 463438 1.24 NO X36 Unknown 10 512 5067 0.01 NO X96 Unknown 14 308 4321 0.01 NO SUM 4.52 a Evidence from the alignment that the repeat has been subjected to RIP mutation.

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Table 3. Comparison of GO classification of unigene and transcript numbers between the planta and oleate library

A. Biological Processes GO identifier Description Loci in planta oleate p-value1 Up-regulated in planta GO:0006412 Protein biosynthesis 128 710 325 5.97E-19 GO:0045493 Xylan catabolism 24 31 0 6.16E-09 GO:0006508 Proteolysis 78 110 39 8.29E-07 GO:0008643 Carbohydrate transport 58 22 0 1.26E-06 GO:0000272 Polysaccharide catabolism 12 24 1 4.29E-06 GO:0016068 Type I hypersensitivity 13 87 31 9.67E-06 GO:0030245 Cellulose catabolism 16 18 0 1.33E-05 GO:0005975 Carbohydrate metabolism 102 53 16 6.57E-05 GO:0042732 D-xylose metabolism 2 25 4 2.01E-04 GO:0009051 Pentose-phosphate shunt, oxidative branch 2 21 3 4.07E-04 Up-regulated oleate GO:0007582 Physiological process 24 8 48 1.04E-10 GO:0006629 Lipid metabolism 20 6 40 1.42E-09 GO:0006096 Glycolysis 21 42 92 5.93E-09 GO:0006108 Malate metabolism 4 12 45 5.48E-08 GO:0006099 Tricarboxylic acid cycle 20 50 85 4.11E-06 GO:0015986 ATP synthesis coupled proton transport 26 34 65 6.56E-06 GO:0006183 GTP biosynthesis 1 0 13 1.54E-05 GO:0006228 UTP biosynthesis 1 0 13 1.54E-05 GO:0006241 CTP biosynthesis 1 0 13 1.54E-05 GO:0006334 Nucleosome assembly 12 65 95 3.21E-05

B. Cellular Components GO identifier Description Loci in planta oleate p-value1 Up-regulated in planta GO:0005840 Ribosome 89 567 262 3.14E-15 GO:0015935 Small ribosomal subunit 11 93 33 4.86E-06 GO:0005576 Extracellular region 36 23 1 7.44E-06 GO:0005730 Nucleolus 6 23 2 4.15E-05 GO:0030529 Ribonucleoprotein complex 25 60 19 4.31E-05 GO:0030125 Clathrin vesicle coat 9 7 0 8.86E-03 GO:0016020 Membrane 338 127 122 1.07E-02 GO:0016021 Integral to membrane 401 243 213 1.38E-02 GO:0019867 Outer membrane 7 45 24 1.40E-02 GO:0005874 Microtubule 19 8 1 1.97E-02 Up-regulated oleate GO:0005829 Cytosol 34 19 50 1.01E-06 GO:0016469 Proton-transporting two-sector atpase complex 24 27 60 1.41E-06 GO:0000786 Nucleosome 11 65 95 3.21E-05 GO:0043234 Protein complex 33 15 29 1.23E-03 GO:0005739 Mitochondrion 102 138 147 1.62E-03 GO:0005634 Nucleus 288 183 186 1.90E-03 GO:0005777 Peroxisome 14 26 38 3.39E-03 GO:0005746 Mitochondrial electron transport chain 8 36 47 4.40E-03 GO:0045261 Proton-transporting ATP synthase complex, catalytic core F(1) 5 14 23 7.49E-03 GO:0005778 Peroxisomal membrane 3 1 7 8.63E-03

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Table. 3 (continued)

C. Molecular Functions GO Identifier Description Loci in planta oleate p-value1 Up-regulated in planta GO:0003735 Structural constituent of ribosome 111 709 328 2.09E-18 GO:0004553 Hydrolase activity, hydrolyzing O-glycosyl compounds 83 55 5 4.13E-10 GO:0004252 Serine-type endopeptidase activity 14 43 3 6.92E-09 GO:0005351 Sugar porter activity 64 22 0 1.26E-06 GO:0046556 Alpha-N-arabinofuranosidase activity 6 19 0 7.39E-06 GO:0030248 Cellulose binding 19 18 0 1.33E-05 GO:0004029 Aldehyde dehydrogenase (NAD) activity 1 15 0 7.85E-05 GO:0050661 NADP binding 6 23 3 1.60E-04 GO:0004185 serine carboxypeptidase activity 8 13 0 2.56E-04 GO:0004616 phosphogluconate dehydrogenase (decarboxylating) activity 4 22 3 2.56E-04 Up-regulated oleate GO:0004459 L-lactate dehydrogenase activity 2 5 44 2.07E-11 GO:0030060 L-malate dehydrogenase activity 2 5 44 2.07E-11 GO:0005498 Sterol carrier activity 3 7 46 1.02E-10 GO:0008415 Acyltransferase activity 17 4 34 4.64E-09 GO:0005506 Iron ion binding 91 89 128 3.72E-06 GO:0004550 Nucleoside diphosphate kinase activity 1 0 13 1.54E-05 GO:0005554 Molecular function unknown 49 40 65 7.95E-05 GO:0046933 Hydrogen-transporting ATP synthase activity, rotational mechanism 24 34 58 8.73E-05 GO:0046961 Hydrogen-transporting atpase activity, rotational mechanism 24 34 58 8.73E-05 GO:0050660 FAD binding 27 13 30 2.85E-04 1 Probability of significant difference between the libraries (Audic and Claverie 1997).

Table 4. Comparison of tRNA gene clusters flanking the rnl gene of the mitochondrial genome in several ascomycetes

Organism 5-'upstream regionb rnl 3-'downstream regionb Accession number P. marneffei RKG1G2DS1WIS2P rnl TEVM1M2L1AFL2QM3H AY347307 A. niger KGDS1WIS2P rnl TEVM1M2L1AFL2QM3H DQ217399 M. graminicola GDS1WIS2P rnl M1L1EAFL2YQM2HRM3 EU090238 S. nodorum VKGDS1WIRS2P rnl T M1M2EAFLQHM3 EU053989 E. floccosum KGDSIWSP rnl TEVM1M2L1AFL2QM3H AY916130 H. jecorina ISWP rnl TEM1M2L1AFKL2QHM3 AF447590 P. anserina ISP rnl TEIM1L1AFL2QHM2 X55026 a The tRNA gene order of listed organisms is based on Genbank sequences b Capital letters refer to tRNA genes for: R=arginine, K=lysine, G=glycine, D=aspartic acid, S=serine, W=tryptophan, I=isoleucine, P=proline, T=threonine, E=glutamic acid, V=valine, L=leucine, A=alanine, F=phenylalanine, Q=glutamine, H=histidine, Y=tyrosine. 1,2,3 The numbers indicate the presence of more tRNA genes for the same amino acid in the consensus sequence.

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Gene expression during infection. Two EST libraries were constructed and analyzed as part of this project. An in vitro library was constructed from axenic fungal mycelium transferred to media with oleate as the sole carbon source; this is referred to as the oleate library. An in planta library was made from bulked sporulating disease lesions on wheat 9, 10 and 11 days after infection (DAI). For both libraries 5,000 random clones were sequenced in both directions. The oleate library was entirely fungal and hence particularly suited for primary genome annotation purposes. The lipid growth media was chosen to replicate the early stages of infection in which lipolysis, the glyoxalate cycle and gluconeogenesis are thought to be critical metabolic requirements (Solomon et al. 2004a). The in planta library was designed to reveal both plant and fungal genes expressed at a late stage of infection. After trimming and removal of plant ESTs and alignment to the genome assembly, the in planta library formed 1448 and the oleate library formed 1231 unigenes (See Supplement Data Set 2 online). Only 427 of the unigenes were found in both libraries. Although this represents 19% of the unigenes, it encompasses 46% of the ESTs, showing the genes expressed uniquely in one library are of relatively low expression. The unigenes obtained from in planta and oleate libraries were classified according to the gene ontology (GO) categories. GO matches were obtained for 851 (59%) of the unigenes found in the in planta and 736 (59%) of those found in the oleate library. Relative numbers of ESTs and genes in different GO classes were compared (Table 3). GO categories were ranked by statistical discrimination between the two libraries and the top 10 are shown for each of biological process, cellular component and molecular function. Coexpression of fungal gene clusters responsible for the synthesis of secondary metabolites (Bok and Keller 2004) and pathogenicity (Kamper et al. 2006) has been observed. We compared the number of ESTs found in the in planta and oleate libraries to search for clusters of coexpressed genes. Using a window of 10 contiguous genes, we scanned for regions with biased ratios of ESTs from either library. One putatively in planta- induced region stood out. These six genes SNOG_16151.2 to SNOG_16157.2 were exclusively in the in planta library with 4, 20, 0, 4 10 and 1 EST clones respectively. The genes have best hits to a major falcilitatore superfamily transporter, a phytanoyl-CoA dioxygenase, a CocE/NonD hydrolase, a salicylate hydroxylase and are next to a transcription factor. Such a cluster may be involved in the degradation of phytols, phenylpropanoids and

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catechols either for nutritional purposes providing trichloroacetic acid intermediates via the beta-ketoadipate pathway or to detoxify wheat defence compound(s). It is intriguing that overexpression of the thiolase in the beta-ketoadipate pathway in L. maculans markedly reduced pathogenicity (Elliott and Howlett 2006). Experiments to test these ideas in S. nodorum are in progress.

Discussion

As estimated genome size of S. nodorum is 37.2 Mbp, which is significantly larger than the 28 to 32 Mbp previously estimated by pulsed-field gel analysis (Cooley and Caten 1991). Electrophoretic karyotypes have proved to be unreliable estimators of total genome size in many fungal species (Orbach et al. 1988 and 1989; Talbot et al. 1993). In the case of S. nodorum, this discrepancy may be a consequence of comigration of chromosomal bands on pulsed-field gels leading to an underestimation of genome size (Cooley and Caten 1991). The electrophoretic karyotype was found to be highly variable between strains, even when isolated from a single ascus, consistent with the generalisation that many fungal species have plastic genome structures (Zolan 1995). The revised genome size estimate is comparable to other sequenced filamentous fungi such as the rice pathogen Magnaporthe grisea, which is currently estimated to be 41.6 Mbp and the non-pathogen Neurospora crassa now estimated at 39.2 Mbp.

Phylogenetic analysis. The genome sequence has confirmed the phylogenetic placement of S. nodorum in the class Dothideomycetes. Along with the Eurotiomycetes (containing Aspergillus, and human pathogens such as Histoplasma), Lecanoromycetes (the majority of the lichenized species), Leotiomycetes (containing numerous endophytes and the plant pathogen Sclerotinia) and Sordariomycetes (with Neurospora, Magnaporthe and Colletotrichum spp.) the Dothideomycetes is now recognised as a major clade of the filamentous Ascomycota (James et al. 2006). Phylogenetic analyses of full fungal genomes and large-scale taxon sampling agree with the placement of S. nodorum and point to the rapid divergence of these major classes of ascomycetes (Robbertse et al. 2006; Spatafora et al. 2006). The tree in Fig. 2 is a focused sampling of the largest classes of the Ascomycota with

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an emphasis on plant pathogenic species and those with genome sequences. The Dothideomycetes is supported as a single class and represented by samples of five of the nine currently proposed orders (Eriksson 2006; Schoch et al. 2006). S. nodorum is placed in the Pleosporales, a large order containing more than 100 genera and several thousand species, many of which are important plant pathogens. The Pleosporaceae family contains Alternaria, Cochliobolus and Pyrenophora (Kodsueb et al. 2006) and is closely related to the clade containing the genera Leptosphaeria and Phaeosphaeria (Stagonospora). Other orders in the Dothideomycetes include the Dothideales and the Capnodiales (Schoch et al. 2006), which contains the pathogen genera Mycosphaerella and Cladosporium.

Table 5. Comparison of selected gene families identified by PFAM (release 21) domain/family between S. nodorum and latest BROAD releases of M. grisea, N. crassa and A. nidulans and incomplete data from C. heterostrophus and F. graminearum (Kroken et al. 2003; Gaffoor et al. 2005; Lee et al. 2005)

3 s v

n C. heterostrophus

3 a a a

S. nodorum 5 l

s e e (Ch) or s s e u s

i s

Gene family a d r a 7 i r a F. graminearum e g . c e n l

l s . . e s Genes with Genes In Planta e (Fg) r

Oleate Clones M r N a A. PFAM match with EST Clones Clones G-alpha 4 2 3 0 3 3 3 Cfem 4 1 17 15 9 6 4 9 Ch 8 Fg Rhodopsin 2 2 14 8 1 2 1 Hydrophobin class 1 0 0 0 0 1 1 3 Hydrophobin class 2 2 0 0 0 2 1 0 Feruloyl esterase 8 0 0 0 10 1 5 Cutinase 11 4 4 8 16 3 4 Subtilisin 11 3 8 2 26 6 3 Transcription factor 94 25 37 43 97 83 195 Cytochrome p450 103 20 27 20 115 39 102 Polyketide synthase 19 1 3 0 24 7 28 24 Ch 14 Fg Non-ribosomal 8 1 1 0 8 3 13 peptide synthase 10 Ch PKS-NRPS 1 0 0 0 7 0 0 1 Ch

Repeated elements in the nuclear genome. Prior to this study, only one unpublished study had been made of repetitive elements in the S. nodorum genome (Rawson 2000). The de novo analysis of repeats is likely to become a feature of future genome sequencing projects as organisms with little prior molecular work are selected. The total amount of repetitive DNA in the S. nodorum nuclear genome is estimated at 4.5%. This compares with 9.5% in M. grisea. Some of these repeats could be associated with telomeres. Between 19 and 38 copies of telomere-associated repeats were found in the assembly. These numbers accord

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well with the 14 to 19 chromosomes visualized by pulsed-field electrophoresis (Cooley and Caten 1991). Studies of S. nodorum life cycle have indicated that it undergoes regular sexual crossing, particularly in areas with Mediterranean-style climates with the associated need to over-summer as ascospores (Bathgate and Loughman 2001; Stukenbrock et al. 2006). The relatively low content of repetitive DNA is consistent with this observation. The prevalence of clear cases of RIP further confirms that meiosis is a frequent event. RIP has been found to varying degrees in other fungal genomes. It is notable that the closely related L. maculans has previously been shown experimentally to exhibit RIP (Idnurm and Howlett 2003).

Mitochondrial Genome. A distinctive feature of fungal mitochondrial genomes is the clustering of tRNA genes (Ghikas et al. 2006) and it is thought that both the tRNA gene content and their placement will be conserved in fungi (Table 4). The 27 tRNA genes clustered into five groups, with the two larger tRNA gene clusters flanking rnl, a pattern common to other fungal mtDNAs (Tambor et al. 2006). The tRNA gene cluster 5’ to rnl had GDS1WIS2P as a consensus with, its closest sequenced relative M. graminicola (Genbank accession number EU090238), while the 3’-downstream consensus was EAFLQHM having many tRNA genes in the same order found in other Ascomycetes. Variation in the order of tRNAs, such as inversions in Epidermophyton floccosum (tRNA-Ile, tRNA-Tpr) or in Podospora anserina and S. nodorum (tRNA-Met, tRNA-His), suggest that rearrangements are common in fungal mtDNAs (Table 4). Kouvelis et al. (2004) argued that gene pairs nad2-nad3, nad1-nad4, atp6-atp8, and cytb- cox1 would remain joined in ascomycetes with some possible exceptions, as already detected in M. graminicola that present only two of these gene pairs coupled. In S. nodorum, the atp8- 9 genes were not present and cytb-cox1 were uncoupled and, interestingly, the nad1 and nad4 genes were on sections of the mtDNA in an inverted orientation. Two orfs (orf1 and orf2) had homologous sequences in the in planta EST library. While the M. graminicola mitochondrial genome had almost no introns, four intron-encoded genes were found in S. nodorum, with high homology to LAGLIDADG type endonucleases or GIY-YIG type nucleases (See Supplemental Table 1 online). Intron-encoded proteins have also been reported in P. anserina (Cummings et al. 1990) and Penicillium marneffei (Woo et al. 2003).

