EVALUATION OF RESISTANCE IN GLYCINE MAX TO FUSARIUM VIRGULIFORME AND IN PERENNIAL GLYCINE SPECIES TO PHAKOPSORA PACHYRHIZI AND HETERODERA GLYCINES

BY

THERESA HERMAN

THESIS

Submitted in partial fulfillment of the requirements for the degree of Master of Science in Natural Resources and Environmental Sciences in the Graduate College of the University of Illinois at Urbana-Champaign, 2020

Urbana, Illinois

Master’s Committee:

Professor Glen L. Hartman, Chair Assistant Professor Santiago Mideros Professor Andrew N. Miller Professor Michelle M. Wander

ABSTRACT

Soybean [Glycine max (L.) Merr.] averages approximately 40% protein and 20% oil and is one of the world’s most important crops. Production of the crop is increasing, especially in less developed countries. Occurrence of diseases and pests affecting soybean have increased as production has expanded from its origin in China to almost 100 countries in 2019. Constraints to production due to diseases and pests have been estimated by FAO to reduce yield by 20 to 40% worldwide. Sudden death syndrome of soybean, soybean rust, and infection by soybean cyst nematode caused by fungal pathogens Fusarium virguliforme and Phakopsora pachyrhizi and the plant-parasitic nematode Heterodera glycines, respectively, are three major yield-limiting problems. Soybean cultivars have a narrow genetic base due to bottlenecks in modern cultivar development. Lack of partially resistant cultivars, in the case of sudden death syndrome, and lack of durable genetic resistance to organisms that have high genetic variability, in the case of soybean rust and cyst nematode, demand efforts to find, understand, and incorporate new sources of resistance into soybean germplasm. The USDA-ARS Soybean Germplasm Collection at the

University of Illinois Urbana-Champaign maintains 20,099 soybean accessions, 10,144 of which have not been evaluated for reaction to F. virguliforme, and 1,212 accessions in 19 perennial

Glycine species that have not been thoroughly investigated for resistance to diseases or pests affecting soybean, including soybean cyst nematode and soybean rust. This study reports new sources of resistance to these pests in G. max and Glycine species for use in ongoing breeding efforts, and provides material for core collections to use in furthering our understanding of the genetic and molecular nature of resistance in soybean and its wild relatives, and their relationship.

ii ACKNOWLEDGEMENTS

I am grateful to my advisor, Dr. Glen Hartman, for giving me the chance to work in the

Hartman Lab and learn about soybean pathology from the ground up, working on an array of projects, and then making it possible for me to complete the degree program. I thank my co- authors, Mr. Jaeyeong Han and Drs. Ram Singh, Leslie Domier and Glen Hartman, for their contributions to the Chapter 3 work and manuscript, which was pre-published; in particular I would like to acknowledge Mr. Jaeyeong Han for his work on the cyst experiment. I would like to thank my Master’s committee members, Drs. Santiago Mideros, Andrew Miller, and Michelle

Wander, for their insights and suggestions on my thesis. I am also thankful to my lab colleague,

Dr. Roger Bowen, for reviewing and providing many helpful comments on Chapter 2, and for teaching me so many details throughout the progression of the greenhouse experiments.

Additionally, I am grateful to current and former Hartman Lab colleagues, including Jim

Haudenshield and Curt Hill, who were two other valuable teachers and role models -- and also great company to work with over the years.

iii TABLE OF CONTENTS

CHAPTER 1: LITERATURE REVIEW ...... 1

CHAPTER 2: EVALUATION OF OVER TEN THOUSAND SOYBEAN (GLYCINE MAX)

PLANT INTRODUCTIONS FOR RESISTANCE TO FUSARIUM VIRGULIFORME ...... 55

CHAPTER 3: EVALUATION OF WILD PERENNIAL GLYCINE SPECIES FOR

RESISTANCE TO SOYBEAN CYST NEMATODE AND SOYBEAN RUST ...... 102

CHAPTER 4: CONCLUSION ...... 126

iv CHAPTER 1: LITERATURE REVIEW

Soybean: world importance of the crop

Background

As a major source of plant proteins and oils, soybean [Glycine max (L.) Merr.] is the leading oilseed crop produced and utilized in the world. Soybeans accounted for 59% of world oilseed production in 2019, far ahead of rapeseed and sunflower which accounted for 12% and

9%, respectively (USDA-ERS 2020b). With approximately 20% oil and 40% protein content, the highest protein production of any crop per acre (Hartman et al. 2011b), soybean is one of the world’s most versatile crops. Seventy percent of the world’s vegetable protein meal consumption and 29% of vegetable oil consumption comes from soybean. Soy protein is considered a complete protein, containing all essential amino acids needed in a human diet, and equal to animal protein sources. Currently, soybean protein meal is primarily used in the production of livestock and aquaculture, with a smaller fraction for direct human consumption.

Uses of soybean include oil for human consumption, protein for animal feeds, aquaculture, and human “soyfoods,” and many industrial and pharmaceuticals uses. The historical and current importance of soybean and some of its major pathogen and pest constraints have been reviewed

(Hartman et al. 2011b).

Soybean production in the USA has expanded from just one farm in 1765 (Hymowitz and

Shurtleff 2005) to 41 of 50 states in 2017, with production across 36 million hectares amounting to 119 million metric tons (MMT) (www.usda.gov). The top producing states were Illinois (14% of USA production), Iowa (13%), and Minnesota (8%), with 11.6 million hectares harvested, or

1 about 25% of the total production in the USA. The top ten producing states were all in the north central region of the USA, producing 83% of the crop on 30 million hectares.

Worldwide, approximately 349 MMT of soybean were produced in 2018

(fao.org/faostat), on 125 million hectares in 98 countries, with 14 countries producing more than

1 MMT each. The USA, Brazil and Argentina led world production in 2018, with 34%, 32% and

10% of total output, respectively. Soybean production is increasing worldwide, with more than a two-fold increase in worldwide production since 2000 (161 MMT). Notably, in the same period, production has increased almost four-fold in lesser developed countries, from 0.36 MMT in 2000 to 1.4 MMT in 2018. USDA-ERS predicts a 20% increase worldwide by 2029 in production and consumption of soybean (ERS 2020a).

Soybean production is expanding because of the increased demand for protein, local economic opportunity, crop diversification, and/or changing climate conditions. Specific examples of expanding soy production include efforts in Canada (www.soycanada.ca) (Saavedra

2019), Africa (Hartman and Murithi 2019; Santos 2019) and Europe (Fogelberg and Recknagel

2017) to advance the crop in those regions and where planted acreage has doubled or even tripled from 2000 to 2018 (www.fao.org). Increased production in less developed countries could be indicative of efforts to increase farm revenue (www.iita.org), improve soil fertility (Popelka et al.

2004) and/or to satisfy demand for dietary protein (Foyer et al. 2019). The latter aligns with a

World Summit on Food Security target of 70% more food (to be produced) by 2050

(http://www.fao.org/wsfs). This goal requires an average annual increase in production of 44

MMT per year to be sustained for 40 years and represents a 38% increase over historical increases in production. Additionally, markets for niche grain soybeans are expanding, including organic grain for both livestock feed in the organic meat industry as well as food grade soybeans

2 for a variety of human foods; consumption of vegetable soybean also continues to increase in the

USA and around the world (Hartman et al. 2016).

Origin of soybean and soybean allies

Cultivated soybean is an annual species belonging to the family Fabaceae, sub-family

Papilionoideae, genus Glycine Willd., subgenus Soja. The genus Glycine comprises the two subgenera, namely Soja (Moench) F.J. Hermann, and Glycine. Subgenus Soja consists of two species, the cultivated soybean, Glycine max (L.) Merr., and its progenitor, G. soja Sieb. & Zucc.

