Pythium Spp. and Fusarium Graminearum and Their Management Through Host Resistance

The Soybean Seedling Disease Complex: Pythium spp. and Fusarium graminearum and their Management through Host Resistance

DISSERTATION

Presented in Partial Fulfillment of the Requirements for the Degree Doctor of Philosophy in the Graduate School of The Ohio State University

Margaret Lee Ellis, M.S.

Graduate Program in Plant Pathology

The Ohio State University

2011

Dissertation Committee:

Dr. Anne E. Dorrance, Advisor

Dr. Pierce A. Paul, Advisor

Dr. M.A. Rouf Mian

Dr. Thomas K. Mitchell

Copyrighted by

Margaret Lee Ellis

2011

Abstract

Seedling diseases in soybean fields in Ohio have increased over the past decade. This study was conducted to better characterize some of these seedling pathogens, specifically

Fusarium graminearum and two new pathogenic species of Pythium, as well as evaluate management strategies, particularly host resistance, for F. graminearum and Pythium irregulare. A rolled towel assay was developed to understand the potential impact of F. graminearum as a soybean pathogen by evaluating the effect of inoculum density, temperature parameters, and fungicide seed treatments on disease development. Inoculum concentrations of 2.5 × 104 macroconidia/ml or higher were necessary for disease development at temperatures 18 to 25oC, indicating that high levels of inoculum may be necessary for disease to occur. Seed treated with captan at 61.9 g a.i. or fludioxonil at 2.5 or 5.0 g a.i. per 100 kg developed smaller lesions than other seed treatments and the nontreated control. The rolled towel assay was used to screen 24 soybean genotypes for resistance to F. graminearum. Five genotypes had high levels of resistance to F. graminearum, including the cultivar Conrad, a major source of partial resistance to

Phytophthora sojae. A population of 262 F6:8 recombinant inbred lines (RIL) derived from a cross of Conrad x Sloan (Susceptible) was evaluated for resistance and segregated as a quantitative trait. Four putative quantitative trait loci (QTLs) were identified from

Conrad on chromosomes 8, 13, 15, and 16, and one putative QTL from Sloan on

chromosome 19. The putative QTLs identified in this population did not map to the same regions that confer resistance to Ph. sojae, suggesting different mechanisms are required for these two seedling pathogens. In this study, two new species of Pythium, P. schmitthenneri and P. selbyi, were described using morphology and sequence analysis of the ITS1-5.8S-ITS2 region. These new species were recovered from 30% of fields surveyed which was focused on the identification of seedling pathogens; they are both pathogens to corn and soybean. Pythium irregulare is one of the most widespread

Pythium species in Ohio soybean fields and has very high levels of pathogenicity. In a greenhouse assay, 105 soybean genotypes were evaluated for resistance to two isolates of

P. irregulare. Isolate x genotype interaction for root weight and rot root score was not significant. The plant introduction (PI) 424354 had high levels of resistance to P. irregulare. Two BC1F2:3 populations were used to map the resistance including: 192 lines of OHS 303 (moderately susceptible) x (Williams (susceptible) x PI 424354) and 127 lines of Dennison (moderately susceptible) x (Williams x PI 424354). Both populations fit the model for quantitative resistance based on root weight and root rot score. Putative

QTL were identified on chromosomes 1, 5, 6, 8, 10, 11, 13, 14, and 20. These results suggest PI 424354 can be an important source of partial resistance in developing germplasm for breeding new cultivars with more durable resistance to P. irregulare.

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Dedication

I would like to dedicate this dissertation to my loving family, especially my father Mark

Lee Ellis, mother Deborah Lynn Ellis, and my sister Elizabeth Stewart Ellis. They have

been a great source of love, inspiration, and guidance throughout my life. I would also

like to dedicate this dissertation to all my grandmothers who were/are remarkable

women: Carol Epstein, Berenice Ellis, Dotty Appelbaum, and Ruby Bond.

Acknowledgments

I would like to thank my advisors Dr. Anne Dorrance and Dr. Pierce Paul for their constant support and guidance for the research presented in this dissertation. They have both helped me to develop both personally and professionally during my time at The

Ohio State University. My knowledge on the Pythium can greatly be attributed to Dr.

Dorrance and all the tools she provided me to study this amazing genus of plant pathogenic fungi. Dr. Paul’s statistical expertise has contributed greatly to this work and also my own personal knowledge.

I would also like to thank my committee member Dr. Thomas Mitchell and Dr.

Rouf Mian for their contributions and support. I had the privilege of being a teaching assistant for Dr. Mitchell’s mycology class, which was a great experience and helped me to confirm my own passion for teaching, and Dr. Mian, provided expertise in plant breeding.

Dr. Leah McHale and Dr. Steven St. Martin contributed greatly to the last two chapters in my dissertation. Dr. St. Martin developed all of the populations used in this research. Thanks to all the members of the Soybean Pathology and Cereal Pathology

Labs. Maria Ortega, Grant Austin, Sean Dawes, SelyAnn Headley, Michelle LaLonde,

Colton Zody, Nikki Berry, Damitha Wickramasinghe, David Salgado, Wirat

Pipatpongpinyo, Soledad Benitez, Lily Zelaya, Andika Gunadi, Freddy Cruz, Christian

Cruz, Matt Wallhead, Kate Gearhart, Chandra Phelan, Crystal Van Pelt, Zhifen Zhang,

Sungwoo Lee, Alissa Kriss, and Kylea Odenbach for their help and friendships. A special acknowledgement to Kirk Borders, Hehe Wang, and Sue Ann Berry for their many contributions towards this research.

This research was funded in part by the Ohio Soybean Council, OARDC SEEDS

Grant graduate research competition, and Syngenta Crop Protection.

Vita

June 1980 ...... Born – Rockford, Illinois, USA

2003...... B.S. Biology, University of Illinois Urbana-

Champaign

2007...... M.S. Plant Pathology, Michigan State

University

2007 to present ...... Graduate Research Associate, Department

of Plant Pathology, The Ohio State

University

Publications

Ellis ML, Broders KD, Paul PA, Dorrance AE. 2011. Infection of soybean seed by

Fusarium graminearum and effect of seed treatments on disease under controlled conditions. Plant Disease. 95:401-407.

Zelaya-Molina, LX, Ellis, ML, Berry, SA, Dorrance, AE. 2010. First report of

Phytophthora sansomeana causing wilting and stunting on corn in Ohio. Plant Disease.

94: 125.

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Broders, KD, Lipps PE, Ellis ML, Dorrance AE. 2009. Pythium delawarii-a new species isolated from soybean in Ohio. Mycologia. 101: 232-238.

Ellis, ML. 2007. Distribution, identification, and population diversity of Armillaria spp. in Michigan cherry orchards. Thesis. Michigan State University. East Lansing, MI, USA.

Fields of Study

Major Field: Plant Pathology

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Table of Contents

Abstract ...... ii

Dedication ...... iv

Acknowledgements ...... v

Vita ...... vii

List of Tables ...... xiii

List of Figures ...... xix

Chapter Page

1. Introduction...... 1

2. Infection of soybean seed by Fusarium graminearum and effect of seed treatments on disease under controlled conditions ...... 32

Introduction ...... 33

Objectives ...... 36

Material and Methods ...... 37

Results ...... 42

Discussion ...... 44

Acknowledgements ...... 48 ix

List of References ...... 59

3. Two new species of Pythium, P. schmitthenneri and P. selbyi pathogen of corn and soybean in Ohio ...... 63

Introduction ...... 64

Material and Methods ...... 67

Results ...... 71

Taxonomy ...... 73

Discussion ...... 78

Acknowledgements ...... 83

List of References ...... 95

4. Identification of resistant genotypes and molecular mapping of quantitative trait loci in soybean against Fusarium graminearum ...... 98

Introduction ...... 99

Objectives ...... 103

Material and Methods ...... 103

Results and Discussion ...... 109

Acknowledgements ...... 114

List of References ...... 121

5. Identification of resistant genotypes and molecular mapping of quantitative trait loci in the soybean accession PI 424354 against Pythium irregulare ...... 130

Introduction ...... 131

Objectives ...... 136

Material and Methods ...... 136

Results ...... 142

Discussion ...... 147

Acknowledgements ...... 150

List of References ...... 165

6. Conclusions ...... 171

Bibliography ...... 182

Appendix A: Protocol to induce production of sporangia and zoospores for the identification of Pythium species ...... 203

Appendix B: Field history of mapping populations ...... 206

Appendix C: SSR markers and PAMSA primer pairs designed from SNP markers for mapping QTL conferring resistance to Fusarium graminearum ...... 210

Appendix D: Summary of polymorphic SNP markers between parental lines in mapping populations from 1,500 available markers ...... 214

Appendix E: Sources of seed used to identify resistance to Pythium irregulare ...... 217

Appendix F: Screening of 105 soybean genotypes for resistance to Pythium irregulare

...... 223

Appendix G: Introgression of plant introduction (PI 424354) on twenty chromosomes

...... 243

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List of Tables

Table 2.1. Analysis of variance for the effects of inoculum concentration and temperature on disease severity index following inoculation of soybean seeds with Fusarium graminearum in a rolled-towel assay ...... 49

Table 2.2. Analysis of variance for effects of fungicide seed treatments, isolate, and inoculum concentration on disease severity index following inoculation of soybean seeds with Fusarium graminearum isolates K95R and Fay11 in a rolled-towel assay ...... 50

Table 2.3. Mean disease severity following inoculation of soybean seeds with Fusarium graminearum in a rolled-towel assay ...... 51

Table 2.4. Seed treatment comparisons using an ordinal rating scale for diseased soybean seedlings with respect to fungicide following inoculation of soybean seeds with Fusarium graminearum in a rolled-towel assay ...... 52

Table 2.5. Mean disease severity following inoculation of soybean seeds with Fusarium graminearum for soybean seeds treated with strobilurin fungicides in a rolled-towel assay ...... 53

Table 3.1. The DNA sequence differences for the ITS region for Pythium schmitthenneri and Pythium selbii with members within the clade E ...... 84

Table 3.2. Species of Pythium used for the sequence comparison and analysis, along with their Genbank accession numbers ...... 85

Table 3.3. Comparison of morphological features of Pythium schmitthenneri (G7-1) with key members within clade E1 ...... 86

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Table 3.4. Comparison of morphological features of Pythium selbyi (G7-2) with key members within clade E1 ...... 88

Table 4.1. Mean disease severity index (DSI) following inoculation of soybean seed with 100 µl of 2.5x104 macroconidia/ ml of Fusarium graminearum in a rolled-towel assay ...... 115

Table 4.2. Quantitative trait loci for partial resistance to Fusarium graminearum that were identified via interval mapping (IM) and composite interval mapping (CIM) using 262 F6:8 recombinant inbred lines (RILs) of Conrad (Resistant) x Sloan (Susceptible) ...... 116

Table 5.1. Analysis of variance for standardized root weight and root rot score in a greenhouse screening during 2009 of 96 soybean genotypes for resistance to Pythium irregulare ...... 152

Table 5.2. Analysis of variance for standardized root weight and root rot score in a greenhouse screening during 2010 of 79 soybean genotypes for resistance to Pythium irregulare ...... 153

Table 5.3. Quantitative trait loci for partial resistance to Pythium irregulare from the plant introduction (PI) 424354 that were identified via interval mapping (IM) and composite interval mapping (CIM) using 2 BC1F2:3 populations ...... 154

Table 5.4. Putative marker associations for partial resistance to Pythium irregulare from the plant introduction (PI) 424354 that were identified via a one-way ANOVA (P < 0.05) ...... 156

Table B.1: Field history of Conrad x Sloan F6:8 mapping population ...... 207

Table B.2: Field history of Dennison x (Williams x PI 424354) BC1F2:3 mapping population ...... 208

Table B.3: Field history of OHS3032 x (Williams x PI 424354) BC1F2:3 mapping population ...... 209

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Table C.1: PAMSA primer pairs designed from SNP markers for mapping QTL conferring resistance to Fusarium graminearum ...... 211

Table C.2: SSR markers for mapping QTL conferring resistance to Fusarium graminearum ...... 213

Table D.1: Summary of polymorphic SNP markers between parental lines in mapping populations from 1,500 available markers ...... 215

Table E.1: Sources of seed used in a greenhouse experiment to identify sources of resistance to Pythium irregulare ...... 218

Table F.1: Experiment 2: Standardized root weight for 39 genotypes in a greenhouse screening for resistance to Pythium irregulare ...... 224

Table F.2: Experiment 3: Standardized root weight 40 genotypes in a greenhouse screening for resistance to Pythium irregulare ...... 226

Table F.3: Experiment 4: Standardized root weight 36 genotypes in a greenhouse screening for resistance to Pythium irregulare ...... 228

Table F.4: Experiment 5: Standardized root weight 39 genotypes in a greenhouse screening for resistance to Pythium irregulare ...... 230

Table F.5: Experiment 1: Root rot score data for 25 genotypes in a greenhouse screening for resistance to Pythium irregulare ...... 232

Table F.6: Experiment 2: Root rot score data for 39 genotypes in a greenhouse screening for resistance to Pythium irregulare ...... 234

Table F.7: Experiment 3: Root rot score data for 40 genotypes in a greenhouse screening for resistance to Pythium irregulare ...... 236

Table F.8: Experiment 4: Root rot score data for 36 genotypes in a greenhouse screening for resistance to Pythium irregulare ...... 238

Table F.9: Experiment 5: Root rot score data for 39 genotypes in a greenhouse screening for resistance to Pythium irregulare ...... 240

Table G.1: Summary of polymorphic molecular markers for PI 424354 and the recurrent parents in two BC1F2:3 mapping populations ...... 244

Table G.2: Polymorphic molecular markers for PI 424354 and the recurrent parents in two BC1F2:3 mapping populations for chromosome 1 (MLG D1A) ...... 245

Table G.3: Polymorphic molecular markers for PI 424354 and the recurrent parents in two BC1F2:3 mapping populations for chromosome 2 (MLG D1B) ...... 247

Table G.4: Polymorphic molecular markers for PI 424354 and the recurrent parents in two BC1F2:3 mapping populations for chromosome 3 (MLG N) ...... 249

Table G.5: Polymorphic molecular markers for PI 424354 and the recurrent parents in two BC1F2:3 mapping populations for chromosome 4 (MLG C1) ...... 251

Table G.6: Polymorphic molecular markers for PI 424354 and the recurrent parents in two BC1F2:3 mapping populations for chromosome 5 (MLG A1) ...... 252

Table G.7: Polymorphic molecular markers for PI 424354 and the recurrent parents in two BC1F2:3 mapping populations for chromosome 6 (MLG C2) ...... 253

Table G.8: Polymorphic molecular markers for PI 424354 and the recurrent parents in two BC1F2:3 mapping populations for chromosome 7 (MLG M) ...... 254

Table G.9: Polymorphic molecular markers for PI 424354 and the recurrent parents in two BC1F2:3 mapping populations for chromosome 8 (MLG A2) ...... 256

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Table G.10: Polymorphic molecular markers for PI 424354 and the recurrent parents in two BC1F2:3 mapping populations for chromosome 9 (MLG K) ...... 258

Table G.11: Polymorphic molecular markers for PI 424354 and the recurrent parents in two BC1F2:3 mapping populations for chromosome 10 (MLG O) ...... 259

Table G.12: Polymorphic molecular markers for PI 424354 and the recurrent parents in two BC1F2:3 mapping populations for chromosome 11 (MLG B1) ...... 260

Table G.13: Polymorphic molecular markers for PI 424354 and the recurrent parents in two BC1F2:3 mapping populations for chromosome 12 (MLG H) ...... 262

Table G.14: Polymorphic molecular markers for PI 424354 and the recurrent parents in two BC1F2:3 mapping populations for chromosome 13 (MLG F) ...... 263

Table G.15: Polymorphic molecular markers for PI 424354 and the recurrent parents in two BC1F2:3 mapping populations for chromosome 14 (MLG B2) ...... 265

Table G.16: Polymorphic molecular markers for PI 424354 and the recurrent parents in two BC1F2:3 mapping populations for chromosome 15 (MLG E) ...... 267

Table G.17: Polymorphic molecular markers for PI 424354 and the recurrent parents in two BC1F2:3 mapping populations for chromosome 16 (MLG J) ...... 268

Table G.18: Polymorphic molecular markers for PI 424354 and the recurrent parents in two BC1F2:3 mapping populations for chromosome 17 (MLG D2) ...... 270

Table G.19: Polymorphic molecular markers for PI 424354 and the recurrent parents in two BC1F2:3 mapping populations for chromosome 18 (MLG G) ...... 271

Table G.20: Polymorphic molecular markers for PI 424354 and the recurrent parents in two BC1F2:3 mapping populations for chromosome 19 (MLG L) ...... 273

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Table G.21: Polymorphic molecular markers for PI 424354 and the recurrent parents in two BC1F2:3 mapping populations for chromosome 20 (MLG I) ...... 275

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List of Figures

Figure 2.1. Disease severity index for soybean seedlings infected with Fusarium graminearum. Disease severity index was calculated by dividing the lesion length by the total length and multiplying by 100 ...... 54

Figure 2.2. Diseased seedlings infected by Fusarium graminearum. A) Ordinal scale used to rate seed and seedling infection caused by F. graminearum with 1= healthy plant no visible signs of colonization or decreased germination and 5= no germination, complete colonization of the seed. B) Soybean seedlings inoculated at different levels starting from the left with 0, 2.5x102, 2.5x103, 2.5x104, and 2.5x105 macroconidia/ml that were grown at 22°C. C-G) Soybean seed treatments from left to right in each picture show the noninoculated control, inoculated with 2.5 x 104 macroconidia/ml with the isolate K95R, and inoculated with 2.5 x 104 macroconidia/ml with the isolate Fay11: (C) noninoculated; (D) metalaxyl plus fludioxonil; (E) captan; (F) fludioxonil (high rate); and(G) azoxystrobin (high rate) ...... 55

Figure 2.3. Bar graph of the disease severity of soybean seedlings with respects to inoculum concentration and temperature following inoculation of soybean seed with Fusarium graminearum. Disease severity values are the mean percent area of disease divided by the total area x 100. Groups of bars followed by the same letter are not significantly different according to Fisher’s protected least significant difference (P < 0.05), based on the arcsine-transformed data. The experimental design was a randomized complete block design with two factors, including concentration and temperature. The experiment was repeated over time ...... 57

Figure 2.4. Bar graph of the disease severity of soybean seedlings with respects to isolate following inoculating soybean seeds with Fusarium graminearum. Disease severity values are the mean percent area of disease divided by the total area x 100. The experimental design was a complete randomized design with three replications that was repeated. The noninoculated control had no disease ...... 58

Figure 3.1. Pythium schmitthenneri sporangia. Terminal globose sporangia (A-E) and sporangia with discharge tube (A, D, E). Bars = 10 µm (A-C) and 100 µm (D,E) ...... 90 xix

Figure 3.2. Pythium schmitthenneri oogonia, antheridia, and oospores. Oogonia are terminal occasionally intercalary. Oospores are plerotic or nearly so and antheridia, indicated by arrows, are mostly diclinous (A, B, D). Bars = 10 µm ...... 91

Figure 3.3. Pythium selbyi sporangia. Terminal globose sporangia and sporangia with discharge tubes (C, D) and the beginning formation of a discharge tube (B). Bars = 10µm ...... 92

Figure 3.4. Pythium selbyi oogonia, antheridia, and oospores. Oogonia are intercalary (A-C, E) and terminal (D). Oospores are plerotic or nearly so, with mostly one (A-C) but often two oospores per oogonium (D, E). Antheridia, indicated by arrows, are hypogenous. Bars = 10 µm ...... 93

Figure 3.5. The majority-rule consensus tree from the Bayesian analysis of the ITS1- 5.8S-ITS2 sequence of the nuclear rDNA showing the positions of isolates of P. schmitthennerri and P. selbyi in relation to other known tax in clade E1 with Pythium ultimum var. ultimum as the outgroup. Bayesian posterior probabilities are displayed next to each node. Species names are followed by their Genbank accession number. Scale bar represents the expected changes per site ...... 94

Figure 4.1. Symptoms of Fusarium graminearum infection 7 dai on Plant introduction (PI) 424354 and Conrad (high levels of resistance) compared to Williams and Sloan (lower levels of resistance). Seed was inoculated with 2.4x104 macroconidia/ml in a rolled towel assay ...... 117

Figure 4.2. Distribution of best linear unbiased predictor (BLUP) values for the disease severity index (DSI) among F6:8 recombinant inbred lines (RIL) derived from a cross of Conrad (Resistant) x Sloan (Susceptible) at 7 dai with a 2.5x104 macroconidia/ml of Fusarium graminearum ...... 118

Figure 4.3. Genetic maps generated from the genotype data from the Conrad (Resistant) x Sloan (Susceptible) F6:8 recombinant inbred lines (RIL) using JoinMap4.0 (van Ooijen, 2006); and logrithim of odds (LOD) charts of the putative quantitative trait loci (QTL) from composite interval mapping (CIM) analysis by MapQTL 5.0 (van Ooijen, 2004). The chromosome number and assigned molecular linkage group (MLG) is listed above each linkage group. Significant P-values (P < 0.05) from the one-way ANOVA are listed beside each marker ...... 119

Figure 5.1. Symptoms of Pythium irregulare infection 14 dai and non-inoculated control (right) on plant introduction (PI) 424354 (high levels of resistance) compared to Williams (moderately susceptible). Seed was planted in infested vermiculite with a sand-cornmeal inoculum ...... 158

Figure 5.2. Distribution of root weight per seedling and root rot score among 192 and 127 F2 lines from two BC1F2:3 populations used the map resistance in the plant introduction (PI) 424354 to Pythium irregulare. The two populations used to map resistance in PI 424354 to P. irregulare in soybean included: 192 F2:3 plants of OHS 303 (moderately susceptible) x (Williams (moderately susceptible) x PI 424354) (A, B) and 127 F2:3 plants of Dennison (moderately susceptible) x (Williams x PI 424354) (C, D). For the phenotypic assays for the OHS303 populations, the average root weights per seedling were 0.38, 0.17, and 0.36, and the average root rot scores were 2.1, 4.1, and 2.2 for the parental lines PI 424354, Williams, and OHS303 respectively. For the phenotypic assays for the Dennison populations, the average root weights per seedling were 0.35, 0.02, and 0.32, and the average root rot scores were 2.3, 4.9, and 3.2 for the parental lines PI 424354, Williams, and Dennison respectively ...... 159

Figure 5.3. Genetic maps generated from the genotype data from the of OHS 303 (moderately susceptible) x (Williams (moderately susceptible) x PI 424354) BC1F2:3 population using JoinMap4.0 (van Ooijen, 2006); and logrithim of odds (LOD) charts of the putative quantitative trait loci (QTL) from composite interval mapping (CIM) analysis by MapQTL 5.0 (van Ooijen, 2004) for root weight and root rot score data. The chromosome number is listed above each linkage group ...... 161

Figure 5.4. Genetic maps generated from the genotype data from the of Dennison (moderately susceptible) x (Williams (moderately susceptible) x PI 424354) BC1F2:3 population using JoinMap4.0 (van Ooijen, 2006); and logrithim of odds (LOD) charts of the putative quantitative trait loci (QTL) from composite interval mapping (CIM) analysis by MapQTL 5.0 (van Ooijen, 2004) for root weight and root rot score data. The chromosome number is listed above each linkage group ...... 163

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CHAPTER 1

INTRODUCTION

Ohio ranks sixth for production of soybean [Glycine max (L.) Merr] in the United

States. During 2008 to 2010, the United States produced between 3.0 and 3.3 billion bushels of soybean on 75.7 to 77.5 million acres, with Ohio producing approximately 36-

49 bushels per acre on 4.5 to 4.6 million acres. The number of soybean acres in Ohio has increased since 1997 when the acreage was approximately 4.2 million. There are approximately 10 million acres planted to field crops [corn (Zea mays L.), soybean and wheat (Triticum aestivum L.)] in Ohio each year (National Agricultural Statistics Service: http://www.nass.usda.gov) and almost 1/3 of the acreage in Ohio is now continuously cropped to soybean. With the increased production and acreage in continuous soybean in the state of Ohio, seedling diseases have also increased over the past decade. Soybean seedling diseases ranked from second to sixth among diseases that suppressed soybean yields in the United States from 1997-2007, with the greatest yield suppression from

2005-2007 (Wrather and Koenning, 2009). In Ohio during 2003-2005, seedlings diseases reduced soybean yields by 1.10 x 105, 1.845, 5.814 tons respectively. During this time frame, Ohio along with Illinois, Kansas, Minnesota, and North Dakota, were the five states that had the greatest yield suppression due to seedling diseases (Wrather and

Koenning, 2006).

The most common soybean seedling pathogens in Ohio include: Pythium spp.,

Phytophthora sojae Kaufm. and Gerd., Fusarium graminearum Schwabe (teleomorph:

Gibberella zeae (Schwien.) Petch), and Rhizoctonia solani Kühn (teleomorph

Thanatephorus cucumeris (A.B. Frank) Donk). Seedling diseases caused by these pathogens have most likely increased due to a number of changes and shifts in soybean

2 production practices. One such practice is earlier planting dates, which means that seeds are more likely to be planted under cool, wet environmental conditions that can delay seed germination, thus favoring the growth of soil-borne pathogens (Broders et al.,

2007a,b). Earlier plant dates under these conditions also increase the length of time fungicide seed treatments must provide adequate protection from these pathogens (Broders, 2008).

Another factor that has likely influenced the level of seedling diseases in Ohio soybean fields is consecutive years of above-average rainfall during April and May. High soil moisture and cool soil temperatures have been shown to be correlated with seedling disease incidence, which can have a direct impact on yield (Wrather et al., 2001, 2003; Wrather and

Koenning, 2006, 2009). No-till and reduced tillage practices may also contribute to the increase in disease incidence and severity by providing favorable soil conditions for both pathogen growth and survival (Fernandez and Fernandes, 1990; Workneh et al., 1999). Crop rotation practices may also have an impact on the severity of seedling diseases seen in the state. In Ohio, producers often use a corn-soybean or a corn-soybean-wheat rotation, however, in recent years a number of producers plant fields continuously with soybean. A number of pathogens such as Pythium spp. can infect both soybean and corn (Broders et al.,

2007a, 2009; Dorrance et al., 2004), whereas F. graminearum is a pathogen to all three crops

(Broders et al., 2007b). Finally there have been shifts in fungicide seed treatments and in soybean germplasm over the past years. Soybean germplasm has shifted most likely due to the fact that industry now dominates in development of new cultivars compared to the public sector (Diers and Kim, 2008), especially with the development of genetically modified (GM) soybeans, where 87-90% of all soybean acres are planted with GM soybeans (National

Agricultural Statistics Service: http://www.nass.usda.gov). It is also important to note that

3 the diversity within elite lines carrying the „Roundup Ready‟ gene from some companies is limited, due in part to the limited exchange of germplasm (Sneller, 2003). Fungicide chemistries that are broad-spectrum and highly effective seed treatments, such as Rival® and captan are no longer available, and a shift to new chemistries with active ingredients that have narrower pathogen efficacy profiles has occurred.

F. graminearum is well known as an economically important pathogen of cereal crops that can cause substantial yield and quality losses. In wheat, barley (Hordeum vulgare L.), and oat (Avena sativa L.), it is the cause of Fusarium head blight (FHB), and in corn, this fungus can cause Gibberella ear and stalk rot (McMullen et al., 1997; Sutton,

1982). In addition to head blight and stalk rot, F. graminearum is also an important seedling pathogen of both corn (Carter et al., 2002) and wheat (Jones, 1999). F. graminearum is not limited to cereal host and has been identified as a pathogen to dry bean (Phaseolus vulgaris L.) (Bilgi et al., 2011), canola (Brassica napus L. and Brassica rapa L.) (Chongo et al., 2001), potato (Solanum tuberosum L.) (Ali et al., 2005), and sugar beet (Beta vulgaris L.) (Hanson, 2006).

F. graminearum survives over winter on corn debris (Cotton et al., 1998; Leslie et al., 1990; and Windels et al., 1998) and has also been isolated from various parts of the soybean plant as well as soybean debris (Anderson et al., 1988; Baird et al., 1997; Clear et al., 1989; Fernandez and Fernandes, 1990; Harrington et al., 2000; Jacobsen et al.,

1995; Leslie et al., 1990; Osorio and McGee, 1992; and Wicklow et al., 1987). In 2004, this was found to be the cause of pod blight and root rot on soybeans (Martinelli et al.,

2004; and Pioli et al., 2004). Subsequent studies have confirmed the pathogenicity to

4 soybean and also its role as a seedling pathogen (Broders et al., 2007b; Xue et al., 2006;

Xue et al., 2007).

In Ohio, the impact of F. graminearum as a seedling pathogen to soybean is still not known. For instance, the optimum conditions for infection and disease development and the effect of this pathogen on stand establishment and yield are unknown.

Macroconidia have the highest rates of germination at high relative humidity (>80%) at

~20°C in the dark (Beyer et al., 2004), while the vegetative growth conditions for many

Fusarium species are a 12-hour period of light at 25°C and a 12-hour period of darkness at 20°C (Leslie et al., 2006). Brennan et al. (2003) found the temperature range for mycelial growth inhibition of wheat seedlings to be 10-30°C, with an optimum temperature of 25°C. Therefore, it seems reasonable to assume that F. graminearum would be most pathogenic to soybean seedlings at 25°C. However, at this temperature soybean seeds can germinate more quickly, making them less susceptible to disease, while cooler temperatures of around 18°C can delay germination, making seeds and seedlings more susceptible to disease. In this scenario, the delayed germination time may provide a longer infection period, whereas with warmer temperatures, seedlings germinate more quickly, becoming less susceptible possibly with ontogenic resistance playing a role.

Seed treatments used in the past that had broad efficacies to a number of seedling pathogens may have prevented F. graminearum from having a major impact on soybean.

Captan and Rival® were highly effective seed treatments in corn and soybean, respectively; but are no longer available for a number of reasons. Previous work by

Broders et al. (2007b) evaluated the efficacy of seed treatments on F. graminearum using amended agar plate assays to test the following fungicides: azoxystrobin, trifloxystrobin, fludioxonil, and captan. Fludioxonil was the only fungicide that inhibited mycelia growth. However, fludioxonil insensitive mutants that were pathogenic on soybean were readily generated during the assay. New soybean seed treatment chemistries are now available but their efficacy towards F. graminearum is unknown. In addition, the association between results from amended-agar plate assays and in vivo responses to seed treatments is also unknown.

In addition to F. graminearum, a number of Pythium spp. have been associated with severe stand establishment issues in Ohio (Dorrance et al., 2004; Borders et al.,

2007a; Broders et al., 2009). Pythium spp. are commonly associated with seed and seedling diseases of soybean, and infections can result in both pre- and post-emergence damping-off (Brown and Kennedy, 1965; Griffin, 1990; Rizvi and Yang, 1996).

Surviving plants may be able to grow and produce a root system; however these non- lethal infections generally lead to reduced root and shoot growth, resulting in reduced plant vigor and consequently yield. Within the north central region, several species of

Pythium have been reported to cause seedling disease of soybean, of which Py. aphanidermatum (Edison) Fitzp., Py. debaryanum Auct. non R. Hesse, Py. irregulare

Buisman, and Py. ultimum Trow were identified most frequently (Rizvi and Yang, 1996,

Zhang et al., 1998; Zhang and Yang, 2000). In Ohio, greater than 20 described species of

Pythium have been confirmed as pathogens on soybean and corn, including; Py. irregulare, Py. inflatum V.D. Matthews, Py. torulosum Coker & P. Patt., Py. ultimum

Trow var. ultimum, Py. ultimum var. sporangiiferum Drechsler, Py. dissotocum Drechler,

Py. pleroticum T. Itô, Py. aphanidermatum, Py. arrhenomanes Drechsler, Py. attrantheridium Allain-Boulé & Lévesque, Py. graminicola Subraman., Py. hypogynum

Middleton, Py. longandrum B. Paul, Py. middletonii Sparrow, Py. oligandrum Drechsler,

Py. orthogonun Ahrens, Py. parvum Ali-Shtayeh, Py. perplexum H. Kouyeas & Theoh.,

Py. sylvaticum W.A. Campb. & F.F. Hendrix, Py. vanterpoolii V. Kouyeas & H.

Kouyeas, Py. echinulatum V.D. Matthews, Py. helicoides Drechsler, Py. catenulatum

V.D. Matthews, Py. paroecandrum Drechsler, and Py. splendens Hans Braun (Broders et al., 2007,2009; Deep and Lipps, 1996; Dorrance et al., 2004; Rao et al., 1978).

In addition to known species of Pythium found in the two surveys of Ohio production fields, a newly described species, Py. delawarii Broders, Lipps & Dorrance

(Broders et al., 2009) and a putative new species tentatively classified as Pythium Group

7 (G7) were also reported. Interestingly, the G7 isolates were baited from soils from 30% of the 88 production fields used in a statewide survey (Broders et al., 2009). The G7 group of isolates has a radiate to rosette growth pattern in potato-carrot agar, with usually terminal oogonia, plerotic oospores, diclinous and monoclinous antheridia and mycelial growth of 7-10 mm per day. Sporangia were not observed in grass blade culture. The

ITS1-5.8S-ITS2 region of the ribosomal DNA was similar to Py. acrogynum Y.N. Yu and Py. hypogynum (Broders et al., 2009).

Currently most seedling diseases, such as those caused by Pythium spp. and F. graminearum are managed by planting seeds treated with a combination of seed-applied fungicides. Fludioxonil is an effective fungicide against F. graminearum (Broders et al.,

2007b), while metalaxyl or mefenoxam are specifically targeted towards oomycete pathogens, such as Pythium (Cohen and Coffey, 1986; Erwin and Ribeiro, 1996; Yang,

1999). However, some Pythium spp. are insensitive to metalaxyl (Dorrance et al., 2004;

Broders et al., 2007a). Some of the newer seed treatments contain active ingredients that belong to a relatively new fungicide class, the Quinone Outside Inhibitor (strobulurin), including; azoxystrobin, triflozystrobin, and pyraclostrobin. In a previous study of the effects of these new strobulurin fungicides on Pythium spp. and F. graminearum, some were found to be insensitive (Broders et al., 2007a,b). The efficacy these fungicides have not been evaluated for every species of Pythium.

The inconsistency in efficacy across the range of soybean seedling diseases and the diversity of seedling pathogens that can vary within a given field make management of these pathogens difficult. This is especially challenging with the changing composition of Pythium spp. across geographical locations, within fields, as well as the environmental conditions that occur during seed germination and emergence (Rizvi and Yang, 1996,

Zhang et al., 1998; Zhang and Yang, 2000, Broders et al., 2009). For these reasons, new management strategies, such as resistance, should be considered. Finding sources of resistance to these seedling pathogens that are commonly expressed in cultivars used in

Ohio or resistance genes that could be introduced into those lines would greatly enhance the ability to manage seedling diseases. This would also reduce the reliance on fungicide seed treatments. In addition, Pythium spp. tend to vary in their pathogenicity to soybean.

The less aggressive “root nibblers” could be managed through the use resistant varieties

8 or through a management strategy using a combination of fungicide seed treatments and resistance.

There are three general types of plant resistance to pathogens: innate immunity or basal resistance is non-specific recognition of broadly conserved pathogen features such as flagellin from bacteria or chitin from fungal cell walls; qualitative (complete, vertical, major-gene, or narrow-spectrum) resistance is usually conditioned by a single gene and is involved in specific recognition of pathogen effectors or their targets; quantitative

(incomplete, horizontal, minor-gene, or broad-spectrum) resistance is conditioned by multiple genes of partial effect. In some pathosystems, qualitative resistance tends to be less durable than quantitative resistance, since pathogens can adapt to single-gene mediated resistance more easily than to the multiple genes often involved in quantitative resistance (Poland et al., 2009; St.Clair, 2010). Quantitative resistance is broad-spectrum and effective against many pathogen pathotypes, including biotrophs, and is often the type of resistance associated with necrotrophic pathogens, with very few cases of qualitative resistance observed (Oliver and Ipcho, 2004). Many Pythium spp. are necrotrophs, while others are hemibiotrophs, producing appressoria and haustoria-like structures during the biotrophic phase (Latignhouwers et al., 2003). Two of the most pathogenic and frequently isolated species of Pythium from soybean in Ohio include Py. irregulare and Py. ultimum var. ultimum (Broders et al., 2009). Pythium ultimum var. ultimum is a necrotroph, while Py. irregulare can be classified as a hemibiotroph. The necrotrophic nature of Py. irregulare has been well documented as it produces both lytic enzymes (Deacon, 1979) and phytotoxins (Brandenburg, 1950) during the infection

9 process that degrade plant tissue. However, it is important to note that this line between biotrophic and necrotrophic behavior is not definitive. While the plants response to Py. irregulare is similar to that observed following infection by a necrotrophic pathogen, Py. irregulare does have infection structures similar to biotrophic pathogens. The infection process of Py. irregulare has been observed in two systems, Arabidopsis (Arabidopsis thanliana (L.) Heynh.) (Adie et al., 2007) and with the moss Physcomitrella patens

(Hedw.) Bruch & Schimp (Oliver et al., 2009). In both systems, infection starts in a biotrophic phase with the production of appressoria and haustoria-like structures, with further hyphal ingression being primarily intracellular moving through the vascular tissues of the plant (Adie et al., 2007; Oliver et al., 2009).

There is controversy as to whether F. graminearum uses a necrotrophic mode of infection to invade the wheat spiklets (Leonard and Bushnell, 2003) or a biotrophic mode, initially absorbing nutrients from the extracellular exudates in the apoplast. Once the host cell death response is initiated, it switches over to a necrotrophic phase accompanied by intercellular colonization of the cell lumen (Brown et al., 2010). More studies are required to determine if similar modes -of -action occur for non-cereal hosts, such as soybean. Although the Fusarium genus is heterogeneous, Fusarium virguliforme

O‟Donnell & T. Aoki ( telomorph belonging to Nectria sensu lato) (O‟Donnell et al.,

2010), the casual agent of Sudden Death Syndrome of Soybean (SDS), is a hemibiotroph, producing haustoria in root cells and lytic and digestive enzymes to colonize dead cells

(Roy et al., 1998). Even though a hemibiotroph, resistance to SDS is considered to be quantitative (Chang et al., 1997; Hnetkovsky et al., 1996; Meksem et al., 1999; Njiti et

10 al., 1998). This is mostly due to the nature of the pathogen where the root rot phase of the infection cycle tends to be controlled by different resistance mechanisms than the toxin production phase of the cycle which leads to foliar symptoms (Chang et al., 1997;

Hnetkovsky et al., 1996; Huang and Hartman et al., 1998; Killebrew et al., 1988;

Meksem et al., 1999; Melgar and Roy, 1994; Njiti et al., 1998; Rupe, 1989; Rupe et al.,

1991; Stephens et al., 1993).

Given that F. graminearum has recently been reported as a seedling pathogen to soybean, no studies have been done to identify or characterize resistance in this pathosystem. In other hosts of F. graminearum, resistance is quantitative (Anderson et al., 2001; Bai et al., 1999; Buerstmayr et al., 2002; Gervais et al., 2003; Waldron et al.,

1999; Zhou et al., 2002) and can be greatly influenced by the environment (Bai and

Shaner, 1994, 1996, 2004; Buerstmayr et al., 2011; Snijders and van Eeuwijk, 1991). In fact, resistance screening is considered more reliable in the field as compared to greenhouse assays because of the environmental effects (Geiger and Heun et al., 1989).

In work by Engle et al. (2003) using different inoculation methods, they were unable to separate the different types of disease resistance described for FHB in greenhouse assays.

Two main components of resistance to FHB include resistance to initial infection (type I), and resistance to spread of blight symptoms within a spike (type II) (Schroeder and

Christensen, 1963). Other components of resistance have been proposed including: resistance to kernel infection (type III); yield tolerance (type IV); and resistance to deoxynivalenol accumulation (type V) (Mesterhazy, 1995).

To date, resistance in soybean towards Pythium spp. is limited. Initial work from

Arkansas indicated that the soybean cultivar Archer has some resistance to different

Pythium spp. (Kirkpatrick et al., 2006). In a related study, Bates et al. (2008), evaluated resistance levels to Py. ultimum, Py. irregulare, Py. aphanidermatum, Py. vexans de

Bary, and another unknown Pythium spp. designated as group HS. They reported that the soybean cultivar Archer as resistant to Pythium aphanidermatum (Bates et al., 2008).

This cultivar also has the Rps1k gene for resistance to P. sojae. More recently, in a mapping study, resistance to Py. aphanidermatum was shown to be independent of the

Rps1k gene in Archer, and the Pythium resistance gene, Rpa1, mapped to chromosome 13

(MLG F) (Rosso et al., 2008). This was the first resistance gene in soybean that conferred resistance to a Pythium species. Other single dominate genes have been reported for other

Pythium species, including resistance in corn against Py. inflatum (Yang et al., 2005) and in common bean against Py. ultimum var. ultimum (in Levesque et al., 2010 from personal communication with Mahuku).

The Py. ultimum var. ultimum genome was recently sequenced and the results suggest that not all oomycete plant pathogens contain similar „toolkits‟ for survival and pathogenesis. Unlike Phytophthora spp. and downy mildews, the genome sequence of

Py. ultimum var. ultimum lacks RXLR effectors and has a limited number of Crinkler genes (Cheung et al., 2008; Levesque et al., 2010). Within the Saprolegniales,

Aphanomyces euteiches Drechsler was also sequenced, and no RXLR effector-like proteins were present (Gaulin et al., 2008). Instead a novel YxSL[RK] family of candidate effectors were identified in the sequence of Py. ultimum var. ultimum

(Levesque et al., 2010). Levesque et al. (2010) suggested that the RXLR effectors may be confined to the Peronosporaceae family and may represent an adaptation to facilitate biotrophy, while the absence of RXLR effectors in Py. ultimum var. ultimum correlates with the lack of gene-for-gene specific resistance generally linked with necrotrophic pathogens and may also be functionally associated with the broad host range of Pythium pathogens. Based on these recent findings and the non-host-specific nature of Py. ultimum, the type of resistance will quantitative in nature, or deployed by novel effectors proteins such as the YxSL[RK] effectors.

In a review by Poland et al. (2009), six hypotheses were proposed on mechanisms that are associated with quantitative resistance. Three of these six hypotheses correspond well with possible resistance mechanisms towards necrotrophic pathogens. The first of these hypotheses states that quantitative resistance is conditioned by genes regulating host morphological and developmental phenotypes. This has been well documented in many necrotrophic plant-pathogen systems (Poland et al., 2009), including FHB of wheat. Putative quantitative trait loci (QTL) associated with morphological and developmental characteristics such as spike morphology, date of anthesis, date of flower opening, spike emergence time, and plant height have all been found to be correlated with resistance in wheat to FHB (Buerstmayr et al., 2011; Ellis et al., 2005; Faris and Gill,

2002; Gilsinger et al., 2005; Grausgruber et al., 1998; Simons et al., 2006). Poland et al.

(2009), therefore hypothesize that these genes affecting growth, development, and plant architecture have pleiotrophic effects on disease resistance. Another hypothesis that is often associated with necrotrophic pathogens is that quantitative resistance loci are

13 components of chemical warfare. Necrotrophic pathogen attack often implicates the production of phytotoxins which promote plant disease. The host often responds with enzymes that detoxify these compounds, or with the deployment of phytoalexins, which are associated with quantitative disease resistance (Poland et al., 2009). The last hypothesis states that quantitative resistance loci are involved in defense signal transduction (Poland et al., 2009). An example of this can be seen with the necrotrophic phase of the pathogen Py. irregulare, where abscisic acid was found to be an essential signal affecting jasmonic acid biosynthesis and for the activation of defenses in

Arabidopsis (Adie et al., 2007).

Identifying sources of quantitative resistance may be the best management strategy for necrotrophic seedling pathogens affecting soybean in Ohio. Py. irregulare,

Py. ultimum var. ultimum, Py. ultimum var. sporangiiferum, and F. graminearum had the highest levels of pathogenicity and were recovered from the greatest number of fields in previous surveys in Ohio (Dorrance et al., 2004; Broders et al., 2007a; 2009). One of the most interesting questions will be if two different pathogens with similar life styles such as Py. irregulare and F. graminearum share similar sources of resistance, QTL or mechanisms that could be utilized by plant breeders to create soybean varieties with durable resistance to seedling pathogens.

Currently there are a number of germplasm resources for many plants including soybean that can be screened to find novel sources of resistance. These resources include: currently grown commercial cultivars, obsolete commercial cultivars, breeding lines and stocks, landrace cultivars, undomesticated forms of the crop, plant introductions (PIs),

14 and related species (Stoskopf et al., 1993). The first place to look for sources of resistance is in commercial cultivars of soybean. Modern commercial cultivars are considered to be superior germplasm that have been adapted to a specific environment (Stoskopf et al.,

1993). In soybean, development of modern cultivars has shifted from the public sector and is now dominated by the private sector. As a result, industry breeding has made a great impact on increasing yield gains in modern cultivars, however, when screened for resistance to soybean aphid (Aphis glycines Matsumura) no resistance was found in these modern lines. This may be due to several decades of intensive and selective breeding and the narrow genetic base from which the modern soybean cultivars in North America were developed from (Diers and Kim, 2008). Gizlice et al. (1994) showed that >85% of the genes present in North American public cultivars could be traced to 17 ancestral and first progeny. This low genetic diversity was also found to exist in private cultivars (Sneller,

1994). From these findings, it has become important for breeders to examine new sources of genetic variation in exotic germplasm. The United States Department of Agriculture-

Agricultural Research Service (USDA-ARS) maintains a collection of over 21,000 soybean accessions, including related perennial species, the wild ancestor Glycine soja, and about 19,000 accessions from Asian landraces and elite cultivars at the University of

Illinois (http://www.ars-grin.gov/cgi-bin/npgs/html/site.pl?SOY). A number of studies have since examined germplasm from South Korea, Japan, and China for genetic diversity and new genetic material to help improve agronomic traits in soybean and improve the genetic diversity in the North American populations (Brown-Guedira et al.,

2000; Burnham et al., 2002; Cui et al., 2000a, 200b; Diers and Kim, 2008; Dorrance and

Schmitthenner, 2000; Li et al., 2001; Li and Nelson, 2001; Nichols et al., 2007; Ude et al., 2003). In a study by Dorrance and Schmitthenner (2000), 32 PIs, mostly from South

Korea, were identified as having potential new Rps genes to P. sojae. A number of these

PIs also had high levels of partial resistance to P. sojae. Currently a number of beneficial alleles from exotic germplasm have been adapted into the North American soybean germplasm for improved resistance to the following pathogens: soybean cyst nematode

(SCN) (Concibido et al., 1997; Riggs et al., 1998); soybean rust (Patzoldt et al., 2007); brown stem rot (Lewers et al., 1999; Patzoldt et al., 2005a,b); Phytophthora root rot

(Hegstad et al., 1998); soybean mosic virus (Hayes et al., 2000). Based on these studies, when initially screening germplasm for disease resistance, it is important to examine a genetically diverse collection including both cultivars and PIs.

There are a number of different types of populations used to map traits, such as resistance or QTL, in soybean including: F2 populations, backcross populations, recombinant inbreed lines (RILs), and near-isogeneic lines (NILs). Molecular marker assisted selection (MAS) has aided breeders with introgressing key traits into new cultivars/germplasm, compared to conventional breeding but can also enhance the conventional breeding process. This technology is especially useful when dissecting QTL into their individual components (Tanksley et al., 1993; Quarrie, 1996; Tuberosa et al.,

2002), and can also allow breeders to select for traits in earlier generation (Mackill, 2003;

Varshney et al., 2005; Wang et al., 2005). There are currently a large number of molecular markers that have been developed for soybean and can assist in mapping resistance. Cregan et al. (1999) developed a composite genetic linkage map for soybean

16 that contains over 800 SSR markers. Song et al. (2004) constructed an integrated genetic linkage map of soybean with over 1,000 simple sequence repeats (SSRs), 700 restriction fragment length polymorphisms (RFLPs), 73 random amplification of polymorphic

DNAs (RAPDs), 6 amplified fragment length polymorphisms (AFLPs), and 24 classical traits. Since then Choi et al (2007) discovered 5551 single-nucleotide polymorphisms

(SNPs) and was able to develop a consensus map containing 1,158 sequence tagged sites

(STS). However, only 3,000 of the SNPs discovered were used in the map which was developed using low-throughput technologies involving limited multiplexing. In 2008,

Hyten et al. (2008), used high-throughput genotyping with the GoldenGate assay added another 12,000 newly discovered SNP markers along with the 2,600 markers not added into the map by Choi et al. (2007). The soybean genome (Schmutz et al., 2010),

Phytozome v. 7.0: Glycine max (www.phytozome.net/soybean), is now available and can serve as an additional toolbox for soybean breeders and in mapping resistance or QTL associated with disease.

With the increase of soybean seedling diseases over the past decade in the state of

Ohio, a number of questions should be addressed to aid in the management of these pathogens, particularly with the Pythium species complex and F. graminearum. The first questions to be addressed focus on the biology and characterization of these pathogens. In

Ohio, the impact of F. graminearum as seedling pathogen to soybean is still not known.

The first step in answering this question is to characterize the conditions required for infection and disease development; such as inoculum level and temperature, and to determine if the current seed treatments are protecting seedlings from this pathogen.

Broders et al. (2007b) examined the efficacy of fungicides against F. graminearum using amended agar plate assays to azoxystrobin, trifloxystrobin, fludioxonil, and captan, however these chemistries have yet to be tested as actual seed treatments.

Due to the widespread nature and pathogenicity of the unidentified Pythium species, G7, morphological characterization and sequence analysis should be completed for a number of isolates. Preliminary studies by Broders (2008) indicated that there was sequence variation within the ITS region and colony morphology that existed among the few isolates which were examined (unpublished data).

Completion of these initial questions to further characterize and understand the biology of these seedling pathogens is critically important to design and develop methods to identify and characterize sources of resistance towards seedling pathogens. Within

Ohio, the pathogens that had the highest levels of pathogenicity and were recovered from the greatest number of fields in previous surveys (Broders et al., 2007a,b, 2009; Dorrance et al., 2004) included: Py. irregulare, Py. ultimum var. ultimum, Py. ultimum var. sporangiiferum, and F. graminearum.

Therefore the hypotheses, objectives and approaches of this dissertation were as follows:

Hypotheses to be tested for objective 1: (1) Isolates of F. graminearum collected from wheat, corn, and soybean in Ohio will all be highly pathogenic to soybean, as shown in previous studies (2); High temperatures tested that are common during planting in Ohio will favor pathogen growth, however, at lower temperatures plants will become more

18 susceptible to disease; (3) Seed treatments commonly used for soybean will be effective in reducing disease caused by F. graminearum.

Objective 1: Develop a screening method to identify the inoculum levels and temperature parameters for optimum disease development which can then be utilized to test fungicide efficacy and resistance to F. graminearum.

Approach: To develop a timely and effective method that can be utilized by researchers and industry to test new fungicide chemistries, as well as other parameters that may provide a better understanding of F. graminearum and its role as a seed and seedling pathogen to soybean.

Hypothesis to be tested for objective 2: The Pythium species defined as G7 will be closely related but morphological distinct from P. acrogynum and P. hypogynum and the isolates from this unidentified species may in fact be two distinct varieties or two closely related species.

Objective 2: Characterize a new pathogenic species of Pythium isolated from soybean and corn.

Approach: To identify key morphological differences and variation in sequence data to descriptions of closely related but distinct Pythium spp.

Hypotheses to be tested for objective 3: Quantitative resistance will be identified in adapted and ancestral soybean germplasm to a broad range of Pythium spp. and F. graminearum.

Objective 3: Identify and characterize sources of resistance to F. graminearum and the most prevalent species of Pythium causing disease in Ohio soybean fields.

Approach: Screen germplasm, especially genotypes with known resistance genes or

QTL to other pathogens, for resistance to Pythium irregulare and F. graminearum.

Mapping populations that currently exist can be utilized to map resistance found in the initial germplasm screening.

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CHAPTER 2

INFECTION OF SOYBEAN SEED BY FUSARIUM GRAMINEARUM AND

EFFECT OF SEED TREATMENTS ON DISEASE UNDER CONTROLLED

CONDITIONS.