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Figure 2. Phylogeny of Ascomycota focused on Dothideomycetes. Each species name is preceded by a unique AFTOL ID number (aftol.org). The tree is a 50% majority rule consensus tree of 45,000 trees obtained by Bayesian inference. Similarly, all nodes had maximum likelihood bootstraps above 80% except where numbers are shown below nodes. Asterisks indicate nodes that were not resolved in more than 50% of bootstrap trees. Alignment data are provided in Supllementary Data Set 3 online. The gene data used are listed in Supplemental Table 3 online.

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Table 6. Potential orthologs to S. nodorum non-ribosomal peptide synthase genes

a Domain abbreviations; Adenylation A; Condensation C; Cyclisation Cy; Epimerisation E; Thiolation T; Thioesterase Te . Potential orthologs identified by best blastp hits to NRPS genes in C. heterostrophus (Lee et al. 2005) and by best informative hit to NR at NCBI of e-value < 1x10-10. b The best hit of the identified gene in the S. nodorum gene set was observed reciprocally. c Percent similarity of ortholog pairs (Needleman and Wunsch 1970) via NEEDLE (Rice et al. 2000). d Domain structure and modular organisation for all sequences was determined via the online NRPS-PKS database (Ansari et al. 2004). It should be noted that domain structure predictions may vary slightly from those stated in the original studies. e Protein sequence for AbNPS2 currently available in supplementary appendix S2 (Kim et al. 2007).

Functional Analysis of Proteins. Our primary goal in obtaining the genome sequence was to reveal genes likely to be involved in pathogenicity. Whilst some genes seem to be specifically associated with pathogenicity in a single organism, other genes and gene families have been generally associated with pathogenicity albeit they are also found in non- pathogens (see http://www.phi-base.org/about.php; Baldwin et al. 2006). Some of the generic functions are listed (Table 5; see Supplemental Data Set 2 and Supplemental Table 2 online).

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EST support was found for 59 of the genes, with no statistically significant difference in the numbers of ESTs in the in planta and oleate libraries. Non-ribosomal peptide synthetases (NRPS) are modular genes that control the synthesis of a diverse set of secondary metabolites including the dothideomycete host-specific toxins AM-toxin, HC-toxin and victorin from Alternaria and Cochliobolus species (Wolpert et al. 2002). NRPS genes from C. heterostrophus have been analyzed in detail (Lee et al. 2005). Comparison of both protein sequences and domain structure of the C. heterostrophus NRPS genes (NPS1-11) with the eight identified in S. nodorum was undertaken (Table 6). Putative orthology was determined by identifying reciprocal best hits amongst the gene sets. Three pairs were identified. SNOG_02134.2 was linked to NPS2 and both appear to be orthologous to the A. nidulans gene SidC (Eisendle et al. 2003), which is responsible for the synthesis of ferricrocin, an intracellular iron storage and transport compound involved in protection against iron toxicity (Eisendle et al. 2006). It is likely that SNOG_02134.2 and NPS2 have similar roles. SNOG_14638.2 was linked to NPS6, a ubiquitous gene with a related role in siderophore-mediated iron uptake and oxidative stress protection (Oide et al. 2006). Third, SNOG_14834.2 appears to be directly related to NPS4, Psy1 from Alternaria brassicae (Guillemette et al. 2004) and NPS2 from A. brassicicola (Kim et al. 2007). Ab NPS2 mutants are reduced in virulence and the gene is predicted to encode a component of the conidial wall. It is likely that SNOG_14834.2 will have a similar generic role. Reciprocal best-hit relationships were observed between a further two SNOG NRPS genes and other fungal genes; SNOG_09081.2 was related to PesA (Bailey et al. 1996) and SNOG_14908.2 to the Salps2 gene from Hypocrea lixii (Vizcaino et al. 2006). These genes plus SNOG_14834.2, SNOG_09488.2 and SNOG_01105.2 are all closely related to NPS4, suggesting this five- gene subfamily is expanded in S. nodorum. Interestingly, a further seven NRPS genes from C. heterostrophus (NPS3, 5, 8, 10, 11 and 12) have no obvious ortholog in S. nodorum, suggesting expansion of this subfamily in the maize pathogen (Yoder and Turgeon 2001). Intensive studies in C. heterostrophus showed that individual gene knockouts produced altered phenotypes only for NPS6 (Lee et al. 2005) indicating redundancy of function. The smaller complement of NRPS genes in M. grisea (eight) and S. nodorum indicate that these organisms may be more fruitful models to study NRPS function. Furthermore, although toxins have been implicated in the virulence of both pathogens, nonribosomal synthetases

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cannot be expected to be a major source. No ESTs were found corresponding to these genes. This may be due to their large size or to a generally low level of expression.Polyketide synthases (PKS) are a second modular gene family strongly associated with pathogenicity (Kroken et al. 2003; Gaffoor et al. 2005) being responsible for the production of T-toxin from C. heterostrophus and PM-toxin from Mycosphaerella zeae-maydis (Yun et al. 1998; Baker et al. 2006). S. nodorum is predicted to contain 19 PKS genes compared to the 24, 14 and 24 in the pathogens M. grisea, Fusarium graminearum and C. heterostrophus respectively, and 28 in the saprobe A. nidulans, but significantly more than the seven in N. crassa (Table 5).

Figure 3. Homology relationship of the S. nodorum secretome. The 1231 predicted extracellular proteins without GO annotation were compared with the latest releases of the U. maydis, N. crassa and M. grisea genomes. Counts are best hits of e-value < 1e-10 if predicted as extracellular by WolF PSORT.

Orthology relationships between the well-studied F. graminearum and C. heterostrophus gene sets and S. nodorum are shown in Table 7. Reciprocal best Blast hits were observed with eight genes from C. heterostrophus and five from F. graminearum. This close relationship, particularly with C. heterostrophus, reflects the close phylogenetic relationship and suggests an ancient origin for the majority of the PKS paralogs (Kroken et al. 2003).

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SNOG_11981.2 is supported by five ESTs from the in planta library and none from the oleate library, consistent with upregulation during infection and sporulation (no other PKSs have EST support). This gene is orthologous to non-reducing clade 2 PKS genes that are associated with 1,8-dihydroxynaphthalene melanin biosynthesis in Bipolaris oryzae and many other pathogens (Kroken et al. 2003; Moriwaki et al. 2004; Amnuaykanjanasin et al. 2005). We showed previously that S. nodorum produces melanin from dihydroxyphenlyalanine (Solomon et al. 2004b) for which a PKS would not be necessary. This finding suggests that either S. nodorum may produce 1,8-dihydroxynaphthalene melanin in addition to dihydroxyphenlyalanine melanin or that SNOG_11981.2 plays another role. A single PKS-NRPS hybrid protein (SNOG_00308.2.) was identified in the genome of S. nodorum as was found for F. graminearum (Gaffoor et al. 2005) and C. heterostrophus (Lee et al. 2005). C. heterostrophus NPS7 and SNOG_00308.2 do not appear to be closely related and it is likely that they evolved independently. In contrast, the hybrid protein of F. graminearum (GzFUS1/FG12100) is closely related to SNOG_00308.2. Overall they are 54.5% similar and apart from an acyl binding domain found only in SNOG_00308.2 the domain structures are identical. Gz FUS1 produces fusarin C, a mycotoxin (Gaffoor et al. 2005). The best hit (with 59.4% similarity) to SNOG_00308.2 in M. grisea is Ace1, a hybrid PKS/NRPS that confers avirulence to M. grisea during rice (Oryza sativa) infection (Bohnert et al. 2004). It will be intriguing to determine if the product of SNOG_00308.2 is required for pathogenicity. G-alpha proteins have been extensively studied in fungi (Lafon et al. 2006) and many are required for pathogenicity. Distinct roles for three g-alpha genes have been revealed in M. grisea, A. nidulans and N. crassa. It was therefore a surprise to find a fourth g-alpha gene in the S. nodorum genome. This gene (SNOG_06158.2) was shown to be expressed in vitro and in planta. It was investigated by gene disruption and its loss resulted in no discernable phenotype (data not shown). A fourth g-alpha protein has been recently identified in both A. oryzae (Lafon et al. 2006) and Ustilago maydis (Kamper et al. 2006), but neither shows significant sequence similarity to that of S. nodorum. Indeed SNOG_06158.2 is most similar to Gba3 amongst the U. maydis g-alphas and GpaB amongst the A. oryzae genes.

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Table 7. Potential Orthologs of S. nodorum PKS Genes

Domain/Module Domain/Module Inferred Clade Inferred Function Ortholog SN15 PKS Structure Best Hit Accession Organism Reciprocal Similarity Structure fg12100 F. graminearum No 21.60% KsAtAcp/KrAcp/Acp SNOG_00477.2 KsAtKrAcp PKS25 AAR90279 C. heterostrophus Yes 59.70% fungal 6MSAS KsAtKrAcp 6-methylsalicylic acid synthesis atX BAA20102 A. terreus Yes 69.00% KsAtKrAcp fg12109 F. graminearum No 42.10% KsAtErKrAcp reduc PKS Synthesis diketide moiety SNOG_02561.2 KsAtErKrAcp PKS3 AAR90258 C. heterostrophus Yes 45.80% KsAtErKrAcp clade I compactin or similar polyketide. mlcB BAC20566 P. citrinum Yes 47.70% KsAtDhErKrAcp fg05794 F. graminearum Yes 38.90% KsAtAcp/ErKrAcp reduc PKS SNOG_04868.2 KsAtErKrAcp PKS6 AAR90261 C. heterostrophus No 46.50% KsAtErKr Synthesis squalestatin clade I typeI PKS AAO62426 Phoma sp. C2932 No 49.80% KsAtErKrAcp fg12109 F. graminearum Yes 43.10% KsAtErKrAcp reduc PKS SNOG_05791.2 KsAtErKrAcp PKS5 AAR90261 C. heterostrophus Yes 73.10% KsAtErKr Synthesis alternapyrone clade I atl5 BAD83684 A. solani Yes 79.20% KsAtErKrAcp fg01790 F. graminearum No 31.30% KsAtErKrAcp reduc PKS SNOG_06676.2 KsAtErKr PKS14 AAR92221 G. moniliformis No 31.80% KsAtErKr Synthesis fumonisin clade IV FUM1 AAD43562 G. moniliformis No 30.00% KsAtErKrAcp fg03964 F. graminearum No 36.20% KsAtAcp non-reduc PKS SNOG_06682.1 KsAtAcp PKS17 AAR90253 B. fuckeliana Yes 43.90% KsAtAcp Synthesis citrinin clade III pksCT BAD44749 M. purpureus Yes 44.70% KsAtAcp fg12100 F. graminearum No 37.80% KsAtAcp/KrAcp/Acp reduc PKS Synthesis polyketide similar to SNOG_07866.2 KsAtKr PKS16 AAR90270 C. heterostrophus Yes 67.90% KsAtKr clade II citrinin/lovastatin. EqiS AAV66106 F. heterosporum Yes 39.80% KsAtKrAcp/Acp fg12040 F. graminearum No 40.30% KsAtAcp non-reduc PKS Synthesis perithecial pigment, SNOG_08274.2 KsAcp/AtAcp/Acp PKS12 AAR90248 B. fuckeliana No 44.50% KsAtAcp/Acp clade II autofusarin or similar polyketide PKS AAS48892 N. haematococca No 47.80% KsAtAcp/Acp fg12125 F. graminearum Yes 41.20% KsAtAcp/Acp non-reduc PKS Synthesis perithecial pigment, SNOG_08614.2 KsAtAcp/Acp/Te PKS3 AAR92210 G. moniliformis No 49.30% KsAtAcp/Acp clade I cercosporin or similar polyketide. PKS AAT69682 C. nicotianae No 60.70% KsAtAcp/Acp fg01790 F. graminearum No 58.90% KsAtErKrAcp reduc PKS SNOG_09623.2 KsAtAcp/ErKrAcp PKS11 AAR90266 C. heterostrophus Yes 56.10% KsAtErKrAcp Synthesis fumonisin clade IV FUM1 AAD43562 G. moniliformis Yes 57.70% KsAtErKrAcp fg12055 F. graminearum No 43.20% KsAtErKrAcp reduc PKS High virulence; synthesis T-toxin; SNOG_11066.2 KsKsAtErKrAcp PKS8 AAR90244 B. fuckeliana Yes 59.70% KsAtErKrAcp clade III zearalenone PKS2 ABB76806 C. heterostrophus Yes 44.90% KsAtErKrAcp fg01790 F. graminearum Yes 62.80% KsAtErKrAcp reduc PKS SNOG_11076.2 KsAtDhErKrAcp PKS14 AAR90268 C. heterostrophus Yes 82.70% KsAtDHErKrAcp Synthesis fumonisin clade IV FUM1 AAD43562 G. moniliformis No 53.90% KsAtErKrAcp fg12055 F. graminearum No 44.70% KsAtErKrAcp Synthesis zearalenone or similar reduc PKS SNOG_11272.2 KsKsAtErKrAcp PKS14 AAR92221 G. moniliformis Yes 48.70% KsAtErKr polyketide. Similar to HR type clade IV PKSKA1 AAY32931 Xylaria sp. BCC 1067 No 47.30% KsAtErKrAcp PKS fg12040 F. graminearum Yes 54.90% KsAtAcp non-reduc PKS SNOG_11981.2 KsAtAcp/Acp/Acp/Te PKS18 AAR90272 C. heterostrophus Yes 85.70% KsAtAcp/Acp/Te Synthesis melanin clade II PKS1 BAD22832 B. oryzae Yes 88.20% KsAtAcp/Acp/Te fg10548 F. graminearum No 39.70% KsAtErKrAcp reduc PKS SNOG_12897.2 KsAtErKr PKS5 AAR92212 G. moniliformis No 38.20% KsAtAcp/ErKrAcp Synthesis alternapyrone clade I alt5 BAD83684 A. solani No 37.80% KsAtErKrAcp fg01790 F. graminearum No 40.40% KsAtErKrAcp reduc PKS SNOG_13032.2 KsAtAcpKr PKS12 AAR92219 G. moniliformis No 45.10% KsAtAcp/Acp/ErKrAcp Synthesis fumonisin clade IV FUM1 AAD43562 G. moniliformis No 39.10% KsAtErKrAcp fg01790 F. graminearum No 44.30% KsAtErKrAcp reduc PKS Synthesis diketide moiety SNOG_14927.2 KsAtDhKrAcp PKS15 AAR90269 C. heterostrophus No 43.50% KsAtAcp/ErKrAcp clade IV compactin PKS BAC20566 P. citrinum No 39.10% KsAtDhErKrAcp fg12040 F. graminearum No 42.20% KsAtAcp Synthesis melanin, autofusarin or SNOG_15829.2 KsAtAcp PKS1 BAD22832 B. oryzae No 41.30% non-reduc PKS KsAtAcp/Acp/Te similar polyketide PKS14 AAR90250 B. fuckeliana No 67.60% KsAtAcp/Acp fg10548 F. graminearum No 43.90% KsAtErKrAcp reduc PKS SNOG_15965.2 KsAtErKrAcp PKS10 AAR90246 B. fuckeliana Yes 68.80% KsAtErKrAcp Synthesis fumonisin clade IV PKSKA1 AAY32931 Xylaria sp. BCC 1067 No 54.70% KsAtErKrAcp

Domain abbreviations; Acyl-carrier protein domain ACP; Acetyl transferase At; Dehytratase Dh; Enoyl Reductase Er; Keto Reductase Kr; Keto Synthase Ks; Thioesterase Te. Potential orthologs to polyketide synthases C. heterostrophus and F. graminearum (Kroken et al., 2003; Gaffoor et al., 2005) and by best informative hit to NR at NCBI of e-value < 1x10-10. Domain structure and modular organisation for all sequences was determined via the online NRPS-PKS database (Ansari et al., 2004). It should be noted that domain structure predictions may vary slightly from those stated in the original studies. Percent similarity of ortholog pairs was determined (Needleman and Wunsch, 1970) via NEEDLE (Rice et al., 2000). References for ortholog function: 6-methylsalicylic acid synthesis (Fujii et al. 1996); synthesis diketide moiety compactin or similar polyketide (Abe et al. 2002a and 2002b); synthesis diketide (Abe et al. 2002a and 2002b); synthesis squalestatin (Nicholson et al. 2001); synthesis alternapyrone (Fujii et al. 2005); synthesis fumonisin (Schimlzu et al. 2005; Proctor et al. 1999); Synthesis citrinin (Schimlzu et al. 2005); synthesis perithecial pigment, autofusarin or similar polyketide (Graziani et al. 2004; Chung et al. 2003); high virulence, synthesis T-toxin, zearalenone (Gaffoor et al. 2005; Baker et al. 2006); Synthesis melanin (Moriwaki et al. 2004).