(formerly G. ussuriensis), often called wild soybean, which remains cross-compatible with G. max. Subgenus Glycine currently consists of at least 27 perennial species (Barrett and Barrett

2015), considered wild relatives of soybean (Table 1.1). Indigenous to Australia and various

Pacific islands, perennial Glycine species are morphologically distinct and adapted to diverse agro-climatic conditions and may harbor many genes of economic importance for soybean

(Sherman‐Broyles et al. 2014). However, these species belong to the tertiary gene pool (Harlan and de Wet 1971), are not cross-compatible with G. max, and require the use of advanced techniques for gene transfer. Hybridization can result in hybrid weakness, sterility, seedling lethality and seed inviability (Singh and Hymowitz 1985). Research on relationships among

Glycine species led to creation of seven nuclear genome groups, later expanded to nine

(Hymowitz et al. 1998), based on meiotic chromosome behavior in intra- and interspecific hybrids. Genomic grouping helps predict success of gene transfer of crosses within and among perennial Glycine species. Hwang et al. (2019) compared 100 accession in six perennial Glycine species as well as G. max and G. soja and reported that G. falcata was the most divergent of the six perennial species from G. max, while G. canescens was least divergent while also the species with the most nucleotide diversity. Based upon 76 orthologous gene sets, all perennials except

3 G. tomentella had higher diversity than the G. max and G. soja accessions (Hwang et al. 2019).

A recent study (González-Orozco et al. 2012) mapped hotspots for Glycine diversity in Australia.

As poorly-surveyed geographical areas continue to be explored, especially these recently investigated hotspots, new species will likely continue to be added and characterized (Barrett and

Barrett 2015; Pfeil et al. 2006). And, as plant breeding biotechnology advances (Zaidi et al.

2019; Zhang et al. 2017), the utilization of diversity from perennial Glycine species into soybean will likely become a more successful endeavor.

Investigations into the origin of modern day cultivated soybean are ongoing.

Archeological evidence points to an origin in the Yangtze (Guo et al. 2010) or Yellow River basins in China (Lee et al. 2011) 5000-9000 years ago (Kim et al. 2010). Various studies indicate multiple domestication events (Lee et al. 2011) with points of domestication in Korea and Japan as well. Genetic studies reveal gene flow from wild species G. soja to an interim species G. gracilis and to G. max (Han et al. 2016). For this reason, G. soja is considered the wild progenitor of the current day cultivated soybean, with G. gracilis as the closest semi-wild relative, a transitional species in the evolutionary process of domesticated soybean (Gao and Gao

2017). A review of the genes involved in domestication includes those related to pod shattering; seed hardness; shoot architecture and stem growth habit; photoperiodism; flower, seed coat and pod color; as well as resistance and other traits (Sedivy et al. 2017). A major focus of modern soybean improvement has been on increased yield (Anderson et al. 2019). However, along with increased yield, other traits were selected. New cultivars had later maturity, reduced lodging and plant height, lower seed protein concentration, greater seed oil concentration (Rincker et al.

2014), and showed general improvement in disease resistance (Hartman et al. 2015b).

4 While introducing desired traits, the process of creating a cultivated species decreases genetic diversity, changes allele frequencies, and eliminates or reduces the prevalence of rare genes through the domestication bottleneck. It is reported that 81% of rare alleles (Hyten et al.

2006) were lost during several steps: from G. soja to landraces, selection of landraces, and to the subsequent development of elite cultivars. While the domestication of soybean contributed to

50% loss of diversity, low nucleotide diversity in modern elite soybean cultivars has been attributed to low level of genetic variability in the wild progenitor, G. soja (Hyten et al. 2006).

Furthermore, 95% of genes in elite USA cultivars released from 1947 to 1988 originated from as few as 35 genotypes (Gizlice et al. 1994). Going forward, G. max landraces, the rare alleles lost from G. soja, and the diversity available in many species of Glycine perennials can be valuable sources of genetic diversity for cultivated soybean.

Collections of soybean and soybean allies

Soybean genetic resources are curated in 189 collections around the world which hold

229,944 accessions (FAO 2010). Collections maintain varying number of accessions of wild species, landraces, research materials/breeding lines, advanced cultivars, and material that is an unknown mix of two or more types. As of 2010, the largest collection, containing 14% of all soybean germplasm, is in China (32,021 accessions), followed in size by collections in the USA

(22,490), Taiwan (18,059), Korea (17,644), Brazil (11,800), Japan (11,473), Russia (6,439) and

India (4,022). Aggregated collections in Europe and Africa hold 6,467 and 7,872 accessions, respectively. The largest collection of wild species, 20% of total holdings, is in China, while the

USA collection contains 10% wild species.

More attention is now being paid to increasing genetic diversity within production systems as one way to reduce risk, particularly in light of changing climate, and emerging

5 diseases and pests (Bebber et al. 2013). Whether improving crops genetically through traditional crossing and selection or through the most recent gene transfer techniques, a vital input is availability of genes for the traits needed in new varieties. Toward this end, most countries support some form of public and/or private plant breeding system (NRC 1991). Plant germplasm collections play a hugely important role in this system.

The National Plant Germplasm System (NPGS; www.ars-grin.gov) in the USA is a collaborative effort composed of multiple repositories with varying responsibilities at multiple locations throughout the United States. Established to preserve and protect the genetic diversity of agriculturally important plants, the mission of the NPGS is to support agricultural production by acquiring, conserving, evaluating, documenting, and distributing crop germplasm. The USDA

Soybean Germplasm Collection (SGC), housed at the University of Illinois in Urbana-

Champaign, makes up about four percent of NPGS. Cultivated soybean, Glycine max, comprises the largest part of the SGC (20,099 accessions) (Peregrine 2019). The remainder includes

1,179 wild soybean, G. soja, 1,212 accessions of 19 perennial Glycine species, and a small number of Glycine accessions of unknown species. Eighty-nine percent of the SGC is backed up at the Svalbard Arctic Seed Vault and over 99% is backup up at the USDA National Laboratory for Genetic Resources Preservation in Ft. Collins, CO.

The 20,099 accessions of cultivated soybeans in the SGC include lines that originate from a wide array of geographic locations (Hymowitz 1990). Each accession added to the NPGS is assigned a plant introduction (PI) number, a system in use since 1898, and is categorized by maturity group. There are 13 soybean maturity groups (MG), ranging from 000, 00, 0 and I to X, that correspond to geographic adaptation, based on the effect of day length on flowering.

Cultivars adapted to northernmost latitudes range from MG 000 to 0, those adapted to the USA

6 central states range from MG II to V, and those adapted to the subtropical and tropical zones are

MG IX and X. The entire SGC has been genotyped using the SoySNP50K iSelect BeadChip, containing over 50,000 single nucleotide polymorphisms (SNPs) (Song et al. 2015) and a more extensive 3.7 M SNP dataset created at the Soybean Genetics and Genomics Laboratory at the

University of Missouri was used to create a subset of the SGC, 350 PIs, representing broad genetic diversity in the collection (Pawlowski et al. 2020).

World importance of diseases and pests

From 1996 to 2016, the total estimated economic loss due to soybean diseases in the USA was $95.48 billion (Bandara et al. 2020), with $80.89 billion and $14.59 billion accounting for the northern and southern region losses, respectively. Over the entire time period, the average annual economic loss due to soybean diseases in the USA reached nearly $4.55 billion, with approximately 85% of the losses occurring in the northern USA. FAO estimates that between 20 to 40% of global crop production is lost worldwide to plant pests and diseases annually; plant diseases alone costing the global economy an estimated $220 billion annually, and sometimes resulting in complete crop failure (FAO 2017).

A recent summary of global spread of crop pests and pathogens from 1950 to 2000 found that saturation (number of crop pests and pathogens currently present divided by the number that could occur) has reached 60% in North America, 20% in Asia and Europe, 15% in Latin

America and 10% in Africa (Bebber et al. 2014); furthermore, it was estimated that on average

10% of the major plant pest and disease agents have already infested half of the countries that they could have theoretically infested. This leaves much room for new and emerging disease and pest problems around the world which may increasingly be transmitted long distances through

7 movement of planting materials, trade, travelers as well as through changing climate (Anderson et al. 2004).

Various management strategies are employed to combat the challenges of diseases and pests that threaten crops, whether emerging or established, however the most effective of those is an integrated pest management (IPM) strategy that uses multiple tools. USDA-ARS describes

IPM as a sustainable, science-based, decision-making process that combines biological, cultural, physical, and chemical tools to identify, manage, and reduce risk from pests and pest management tools and strategies in a way that minimizes overall economic, health and environmental risks (USDA-ARS 2018). There are many aspects of an IPM program. Host resistance, the earliest aspect of IPM to be developed (Oerke 2006), remains a first line of defense. Improving crop resistance to pathogens through breeding is an environmentally sound method for managing disease and minimizing losses to crop production (Nelson et al. 2018).

Furthermore, host resistance is most useful in areas with less capacity for other IPM tools, for example where chemical control is logistically or economically out of reach (Popelka et al.

2004).

Improving soybean response to diseases and pests

Efforts to improve soybean through selective breeding in the USA began in the public sector in the 1930’s and have primarily taken place in the private sector since the 1970/80s when costs associated with developing and getting approval of biotechnology traits increased and legal protection for intellectual property expanded (Anderson et al. 2019). Increase in yield was a major priority at the time and soybean yields in the USA have doubled since 1965

(www.nass.usda.gov). As more reports of diseases affecting the crop were made, protecting soybeans from diseases and pests, part of breeding for yield stability as opposed to increase, has

8 also been especially important in breeding efforts. Whether in public or private work, PIs in the

USDA SGC have provided important sources of resistance to many diseases and pests, including soybean cyst nematode (Ross 1957), sudden death syndrome (Hartman et al. 1997; Mueller et al.

2002), and soybean rust (Miles et al. 2006), three important diseases affecting soybean in the

USA and in many other soybean producing countries.

Sudden Death Syndrome

Background and losses

Sudden death syndrome of soybean (SDS) was first observed affecting soybean in the

USA in Arkansas in 1971 (Hirrel 1983; Roy 1997). The disease was discovered in several additional states by 1986 and determined to be caused by the fungus Fusarium solani, later clarified to be Fusarium solani (Mart.) Sacc. f. sp. glycines Roy (Roy 1997; Rupe 1989) and later again renamed Fusarium virguliforme (Aoki et al. 2003). SDS can cause slight to 100% yield losses (Hartman et al. 2015a), with greater losses associated with earlier onset (Gongora-Canul and Leandro 2011b; Navi and Yang 2008; Wang et al. 2019a). Occurrence of SDS has increased steadily since the first report of the disease in the USA and is consistently among the most impactful yield-limiting diseases in any year, with suppression estimated at 1.2 to 2% of total yield from 2010 to 2014 (Allen et al. 2017). The majority of losses reported due to SDS from

2010 to 2014, 76% to 81% of occurrences on average, were recorded in northern states. This is in agreement with long-standing risk assessments based on temperature and moisture which projected that areas in the north central region were the most vulnerable to the disease (Scherm and Yang 1999). Disease related losses to SDS were second to SCN from 2010 to 2014 across

99% of soybean production in the United States, and one province of Canada.

9 Additional Fusarium species have been reported causing SDS, with some association geographically, as reports of the disease have expanded worldwide. Fusarium virguliforme is responsible for the disease in North America and has also been reported in Canada (Anderson and Tenuta 1998), Brazil (Aoki et al. 2005; Aoki et al. 2012), Malaysia (Chehri et al. 2014) and

South Africa (Tewoldemedhin et al. 2015). In addition to F. virguliforme in South America, F. tucumaniae, F. brasiliense, F. cuneirostrum, F. paranaense and F. crassistipitatum also have been reported (Aoki et al. 2003; Aoki et al. 2005; Costa et al. 2016), and F. brasiliense and a novel undescribed Fusarium species (Tewoldemedhin et al. 2017) were reported in South Africa.

F. brasiliense was recently reported in the USA (Wang et al. 2019b). While races of F. virguliforme are not known to occur, isolates have been shown to vary in aggressiveness (Li et al. 2009a). The F. virguliforme genome sequence has been published and putative pathogenicity genes identified toward better understanding of pathogenicity mechanisms of the fungus

(Srivastava et al. 2014).

Life cycle and infection process

F. virguliforme survives for up to a decade or more in the soil as chlamydospores. From season to season, the fungus survives in crop residue and on the cysts of soybean cyst nematode

(SCN) (Hartman et al. 2015a). Many common rotation crops, cover crops, and weeds, including corn, wheat, dry bean, ryegrass, alfalfa, clover, pigweed and lambsquarters (Kolander et al.

2012), can be infected by the fungus and aid in its survival. The fungus can be moved among fields and long distances by equipment, winds and water, and wildlife. Progress in understanding F. virguliforme has been reviewed by Leandro et al. (2012).

The SDS infection cycle in soybean begins with the colonization of the root soon after the radicle emerges from seed under wet and cool conditions. Unfavorable conditions for seed

10 germination and emergence such as low temperature, high precipitation, high soil moisture, and compacted soils, may increase the risk of infection (Gongora-Canul and Leandro 2011a; Scherm et al. 1998). Earlier infection was found to result in greater disease severity, while root rot and foliar symptoms were less severe with increasing soil temperature and with increasing plant age at inoculation (Gongora-Canul and Leandro 2011b).

Colonized roots become necrotic and rot away, reducing the ability of the root to absorb water and nutrients from the soil. Foliar symptoms, most typically interveinal chlorosis and necrosis, result from translocation of fungal toxin, FvTox1 (Brar et al. 2011; Jin et al. 1996) and several others (Abeysekara and Bhattacharyya 2014; Chang et al. 2016), from affected roots upward; the fungus is not culturable from affected foliage (Hartman et al. 2015a). Plants often remain asymptomatic until after flowering, however, at late reproductive phases, increased temperatures promote toxin transport through xylem, causing foliar symptoms. Patches of affected areas in fields turning tan or brown can be identified from a distance (Fig. 1.1). Typical progression of foliar symptoms begins with scattered chlorotic spots which develop into characteristic interveinal chlorosis and necrosis. Symptoms can progress to premature defoliation and, in severe cases, flower and pod abortion, lack of pod fill, and premature plant death. Affected plants are easily removed from the soil due to rotted tap and lateral roots. While pith of infected stems remains white, affected roots and root crown are often discolored reddish brown and bluish masses of spores may be visible on roots. Wang et al. (2019a) found SDS foliar disease severity ratings not associated with quantity of F. virguliforme fungal DNA quantity in roots, suggesting root colonization of the pathogen on non-symptomatic cultivars could be leading to persistence of the pathogen in the field, and possible hidden yield loss.

Various studies have elucidated the process of root infection and disease progress

11 including gene expression in foliar response (Radwan et al. 2011; Swaminathan et al. 2019), defense pathways (Radwan et al. 2013), biochemical responses in roots (Lozovaya et al. 2004;

Lozovaya et al. 2006), and changes in pathogen transcriptomes (Sahu et al. 2017).

Management

Progress in research and management of SDS over the years has been reviewed (Hartman et al. 2015a). Information translated to producers toward controlling the disease includes following practices than ensure overall soybean plant and field health: using high quality vigorous seed, maintaining soil fertility, avoiding compaction, reducing excessive moisture in fields through proper drainage and irrigation (www.unitedsoybean.org); diversification has been reported to reduce soil density of F. virguliforme (Leandro et al. 2018) and long-term rotation is a recommended strategy noting, however, that many cover and rotation crops are susceptible or may harbor the pathogen (Kobayashi-Leonel et al. 2017). Recommendations more specific to limiting SDS include removing debris cleanly from fields, especially corn residue which can harbor F. virguliforme (Navi and Yang 2015) as well as planting early to maintain yields (Kandel et al. 2016a), however avoiding planting fields with known occurrence of SDS in cool, wet soils by planting them last.

In addition to cultural practices, in-furrow or seed treatment fungicides are available to combat the disease, including Adepidyn® (Pydiflumetofen+Azoxystrobin+Propiconazole;

Syngenta) and ILeVO® (fluopyram; BASF); however, while severity was reduced and yield improved with use of fluopyram in some studies (Kandel et al. 2019; Vosberg et al. 2017), foliar severity was not reduced in another (Zaworski 2014). There are no peer reviewed studies available on Adepidyn® used to control SDS in field conditions. Exclusive reliance on these chemical controls is discouraged due to the concerns about the development of fungicide

12 resistance. Nine of 185 F. virguliforme isolates tested were not inhibited more than 50% by fluopyram even at the highest concentrations (Wang et al. 2017). Fungal resistance to fluopyram has been reported in Botrytis affecting strawberry (Amiri et al. 2014), and F. virguliforme fungal

DNA was not reduced in roots in fungicide treatments in 9 of 10 experiments (Kandel et al.

2016b), which could lead to resistant strains. Cost benefit analysis found a benefit of fungicide seed treatment only when disease pressure was high, which is not predictable at planting (Kandel et al. 2018). More environmentally friendly products might be available in the future.

Arbuscular mycorrhizal fungus Rhizophagus intraradices reduced SDS severity and relative F. virguliforme DNA quantities while simultaneously increasing growth and nutrient uptake of plants (Pawlowski and Hartman 2020). Bradyrhizobium japonicum seed treatments reduced

SDS foliar symptoms (Huynh 2019). Trichoderma inhibited F. virguliforme growth and root rot severity (Pimentel et al. 2020) and a biocontrol seed treatment (Heads Up®; Chenopodium quinoa saponins; HeadsUp Plant Protectant, Inc.) has shown effectiveness and low cost at reducing the occurrence of SDS (Navi and Yang 2016; Navi et al. 2010).

Genetic resistance

Host resistance is a fundamental part of efforts to limiting yield loss to SDS, and cultivar selection is a recommended measure to manage SDS. A meta-analysis of 52 field experiments across six USA states and Ontario, Canada reported a 0.5% decrease in yield per unit increase in foliar disease severity, that resistant cultivars had lower foliar disease and produced higher yields, and that yield loss occurred even when SDS foliar severity was low (Kandel et al. 2020).

Other studies indicated the importance of using resistant cultivars showing yield decreases of up to 7% when disease index increased 10% (Chong et al. 2005) and that an SDS-resistant cultivar can yield 36% more than an SDS-susceptible cultivar (Brzostowski et al. 2014). Plant resistance

13 provided an overall better yield-advantage than using a seed treatment alone (Kandel et al.

2016b).

The search for genetic resistance to SDS in soybean germplasm accessions began in the

1990’s (Chang et al. 1996; Hartman et al. 1997; Hnetkovsky et al. 1996; Mueller et al. 2002;

Mueller et al. 2003; Rupe et al. 1991; Stephens et al. 1993) was recently reviewed by Hartman et al. (2015a). Public cultivars like Forrest and Ripley and plant introductions including PI 520733,

567374, 567315, 567441C, 567650B, and 567664 were reported to have resistance. These sources have been utilized by breeding programs (Cianzio et al. 2014; Cianzio et al. 2016; de

Farias Neto et al. 2007; Luckew et al. 2013).

Genetic resistance to F. virguliforme is partial and complex, with resistance encoded by a large number of quantitative trait loci (QTL) each contributing only a small amount toward expression of resistance. Chang et al. (2018) reviewed research progress in genetic mapping of resistance to F. virguliforme in soybean, including discovery of more than 80 QTL and dozens of single nucleotide polymorphisms (SNPs) associated with soybean resistance to SDS. QTL associated with foliar and root resistance (Kazi et al. 2008; Luckew et al. 2013; Tan et al. 2019) have been reported.

Breeding efforts and the use of plant genomic resources to aid breeding selection for resistance to SDS in two areas, resistance to foliar phytotoxins and root resistance to pathogen invasion, colonization and rot, have been reviewed (Lightfoot 2015). Another study (Chang et al. 2019) reported resistance due to loss of susceptibility associated with STAY-GREEN genes, a new group of R genes based on loss-of-susceptibility mechanism. Two soybean STAY-GREEN genes were found to be associated with development of chlorosis, and resistance to SDS foliar chlorosis was attributed to a double mutation.

14 Additional knowledge on the genetic resources available to breeders of soybeans for a variety of uses and in differing geographic regions will be helpful and can be gained by evaluating PIs in the SGC that have not been included in previous screening efforts. Due to variation in photosensitive flowering response, using correct MG for the geographical area has been correlated with increased yield (Li et al. 2020). SDS continues to spread and today occurs widely in USA and in other major world soybean growing areas including Brazil and Argentina.

Because of the potentially devastating losses that the disease can inflict, ongoing and improved methods of control continue to be a high priority for soybean pathologists and breeders. Most germplasm accessions previously evaluated for resistance to SDS were in maturity groups II-IV and multiple sources of resistance obtained from a variety of MGs will be helpful in the development of resistant cultivars for various uses or geographic regions. Thus, it is proposed to evaluate over 10,000 lines in the USDA SGC not previously tested against F. virguliforme, and provide an expanded set of sources of resistance for breeders and pathologists to use in breeding programs and/or in advanced phenotyping programs, as well as for biologists who continue to study the host-pathogen interaction.

Soybean Cyst Nematode

Origin

Soybean cyst nematode (SCN), Heterodera glycines Ichinohe, was officially described in

1952 on soybean in Hokkaido, Japan (Ichinohe 1952), but historical reports of its likely occurrence observed as circular patches of chlorotic and stunted soybeans called “moon night” or

“yellow dwarf” were made in Japan and China in the early 1900s (Liu et al. 1997). SCN was first reported in the USA in 1954 (Winstead et al. 1955) and, while it is generally thought the

15 organism was introduced with seed stock or in soil imported for Bradyrhizobium japonicum inoculum (Noel 1986), some have proposed SCN might be indigenous to the USA (Davis and

Tylka 2000). In either case, SCN has now been reported throughout the USA as well as in all major soybean producing regions of the world, including Brazil (Mendes and Dickson 1993) and

Argentina (Dias et al. 1998) and across South America (Doucet et al. 2008). Occurrence is known in Egypt, Indonesia, Iran, Italy, Korea, and the former Soviet Union (CABI; www.plantwise.org) but, notably, SCN has not been reported in Africa (Fourie et al. 2015) other than the first occurrence in Egypt in 1968 (Riggs et al. 1977).

Background and losses

SCN is described as the most economically destructive pest of soybean in the USA and is known to be problematic in soybean production around the world. In the United States, SCN was estimated to cause more yield losses (14 MMT) than any other disease from 2006 to 2009,

(Koenning and Wrather 2010) and, from 2010 to 2014, in a survey that included 99% of USA soybean producing area and one Canadian province, SCN was estimated to have caused more than twice as much yield loss than any other disease (Allen et al. 2017). Though quantitative, standardized information on crop losses is difficult to compile and compare across crops, agroecosystems and regions worldwide, SCN was determined to be the top pest of soybean on a global scale (Savary et al. 2019).

Signs and symptoms

SCN can infect other hosts, including 399 species in 23 genera (out of 1,152 species tested in the Leguminosae) (Riggs and Hamblen 1962, 1966) and including weeds in the

Brassicaceae and Lamiaceae that may play a role in SCN reproduction in infested fields when soybean plants are absent (Venkatesh et al. 2000). Symptoms of SCN on soybean include slight

16 to severe stunting and chlorosis of plants that often occurs in circular to oblate patches in the field. However, visible symptoms may not be apparent or may be attributed to other causes, leading to non‐detection of the nematode for several years while its population builds up; more than 30% yield loss due to SCN can occur without above ground symptoms (Wang et al. 2003).

Upon further examination however, infected plants are often identified by roots that are parasitized by lemon-shaped “cysts,” swollen egg-filled female nematodes, which are visible to the naked eye can be also found abundantly in affected soils (Fig. 1.2). In addition, SCN can provide opportunities for other soybean pathogens and pests and synergistically can cause even greater yield losses (Bandara et al. 2020; Hartman et al. 2015a), which makes it even more imperative to understand, identify, and manage this pest.

Infection process and life cycle

SCN has three life stages (Davis and Tylka 2000): egg, juvenile (J), and adult. The J2 is a soil motile vermiform stage and the infective form that is attracted to soybean roots by exudates after hatching. After migrating to and penetrating the root using a needle-like stylet, the J2 uses enzymes to degrade cells and move into vascular tissue, where it modifies plant cells to form a feeding site called a syncytium. After enlarging and molting to the J4 stage, about half of juveniles become female and half become male, and both adult forms exit roots. Males exit completely, are motile and vermiform, and fertilize adult females that have exited from roots except for their heads. The female, after developing eggs and swelling to the characteristic lemon shape, may release some eggs, but retains 200-600 in a hardened structure (cyst), ranging from 500 to 900 µm long and 200 to 700 µm wide. Females turn from white to yellow and, finally, brown as they die. Mature egg-filled cysts can survive in the soil for years and can be transferred short distances by cultural practices including cultivation, and long distances by farm

17 machinery, winds, water, and wildlife and in contaminated seed stocks; SCN is not carried in or on seeds themselves. SCN is a pest in temperate areas and does not develop below 15°C or above 33°C. Once introduced, the populations of the nematode can rapidly increase via a 24- to

30-day life cycle and can complete 2-6 generations per growing season depending on local conditions.

Characterization

As a result of sexual reproduction, SCN is a pathogen with a high degree of genetic diversity. To characterize populations, a race system was created (Golden et al. 1970) using four differential lines to compare female development. The system was revised using seven indicator lines and was in use until 2002 when a new system to classify populations according to “HG”

(Heterodera glycines) “types” was proposed (Niblack et al. 2002). The HG type number for any

SCN population refers to the indicator line or lines (1 to 7) on which that population reproduces, female index (FI) is greater than or equal to 10%; a population with FI of less than 10% on any indicator line is designated as HG Type 0. Female index is computed as follows: (mean number of females on a test soybean line) / (mean number of females on the standard susceptible) × 100.

So, for example, HG Type 1.2.3 reproduces on indicator lines, 1, 2, and 3, meaning that the female index was greater than or equal to 10% on each of those three indicator lines. While HG type classification is now the standard in the scientific research community, race-scheme classification is still commonly found in seed company-to-producer communication.

Management

Current mainstream recommendations for SCN control include using rotation, resistant varieties, and nematicides (chemical or biological) (www.unitedsoybean.org). While organisms used in biologics have proven efficacious in laboratory and/or small plot trials, there is currently

18 a lack of independent data showing product efficacy under field conditions and a lack of understanding on impacts of biological control products on complex soil fungal communities; overall there has not been significant broad-scale commercial success of biologicals against nematodes (Haarith et al. 2019; Haarith et al. 2020; Wilson and Jackson 2013). Because chemical control could be economically costly and environmentally harmful, while also having limited effectiveness (Beeman et al. 2019), by far the most commonly used management strategies are crop rotation and host resistance.

Recent studies on crops used as non-hosts has confirmed previous studies (Riggs and

Hamblen 1962, 1966) that most red clovers (Trifolium spp.) and peas (Pisum sativum L.) do not allow SCN population increase: 28 leguminous and non-leguminous cover crops species were classified as non-hosts or poor hosts (Acharya et al. 2020; Kobayashi-Leonel et al. 2017); rye and rapeseed decreased SCN levels in the soil (Wen 2013). However, often commonly rotated with soybean, corn was among the least effective in reducing nematode populations compared to leguminous non-hosts or poor hosts (Miller et al. 2006) and host compatibility could vary by cultivar within cover crop species (Acharya et al. 2020).

Host resistance

Efforts to develop soybean host resistance have been widely reviewed (Concibido et al.

2004; Klink and Matthews 2009; Mitchum 2016; Noel 1986; Roberts 1992; Yan and Baidoo

2018). Over 118 sources of soybean resistance to SCN have been identified, however, only a few of these sources are used for commercial development in the United States (Shannon et al.

2004). The most commonly used source of resistance is PI 88788 (Mitchum 2016). Other sources include PI 548402 (Peking), 907643, 437654 and 209332.

19 SCN depends on the formation of a feeding site (syncytium), the only source of nutrients during parasitism, in order to complete its life cycle. In all resistant cultivars, the infective juveniles are capable of penetrating into roots and can induce the formation of syncytia, but the syncytia become necrotic soon after establishment and the nematodes starve to death (Kandoth et al. 2011). Two types of SCN resistance in soybean have been established, namely, PI 88788-type resistance and Peking-type resistance (Yan and Baidoo 2018). Both types of resistance are mediated by two major QTL loci carrying the genes Rhg1 and Rhg4. Genes and pathways that are up- and down-regulated in roots and syncytia during the interaction of soybean with SCN have been identified (Klink and Matthews 2009). In Peking-type resistance, there is a rapid and potent localized hypersensitive response that affects SCN J2, whereas in PI 88788-type resistance, the resistance response is more prolonged, and affects the SCN third-and fourth-stage juvenile (Mitchum 2016).

Advancing molecular and biochemical studies are shedding more light on the nature of

SCN resistance in soybean, which is a highly complex defense response, by examining both resistance and susceptibility genes, gene expression in both roots and in the syncytium, as well as changes in the SCN transcriptome (Klink and Matthews 2009). For example, root penetration was found to be similar in susceptible and resistant near isogenic (NIL) lines, while growth, development, and fecundity of nematode females was suppressed in NIL-R (Li et al. 2004).

Kandoth et al. (2011) reported stress- and defense-related genes associated with Rhg1-mediated resistance and Bayless et al. (2016) reported that a dysfunctional variant of an essential gene in the Rhg1 locus also contributed to the demise of the feeding site. Alleles of Rhg4 conferring resistance or susceptibility were found to differ by two genetic polymorphisms that alter a key regulatory property of the enzyme in the folate pathway (serine hydroxymethyltransferase);

20 disruption of the folate pathway may lead to a nutritional deficiency that starves the nematode

(Liu et al. 2012). Many genes involved in ethylene, protein degradation, and phenylpropanoid pathways were also revealed differentially regulated in two resistant soybean lines showed distinctive gene expression profiles from each other and from a susceptible cultivar in response to the SCN inoculation as well as in the absence of SCN; elements thought to be involved in defense-response regulation were observed for the first time Wan et al. 2015). A transcriptome analysis of nonhost vs. susceptible response in cultivar Lee detected genes intrinsic to membrane, cell periphery and plasma membrane much more enriched in the resistant reaction compared to the susceptible (Song et al. 2019).

Continuous use of cultivars derived from a single genetic source of resistance can cause the SCN population to evolve to overcome host resistance. Earlier studies showed SCN changed in virulence and pathotypes were developed when challenged by soybean lines with different resistance genes (Riggs et al. 1977; Triantaphyllou 1975); an SCN field population was divided into subpopulations compatible with sources of resistance the populations were harvested from, and less compatible on cultivars with other sources of resistance (Young 1984). Thus, a rotation scheme would involve for example: a nonhost crop, followed by ‘PI88788'-type resistant soybean, a nonhost crop, 'Peking'-type resistant soybean, a nonhost crop, and a high-yielding though susceptible (tolerant) soybean (Tylka 1997). It is estimated that over 90% of soybean lines use PI 88788 as a single source of resistance (Niblack 2005). Several studies have shown that some soybean resistant cultivars are not showing complete effectiveness against the SCN

HG types (Acharya et al. 2016; Niblack 2005). Not just an issue in the USA, the genetic basis of the resistance found in Brazilian soybean cultivars, which derive from North American cultivars, is also relatively narrow (Godoy et al. 2016).

21 There is an increasing need to find new sources of resistance, to broaden the resistance background in soybean as well as to aid in the understanding of resistance. Screening of the

USDA core collection of common bean (Phaseolus vulgaris) germplasm identified resistant genotypes that, notably, did not allow SCN increase over successive generations (Pormarto et al.

2011); SNPs in common bean (Phaseolus) associated with resistance to two SCN HG types were later reported (Wen 2017). Additionally, researchers are looking more and more into crop relatives for resistant germplasm and potential novel mechanisms of resistance. Investigations into resistance reported in G. soja, suggested that the underlying genes may differ from those at

Rhg1 and Rhg4 (Wang et al. 2001) and two G. soja QTL alleles significantly enhanced the resistance derived from PI 88788 (Kim et al. 2011). Ten SNPs and candidate genes were identified (Zhang et al. 2016; Zhang et al. 2017). There have been several large evaluations of accessions of perennial wild Glycine species for resistance to SCN. Riggs et al. (1998) reported that 12 accessions from nine perennial Glycine species were moderately resistance to resistant to four races of H. glycines. Bauer et al. (2007) reported that 56% of 491 accessions representing 12 perennial Glycine species were highly resistant or immune to HG Type 0. Wen et al. (2017b) reported high levels of resistance including 16 Glycine accessions to HG Type 1.2.3.4.5.6.7 out of 282 perennial accessions from 13 species evaluated, including broad resistance (against three

HG types) in G. tomentella, G. argyrea and G. pescadrensis and with a number of accessions not allowing any SCN reproduction. Further investigations into Glycine perennial species will identify accessions with potential of transferring unique resistance genes to soybean, as well as contribute to a panel of accessions for further investigations of the nature of resistance in soybean and other legume species to SCN.

22 Soybean Rust

Origin and spread

The history of soybean rust (SBR) is as long as modern soybean cultivation. SBR is caused by the obligate biotrophic fungus, Phakopsora pachyrhizi Syd. Its discovery and occurrence have been reviewed over the years (Bromfield 1984; Childs et al. 2018). The organism was first described causing disease on soybean in 1902 in Japan and received its current name in 1913 after being found occurring on jicama (Pachyrhizus erosus L. Urban) in Taiwan. After the first report of SBR in Australia in 1934, the disease was successively reported throughout East Asia

(Japan, Taiwan, Thailand, Indonesia, Philippines, China, Indonesia) and India, becoming an economically important disease in those areas in ensuing years (Bromfield 1984). The first official report of SBR caused by P. pachyrhizi in Africa was in the 1990s and the pathogen gradually spread across the continent (Levy 2005; Murithi et al. 2017). Reports of P. pachyrhizi in the Americas (Central America, the Caribbean and Puerto Rico) were made in the early 1900s and later in the 1970’s (Bromfield 1979; Vakili and Bromfield 1976), these occurrences were most likely caused by P. meibomiae, a less virulent species with a smaller geographic distribution (Frederick et al. 2002; Goellner et al. 2010) and which can only be distinguished morphologically from P. pachyrhizi by differences in telia (Ono et al. 1992); uredinial forms are identical (Bonde and Brown 1980). Occurrence of SBR in the western hemisphere caused by P. pachyrhizi began in Hawaii in 1994 (Killgore and Heu 1994), followed by Paraguay in 2001

(Yorinori et al. 2005), Brazil and Argentina in 2002, Bolivia and Colombia in 2004 (Rossi 2003;

Yorinori et al. 2005) and, from there, likely on Hurricane Ivan, to the continental USA

(Louisiana) in 2004 (Schneider et al. 2005) as well. Today SBR is known to affect most soybean growing regions worldwide.

23 The discovery of SBR in the western hemisphere, and the imminent threat it posed to the

70 MMT of soybeans produced in the USA at that time, sparked a flurry of research and extension activity that had wide-reaching consequences that went beyond the context of SBR alone. It was reported that a significantly greater mean loss was observed to diseases in general in the USA after the discovery of SBR (2004 to 2016) compared to the pre-discovery period

(1996 to 2003), however the increase was not found to be due to losses caused by SBR but rather all diseases in general (Bandara et al. 2020). Thus, the arrival of SBR in the USA, and the widespread and coordinated activities that came with it to rapidly understand the biology, ecology, epidemiology, management of an important pathogen and disease of soybean, resulted in increased scouting and prediction systems, improved education and carefully implemented management practices, as well as improved identification techniques. Together this resulted in an increased awareness of, detection of and better identification of soybean diseases in the USA, as well as an upward trend of foliar fungicide use in soybean and other field crops (Bandara et al.

2020; Hershman et al. 2011; Sikora et al. 2014). A nationwide monitoring system, Soybean

Rust-Pest Information Platform for Extension and Education or SBR-PIPE (Isard et al. 2007;

Isard et al. 2006a), was established in the USA for detection of rust outbreaks. This platform is an example of effective disease monitoring and communication with stake holders, and has been expanded beyond rust to share data on other issues affecting soybean (occurrence of QoI- fungicide-resistant isolates of Cercospora sojina Hara, causal organism of frogeye leaf spot of soybean) as well as information on other crops, including corn, cucurbits, legumes, and pecans

(Sikora et al. 2014). Overall, SBR remains one of the most important threats to soybean production worldwide (Fones et al. 2020; Hartman et al. 2011b). The disease has been reported

24 in 20 USA states by the end of 2009 (Li et al. 2010) and remains a threat to southern states

(Allen et al. 2014), as well as to wider USA regions based on a perfect storm of circumstances.

Background and losses

SBR reduces seed size, seed weight, oil content, and total yield (Bromfield 1984). In

2019, it was estimated that the disease caused 4% losses to soybean yield globally (Savary et al.

2019). A previous report estimated global losses at over 13 MMT in 2006, approximately 6% of production that year (Wrather et al. 2010). Most severely affected areas, with losses averaging approximately 6% but as great as 50-100%, were in South America and Africa (Savary et al.

2019). The greatest part of losses in Brazil and China in 2006 was attributed to SBR, 4.7 and 6.4

MMT, respectively, and the disease was one of the worst affecting the soybean crop in India,

Bolivia, Brazil, and Paraguay. SBR is a major yield limiting constraint in Africa, where the demand for the crop outpaces the supply (Kawuki et al. 2003; Murithi et al. 2016). Although rust was among the least economically damaging diseases in the USA in recent decades, losses were noted in Alabama, Florida, Georgia, Louisiana, and Texas (Bandara et al. 2020) where geographical and environmental conditions are most favorable to development of the disease.

Numerous reviews are available on the biology, effect, and management of SBR across regions strongly impacted by the disease (Childs et al. 2018; Godoy et al. 2016; Goellner et al. 2010;

Hartman et al. 2005; Ivancovich 2005; Kawuki et al. 2003; Kelly et al. 2015; Li et al. 2010;

Murithi et al. 2017; Sharma and Gupta 2006; Yorinori et al. 2005).

Life cycle and infection of soybean

P. pachyrhizi is a microcyclic, biotrophic basidiomycete that lacks basidial, pycnial, and aecial states, thus producing only uredinia and telia. An alternate host is currently not known.

Teliospores have been infrequently observed (Carmona et al. 2005; Harmon et al. 2006; Yeh et

25 al. 1981) and basidiospores have been observed only in laboratory conditions (Saksirirat and

Hoppe 1991). The most commonly visible sign of infection (Fig. 1.3) by far is the appearance of uredinia which, depending on cultivar and environmental conditions, often produce copious urediniospores (Hartman et al. 2015a; Rupe and Sconyers 2008). Urediniospores are asexual

“repeating spores” which cause polycyclic infection throughout the season and can be transported short and long distances by wind. The infection process begins when urediniospores land on susceptible leaflets and, under optimal environmental conditions (wet leaves and temperatures between 16°C to 28°C) germinate within 6 to 12 hours. Germ tubes develop, followed by appressoria which penetrate epidermal cells and form a specialized feeding structure called a haustorium (Vittal et al. 2012). Uredinia develop 7 to 14 days after infection, mostly on the abaxial leaf surfaces, and in turn produce more urediniospores. Due to this short life cycle and under the right conditions, SBR epidemics can quickly build up from barely detectable to very high levels. Because of the obligate nature of the pathogen, the life cycle is interrupted by crop maturity or seasonal dieback. In areas with mild winters, alternative hosts (species on which the fungus sporulates and produces viable spores) can maintain the pathogen until the next growing season. Currently over 150 species in 25 genera are known as hosts for P. pachyrhizi

(Ono et al. 1992; Rytter et al. 1984; Slaminko et al. 2008). In the USA, for example, P. pachyrhizi overwinters in frost-free areas in the south, mainly on the introduced and invasive legume kudzu (Pueraria montana var. lobata) (Pivonia and Yang 2004), which is widely distributed in the area. Conditions in much of Brazil allow year-round survival of the pathogen

(Li et al. 2010; Yorinori et al. 2005) with severe outbreaks developing if conditions are ideal and if fungicides are not applied in a timely manner. Studies on spore germination, infection, latent period, lesion expansion, sporulation, and senescence of uredinia in response to host and

26 environmental variation (Marchetti et al. 1976; Marchetti et al. 1975; Melching et al. 1989;

Twizeyimana and Hartman 2010), as well as atmospheric weather and aerobiological modeling of distant (Isard et al. 2005; Isard et al. 2007; Li et al. 2009b; Pan et al. 2006; Pivonia and Yang

2004; Pivonia et al. 2005; Yang et al. 1991) and local spread (Wen et al. 2017a), have been conducted to understand the survival and dispersal of the pathogen and to predict occurrence of disease epidemics and their economic impact (Kuchler et al. 1984; Livingston et al. 2004).

Frequent rain events, long dew periods, temperatures ranging from 15°C to 29°C and overcast conditions (Dias 2008; Isard et al. 2006b; Koch and Hoppe 1987) are considered ideal conditions for disease development and long-distance transport of inoculum is enabled by storm systems, including hurricanes.

Signs and symptoms

The sign of rust infection is the appearance of tiny lesions on the upper leaf surface which, upon closer inspection, reveal the formation of pustules, or uredinia, on the lower leaf surfaces. Lesions tend to be angular, bounded by leaf veins, but they can also appear on petioles, pods and stems (Hartman et al. 2015a). Within each lesion, zero to numerous uredinia form and produce ellipsoid urediniospores that are colorless to pale yellow and can darken to brownish with age. Lesions and uredinia vary in appearance according to host compatibility, as does spore production, though the latter is also dependent on conditions. Three infection types have been described (Bromfield 1984). In general light- or tan-colored lesions (TAN) produce prolifically sporulating pustules and are associated with complete compatibility, whereas “RB” or red brown lesions appear in a partially resistant response, and are dark brown or reddish-brown, producing few, if any, pustules. Partially resistant reactions associated with RB lesions may have longer latent periods and lower rates of increase in pustule number over time (Hartman et al. 2011a),

27 however RB lesions have been observed to produce as many urediniospores as the TAN lesions

(Bonde et al. 2006). Finally, complete resistance is identified by an immune (IM) response which is an incompatible interaction producing no visible necrosis or development of fungal reproductive structures. RB and IM reactions may both involve a hypersensitive response (HR) involving programmed cell death upon detection of the pathogen. While soybean response to rust infection is typically characterized by the lesion type produced on soybean, alternative hosts may show more variability of lesion and pustule appearance (Burdon and Speer 1984; Slaminko et al. 2008). Susceptible genotypes on any host can produce large numbers of spores which can spread through the canopy causing chlorosis of foliage, premature defoliation and early maturation of pods, leading to decreased yield. Severe outbreaks can defoliate fields in a few days and cause complete crop loss (Burdon and Speer 1984).

Management

There are three basic management tactics for reducing SBR epidemics: fungicides, genetic resistance, and cultural practices. Cultural practices include planting early and/or planting early-maturing cultivars that evade rust epidemics, as well as the implementation of

“free host” periods enforced in Brazil to interrupt production of inoculum and delay epidemic onset in the next season. However, controlling SBR relies heavily on fungicides (Juliatti et al.

2017), including chlorothalonil and strobilurin (quinone outside inhibitor; QoI) fungicides, which act as protectants, and triazoles which can kill the fungus in the plant and prevent fungal reproduction, or a mixture of products. Mode of action as well as number and timing of application is important (Chechi et al. 2019; Chechi et al. 2020; Miles et al. 2003a; Miles et al.

2003b; Mueller et al. 2009; Scherm et al. 2009; Sikora et al. 2009; Yorinori et al. 2005) both for efficacy against disease and minimizing environmental impact (Ochoa-Acuña et al. 2009). Thus,

28 timely knowledge of the presence of the pathogen is also key to fungicide application and monitoring networks such as SBR-PIPE in the USA or “Sistema de Alerta” in Brazil, and/or local scouting done by producers in their fields, are critical components of disease management.

(Godoy et al. 2016; Kelly et al. 2015; Sikora et al. 2014).

Despite crucial benefits, fungicide use incurs economic and environmental costs.

Brazilian growers spent an estimated US $2.2 billion on fungicides in 2013-2014. However, there are reports of resistant pathogen strains to commonly used products (Godoy et al. 2016) and of fungicidal active ingredients leaving the target area during the first rain event following application and persisting in soil for long periods (Edwards et al. 2016; Spradley 2005).

Fungicides used to combat SBR have been found to disturb the ecological balance of aquatic ecosystems and to create distinct ecological risks (Lu et al. 2019), as well as to affect the microbiome of soybean plants and seeds, which might adversely impact seed quality (Batzer and

Mueller 2020). Another issue with fungicides for control of rust is that they are not always available, for example, in low input systems in Africa (Murithi et al. 2016).

Genetic resistance to P. pachyrhizi in soybean

Development of commercial soybean cultivars with resistance to P. pachyrhizi may be a more cost effective and environmentally friendly method of reducing yield losses (Hartman et al.

2005); a recent modeling study found that use of SBR-resistant cultivars can reduce the cost of controlling SBR by approximately half, and is essential for sustainable soybean production and a stable global soybean market (Ishiwata and Furuya 2020). The discovery of P. pachyrhizi resistance genes (Rpp) in soybean has been reviewed (Chander et al. 2019; Childs et al. 2018;

Goellner et al. 2010; Langenbach et al. 2016; Rosa et al. 2015). Since 1980, single genes mapping to at least seven independent loci have been reported in numerous plant introductions.

29 These Rpp genes mostly follow the gene-for-gene model between host and pathogen where a qualitative resistance response is triggered in the plant with an Rpp gene complementing the pathogen Avr gene (Lefebvre et al. 2020). Quantitative reactions indicative of tolerance have also been noted in genotypes with yield stability while producing TAN reactions (Bromfield

1984; Kawuki et al. 2004; Oliveira et al. 2005; Oloka et al. 2009; Pereira et al. 2018) or producing TAN reactions with reduced chlorosis around lesions when severely infected

(Yamanaka et al. 2010). However, single gene resistance in soybean is pathotype specific

(Hartman et al. 2005) and there are no sources of resistance that confer resistance to all populations of P. pachyrhizi (Bonde et al. 2006; Murithi et al. 2017; Paul and Hartman 2009;

Pham et al. 2009).

Pathogen diversity and characterization

Many studies have reported on the diversity of P. pachyrhizi populations, varying in virulence (ability of the pathogen ability to overcome resistance genes) and aggressiveness

(degree of damage or multiplication) (Akamatsu et al. 2013; Bonde et al. 2006; Burdon and

Speer 1984; Lawrence et al. 1989; Lin 1966; Murithi et al. 2017; Paul et al. 2013; Pham et al.

2009; Twizeyimana et al. 2009; Yamanaka et al. 2010; Yamaoka et al. 2014). Isolates have been characterized by testing on a set of differential genotypes to observe reaction time as well as latent period (number of days after inoculation to first appearance of lesions), number of uredinia, and sporulation (the number of lesions and sporulating uredinia per square centimeter of leaf tissue, and the number of uredinia per lesion) (Murithi et al. 2017; Twizeyimana and

Hartman 2012). Other studies have used DNA sequencing to understand diversity (Akamatsu et al. 2017; Darben et al. 2020; Freire et al. 2008; Jorge et al. 2015; Twizeyimana et al. 2011;

Zhang et al. 2012).

30 In absence of the sexual stage, various explanations based on pathogen biology, host range and mode of dispersal have been offered to account for variability of P. pachyrhizi.

Anastomosis has been observed in germ tube formation may lead to genetic recombination

(Manners and Bampton 1957; Vittal et al. 2012) and changes in virulence. The broad range of hosts infected by the pathogen might contribute to the development of these differences.

However, while isolates of P. pachyrhizi collected from various countries have been reported to differ in virulence based on reactions on differential hosts (Bonde et al. 2006; Miles et al. 2006;

Pham et al. 2009), a subsequent study found greater diversity (>90%) within field populations than among isolates from different fields (approximately 6%) (Twizeyimana et al. 2011).

Further studies similarly found greater variation within a location, and concluded that wide dispersal and mixing of inoculum by wind currents created variation in a particular local area

(Jorge et al. 2015; Lourdes Rocha et al. 2015). Finally, a distribution map of Glycine perennial populations possessing qualitative resistance to P. pachyrhizi showed no clear geographic patterns in the occurrence of resistance (Burdon and Marshall 1981a), indicating exposure to isolates of diverse virulence.

The diversity of P. pachyrhizi presents challenges to the development of durable resistance. Several studies have reviewed future directions that may include one or a combination of technologies including conventional breeding for SBR resistance, use of host and non-host resistance, race or non-race specific resistance, transgenic approaches including gene pyramiding or discovery and silencing of “S” genes (genes associated with susceptibility), as well as exploitation of transcription factors, secondary metabolites, and antimicrobial peptides,

RNAi/HIGS, biocontrol strategies (Chander et al. 2019; Langenbach et al. 2016; Popelka et al.

2004). Legume species related to soybean such as pigeonpea, cowpea, common bean and others

31 could provide a valuable and diverse pool of resistance traits and the cloning of a P. pachyrhizi resistance gene CcRpp1 that confers full resistance to P. pachyrhizi in soybean has been reported

(Kawashima et al. 2016). However, species more closely related to G. max, namely Glycine perennial wild relatives are also of interest.

Glycine species and resistance to SBR

Viewing wild relatives of crops as “treasure troves” for tolerance to biotic and abiotic stresses is currently a topic of much interest (Mammadov et al. 2018), but similar ideas were already of interest in the 1970’s that “there is a good possibility that they possess variation in characteristics of economic value which is missing in the cultivated germplasm, e.g., pest and disease resistance” (Ladizinsky et al. 1979). Screening for resistance in Glycine perennial species to SBR that began shortly thereafter found several species, G. canescens, G. clandestina,

G. tabacina and G. tomentella, to have high levels of resistance, while G. falcata and G. latrobeana showed no resistance. Similar to patterns seen in studies of G. max and P. pachyrhizi today, resistance was both qualitative and quantitative and variability in pathogen virulence and aggressiveness on test accessions was observed (Burdon and Marshall 1981a, b). Race-specific and non-specific resistance was reported along with repeated observation of different virulence combinations amongst the eight pathogen isolates (Burdon and Speer 1984). These initial studies led to the discovery of a minimum of 10 and 12 resistance genes in two populations of G. canescens, with 78% of one population showing resistance, and with resistance reported to be conditioned by single dominant genes at four distinct loci with major phenotypic effects and confirmed that race specific resistance characterized by simply inherited, dominant genes with major phenotypic effects is relatively common in non-agricultural plant-pathogen interactions

(Burdon 1987, 1988). Next, resistance was reported in a population of G. argyrea (Jarosz and

32 Burdon 1990), in six species, two of them new reports (G. latifolia and G. microphylla), while G. arenaria, G. cyrtoloba, G. curvata, and G. falcata showed no resistance (Hartman et al. 1992).

Additional studies confirmed resistance in G. tomentella (Patzoldt et al. 2007; Schoen et al.

1992).

Intra- and interspecific variation was initiated in the early 1970’s and, until recently, were unsuccessful (Ladizinsky et al. 1979). First successes were via in vitro ovule culture sterile hybrids plants (Broué et al. 1982; Newell and Hymowitz 1982). Subsequent efforts struggled with poor crossability, pod abortion, and absence of chromosome pairing (Singh and Hymowitz

1987), the first report of the successful development of new alloplasmic soybean lines with cytoplasm from G. tomentella was made (Singh and Nelson 2014). In recent years, wide hybridization in the genus Glycine demonstrated that selected derived fertile lines do not inherit undesirable traits from the Glycine spp., such as stem vining, stem lodging, lack of complete leaf abscission and seed shattering (Singh 2019). Derived lines from G. max ‘Dwight’ x PI 441001

(G. tomentella) and PI 441001 x ‘Dwight’ show that SBR resistance form PI 441001 to ‘Dwight’ was introgressed (Singh and Nelson 2015).

Undiscovered resistance to SDS, SCN and SRB in Glycine max and related species

Occurrence of diseases and pests affecting soybean have increased as production of the crop has expanded from its origin in China, throughout Asia, Africa, and North and South

America. SDS of soybean, SBR, and infection by nematodes, caused by fungal pathogens, F. virguliforme and P. pachyrhizi, and the plant-parasitic nematode, H. glycines, respectively, are three major yield-limiting problems, all of which have potential to be curtailed. Host resistance is the most sustainable and environmentally-friendly method of reducing crop damage to disease.

33 Soybean seed varieties available to producers have a narrow genetic base due to bottlenecks in the development of modern cultivars. Lack of partially resistant cultivars, in the case of SDS, and lack of durable genetic resistance to organisms that have high genetic variability, in the case of SBR and cyst nematode, demand efforts to find, understand, and incorporate new sources of resistance into soybean germplasm. This process begins with evaluating G. max accessions available in curated soybean collections around the world, as well as by investigating accessions in the soybean wild relatives, including Glycine perennial species, as crop wild relatives are being investigated more and more for their genetic diversity to utilize in cultivated crops. The

USDA-ARS Soybean Germplasm Collection at the University of Illinois Urbana-Champaign maintains 20,099 soybean accessions, 10,144 of which have not been evaluated for reaction to F. virguliforme, and 1,212 accessions in 19 perennial Glycine species that have not been thoroughly investigated for resistance to diseases or pests affecting soybean, including SDS and SBR.

Discovering new sources of resistance to diverse pathogens, whether in Glycine max or perennial

Glycine species, will offer new options for soybean breeders seeking to incorporate resistance, as well as other traits, into soybean, and will provide material for core collections to use in furthering our understanding of the genetic and molecular nature of resistance in soybean and its wild relatives, and the relationship thereof. The following chapters describe studies investigating resistance in Glycine max to F. virguliforme and in Glycine species to H. glycines and P. pachyrhizi and reports new sources of resistance in both cases.

34 TABLE AND FIGURES

Table 1.1. † Glycine species listed by taxonomic treatment and including subgenus, authority, growth form and genome group, chromosome number, geographic distribution, and number of accessions in the USDA National Plant Germplasm System (NPGS).

Treatment Subgenus and Authority Growth form Chromo- Geographic # of Species or genome some #3 distribution PIs in 2 group NPGS Hermann, 1962 Subgenus Soja (Moench) F. J. Herm. Annual G. soja Sieb. & Zucc. G 40 China, Japan, Korea, 1,181 “wild soybean” Russia, Taiwan Glycine max (L.) Merr. G 40 Worldwide 19,541

Subgenus Glycine Willd. Perennial Glycine canescens F. J. Herm. A 40 Australia 123 G. clandestina Wendl. A 40 Australia 90 G. latrobeana (Meisn.) Benth. A 40 Australia 6 G. tabacina (Labill.) Benth. B 40 Australia 142

Complex 80 Australia, South Pacific Islands G. tomentella Hayata E 38 Australia 299

D 40 Australia, New Guinea Complex 78 Australia, New Guinea Complex 80 Australia, New Guinea, Indonesia, Philippines, Taiwan G. falcata Benth. F 40 Australia 29 Newell and G. latifolia4 (Benth.) C. Newell & B 40 Australia 44 Hymowitz, 1980 Hymowitz Tindale, 1984 G. argyrea Tind. A 40 Australia 14

G. cyrtoloba C 40 Australia 48 Tindale, 1986b G. curvata Tind. C 40 Australia 9 Tindale, 1986a G. arenaria Tind. H 40 Australia 5 G. microphylla (Benth.) Tind. B 40 Australia 33 Tindale and G. albicans Tind. & Craven I 40 Australia 0 Craven, 1988 G. hirticaulis Tind. & Craven H 40 Australia 0

? 80 Australia 0 G. lactovirens Tind. & Craven I 40 Australia 0 Tateishi and G. dolichocarpa5 Y. Tateishi & H. Ohashi A/D 40 Australia, New 13 Ohashi, 1992 Guinea, