The Soybean Seedling Disease Complex: Pythium spp. and Fusarium graminearum and their ...

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 By 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 ii

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.

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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 v

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.

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Vita June 1980 .......................................................Born – Rockford, Illinois, USA 2003................................................................B.S. Biology, University of Illinois UrbanaChampaign 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

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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

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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 xiv

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

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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 ITS15.8S-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 xx

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

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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 3649 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 10 5, 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

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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 5

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 nonlethal 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 6

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., 7

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

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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).

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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 12

(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 AgricultureAgricultural 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 15

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. 17

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. 19

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. 32

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 33

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 postemergence 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 reducedtillage 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 cornsoybean 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 36

(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. 37

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 2.5x10 4 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.

41

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