Ellis, M. L., Broders, K. D., Paul, P. A., and Dorrance, A. E. 2011. Infection of soybean seed by Fusarium graminearum and effect of seed treatments on disease under controlled conditions. Plant Dis. 95:401-407.

INTRODUCTION

A high incidence of soybean [Glycine max (L.) Merr] seedling disease causes poor stands, which can result in added costs of replanting and reduced yields as a result of later planting dates. The most common soybean seedling pathogens in Ohio include

Pythium spp., Phytophthora sojae Kaufm. and Gerd., and Rhizoctonia solani Kühn

(teleomorph Thanatephorus cucumeris (A.B. Frank) Donk). Recently, Fusarium graminearum Schwabe (teleomorph: Gibberella zeae (Schwien.) Petch) was identified as a pathogen of soybean (Broders et al., 2007b; Martinelli et al, 2004; Pioli et al., 2004;

Xue et al., 2006; Xue et al., 2007). This fungus is primarily regarded as an economically important pathogen of wheat (Triticum aestivum L.), barley (Hordeum vulgare L.), and oat (Avena sativa L.), where it causes Fusarium head blight (Bai and Shanner, 1994;

McMullen et al., 1997); and in corn (Zea mays L.), where it causes Gibberella ear and stalk rot (Sutton, 1982). F. graminearum also causes seedling diseases of both corn

(Carter et al., 2002) and wheat (Jones, 1999). In addition to its cereal hosts and soybean,

F. graminearum has also been identified as a pathogen to several other non-cereal hosts, including dry bean (Phaseolus vulgaris L.) (Bilgi et al., 2011), canola (Brassica napus L. and Brassica rapa L.) (Chongo et al., 2001), potato (Solanum tuberosum L.) (Ali et al.,

2005), and sugar beet (Beta vulgaris L.) (Hanson, 2006).

Prior to the recognition of F. graminearum as a significant pathogen of soybean, it had been isolated from various parts of the soybean plant as well as soybean debris

(Anderson et al., 1988; Baird et al., 1997; Clear et al. 1989; Fernandez and Fernandes,

1990; Harrington et al., 2000; Jacobsen et al., 1995; Leslie et al., 1990; Osorio and

McGee, 1992; Wicklow et al., 1987). These earlier reports were conflicting on whether F. graminearum was pathogenic to soybean (Agarwal, 1976; Anderson et al., 1988;

Chamberlain, 1972; Fernandez and Fernandes, 1990; Garcia-Romera et al., 1998; Miller et al., 1998; Wicklow et al., 1987; Wildermuth and McNamara, 1987). Wicklow et al.

(1987) first described F. graminearum as a secondary pathogen and others considered F. graminearum to be non-pathogenic to soybean (Chamberlain, 1972; Fernandez and

Fernandes, 1990; Garcia-Romera et al., 1998; Miller et al., 1998). This was due to failed attempts to complete Koch’s postulates, carried out through direct inoculations of the hypocotyls of seedlings (Chamberlain, 1972) or applications of spore suspensions of F. graminearum to flowers (Fernandez and Fernandes, 1990).

F. graminearum causes pod blight, seed and root rot, and pre- and post- emergence damping-off of soybean (Broders et al., 2007b; Clear et al., 1989; Martinelli et al., 2004; Pioli et al., 2004; Xue et al., 2006; Xue et al., 2007). Lesions observed in artificial inoculations on the roots first appear water-soaked, followed by a pinkish-brown discoloration spreading vertically in both directions (Xue et al., 2007). Lesions on seedlings observed in the field are similar to those observed in the laboratory (personal observation). Infections at later growth stages (R5) developed external browning and internal discoloration of the stem. Pod blight and interveinal chlorosis of the leaves followed by plant wilt and death has only been reported from Argentina (Pioli et al.,

2004). Seed infected by F. graminearum at harvest appear pink to reddish in color; however, seed infection may also be asymptomatic. Deoxynivalenol and HT-2 mycotoxins have been detected in symptomatic soybean seed infected by F.

34 graminearum and F. sporotrichioides (Clear et al., 1989).

There has been an increase in occurrence of soybean seedling diseases in Ohio, such as those caused by F. graminearum. This may be due to earlier planting dates (prior to 10 May) where cool, moist soil conditions delay seed germination and favor the growth of soil-borne pathogens (Broders et al., 2007a,b). In addition, no-till and reduced- tillage practices also increase seedling disease incidence and severity by creating soil conditions that are favorable for pathogen growth and survival (Fernandez and

Fernandes, 1990; Workneh et al., 1999). In Ohio, producers predominantly use a corn- soybean or corn-soybean-wheat rotation in combination with reduced-tillage or no-tillage to conserve soil, prevent erosion, and increase organic matter. These practices may also favor the survival of F. graminearum since the fungus can overwinter on residue of all three crops (Baird et al., 1997; Cotton and Munkvold, 1998; Leslie et al., 1990; Windels et al., 1988). Isolates of F. graminearum collected from wheat and corn were moderately to highly pathogenic to soybean (Broders et al., 2007b; Xue et al., 2004; Xue et al.,

2007). Xue et al., (2007) proposed that selection pressure for highly aggressive F. graminearum isolates may exist for this rotation.

The active ingredients used in seed-treatment fungicides have changed in the past few years, possibly contributing to increase in seedling disease incidence in soybean.

Products such as Captan (37.4% captan; Bayer CropScience, NC) and Rival (19.8% captan plus 8.4% PCNB plus 1.0% thiabendazole; Gustafson, Plano, TX), which were highly effective seed-treatment fungicides, are no longer commonly used. The sensitivity of F. graminearum to recently labeled seed-treatment fungicides such as azoxystrobin,

35 trifloxystrobin, as well as standard fungicides, fludioxonil, and captan, were evaluated using amended agar plate assays. Of these fungicides, fludioxonil was the only one that inhibited mycelia growth (Broders et al. 2007b). Interestingly, F. graminearum mutants insensitive to fludioxonil were readily generated during the laboratory assay, although none were recovered from the field (Broders et al., 2007b). The efficacy of these fungicides as seed treatments for control of F. graminearum should be examined to confirm the results obtained from amended agar plate assays.

The impact of F. graminearum as a seedling pathogen of soybean in Ohio is still unknown. The first step in addressing this question would be to determine the optimum conditions required for infection and disease development, such as inoculum concentration and temperature. The optimum conditions for germination of F. graminearum macroconidia are relative humidity >80%, based on in vitro studies at approximately 20°C in darkness (Beyer et al., 2004). Conditions for vegetative growth of

Fusarium spp. were a 12-h period of light at 25°C and a 12-h period of darkness at 20°C

(Leslie and Summerell, 2006). Thus, disease severity would be expected to increase at temperatures between 20 and 25°C. However, at these warmer temperatures soybean seeds germinate more quickly than at cooler temperatures, possibly making them less susceptible to infection.

OBJECTIVES

The objective of this study was to address some of the factors that may have contributed to the emergence of F. graminearum as a soybean pathogen by determining

(i) optimal inoculum concentrations and temperature required for disease development by

F. graminearum; and (ii) the efficacy of recently labeled seed treatment fungicides for the control of seedling disease caused by F. graminearum.

MATERIALS AND METHODS

Isolates and inoculum preparation. Six single-macroconidia isolates of F. graminearum were used in this study. Isolates were collected from infected corn during the spring of 2004 (K95R and K85R), soybean during the spring of 2007 (Fay11 and

Fay15), and wheat during the summer of 2007 (Van and Woo). All isolates were collected from symptomatic seedlings in Ohio fields and maintained on carnation leaf agar (CLA). The corn isolates were used in an earlier study by Broders et al. (2007b), and all other isolates used in this study were previously untested on soybean. Inoculum was prepared by growing isolates on CLA for 10-14 days with a 12-h light period to enhance macroconidia production. The macroconidia were dislodged into 2-3 ml of sterilized water from the agar surface with a sterile glass rod. This was transferred from the plate with a pipette and filtered through three layers of cheesecloth to reduce the amount of mycelial fragments present in the inoculum. The filtered macroconidial suspension was then quantified using a hemacytometer (Bright-Line Hemacytometer: Hausser Scientific,

Horsham, PA) as described by Tuite (1969). This was repeated four times and an average concentration was calculated. Sterile water was added to the inoculum to achieve the desired macroconidia concentrations, and the adjusted suspensions were then recounted to verify the proper concentrations.

Optimum conditions for disease development. To determine the optimum inoculum concentrations and temperature required for disease development, a rolled-towel assay was used. Twenty seeds of soybean ‘Sloan’, susceptible to F. graminearum, were placed in a row on a moistened towel and each seed was inoculated with a 100-µl suspension of macroconidia at one the following concentrations using the previously tested corn isolate

K95R (8): 0, 2.5x102, 2.5x103, 2.5x104, or 2.5x105 macroconidia/ml. Another moistened towel was placed over the inoculated seeds and the towels were rolled and then placed in

25-liter buckets. The experimental design was a randomized complete block with temperature and inoculum concentration in a split plot arrangement. Temperature was the whole plot and inoculum concentration the subplot. The experiment was repeated once, with time as the blocking factor. For each temperature, there were three towels per concentration. The towels were randomized within a bucket and care was used to avoid cross contamination from the different concentrations. A black plastic bag was then placed over each bucket, and these were placed in a growth chamber at 18, 22, or 25ºC.

After 7 days, the seedlings were rated using two methods. First, a disease severity index was calculated by measuring the root, shoot, and the length of the lesion on each plant with a ruler and then dividing the lesion size by the total length and multiplying by

100 (Fig. 2.1). Seeds that did not germinate and were colonized by F. graminearum were given an index rating of 100 %. The second method rated seedlings using a 1-to-5 scale, where 5= no germination, complete colonization of the seed; 4= germination, complete colonization of the seed, and 75% or more of the seedling root with lesions; 3= germination, some colonization of seed, and 20-74% of the root with lesions; 2=

38 germination, little colonization of the root, and 1-19% of the root with lesions; 1= germination, healthy seedling with no visible signs of colonization (Fig. 2.2A).

The disease severity index data was arcsine-transformed and analyzed using the general linear model procedure (PROC GLM) of SAS (SAS Institute Inc., Cary, NC). Means were compared using Fisher’s protected least significant difference (LSD) at P = 0.05.

The ordinal rating data was analyzed using a nonparametric approach as described by

Shah and Madden (2004) using PROC MIXED of SAS where isolate and inoculum concentration were treated as fixed effects and the relative pathogenicity among isolates and treatments were compared using contrasts.

Pathogenicity assays. To select isolates to evaluate fungicide efficacy to F. graminearum, the pathogenicity of six isolates of F. graminearum collected from soybean (Fay11 and Fay15), corn (K85R and K95R), and wheat (Woo and Van) in Ohio was evaluated. The isolates collected from soybean and wheat had not previously been tested for pathogenicity, whereas the corn isolates had previously been tested in greenhouse assays by Broders et al. (2007b). The isolates were compared using the rolled-towel method and an inoculum concentration of 2.5x104 macroconidia/ml, at 22ºC.

Noninoculated seeds were used as the check to ensure that other seed colonizing pathogens were not present in the seed. These results were not included in final analysis.

The experimental design was a randomized complete block, with each isolate randomly assigned to three separate buckets within a growth chamber. Because each bucket provided a physical separation among the replicates of the isolates and we assumed that

39 the microenvironment was homogeneous within buckets but heterogeneous among buckets, we considered each bucket to be a block and random effect in the analysis.

The disease severity index data was arcsine-transformed and then analyzed using

PROC GLM of SAS (SAS Institute Inc.). As a preliminary step in the analysis, Levene’s test of homogeneity of variance was performed using PROC GLM and plots of the raw data were evaluated to determine whether the data from the two experiments could be pooled. Because the test was not statistically significant (P = 0.08), the experiments were combined and analyzed as one. The transformed means were compared using Fisher’s protected least significant difference (LSD) at P = 0.05.

Fungicide efficacy assay. Soybean seed was treated with one of the following fungicides: captan at 61.9 g a.i. (Captan 400; Bayer CropScience, NC), fludioxonil at 2.5 g a.i. (Maxim 4S; Syngenta Crop Protection Inc., NC), fludioxonil at 5.0 g a.i. (Maxim

4S), azoxystrobin at 1.0 g a.i (Dynasty; Syngenta Crop Protection Inc., NC), azoxystrobin at 3.0 g a.i. (Dynasty), and mefenoxam + fludioxonil at 3.75 g a.i. + 2.5 g a.i. (Apron

Maxx RTA; Syngenta Crop Protection Inc., NC) per 100 kg. Fungicide-treated seeds were placed on towels as described above and each seed was inoculated with a 100 µl of

F. graminearum spore suspension. The experimental design was completely randomized with a factorial arrangement of inoculum concentration (2.5x104 or 2.5x105 macroconidia/ml), fungal isolate (Fay11 and K95R), and fungicide seed treatment.

Nontreated seeds were used as checks. Noninoculated and nontreated seed for all treatments were also included to verify seed health, but were not included in the

40 statistical analysis. The buckets were placed in an incubator at 22ºC and rated after 7 days using both methods described previously. This experiment was done three times.

Levene’s test of homogeneity of variance and raw data plots were used as previously described to compare experiments, and data from the three experiments were pooled for analysis. Disease severity index data were arcsine-transformed and analyzed using PROC GLM of SAS (SAS Institute Inc.). Means were compared using Fisher’s protected LSD at P = 0.05. Data for the ordinal rating scale were analyzed using a nonparametric approach as described by Shah and Madden (2004). The ordinal rating was analyzed using PROC MIXED of SAS where isolate, inoculum concentration, and fungicide treatments were treated as fixed effects and the relative pathogenicity and fungicide efficacy among isolates and treatments were compared using contrasts.

Strobilurin fungicide efficacy assay. A separate rolled-towel assay was used to evaluate the strobilurin fungicides azoxystrobin at 3.0 g a.i. (Dynasty), trifloxystrobin at 10.0 g a.i.

(Trilex; Bayer CropScience, NC), and pyraclostrobin at 9.9 g a.i. (Stamina; BASF Corp.,

NC) per 100 kg. The experiment was similar to the previous fungicide seed treatment experiment except that only one isolate, Fay11, and only one inoculum concentration,

2.5x104 macroconidia/ml, was used. The design for this experiment was a completely randomized design in which the isolate and noninoculated controls were separated by a tray within the bucket to avoid cross contamination. There were three towels per treatment per experiment. The experiment was repeated.

The disease severity index data was arcsine-transformed and analyzed using

PROC GLM of SAS (SAS Institute Inc.). Levene’s test of homogeneity of variance was used to compare experiments. Because there was no significant difference (P = 0.70) between experiments, they were analyzed together. The transformed means were compared using Fisher’s protected LSD at P = 0.05.

RESULTS

Inoculum concentration and temperature. Based on the arcsine-transformed data for disease severity index, the main effect of temperature and the interaction between inoculum concentration and temperature were not statistically significant (P < 0.05).

However, the main effect of inoculum concentration on disease development was highly significant (P<0.001) (Table 2.1). As expected, higher disease severity developed at the highest inoculum concentrations (Fig. 2.3). At the lowest concentration of 2.5 x 102 macroconidia/ml, the mean disease severity was 13.8% across all temperatures and lesions were small, averaging between 5 and 10 mm in length or absent (Fig. 2.2B). At higher inoculum concentrations of 2.5 x 104 and 2.5 x 105 macroconidia/ml, disease severity was greater than 50% (Fig. 2.3). Symptoms at these higher inoculum concentrations included water-soaked lesions that were dark-brown to pinkish-brown in color and covered a majority or the entire soybean seedling. Seeds were often completely colonized by the fungus and were discolored red to pink, with the mycelium often present on the seeds (Fig. 2.2B).

Isolate pathogenicity. All of the isolates were able to infect and colonize soybean seedlings to different degrees. Based on the arcsine-transformed data for the disease severity index, the isolates were significantly different (P = 0.016), with the highest mean, 75.1% seedling affected by K85R, from corn and the lowest by the isolate Woo from wheat, at 44.8% for disease severity (Fig. 2.4). There was a significant difference

(P < 0.05) between the isolate Woo and three of the six isolates (Fig. 2.4). This isolate produced fewer macroconidia than the other isolates, which may have contributed to the relatively lower level of disease compared to the other isolates.

Fungicide efficacy. For the fungicide efficacy assay, there were significant interactions for isolate by fungicide (P = 0.042), and isolate by concentration by fungicide (P =

0.006) for the arcsine-transformed data for the disease severity index (Table 2.2). The main effects of isolate, inoculum concentration, and fungicide were also significant (P <

0.001), with the fungicide having the most significant effect, with a greater than two-fold difference in the F-value (Table 2.2). All fungicides were significantly (P < 0.05) different from the nontreated controls, indicating that they all provided some level of protection. Seed treated with captan or fludioxonil had significantly lower disease severity across all isolates and concentrations, while seed treated with azoxystrobin had the highest (Table 2.3; Fig. 2.2C-G). There was no significant difference (P < 0.05) between the high and low fungicide rates for fludioxonil or captan, based on arcsine- transformed data for disease severity (Table 2.3). Contrasts were used to evaluate the ordinal rating scale. All seed treatments were significantly different from the nontreated

43 controls (P <0.0001), similar to the data for disease severity. The only difference was that the low and high fludioxonil rates were significantly different from each other (P =

0.0085) using the ordinal scale to rate disease (Table 2.4).

For the strobilurin fungicide seed treatment assay, there was a significant effect of treatment on the arcsine-transformed disease severity index (P = 0.046). Trifloxystrobin and pyraclostrobin had significantly lower disease severity than the nontreated seed (P <

0.05); however, there was no significant difference (P < 0.05) among the strobilurin seed treatments (Table 2.5), based on contrasts (data not shown).

DISCUSSION

This study addressed two important questions concerning the emergence of F. graminearum as a soybean pathogen: optimum inoculum and temperature parameters for disease development and the efficacy of fungicide seed treatments in a seed-based assay.

The results indicate that high levels of inoculum are necessary for seed and seedling infections to occur at temperatures conducive for seedling emergence. Severe symptoms on seedlings developed only when inoculum concentrations of 2.5 x 104 macroconidia/ml or higher were used. When the inoculum concentration was below this level, only small minute lesions developed on a few seedlings. It is unlikely that these small lesions would impede seedling growth. Field inoculum includes ascospores, macroconidia, and hyphal fragments on crop debris (Sutton, 1982). When seeds are planted into no-till fields, they often come into contact with all of these inoculum units. The rolled towel assay uses macroconidia, from which mycelium developed within 2 to 3 days after inoculation.

In wheat, the reemergence of Fusarium head blight, and in corn, increased prevalence of ear and stalk rot, all caused by F. graminearum, are linked due to widespread adoption of conservation tillage (Dill-Macky and Jones 2000; Munkvold,

2003). This fungus survives in crop residue left on the surface, thus increasing the inoculum density, and consequently, disease intensity, in fields planted into residue from previous host crops (Schaafsma et al., 2005). Hence, it is highly likely that the emergence of the organism as a pathogen of soybean is also associated with the widespread uses of minimum- and no-till cropping systems and the corresponding increase due to in-field inoculum density.

The range of temperatures evaluated in this study was representative of conditions that occur at the time of planting in Ohio. Infections of soybean from F. graminearum were similar across all temperatures evaluated in this study. Because seedling growth is reduced at lower temperatures, more time is available for the fungus to infect them.

However, fungal growth of F. graminearum was also reduced at lower temperatures in these studies. The optimum temperature range for growth of F. graminearum is reported to be 20 to 25ºC (Beyer et al., 2004; Leslie and Summerell, 2006). Thus, the seedlings and fungus would be expected to grow proportionally to one another at the different temperatures and low temperatures would not favor infections.

The rolled-towel inoculation method developed in this study provides a timely and effective method that can be utilized by researchers and industry to develop and test new fungicide chemistries, as well as other parameters that may provide a better understanding of F. graminearum and its role as a seed and seedling pathogen to

45 soybean. Fungicide seed treatments labeled for soybeans are changing as older chemistries are replaced with new active ingredients. Seed treated with captan and fludioxonil had the lowest disease severity compared to azoxystrobin. The newer class of fungicides known as strobilurins, did not effectively protect the seeds from infection caused by F. graminearum. It is important to note that some of the results from the rolled-towel assays were different from the previously reported amended agar assays using some of the same isolates (Broders et al., 2007b). In this study, captan performed equally to fludioxonil as a seed treatment, whereas in the amended agar assays, fludioxonil was the only fungicide that sufficiently inhibited mycelial growth (Broders et al., 2007b). This study found similar results to the amended agar assays, for azoxystrobin, trifloxystrobin (Broders et al., 2007b), and pyraclostrobin (M.L. Ellis and A.E. Dorrance, unpublished), in which there was not a significant reduction in mycelial growth compared to the nonamended controls. The mode of action of strobilurin is targeted towards spore germination by inhibiting mitochondrial respiration, which occurs by blocking electron transfer in cytochromes b and c1 (Ypema and Gold, 1999). Unlike the plate assays which measure mycelial growth, the rolled-towel method in this study evaluated the fungicides’ effect directly on macroconidia.

The strobilurin fungicides did not provide complete control, although disease severity was significantly reduced relative to the untreated check for two of the three fungicides. In addition, the seed-treatment fungicides Rival and Captan are no longer commonly used or available for soybean. Crop production is still predominately no-till or reduced tillage; therefore, a continued increase in severity of seed and seedling disease

46 caused by F. graminearum is expected. This will provide both a need and a challenge for industry to develop new chemistries for seed treatments that are broad spectrum for protection against the wide array of seedling pathogens. Another challenge industry will face when designing new products is the pathogen’s ability to mutate and overcome the fungicides’ ability to protect the seed from infection. Previous work by Broders et al.

(2007b) demonstrated that this is possible via the generation of fludioxonil mutants under laboratory conditions and, in this study, the low rate of fludioxonil was significantly different from the high rate using orthogonal contrasts. Although no fludioxonil mutants were recovered from the field to date, this could be a challenge in managing soybean seed and seedling diseases. Alternative strategies may be needed as Zhang et al. (2009) have reported that novel strains of Bacillus subtilis inhibited mycelial growth and macroconidial germination of F. graminearum and F. oxysporum in both in vitro and greenhouse assays.

Various factors may have prevented F. graminearum from emerging as a soybean pathogen prior to 2007: high inoculum levels required for disease to develop, seeds infected by F. graminearum may not have emerged from the soil, oomycete-selective media may have prevented the isolation of this pathogen, symptoms caused by F. graminearum are common to several other soybean pathogens, and fungicides previously used in soybeans were highly effective. No-till and reduced-tillage practices currently used in Ohio optimize favorable soil conditions for pathogen growth and survival

(Fernandez and Fernandes 1990; Workneh et al., 1999), likely increasing the amount of inoculum in the field. With increased inoculum levels and the previously effective

47 fungicides Rival and Captan no longer commonly used, it is possible that F. graminearum was able to emerge as a pathogen to soybean. Due to the limited choice of seed-treatment fungicides, identifying integrated management strategies for this newly emerged pathogen of soybean should be a priority.

ACKNOWLEDGEMENT

We thank F. Cruz, C. Cruz, W. Pipatpongpinyo, M. Benítez, M. Ortega, G.

Austin, and S. Dawes for technical assistance. This project was funded by State and

Federal Funds appropriated to the Ohio Agricultural Research and Development Center,

The Ohio State University. Funding was also provided, in part, through soybean checkoff dollars from Ohio Soybean Council.

Sourcez Df MS F value P value Block (B) 1 0.17 Temperature (T) 2 < 0.001 0.01 0.991 B x T (Error 1) 2 0.003 Concentration (C) 4 1.262 159.55 <0.001 T x C 8 0.006 0.83 0.597 Error 2 12 0.09

Table 2.1: Analysis of variance for the effects of inoculum concentration and temperature on disease severity index following inoculation of soybean seeds with Fusarium graminearum in a rolled-towel assay. z The experimental design was a randomized complete block, with temperature and inoculum concentration in a split-plot arrangement and time as the blocking factor. Disease severity data were arcsine- transformed. Inoculum concentrations were evaluated at 0, 2.5x102, 2.5x103, 2.5x10, and 2.5x105 macroconidia/ml. Temperatures were evaluated at 18, 22, and 25ºC.

Sourcez Df MS F value P value Isolate (I) 1 0.19 16.80 <0.001 Concentration (C) 1 0.30 26.81 <0.001 I x C 1 0.02 1.39 0.240 Fungicide (F) 6 2.15 189.37 <0.001 I x F 6 0.03 2.22 0.042 C x F 6 0.01 1.00 0.424 I x C x F 6 0.04 3.12 0.0059

Table 2.2: Analysis of variance for effects of fungicide seed treatments, isolate, and inoculum concentration on disease severity index following inoculation of soybean seeds with Fusarium graminearum isolates K95R and Fay11 in a rolled-towel assay. z The experimental design was completely randomized with three factors: isolate, concentration, and fungicide seed treatment. Disease severity data was arcsine-transformed. Concentrations were evaluated at 2.5x104 and 2.5x105. Soybean seed was nontreated or treated with one of the following fungicide seed treatments: captan at 61.9 g a.i. (Captan 400; Bayer CropScience), fludioxonil at 2.5 g a.i. (Maxim 4S; Syngenta Crop Protection Inc.), fludioxonil at 5.0 g a.i. (Maxim 4S; Syngenta Crop Protection Inc.), azoxystrobin at 1.0 g a.i. (Dynasty; Syngenta Crop Protection Inc.), azoxystrobin at 3.0 g a.i. (Dynasty; Syngenta Crop Protection Inc.) or mefenoxam + fludioxonil at 3.75 g a.i. + 2.5 g a.i. (Apron Maxx RTA; Syngenta Crop Protection Inc.) per 100 kg.

Mean percent seedling affectedy F. graminearum K95R Fay11 Fungicide treatmentz 2.5x105 2.5x104 2.5x105 2.5x104 Mean Non-treated 65.5 aA 55.0 aB 52.7 aBC 43.9 aC 54.3 Metalaxyl plus fludioxonil 17.3 dAB 19.3 cA 22.9 cA 11.1 dB 17.7 Captan 10.0 deA 5.8 dA 8.0 dA 9.3 dA 8.3 Fludioxonil (high rate) 6.8 eA 6.1 dA 6.9 dA 3.9 dA 5.9 Fludioxonil (low rate) 9.1 eA 4.3 dB 3.7 dB 6.4 dAB 5.9 Azoxystrobin (low rate) 55.1 bA 37.7 bB 37.2 bB 35.5 bB 41.3 Azoxystrobin (high rate) 42.2 cA 31.8 bBC 32.8 bAB 22.9 cC 32.4 Mean 29.4 22.8 23.5 19.0

Table 2.3: Mean disease severity following inoculation of soybean seeds with Fusarium graminearum in a rolled-towel assay. y Mean disease severity represents the lesion length divided by the total length of the seedling multiplied by 100. Disease severity data was arcsine-transformed; the actual means are reported in the table. The experimental design was completely randomized with three factors: isolate, concentration, and fungicide seed treatment. Values followed by the same lowercase letter for treatment and uppercase letter for isolate and concentration are not significantly different according to Fisher’s protected least significant difference (P < 0.05) based on the arcsine-transformed data. z Soybean seed was nontreated or treated with one of the following fungicide seed treatments: captan at 61.9 g a.i. (Captan 400; Bayer CropScience), fludioxonil at 2.5 g a.i. (Maxim 4S; Syngenta Crop Protection Inc.), fludioxonil at 5.0 g a.i. (Maxim 4S; Syngenta Crop Protection Inc.), azoxystrobin at 1.0 g a.i. (Dynasty; Syngenta Crop Protection Inc.), azoxystrobin at 3.0 g a.i. (Dynasty; Syngenta Crop Protection Inc.), or mefenoxam + fludioxonil at 3.75 g a.i.+ 2.5 g a.i. (Apron Maxx RTA; Syngenta Crop Protection Inc.) per 100 kg. 51

Contrasty ATSz P value

Control vs all treatments 2704.34 <0.0001 Control vs fludioxonil(avg)xx 4528.57 <0.0001 Control vs azoxystrobin (avg) 180.63 <0.0001 Metalaxyl plus fludioxonil vs fludioxonil (low)y 385.45 <0.0001 Metalaxyl plus fludioxonil vs captan 356.38 <0.0001 Captan vs fludioxonil (low) 0.09 0.7590 Captan vs azoxystrobin (low) 1538.08 <0.0001 Fludioxonil (low) vs azoxystrobin (low) 1725.65 <0.0001 Fludioxonil (low) vs fludioxonil (high)z 6.94 0.0085 Azoxystrobin (low) vs azoxystrobin (high) 23.77 <0.0001

Table 2.4: Seed treatment comparisons using an ordinal rating scale for diseased soybean seedlings with respect to fungicide following inoculation of soybean seeds with Fusarium graminearum in a rolled-towel assay. y Low = the low recommended and High = the high recommended fungicide seed treatment rate for fludioxonil and azoxystrobin; Avg = the combined average of the low and high recommended fungicide seed treatment rates for fludioxonil and azoxystrobin. Soybean seed was nontreated or treated with one of the following fungicide seed treatments: captan at 61.9 g a.i. (Captan 400; Bayer CropScience), fludioxonil at 2.5 g a.i. (Maxim 4S; Syngenta Crop Protection Inc.), fludioxonil at 5.0 g a.i. (Maxim 4S; Syngenta Crop Protection Inc.), azoxystrobin at 1.0 g a.i. (Dynasty; Syngenta Crop Protection Inc.), azoxystrobin at 3.0 g a.i. (Dynasty; Syngenta Crop Protection Inc.), or mefenoxam + fludioxonil at 3.75 g a.i.+ 2.5 g a.i. (Apron Maxx RTA; Syngenta Crop Protection Inc.) per 100 kg. z Analysis of variance-type statistic (30).

Treatmentz Percent seedling affected Non-treated 25.3 A Azoxystrobin 13.7 AB Pyraclostrobin 7.6 B Trifloxystrobin 7.3 B Mean 13.5

Table 2.5: Mean disease severity following inoculation of soybean seeds with Fusarium graminearum for soybean seeds treated with strobilurin fungicides in a rolled-towel assay. y Mean disease severity represents the lesion length divided by the total length of the seedling multiplied by 100. Disease severity data was arcsine-transformed; the actual means are reported in the table. The experimental design was completely randomized with three replications. Values followed by the same uppercase letter for treatment are not significantly different according to Fisher’s protected least significant difference (P < 0.05), based on the arcsine-transformed data. z Soybean seed was nontreated or treated with one of the following strobilurin fungicides: azoxystrobin at 3.0 g a.i. (Dynasty; Syngenta Crop Protection Inc.), trifloxystrobin at 10.0 g a.i. (Trilex; Bayer CropScience), or pyraclostrobin at 9.9 g a.i. (Stamina: BASF Corp.) per 100 kg.

Figure 2.1: Disease severity index for soybean seedlings infected with Fusarium graminearum. Disease severity index was calculated by dividing the lesion length by the total length and multiplying by 100.

Figure 2.2: Diseased seedlings infected by Fusarium graminearum. A) Ordinal scale used to rate seed and seedling infection

caused by F. graminearum with 1= healthy plant no visible signs of colonization or decreased germination and 5= no

germination, complete colonization of the seed. B) Soybean seedlings inoculated at different levels starting from the left with

0, 2.5x102, 2.5x103, 2.5x104, and 2.5x105 macroconidia/ml that were grown at 22°C. C-G) Soybean seed treatments from left 55 4 to right in each picture show the noninoculated control, inoculated with 2.5 x 10 macroconidia/ml with the isolate K95R, and

inoculated with 2.5 x 104 macroconidia/ml with the isolate Fay11: (C) noninoculated; (D) metalaxyl plus fludioxonil; (E)

captan; (F) fludioxonil (high rate); and(G) azoxystrobin (high rate).

Figure 2.3: Bar graph of the disease severity of soybean seedlings with respects to inoculum concentration and temperature following inoculation of soybean seed with

Fusarium graminearum. Disease severity values are the mean percent area of disease divided by the total area x 100. Groups of bars followed by the same letter are not significantly different according to Fisher’s protected least significant difference (P <

0.05), based on the arcsine-transformed data. The experimental design was a randomized complete block design with two factors, including concentration and temperature. The experiment was repeated over time.

Figure 2.4: Bar graph of the disease severity of soybean seedlings with respects to isolate following inoculating soybean seeds with Fusarium graminearum. Disease severity values are the mean percent area of disease divided by the total area x 100. The experimental design was a complete randomized design with three replications that was repeated. The noninoculated control had no disease.

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CHAPTER 3

TWO NEW SPECIES OF PYTHIUM, P. SCHMITTHENNERI AND P. SELBYI

PATHOGENS OF CORN AND SOYBEAN IN OHIO

Ellis, M.L., Broders, K.D., Paul, P.A., Dorrance, A.E. Two new species of Pythium, P. schmitthenneri and P. selbyi pathogens of corn and soybean in Ohio. Mycologia. IN PRESS.

INTRODUCTION

In Ohio, Pythium species have been reported to be important root rot pathogens of corn (Zea mays L.) (Deep and Lipps, 1996; Rao et al., 1978; Yanar et al., 1997), as well as seed and seedling pathogens of both corn and soybean [Glycine max (L.) Merr]

(Broders et al., 2007, 2009; Dorrance et al., 2004). In a series of studies, 24 described species of Pythium were isolated from diseased seed and seedlings of corn and soybean in

Ohio (Broders et al., 2007, 2009; Dorrance et al., 2004). During a recent survey of agronomic soils from 88 locations in Ohio, an unidentified group of Pythium, designated as Group 7 (G7), was recovered from 30% of the locations sampled using a high- throughput system of soil baiting, direct-colony polymerase chain reaction, single-strand conformational polymorphism (Broders et al., 2009). In this survey, G7 was recovered from four major soil regions in the state where grain production predominates. These four soil regions were covered by glacial ice during one or more glaciations, making the soils very deep to bedrock. The bedrock is commonly limestone, dolomite, and limy shales, which gives the soils in these regions relatively high levels of lime (The Ohio Department of Natural Resources: http://www.dnr.state.oh.us). Isolates within the G7 complex were identified in clay to clay-loam soils within each of these four regions, but were occasionally found in fields with either high sand or high silt content (Broders, 2008). In further analysis of G7, Koch’s postulates were established and a diverse set of isolates belonging to G7 were found to be moderately aggressive pathogens to both soybean and corn (Dorrance et al., unpublished data). The frequency and diverse distribution of this moderately pathogenic group of isolates throughout Ohio makes the characterization of

64 this group a priority for the future management of the Pythium complex affecting corn and soybeans.

Isolates of Pythium designated as G7 were separated into two distinct subgroups based on morphology and sequence analysis of the ITS1-5.8S-ITS2 region of the ribosomal DNA, both belonging to the Clade E1 according to Levesque and de Cock

(2004). The first group (G7-1) was most similar to P. acrogynum, P. hypogynum, and P. rostratum based on morphology, and in sequence analysis to P. acrogynum, and P. hypogynum. The second group (G7-2) was most similar to P. longandrum and P. longisporangium, based on both morphology and sequence analysis.

The ITS1-5.8S-ITS2 region of G7-1 was 99.9% similar to P. acrogynum and

99.8% similar to P. hypogynum, while only 82% similar to P. rostratum. Specifically,

G7-1 differs by one nucleotide from P. acrogynum and two nucleotides from P. hypogynum within the ITS2 region (Table 3.1). All of these species have mostly (sub) globose, non-proliferating sporangia, and plerotic or nearly plerotic oospores. They differ from each other on several key morphological characters. The discharge tubes for P. hypogynum are approximately twice the diameter of the sporangia (Middleton, 1943; van der Plaats-Niterink, 1981), while G7-1 has longer, narrower discharge tubes, which are two times greater than the length of the sporangia. Pythium acrogynum has ornamented oogonia (van der Plaats-Niterink, 1981), while G7-1, P. hypogynum and P. rostratum have smooth oogonial walls (Middleton, 1943; van der Plaats-Niterink, 1981). Both P. hypogynum and P. acrogynum have strictly hypogynous antheridial cells (Middleton,

1943; van der Plaats-Niterink, 1981) and G7-1 does not. Pythium rostratum has

65 monoclinous and occasionally hypogynous antheridia (Middleton, 1943; van der Plaats-

Niterink, 1981), while G7-1 has mostly diclinous, occasionally monoclinous, and rarely hypogynous antheridia.

In culture, the mycelium of P. hypogynum has a radiate pattern on cornmeal agar,

P. rostratum is submerged with a rosette pattern (Middleton, 1943; van der Plaats-

Niterink, 1981), and G7-1 is submerged on cornmeal agar with no distinct pattern. G7-1 mycelium also has a rosette to chrysanthemum pattern on potato carrot agar (PCA) and P. rostratum has a chrysanthemum pattern (Middleton, 1943; van der Plaats-Niterink,

1981). G7-1 has relatively low maximum temperature (32°C) for growth compared to P. hypogynum which reportedly has a maximum temperature of 37°C with traces of growth reported as high as 40°C; and P. rostratum has a maximum temperature of 35°C

(Middleton, 1943; van der Plaats-Niterink, 1981). Pythium hypogynum grew faster, with optimum daily growth rate of 16 mm at 34°C (Middleton, 1943; van der Plaats-Niterink,

1981), than G7-1 which grew at 13.5 mm at its optimum growth temperature at 21°C.

The ITS region of G7-2 was 97.1% similar to P. longandrum and 97.5% similar to P. longisporangium. Specifically within the ITS1 and ITS2 region, G7-2 differs by seven and 19 nucleotides from P. longandrum and nine and 14 nucleotides from P. longisporangium, respectively (Table 3.1). The morphology of G7-2 was most similar to

P. longandrum and P. longisporangium, which along with G7-2 all have globose to oval sporangia, smooth walled oogonia that are terminal to intercalary with one to two oospores per oogonium. Pythium longandrum has plerotic and aplerotic oospores (Paul,

2001), while P. longisporangium (Paul et al., 2005) and G7-2 have mostly plerotic

66 oospores and occasionally aplerotic oospores. The antheridia of P. longandrum and P. longisporangium are either hypogynous or monoclinous (Paul, 2001; Paul et al., 2005), while those of G7-2 are mostly hypogynous and only occasionally monoclinous. Pythium longandrum may possess some of the longest antheridia, 40–50 µm in length, described within the genus Pythium (Paul, 2001), while G7-2 has antheridia that are approximately

50% smaller, 10–22 µm in length and 6–13 µm wide. The size of antheridia of P. longisporangium was not included in the original description (Paul et al., 2005). Based on both the sequence and morphological analysis these two subgroups, previously designated as G7, are herein described as two new species, Pythium schmitthenneri sp. nov. (G7-1) and Pythium selbyi sp. nov. (G7-2).

MATERIALS AND METHODS

Isolation. All isolates used in this study were recovered from soils collected from fields in 11 counties in the corn and soybean production regions in Ohio between the 20 June and 19 July 2006 and 7 and 25 June 2007. The isolates were recovered from diseased soybean and corn seedlings that were used in a baiting procedure as described by Broders et al. (2009). Pieces of symptomatic tissue were plated on PIBNC (Schmitthenner and

Bhat, 1994), an oomycete-specific medium. Hyphal tips, from mycelia growing from diseased tissue, were transferred to potato-carrot agar (PCA) (van der Plaats-Niterink,

1981). Cultures were maintained on PCA slant vials at 10°C. Morphological structures were observed on PCA, cornmeal agar (Tuite, 1969), and sterile grass blades floated in sterile water (distilled 2: rain water 1) (Waterhouse, 1967; Appendix A). A protocol

67 using Chen and Zentmyer’s salt solution (Chen and Zentmyer, 1970) was used to favor development of sporangia and zoospores for observations. Morphological characteristics were compared to original species descriptions from standard Pythium keys (Middleton,

1943; Waterhouse, 1968; van der Plaats-Niterink, 1981), and also more recent descriptions of Pythium species from the E1 clade (Paul, 1992, 2001, 2002, 2003, 2006,

2009; Paul et al., 2005).

Assessment of growth rate at different temperatures. Growth rate of two isolates from each species, Cham222 and Darke1611 for P. schmitthenneri, and Pre234 and Miami212 for P. selbyi, were evaluated on PCA in 10-cm Petri dishes. A 5-mm diameter plug of each isolate was transferred to three replicate plates for each of the nine temperatures evaluated. The plates were incubated at 4, 12, 15, 18, 21, 25, 28, 32, or 34°C in the dark.

Growth rate was determined by measuring the colony diameter in two places at 48, 72,

96, and 120-h at each temperature. The experiment was repeated three times with at least

24 hours between each experiment. The average daily growth for each species from the three replications was calculated for each temperature.

Direct Colony-PCR and sequencing. The nuclear ribosomal DNA region of the internal transcribed spacer (ITS), including the 5.8S rDNA, and cytochrome oxidase I and II genes (cox I and cox II) of 21 isolates were sequenced via direct colony-PCR. A sterile toothpick was used to collect ≈1 mm3 of mycelia by gently touching the toothpick tip along the growing edge of a 3- to 5-day-old culture grown on PCA. The mycelia were

68 then added directly to a 50-μl reaction, which consisted of 10-μl of 5× Colorless GoTaq

Reaction buffer (Promega Corp., Madison, WI), 5-μl of 25-mM MgCl2, 3-μl containing

1.3-mM each dNTP, 0.5-μl of GoTaq Taq polymerase (Promega Corp.), 5-μl each of a 5- pmol concentration of primers, and 21.5-µl of sterile deionized water. The following pairs of primers were used in each of the reactions: ITS1

(TCCGTAGGTGAACCTGCGG) and ITS4 (TCCTCCGCTTATTGATATGC) (White et al., 1990) for amplification of the ITS region, FM59 (TTTATGGTCAATGTAGTGAAA) and FM 55 (GGCATACCAGCTAAACCTAA) for amplification of the cox I gene

(Martin, 2000), and FM 35 (CAGAACCTTGGCAATTAGG) and FM 52

(GTTGTGCTAATTCCATTCTAA) for amplification of the cox II gene (Martin, 2000).

PCR parameters were 94°C for 5 min; followed by denaturation at 94°C for 1 min; primer annealing for 1 min at 53°C for ITS, and 52°C for cox I and cox II; and elongation at 72°C for 1 min for 34 cycles for ITS and at 72°C for 2 min for 40 cycles for cox I and cox II; with a 5 min extension for ITS and 7 min extension for cox I and cox II at 72°C after the final cycle. PCR product was then purified using ExoSap (USB, Corp.,

Cleveland, OH) following manufacture instructions. For sequencing, 3-µl of primers

ITS1, ITS4, FM59, FM55, FM35, or FM52 at 2 pmoles/µl were added to 6-µl purified

DNA (3.6 ng per 100 bp). Sequencing was done at the Molecular and Cellular Imaging

Center at the Ohio Agricultural Research and Development Center (OARDC, Wooster,

OH).

Sequence analysis. DNA sequences were edited and aligned using CodonCode Aligner version 3.7.1 (CodonCode Corp., Dedham, MA). The sequence data was then compared to the ITS region, cox I gene, and cox II gene sequence data of species of Pythium (Table

3.2). The phylogenetic and molecular analyses were completed with MEGA version 4

(Tamura et al., 2007). After alignment with Clustal W, neighbor joining and maximum parsimony phylogenetic analyses with representative ITS sequences for each species and

ITS sequences from GenBank were performed. A bootstrap 50% majority-rule consensus tree that was generated with 1000 replications was included for the Clade E1 as designated by Levesque and de Cock (2004). A maximum likelihood phylogenetic tree was also inferred using Bayesian inference as implemented in MrBayes v. 3.1.2

(Huelsenbeck and Ronquist, 2001). A Bayesian analysis using the general time reversible

(GTR) model was selected for the entire unpartitioned alignment, with likelihood parameters settings (lset) number of substitution types (nst) = 6, with a proportion of sites invariable and the rest drawn from the gamma distribution (rate = invgamma). Four independent analyses, each starting from a random tree, were run under the same conditions for the combined gene alignment. Three hot and one cold chain Markov Chain

Monte Carlo with 1,000,000 generations with sampling every 100 generations was used for the analysis. The first 250,000 generations were discarded as the chains were converging (burn-in period).

RESULTS

Sequence analysis. The ITS 1, 5.8S, and ITS 2 region were 237, 159, and 475 bp, respectively. BLAST probes in GenBank found the sequence was unique compared to all other sequence in the database. The two species with the closest homology to our isolates were P. hypogynum and P. acrogynum, which had 99.9% sequence similarity with P. acrogynum and 99.8% sequence similarity with P. hypogynum according to the ITS 1,

5.8S, and ITS 2 region. Pythium schmitthenneri had one deletion and one transition from an adenine to a guanine within the ITS 2 region when compared to P. hypogynum, and one deletion within the ITS 2 region when compared to P. acrogynum (Table 3.1). Based on this information, the new species presented here belongs to the E1 clade according to

Levesque and de Cock (2004). Based on partial sequences of the cox I and cox II genes that have been deposited for P. acrogynum and P. hypogynum, P. schmitthenneri had

100% sequence identity. Partial sequence of 1277 bp starting at the 5’end of the cox I gene for P. schmitthenneri had 100% identity with 727 bp sequence from the 5’ end of the gene for P. acrogynum, and 680 bp for P. hypogynum Sequence of 928 bp from the 3’ end of the gene for P. hypogynum was also found to have 100% identity with 768 bp starting from the 5’ end of the sequence, which overlapped with 268 bp with the 3’ end of the sequence for P. acrogynum. Comparison of 684 bp starting at the 3’ end of cox II gene were found to have 100% identity to 563 bp of sequence for P. hypogynum and P. acrogynum, 97.5% identity to 563 bp of sequence for P. echinulatum and P. erinaceum, and 97.1% identity to 684 bp of sequence for P. rostratum, with 17 of the 20 nucleotide changes occurring within the 563 bp region that was compared with other members in the

71 clade E1. The nucleotide sequences of the ITS1, 5.8S, and ITS 2 ribosomal genes and partial sequences for the cox I and cox II genes were submitted to GenBank [JF836869,

JF895534, JF895530, JF836870, JF895535, JF895531].

For the G7-2 isolates The ITS 1, 5.8S, and ITS 2 region were 236, 159, and 491 bp, respectively. BLAST queries in GenBank found that the sequence was unique. The two species with the closest homology to our isolates were P. longandrum with 97.1% sequence similarity and P. longisporangium with 97.5% similarity, according to the ITS

1, 5.8S, and ITS 2 region. There were five transitions and two transversions within the

ITS 1 region and ten transitions, four transversions, four deletions, and one insertion within the ITS 2 region when compared to P. longandrum. Compared to P. longisporangium, there were five transitions, three transversions, and one insertion within the ITS 1 region, and five transistions, five transversions, four deletions, and one nucleotide was inconclusive based on available sequence data within the ITS 2 region

(Table 3.1). Based on this information the new species presented here belongs to the E1 clade according to Levesque and de Cock (2004). Partial sequences of 1277 bp starting at the 5’end of the cox I gene were 98.1% similar to P. longisporangium, 97.6% similar to

P. longandrum (680 bp from the 5’ end), 96.3% similar to P. schmitthenneri, 96.6% similar to P. acrogynum and P. echinulatum (727 bp from the 5’ end), and 95.4 % similar to P. hypogynum (768 bp from the 3’ end). Comparison of 684 bp starting at the 3’ end of cox II gene, P. selbyi had close homology to P. schmitthenneri 97.4% and P. rostratum

97.1% in sequence identity, and P. hypogynum and P. acrogynum with 97.2% sequence similarity to 563 bp. The cox II gene was not available for P. longandrum and P.

72 longisporangium. The nucleotide sequence of the ITS1, 5.8S, and ITS 2 ribosomal genes and the partial sequences for the cox I and cox II genes were submitted to GenBank

[JF836871, JF895536, JF895532, JF836872, JF895537, JF895533].

TAXONOMY

Pythium schmitthenneri Ellis, Broders, and Dorrance sp. nov. Figs. 3.1-3.2

MycoBank MB 561984

Coloniae in agar PCA demergatur parte, plerumque chrysanthemal ad rosette, hyphis usque ad 4–8 µm crassis compositae. Zoosporangia terminalia, rare interposita, globosa leviter ellipsoideae vel limoniform, 17–43 µm diam., 48 usque dum µm longis limonform, non-prolificantes. Zoosporae 7–10 µm longa. Oogonia laevia, terminalia, interdum intercalaria, globosa, interdum elongata, 19–26 µm diam, paries 0.7–1.8 µm crassus. Oosporae pleroticae, vel fere, globosae, unus oosporae per oogonium, interdum duo oosporae per oogonium, 14–23 µm diam., paries 1–2.5 µm crassus. Antheridia diclinata, interdum monoclinata, raro hypogyna, plerumque singularia raro > 1 per oogonia, 10–25 µm longa, 6 to 12 µm crassi. Typus in the Centraalbureau voor

Schimmelcultures (CBS H-20613).

Mycelial growth on PCA partially submerged with a rosette to chrysanthemal growth pattern, and on cornmeal submerged with no distinct pattern. The main hyphae was 4–8 µm diam. Asexual structures rarely form in grass blade culture, whereas sexual structures form in abundance. Asexual structures form in abundance in Chen-Zentmyer’s salt solution. Sporangia globose to slightly ellipsoidal or limoniform, non-proliferating,

17–43 µm diam. (av. 32-µm), up to 48-µm in length when limoniform, mostly terminal or rarely intercalary. The discharge tube arising from the sporangia was long, over two times in length of the sporangia and narrow (Fig. 3.1). Zoospores 7–10 µm in length.

Oogonia smooth walled, spherical, at times elongated, terminal, occasionally intercalary, 19–26 µm diam. (av. 23-µm). The oogonial stalk was 3–10 µm. The oogonial wall was 0.7–1.8 µm thick. Antheridia 10–25 µm long and 6 to 12 µm wide, mostly diclinous, occasionally monoclinous, or rarely hypogynous. Each oogonium was supplied by usually one, occasionally as many as three antheridia. Oospores plerotic, or nearly so,

14–23 µm in diam. (av. 20-µm), usually one but occasionally two oospores per oogonium. The oospore wall was smooth and 1–2.5 µm thick (Fig. 3.2). Daily growth on

PCA was 0.7-mm at 4°C, 7-mm at 12°C, 9-mm at 15°C, 12-mm at 18°C, 13.5-mm at

21°C, 13-mm at 25°C, 11.5-mm at 28°C, and 6-mm at 32°C, and 0-mm at 34°C.

Holotype. UNITED STATES, Ohio: Darke County. Isolate Darke1611 designated as the holotype, was recovered from soybean (Glycine max L. Merr.) root tissue by using a soil baiting procedure from agronomic soil collected during the summer of 2006, collector K.

Broders. The dried herbarium material was deposited at the Centraalbureau voor

Schimmelcultures (CBS), Utrecht, Netherlands, collection (CBS H-20613). A live culture as the ex-holotype was also deposited (CBS 129726). The complete ITS sequence, and partial sequences of the cox I and cox II genes were deposited in GenBank (accession

Nos. JF836869, JF895534, JF895530).

Additional specimens. UNITED STATES, Ohio: Pickaway County. Isolate Pick1415 was recovered from corn (Zea mays L.) root tissue by using a soil baiting procedure from agronomic soil collected during the summer of 2006, collector K. Broders. The live culture and dried herbarium material were deposited at the Centraalbureau voor

Schimmel-cultures, Utrecht, Netherlands, collection (paratype, CBS 129727, CBS H-

20614). The complete ITS sequence, and partial sequences of the cox I and cox II genes were deposited in GenBank (accession Nos. JF836870, JF895535, JF895531).

Etymology. The name is taken from August F. Schmitthenner (1926- ), an emeritus professor in the Department of Plant Pathology at the Ohio State University. During

1965-66 on sabbatical leave at the Imperial College, England, Schmitthenner studied the physiology and taxonomy of Pythium in collaboration with Grace Waterhouse of the

Commonwealth Mycological Institute, Key, Surrey. It was this and subsequent work on

Pythium that led to his worldwide recognition for expertise in the taxonomy of this genus

(Williams and Ellett, 1998).

Pythium selbyi Ellis, Broders, and Dorrance sp. nov. Figs. 3.3-3.4

MycoBank MB # 561985

Coloniae in agar PCA demergatur parte, plerumque rosette ad radiata, hyphis usque ad 4–

7 µm crassis compositae. Zoosporangia terminalia, rare interposita, globosa leviter ellipsoideae, 24–41 µm diam. Zoosporae 7–10 µm longa. Oogonia laevia, terminalia, intercalaria, globosa, interdum elongata, 26–30 µm diam, paries 0.8–1.3 µm crassus.

Oosporae pleroticae, vel fere, globosae, unus oosporae per oogonium, frequento duo oosporae per oogonium, 18–26 µm diam., paries 1–2.5 µm crassus. Antheridia hypogyna, interdum monoclinata, raro diclinata, plerumque 1–2 antheridia per oogonia, raro >2 per oogonia, 10–22 µm longa, 6 to 13 µm crassi. Typus in the Centraalbureau voor

Schimmelcultures (CBS H-20615).

Mycelial growth on PCA partially submerged with a radiate to rosette growth pattern and the main hyphae 4–7 µm diam, some branching occurring in older hyphae.

Asexual structures rarely formed in grass blade culture, whereas sexual structures were much more abundant. Sporangia, form in abundance in Chen-Zentmyer’s salt solution.

Sporangia 24–41 (av. 35-µm) µm diam, mostly terminal or rarely intercalary, globose to slightly ellipsoidal (Fig. 3.3). Zoospores 7–10 µm in length.

Oogonia smooth walled, spherical, at times elongated, terminal, intercalary, 26–

30 µm diam (av. 27.5-µm). Oogonial wall 0.8–1.3 µm thick. Antheridia mostly hypogynous, at times monoclinous, rarely diclinous. Each oogonium supplied by 1–3 antheridial cells 10–22 µm long and 6–13 µm wide. Oospores plerotic, or nearly so, 18–

26 µm in diam. (av. 23-µm), usually one but frequently two oospores per oogonium. The oospore wall was 1–2.5 µm thick (Fig. 3.4). Daily growth on PCA was 1-mm at 4°C, 7- mm at 12°C, 9-mm at 15°C, 11.5-mm at 18°C, 13-mm at 21°C, 12-mm at 25°C, 3.5-mm at 28°C, and 0.5-mm at 32°C, and 0-mm at 34°C.

Holotype. UNITED STATES, Ohio: Preble County. Isolate Pre234, was recovered from corn (Zea mays L.) root tissue by using a soil baiting procedure from agronomic soil

76 collected during the summer of 2007, collector K. Broders. The dried herbarium material was deposited at the Centraalbureau voor Schimmel (CBS)-cultures, Utrecht,

Netherlands, collection (CBS H-20615). A live culture, ex-holotype, was also submitted to CBS (CBS 129728) The complete ITS sequence, and partial sequences of the cox I and cox II genes were deposited in GenBank (accession Nos. JF836871, JF895536,

JF895532).

Additional specimens. UNITED STATES, Ohio: Champaign County. Isolate Cham264 was recovered from soybean (Glycine max L. Merr.) root tissue by using a soil baiting procedure from agronomic soil collected during the summer of 2006, collector K.

Broders. The live culture and dried herbarium material were deposited at the

Centraalbureau voor Schimmel-cultures, Utrecht, Netherlands, collection (paratype, CBS

129729, CBS H-20616). The complete ITS sequence, and partial sequences of the cox I, and cox II genes were deposited in GenBank (accession Nos. JF836872, JF895537,

JF895533).

Etymology. The name is taken from Augustine D. Selby (1859-1923) a professor in the

Department of Botany at the Ohio Agricultural Experiment Station (OAES). Although not the first to work on plant diseases in Ohio, Selby is considered the first plant pathologist by profession at the OAES. During his time he described a number of diseases including the Colletotrichum pathogen causing wheat anthracnose and the

Fusarium (Gibberella) pathogen causing wheat scab. Other contributions include

77 numerous publications such as the first and second Ohio weed manuals and A Condensed

Handbook of Diseases of Cultivated Plants in Ohio which was used as a text book throughout the United States. Selby was a founding member of the American

Phytopathological Society (APS) and its publication Phytopathology and he was the third president of APS. The Department of Plant Pathology in Wooster is now housed in Selby

Hall (Williams and Ellett, 1998).

DISCUSSION

Pythium schmitthenneri and Pythium selbyi both have morphological attributes that distinguish them from other known species of Pythium within the E1 clade designated by

Levesque and de Cock (2004) (Tables 3.3-3.4). The sequence data for the isolates designated as P. schmitthenneri and P. selbyi were unique according to the ITS 1, 5.8S,

ITS 2 region when compared with other members belonging to the E1 clade (Table 3.1-

3.2, Fig. 3.5). Based on the ITS region, the ten isolates designated as P. schmitthenneri which were collected from eight different counties in Ohio had identical sequences, and the ten isolates designated as P. selbyi from six different counties in Ohio had identical sequences. One isolate had unique sequence data to the other 20 isolates. This isolate had

99% a homology to P. longandrum and P. longisporangium, in the ITS 1, 5.8S, ITS 2 region. Further examination of this isolate is in progress to assess if this is also a new species, but more isolates with identical sequence are required to verify that it is not a variant of either P. longandrum or P. longisporangium.

It has recently been proposed that Pythium be split into five new genera based on phylogeny and morphology (Uzuhashi et al., 2010). In this study, the E1 clade would fall under the newly proposed genus Globisporangium, which is characterized by the globose sporangia of its members. However, this genus is composed of phylogenetically distinct species thus Uzuhashi et al. (2010) suggested that further examination of the taxonomy of this genus is required. If these five new genera names are accepted by the Pythium community, P. schmitthenneri and P. selbyi would be transferred to the genus

Globisporangium.

There are currently over 26 species within the E1 and E2 clade (Paul, 2009), including P. schmitthenneri and P. selbyi. Comparisons of sequences from the ITS 1,

5.8S, ITS 2 region, along with morphology, are the most common method to confirm speciation in Pythium. The cox I, cox II, and β-tubulin genes, and the D1, D2, and D3 of the adjacent large subunit nuclear ribosomal DNA have all been examined for sequence variation among species of Pythium (Levesque and de Cock, 2004; Martin, 2000; Villa et al., 2006). However, insufficient data exist within a number of clades to adequately use these regions for comparison among species. The β-tubulin gene, for example, has not been sequenced for all of the species within the E1 clade.

There is also some uncertainty as to how much variation within the ITS region is needed to be considered a new species and this may vary depending on the clade being examined. This has been observed among species of Phytophthora, where the ITS region may reveal little difference between closely related but distinct species (Kang et al.,

2010). It has been suggested that P. hypogynum and P. acrogynum are possibly one

79 species due to their similarity in morphology, as P. acrogynum was placed in the group of doubtful or excluded species by van der Plaats-Niterink (1981); the ITS 1, 5.8S, ITS 2 region (Levesque and de Cock, 2004); and the cox II gene, which have 100% sequence identity. In a recent review, Hyde et al. (2010) discussed the importance morphology still plays when classifying taxa and strongly suggest that mycologist return to the field, recollect species, and re-typify taxa with living cultures. Kang et al. (2010), also discussed the potential pitfalls in sequence-based identification. In both reviews, they raise the question as to how many genes and how much variation within these genes is needed to be considered a new species. As suggested by Kang et al. (2010), speciation can result from various factors such as: geospatial separation, host selection, and/or mating isolation. Therefore, defining a species based on a single locus is problematic.

These questions will be important for sorting out many of the members in the E clade. Based on our analysis of ten isolates, there is enough variation to separate P. schmitthenneri from P. hypogynum and P. acrogynum based primarily on morphology.

The most striking morphological difference between these species is the antheridial cell type that attaches to the oogonia. Both P. hypogynum and P. acrogynum have strictly hypogynous antheridia (Middleton, 1943; van der Plaats-Niterink, 1981). According to the original species description of P. hypogynum (Middleton, 1943), the antheridium was believed to be more primitive than those of other Pythium species with more advanced antheridial cell types, and because the hypogynous antheridia in P. hypogynum were not always formed. Instead a moderately sized nucleus cell in the oogonial stalk migrates upwards towards the oogonial cavity to fertilize the oospore (Middleton, 1943). Pythium

80 schmitthenneri has mostly diclinous antheridia, and the migration of fertilization tube in place of an antheridium has not been observed in this species. The growth habit is also different for P. hypogynum and P. schmitthenneri. Pythium hypogynum has a radiate growth pattern on cornmeal agar, while P. schmitthenneri is submerged with no distinct pattern, and the temperature range for growth also varies dramatically for these two species (Table 3.2). Thus, P. schmitthenneri has distinct morphological features, culture growth habits, distinct optimum temperature requirements, geographical associations as well as sequence divergence among other species within the E1 clade to support it as a new species.

A number of species of Pythium in the E1 clade have been found associated with plants. Pythium hypogynum has been reported to be a pathogen of cereal crops in the

United States (Middleton, 1941,1943; Sprague, 1946, 1950), and a weak pathogen of

Fragaria sp. (Nemec, 1972). Pythium acrogynum was first isolated from soil in

Wuchang, Hupei (Yü, 1973), and has not been reported in the United States. Both P. longandrum and P. longisporangium were isolated from vineyard soil in France (Paul,

2001; Paul et al., 2005). Currently five species within the E1 clade were found associated with soybean and corn in Ohio, including; P. hypogynum, P. longandrum, P. echinulatum, P. schmitthenneri, and P. selbyi (Broders et al., 2007, 2009). Pythium echinulatum (Broders et al., 2007), P. schmitthenneri, and P. selbyi (Dorrance et al., unpublished data) were all found to be moderately aggressive pathogens to both soybean and corn, however, Koch’s postulates have yet to be completed for P. hypogynum and P. longandrum on both soybean and corn. Pythium schmitthenneri and P. selbyi were

81 isolated more frequently from soybean and corn than P. hypogynum, P. longandrum, and

P. echinulatum.

It is interesting that these new species strongly associated with soybean and corn were not identified prior to the studies by Broders et al. (2009), especially P. schmitthenneri with its distinct morphological differences from P. hypogynum. This could be due to the isolation methods used. In a study by Broders et al. (2007), where

Pythium spp. were isolated directly from symptomatic plants collected from fields with a history of stand establishment issues in Ohio, three isolates of P. echinulatum were isolated from soybean. In a more comprehensive survey of the state of Ohio, P. schmitthenneri and P. selbyi were recovered from 30% of the 88 locations in a soil baiting assay at 18°C, compared to P. hypogynum (<0.1%) and P. longandrum (<10 %), while P. echinulatum was not recovered (Broders et al., 2009). These new species may have been favored by this baiting method for isolating Pythium spp. since both species have optimum growth at relatively low temperatures compared with P. hypogynum.

Another key difference between the two isolation methods is when isolated from field samples the pathogens had been established much longer in the host and it was possible that secondary invaders were also being recovered, whereas the baiting procedure targeted the primary invaders. However, since this initial survey, both P. schmitthenneri and P. selbyi were recovered from lesions on soybean roots collected early in the season from a number of additional soybean fields in Ohio as well as the soil baiting procedure

(Dorrance et al., unpublished data). The frequency with which these species were isolated from infected root tissue of soybean made them important to characterize so that

82 better management strategies can be developed to control Pythium spp. affecting soybean in Ohio.

ACKNOWLEDGEMENTS

This project was supported in part by the Ohio Soybean Council, The OARDC

Graduate Research Enhancement Grant Program (SEEDS). We thank the OARDC

Molecular Cellular Imaging Center for assistance in sequencing. Salaries and research support provided in part by State and Federal Funds appropriated to the Ohio Agricultural

Research and Development Center, The Ohio State University.

Pythium schmitthenneri 755 851-853 JF836869.1|P. schmitthenneri gaatt cctt__tggc HQ643414.1| P. acrogynum gaatt cctt_ttggc HQ643565.1| P. hypogynum gagtt cctty_tggc

Pythium selbyi 32 37 49 78 95 139 155 157 JF836871.1|P. selbyi ttcgtataag ccgag gctat ggcgt tgtgc gtatcgg AY039713.2| P. longandrum tttgtatcag ccgag gcgat ggcgt tgcgc gtgttgg EF583438.1| P. longisporangium tt_gtatcag ccaag gctat ggtgt tgcgc gtattgg

173 183 187 205 407 432 473 JF836871.1|P. selbyi ttcaa ttaaattaa gtaag tgcct attga ataatt AY039713.2| P. longandrum ttcaa ttaaattaa gtgag tgtct atcga atcatt EF583438.1| P. longisporangium tttaa ttcaataaa gtaag tgcct attga atcatt 84 491 504-510 513-515 578 600 715-716 JF836871.1|P. selbyi cgcaa tat____gctattctat gtgta cttgg ttcgct AY039713.2| P. longandrum cgtaa tacataagctagtatat gtgta ctcgg ttaact EF583438.1| P. longisporangium cgtaa tatataaggtagtatat gtcta ctygg ttcgct

744 749 779 785 864 JF836871.1|P. selbyi ggcttgaacc atatcgatatt gcact AY039713.2| P. longandrum ggtttgagcc atgtcgat_tt gcgct EF583438.1| P. longisporangium ggtttgagcc atgtcgatatt gcgct

Table 3.1: The DNA sequence differences for the ITS region for Pythium schmitthenneri

and Pythium selbyi with members within the clade E1.

Pythium species Accession Number ITS region coxI coxII Pythium ultimum var. ultimum HQ643942 Pythium rostratum AY598696 HQ708808 AF196615 Pythium radiosum HQ643756 HQ708797 Pythium echinulatum HQ643531 HQ708577 AB362327 Pythium erinaceum HQ643534 HQ708578 AB362326 HQ643535 HQ708579 Pythium ornacarpum HQ643721 HQ708762 Pythium apiculatum HQ643443 HQ708490 DQ211530 Pythium hypogynum HQ643565 HQ708609 AB362325 AY598693 EF035020 Pythium acrogynum HQ643414 HQ708461 AB362324 AY598638 EU350528 Pythium schmitthenneri JF836869 JF895534 JF895530 JF836870 JF895535 JF895531 Pythium spp. F1216 AY455697 Pythium spp. F1253 EF125022 Pythium selbyi JF836871 JF895536 JF895532 JF836872 JF895537 JF895533 Pythium longandrum HQ708722 HQ643679 HQ708723 Pythium spp. F923 EF583445 Pythium bifurcatum AY083935 Pythium longisporangium HQ643680 HQ708724

Table 3.2: Species of Pythium used for the sequence comparison and analysis, along with their Genbank accession numbers

Morphological ab b ab P. rostratum P. acrogynum P. hypogynum P. schmitthenneri differences Colony pattern Chrysanthemum pattern on Not reported No report on PCA, radiate Rosette to chrysanthemum PCA, submerged on pattern on cornmeal agar pattern on PCA, submerged cornmeal agar on cornmeal agar Hyphae 6-8 µm wide 7.7 µm wide 1.5-8.3 µm wide 4-8 µm wide Sporangia Terminal or intercalary, 24-40 (av. 31) µm Terminal, occasionally Terminal, occasionally globose, ovoid, limoniform, diam, terminal, rarely intercalary, (sub) globose, intercalary, (sub) globose, or ellipsoidal, non- intercalary, non-proliferating, 6.5-34.5 lemon shaped, 17-43 (av. 32) proliferating, 17-32(av. 25) (sub)globose (av. 22) µm, discharge tubes µm, up to 48 µm in length µm, up to 27 x 23 µm when about twice the diameter of when limoniform oblong the sporangia 86

Antheridia Monoclinous mostly sessile Hypogynous, Strictly hypogynous, Mostly diclinous occasionally and arising immediately antheridial cells large, antheridial cells 3.0- monoclinous and below the oogonium, 8-15x6-14 (av. 11.5-9) 11.1x2.8-8.3 (av. 6.5x5.5) hypogynous, antheridial cells hypogynous µm µm delimited within the 10-25x6-12 µm oogonial stalk at disitance of 5-30 µm below the oogonium Continued

Table 3.3: Comparison of morphological features of Pythium schmitthenneri (G7-1) with key members within clade E1

a = description taken from Middleton (1943)

b = description taken from van der Plaats-Niterink (1981)

Table 3.3 continued

Morphological ab b ab P. rostratum P. acrogynum P. hypogynum P. schmitthenneri differences Oogonia Mostly intercalary, Terminal, (sub)globose, Terminal, (sub)globose, Mostly terminal, occasionally terminal, papillate, rarely smooth, smooth, 10-35 (av. 22) µm occasionally intercalary, smooth, 17-26 (av. 21.5) 18-25 (av. 21) µm diam. smooth 19-26 (av. 23) µm, µm, often in chains diam. oogonial stalk 3-10 µm

Oospores Plerotic or nearly so, single, Plerotic, single, 18-23 Plerotic, single, smooth- Plerotic, single, occasionally two oospores (av. 20) µm diam, wall walled, measurements not occasionally two oospores per oogonium, wall 2 µm smooth, 0.8-1.7 (av. reported per oogonium, 14-23 (av. thick 1.5) µm thick 20) µm diam., wall smooth, 87 1-2.5 µm thick

Cardinal temperature Minimum below 5°C, Not reported Minimum 1°C, Minimum below 4°C, optimum 25°C, maximum, optimum 31-34°C, optimum 18-25°C, 35°C maximum 37°C maximum 32°C

Growth rate 8.0 mm at 25°C Not reported 11 mm at 25°C 13.2 mm at 25°C

Morphological a b P. longandrum P. longisporangium P. selbyi differences Colony pattern Submerged, chrysanthemal on PCA, Submerged, chrysanthemal on PCA, Radiate to slightly chrysanthemal on not reported on cornmeal agar not reported on cornmeal agar PCA, submerged on cornmeal agar

Hyphae 7-8µm, well branched 6-8µm, well branched 4-7 µm, some branching in older hyphae Sporangia Globose to somewhat elongated, Globose to somewhat cylindrical, Globose to oval, mostly terminal, mostly intercalary and catenulate, at oval, intercalary and catenulate, 15-55 intercalary, 24-41(av. 35) µm times terminal and subterminal, 16-36 ( av. 32.6) µm diam., up to 65 µm in (av. 29.4) µm diam., long discharge length tubes

88 Antheridia Hypogynous and monoclinous, Hypogynous and monoclinous sessile, Hypogynous, occasionally

antheridial cells are inflated, at times 1-3 antheridial cells and at times monoclinous, rarely diclinous 10- bi-lobed into two conspicuous cells, catenulate, rarely diclinous 22x7.6-13 µm very long and longitudinally applied to the oogonia, 40-50µm in length and 8-9µm in breadth Continued

Table 3.4: Comparison of morphological features of Pythium selbyi (G7-2) with key members within clade E1

a = description taken from Paul (2001)

b = description taken from Paul et al. (2005)

Table 3.4 continued

Morphological a b P. longandrum P. longisporangium P. selbyi differences Oogonia Smooth walled, spherical, at times Smooth walled, spherical, terminal, Terminal and intercalary, smooth elongated, terminal, subterminal, subterminal, intercalary, 17-36 (av. walled, spherical, at times elongated intercalary, 17-26 (av. 21.5) µm diam. 19.5) µm diam. 26-30 (av. 27.5) µm diam.

Oospores Plerotic and aplerotic, spherical, one Plerotic or nearly so, usually one, Mostly plerotic occasionally aplerotic, but at times two oospores per occasionally two and rarely three, one often two oospores per oogonium, oogonium, 18-23(av. 20.1) µm, wall intercalary oogonia can be aplerotic, 18-26 (av. 23) µm 1-2.5 µm smooth walled, 12-22(av. 18.1) µm,

89 wall 1-1.5 µm

Cardinal temperature Not reported Not reported Growth Range 4-32°C Optimum 18-25°C Maximum 32°C Growth rate 7 mm at 25°C 11 mm at 25°C 11.9 mm at 25°C

Fig. 3.1: Pythium schmitthenneri sporangia. Terminal globose sporangia (A-E) and sporangia with discharge tube (A, D, E). Bars = 10 µm (A-C) and 100 µm (D,E).

Fig. 3.2: Pythium schmitthenneri oogonia, antheridia, and oospores. Oogonia are terminal occasionally intercalary. Oospores are plerotic or nearly so and antheridia, indicated by arrows, are mostly diclinous (A, B, D). Bars = 10 µm. 91

Fig. 3.3: Pythium selbyi sporangia. Terminal globose sporangia and sporangia with discharge tubes (C, D) and the beginning formation of a discharge tube (B). Bars =

10µm.

Fig. 3.4: Pythium selbyi oogonia, antheridia, and oospores. Oogonia are intercalary (A-C,

E) and terminal (D). Oospores are plerotic or nearly so, with mostly one (A-C) but often two oospores per oogonium (D, E). Antheridia, indicated by arrows, are hypogynous.

Bars = 10 µm.

Fig. 3.5: The majority-rule consensus tree from the Bayesian analysis of the ITS1-5.8S-

ITS2 sequence of the nuclear rDNA showing the positions of isolates of P. schmitthennerri and P. selbyi in relation to other known tax in clade E1 with Pythium ultimum var. ultimum as the outgroup. Bayesian posterior probabilities are displayed next to each node. Species names are followed by their Genbank accession number. Scale bar represents the expected changes per site.

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CHAPTER 4

IDENTIFICATION OF RESISTANT GENOTYPES AND MOLECULAR

MAPPING OF QUANTITATIVE TRAIT LOCI IN SOYBEAN TO FUSARIUM

GRAMINEARUM

INTRODUCTION

Over the past decade, seedling diseases of soybean [Glycine max (L.) Merr] have increased in Ohio. Several factors may have contributed to this increase in incidence and severity including: earlier planting dates where seeds were planted under cooler and wetter environmental conditions that delayed germination; consecutive years of above- average rainfall during April and May; a high proportion of acres in long-term no-till soil conservation systems; shifts in fungicide-seed treatment chemistries; and changes in the base soybean germplasm (Broders et al., 2007a,b; Fernandez and Fernandes, 1990;

Sneller, 2003; Workneh et al., 1999; Wrather et al., 2001, 2003; Wrather and Koenning

2006, 2009). From these changes in environment and production practices, one of the soybean seedling pathogens that emerged in the last decade is the necrotroph Fusarium graminearum Schwabe (teleomorph: Gibberella zeae (Schwien.) Petch) (Broders et al.,

2007; Chapter 2; Xue et al., 2006, 2007).

Broders et al. (2007) recovered F. graminearum from soybean seedlings collected from over 30 locations in Ohio and reported that these isolates were moderately pathogenic in greenhouse pot assays. In further studies, it was determined that high levels of inoculum were needed for disease development (Chapter 2). Thus, no-till and reduced tillage practices may contribute to the increase in disease incidence in soybean by F. graminearum as these leave large quantities of crop residue on the soil surface and provide favorable soil conditions for both pathogen growth and survival (Baird et al.,

1997; Fernandez and Fernandes, 1990; Cotton and Munkvold, 1998; Leslie et al., 1990;

Sutton, 1982; Windels et al., 1988; Workneh et al., 1999).

Current management strategies for seedling diseases, such as those caused by F. graminearum, rely heavily on fungicide-seed treatments, and improving soil drainage through tillage and tiling. However, many of the broad-spectrum and highly effective seed treatments, such as Rival® (19.8% captan plus 8.4% pentachloronitrobenzene plus

1.0% thiabendazole; Gustafson, Plano, TX) and Captan (37.4% captan; Bayer Crop

Science, NC) are no longer available, and a shift to chemistries that have narrower pathogen efficacy profiles has occurred. In two previous studies the efficacy of fungicide- seed treatments for F. graminearum was evaluated (Broders et al., 2007; Chapter 2).

Fludioxonil (Maxim 4S; Syngenta Crop Protection Inc., NC) and captan had the highest level of control compared to the newer class of stobilurin fungicides (Broders et al., 2007;

Chapter 2). Although fludioxonil was effective both in amended agar plate assays

(Broders et al., 2007) and as a fungicide-seed treatment (Chapter 2), mutants insensitive to fludioxonil were readily generated in the amended agar plate assays (Broders et al.,

2007). While no such mutants have been recovered from the field, there are costs associated with planting treated seed as well as those associated with tillage and tiling.

Thus, more effective and less costly disease management strategies are a priority for F. graminearum.

Disease resistance is a promising strategy for management of F. graminearum.

Recent shifts in soybean germplasm have occurred, as industry now dominates in the development and delivery of new cultivars compared to the public sector (Diers and Kim,

2008). As such, there is limited diversity within elite lines from some companies, due in part to the limitation of the exchange of germplasm (Sneller, 2003). The emergence of F.

100 graminearum as a pathogen of soybean may also be linked to these shifts in germplasm.

The first hypothesis of this study is that resistance to F. graminearum is present in adapted soybean cultivars which were widely grown prior to the recent emergence of this seedling pathogen.

There are three general types of plant resistance to pathogens: innate immunity or basal resistance which is non-specific recognition of broadly conserved pathogen features such as flagellin from bacteria or chitin from fungal cell walls (Boller and Felix, 2009;

Boller and He, 2009; Chisholm et al. 2006; Jones and Dangl, 2006; Medzhitov and

Janeway, 1997); qualitative (complete, vertical, major-gene, or narrow-spectrum) resistance which is usually conditioned by a single gene and is involved in specific recognition of pathogen effectors or their targets (Chrisholm et al., 2006; Flores, 1955,

1971; Jones and Dangl, 2006; van der Plank, 1968); and quantitative (incomplete, horizontal, minor-gene, or broad-spectrum) resistance which is conditioned by multiple genes with partial effect (Poland et al., 2009; van der Plank, 1968; Young, 1996). Based on current knowledge, the type of resistance that is observed often depends on the lifestyle of the pathogen (Glazebrook 2005; Hammond-Kosack and Parker, 2003; Oliver and Ipcho, 2004; Poland et al., 2009). Necrotrophic pathogens tend to have wide host ranges and rapidly kill their host usually through the secretion of toxins, while biotrophic pathogens have a more intimate association with their host and require living host cells, are host-specific, and often establish themselves by forming specialized structures such as appresoria and haustoria. A number of plant pathogens have lifestyles that are intermediate and are referred to as hemibiotrophs, which establish infection in a similar

101 manner as biotrophs, but later in the infection process they begin to actively spread through the host and kill host cells (Agrios 2005; Erwin and Ribeiro, 1996; Qutob et al.,

2002). In some host-pathosystems, qualitative resistance is often targeted towards pathogens which are host specific (hemibiotrophs or biotrophs) and for many interactions was less durable than quantitative resistance, as pathogens can adapt to single-gene mediated resistance (Poland et al., 2009; St.Clair, 2010). In contrast, quantitative resistance is broad-spectrum and is the type of resistance often associated with biotrophic and necrotrophic pathogens, with few cases of qualitative resistance being reported for necrotrophs (Oliver and Ipcho, 2004).

Given that F. graminearum was only recently reported as a seedling pathogen to soybean, no studies have been reported to identify or characterize resistance to this pathogen. In Ohio and other Midwest states, F. graminearum is highly recognized as a key pathogen causing Fusarium head blight of wheat (Triticum aestivum L.) and barley

(Hordeum vulgare L.) (Bai and Shaner, 1994; McMullen et al., 1997), and ear and stalk rot of corn (Zea mays L.) (Sutton, 1982). In these and other hosts, resistance to F. graminearum is quantitative (Anderson et al., 2001; Bai et al., 1999; Buerstmayr et al.,

2002; Gervais et al., 2003; Waldron et al., 1999; Zhou et al., 2002) and can also be greatly influenced by the environment (Bai and Shaner, 1994, 1996, 2004; Buerstmayr et al., 2011; Snijders and van Eeuwijk, 1991). Quantitative resistance in soybean has been studied intensively for both hemibiotrophic and necrotrophic root pathogens including;

Phytophthora sojae Kaufm. and Gerd. (Burnham et al., 2002, 2003; Dorrance and

Schmitthenner, 2000; Han et al., 2008; Tooley and Grau, 1982; Tucker et al.,

102

2010;Walker and Schmitthenner,1984; Wang et al., 2010; Weng et al., 2007); Fusarium virguliforme O’Donnell & T. Aoki (telomorph belonging to Nectria sensu lato) (Chang et al., 1996; Farias Neto et al., 2007; Hnetkovsky et al., 1996; Iqbal et al., 2001; Lightfoot et al., 2005; Meksem et al., 1999; Njiti et al., 1996, 2002); Macrophomina phaseolina

(Tassi) Goid. (Mengistu et al., 2007; Paris et al., 2006; Smith and Carvil, 1997); and

Rhizoctonia solani Kühn (teleomorph Thanatephorus cucumeris (A.B. Frank) Donk)

(Bradley et al., 2005; Zhao et al., 2005). Several soybean populations which are segregating for resistance to P. sojae are available (Gordon et al. 2007). If at least one of these same populations segregated for resistance to F. graminearum, this would allow for comparison of resistance loci to both hemibiotrophic and necrotrophic soybean root pathogens. As such, the second hypothesizes for this study was that resistance to F. graminearum is inherited quantitatively and is conferred by different loci compared to hemibiotrophic root pathogens.

OBJECTIVES

The objectives of this study were (i) to identify sources of resistance to F. graminearum, and (ii) map resistance to F. graminearum in a RIL population that was also segregating for resistance to P. sojae.

MATERIAL AND METHODS

Phenotypic assay. Soybean genotypes were chosen for the resistance screening with F. graminearum based on two criteria: genotypes with known resistance genes or partial

103 resistance to other soybean pathogens; and that had been used as parents for the development of segregating populations which were available for phenotyping. Twenty- four soybean genotypes were evaluated for resistance to F. graminearum using a rolled towel assay described previously in Chapter 2. Briefly, twenty seeds of each genotype were placed in a row on a moistened towel and each seed was inoculated with a 100 μl suspension of 2.5 × 104 macroconidia ml-1 from the F. graminearum isolate Fay11.

Another moistened towel was placed over the inoculated seed and the towels were rolled and placed in 25 L buckets with 24 towels per bucket. There were three buckets, with one towel for each genotype in each bucket. A black plastic bag was placed over each bucket and these were placed in a growth chamber at 22°C. The experimental design was a randomized complete block, with three replicate blocks. As each of the three buckets provided a physical separation between the replicates of the genotype and that the microenvironment was homogeneous within buckets but heterogeneous among buckets, we considered each bucket to be a block and random effect in the analysis. The experiment was conducted twice. Seven days after inoculation (dai), total lesion length and plant length was recorded for each seedling. A disease severity index (DSI) was calculated by dividing the lesion length by the total length of seedling and multiplying by

100.

Because the data was converted into a percentage using the DSI calculation and the range in percentages exceeded 40% the data was arcsine-transformed as suggested by

Little and Hill (1978) and analyzed using the general linear model procedure (PROC

GLM) of SAS 9.2 (SAS Institute Inc., Cary, NC). Levene’s test of homogeneity of

104 variance was used to compare experiments. Because there was no significant difference

(P = 0.16) between experiments, the data were pooled and analyzed together. Means were compared using Fisher’s protected Least Significant Difference (LSD) at P = 0.05.

Plant material for QTL mapping. A total of 262 F6:8 recombinant inbred lines (RILs) derived from a cross of partial resistant cultivar ‘Conrad’ (Fehr et al., 1989) (R) by the susceptible cultivar ‘Sloan’ (Bahrenfus and Fehr, 1980) (S) (Appendix B) was evaluated for partial resistance to F. graminearum. The population was developed from eight F1 plants and each generation was advanced through single seed descent. This population was previously used to map QTL that confer resistance to P. sojae (Wang, 2011).

Phenotypic assay for quantitative trait loci mapping. Twenty seeds from each of the

262 RILs were evaluated for resistance using the rolled towel method, described above.

The experimental design was an augmented randomized complete block, with R and S parents included as checks in each bucket which contained 21-22 RILs. The 262 RILs were separated into three groups of approximately 87 RILs and evaluated over three separate time points with a period of 24 h between each inoculation. At 7 dai the DSI data was taken as previously described. This was repeated for a total of two experiments.

The DSI data was analyzed using a mixed model to obtain the best linear unbiased predictor (BLUP) (Stroup, 1989). The BLUP equation was: Yijklm = μ + Ri + I(R)ij +

K(IR)ijk+ Cl + G(C)lm + εiijklm, where Yijklm = observation of ith experiment, jth incomplete block (time), kth bucket, lth class, and mth genotype, and μ = overall mean, Ri

105

= effect of the ith experiment (F6:8), I(R)ij = effect of the jth incomplete block (time) in the ith experiment, K(IR)ijk = effect of the kth bucket in the jth incomplete block (time) of the ith experiment, Cl = effect of the lth class (Conrad, Sloan, and RILs), G(C)lm = effect of mth genotype within lth class for recombinant lines only (genotypic variance), and εijklm refers to sampling variation from plant to plant within an experimental unit. One class was assigned for each parental line and another class for all of the RILs. Class of entry was assumed to be a fixed effect, and all other terms random. This model permitted an analysis in which checks (parents) were fixed effects and RILs were random. Variance components were estimated using restricted maximum likelihood (Burnham et al., 2003;

Tucker et al., 2010; Wang et al., 2010). Heritability, on a family mean basis, was

2 2 2 calculated as: σ G(C)/(σ G(C) + σ ε/2).

Molecular mapping. The genetic map for the Conrad × Sloan F6:8 population was composed of 208 single nucleotide polymorphism (SNP) and simple sequence repeat

(SSR) markers. The initial genetic map for this population was developed by Wang

(2011) and was used to map QTL for resistance to P. sojae and to identify genomic regions. Briefly, to develop the map, a total of 147 RILs were genotyped with 384 single nucleotide polymorphism (SNP) markers using the VeraCode GoldenGate Genotyping

Kit (Illumnia Inc., San Diego, CA) and analyzed using the Illumnia BeadXpress Reader

(Illumnia Inc., San Diego, CA). A total of 128 polymorphic SNP and 65 simple sequence repeat (SSR) markers were used to develop the initial map using JoinMap 4.0 ® using the

Kosambi function (van Ooijen, 2006). Additionally, 15 SSR markers were specifically

106 assayed on the population and added to the map in regions of putative QTL for resistance to F. graminearum and also to ensure thorough coverage of regions in the genome that were associated with resistance to F. virguliforme and S. sclerotiorum.

From the 208 markers screened for the 147 RILs, 104 of these markers were assayed on the entire population to further define the putative QTLs for resistance to F. graminearum. This included 72 SSR markers and 32 PCR amplification of multiple specific alleles (PAMSA) markers designed from SNPs using the protocol from Gaudet et al. (2007) (Appendix C). SSR and PAMSA markers were amplified by polymerase chain reaction (PCR) using a modified protocol from Gordon et al. (2007). A 12.5 µL PCR mix containing 50 ng genomic DNA, 1x PCR buffer (Promega, Madison, WI), 130 µM of each dNTP, 2mM MgCl2 (Promega), 0.4 µM forward and reverse primers, as well as 0.5-

1.0 unit of Taq DNA polymerase (Promega), for the SSR and PAMSA markers, respectively. A touchdown program was used in which the annealing temperature decreased from either 60°C to °50 or 58°C to 48°C by 1°C each cycle for the first 10 cycles and the annealing temperature was kept at 50°C or 48°C for the remaining 28 cycles. PCR products were analyzed by electrophoresis on 4% 3:1 HRBTM agarose

(AMERSCO Inc., Solon, OH) containing 0.7% GelRedTM (Phenix Research Products,

Candler, NC) for 120-180 min at 150 volts in the RapidRunTM Agarose Buffer

(Affymetrix/USB Inc., Cleveland, OH). The products were sized with TriDyeTM 100bp

DNA ladder (UVP Inc., Upland, CA). The gels were photographed using the Kodak

Electrophoresis Documentation and Analysis System 290 (EDAS, 290: Kodak Company,

Rochester, NY) and the product bands were scored. The map for the 104 molecular

107 marker for the entire population was created using JoinMap 4.0 ® using the Kosambi function (van Ooijen, 2006).

QTL Analysis. An initial analysis using interval mapping (IM) was performed using

MAPQTL ® to identify putative QTL from the map of 208 molecular markers from the

147 RILs. The walking speed was 1.0 centimorgan (cM) for QTL analysis (van Ooijen,

2004). Permutation tests with 1000 iterations were performed on each linkage group and on the whole genome to estimate significant logarithm of odds (LOD) scores (Churchill and Doerge, 1994). From these initial results, which identified putative QTL associated with resistance to F. graminearum, the entire population of 262 RILs in these regions was reanalyzed, generating a new map that consisted of 104 molecular markers. IM and composite interval mapping (CIM) were performed using MAPQTL ® with a walking speed for QTLs analyses was 1.0 cM. Permutation tests with 1000 iterations were performed on each linkage group and on the whole genome to estimate significant logarithm of odds (LOD) scores (Churchill and Doerge, 1994). One-way ANOVA with the PROC GLM procedure (SAS Institute Inc.) was used to confirm the single marker association with phenotypic variation. QTLNetwork 2.0 (Yang et al. 2008), based on linear mixed model (Wang et al. 1999), was used to confirm the main effect QTL identified using MAPQTL ® and to detect if interactions occurred between QTL. A window size and filtration size of 10 with 1 cM walk was used in the analysis.

Permutation tests with 1000 iterations were performed on each linkage group with Gibbs sample size of 20,000. The significance level threshold was 0.05.

108

RESULTS AND DISCUSSION

Sources of resistance. There was a wide range of responses among the 24 soybean genotypes following inoculation with F. graminearum. The arcsine-transformed data for the DSI was highly significant (P<0.0001). The genotypes with the highest levels of resistance and lowest disease severity, 24.0 to 41.5%, included plant introductions (PI)

424354 and 408211B, a breeding line HC99-2846 (Mian, 2006), and cultivars Conrad and ‘Prohio’ (Mian et al., 2008) (Table 4.1, Fig. 4.1). Soybean genotypes with the highest susceptibility and disease severity, 81.7 to 94.3%, included PI 399073 and cultivars

Sloan, ‘Archer’ (Cianzio et al., 1991), ‘Resnik’ (McBlain et al., 1990), and ‘Ripley’

(Cooper et al., 1990) (Table 4.1, Fig. 4.1). Of the genotypes expressing high levels of resistance to F. graminearum, none exhibited a phenotypic response for complete resistance and all had minor lesion development following infection.

These results suggest that resistance to F. graminearum may be common in soybean based on this select group of 24 genotypes. Similarly, studies for resistance to M. phaseolina also found moderate levels of resistance among 24 commercial cultivars

(Smith and Carvil, 1997) and 18 soybean breeding lines and six cultivars (Mengistu et al.,

2007). If resistance to pathogens such as F. graminearum and M. phaseolina is common in soybean genotypes, it may not be necessary for breeders to focus initial efforts on non- adapted germplasm when developing new cultivars, but instead focus screens for resistance to these pathogens on advanced breeding lines. Since resistance to F. graminearum was very readily identified, this may also indicate that shifts and changes in the base soybean germplasm may have contributed to the emergence of this seed and

109 seedling pathogen in Ohio. An evaluation of representative cultivars that were grown prior to 2000, compared to those that are available today, will be necessary to confirm this hypothesis.

QTL for resistance. Based on the results of the study above, Conrad was identified as a source of resistance to F. graminearum. The putative QTL for F. graminearum were mapped in Conrad x Sloan F6:8 RIL population that had also been used to map for partial resistance to P. sojae (Wang, 2011). The phenotypic results for the 262 RIL’s of the

Conrad × Sloan F6:8 population had a normal distribution, which indicated that the resistance was quantitatively inherited (Fig. 4.2). The DSI BLUP values ranged from

−30.71 to 21.20 (DSI 22.23% to 100%). The broad-sense heritability estimated from the

DSI for this population was 0.72. In this study, the R and S checks were consistent among blocks (buckets) and across experiments.

The linkage map constructed from the 208 molecular markers covered 961.1 cM across 34 fractional MLGs (unlinked markers were not included). The constructed map was mostly in accordance with the physical positions aligned with the Soybean

Consensus Linkage Map 4.0 (Hyten et al., 2008) and covered approximately 54% of the consensus map. Sixteen of the 20 chromosomes had good coverage with approximately 1 to 20 cM distances between markers and only a few regions with a greater than 20 cM distance between markers. The four chromosomes with poor coverage included chromosomes 4 (MLG C1), 6 (MLG C2), 11 (MLG B1) and particularly chromosome 20

(MLG I) in which only two polymorphic SSR markers were identified. One of these two

110 markers was Sat_268, which is in a region that was previously reported to be associated with resistance to F. virguliforme (Iqbal et al., 2001).

Four putative QTL from the cultivar Conrad were identified through both IM and

CIM using MAPQTL 5.0 (van Ooijen, 2004) on chromosomes 8 (MLG A2), 13 (MLG

F), 15 (MLG E), and 16 (MLG J) and one putative QTL from the cultivar Sloan was identified through IM and CIM on chromosome 19 (MLG L) (Table 4.2, Fig. 4.3). The

LOD scores ranged from 2.2 to 3.4 for CIM, which was significant based on the permutation threshold of P < 0.05 (Churchill and Doerge, 1994) (Table 4.2). The total phenotypic variation explained for IM and CIM was 30% and 24%, respectively, with each individual QTL contributing approximately 3-11% (Table 4.2). Additionally, based on the one-way ANOVA (P < 0.05), putative associations were also identified on chromosomes 2 (MLG D1B), 3 (MLG N), 9 (MLG K), 11 (MLG B1), 12 (MLG H), and

18 (MLG G). QTLNetwork 2.0 identified four of the same QTL as IM and CIM, with the

QTL on chromosome 19 falling just below the 0.05 false discovery rate. No interactions among the QTLs were detected (data not shown).

In this study only 24 to 30% of the phenotypic variation could be associated with five QTL. This may be partly attributed to the lack of polymorphic markers in some regions. This lack of markers is presumed to be due to the genetic similarity of Conrad and Sloan (Appendix D).

Three QTL identified by IM and CIM in this study for resistance to F. graminearum are in similar regions to previously reported QTL conferring resistance to another necrotroph, Sclerotinia sclerotiorum (Lib.) de Bary, on chromosomes 8 (Arahana

111 et al., 2001; Vuong et al., 2008; Guo et al., 2008), 13 (Arahana et al., 2001; Guo et al.,

2008), and 15 (Arahana et al., 2001; Guo et al., 2008) (Fig. 4.3). In addition to S. sclerotiorum, a number of disease resistance QTL have been reported from the same region on chromosome 13. Other regions for resistance to S. sclerotiorum that were also significant for F. graminearum through one-way ANOVA were: chromosome 9 (Arahana et al., 2001; Kim and Dier, 2000; Vuong et al., 2008), 11 (Arahana et al., 2001), and chromosome 18 (Arahana et al., 2001; Guo et al., 2008). QTL conferring resistance to S. sclerotiorum were minor, with R2 values reported to range from 4-15.7% (Arahana et al.,

2001; Guo et al., 2008; Kim and Dier et al., 2000; Vuong et al., 2008). Conrad has been identified as being moderately susceptible to S. sclerotiorum based on field evaluations from data collected in 1994 (Kim et al., 1999). Further studies are necessary to assess if these same loci confer resistance to both of these pathogens.

Of the two cultivars, ‘Jack’ (Nickell et al., 1990) and Ripley (susceptible), that have high levels of partial resistance to F. virguliforme, Jack (Hartman et al., 1997; Jin et al., 1996) had moderate levels of resistance to F. graminearum (Table 4.1). To the best of our knowledge, neither Conrad nor Sloan has been identified as sources of resistance for

F. virguliforme. It is also important to note that resistance to F. virguliforme has two different components, a root rot phase and a toxin production phase which causes foliar symptoms in the leaves (Chang et al., 1997; Hnetkovsky et al., 1996; Huang and

Hartman, 1998; Killebrew et al., 1988; Meksem et al., 1999, 2008; Melgar and Roy,

1994; Njiti et al., 1998; Rupe, 1989; Rupe et al., 1991; Stephens et al., 1993). Therefore, it seems unlikely that the QTL associated with the toxin phase of this disease would

112 contribute to resistance for F. graminearum. QTL on chromosomes 6, 17, and 18, which were associated with root rot resistance to F. virguliforme (Kazi et al., 2008), were not associated with resistance to F. graminearum in this study. However, two QTL on chromosomes 13 and 16 associated with toxin resistance to F. virguliforme overlapped with two putative QTL identified by IM and CIM in this study (Fig. 4.3). Kassem et al.

(2006) reported that the Satt160 marker on chromosome 13 appeared to be a major determinant of seed yield. The QTL identified on chromosome 16 was significantly associated with the reduction in leaf scorch score which is resistance response to the toxin

(Sanitchon et al., 2004).

Conrad is a source of partial resistance to both P. sojae and F. graminearum.

There were three regions on three chromosomes associated with resistance to both pathogens. The Satt693 marker on chromosome 16 and the region spanning from Satt160 to Satt149 markers on chromosome 13, were associated with resistance to F. graminearum from Conrad, while these same regions were associated with resistance to

P. sojae from Sloan. On the third chromosome, 19; Satt527 and GML_OSU10 (Appendix

C) markers were associated with resistance to F. graminearum from Sloan, while the resistance to P. sojae was from Conrad (Wang et al., 2010) (Fig. 4.3). Based on these initial results, the putative QTLs identified in this population from Conrad and Sloan do not confer resistance to both pathogens, suggesting that different mechanisms contribute to resistance to P. sojae and F. graminearum. Future expression studies on genes involved in resistance in the regions with overlapping QTL to these two pathogens could

113 provide insights on how plants defend themselves from biotrophic and necrotrophic pathogens.

ACKNOWLEGEMENTS

I would like to thank Dr. Hehe Wang, Dr. Anne E. Dorrance, Dr. Pierce A. Paul,

Dr. Leah K. McHale, and Dr. Steven K. St. Martin. They all contributed greatly to this work. I would like to thank Sue Ann Berry for technical assistance and OARDC farm crew for assistance with advancing the population. Funding was provided in part through the soybean checkoff dollars from Ohio Soybean Council and United Soybean Board.

Salaries and research support for this project was provided by State and Federal Funds appropriated to the Ohio Agricultural Research and Development Center, The Ohio State

University. We would also like to thank the staff of the Molecular and Cellular Imaging

Center (MCIC, OARDC) for sequencing, and the Ohio BioProducts Innovation Center

(OBIC) for funding of genotyping equipment.

114

Genotype DSI† PI 399073 94.3 A Sloan 89.6 AB Archer 87.8 ABC Resnik 86.2 BC Ripley 85.6 BC Strong 82.8 BCD Williams 81.8 BCD Kottman 81.7 BCD Williams 82 81.8 CD OH-FG5 80.9 CD OX-208 78.2 CD L85-2325 77.8 CDE Dennison 74.4 DE L83-570 74.3 DE Jack 73.4 DE Stressland 72.8 DEF OH-FG1 65.9 EF Flint 65.2 EF OHS 303 60.5 F Prohio 41.5 G Conrad 35.0 HG PI 408211B 33.5 HG Wooster 31.7 HG PI 424354 24.0 H Mean 69.2

Table 4.1: Mean disease severity index (DSI) following inoculation of soybean seed with

100 µl of 2.5 × 104 macroconidia ml-1 of Fusarium graminearum in a rolled-towel assay.

† Mean disease severity represents the lesion length divided by the total length of the seedling multiplied by

100. Disease severity data were arcsine transformed; the actual means are reported in the table. The experimental design was randomized complete block, with three replications. The experiment was repeated for a total of two times. Values followed by the same uppercase letter were not significantly different according to Fisher’s protected Least Significant Difference (LSD) (P < 0.05) based on the arcsine- transformed data.

115

IM CIM Exp. Exp. Interval Consensus Var. Var. LOD Chromosome (cM) Nearest Marker Map (cM) † LOD (%) LOD (%) Thr.‡ R2 (%)§ 8 0.0-10.8 BARC_051847_11270 101.9 3.1 6.0 3.1 5.0 1.4 9.2 13 21.0-23.8 FLOWER_COLOR 17.4 1.9 3.6 2.8 4.4 1.5 5.1 15 0.0-19.0 BARC_025663_049888 47.9 3.6 11.2 3.4 6.7 1.1 7.2 16 12.2-21.9 Satt693 38.0 3.0 5.9 2.9 4.3 1.4 5.2 19 31.7-40.3 BARCSOYSSR_19_1452 1.8 3.5 2.2 3.3 1.8 3.6

116

Table 4.2: Quantitative trait loci for partial resistance to Fusarium graminearum that were identified via interval mapping (IM)

and composite interval mapping (CIM) using 262 F6:8 recombinant inbred lines (RILs) of Conrad (Resistant) × Sloan

(Susceptible)

† Consensus map position (Hyten et al., 2008) of the nearest marker in each interval.

‡ Threshold of significance for LOD for each chromosome based on permutation tests of 1000 iterations (P<0.05, Churchill and Doerge, 1994).

§ R-squared values from one-way ANOVA.

Figure 4.1: Symptoms of Fusarium graminearum infection 7 dai on Plant introduction

(PI) 424354 and Conrad (high levels of resistance) compared to Williams and Sloan

(lower levels of resistance). Seed was inoculated with 2.4 × 104 macroconidia ml-1 in a rolled towel assay.

117

Figure 4.2: Distribution of best linear unbiased predictor (BLUP) values for the disease severity index (DSI) among F6:8 recombinant inbred lines (RIL) derived from a cross of

Conrad (Resistant) × Sloan (Susceptible) at 7 dai with a 2.5 × 104 macroconidia ml-1 of

Fusarium graminearum.

118

Figure 4.3: Genetic maps generated from the genotype data from the Conrad (Resistant) × Sloan (Susceptible) F6:8 recombinant

inbred lines (RIL) using JoinMap4.0 ® (van Ooijen, 2006); and logrithim of odds (LOD) charts of the putative quantitative

trait loci (QTL) from composite interval mapping (CIM) analysis by MapQTL 5.0 ® (van Ooijen, 2004). The chromosome

number and assigned molecular linkage group (MLG) is listed above each linkage group. Significant P-values (P < 0.05) from

the one-way ANOVA are listed beside each marker. Colored lines indicate regions where putative QTL overlap with QTL

identified for other soybean pathogens and asterisk indicates significance of a molecular marker from both pathogens. The 119

different pathogens are indicated by color: Blue (Fusarium virguliforme), Red (Phytophthora sojae), and Yellow (Sclerotinia

sclerotiorum).

Figure 4.3

120

Figure 4.3

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CHAPTER 5

IDENTIFICATION OF RESISTANT GENOTYPES AND MOLECULAR

MAPPING OF QUANTITATIVE TRAIT LOCI IN THE SOYBEAN ACCESSION

PI 424354 TO PYTHIUM IRREGULARE

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INTRODUCTION

Pythium spp. are commonly associated with seed and seedling diseases of soybean [Glycine max (L.) Merr], and infections can result in both pre- and post- emergence damping-off (Brown and Kennedy, 1965; Griffin, 1990; Rizvi and Yang,

1996). In Ohio, greater than 20 described species of Pythium have been confirmed as pathogens on soybean (Broders et al., 2007, 2009; Dorrance et al., 2004), and within a given field, species richness was reported to range from 2 to 9 different species (Broders et al., 2009). In an intensive survey of production fields in Ohio, Broders et al. (2009) found that 30.5% of the recovered isolates (7,064) were P. irregulare Buisman, followed by P. inflatum V.D. Matthews (14.9%). Other prominent species included P. torulosum

Coker & P. Patt., P. ultimum Trow var. ultimum, P. ultimum var. sporangiiferum

Drechsler, and P. dissotocum Drechsler. These six species were recovered from 47 to

81% of the 88 fields surveyed (Broders et al., 2009). In growth chamber and Petri plate assays, Pythium irregulare, P. ultimum var. ultimum, and P. ultimum var. sporangiiferum all had high levels of pathogencity, causing severe taproot lesions, while P. inflatum, andP. torulosum were less aggressive, causing only minor lesions on the lateral roots of diseased seedlings. P. dissotocum had high levels of pathogencity on soybean seed based on Petri plate assays at 22°C, however only minor lateral root lesions were observed in growth chamber assays at 18°C (Broders et al., 2007, 2009; Dorrance et al., unpublished data).

Currently soybean seedling diseases, caused by Pythium spp. and other oomycetes, are managed by planting seeds treated with a combination of seed-applied

131 fungicide, metalaxyl or mefenoxam (Cohen and Coffey, 1986; Erwin and Ribeiro, 1996;

Yang, 1999). However, some Pythium spp. such as P. inflatum, P. dissotocum, and P. torulosum have reduced sensitivity to metalaxyl (Dorrance et al., 2004; Broders et al.,

2007). Newer fungicide seed treatments such as the strobilurins, i.e.; azoxystrobin, trifloxystrobin, and pyraclostrobin, were introduced to the market over the last several years as companion to seed-applied fungicides to improve efficacy against a broad spectrum of pathogens. However, it is important to note that some species of Pythium, including P. irregulare and P. ultimum var. ultimum, have reduced sensitivity to strobilurin fungicides (Broders et al., 2007; Dorrance et al., unpublished data) and the efficacy of these fungicides has not been evaluated for every species of Pythium. The specificity of active ingredients towards the different species of Pythium can minimize the overall efficacy of chemical seed treatment. This is especially challenging due to the species richness within a given field (Broders et al., 2009). Thus management which focuses on resistance should now become a priority. Identifying sources of resistance to these seedling pathogens and characterizing the resistance genes so that they could be readily introgressed into elite germplasm would greatly enhance the ability to manage seedling diseases.

To date, limited resistance in soybean towards Pythium spp. has been reported and there has also been little advancement in resistance screening since earlier studies conducted during the 1970s (Bates et al., 2008; Griffin, 1990; Keeling, 1974; Kirkpatrick et al., 2006; Laviolette and Athow, 1971; Rosso et al., 2008; Strissel and Dunleavy,

1970). Laviolette and Athow (1971) screened 2,156 soybean Plant Introductions from the

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USDA Soybean Germplasm collection with P. ultimum using a hypocotyl inoculation method and found high levels of seedling resistance, where plants of a number of genotypes were unaffected by the inoculation (Bernard et al., 1998). Based on the inoculation assay and the plant response, they hypothesized that this was an R-gene mediated response; however, in an attempt to map resistance for one of the resistant genotypes (not reported), the segregation results were inconclusive. Keeling (1974) reported that carbohydrate exudates from seed increased susceptibility, and reported that the cultivar Semmes (Hartwig, 1966) had some level of resistance against P. ultimum and

P. debaryanum Auct. non R. Hesse. Based on measurements of plant height in greenhouse experiments with soil inoculated with a mycelial suspension, Strissel and

Dunleavy (1970) identified eight cultivars with high levels of resistance and two cultivars with moderate levels of resistance to P. debaryanum.

Both reduction in root rot severity, a type of partial resistance, and single dominate R-genes have been described for resistance to Pythium spp. Based on measurements of emergence, disease severity index, cotyledon and hypocotyl colonization, and hypocotyl height, Griffin (1990) reported that the soybean cultivar Dare

(Brim, 1966) had moderate levels of resistance and breeding line V81-141 had high levels of resistance when planted into naturally Pythium-infested soils in a greenhouse study. In Griffin’s (1990) study there was infection and symptom development in the resistant cultivars, but they were significantly less when compared to the susceptible cultivar Essex (Smith and Camper, 1973). Dare also had significantly higher levels of emergence and plant height and lower levels of damping-off when compared with the

133 susceptible cultivar Essex in field studies (Griffin, 1990). Similarly, in a more recent greenhouse assay using infested sand-cornmeal inoculum, both in flooded and non- flooded environments, Kirkpatrick et al. (2006) reported that the soybean cultivar Archer

(Cianzio et al., 1991) had moderate levels of resistance to Pythium ultimum, based on stand count, root weight, and top dry weight. Quantitative resistance against P. ultimum var. ultimum has also been identified and mapped for seed rot and pre-emergence damping-off both in snap bean (Navarro et al., 2008; York et al., 1977) and common bean (Campa et al., 2010).

Bates et al. (2008) evaluated resistance in soybean to P. ultimum, P. irregulare, P. aphanidermatum (Edison) Fitzp., P. oligandrum Drechsler, P. vexans de Bary, and an unknown Pythium spp. designated as group HS. In this greenhouse study, Archer had significantly lower disease levels than the susceptible cultivar Hutcheson (Buss et al.,

1988), based on both emergence and plant growth assays. The responses were similar for several different Pythium spp., with the exception of P. oligandrum, for which there was no disease development on either cultivar. In Archer, disease development on roots was less than 1% when inoculated with P. aphanidermatum, while 1 to 20% of the roots were symptomatic when inoculated with other Pythium spp. The response in Archer when inoculated with P. aphanidermatum was characteristic of an R-gene mediated response.

Subsequently, resistance to P. aphanidermatum was mapped to a locus on chromosome

13 (MLG F) (Ross et al., 2008). This was the first single dominant resistance gene that conferred resistance to a Pythium species in soybean. Other single dominate resistance genes that have been reported for other Pythium spp-host interactions include: corn (Zea

134 mays L.) against P. inflatum (Yang et al. 2005) and common bean (Phaseolus vulgaris

L.) against P. ultimum var. ultimum (Mahuku et al., 2005).

There are several highly pathogenic Pythium species that impact soybean in Ohio:

P. irregulare, P. ultimum var. ultimum, P. ultimum var. sporangiiferum (Broders et al.,

2007, 2009; Dorrance et al., 2004), as well as P. aphanidermatum which was recovered directly from diseased soybean seedlings in southern Ohio (Broders et al., 2009;

Dorrance et al., unpublished data). In a survey of agronomic soils from 88 locations, P. irregulare was identified from four of the five Pythium communities across Ohio, and was identified from approximately 90% of the locations, while P. ultimum var. ultimum and P. ultimum var. sporangiiferum were isolated from approximately 50% of the locations (Broders et al., 2009). Thus, it is important to identify and characterize sources of resistance to these species in order to deploy cultivars with resistance for subsequent management of seedling pathogens in the state of Ohio. In particular, management of P. irregulare is a priority among the soybean seedlings pathogens affecting soybean in

Ohio.

Disease resistance is a promising strategy for management of P. irregulare, especially since high levels of resistance to P. irregulare were reported previously in the soybean cultivar Archer, but no other sources of resistance have been reported. The hypotheses of this study were that resistance to P. irregulare is present in adapted germplasm, and this resistance is quantitatively inherited. To test these hypotheses, a large number of soybean genotypes (cultivars and plant introductions) with R-gene mediated resistance and/or partial resistance to other root and stem pathogens was

135 screened. Many of these genotypes were used as parents in populations that were available for immediate use to map resistance that may have been found from the initial screening for resistance to P. irregulare.

OBJECTIVES

The objectives of this study were (i) to identify sources of resistance in soybean genotypes to P. irregulare; and (ii) map the resistance in an available mapping population.

MATERIAL AND METHODS

Isolates and inoculum preparation. Two isolates of P. irregulare were collected from soybean fields in Ohio during 2006 and identified by Broders et al. (2009). The first isolate, Br2-3-5, was baited from a clay loam soil (42.4% silt, 22.4% clay, and 35.2% sand) collect from a no-till agronomic field in Brown County. The field had previously been planted to wheat. The second isolate, Cler1-4-1, was also baited from agronomic soil, collected from a no-till field in Clermont County. This latter field had previously been planted to corn and the soil had high silt content (53.2%). Cultures were maintained on PCA slant vials at 15°C. Sequence analysis of the ITS region found both isolates had identical sequences and 100% identity to isolates of P. irregulare sensu stricto used by

Garzón et al. (2007). The two isolates had previously been tested for pathogenicity to soybean using a sand-cornmeal inoculum assay in the greenhouse among other P.

136 irregulare isolates collected from Ohio, and were chosen based on their high levels of pathogenicity compared to the other isolates (Ellis et al., unpublished data).

A greenhouse assay was used to evaluate soybean genotypes for resistance to P. irregulare. Inoculum was prepared using a modified protocol by Broders et al. (2007) and Kirkpatrick et al. (2006). Briefly, eight 10-mm plugs of a 3-day-old PCA culture of each isolate were placed into a previously double-sterilized spawn bag containing 950 ml of sand, 50 ml of cornmeal, and 250 ml deionized water. The bags were sealed using a sealer-electrical impulse (Harbor Freight Tools; Calabasas, CA) and then shaken every other day for 10 days to ensure even and thorough colonization of the mycelia.

One-liter of inoculum was mixed with 4-liter of fine vermiculite for a 4:1 ratio of vermiculite to inoculum, and 300 ml of the mixture was placed into 500 ml Styrofoam cups with a 100 ml layer of coarse vermiculite at the bottom. Cups were watered three times over 32 h to allow the vermiculite mixture to become saturated and ensure high moisture conditions for optimum disease development. Once the cups were saturated, 8 seeds of each genotype were planted and covered with approximately 100 ml of coarse vermiculite. The cups were watered twice a day to ensure high moisture.

Data for stand at two time points 10 dai, and when the non-inoculated controls reached vegetative growth state V1 (14 or 16 dai), when the first trifoliate is fully emerged and open; total weight at V1; root weight at V1; and a root rot score at V1 was collected. Root rot was rated on a 1-to-5 scale, where: 1 = healthy root system with no symptoms of lesions or rot on the root system; 2 = small lesions on the lateral roots, with approximately 1-20% of roots with visible symptoms; 3 = rot on lateral roots, visible

137 symptoms of rot beginning on the main tap root, with approximately 21-75% of the roots with visible symptoms; 4 = both lateral roots and main tap roots with visible symptoms of root, approximately 76-100% of the roots infected; and 5 = no germination, complete colonization of the seed.

Sources of Resistance. A total of 105 soybean genotypes were screened over five separate experiments for resistance using the inoculation method described above. Seeds were provided by Rouf Mian from the Ohio Agricultural Research and Development

Center (Wooster, OH), and Steven. St. Martin from the Ohio State University (Columbus,

OH), the USDA Soybean Germplasm Collection (Urbana, IL), and Alison Robertson from the Iowa State University (Ames, IA) provided the cultivar Archer (Appendix E).

The selection of soybean genotypes was based on two criteria: genotypes with known resistance genes or partial resistance to other soybean pathogens; and genotypes from populations that were available to map resistance from sources found in the initial screening. Each experiment was arranged in a randomized complete block design in the greenhouse. There were two factors in each experiment, soybean genotype and isolate treatment, which included the P. irregulare isolates Br2-3-5, Cler1-4-1, and a noninoculated check. There were three replicates in each experiment, which was also the blocking factor. The cultivars Archer (Resistant), Sloan (Bahrenfus and Fehr, 1980)

(Susceptible), and Kottman (St. Martin et al., 2001) (Susceptible) were used as checks in all five experiments.

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The first three greenhouse experiments were during February to April of 2009, with average temperature ranging from approximately 17-24°C, consistent with spring temperatures during planting in Ohio. There were 25, 39, and 40 genotypes in experiments 1, 2, and 3, respectively, for a total of 96 genotypes. During December to

January of 2010, only 70 of the 96 genotypes were screened due to seed availability, as well as nine additional genotypes. The 79 genotypes were screened in two separate experiments, with 36 and 39 genotypes in experiments 4 and 5, respectively. The average temperature was 15-22°C during the two experiments in 2010, which was slightly cooler than the 2009 experiments.

The data of the five experiments was analyzed separately. Data for root weight was not collected from experiment 1. For root weight a standardized root weight was calculated by comparing the percentage of root weight to the non-inoculated check for each genotype, which adjusted for the weight variation among genotypes based on natural growth habit of the root system. The calculation used to determine standardized root weight was: (root weight/number of germinated seedlings) / (root weight of the noninoculated check of the same genotype/divided by the total number of seedlings that germinated) x 100. The range of standardized root weight data exceeded 40%, thus the data was arcsine transformed as suggested by Little and Hill (1978) and analyzed using the PROC RANK, and PROC GLIMMIX procedures of SAS 9.2 (SAS Institute Inc.,

Cary, NC). The ordinal root rot score data was analyzed using PROC RANK and PROC

GLIMMIX of SAS 9.2 (SAS Institute Inc., Cary, NC) as suggested by Shah and Madden

(2004).

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Plant Material for Mapping. Two populations were used to map resistance in PI

424354 to P. irregulare in soybean: 192 F2:3 plants of OHS 303 (moderately susceptible) x (Williams (moderately susceptible) x PI 424354) and 127 F2:3 plants of Dennison (St.

Martin et al., 2008) (moderately susceptible) x (Williams x PI 424354). The populations were developed by crossing Williams with PI 424354 and then a selected F3 plant from this population was crossed with Dennison or OHS303 and these crosses were carried to the F2 generation (Appendix B). The populations were initiated to map putative novel Rps genes from PI 424354, which confer resistance to Phytophthora sojae.

Phenotypic assay of two populations. The sand-cornmeal inoculation method was used to phenotype both populations. Briefly, 10 seeds of an F2 line were placed in a cup with the inoculum mixture, using isolate Br2-3-5, and covered with coarse vermiculite. For the

OHS population, the cups were set up during November of 2010, and arranged in a completely randomized design in a growth chamber at 18°C. The cups for Dennison population were also arranged in a completely randomized design, however, this experiment was set up in the greenhouse during April of 2010, with temperatures averaging at 18-21°C for the entirety of the experiments. Each population was evaluated twice. Data for stand count, root weight, total weight, and a root rot score was collected at the V1 growth stage. For the analysis, the root weights were divided by the number of seedlings germinated. Both the root weight data and the root rot score data were analyzed using PROC MIXED of SAS 9.2 (SAS Institute Inc., Cary, NC).

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Molecular mapping. A genetic map was developed for both populations to identify genomic regions associated with resistance to P. irregulare. To develop the map, both populations were genotyped with 384 single nucleotide polymorphism (SNP) markers using the VeraCode GoldenGate Genotyping Kit (Illumnia Inc., San Diego, CA) and analyzed using the Illumnia BeadXpress Reader (Illumnia Inc., San Diego, CA). Simple sequence repeat (SSR) markers were added to fill in gaps where regions in the genome were not covered by the SNP markers. SSR markers were amplified by polymerase chain reaction (PCR) using a modified protocol from Gordon et al. (2007). A 12.5 µL PCR mix containing 50ng genomic DNA, 1x PCR buffer (Promega, Madison, WI), 130 µM of each dNTP, 2mM MgCl2 (Promega), 0.4 µM forward and reverse primers, and 0.5 unit of Taq DNA polymerase (Promega). A touchdown program was used in which the annealing temperature decreased from 60°C to °50 by 1°C each cycle for the first 10 cycles and the annealing temperature was kept at 50°C for the remaining 28 cycles. PCR products were analyzed by electrophoresis on 4% 3:1 HRBTM agarose (AMERSCO Inc.,

Solon, OH) containing 0.7% GelRedTM (Phenix Research Products, Candler, NC) for

120-180 min at 150 volts in the RapidRunTM Agarose Buffer (Affymetrix/USB Inc.,

Cleveland, OH). The products were sized with TriDyeTM 100bp DNA ladder (UVP Inc.,

Upland, CA). The gels photographed using the Kodak Electrophoresis Documentation and Analysis System 290 (EDAS, 290: Kodak Company, Rochester, NY) and the product bands were scored. The map was developed in JoinMap 4.0 using the Kosambi function

(van Ooijen, 2004) with 70 and 47 polymorphic SNP and 4 and 6 SSR markers, for the

141

Dennison and OHS303 populations, respectively. In order to create the maps, Williams,

OHS303 or Dennison were considered the recurrent parent. Markers were chosen that were polymorphic between the PI 424354 and the recurrent parent. Interval mapping

(IM) and composite interval mapping (CIM) was performed using MAPQTL 5.0 (van

Ooijen, 2004). The walking speed for QTL analyses was 1.0 cM. Permutation tests with

1000 iterations were performed on each linkage group and on the whole genome to estimate significant logarithm of odds (LOD) scores (Churchill and Doerge, 1994). The total genotypic variation explained by additive effects was calculated by adding the percentage of explained variation from each potential QTL from CIM and IM using

MAPQTL. One-way ANOVA with the Proc GLM procedure (SAS Institute Inc.) was used to identify the single marker association with phenotypic variation.

RESULTS

Sources of resistance. There were significant differences among the 105 genotypes based on the standardized root weight and the root rot score (Table 5.1-5.2 and Appendix

F). The standardized root weight was measured as the mean percentage of the final inoculated root weight over the non-inoculated control per seedling. In these studies the overall standardized root weight ranged from 0.0 to 103.2%, with the highest values indicating resistance. There was also a significant difference between the two isolates, with the exception of experiment 4 for standardized root weight and experiment 2 for the root rot score. The genotype x isolate interaction was not significant for any of the five experiments for both standardized root weight and the root rot score (Table 5.1-5.2). The

142 check Archer was moderately susceptible in all five experiments with an average standardized root weight of 46.3% and root rot score of 3.2. There were 28, 25, 31, and

27 genotypes that had higher ranks standardized root weight, indicating higher levels of resistance, when compared with Archer in experiments 2, 3, 4, and 5, respectively. For the root rot score there were 13, 23, 26, 25, and 19 genotypes with lower ranks, which indicated higher levels of resistance, when compared with Archer in experiments 1, 2, 3,

4, and 5, respectively. Among genotypes tested over multiple experiments, 36 for standardized root weight and 24 for the root rot score had consistently higher levels of resistance across experiments from 2009 and 2010 when compared to Archer (Appendix

F). A few genotype ranks did vary across experiments (Appendix F). This may be due in part to different sources of seed for a particular genotype (Appendix E).

Phenotypic assay for QTL mapping. Based on the results above, the plant introduction

(PI) PI 424354 had high levels of resistance with an average standardized root weight of

99.7%. Symptoms on PI 424354, were small tan to brown lesions on the lateral roots and no lesion development on the main taproot, and the average root rot score was 1.9. The cultivar Williams (Bernard and Lindahl, 1972) was significantly different from the PI

424354 with an average standardized root weight of 61.7 and root rot score of 3.2 (Fig.

5.1, Appendix F). In addition, OHS303 and Dennison were also moderately susceptible to

P. irregulare in experiment 5 with an standardized root weight of 40.9% and 55.5% and were also susceptible in experiment 1 and 5 for the root rot score, with averages of 4.3 and 3.6 (Appendix F) for OHS303 and Dennison, respectively.

143

The two mapping populations used in this study fit the model for quantitative resistance based on the distribution of the 192 and 127 F2 lines for root weight and for the root rot score (Fig. 5.2). The mean root weights per seedling across the F2 lines in both populations were 1.6 and 0.21 and the average root rot scores were 3.6 and 4.1 for the

OHS303 and Dennison populations, respectively. For the phenotypic assays for the

OHS303 population, the average root weights per seedling were 0.38, 0.17, and 0.36, and the average root rot scores were 2.1, 4.1, and 2.2 for the parental lines PI 424354,

Williams, and OHS303, respectively. The parental line OHS303 had lower levels of disease compared to the initial germplasm screening. One reason for this difference may be the different sources of seed (Appendix E), as the OHS303 typically has higher root weight compared to PI 424354 in the non-inoculated checks. For the phenotypic assays, for the Dennison population, the average root weights per seedling were 0.35, 0.02, and

0.32, and the average root rot scores were 2.3, 4.9, and 3.2 for the parental lines PI

424354, Williams, and Dennison, respectively.

Mapping of quantitative trait loci. Linkage maps were constructed from 53 and 74 molecular markers which covered 210.8 and 289.2 cM across 15 and 16 fractional MLGs

(unlinked markers not included) for the OHS303 and Dennison populations, respectively.

A number of markers that were polymorphic among the parents could not be used to create the maps since they were monomorphic in the populations, which indicated the PI

424354 was not represented in those chromosome regions (Appendix D, G).

144

Seven putative QTL were identified from the OHS303 population through IM on chromosomes 1, 5, 6, 8, 13, 14, and 20 for root weight and explained 67.9% of the phenotypic variation, with each QTL contributing approximately 6-15% (Table 5.3). The

QTL on chromosomes 1, 6, 13, 14, and 20 were also identified using IM for the root rot score data and explained 59.3% of the phenotypic variation, with each QTL contributing

6-18% (Table 5.3). The putative QTL on chromosome 1 and 6 were also identified with

CIM for root weight and root rot score data, and explained 22.8% and 30.1% of the phenotypic variation, respectively (Table 5.3, Fig. 5.3). Another putative association through one-way ANOVA was identified on chromosome 2 for root weight and root rot score (Table 5.4).

Three putative QTL were identified from the Dennison population with IM on chromosomes, 8, 10, and 13 for root weight (Table 5.3). CIM also identified the QTL on chromosomes 8 and 10, along with a QTL on chromosome 11 (Table 5.3, Fig. 5.4). The

QTL on chromosome 8 and 10 identified for root weight explained 27.3% and 23.7% of the phenotypic variation, with each QTL contributing approximately 12 to 15% and 11 to12% for IM and CIM, respectively (Table 5.3). For the root rot score data, two putative

QTL were identified with IM on chromosomes 8 and 13 and explained 27.9% of the phenotypic variation, with each QTL contributing approximately 10-18% (Table 5.3).

The QTL on chromosome 13 was also identified using CIM and explained 15.6% of the phenotypic variation (Fig. 5.4). Other putative associations identified with the single maker association were on chromosome 1 for root weight and chromosomes 2, 5 and 13 for root weight and root rot score (Table 5.4).

145

There were 2 to 4 QTL identified for resistance to P. irregulare in both populations. The QTL on chromosome 6 was identified from the single marker analysis in both populations, and IM, and CIM in the OHS population for root weight and root rot score (Tables 5.3-5.4, Fig. 5.3). There was a larger region identified on chromosome 1 that ranged from approximately 35 to 85 cM, based on the consensus map (Hyten et al.,

2008). In the OHS population, the nearest marker was Satt515 at 38.8 cM (Hyten et al.,

2008), associated with root weight and root rot score (Tables 5.3-5.4, Fig. 5.3), while marker BARC-030807-06945 at 85.9 cM (Hyten et al., 2008) was significant in the

Dennison population for root weight (Table 5.4). There were one or two QTL on chromosome 8 ranging from approximately 45 to 90 cM, based on the consensus map

(Hyten et al., 2008), associated with resistance through IM for root weight and root rot score in both populations, and CIM and from the single marker analysis for root weight in the Dennison population (Tables 5.3-5.4, Fig. 5.4). There may also be two QTL on chromosome 13 that confer resistance to P. irregulare. One putative association with resistance to P. irregulare was identified in the Dennison population at 76.7 cM (BARC-

062009-17616) based on the consensus map of Williams82 (Hyten et al., 2008) (Table

5.4). There was also a putative QTL on chromosome 13, approximately 5 to 40 cM, based on the consensus map (Hyten et al., 2008), identified with IM for root weight and root rot score and CIM for the root rot score in the Dennison population, and identified by IM in the OHS population (Tables 5.3-5.4). One association that was identified on chromosome 2, was identified with single marker association for marker Sat_373 (35.75

146 cM) in the OHS population and BARC-053841-11881 (26.14 cM) and BARC-007889-

00156 (36.1 cM) in the Dennison population for root weight and score data.

DISCUSSION

From the screening of the 105 soybean genotypes, approximately ½ of the genotypes were moderately resistance to P. irregulare (Appendix F). PI 424354 and other soybean genotypes with high levels or resistance all had some disease symptoms, tan to brown lesions on the lateral roots that were absent in the non-inoculated controls, and standardized root weight values of approximately 80 to 100% and root rot scores ranging from 1.9 to 2.7. These results indicate that resistance to P. irregulare in this soybean germplasm is quantitatively inherited. In the germplasm selected for this study, approximately ½ of the genotypes have R-gene mediated resistance from characterized or novel Rps genes, or partial resistance to Ph. sojae; however, many of these genotypes also had high levels of susceptibility to P. irregulare. These results suggest that there are different mechanisms in soybean that contribute to resistance to these two oomycete seedling pathogens. This can be supported with the recently sequenced P. ultimum var. ultimum genome where Lévesque et al. (2010) suggests that the ‘toolkits’ for survival and pathogenesis vary among oomycetes. Unlike Phytophthora spp. and downy mildews, the genome sequence of P. ultimum var. ultimum lacks RXLR effectors and has a limited number of Crinkler genes (Cheung et al., 2008; Lévesque et al., 2010). Lévesque et al.

(2010) suggest that resistance identified in plants against P. ultimum var. ultimum will be quantitative due to the non-host-specific nature of this pathogen, or deployed by novel

147 effectors proteins such as the YxSL[RK] effectors identified in the study. Future studies to determine if these finding are representative across species of Pythium could provide insight as to how plants defend themselves against a range of oomycete pathogens.

The two BC1F2:3 mapping populations used in this study were originally initiated to map putative novel Rps genes from PI 424354, which confer resistance to Ph. sojae.

The advantage of using these populations is that individual lines with high levels of resistance can easily be advanced and released as germplasm. However, there were also two disadvantages in using these mapping populations. The first disadvantage was the lack of polymorphic markers between the parents. There was genetic variation between the recurrent parents (Williams, OHS303, and Dennison) when screening the molecular markers to map the resistance for the PI 424354 (Appendix G). The second disadvantage was based on the nature of the crosses used to create these populations where the PI

424354 was not represented in a large portion of the genome in each population.

Chromosome 19 had a number of markers that were polymorphic between the recurrent parents and the PI 424354, however, none of the markers were polymorphic among the

192 and 127 F2 lines, indicating the lack of genetic contribution from the PI 424354.

Based on the marker positions from consensus map (Hyten et al. 2008), there were other regions that were monomorphic in the Dennison population including: chromosome 1 with the first introgression from PI424354 at 83 cM; 103 to 132 cM on chromosome 2;

86 to 132 cM on chromosome 6; and chromosome 17 with the first introgression from PI

424354 at 73 cM. A similar situation resulted for the OHS population, where the first introgression from PI 424354 on chromosome 1 was at 41 cM, and the last at 64 cM;

148 none on chromosome 3; none from 56 to 87 cM on chromosome 5; none from 36 to 88 cM on chromosome 6; none on chromosome 8 from 44 to 66 cM and 128 to 142 cM; and none on chromosome 17 from 55 to 95 cM. It was a challenge to confirm the QTL as there were few regions with introgressions from PI 424354 that were common between the two populations. There were a number of QTL identified by IM, but not CIM.

Populations of larger size and more advanced may solve some of these issues.

The putative QTL identified in the two populations were in regions with previously reported QTL for resistance to other soybean pathogens and pests. The QTL identified on chromosome 1, 6, and 8 are in similar regions for QTL reported for soybean cyst nematode (Mahalingam and Skorupska, 1995; Yue et al., 2001). The QTL on chromosome 1 overlaps a region for partial resistance to Ph. sojae (Wang, 2011). Four

QTL are in regions where QTL have been associated with seed traits such as seed weight and seed yield on chromosomes 1, 10, 14, and 20 (Csanadi et al., 2001; Mian et al., 1996;

Panthee et al., 2005; Reinprecht et al., 2006). Interestingly, the QTL on chromosome 13 is in a similar region with QTL associated for a number of other soybean pathogens including: Ph. sojae (Burnham et al., 2003; Han et al., 2008; Wang et al., 2010); F. virguliforme (Kassem et al., 2006; Kazi et al., 2008); F. graminearum (Chapter 4); and

Sclerotinia sclerotiorum (Arahana et al., 2001; Guo et al., 2008). The QTL near the top of chromosome 8 is in a similar location to a QTL reported for F. virguliforme (Hashmi,

2004). The QTL on chromosome 5, 11, and 20 are in similar regions to QTL identified for S. sclerotiorum (Arahana et al., 2001). The QTL on chromosome 6 is near the bottom of the chromosome where QTL reported for Ph. sojae (Li et al., 2010), and F.

149 virguliforme (Hnetkovsky et al., 1996; Iqbal et al., 2001; Njiti et al., 1998, 2002) have been identified. The putative association identified on chromosome 2 is north of a QTL identified for Ph. sojae (Burnham et al. 2003) based on the Williams82 consensus map

(Hyten et al., 2008).

PI 424354 is a source of resistance to two other seedling pathogens, Ph. sojae

(Dorrance and Schmitthenner, 2000) and F. graminearum (Chapter 4). Dorrance and

Schmitthenner (2000) identified the PI 424354 as a source of novel Rps genes and partial resistance to Ph. sojae. For these reasons, the PI 424354 is a candidate for developing new cultivars with high levels of resistance to three different seedling pathogens; P. irregulare, Ph. sojae (Dorrance and Schmitthenner, 2000), and F. graminearum (Chapter

4). Future studies that map the resistance to these pathogens should be high priority as well as confirming the putative QTL identified in this study that confer resistance to P. irregulare. However, based on the differences in the resistance to P. irregulare in Archer, reported from Arkansas (Bates et al., 2008) and this study, further studies are needed to assess resistance with geographically distinct isolates.

ACKNOWLEGEMENTS

I would like to thank Dr. Anne E. Dorrance, Dr. Pierce A. Paul, Dr. Leah K.

McHale, and Dr. Steven K. St. Martin. They all contributed greatly to this work. I would like to thank Sue Ann Berry for technical assistance and OARDC farm crew for assistance with advancing the population. Funding was provided in part through the soybean checkoff dollars from Ohio Soybean Council and United Soybean Board.

150

Salaries and research support for this project was provided by State and Federal Funds appropriated to the Ohio Agricultural Research and Development Center, The Ohio State

University. We would also like to thank the staff of the Molecular and Cellular Imaging

Center (MCIC, OARDC) for sequencing, and the Ohio BioProducts Innovation Center

(OBIC) for funding of genotyping equipment.

151

Experiment 1 Experiment 2 Experiment 3 Root Rot Disease Root Rot Disease Root Rot Scorey Severityz Scorey Severityz Scorey Effectx df F P>F df F P>F F P>F Df F P>F F P>F Genotype (G) 24 2.37 <0.0001 38 5.63 <0.0001 8.16 <0.0001 39 2.48 <0.0001 4.89 <0.0001 Isolate (I) 1 5.64 0.0005 1 5.01 0.0178 1.73 0.1908 1 26.65 <0.0001 61.07 <0.0001 G x I 24 1.21 0.1613 38 0.78 0.8514 0.91 0.6262 39 0.58 0.9771 0.72 0.8860

152 Table 5.1: Analysis of variance for standardized root weight and root rot score in a greenhouse screening during

2009 of 96 soybean genotypes for resistance to Pythium irregulare.

x The experimental design for each greenhouse experiments was a randomized complete block design with two factors, soybean

genotype and isolate treatment, which included the P. irregulare isolates Br2-3-5, Cler1-4-1, and a non-inoculated check (not included

in the analysis). There were three replications within each experiment. There were 25, 39, and 40 genotypes in experiments 1, 2, and 3

respectively. The cultivars Archer, Sloan, and Kottman were used a checks in all three experiments.

y The root rot scale used on a 1-to-5 scale where: 1 = healthy root system with no symptoms of lesions or rot on the root system and

5 = no germination, complete colonization of the seed.

z The standardized root weight was calculated as follows: (root weight/number of germinated seedlings) / (root weight of the non-

inoculated check of the same genotype/divided by the total number of seedlings that germinated) x 100.

Experiment 4 Experiment 5 Disease Root Rot Disease Root Rot Severityz Scorey Severityz Scorey Effectx df F P>F F P>F df F P>F F P>F Genotype (G) 35 1.88 0.0075 2.46 0.0001 38 2.27 0.0004 6.11 <0.0001 Isolate (I) 1 0.52 0.2923 8.79 0.0036 1 19.83 <0.0001 33.46 <0.0001 G x I 35 0.70 0.9067 0.4 0.9989 38 0.93 0.5924 0.81 0.3701

153 Table 5.2: Analysis of variance for standardized root weight and root rot score in a greenhouse screening during

2010 of 79 soybean genotypes for resistance to Pythium irregulare.

x The experimental design for each greenhouse experiment was a randomized complete block design with two factors, soybean

genotype and isolate treatment, which included the P. irregulare isolates Br2-3-5, Cler1-4-1, and a non-inoculated check (not included

in the analysis). There were three replications within each experiment. There were 36, and 39 genotypes in experiments 4, and 5

respectively. The cultivars Archer, Sloan, and Kottman were used a checks in both experiments.

y The root rot scale used on a 1-to-5 scale where: 1 = healthy root system with no symptoms of lesions or rot on the root system and

5 = no germination, complete colonization of the seed.

z The standardized root weight was calculated as follows: (root weight/number of germinated seedlings) / (root weight of the non-

inoculated check of the same genotype/divided by the total number of seedlings that germinated) x 100.

Table 5.3: Quantitative trait loci for partial resistance to Pythium irregulare from the plant introduction (PI)

424354 that were identified via interval mapping (IM) and composite interval mapping (CIM) using 2 BC1F2:3

populations

x Two populations were used to map resistance in PI 424354 to P. irregulare in soybean: 192 F2:3 plants of OHS 303 (moderately

susceptible) x (Williams (moderately susceptible) x PI 424354) and 127 F2:3 plants of Dennison (moderately susceptible) x (Williams 154 x PI 424354).

y The root rot scale used on a 1-to-5 scale where: 1 = healthy root system with no symptoms of lesions or rot on the root system and 5

= no germination, complete colonization of the seed. The total root weight was divided by the number of germinated seedlings for root

weight per seedling.

z Consensus map position (Hyten et al. 2008) of the nearest marker in each interval.

xx Threshold of significance for LOD for each chromosome based on permutation tests of 1000 iterations (P<0.05, Churchill and

Doerge, 1994).

Populationx Traity Chromosome Intervals Nearest Marker Consensus IM Exp. CIM Exp. LOD (cM) Map (cM)z LOD Var. LOD Var. Thr.xx (%) (%) OHS303 Root/Germ 1 30.1-37.9 Satt515 38.8 2.8 14.0 2.2 9.6 1.8 OHS303 Score 1 14.1-37.9 Satt515 38.8 4.3 17.7 4.8 17.8 1.9 OHS303 Root/Germ 5 1.0-6.7 BARC_050697_09840 38.0 2.3 6.0 1.0 1.9 1.7 OHS303 Root/Germ 6 0.0-13.5 BARC_013837_01254 86.3 4.0 15.4 3.8 13.2 1.8 OHS303 Score 6 0.0-10.5 BARC_013837_01254 86.3 3.8 14.9 2.8 12.3 1.8 Dennison Root/Germ 8 14.5-19.5 BARC_032503_08989 44.5 2.9 12.6 2.3 11.4 2.1 Dennison Score 8 16.4-19.4 BARC_041561_08032 62.5 2.8 10.3 1.2 4.4 2.2 155 OHS303 Root/Germ 8 0.0-12.0 BARC_021577_04150 89.6 3.5 8.8 1.4 3.0 1.8

OHS303 Score 8 0.0-8.0 BARC_021577_04150 89.6 2.8 7.0 1.3 3.1 1.7 Dennison Root/Germ 10 7.3-16.3 BARC_018101_02517 10.7 3.1 14.7 2.7 12.3 2 Dennison Root/Germ 11 0-2.9 BARC_053481_11881 23.9 1.1 4.4 2.3 7.9 1.5 Dennison Root/Germ 13 4.0-11.7 BARC_900926_00961 5.1 2.2 8.2 1.3 4.7 1.8 Dennison Score 13 3-11.8 BARC_900926_00961 5.1 3.2 17.6 2.5 15.6 1.8 OHS303 Root/Germ 13 0.0-12.0 BARC_062009_17616 36.7 2.4 7.1 0.2 0.4 1.7 OHS303 Score 13 0-10.0 BARC_062009_17616 36.7 2.2 6.3 0.5 1.4 1.8 OHS303 Score 14 0.0-5.0 BARC_065411_19443 13.1 2.3 7.4 1.1 3.7 2.0 OHS303 Root/Germ 14 1.0-8.9 BARC_015539_02002 27.4 2.6 8.3 0.9 2.8 2.0 OHS303 Root/Germ 20 0.0-11.3 BARC_052017_11314 20.0 3.0 8.3 0.5 1.0 1.9 OHS303 Score 20 5.4-11.3 BARC_052017_11314 20.0 2.3 6.0 0.8 1.9 1.9 Table: 5.3

Table 5.4: Putative marker associations for partial resistance to Pythium irregulare from the plant introduction

(PI) 424354 that were identified via a one-way ANOVA (P < 0.05).

The dashes indicate that the marker was not significant. The blue represents that the marker was monomorphic in the population,

indicating the PI 424534 was not represented in that region on the chromosome. The white indicates that the marker was not

polymorphic for that population.

x Two populations were used to map resistance in PI 424354 to P. irregulare in soybean: 192 F2:3 plants of OHS 303 (moderately

156 susceptible) x (Williams (moderately susceptible) x PI 424354) and 127 F2:3 plants of Dennison (moderately susceptible) x (Williams

x PI 424354).

y Consensus map position (Hyten et al. 2008) of the nearest marker in each interval.

z The root rot scale used on a 1-to-5 scale where: 1 = healthy root system with no symptoms of lesions or rot on the root system and 5

= no germination, complete colonization of the seed. The total root weight was divided by the number of germinated seedlings for root

weight per seedling.

Consensus Map OHS303 Dennison Chromosome Marker (cM)y Populationx Populationx Root Root Weightz Scorez Weightz Scorez 1 Satt515 38.793 0.0068 <0.0001 BARC-061099-17047 41.578 0.0171 BARC-064293-18611 42.572 0.0488 BARC-060617-16751 43.745 0.007 BARC-030807-06945 85.93 0.0325 2 BARC-050661-09809 26.14 0.0173 0.0249

157 Sat_373 35.75 0.0046 0.0037 BARC-007889-00156 36.115 0.0285 - 5 BARC-053481-11881 23.856 0.0210 BARC-053373-11828 34.778 0.0184 - - BARC-050697-09840 38.045 0.0057 BARC-053443-11853 41.627 0.0398 BARC_043209_08557 80.51 0.0056 0.0159 6 BARC-016957-02165 26.077 0.0174 0.0374 BARC-013837_01254 36.765 0.0005 0.0023 - - BARC-047715-10388 0.0008 0.0034 Satt307 0.0184 8 BARC-032503-08989 44.469 0.0454 - 11 BARC-059773-16088 80.992 - - - 0.021 13 BARC-062009-17616 36.736 0.0043 0.0268 - - BARC-028887-06033 76.682 0.0116 0.0369 14 BARC-016831-02340 81.186 0.0479 Table: 5.4

Figure 5.1: Symptoms of Pythium irregulare infection 14 dai and non-inoculated control

(right) on plant introduction (PI) 424354 (high levels of resistance) compared to Williams

(moderately susceptible). Seed was planted in infested vermiculite with a sand-cornmeal inoculum.

158

Figure 5.2: Distribution of root weight per seedling and root rot score among 192 and 127 F2 lines from two BC1F2:3

populations used the map resistance in the plant introduction (PI) 424354 to Pythium irregulare. The two populations used to

map resistance in PI 424354 to P. irregulare in soybean included: 192 F2:3 plants of OHS 303 (moderately susceptible) x

(Williams (moderately susceptible) x PI 424354) (A, B) and 127 F2:3 plants of Dennison (moderately susceptible) x (Williams

x PI 424354) (C, D). For the phenotypic assays for the OHS303 populations, the average root weights per seedling were 0.38,

0.17, and 0.36, and the average root rot scores were 2.1, 4.1, and 2.2 for the parental lines PI 424354, Williams, and OHS303 159

respectively. For the phenotypic assays for the Dennison populations, the average root weights per seedling were 0.35, 0.02,

and 0.32, and the average root rot scores were 2.3, 4.9, and 3.2 for the parental lines PI 424354, Williams, and Dennison

respectively.

160

Figure: 5.2

Figure: 5.3: Genetic maps generated from the genotype data from the of OHS 303 (moderately susceptible) x (Williams

(moderately susceptible) x PI 424354) BC1F2:3 population using JoinMap4.0 (van Ooijen, 2006); and logrithim of odds (LOD)

charts of the putative quantitative trait loci (QTL) from composite interval mapping (CIM) analysis by MapQTL 5.0 (van

Ooijen, 2004) for root weight and root rot score data. The chromosome number is listed above each linkage group. 161

162

Figure: 5.3

Figure: 5.4: Genetic maps generated from the genotype data from the of Dennison (moderately susceptible) x (Williams

(moderately susceptible) x PI 424354) BC1F2:3 population using JoinMap4.0 (van Ooijen, 2006); and logrithim of odds (LOD)

charts of the putative quantitative trait loci (QTL) from composite interval mapping (CIM) analysis by MapQTL 5.0 (van

Ooijen, 2004) for root weight and root rot score data. The chromosome number is listed above each linkage group.

163

164

Figure: 5.4

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CHAPTER 6

CONCLUSIONS

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Seedling diseases of soybean [Glycine max (L.) Merr] have increased over the last decade in Ohio. The objectives of this dissertation were to further characterize some of these seedling pathogens in an effort to better understand their lifecycle and biology, and to identify and characterize sources of resistance. The seedling pathogens examined in the previous chapters negatively impact soybean production in Ohio. They include:

Fusarium graminearum Schwabe (teleomorph: Gibberella zeae (Schwien.) Petch),

Pythium schmitthenneri Ellis, Broders, and Dorrance, Pythium selbyi Ellis, Broders, and

Dorrance, and Pythium irregulare Buisman.

This dissertation addressed four important questions concerning the emergence and management of F. graminearum as a seedling pathogen of soybean: optimum inoculum and temperature parameters for disease development; efficacy of fungicide seed treatments in a seed-based assay; identification of sources of resistance; and mapping putative quantitative trait loci (QTL) conferring resistance to F. graminearum. The range of temperatures evaluated in Chapter 2 were typical during the time of planting in Ohio.

There were no significant differences among temperature treatments in the study (P =

0.05). Observations indicate that the plant and pathogen grew proportionally to one another at different temperatures. However, the results from Chapter 2 indicate that severe disease development only occurred when high levels of inoculum, 2.5 x 104 macroconidia/ml or higher, were used. In Ohio, producers predominantly use a corn- soybean or corn-soybean-wheat rotation in combination with reduced-tillage or no-tillage to conserve soil, prevent erosion, and increase organic matter. These practices favor the survival of F. graminearum, since the pathogen can overwinter on crop debris from all

172 three hosts (Baird et al., 1997; Cotton and Munkvold, 1998; Leslie et al., 1990; Windels et al., 1988). Thus, it can be hypothesized that these changes in production have led to an increase in inoculum in Ohio’s agricultural fields. In more recent years, other plant species, besides soybean, have also been named as hosts of F. graminearum (Ali et al.,

2005; Bilgi et al., 2011; Chongo et al., 2001; Hanson, 2006). Burrlakoti et al. (2008) examined genetic relationships among populations of Gibberella zeae from barley

(Hordeum vulgare L.), wheat (Avena sativa L.), potato (Solanum tuberosum L.), and sugar beet (Beta vulgaris L.) and found that there were no differences among populations structures from infected the tested crop species. In other studies, isolates of F. graminearum collected from wheat and corn were moderately to highly pathogenic to soybean (Broders et al., 2007; Xue et al., 2004; Xue et al., 2007). Xue et al., (2007) proposed that selection pressure for highly aggressive F. graminearum isolates may exist for a wheat-soybean rotation. The emergence of these non-cereal hosts of F. graminearum in recent years, leads us to ask what factor(s) were missing from the disease triangle. This pathogen has recently been found infecting a larger number of hosts

(Ali et al., 2005 ; Bilgi et al., 2011; Chongo et al., 2001; Hanson, 2006). However, it would seem unlikely mutation of the pathogen is responsible for the disease seen in these new host species, as in the case of soybean where older isolates (from long-term storage) were pathogenic on soybean. Based on the current studies and observations, it seems inoculum levels may have been a driving force and the major component that was missing from the disease triangle. The susceptibility of soybean may also be a target.

Recently there has been a shift in soybean germplasm may partly explain the emergence

173 of F. graminearum on soybean. The recent shifts in soybean germplasm are likely due to the fact that industry now dominates in development of new cultivars compared to the public sector (Diers and Kim, 2008). These shifts and changes in the base soybean germplasm may have contributed to the emergence of this seed and seedling pathogen in

Ohio if cultivars grown prior to 2000 have high levels of resistance to F. graminearum.

Seed-treatments used in the past that had broad efficacy to a number of seedling pathogens may have also prevented F. graminearum from having a major impact on soybean. Captan (37.4% captan; Bayer Crop Science, NC) and Rival (19.8% captan plus

8.4% pentachloronitrobenzene plus 1.0% thiabendazole; Gustafson, Plano, TX) were highly effective seed-treatments in corn and soybean, respectively; but are no longer widely available for a number of reasons. Even the newer class of fungicides, the

Quinone Outside Inhibitor (strobulurins), which have broad efficacies (used for management of true fungi and oomycetes), were found to be ineffective as seed- treatments for the management of F. graminearum (Broders et al., 2007; Chapter 2).

Fludioxonil was the only fungicide that inhibited mycelia growth in amended agar assays

(Broders et al., 2007), and the rolled towel assay (Chapter 2); however, captan performed equally as well as fludioxonil in the rolled-towel assay (Chapter 2). With fludioxonil as the only known fungicide seed-treatment currently available for management of F. graminearum on soybean this creates a demand on industry to develop new effective seed-treatments. This is especially true, since fludioxonil insensitive mutants that were pathogenic on soybean were readily generated during a laboratory assay (Broders et al.

2007), although no mutants have been identified from the field. These results also

174 identify the importance of using an integrated management strategy, due to the limited choices of fungicide seed-treatments. This led us to the next objective in this dissertation, which was to identify sources of resistance to F. graminearum in soybean and to map the resistance identified, so that in the future resistance might be utilized along with fungicide seed-treatments in an integrated management program or even reduce the reliance on fungicide seed-treatments for this pathogen.

The last objective of this dissertation, with respects to F. graminearum as a seedling pathogen to soybean, was to examine disease resistance and to map the resistance that was identified in an existing population (Chapter 4). The hypotheses of this study were that resistance was present in adapted soybean cultivars which were widely grown prior to the recent emergence of F. graminearum as a seed and seedling pathogen of soybean, and that the type of resistance that would be identified would be quantitative in nature. The results suggest that resistance to F. graminearum may be common in soybean based on the select group of 24 genotypes that were screened for resistance. If resistance to pathogens such as F. graminearum is common in soybean genotypes, it may not be necessary for breeders to focus initial efforts on non-adapted germplasm when developing new cultivars, but instead conduct screens for resistance to these pathogens in advanced breeding lines. Since resistance to F. graminearum was very readily identified, this may also indicate that shifts and changes in the base soybean germplasm may have contributed to the emergence of this seed and seedling pathogen in

Ohio. An evaluation of representative cultivars that were grown prior to 2000, compared to those that are available today will be necessary to confirm this hypothesis.

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Of the genotypes expressing high levels of resistance to F. graminearum, none exhibited a phenotypic response for complete resistance and all had minor lesion development following infection, suggesting that resistance in these select germplasm is quantitatively inherited. This is consistent with other necrotrophic host-pathogen interactions. This is partly because R-gene mediated resistance, often utilized by biotrophic and hemibiotrophic pathogens which have limited host ranges, involves a hypersensitive response where the tissue immediately adjacent to the site of pathogen infection undergoes rapid programmed cell death. This response can actually increase susceptibility in necrotrophic pathogens that thrive on dead host tissue (Poland et al.,

2009). The resistance identified in the F6:8 recombinant inbred line (RIL) population of

Conrad x Sloan was quantitative based on the phenotypic distribution of lines (Chapter

4). Five putative QTL associated with resistance to F. graminearum were indentified in this soybean population. The QTL in this study were minor (Chapter 4), with each locus only explaining 3 to 11 % of the variation, which may make breeding for resistance to this pathogen difficult in soybean. However, if the resistance is readily available as suggested by the 24 genotypes that were screened, these breeding efforts may not be necessary.

Conrad is a source of partial resistance to both Phytophthora sojae and F. graminearum (Burnham et al., 2003; Wang et al., 2010; Weng et al., 2007; Chapter 4).

An interesting observation from this study was there was no direct evidence of pleiotropy among QTL for two different soybean seedling pathogens. This was not surprising given the lifestyles of these two pathogens, where Ph. sojae is hemibiotroph. Moreover, three

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QTL identified by interval mapping and composite interval mapping, and three putative associations from the one-way ANVOA were found to be in similar regions with QTL reported for another necrotrophic pathogen, Sclerotinia sclerotiorum. Conrad has been identified as being moderately susceptible to S. sclerotiorum based on field evaluations from 1994 data collected by Kim et al. (1999). Further studies are necessary to assess if these same loci confer resistance to both of these pathogens, which might suggest pleoitropy for two pathogens with more similar lifestyles. Eventually, evaluation of the genes involved in resistance in regions with overlapping QTLs to these three pathogens could provide insights on how plants defend themselves from biotrophic and necrotrophic pathogens. This study would also be able to identify putative pleoitropic genes that may be involved in host defense against F. graminearum and S. sclerotiorum.

This dissertation had two objectives related to Pythium spp. that are seedling pathogens to soybean: to identify two new species of Pythium that are pathogenic to soybean and corn; and to identify and map resistance to P. irregulare. The new species described in this dissertation were widely dispersed throughout the soybean and corn producing regions in Ohio, making their characterization critical for managing the

Pythium complex that causes seedling and root rot diseases in Ohio soybean and corn fields. The two new species of Pythium that were described in this dissertation were P. schmitthenneri and P. selbyi. They both have morphological and sequence characteristics that place them in Clade E1 of the genus Pythium. The ITS region of Pythium schmitthenneri was 99.9% similar to P. acrogynum and 99.8% similar to P. hypogynum, while the ITS region of P. selbyi was 97.1 % similar to P. longandrum and 97.5% similar

177 to P. longisporangium. Partial sequences for the cytochrome oxidase I and II genes were also compared to members within the clade E1. However, these genes were not the best indicators to determine speciation, especially for P. schmitthenneri. One possible reason, is that these housekeeping genes likely evolve more slowly compared to the ITS region.

Members of the clade E1 have globose to limoniform sporangia and mostly plerotic oospores, which were both observed for P. schmitthenneri and P. selbyi. Pythium schmitthenneri has mostly diclinous antheridia, compared to the strictly hypogynous antheridia of P. acrogynum and P. hypogynum, while P. selbyi has hypogynous or monoclinous antheridia. Additionally, both species frequently had two oospores per oogonium.

The last objective of this dissertation was to identify and map resistance to P. irregulare. In a survey of agronomic soils from 88 locations, P. irregulare was identified from four of the five Pythium communities across Ohio, and was identified from approximately 90% of the locations (Broders et al., 2009), making the management of this seedling pathogen a priority among the soybean seedlings pathogens affecting soybean in Ohio. Approximately ½ of the genotypes screened in this study were moderately resistance to P. irregulare (Appendix F). Soybean genotypes with high levels of resistance all had some disease symptoms, which indicated that resistance to P. irregulare in this soybean germplasm is quantitatively inherited. The results from the initial screening also suggested that different mechanisms in soybean are responsible for resistance to P. irregulare and Ph. sojae. Approximately ½ of the genotypes screened had

R-gene mediated resistance from characterized or novel Rps genes, or partial resistance to

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Ph. sojae; however, many of these genotypes had high levels of susceptibility to P. irregulare.

The plant introduction (PI) 424354 was identified as a source of high partial resistance to P. irregulare in the germplasm screening and mapping of QTL in two

BC1F2:3 populations [OHS 303 (moderately susceptible) x (Williams (moderately susceptible) x PI 424354) and Dennison (moderately susceptible) x (Williams x PI

424354)] (Chapter 5). Two putative QTL in the OHS303 population and four putative

QTL in the Dennison population were identified with composite interval mapping. The

QTL were not confirmed in the two populations due to the nature of the crosses used to create these populations where the PI 424354 was not represented in a large portion of the genome in each population.

PI 424354 is also a source of resistance to two other seedling pathogens, Ph. sojae

(Dorrance and Schmitthenner, 2000) and F. graminearum (Chapter 4). Dorrance and

4). Future studies to map the resistance to these pathogens should be high priority as well as confirming the putative QTL identified in this study that confer resistance to P. irregulare.

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