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G-alpha proteins transduce extracellular signals leading to infection-specific development (Solomon et al. 2004b). Pth11 and ACI1 are two M. grisea genes encoding transmembrane receptors that defined a new protein domain, CFEM (Kulkarni et al. 2003) with roles in g- protein signalling. M. grisea has nine CFEM domain proteins and F. graminearum has eight. Using a combination of domain searches and blast searches seeded with the M. grisea and F. graminearum genes, we identified a total of six related genes (Table 8). Four of these have at least a weak match to the CFEM domain but only three are predicted to be transmembrane proteins. SNOG_09610.2 appears to be the ortholog of Pth11 and the F. graminearum gene fg05821, suggesting these genes are ancient and conserved. Pth11 is required for appressorial development and perception of suitable surfaces (DeZwaan et al. 1999). Neither S. nodorum nor F. graminearum form classical appressoria (Solomon et al. 2006b) suggesting that the genes have different functions in these species. SNOG_05942.2 is also closely related to Pth11. Knockout strains for this gene were obtained but had no obvious phenotype (data not shown). SNOG_03589.2 is also related to Pth11, and appears to be a transmembrane protein but lacks the CFEM domain. Both SNOG_08876.2 and SNOG_15007.2 possess CFEM- domains and a signal peptide but do not appear to be integral membrane proteins. Knockout strains for SNOG_08876.2 were obtained but revealed no obvious phenotype (data not shown). SNOG_15007.2 is similar to glycosylphosphatidylinositol-anchored CFEM- containing proteins from three other fungal species. It appears to be heavily expressed both in the oleate and in planta EST libraries with 17 and 27 ESTs respectively. A clear role for this gene is as yet unknown. CFEM-domain proteins are thought to be involved in surface signal perception and three candidates for this role have been identified. The paucity of such genes in S. nodorum and lack of phenotype associated with deletion of two of them suggests that this function may be covered by a different class of transmembrane receptors. Hydrophobins are small, secreted proteins with eight Cys residues in a conserved pattern that coat the fungal mycelium and spore (Wessels 1994). Class 2 hydrophobins are restricted to ascomycetes, whereas class 1 hydrophobins are also found in other fungal divisions (Linder et al. 2005). Two class 2 and no class 1 hydrophobin genes were found in the S. nodorum genome (See Supplemental Figure 1 online). This is the first example of an ascomycete genome with only class 2 hydrophobin genes. It is interesting to note that although a range of Neurospora species all contained a gene orthologous to the class 1

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hydrophobin EAS gene from N. crassa, they were expressed significantly only in species that produced aerial conidia (Winefield et al. 2007). S. nodorum produces pycnidiospores in a gelatinous cirrhus adapted for rain-dispersal (Solomon et al. 2006b). It may be that the absence of aerial mitosporulation negates the need for class 1 hydrophobins. Two rhodopsin-like genes were found in the genome, one of which is similar to the bacteriorhodopsin-like gene found in L. maculans that is a proton pump (Sumii et al. 2005). The likely physiological roles of these genes are currently under investigation.

Table 8. Potential orthologs of S. nodorum CFEM proteins identified by matches to PFAM domain PF05730 and best hit to M. grisea and F. graminearum CFEM proteins

a In addition to HMMER matches to PFAM accession PF05730 (using gathering cutoffs), CFEM domain containing proteins from Magnaporthe grisea (BROAD release 5: MGG_01149.5, MGG_01872.5, MGG_05531.5, MGG_05871.5, MGG_06724.5, MGG_06755.5, MGG_07005.5, MGG_09570.5, MGG_10473.5) and Fusarium graminearum (FGDB: fg00588, fg02077, fg02155, fg02374, fg03897, fg05175, fg05821, fg08554) were used as seeds to identify putative CFEM proteins by their best blastp match with an e-value < 1x10-10 to S. nodorum. b,c Cellular location was determined with WoLF PSORT (Horton et al. 2007) and presence of transmembrane spanning regions (7tm) were determined by consensus between TMHMM (Krogh et al., 2001), TMPRED (Hofmann and Stoffel, 1993) and Phobius (Kall et al., 2004). Best hits of Stagonospora CFEM proteins to the non-redundant protein database at NCBI was determined by ‘informative’ blastp hits of e-value < 10-10 (hits excluding seed and self hits, which are not hypothetical or unknown and preferentially yield useful functional information).

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The interaction between a pathogen and its host is to a large extent orchestrated by the proteins that are secreted or localized to the cell wall or cell membrane. Pathogens such as M. grisea, which kill and degrade host tissues, have been shown to secrete large numbers of degradative enzymes (Dean et al. 2005). More surprisingly, the biotrophic pathogen U. maydis was also found to secrete many proteins; many of the genes are clustered, coexpressed and required for normal pathogenesis but are of unknown molecular functions (Kamper et al. 2006). We have therefore analyzed the putative proteome of S. nodorum for potentially secreted proteins and compared them with these pathogens and the saprobe N. crassa. A total of 1782 proteins were predicted to be extracellular based on predictions using WoLFPSORT; a further 1760 were predicted to be plasma membrane locatede (See Supplemental Data Set 2 online). GO annotations were assigned via Blast2GO for 551 of the putatively extracellular proteins (Table 9). They are dominated by carbohydrate and protein degradation enzymes as would be expected and which is consistent with the EST analysis (see below). The role of many fungal extracellular proteins is currently unknown. Among the S. nodorum predicted extracellular proteins, 1231 had no GO annotation. Of these, only 410 had significant matches to putatively extracellular proteins from U. maydis, M. grisea, or N. crassa (Figure 3). More of these 410 genes had homologs in M. grisea (13 + 91 = 104) than in N. crassa (3 + 39 = 42). As M. grisea and N. crassa are phylogenetically equidistant from S. nodorum, this suggests both that the pathogens secrete more proteins than N. crassa and that the genes are related. Expanding this generalization will require genome analysis of a saprobic dothideomycete. A further 251 genes (89 + 162) had homologs in both M. grisea and N. crassa. Another 118 S. nodorum putatively secreted genes of unknown function had significant similarity to genes encoding the U. maydis secretome, including 13 that uniquely hit the biotrophic basidiomycete. We found no obvious patterns of clustering of any of these secreted genes. The most striking finding was that 821 genes had no significant similarity to predicted extracellular proteins of any of these fully sequenced genomes. These large numbers of putatively secreted proteins of mostly unknown functions, whose genes appear to be rapidly evolving, points to a hitherto unsuspected complexity and subtlety in the interaction between the pathogen and its environments. One newly recognized aspect of S. nodorum is the production of secreted proteinaceous toxins. SNOG_16571.2 encodes a host-specific protein toxin called ToxA that determines the

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interaction with the dominant wheat disease susceptibility gene Tsn1 (Friesen et al. 2006; Liu et al. 2006). Population genetic evidence suggests that this gene was interspecifically transferred to the wheat tan spot pathogen, P. tritici-repentis, prior to 1941, thereby converting a minor into a major pathogen. An RGD motif that is involved in import into susceptible plant cells is required for activity (Meinhardt et al. 2002; Manning et al. 2004; Manning and Ciuffetti 2005). Biochemical and genetic evidence suggests that S. nodorum isolates contain several other proteinaceous toxins (Liu et al. 2004a and 2004b). ToxA is a 13.2-kD protein, and current research indicates that the other toxins are also small proteins. Among the predicted extracellular proteins, 840 are smaller than 30 kD and 26 have an RGD motif (see Supplemental Data Set 2 online). Analysis of these toxin candidates is underway.

Table 9. The most abundant gene ontologies associated with the predicted secretome

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Gene Expression during Infection. When analyzed by biological process and molecular function, the in planta EST library was dominated by genes involved in the biosynthesis of proteins and in the degradation and use of extracellular proteins and carbohydrates, specifically cellulose and arabino-xylan (Table 3; see Supplemental Table 5 online). The secretion of proteases (Bindschedler et al. 2003), xylanases, and cellulases suggests that the fungus catabolizes plant proteins and carbohydrates for energy in planta at this late stage of infection. Studies in a range of pathogens suggest that early infection is characterized by the catabolism of internal lipid stores and that mid stages are characterized by the use of external sugars and amino acids (Solomon et al. 2003a). These studies of late infection suggest that polymerized substrates are used after the more easily available substrates are exhausted and provide a novel perspective to in planta nutrition. The abundance of transcripts linked to protein synthesis indicates that this process is very active during this stage of infection and may be related to the massive secretion of degradative enzymes and to the synthesis of proteins needed for sporulation. A similar picture was observed when the genes were analyzed by cellular component (Table 3) with gene products destined for the ribosome dominating. Genes whose products are targeted to the nucleolus and cytoskeleton illustrate the importance of nuclear division and cytokinesis at this stage of infection as many new cell types are elaborated in the developing pycnidium. Thirty-six gene products targeted to the extracellular region include a protease, an a-glucuronidase, and various glucanases consistent with the picture of polymerized substrate breakdown. Late-stage infection has rarely been examined in plant-fungal interactions, and it is therefore noteworthy that upregulation of transcripts involved in protein synthesis was also observed in late-stage infections of wheat by M. graminicola (Keon et al. 2005). The high rate of protein synthesis may be required for pycnidial biogenesis and may also represent an attractive target for fungicidal intervention. The oleate EST library was dominated by genes involved in lipid and malate metabolism, the trichloroacetic acid cycle, and electron transport. To determine whether the ratio of ESTs in the in planta and oleate libraries was indicative of early- and late stage infection, transcript levels from eight candidate genes were determined by a quantitative PCR. The genes were chosen from those found exclusively in the in planta library. Transcripts were quantified in cDNA pools made from RNA isolated from in vitro and in planta growth of SN15 at early

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and late infection time points. The in vitro cultures sampled at 4 DAI did not contain any pycnidia, whereas cultures sampled at 18 DAI were heavily sporulating with many pycnidia. To isolate RNA from both early and late infections of wheat, an SN15 infection latent period assay was used to provide in planta infection transcripts (Solomon et al. 2003b). Lesions were excised after 8 and 12 DAI, representing early and late infection stages. The three genes most upregulated during growth in planta (SNOG_00557.2, SNOG_03877.2, and SNOG_16499.2) all had less than 20 in planta ESTs, indicating that the EST frequencies were useful predictors of gene expression at these levels. SNOG_00557.2 was the gene with the highest peak expression level in planta and the largest difference between in vitro and in planta conditions. As the gene is predicted to be an arabinofuranosidase, this reaffirmed the important role of carbohydrolases during colonization of the host tissue. Overall, the four tissue types represented clear states of nonsporulation and sporulation during both in vitro and in planta growth. All the genes were found to be expressed in the 12-DAI infected sample, and this was the highest level observed in all but one case (see Supplemental Figure 2 online). On the other hand, moderate to high levels of gene expression were found in the in vitro samples from six of the eight genes. Attempts to use axenic samples to mimic infection has a long history (Coleman et al. 1997; Talbot et al. 1997; Solomon et al. 2003a; Trail et al. 2003; Thomma et al. 2006). Our data indicate that oleate feeding is not a significantly closer model for infection than starvation has proved to be.

Genome Architecture. Colinearity of gene order is a notable feature of closely related plant and animal genomes but is represented in fungi by a complex pattern of dispersed colinearity, such as observed between Aspergillus spp (Galagan et al. 2005). This low degree of organizational conservation can be attributed to the 200 million year separation of these species and the rarity of meiotic events that would tend to maintain chromosomal integrity. S. nodorum is the first dothideomycete to have its sequence publicly released; thus, the closest species for which whole-genome comparisons could be made are the Aspergilli and N. crassa, which are separated from S. nodorum by approximately 400 million years of evolution. Thus far, we have been unable to detect significant regions of colinearity with other sequenced genomes, but it is possible that more sensitive methods and the release of

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more closely related genome sequences will succeed in revealing patterns of chromosomal level evolution.

Figure 4. Collinearity between S. nodorum SN15 and L. maculans identified by tBLASTX. (A) Mating type locus. (B) A 38-kb region of L. maculans.. Colours indicate an orthologous relationship between genes, whereas black indicates no relationship. Numbers in red give coordinates on the S. nodorum scaffold.

At a smaller scale, the mating type loci of L. maculans, C. heterostrophus, A. alternata, and M. graminicola have been previously analyzed (Cozijnsen and Howlett 2003). Apart from Mat1-1 and orf1, the only shared genes were a DNA ligase gene found in L. maculans and M. graminicola and Gap1 found in L. maculans and C. heterostrophus. The colinearity between L. maculans and S. nodorum is more complete. Fig. 4A shows the relationship of gene order and orientation between these sibling species. It is clear that gene order and orientation are conserved, though the intergenic regions have no discernable relationships. This confirms the close phylogenetic relationship between these species, with S. nodorum closest to L. maculans and more distantly related to C. heterostrophus. There is tantalizing evidence of residual colinearity of the genes present in a contiguous 38-kb region of L. maculans DNA (Idnurm et al. 2003). Six of the nine L. maculans genes

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have orthologs within a 200-kb region of S. nodorum DNA. Gene orientation is retained, but they are interspersed with about 60 other predicted genes (Fig. 4b).

Figure 5. Organization of quinate cluster from severeal sequenced fungal genomes. Numbers under the S. nodorum genes refer to the SNOG identifiers. The S. nodorum genes are located on scaffold 19 and 12, respectively

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A different pattern of colinearity is apparent in the quinate gene cluster. The quinate genes regulate the catabolism of quinate and have a wide distribution in filamentous fungi (Giles et al. 1991). The cluster comprises seven coregulated genes. In some cases, portions of the cluster are repeated at other genomic locations. In S. nodorum, the main cluster is located on scaffold 19 with two genes on scaffold 12. Fig. 5 shows the relationship of gene content and order in six fungal species. As the species for comparison span 400 million years of evolution, it is apparent that clustering of these genes per se is highly conserved. However, the gene order and orientation shows no conservation apart from the constant juxtaposition of homologs of Qa-1S and Qa1-F and of Qa-X and Qa-2. Even in these cases, though, some are 5’ to 5’ and others are 3’ to 3’. It appears, therefore, that there must be selection for retention of clustering of these seven genes, even if the exact orientation may not be so important. It may be that such proximity clustering is important in that it enables gene regulation by chromatin remodelling mediated by a gene such as LaeA (Bok and Keller 2004). SNOG_11365.2 is an apparent ortholog of LaeA. Fungi have a truly ancient history, many times longer than that of animals and flowering plants (Padovan et al. 2005). The extent of genetic diversity is correspondingly large. Phylogenetic analysis of fungi has been hampered by a paucity of reliable morphological indicators. As a consequence, phylogenetic reconstruction of the fungi has been particularly unstable until the widespread introduction of multigene-based DNA sequence comparisons. This study confirms the overall monophyletic characters of the Dothideomycetes and the Pleosporales taxa. These groups contain many thousands of species and are notable for their content of major plant pathogens infecting many important plant families. The origins of this class, likely more than 400 million years ago, is considerably older than their plant hosts. It is particularly interesting to note that all the fungal plant pathogens that are well established as host-specific toxin producers are in this class (Stagonospora, Cochliobolus, Pyrenophora, M. zeae-maydis and Alternaria). Taken as a whole, the pathogens in this class are mainly described as necrotrophic, while a few are debatably described as biotrophic (Venturia and C. fulvum) or hemibiotrophic (L. maculans, M. graminicola, and M. fijiensis). None of the species in this class are obligate pathogens, and none possess classical haustoria (Oliver and Ipcho 2004); furthermore, many other species are nonpathogenic. The genome sequence of S. nodorum represents an important point of comparison from which to derive hypotheses about

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the genetic basis of pathogenicity in these organisms. Genome sequences of several of these species are in progress (Goodwin 2004), including A. brassicicola, M. fijiensis, M. graminicola, L. maculans, and P. tritici-repentis, or have been completed but not released (C. heterostrophus; Catlett et al. 2003). Three of these species, S. nodorum, M. graminicola, and P. tritici-repentis, are wheat pathogens. The possibility of multiple pairwise comparisons of gene content between phylogenetically and ecologically close species promises to be a powerful method to derive workably small lists of candidate effector genes controlling pathogenicity, host specificity, and life cycle characters and thus provide ideas for the generation of novel crop protection strategies. The genome sequence provides the tools for global transcriptome analysis, thereby identifying the genes expressed during different phases of infection. This study has also highlighted secreted proteins, which appear to be markedly more numerous than in nonpathogens but which have predominately mysterious roles. Finally, the genome sequence is an essential prerequisite for the critical analysis of hypotheses of interspecific gene transfer. This has already been identified in pathogens in general (Richards et al. 2006) and S. nodorum in particular (Friesen et al. 2006; Stukenbrock and McDonald 2007) and may emerge as a major feature in the evolution of these organisms.

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Supplemental Data

The following materials are available in the online version of this article. Supplemental Figure 1. Aligned Kyte and Doolittle Hydrophobicity Plots. Supplemental Figure 2. Quantitative PCR Analysis of Gene Expression from in Planta- Associated Genes. Supplemental Table 1. Mitochondrial Genes. Supplemental Table 2. Summary of PFAM Domains Used for Identification. Supplemental Table 3. List of Species Used in This Study. Supplemental Table 4. PCR Primers for Abundant in Planta-Associated Genes. Supplemental Table 5. EST Data for Abundant in Planta-Associated Genes. Supplemental Data Set 1. Repetitive Elements: Telomeres, Subrepeats, and Similarity Scores. Supplemental Data Set 2. Gene Summary. Supplemental Data Set 3. Alignments for Fig. 1 as a Noninterleaved Nexus Formatted Text File.

Acknowledgements

Funding was provided by the Australian Grains Research and Development Corporation (UMU14; we particularly thank James Fortune, John Sandow, and John Lovett for their support of this project), by the Swiss Federal Institute of Technology Zurich, by the Swiss National Science Foundation (Grant 3100A0-104145), by MIT, and by the National Science Foundation (DEB-0228725; Assembling the Fungal Tree of Life). We thank Soeren Rasmussen for help with bioinformatics, Robert Lee for the oleate EST library, and Tim Friesen (USDA) for comments on the manuscript. We dedicate this article to the recently retired Chris Caten who has inspired our work on S. nodorum.

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Trail F, Xu JR, San Miguel P, Halgren RG, Kistler HC. 2003. Analysis of expressed sequence tags from Gibberella zeae (anamorph Fusarium graminearum). Fungal Genet Biol. 38:187-197. Vizcaino JA, Cardoza RE, Dubost L, Bodo B, Gutierrez S, Monte E. 2006. Detection of peptaibols and partial cloning of a putative peptaibol synthetase gene from T. harzianum CECT 2413. Folia Microbiol. (Praha) 51:114-120. Wessels JGH. 1994. Developmental regulation of fungal cell wall formation. Annu Rev Phytopathol. 32:413-437. Winefield RD, Hilario E, Beever RE, Haverkamp RG, Templeton MD. 2007. Hydrophobin genes and their expression in conidial and aconidial Neurospora species. Fungal Genet Biol. 44:250-257. Winka K, Eriksson OE. 1997. Supraordinal taxa of Ascomycota. Mol Phylogenet Evol. 1:1- 16. Wolpert TJ, Dunkle LD, Ciuffetti LM. 2002. Host-selective toxins and avirulence determinants: What’s in a name? Annu Rev Phytopathol. 40:251-285. Woo P, et al. 2003. The mitochondrial genome of the thermal dimorphic fungus Penicillium marneffei is more closely related to those of molds than yeasts. FEBS Lett. 555:469-477. Yadav G, Gokhale RS, Mohanty D. 2003. SEARCHPKS: A program for detection and analysis of polyketide synthase domains. Nucleic Acids Res. 31:3654-3658. Yoder OC, Turgeon BG. 2001. Fungal genomics and pathogenicity. Curr Opin Plant Biol. 4:315-321. Yun SH, Turgeon BG, Yoder OC. 1998. REMI-induced mutants of Mycosphaerella zeae- maydis lacking the polyketide PMtoxin are deficient in pathogenesis to corn. Physiol Mol Plant Pathol. 52:53-66. Zhang Z, Schwartz S, Wagner L, Miller W. 2000. A greedy algorithm for aligning DNA sequences. J Comput Biol. 7:203-214. Zolan ME. 1995. Chromosome-length polymorphism in fungi. Microbiol Rev. 59:686-698.

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CHAPTER 5

QoI resistance evolution in European populations of M. graminicola

Stefano FF Torriani, Patrick C Brunner, Bruce A. McDonald, Helge Sierotzki. 2009. QoI resistance emerged independently at least four times in European populations of Mycosphaerella graminicola. Pest Management Science 65:155-162

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Abstract

QoI fungicides or quinone outside inhibitors (also called “strobilurins”) have been widely used to control agriculturally important fungal pathogens since their introduction in 1996. Strobilurins block the respiration pathway by inhibiting the cytochrome bc1 complex in mitochondria. Several plant pathogenic fungi have developed field resistance. The first QoI resistance in Mycosphaerella graminicola was detected retrospectively in UK in 2001 at a low frequency in QoI treated plots. During the following seasons resistance reached high frequencies across northern Europe. The aim of this study was to identify the main evolutionary forces driving the rapid emergence and spread of QoI resistance in M. graminicola populations. G143A mutation causing QoI resistance was first detected during 2002 in all tested populations and in eight distinct mtDNA sequence haplotypes. By 2004, 24 different mtDNA haplotypes contained the G143A mutation. Phylogenetic analysis showed that strobilurin resistance was acquired independently through at least four recurrent mutations at the same site of cytochrome b. Estimates of directional migration rates showed that the majority of gene flow in Europe had occurred in a west-to-east direction. This study demonstrated that recurring mutations independently introduced the QoI resistance allele into different genetic and geographic backgrounds. The resistant haplotypes then increased in frequency due to the strong fungicide selection and spread eastward through wind dispersal of ascospores.

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Introduction

Mycosphaerella graminicola (anamorph: Septoria tritici) is the causal agent of Septoria tritici leaf blotch, one of the most important foliar diseases of wheat in many parts of the world (Hardwick et al. 2001; Bearchell et al. 2005). M. graminicola is a haploid, heterothallic ascomycete, characterized by both sexual and asexual reproduction. Sexual spores play an important role as the primary source of inoculum initiating an epidemic (Shaw et al. 1989; Hunter et al. 1999; Zhan et al. 2001) but they also contribute to secondary infection and can be dispersed over tens of kilometers (Sanderson 1972). The asexual pycnidiospores are disseminated over limited distances from plant to plant via rain splash and they contribute only to the secondary infection (Bannon et al. 1998). M. graminicola was controlled mainly by demethylation-inhibiting (DMI) fungicides until the introduction of strobilurin-based fungicides in 1996. This new class of fungicides provided a superior disease control and additional favorable effects on the physiology of the plant (Fraaije et al. 2003). QoI fungicides act by inhibiting the Qo site of the cytochrome bc1 complex in the mitochondria, thereby blocking the electron transfer process in the respiration chain and causing an energy deficiency due to a lack of adenosine triphosphate (ATP) (Bartlett et al. 2002). In most pathogens, including M. graminicola, resistance towards strobilurins is conferred by a single nucleotide change in the mitochondrial cytochrome b gene (cyt b), leading to an amino acid change at codon 143 from glycine to alanine (G143A) (Gisi et al. 2002). In some fungi, such as Alternaria solani (Pasche et al. 2005) or Pyrenophora teres (Sierotzki et al. 2007) another mutation in cyt b (F129L) was identified, however this mutation results in a less resistant phenotype compared to the G143A mutation (Gisi et al. 2002; Kim et al. 2003). Recently it was postulated that for fungi such as A. solani and P. teres that possess an intron placed directly after G143, the mutation leading to the G143A change cannot occur, because this mutation would strongly affect the splicing process, causing a deficient cytochrome b (Grasso et al. 2006). Other unknown mechanisms leading to resistance to QoI’s were reported in Venturia inaequalis (Steinfeld et al. 2001) and Podosphaera fusca (Fernández-Ortuño et al. 2008). The first QoI resistant isolates of M. graminicola were detected retrospectively in the UK in 2001 at low frequency in QoI treated plots (Fraaije et al. 2005a) and subsequently in 2002

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in five European countries (Gisi et al. 2005). During 2003 and 2004 the frequency of resistant isolates increased rapidly in northern Europe. The resistance is now widespread across the entire UK (Fraaije et al. 2005a), whereas in France and Germany resistance levels are higher in the north than in the south (Gisi et al. 2005). The north-south gradient in resistance distribution is thought to be due to differences in the intensity of QoI use because of lower disease pressure in southern regions. The aim of this study was to clarify the evolutionary mechanisms behind the emergence and spread of QoI resistant isolates in M. graminicola. The main hypotheses tested were:

1. The G143A mutation occurred only once or very few times, potentially in only one mtDNA haplotype and/or one region, and was subsequently distributed to other regions by migration. 2. The G143A mutation occurred independently in several different mtDNA haplotypes and/or geographic regions.

Parallel genetic adaptation to drugs and pesticides was until now widely studied in animals for insecticides (Andreev et al. 1999; Nardi et al. 2006) and nematicides (Elard et al. 1996), in plants for herbicides (Bernasconi et al. 1995) and in bacteria for antibiotics (Barlow and Hall 2003; Hall et al. 2004). However, very little is presently known about the processes driving the development of fungicide resistance alleles in plant pathogens. The unique features of mitochondrial genomes, including their uniparental inheritance, the near absence of genetic recombination, their small size and fixed complement of genes enabled us to clearly differentiate between multiple or single occurrences and origins of fungicide resistance in M. graminicola. To accomplish this, we sequenced three loci of the mtDNA genome and assessed the QoI resistance/sensitivity in each isolate by identifying the presence/absence of the G143A mutation.

Materials and methods

Fungal isolates. Isolates from geographically distinct European populations of M. graminicola were obtained from infected leaves collected from locations in Germany (GER),

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England (UK), Denmark (DN), Ireland (IR) and France (FR). To address the temporal dimension of evolution of QoI resistance, isolates from the same regions -whenever possible- included samples collected before the use of QoI (pre-QoI) and samples collected after the first occurrence of QoI resistant isolates (post-QoI). In total, 181 M. graminicola isolates obtained from infected leaf samples by the methods previously described (McDonald et al. 1994; Linde et al. 2002) were used in this study (Table 1). The pre-QoI isolates from 1992 and 1994 were part of a previously described worldwide collection of M. graminicola (McDonald et al. 1999; Linde et al. 2002; Zhan et al. 2003; Banke and McDonald 2005). The post-QoI isolates from 2002 were supplied by Syngenta Switzerland (Gisi et al. 2005) and the German isolates from 2004 were collected close to Dedelow in the north-eastern German state of Brandenburg (Ger-D) and close to Quarnbek in the north-western German state of Schleswig-Holstein (GER-Q) (Brunner et al. 2008).

PCR-RFLP to detect the QoI resistant allele. All 181 isolates were assayed using a PCR-RFLP approach to detect the QoI-resistant A143 allele. Using the recently published mitochondrial genome of M. graminicola (EU090238; Torriani et al. 2008), we designed two primers to partially amplify cytb. The total PCR reaction volume was 20 µl per well, containing 10 pmol of each primer (MgcytbF 5’-TCG TTA CTG GTG TTA CAC TTG C-3’ and MgcytbR 5’-GCC ATA ACA TAA TTC TCG CTG TCA CC -3’), 100 µM of each nucleotide, 2 µl of 10x PCR buffer (1x PCR buffer: 10 mM KCl, 10 mM (NH4)2SO4, 20 mM

Tris-HCl, 2 mM MgSO4, 0.1% Triton X-100, [pH 8.8]), 1 U of Taq DNA Polymerase (New England Biolabs, England) and 4 µl of M. graminicola genomic DNA (5 to 10 ng final DNA concentration). Thermal cycling conditions were as follows: initial hold at 96°C for 2 min, 35 cycles of 96°C for 1 min, 50°C for 1 min, 72°C for 1 min. The final products were incubated for 5 min at 72°C. A portion of each PCR product (10 µl) was digested using 1U Fnu4HI (New England BioLabs, England) for 4 h at 37°C. Digests were visualized on a 1% agarose gel with 1x Tris-borate-EDTA (TBE) buffer (Fig. 1).

Sequencing and sequence analysis. The mtDNA loci Mg1, Mg2 and Mg3 (Torriani et al. 2008) were amplified and sequenced for all 181 isolates. Sequences were aligned and edited

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manually using Sequencher 4.5 (Gene Code Corporation, Ann Arbor, MI, USA). The concatenated nucleotide sequences were then collapsed into haplotypes recording insertions and deletions (indels) with the program SNAP Workbench (Table 1 and Fig. 2; Price and Carbone 2005). DnaSP was used to test for recombination within and among the tested loci (Rozas et al. 2003).

Data analysis. We used the Kishino-Hasegawa test (KH test; Kishino and Hasegawa 1989) as implemented in PAUP* 4.0b.10 (Swofford 2002) to test different hypotheses of resistance appearance by comparing tree topologies using the full mtDNA data set (all codon positions). We compared the unconstrained tree obtained by Maximum Likelihood (ML) and Maximum Parsimony (MP) analyses, respectively, to two alternative hypotheses of haplotype genealogy; i) resistant (R) haplotypes were assumed to be monophyletic, ii) sensitive (S) haplotypes were assumed to be monophyletic. Results and probability values (two-tailed test) were obtained through 1000 nonparametric bootstrap replicates and the “full optimization” criterion (Table 2). Classic estimates of migration rates assume that populations have reached equilibrium between drift and migration and are of equal size. However, the historical time frame we are investigating is likely too short for haplotypes drawn from populations to have sorted into distinct lineages (Avise 2001) and hence, these populations are probably not in equilibrium. Thus, we applied the likelihood-based coalescent method implemented in MIGRATE version 2.1.3 (Beerli and Felsenstein 2001), which does not rely on the assumption of populations in equilibrium or equal population size, and therefore provides a biologically more realistic approach. Furthermore, MIGRATE estimates asymmetric/directional gene flow among populations, making this approach particularly useful in epidemiological settings. Following the authors’ recommendations, we made a first MIGRATE run with the default values using FST to find the starting parameters for the four tested populations (UK-1994, DN-1994, GER-Q-2004 and GER-D). Parameters obtained from this initial run were used to re-run the program with the following Markov chain settings; short chains 10, long chains 3, averaging over 3 replicates and a 4-chain heating scheme.

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Table 1. Characterization of mtDNA haplotypes found in Mycosphaerella graminicola isolates. The number of isolates is shown in parentheses.

GER(20) UK (44) DN (13) UK (6) IR (5) DN (1) FR (9) GER-Q (49) GER-D (34) a Haplotype 1992 1994 2002 2004 R (70) S (111) H1 (5) - 2 - - - - - 1 2 1 4 H2 (11) 4 4 - - - - 2 1 - 1 10 H3 (28) 6 8 2 - - - 1 7 4 8 20 H4 (19) 3 2 1 - - - - 6 1 6 6 13 H5 (2) 1 - 1 ------2 H6 (8) - 3 - - - - 1 2 2 3 5 H7 (2) - 2 ------2 H8 (4) ------3 1 3 1 H9 (1) ------1 - 1 H10 (2) - - - - - 1 - - 1 1 1 H11 (1) ------1 - 1 H12 (1) ------1 - 1 - H13 (4) ------4 - 4 - H14 (1) - 1 ------1 H15 (1) ------1 1 - H16 (4) - 2 1 - - - - - 1 - 4 H17 (1) ------1 - 1 - H18 (2) ------2 - - 2 - H19 (1) ------1 - 1 H20 (2) ------1 1 2 - H21 (1) ------1 1 - H22 (3) - 2 1 ------3 H23 (5) - 2 - - 3 - - - - 3 2 H24 (8) - 2 3 2 - - - 1 - 3 5 H25 (2) 1 1 ------2 H26 (1) - 1 ------1 H27 (1) - 1 ------1 H28 (6) 2 - 3 - - - 1 - - - 6 H29 (1) 1 ------1 H30 (1) - 1 ------1 H31 (1) - 1 ------1 H32 (1) ------1 - 1 - H33 (21) 1 3 - 2 2 - - 11 2 13 8 H34 (1) ------1 - 1 H35 (1) ------1 - 1 - H36 (1) - 1 ------1 H37 (1) ------1 - 1 H38 (1) ------1 - - - 1 H39 (1) - 1 ------1 H40 (1) - 1 ------1 H41 (5) - 1 1 1 - - - 1 1 2 3 H42 (1) ------1 1 - H43 (2) 1 ------1 - 2 H44 (1) ------1 - 1 H45 (1) ------1 - 1 - H46 (1) ------1 - 1 - H47 (1) ------1 - 1 - H48 (3) ------1 2 3 - H49 (4) - 1 - - - - 1 1 1 3 1 H50 (1) ------1 - 1 - H51 (1) - 1 ------1 H52 (1) - - - 1 - - - - - 1 - a Resistant isolates are in bold text

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Results

A total of 181 strains were analyzed, including 111 sensitive and 70 resistant isolates (Table 1). The first QoI resistant isolates were found in 2002 in four sampled locations. All 77 pre- QoI samples were sensitive and 67% of post-QoI isolates were resistant. In 2004, GER-Q had only one sensitive isolate while GER-D had 71% sensitive isolates (Table 1, Fig. 3a). The concatenated sequences of the 181 analyzed isolates collapsed into 52 nucleotide haplotypes, designated as H1 to H52 (Table 1 and Fig. 4), of which 29 included a single isolate and ten included at least five isolates (Table 1; Fig. 2). The ten most frequent haplotypes represented 64% of all isolates, including 69% of the pre- and 54% of the post- QoI isolates. The remaining 42 “rare” haplotypes had on average 1.55 isolates per haplotype. The program DNAsp did not detect any recombination events within or between the tested mitochondrial loci Mg1, Mg2 and Mg3. Nine of the ten most frequent haplotypes acquired the resistance mutation independently; with only haplotype H28 having all sensitive isolates (Fig. 2). Twelve mtDNA sequence haplotypes had both resistant and sensitive strains, 24 haplotypes were exclusively sensitive and 16 were exclusively resistant. Resistant isolates were first detected in 2002 in all tested geographical populations and belonged to 8 distinct mtDNA sequence haplotypes out of 13 total mtDNA haplotypes detected in that year. In 2002, none of the resistant sequence haplotypes were found in more than one population. Two years later, 24 sequence haplotypes out of the 33 detected were resistant and four of these haplotypes were found previously in 2002. We used the KH-tests to statistically assess different hypotheses of haplotype evolution by comparing tree topologies. In both the ML and MP topologies the unconstrained trees performed significantly better then the two alternative hypotheses, where trees with R- haplotypes or S-haplotypes were considered monophyletic, respectively (Table 2). The unconstrained ML tree formed an unrooted cladogram and identified four major clades, all of which consisted of a mixture of R, S and mixed (RS) haplotypes (Fig. 4). Estimates of directional migration rates indicated that the majority of gene flow in Europe had occurred in a west-to-east direction (Table 3, Fig. 3b). For example, estimates of gene flow were high (Nm = 86) from the UK to GER-Q, whereas there was no or little detectable

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gene flow in the opposite direction. Similarly, gene flow was 10 times higher from GER-Q into GER-D than in the opposite direction.

Table 2. Kishino-Hasegawa tests to statistically assess different hypotheses of haplotype evolution by comparing tree topologies as implemented in PAUP. The unconstrained tree topologies obtained by Maximum Likelihood and Maximum Parsimony analyses, respectively, were compared to two alternative hypotheses of haplotype genealogy; i) resistant (R) haplotypes were assumed to be monophyletic, ii) sensitive (S) haplotypes were assumed to be monophyletic. Probabilities (P) of obtaining better trees were assessed using two-tailed tests, the full optimization criterion and 1000 bootstrap replicates.

Tree Tree score Probability Maximum Likelihood -ln L -ln L diff P unconstrained 1042.71823 best R-constrained 1072.48505 29.76681 0.016* S-constrained 1072.48506 29.76683 0.016*

Maximum Parsimony Length Length diff unconstrained 1158 best R-constrained 1207 49 < 0.001* S-constrained 1216 58 < 0.001* * P < 0.05

Figure 1. PCR-RFLP analysis of the cytb-locus for detection of the A143 strobilurin-resistant allele. a) The G143A mutation causes a second Fnu4HI restriction site in cyt b, conferring resistance to strobilurin. Molecular sizes are indicated in each fragment. b) An example of the PCR-RFLP results for two sensitive (S) and two resistant (R) isolates. The first lane is a 100-bp size ladder (M). The size of the digested products is shown.

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Closer inspection of the dynamics of individual haplotypes revealed some interesting patterns. H3 was the most common sequence haplotype (15.5%), found in six of the nine sampled populations and in four of the five countries sampled (Table 1, Fig. 2). H3 was the most frequent haplotype in the pre-QoI samples and the third most common in the post-QoI samples. H4 was the only sequence haplotype including resistant and sensitive individuals in the same population. The ten most frequent sequence haplotypes did not show a clear pattern of geographical association. Only H23 and H28 could be identified as “local” haplotypes, because H23 was never found on continental Europe, while H28 was found only on the continent. H28 had a frequency of 15.1% in GER-1992 and DN-1994 populations, but was not present in the post-QoI samples of GER-Q and GER-D. This haplotype showed the strongest decrease in frequency after the introduction of strobilurins. H33 was the most frequent haplotype within post-QoI samples (16.3%), tripling in frequency compared to the pre-QoI period.

Figure 2. Comparison of sensitive (S, black) and resistant (R, grey) isolates belonging to the most frequent mitochondrial haplotypes (at least five isolates).

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Figure 3. a) Geographical locations of the six sampled post-QoI Mycosphaerella graminicola populations. The total number of isolates assayed for each population is indicated in the circles, which also show the frequencies of sensitive (black) and resistant (grey) strains. All pre-QoI populations were completely sensitive to strobilurins b) Migration patterns of Mycosphaerella graminicola among populations. Arrows sizes are proportional to the migration rate. Absence of an arrow indicates no or little detected migration (Nm < 0.5).

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Discussion

The main result of this study was to unequivocally demonstrate that QoI resistant M. graminicola isolates arose independently in different genetic and geographic backgrounds, falsifying the hypothesis that a single mutant haplotype emerged and subsequently spread across other regions in Europe. This finding indicates that recurring mutations introduced the resistance allele into several distinct mtDNA haplotypes, which then increased in frequency due to the strong fungicide selection, and spread eastward through wind dispersal of ascospores. Since the introduction of QoI fungicides into the cereal market in 1996, QoI fungicide resistant isolates were detected in field populations of a wide range of pathogen species, including Blumeria graminis f. sp. tritici and hordei (Sierotzki et al. 2000) and Pyrenophora tritici-repentis (Sierotzki et al 2007). Resistance in M. graminicola emerged simultaneously in several locations during 2002, with a rapid increase in the frequency of resistant isolates during the two following seasons, reaching especially high levels in Northern Europe (Gisi et al 2005), where the G143A resistance allele was found in more than half of the identified mtDNA sequence haplotypes (Table 1, Fig. 4). The hypothesis that the mutations to resistance emerged independently in different genetic backgrounds is clearly supported by the unconstrained ML tree (Fig. 4), which shows that in M. graminicola the A143-allele was acquired through at least four distinct mutational events. Similar findings for the parallel emergence of fungicide resistance were identified for the grape pathogen Plasmopara viticola (Chen et al. 2007). This is the first time that intraspecific parallel evolution of fungicide resistance has been demonstrated for a cereal pathogen and it confirms previous results from P. viticola suggesting that “de novo” appearance of a resistance allele in distinct genetic backgrounds may be common for plant pathogenic fungi. The interspecific parallel evolution of resistance alleles was previously shown across a wide range of plant pathogens (Grasso et al 2006). No mutants were found when screening a worldwide collection of 1000 pre-QoI field isolates of M. graminicola for the presence of the A143 resistance allele. Assuming a binomial distribution for the mutation, the 95% confidence interval for the frequency of the G143A mutation in the global population ranged from 0 to 0.003 (McDonald, unpublished).

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Figure 4. Unconstrained Maximum Likelihood tree obtained for all resistant (R, dark-grey hatched), susceptible (S, not hatched) and mixed (RS, soft-grey) mtDNA haplotypes.

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By 2002, eight mtDNA sequence haplotypes acquired the resistance allele. None of these resistance haplotypes were present in more than one population, indicating that 2002 was the starting point for the subsequent rapid emergence of resistant haplotypes. Published data shows that the 143A allele was present at low frequency in QoI treated plots in the UK in 2001 (Fraaije et al. 2005a). The mutation was therefore present at detectable levels prior to 2002 but became much more common in 2002, a year of high Septoria disease pressure in NW Europe. While recurring mutations were important for driving the evolution of strobilurin resistance in M. graminicola, the subsequent role of natural or anthropogenic gene flow should not be underestimated. In fact, directional migration rates clearly showed the importance of gene flow in moving mtDNA haplotypes from Western to Eastern Europe (Table 3, Fig. 3b). The airborne ascospores have the potential to be dispersed over many kilometers (Fraaije et al. 2005b) following the prevailing wind directions across Europe. The same patterns of M. graminicola migration in Europe were found using the nuclear-encoded Cyp51 locus (Brunner et al. 2008). The unique properties of mtDNA allowed us to unequivocally demonstrate the intraspecific parallel evolution of QoI resistance. The lack of recombination found in the mtDNA of M. graminicola using the present and previous dataset (Torriani et al. 2008) means that the G143A mutation had to emerge independently in different genetic backgrounds, instead of being shuffled into different backgrounds through sexual recombination. Most modern pesticides, like DMI fungicides, have as their target nuclear- encoded proteins whose genes are subject to recombination (Brunner et al. 2008). For these resistances, recombination makes it difficult to determine how many times the mutation to resistance occurred because the same mutation can be recombined into many different genetic backgrounds. The results arising from this study provide a better insight into the processes driving the development of fungicide resistance alleles in fungal populations. This study confirms the evidence for the independent multiple acquisition of the resistant allele to a fungicide at the intraspecific level in plant pathogenic fungi, and may provide new perspectives regarding the development of appropriate management strategies.

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Table 3. Pairwise likelihood estimates of directional migration rates between major geographical regions (95% confidence intervals in parenthesis). Donor populations are shown on the left and receiving populations are given along the top. Migration rates are expressed as Nm, the number of immigrants per generation.

UK DN GER-Q GER-D UK  2.33 (0.54 – 5.74) 86.84 (57.67 – 121.55) 0.01(0.00 – 0.01) DN 0.46 (0.06 – 0.84)  16.11 (7.03 – 29.94) 5.52 (0.69 – 9.71) GER-Q 0.25 (0.00 – 0.51) 4.21 (0.65 – 7.12)  37.82 (25.71 – 45.36) GER-D 0.04 (0.00 – 0.10) 0.05 (0.00 – 0.08) 3.58 (0.45 – 5.43) 

Acknowledgements

This project was supported by the Swiss National Science Foundation (grant 3100A0- 104145). The ETH Genetic Diversity Center provided facilities for collecting all DNA sequence data. We thank Andreas von Tiedemann and Christine Schäfer (Georg-August- University of Göttingen) for generously providing isolates from recent German populations.

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Andreev D, Kreitman M, Phillips TW, Beeman RW, French-Constant RH. 1999. Multiple origins of cyclodiene insecticide resistance in Tribolium castaneum (Coleoptera: Tenebrionidae). J Mol Evol. 48:615-624. Avise JC. 1994. Molecular Markers, Natural History and Evolution. Chapman and Hall, 511 pp, New York, USA. Banke S, McDonald BA. 2005. Migration patterns among global populations of the pathogenic fungus Mycosphaerella graminicola. Mol Ecol. 14:1881-1896. Bannon FJ, Cooke BM. 1998. Studies on dispersal of Septoria tritici pycnidiospores in wheat-clover intercrops. Plant Pathol. 47:49-56. Bartlett DW, Clough JM, Godwin JR, Hall AA, Hamer M, Parr-Dobrzanski B. 2002. The strobilurin fungicides. Pest Manag Sci. 58:649-662. Barlow M, Hall BG. 2003. Experimental prediction of the natural evolution of antibiotic resistance. Genetics 163:1237-1241. Bearchell SJ, Fraaije BA, Shaw MW, Fitt BDL. 2005. Wheat archive links long-term fungal pathogen population dynamics to air pollution. Proc Natl Acad Sci USA 102:5438-5442. Beerli P, Felsenstein J. 2001. Maximum likelihood estimation of a migration matrix and effective population sizes in n subpopulations by using a coalescent approach. Proc Natl Acad Sci USA 98:4563-4568. Bernasconi P, Woodworth AR, Rosen BA, Subramanian MV, Siehl DL.1995. A naturally- occurring point mutation confers broad range tolerance to herbicides that target acetolactate synthase. J Biol Chem. 270:17381-17385. Brunner PC, Stefanato FL, McDonald BA. 2008. Evolution of the CYP51 gene in Mycosphaerella graminicola: evidence for intragenic recombination and selective replacement. Mol Plant Pathol. 9:305-316. Chen WJ, Delmotte F, Richard-Cervera S, Douence L, Greif C, Corio-Costet MF. 2007. At least two origins of fungicide resistance in grapevine downy mildew populations. Appl Environ Microb. 73:5162-5172.

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Elard L, Comes AM, Humbert JF. 1996. Sequences of beta-tubulin cDNA from benzimidazole-susceptible and -resistant strains of Teladorsagia circumcincta, a nematode parasite of small ruminants. Mol Biochem Parasitol. 79:249-253. Fernández-Ortuño D, Torés JA, de Vicente A, Pérez-García A. 2008. Field resistance to QoI fungicides in Podosphaera fusca is not supported by typical mutations in the mitochondrial cytochrome b gene. Pest Manag Sci. 64:694-702. Fraaije BA, Burnett FJ, Clark WS, Motteram J, Lucas JA. 2005. Resistance development to QoI inhibitors in populations of Mycosphaerella graminicola in the UK. In: Dehne HW, Gisi U, Kuck KH, Russell PE, Lyr H, eds, Modern Fungicides and Antifungal Compounds IV. pp 63-71 BCPC, Alton, UK. Fraaije BA, Cools HJ, Fountaine J, Lovell DJ, Motteram J, West JS, Lucas JA. 2005. Role of ascospores in further spread of QoI-resistant cytochrome b alleles (G143A) in field populations of Mycosphaerella graminicola. Phytopathology 95:933-941. Fraaije BA, Lucas JA, Clark WS, Burnett FJ. 2003 QoI resistance development in populations of cereal pathogens in the UK. In: The BCPC International Congress-Crop Science & Technology, pp. 689-694. Gisi U, Pavic L, Stanger C, Hugelshofer U, Sierotzki H. 2005. Dynamics of Mycosphaerella graminicola populations in response to selection by different fungicides. In Dehne HW, Gisi U, Kuck KH, Russell PE and Lyr H, eds., Modern Fungicides and Antifungal Compounds IV, pp 73-80, BCPC, Alton, UK. Gisi U, Sierotzki H, Cook A, McCaffery A. 2002. Mechanisms influencing the evolution of resistance to Qo inhibitor fungicides. Pest Manag Sci. 58:859-867. Grasso V, Palermo S, Sierotzki H, Garibaldi A, Gisi U. 2006. Cytochrome b gene structure and consequences for resistance to Qo inhibitor fungicides in plant pathogens. Pest Manag Sci. 62:465-472. Hall BG, Salipante SJ, Barlow M. 2004. Independent origins of subgroup B1 + B2 and subgroup B3 metallo-beta-lactamase. J Mol Evol. 59:133-141. Hardwick NV, Jones DR, Slough JE. 2001. Factors affecting diseases in winter wheat in England and Wales, 1989-98. Plant Pathol. 50:453-432. Hunter T, Coker RR, Royle DJ. 1999. The teleomorph stage, Mycosphaerella graminicola, in epidemics of septoria tritici blotch on winter wheat in the UK. Plant Pathol. 48:51-57.

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Kim YS, Dixon EW, Vincelli P, Farman ML. 2003. Field resistance to strobilurin (QoI) fungicides in Pyricularia grisea caused by mutations in the mitochondrial cytochrome b gene. Phytopathology 93:891-900. Kishino H, Hasegawa M. 1989. Evaluation of the maximum likelihood estimate of the evolutionary tree topologies from DNA sequence data, and the branching order in Hominoidea. J Mol Evol. 29:170-179. Linde C, Zhan J, McDonald BA. 2002. Population structure of Mycosphaerella graminicola from lesions to continents. Phytopathology 92:946-955. McDonald BA, Miles J, Nelson LR, Pettway RE. 1994. Genetic variability in nuclear-DNA in field populations of Stagonospora nodorum. Phytopathology 84:250-255. McDonald BA, Zhan J, Yarden O et al. 1999. The population genetics of Mycosphaerella graminicola and Phaeosphaeria nodorum. In Lucas JA, Bowyer P, Anderson HM, eds., Septoria on Cereals: A Study of Pathosystems, pp 44-69, CABI, Wallingford, UK. Nardi F, Carapelli A, Vontas JG, Dallai R, Roderick GK, Frati F. 2006. Geographical distribution and evolutionary history of organophosphate-resistant ACE alleles in the olive fly (Bactrocera oleae). Insect Biochem Mol Biol. 36:593-602. Pasche JS, Piche LM, Gudmestad NC. 2005. Effect of the F129L mutation in Alternaria solani on fungicides affecting mitochondrial respiration. Plant Dis. 89:269-278. Price EW and Carbone I. 2005. SNAP: workbench management tool for evolutionary population genetic analysis. Bioinformatics 21:402-404. Rozas J, Sanchez-DelBarrio JC, Messeguer X, Rozas R. 2003. DnaSP, DNA polymorphism analyses by the coalescent and other methods. Bioinformatics 19:2496-2497. Sanderson FR. 1972. Mycosphaerella graminicola (Fuckel) Sanderson comb. nov., the ascogenous state of Septoria tritici Rob. and Desm. New Zeal J Bot. 14:359-360. Shaw MW, Royle DJ. 1989. Airborne inoculum as a major source of Septoria tritici (Mycosphaerella graminicola) infections in winter wheat crops in the UK. Plant Pathol. 38:35-43. Sierotzki H, Frey R, Wullschleger J, Palermo S, Karlin S, Godwin J, Gisi U. 2007. Cytochrome b gene sequence and structure of Pyrenophora teres and P. tritici-repentis and implications for QoI resistance. Pest Manag Sci. 63:225-233.

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Sierotzki H, Wullschleger J, Gisi U. 2000. Point-mutation in cytochrome b gene conferring resistance to strobilurin fungicides in Erysiphe graminis f. sp. tritici field isolates. Pest Biochem Phys. 68:107-112. Steinfeld U, Sierotzki H, Parisi S, Poirey S, Gisi U. 2001. Sensitivity of mitochondrial respiration to different inhibitors in Venturia inaequalis. Pest Manag Sci. 57:787-796. Swofford DL. 2002. PAUP*. Phylogenetic Analysis Using Parsimony (and other methods), Version 4. Sinauer Associates, Sunderland, MA. Torriani SFF, Goodwin SB, Kema GHJ, Pangilinan JL, McDonald BA. 2008. Intraspecific comparison and annotation of two complete mitochondrial genome sequences from the plant pathogenic fungus Mycosphaerella graminicola. Fungal Genet Biol. 45:628-637. Zhan J, Mundt CC, McDonald BA. 2001 Using restriction fragment length polymorphisms to assess temporal variation and estimate the number of ascospores that initiate epidemics in field populations of Mycosphaerella graminicola. Phytopathology 91:1011-1017. Zhan J, Pettway RE, McDonald BA. 2003. The global genetic structure of the wheat pathogen Mycosphaerella graminicola is characterized by high nuclear diversity, low mitochondrial diversity, regular recombination, and gene flow. Fungal Genet Biol. 38:286-297.

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CHAPTER 6

Screening for QoI resistance in a global sample of Rhynchosporium secalis

Stefano FF Torriani, Celeste C Linde, Bruce A. McDonald. 2009. Lack of G143A QoI resistance allele and sequence conservation for the mitochondrial cytochrome b gene in a global sample of Rhynchosporium secalis. Australasian Plant Pathology 38:202-207.

Chapter 6 QoI vs R. secalis

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Abstract

Barley scald caused by Rhynchosporium secalis is often controlled by fungicides, most recently by those in the strobilurin-based (QoI) class. Since the launch of QoIs in 1996 a range of important plant pathogens including Blumeria graminis, Mycosphaerella fijiensis and Plasmopara viticola, developed resistance. Present monitoring data indicate that R. secalis populations remain sensitive. The primary molecular mechanism of QoI resistance in several fungi is a point mutation at codon 143 in the mitochondrial encoded cytochrome b gene (cytb), which causes the substitution of glycine by alanine (G143A). We characterized the cytb gene of R. secalis, assessed the intraspecific and interspecific sequence diversity, developed a PCR-RFLP diagnostic tool to detect the most common allele associated with QoI resistance, screened a global collection of 841 R. secalis isolates for this allele and tested a representative sample of isolates for QoI resistance in vitro. The results indicated a high degree of conservation for the cytb gene at both intra- and interspecific levels and complete QoI sensitivity in all R. secalis populations tested.

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Introduction

Rhynchosporium secalis causes an important disease of barley known as leaf blotch or scald. Scald occurs wherever barley is grown and can cause yield losses of 35% or more (Shipton et al. 1974; Khan 1986). In addition to cultivated barley (Hordeum vulgare), R. secalis infects rye and several wild grass species (Caldwell 1937), although the species on rye is most likely a different species (Zaffarano et al. 2006 and 2008). R. secalis overwinters mainly on infected leaves and crop residues which can serve as sources of primary inoculum (Caldwell 1937; Skoropad 1959; Evans 1969; Ayesu-offei and Carter 1974). The pathogen can also infect seed, although seed-borne inoculum may be only a minor source if the seed are treated. Moist conditions and temperatures between 15-20°C favor host infection and disease development, with typical symptoms produced within approximately 14 days (Caldwell 1937; Skoropad 1957; Shipton et al. 1974). Fungicides are used routinely in Europe to control scald and other principal fungal diseases of barley. For example, by the end of the 1980s 90% of the winter barley crop was treated at least once with fungicides (Oerke et al. 1994). Fungicides exhibited varying efficacy against scald and resistance has developed to most fungicides (Cooke et al. 2004). However, some of the newest generation of active ingredients, particularly QoI chemistry types, remain effective. The QoI fungicides have as their specific target the quinol-oxidizing (Qo) site of the mitochondrial cytb protein. The QoI fungicides act by blocking electron transport, thereby inhibiting respiration (Bartlett et al. 2002). A point mutation at codon 143 in the cytb gene leading to an amino-acid change from glycine to alanine (G143A) has been shown to be the major mechanism of resistance to QoI fungicides in Blumeria graminis, Mycosphaerella fijiensis, Plasmopara viticola and other plant pathogenic fungi (Gisi et al. 2000; Sierotzki et al. 2000a and 2000b; Bartlett et al. 2002). Recently another mutation (F129L), conferring only moderate resistance, was identified in other fungi, including Alternaria solani (Pasche et al. 2005) and Pyrenophora teres (Sierotzki et al. 2007). Based on current knowledge, G143A and F129L mutations display different resistance factors (RF = Effective dose 50 [resistant strain] / Effective dose 50 [sensitive wild-type strain]) ranging from 5 to 15 for F129L and usually greater than 100 for G143A (FRAC International, Germany). The amino acid sequence of the cytochrome b protein is highly conserved both

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within and between species, but some synonymous mutations in nucleotide sequences have been found within species (Yokoyama et al. 2001). Generally the only non-synonymous mutations identified within species were those conferring QoI resistance, but some exceptions have been reported (Kim et al. 2003). The QoI fungicides were introduced in 1996 and the first resistance appeared in B. graminis in 1998 (Sierotzki et al. 2000b), followed by Pseudoperonospora cubensis in 1999 (Ishii et al. 2001) and Pyricularia grisea in 2000 (Vincelli and Dixon 2002). More recently QoI resistant isolates have been detected in several other plant pathogens, including P. viticola on grape, Sphaerotheca fuliginea on cucumber, M. fijiensis on banana, Venturia, inaequalis on apple and Mycosphaerella graminicola on wheat (Ma et al. 2003; Fraaije et al. 2005). In the case of P. grisea, analysis of 58 isolates from nine different states in the USA indicated that the cytb mutations encoding resistance were present in the fungal population before the QoI fungicides were introduced (Kim et al. 2003). The sampling strategy in this case was not appropriate to determine the frequency of the resistant mutations in the naïve populations but Fraaije et al. (2002) showed that the frequency of resistant strains of B. graminis could increase from 2% to 58% in a single season following three applications of the fungicide. Thus even very low frequencies of resistant cytb mutations in naïve populations could lead to a rapid loss in effectiveness of the QoI fungicides. Independent multiple origins of the G143A resistance allele were recently documented in two plant pathogenic fungi (Chen et al. 2007; Torriani et al. 2009). Grasso et al. (2006) predicted that the presence of a Type 1 intron located directly after the codon for glycine at position 143 would prevent the emergence of the G143A mutation by blocking proper splicing of the intron. Until now the QoI fungicides have been effective against scald and no resistance has been reported in the field, but it is not known if the lack of resistance is due to the presence of a Type 1 intron after codon 143. If the intron is not present, we consider it most likely that resistance will appear first in areas where QoIs are used most intensively. If resistance appears, a molecular diagnostic tool will be useful to detect and monitor the development and spread of QoI resistance. In anticipation of this need, we set out to develop a diagnostic tool for the QoI resistance allele that is most likely to emerge.

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With the aim of developing a method for detection of the G143A mutation in R. secalis, the objectives of this study were 1) to characterize the cytb gene and determine if it carries an intron directly after the glycine codon at position 143, 2) to determine how much diversity exists in the cytb gene in a selected worldwide collection, 3) to use the developed PCR-RFLP method to search for the G143A mutation in R. secalis populations from around the world and 4) to test a representative sample of isolates for QoI resistance in vitro.

Materials and methods

Fungal isolation and DNA extraction. The isolations of R. secalis analyzed in this project were made from plant leaves as described by McDonald et al. (1999). DNA was extracted following the protocol described by McDonald et al. (1999) and Linde et al. (2003).

Cytochrome b gene sequencing, characterization and intra/interspecific diversity. The cytb gene of R. secalis was identified using a BLASTN search (Basic Local Alignment Search Tool Nucleotide; NCBI, Bethesda, MD) of the sequences arising from a R. secalis mitochondrial DNA library developed in our laboratory. The entire cytb gene of 40 selected R. secalis isolates (Table 1) was PCR-amplified using the primers RscytbF (5’-ACC AAC CAC AGC GAC TTA GAT AG-3’) and RscytbR (5’- TGG GAT AGC AGT ATC CAC ACC-3’). Each PCR mixture contained 5-10 ng of DNA in a 20 µL reaction volume containing 10 pmol of each primer, 100 µM of each nucleotide, 2

µL of 10× PCR buffer (1× PCR buffer: 10 mM KCl, 10 mM (NH4)2SO4, 20 mM Tris-HCl, 2 mM MgSO4, 0.1% Triton X-100, [pH 8.8]), and 1 U of Taq DNA Polymerase (New England Biolabs, England). The PCR amplifications were carried out under the following conditions: initial denaturation at 96°C for 2 min, followed by 35 cycles of 96°C for 1 min, 55°C for 1 min, and 72°C for 1 min, with a final extension at 72°C for 5 min. PCR products were subjected to three separate sequencing reactions using the primers RscytbF, RscytbR and RscytbstrR (5’-GCA GGT GGA GTT TGC ATA GG-3’), providing a sequence of 1631 nucleotides (FJ346339). Sequencing reactions were performed using the ABI PRISM BigDye Terminator v3.0 ready reaction cycle sequencing kit (Applied Biosystems, Foster City, CA). The sequencing PCRs were in a total volume of 10 µL using 20 to 40 ng DNA, 10 pmol of

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primer and 2 µL BigDye reaction mix diluted 1:4. The cycling profile was: 10 sec denaturation at 95°C, 5 sec annealing at 50°C and 4 min extension at 60°C for 100 cycles. The PCR products were purified after the sequencing reaction to remove buffer salts and unincorporated ddNTPs through Sephadex G-50 DNA Grade F (Amersham Biosciences, Switzerland). The cleaned PCR products were then loaded into a 3100 ABI automated sequencer. The sequences were visualized and analyzed with the Sequencher version 4.2 software package (Gene Codes Corporation, Ann Arbor, MI) using the genetic code of Pezizomycotina that diverges from the standard nuclear code for the codon TGA, which was read as Trp and not as Stop. The complete cytb sequences were translated and tested for similarities with other organisms present in the GenBank database using BLASTP (Fig. 1).

Figure 1. Amino-acid sequence of Rhynchosporium secalis cytb protein deduced from the obtained DNA sequence. The amino-acid sequences from Venturia inaequalis (AF004559.1), Mycosphaerella graminicola (AY247413.1) and Aspergillus niger (D63375.1) are also shown. The conserved amino acids in all presented organisms are marked in light grey; dark gray denotes amino acids conserved in at least two organisms. The glycine at position 143, if replaced by alanine, is expected to confer resistance to strobilurin.

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Detection of QoI resistance allele G143A using PCR-RFLP. A worldwide collection of 841 R. secalis isolates (Table 1) was screened for the G143A mutation known to confer the highest QoI resistance in most fungal pathogens (Gisi et al. 2000; Sierotzki et al. 2000a and 2000b; Bartlett et al. 2002). The isolates were from field populations collected over the last 20 years and most of them were described earlier (McDonald et al. 1989 and 1999; Salamati et al. 2000; Linde et al. 2003; Schürch et al. 2004, Zaffarano et al. 2006). For the screening, specific primers for the R. secalis cytb were designed: RscytbstrF (5’-TGC ATT ACA ACC CTA GTA TAT TAG-3’) and RscytbstrR. The PCR reactions and the thermal cycling conditions were as described above except that the annealing temperature was decreased to 50°C. A portion of each PCR product (10 µL) was digested using 1U Fnu4HI (New England BioLabs, England) for 4 h at 37°C. Digests were visualized on a 1% agarose gel with 1x tris- borate-EDTA (TBE) buffer (Fig. 2). As a control we used M. graminicola isolates known to be QoI-sensitive or QoI-resistant amplified using the MgcytbF and MgcytbR primers described in Torriani et al. (2009).

Table 1. Origin of the 851 isolates of Rhynchosporium secalis used in this study

Continent Origin Years of Sequenced PCR-RFLP Sensitivity- Source or reference (isolates) collection isolates1 isolates test isolates1 Europe (n= 464) Switzerla nd 1999, 2000, 2 97 - Linde et al. 2003, Schürch et al. 2004 2001, 2003 Russia 2003 3 14 - L. Lebedeva England 1997 1 18 1 Schürch et al. 2004, J. Speakman France 1997 - 10 - Schürch et al. 2004, J. Speakman Turkey 1997 - 5 - Schürch et al. 2004, J. Speakman Germany 1997 1 61 1 Schürch et al. 2004, J. Speakman Sweden 1996 - 7 - Schürch et al. 2004, S. Salamati Finland 1996 2 67 2 Linde et al. 2003, Salamati et al. 2000, Schürch et al. 2004 Norway 1996 2 185 2 Linde et al. 2003, Salamati et al. 2000, Schürch et al. 2004 Africa (n=113) Tunisia 2003 2 - 2 A. Yahyaoyi South Africa 2002 2 59 2 Linde et al. 2003 Eritrea 2002 2 21 - A. Yahyaoyi Ethiopia 2001 2 31 2 Linde et al. 2003, Schürch et al. 2004 Asia (n=134) Azerbaijan 2003 2 - 2 A. Yahyaoyi Kazakhstan 2003 2 - 2 A. Yahyaoyi Syria 2002, 2003 2 62 2 M. Abang Jordan 2002 2 68 - Schürch et al. 2004 America (n=43) Argentina 2003 - 3 - B. Perez USA 1988 5 40 5 Linde et al. 2003, McDonald et al. 1989, Salamati et al. 2000, Schürch et al. 2004 Oceania (n=97) New Zealand 2004 4 - 3 M. Cromey Australia 1996, 1997 4 93 1 Linde et al. 2003, McDonald et al.1999, Salamati et al. 2000, Schürch et al. 2004 Total 40 841 27 1 The cytochrome b sequenced isolates and those tested for fungicide resistance were the same.

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In vitro QoI sensitivity test. A representative sample of 27 isolates (Table 1), chosen from the 40 used to assess the intraspecific diversity of cytb, was tested for QoI sensitivity in vitro. Azoxystrobin was dissolved in methanol and adjusted to a concentration of 20 mg/mL. The sensitivity of each isolate was determined by mycelial growth on potato dextrose agar (PDA) amended with 0, 1, 10, or 100 µg/mL azoxystrobin and 0.5 mM salicylhydroxamic acid (SHAM). Azoxystrobin and SHAM were added to autoclaved PDA cooled to 55°C. The concentration of methanol was 0.5% (v/v) in all tests. PDA was also amended with methanol to test for inhibitory effects of methanol. Conidia were suspended in water at 106 conidia/mL and 5 µL aliquots of the conidial suspension were placed onto PDA in Petri dishes. Three different isolates were tested simultaneously in each Petri dish, with three inoculations per isolate. Each Petri dish assay was replicated three times. Following incubation at 18°C for two weeks, mycelial growth was assessed visually and compared with the unamended PDA and PDA amended with methanol controls (Fig. 3).

Figure 2. PCR-RFLP analysis of cytb-locus for detection of QoI resistance allele. a) The G143A mutation resulted in creation of a second Fnu4HI restriction site in cytb-locus for both R. secalis and M. graminicola. Molecular sizes are indicated within each fragment. b) An example of PCR amplification with the primers cytbstrF and cytbstrR from a QoI sensitive (s) isolate of R. secalis either undigested (RS s) or digested (RS s,d). As controls, a QoI sensitive (MG s) and a resistant (MG r) isolate of M. graminicola were amplified with the same PCR conditions using the primers MgcytbF and MgcytbR and digested (MG s,d; MG r,d). First and last lanes are a 100 bp size ladder. Arrows show the size of the bands of R. secalis (left) and from M. graminicola (right).

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Results

Cytochrome b gene sequencing, characterization and intra/interspecific diversity. The entire cytb gene (FJ346339) was sequenced for 40 isolates from five continents (Table 1) to investigate the intraspecific diversity. No polymorphisms were detected, indicating a high degree of conservation globally. Cytb gene is 1191 base pairs long, lacks introns, and is predicted to encode a protein of 396 amino acids (Fig. 2; FJ346339). The organism with the highest similarity was V. inaequalis with 89% identity and an e-value of zero (Table 2 and Fig. 1). In general, organisms with the highest similarities were Ascomycetes, but some similarity was also found with Basidiomycetes (Table 2).

PCR-RFLP analysis. A total of 841 field isolates (Table 1) were screened for the G143A mutation using the primers RscytbstrF and RscytbstrR to amplify the cytb-locus surrounding the G143A mutation site. The amplified PCR products were 652 bp in size and when digested with the restriction enzyme Fnu4HI produced two fragments which were 418 and 234 bp long (Fig. 2). A mutation that generated a second Fnu4HI restriction site (…GGNGC… to …GCNGC…) in the cytb locus of R. secalis would provide evidence for the presence of the QoI resistant allele as already shown for M. graminicola (Fig. 2; Torriani et al. 2009). All isolates had the wild type allele, indicating sensitivity to the QoI fungicide.

Table 2. Fungi having significant alignments with cytochrome b of Rhynchosporium secalis

Organism Taxa Accession number Similarity (%) E-value Venturia inaequalis Ascomycota O48334 89 0 Mycosphaerella graminicola Ascomycota YP_001648755 88 0 Aspergillus niger Ascomycota Q33798 83 0 Mycosphaerella fijiensis Ascomycota AAK27475 87 0 Penicillium marneffei Ascomycota Q6V9D6 85 0 Magnaporthe grisea Ascomycota AAO91629 82 0 Fusarium oxysporum Ascomycota AAW67488 82 0 Trichophyton rubrum Ascomycota Q9ZZ40 80 0 Blumeria graminis Ascomycota AAK26621 87 8e-173 Schizophyllum commune Basidiomycota Q94ZJ2 68 4e-149 Mycena viridimarginata Basidiomycota Q36445 64 2e-146

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In vitro QoI sensitivity test. All 27 R. secalis isolates showed complete sensitivity to azoxystrobin with no mycelial growth detected in PDA amended with azoxystrobin at 1, 10 or 100 ppm (data not presented).

Discussion

We conducted this research prior to the first report of QoI resistance in R. secalis, anticipating that diagnostic tools and prior knowledge of the diversity found in the cytb gene would be useful for monitoring the development and movement of fungicide-resistant populations.

Figure 3. Example of the in vitro azoxystrobin sensitivity test for three of the twenty-seven tested Rhynchosporium secalis isolates.

The cytb of R. secalis is composed of 1191 nucleotides, has no introns, and encodes a protein of 396 amino acids (Fig. 1; FJ346339). Our interest in this gene arises from the finding that the cytb protein is the specific target for QoI fungicides. The replacement of glycine by alanine at amino acid position 143 (G143A) is the major mechanism of resistance for pathogenic fungi, as already demonstrated for V. inaequalis (Zheng et al. 2000), M. fijiensis (Sierotzki et al. 2000a), B. graminis (Sierotzki et al. 2000b) and several other fungi. The lack of an intron after codon 143 in R. secalis indicates that the G143A mutation will not be lethal if it emerges (Grasso et al. 2006).

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No polymorphisms were detected in the complete cytb DNA sequence in a global collection of 40 isolates, indicating a high degree of conservation for this gene. The absence of mutations for cytb is consistent with strong directional selection acting on this gene, reflecting the importance of this protein in cellular respiration. The conservation seen in the amino acid sequence within species is reflected at the interspecific level, with little variation found between different fungal species. This contrasts with the nucleotide sequence variation associated with the presence of different numbers of introns between species. Intron variation in cytb reported thus far in other fungi range from no introns for M. graminicola (Torriani et al. 2008) to the six introns in V. inaequalis (Zheng and Köller 1997). A worldwide collection of 841 field isolates of R. secalis was screened for the presence of the G143A mutation to determine the frequency of QoI resistant allele. No mutants were found among the 841 isolates, indicating that the G143A mutation occurred at a frequency lower than 0.0012 in the global population. The F129L mutation which confers only moderate resistance in A. solani (Pasche et al. 2005), was not detected in the 40 isolates sequenced in this study. The sensitivity test conducted on fungicide-amended PDA was consistent with the molecular screens showing a complete sensitivity of R. secalis isolates to QoI. These results indicate that resistant mutants do not exist at a detectable frequency in R. secalis populations around the world, but selection could rapidly increase the frequency of resistance when it emerges as Gisi et al. (2005) demonstrated for M. graminicola. If resistance to QoI emerges, a molecular method will be useful to detect the resistant allele. In anticipation of this need, the G143A resistance allele of R. secalis can be easily detected through the PCR-RFLP method described here, using RscytbstrF and RscytbstrR as primers and Fnu4HI as a restriction enzyme.

Acknowledgements

We thank M. Zala for his technical assistance and P. Ceresini for critical reading of the manuscript. This project was supported by the Swiss National Science Foundation (grant 3100A0-104145). DNA sequence data were collected using facilities provided by the ETH Genetic Diversity Center.

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Ayesu-offei EN, Carter MV. 1974. Epidemiology of leaf scald of barley. Aust J Agr Res. 22: 383-390. Bartlett DW, Clough JM, Godwin JR, Hall AA, Hamer M, Parr-Dobrzanski B. 2002. The strobilurin fungicides. Pest Manag Sci. 58:647-662. Caldwell RM. 1937. Rhynchosporium scald of barley, rye, and other grasses. J Agr Res. 55:175-197. Chen WJ, Delmotte F, Richard-Cervera S, Douence L, Greif C, Corio-Costet MF. 2007. At least two origins of fungicide resistance in grapevine downy mildew populations. Appl Environ Microb. 73:5162-5172. Cooke LR, Locke T, Lockley KD, Phillips A, Sadiq MDS, Coll R, Black L, Taggart PJ, Mercer PC. 2004. The effect of fungicide programmes based on epoxiconazole on the control and DMI sensitivity of Rhynchosporium secalis in winter barley. Crop Prot. 23:393-406. Evans SG. 1969. Observations on development of leaf blotch and net blotch of barley from barley debris, 1968. Plant Pathol. 18:116-118. Fraaije BA, Burnett FJ, Clark WS, Motteram J, Lucas JA. 2005. Resistance development to QoI inhibitors in populations of Mycosphaerella graminicola in the UK. In: Dehne HW, Gisi U, Kuck KH, Russell PE and H. Lyr eds, Modern Fungicides and Antifungal Compounds IV. 63-71 BCPC, Alton, UK Fraaije BA, Butters JA, Coelho JM, Jones DR, Hollomon DW. 2002. Following the dynamics of strobilurin resistance in Blumeria graminis f.sp tritici using quantitative allele-specific real-time PCR measurements with the fluorescent dye SYBR Green. Plant Pathol. 51:45-54. Gisi U, Chin KM, Knapova G, Farber RK, Mohr U, Parisi S, Sierotzki H, Steinfeld U. 2000. Recent developments in elucidating modes of resistance to phenylamide, DMI and strobilurin fungicides. Crop Prot. 19:863-872. Gisi U, Pavic L, Stanger C, Hugelshofer U, Sierotzki H. 2005. Dynamics of Mycosphaerella graminicola populations in response to selection by different fungicides. In HW Dehne,

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U Gisi, KH Kuck, PE Russell and H Lyr, eds., Modern Fungicides and Antifungal Compounds IV, pp 73-80, BCPC, Alton, UK. Grasso V, Palermo S, Sierotzki H, Garibaldi A, Gisi U. 2006. Cytochrome b gene structure and consequences for resistance to Qo inhibitor fungicides in plant pathogens. Pest Manag Sci. 62:465-472. Ishii H, Fraaije BA, Sugiyama T, Noguchi K, Nishimura K, Takeda T, Amano T, Hollomon DW. 2001. Occurrence and molecular characterization of strobilurin resistance in cucumber powdery mildew and downy mildew. Phytopathology 91:1166-1171. Khan TN. 1986. Effects of fungicide treatments on scald (Rhynchosporium secalis (Oud)

Davis) infection and yield of barley in western-Australia. Austr J Exp Agr. 26:231-235. Kim YS, Dixon EW, Vincelli P, Farman ML. 2003. Field resistance to strobilurin (Q(o)I) fungicides in Pyricularia grisea caused by mutations in the mitochondrial cytochrome b gene. Phytopathology 93:891-900. Linde CC, Zala M, Ceccarelli S, McDonald BA. 2003. Further evidence for sexual reproduction in Rhynchosporium secalis based on distribution and frequency of mating- type alleles. Fungal Genet Biol. 40:115-125. Ma ZH, Felts D, Michailides TJ. 2003. Resistance to azoxystrobin in Alternaria isolates from pistachio in California. Pest Biochem Phys. 77:66-74. McDonald BA, McDermott JM, Allard RW, Webster RK. 1989. Coevolution of host and pathogen populations in the Hordeum vulgare-Rhynchosporium secalis pathosystem. P Natl Acad Sci USA 86:3924-3927. McDonald BA, Zhan J, Burdon JJ. 1999. Genetic structure of Rhynchosporium secalis in Australia. Phytopathology 89:639-645. Oerke EC, Dehne HW, Schönbeck F, Weber A. 1994. Crop Production and Crop Prot., Elsevier, Amsterdam, pp. 297-364. Pasche JS, Piche LM, Gudmestad NC. 2005. Effect of the F129L mutation in Alternaria solani on fungicides affecting mitochondrial respiration. Plant Dis. 89:269-278. Salamati S, Zhan J, Burdon JJ, McDonald BA. 2000. The genetic structure of field populations of Rhynchosporium secalis from three continents suggests moderate gene flow and regular recombination. Phytopathology 902:901-908.

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Schürch S, Linde CC, Knogge W, Jackson LF, McDonald BA. 2004. Molecular population genetic analysis differentiates two virulence mechanisms of the fungal avirulence gene NIP1. Mol Plant Microbe In.10:1114-1125. Shipton WA, Boyd WJR, Ali SM. 1974. Scald of barley. Rev Plant Pathol. 53:840-861. Sierotzki H, Parisi S, Steinfeld U, Tenzer I, Poirey S, Gisi U. 2000a. Mode of resistance to respiration inhibitors at the cytochrome bc(1) enzyme complex of Mycosphaerella fijiensis field isolates. Pest Manag Sci. 56:833-841. Sierotzki H, Wullschleger J, Gisi U (2000b) Point mutation in cytochrome b gene conferring resistance to strobilurin fungicides in Erysiphe graminis f. sp tritici field isolates. Pest Biochem Phys. 68:107-112. Sierotzki H, Frey R, Wullschleger J, Palermo S, Karlin S, Godwin J, Gisi U. 2007. Cytochrome b gene sequence and structure of Pyrenophora teres and P. tritici-repentis and implications for QoI resistance. Pest Manag Sci. 63:225-233. Skoropad WP. 1957. Temperature and humidity relationships in securing infection of barley with Rhynchosporium secalis. Phytopathology 47:32-33. Skoropad WP. 1959. Seed and seedling infection of barley by Rhynchosporium secalis. Phytopathology 49:623-626. Torriani SFF, Brunner PC, McDonald BA, Sierotzki H. 2009. QoI resistance emerged independently at least 4 times in European populations of Mycosphaerella graminicola. Pest Manag Sci. 65:155-162. Torriani SFF, Goodwin SB, Kema GHJ, Pangilinan JL, McDonald BA. 2008. Intraspecific comparison and annotation of two complete mitochondrial genome sequences from the plant pathogenic fungus Mycosphaerella graminicola. Fungal Genet Biol. 45:628-637. Vincelli P, Dixon E. 2002. Resistance to Q(o)I (strobilurin-like) fungicides in isolates of Pyricularia grisea from perennial ryegrass. Plant Dis. 86:235-240. Yokoyama K, Wang L, Miyaji M, Nishimura K. 2001. Identification, classification and phylogeny of the Aspergillus section Nigri inferred from mitochondrial cytochrome b gene. FEMS Microbiol lett. 200:241-246. Zaffarano PL, McDonald BA, Zala M, Linde CC. 2006. Global hierarchical gene diversity analysis suggests the Fertile Crescent is not the center of origin of the barley scald pathogen Rhynchosporium secalis. Phytopathology 96:941-950.

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Zaffarano PL, McDonald BA, Linde CC. 2008. Rapid speciation following recent host shifts in the plant pathogenic fungus Rhynchosporium. Evolution 62:941-950. Zheng DS, Köller W. 1997. Characterization of the mitochondrial cytochrome b gene from Venturia inaequalis. Curr Genet. 32:661-666. Zheng DS, Olaya G, Köller W. 2000. Characterization of laboratory mutants of Venturia inaequalis resistant to the strobilurin-related fungicide kresoxim-methyl. Curr Genet. 38:148-155.

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CHAPTER 7

General conclusions

Chapter 7 General conclusions

160 Chapter 7 General conclusions

The mitochondrial genomes of Mycosphaerella graminicola and Phaeosphaeria nodorum represent the first completely annotated mitochondrial genomes of any species from the class Dothideomycetes (Schoch et al. 2006), that includes economically important plant pathogenic fungi affecting a variety of hosts, including Cochliobolus heterostrophus (southern blight on corn), Leptosphaeria maculans (black leg on brassica crop), Pyrenophora tritici repentis (tan spot on wheat), Venturia inaequalis (apple scab) and Mycosphaerella fijiensis (black Sigatoka on bananas). In total the class Dothideomycetes comprises more than 6000 known species. Only 57 complete fungal mitochondrial genome sequences are deposited in the NCBI database today. The principal reason for the limited mitochondrial genome sequences available was the expense of sequencing, but new low cost sequencing technologies, e.g. pyrosequencing (Ronaghi et al. 1998) have increased the rate of new sequences releases. As chapters 2 and 3 show, fungal mitochondrial genomes display some common features interspecifically, including the expression of a standard set of genes involved in oxidative phosphorylation, two genes encoding the large and the small ribosomal subunit (rnl and rns) and a set of tRNA genes, often clustered in groups showing conservation in the gene order (Ghikas et al. 2006). Although the number of completely sequenced fungal mtDNAs is limited, it is clear that the tRNA gene clusters flanking rnl display a conserved gene order among the classes Dothideomycetes, Eurotiomycetes and Sordariomycetes, forming the large Pezizomycotina subphylum (with more than 32,000 described species; Kirk et al. 2001) of Ascomycota. This mitochondrial genomic region could be used as an additional criterion in phylogenetic analyses to distinguish between fungal classes. The evolutionary history is recorded in the tRNA clusters as rearrangement in gene order; for example 1) Sordariomycetes, in the tRNA genes located 3’-downstream rnl, had an inversion between tRNA-Met and tRNA-His not found in the Eurotiomycetes or 2) Dothideomycetes, in the same region, displayed the insertion of a tRNA-Glu not present neither in the Eurotiomycetes nor in the Sordariomycetes. These tRNA gene rearrangements could also be reflected at order level since M. graminicola underwent the loss of three tRNA genes if compared to P. nodorum and all other fungal species. A distinctive feature among fungal mitochondrial genome is that the intron content varies widely between species, ranging from no or few introns like in M. graminicola and P. nodorum to a substantial intron invasion as found in Leptosphaeria maculans (unpublished).

161 Chapter 7 General conclusions

If we take as example cytb, probably the best studied fungal mitochondrial gene because it encodes the target of QoI fungicides, we find that M. graminicola and Rhynchosporium secalis have an uninterrupted gene, P. nodorum displays one intron and L. maculans has six introns and a total size 8.4x and 4.4x bigger than respectively M. graminicola and R. secalis. Most mitochondrial introns are group I introns and most of the mitochondrial group I intron open reading frames (ORFs) fall into two of the four main families of homing endonucleases (Galburt and Stottard 2002; Lang et al. 2007), encoding LAGLIDADG and GIY-YIG as their conserved sequence motifs (Belfort and Perlman 1995). Group I introns are commonly found in fungal mitochondrial genes but are absent from most animal and protist mtDNA genomes (Haugen et al. 2005). Intraspecifically it seems these introns are unevenly distributed among the genes, with preferences for cox1, cytb and rnl (Lang et al. 2007). Some group I introns are mobile and proliferate through intron homing, a mechanism able to move introns into previously intronless genes (Lang. et al. 2007). Since introns are highly divergent sequences, it is unlikely that they will remain conserved between taxa that separated millions of years ago. A more likely explanation for the distribution of group I intron across the tree of life is horizontal transfer (Dujon 1989). Future studies will be needed to clarify 1) why M. graminicola is intronless, 2) if this is a common feature of all Mycospharellaceae, including M. fijiensis and the S1/S2 populations from uncultivated hosts, 3) what would occur if a group I intron will be introduced into the mtDNA and 4) if the larger number of group I introns in L. maculans reflects an older invasion or if there are species where intron homing is favored. The evolutionary history of the mitochondrial genome inferred from mitochondrial sequences dated the divergence of M. graminicola from the ancestral Mycosphaerella populations, adapted to uncultivated grasses, to between 10,200 and 9,000 years ago, confirming the coalescent analysis conducted using nuclear genes (Stukenbrock et al. 2007). The epochal shift from a hunter-gatherer to an agricultural society left archeological traces, telling of the profound changes occurring in Mesopotamia about 10,000 to 12,000 years ago following cultivation of the first crops (Moore et al. 2000; Gopher et al. 2002). The evolution of M. graminicola was therefore human-mediated through the beginning of agriculture, since this pathogen was domesticated along with wheat. Analogously, the industrial revolution brought changes to society as profound as the invention of agriculture 10,000 years ago. It is,

162 Chapter 7 General conclusions therefore, not surprising that the first traces of evolutionary change thought to be a consequence of the industrial revolution begin to be discovered today; some examples include 1) the effect of air pollution on long term fungal pathogen population dynamics (Bearchell et al. 2005), 2) the extinction/appearance of sensitive or resistant strains after fungicide applications (chapter 5 and 3) the shift northwards of plant pathogens well adapted in the South in response to global warming (La Porta et al. 2008). The ability of horizontal gene transfer to increase virulence in recipient lineages is documented in the literature, as recently was found for Pyrenophora tritici repentis that received ToxA gene from P. nodorum (Friesen et al. 2006). Analogously this work suggests the introgression of an exogenous putative gene in the mitochondrial RFLP haplotype 4 of M. graminicola (chapter 3). The putative open reading frame (ORF) found in type 4, was absent both intraspecifically, in the other mitochondrial haplotypes, and interspecifically in Mycosphaerella spp. collected from uncultivated hosts. This study postulates that a horizontal gene transfer introduced into M. graminicola the RFLP4-ORF that encodes for a protein, acting as virulence factor. The RFLP4-ORF identification strengthens previous data, showing nonrandom associations between mitochondrial haplotypes and infected hosts (Zhan et al. 2004). Future research will need to investigate the functions of the putative gene, when and if it is transcribed and try to genetically silence it in mitochondrial type 4 and/or introduce it into other mitochondrial types to test the effect on pathogenicity in durum wheat (Triticum durum) and bread wheat (T. aestivum). The importance of monitoring programs and studies trying to understand the evolutionary mechanisms involved in the development of fungicide resistance, is well described in the introductory sentence found on the homepage of Fungicide Resistance Action Committee (FRAC): “Fungicides have become an integral part of efficient food production. The loss of a fungicide to agriculture through resistance is a problem that affects us all”. In fact, the development of a fungicide resistance causes critical yield losses, reduces profit and decreases food production. Depending upon the fungicide mode of action, a pathogen can evolve resistance gradually or suddenly. A decreased sensitivity can either be disruptive, like found for QoIs, or gradual as found for the DMIs (Gisi et al. 2005). In the disruptive mechanism the change in sensitivity can be rapid and in most cases is mediated by a single amino acid substitution in the target protein, like the G143A mutations that confer QoI

163 Chapter 7 General conclusions resistance. The continuous mechanism results in a stepwise reduction of sensitivity because the nature of resistance is polygenic. M. graminicola, for example, evolved QoI resistance suddenly in 2001, only five years after the QoI was first released on the market (Fraaije et al. 2005). As this work showed (chapter 5), the mutation causing G143A occurred several times in different genetic and geographic backgrounds. The DMIs have been used for more than twenty years and are still effective, although some reduction in efficacy has been detected (Cools et al. 2005). When released, QoIs were supposed (wrongly) to display low risk to develop resistance although the disruptive resistance mechanism because targeting the product of a mitochondrial gene. The latest fungicide resistance management strategies suggest using products in mixtures or in alternating spray programs to decrease the likelihood that a pathogen develops resistance, since any isolates resistant to one fungicide could be negatively selected by the second. As presented in this work a strong fungicide selection can introduce the resistance allele independently several times through parallel evolution, therefore a reduction of the fungicide amount in the environment has to be achieved to decrease the selection pressure. An important piece of the fungicide resistance management puzzle is based on effective monitoring to know the spread of the resistance and to evaluate the effect of the different treatments and management strategies. This PhD thesis brought new insights to better understand mitochondrial genetics and evolution of some of the most economically damaging plant pathogenic fungi. These studies have for the first time described the mitochondrial genomes from species belonging to the Dothideomycetes class, providing the basis for further studies connected to this important branch of the Ascomycetes. A more applied result from this work deals with fungicide resistance management, identifying selection, parallel genetic adaptation and migration as the principal evolutionary forces involved in the emergence and spread of fungicide resistance.

164 Chapter 7 General conclusions

References

Bearchell SJ, Fraaije BA, Shaw MW, Fitt BDL. 2005. Wheat archive links long-term fungal pathogen population dynamics to air pollution. PNAS 102:5438-5442. Belfort M, Perlman PS. 1995. Mechanisms of intron mobility. J Biol Chem. 270:30237- 30240. Cools HJ, Fraaije BA, Lucas JA. 2005. Molecular examination of Septoria tritici isolates with reduced sensitivities to triazoles. In Dehne HW, Gisi U, Kuck KH, Russell PE and Lyr H, eds., Modern Fungicides and Antifungal Compounds IV, pp 103-114. BCPC Alton, UK. Dujon B. 1989. Group I introns as mobile genetic elements: facts and mechanistic speculations - a review. Gene. 82:91-114. Galburt EA, Stoddard BL. 2002. Catalytic mechanisms of restriction and homing endonucleases. Biochemistry 41:13851-13860. Ghikas DV, Kouvelis VN, Typas MA. 2006. The complete mitochondrial genome of the entomopathogenic fungus Metarhizium anisopliae var. anisopliae: gene order and trn gene clusters reveal a common evolutionary course for all Sordariomycetes, while intergenic regions show variation. Arch Microbiol 185:393-401. Gisi U, Pavic L, Stanger C, Hugelshofer U and Sierotzki H. 2005. Dynamics of Mycosphaerella graminicola populations in response to selection by different fungicides. In Dehne HW, Gisi U, Kuck KH, Russell PE and Lyr H, eds., Modern Fungicides and Antifungal Compounds IV, pp 73-80, BCPC, Alton, UK. Gopher A, Abbo S, Lev-Yadun ST. 2002. The ‘when’, the ‘where’ and the ‘why’ of the Neolithic revolution in the Levant. Doc Praehist. 28:49-62. Haugen p, Simon DM, Bhattacharya D. 2005. The natural history of group I introns Trends Genet. 21:111-119. Kirk PM, Cannon PF, David JC, Stalpers JA. 2001. Ainsworth and Bisby’s Dictionary of the Fungi, 9th ed. CAB International, Wallingford, UK. La Porta N, Capretti P, Thomsen IM, Kasanen R, Hietala AM, Von Weissenberg K. 2008. Forest pathogens with higher damage potential due to climate change in Europe. Can J Plant Pathol. 30:177-195.

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Lang BF, Laforest MJ, Burger G. 2007. Mitochondrial introns: a critical view. Trends Genet. 23:119-125. Moore AMT, Hillman GC, Legge AJ. 2000. Village on the Euphrates: from foraging to farming at Abu Hureyra. Oxford Univ. Press, New York, USA. Ronaghi M, Uhlén M, Nyrén P. 1998. A sequencing method based on real-time pyrophospate. Science 281:363-365. Schoch CL, Shoemaker RA, Seifert KA, Hambleton S, Spatafora JW, Crous PW. 2006. A multigene phylogeny of the Dothideomycetes using four nuclear loci. Mycologia 98:1041-1052. Stukenbrock EH, Banke S, Javan-Nikkhah M, McDonald BA. 2007. Origin and domestication of the fungal wheat pathogen Mycosphaerella graminicola via sympatric speciation. Mol Biol Evol. 24:398-411. Zhan J, McDonald BA. 2004. The interaction among evolutionary forces in the pathogenic fungus Mycosphaerella graminicola. Fungal Genet Biol. 41:590-599.

166 Acknowledgements

Acknowledgments

I am grateful to many people for their support during this period. Especially thanks to:

Bruce McDonald for giving me the opportunity of this thesis Patrick Brunner and Soren Banke for supervising me Alex Widmer for being my co-examiner Mamma Mia (non il musical) per tutto quello che mi ha dato Marcello Zala, per quello che mi hai insegnato, dentro e fuori il labo Paolo, per i peperoncini, i ricordi del Kerkis, ma soprattutto per avermi tenuto alto morale A-(floor) people. Joana, Megan, Eva, Rubik, Pascal, Francesca, Carlotta All others from the phytopathology group, Giovanni, Pato, Cate, Rex, Gob, Rochi, Frep, Fabi, Patrice, Andi, Miske, Thalia, J(u)ana, Paulo, Danilo, Gogo, Cesare, Ueli, Uli, Gabri, Thomas, Pierre, Moni, Celeste, Yvonne, Tina and those I forgot, because it is 5.30 am

I miei amici senza i quali la vita sarebbe noiosa Teo e Geo (i coinqui), Alan, Dada, Olmo, Sandro, Vano, Guaina, Meui, Babs, Bastian, Lucio (e tutto il Brè), Jamal, Tognone, Sam (il), Sam (la), Aida, Peda, Glauco, Puzzle, Daniel, Stella, Nick R, Tania, Vero, Anna, Annina, Meda, Chiara, Mattia, Alice, Naty, The Pussywarmers, Nick e Jenny, Crimy, Fedi, Ronzi, Fabbio, KiKa, Claudio, Alessio, Yvonne, Imo, Canguri, Manu, Frige, Piffa, Zan, Teresa, Laura, Deon, Luli, Pisu e Rosy e tutti gli altri…

Raoul, 3 anni non son bastati a capire l’ora della colazione, ma l’12.34 non si tocca. GRAZIE

Questa tesi è stata portata a termine nonostante Medo, Eli, Aldo e Mitch

GRAZIE A TUTTI

167 Acknowledgements

168 Curriculum vitae

Curriculum Vitae

Stefano Torriani, born in Sorengo (TI), Switzerland, 17th January 1980

2005-2008 PhD student, Institute for Integrative Biology, Phytopathology Group, Federal Institute of Technology, ETH-Zurich, Switzerland. Project title: Mitochondrial genomes of plant pathogenic fungi. Supervised by Prof. Bruce A. McDonald and Dr. Patrick C. Brunner.

1999-2004 Diploma in Natural Sciences (Biology), ETH Zurich: Dipl. Natw. ETH

1995-1999 Liceo Lugano 1 (TI), scientific direction (Maturität Typus B)

1991-1995 Scuole Medie Istituto Elvetico, Lugano (TI)

1986-1991 Scuole Elementari Istituto Elvetico, Lugano (TI)

Pubblications

• Stefano FF Torriani, Stephen B Goodwin, Gert HJ Kema, Jasmyn L Pangilinan, Bruce A. McDonald. 2008. Intraspecific comparison and annotation of two complete mitochondrial genome sequences from the plant pathogenic fungus Mycosphaerella graminicola. Fungal Genetics and Biology 45:628-637.

• Stefano FF Torriani, Patrick C Brunner, Bruce A. McDonald, Helge Sierotzki. 2009. QoI resistance emerged independently at least 4 times in European populations of Mycosphaerella graminicola. Pest Management Science 65:155-162

• Stefano FF Torriani, Celeste C Linde, Bruce A. McDonald. 2009 Lack of G143A QoI resistance allele and sequence conservation for the mitochondrial cytochrome b gene in a global sample of Rhynchosporium secalis. Australasian Plant Pathology 38:202-207

• James K Hane, Rohan GT Lowe, Peter S Solomon, Kar-Chun Tan, Conrad L Schoch, Joseph W Spatafora, Pedro W Crous, Chinappa Kodira, Bruce W Birren, Stefano FF

169 Curriculum vitae

Torriani, Bruce A McDonald, Richard P Oliver. 2007. Dothideomycete-Plant interactions illuminated by genome sequencing and EST analysis of the wheat pathogen Stagonospora nodorum. The Plant Cell 19:3347-3368.

• Jiasui S Zhan, Stefano FF Torriani, Bruce A McDonald. 2007. Significant difference in pathogenicyty between MAT1-1 and MAT1-2 isolates in the wheat pathogen Mycosphaerella graminicola. Fungal Genetics and Biology 44:339-346.

170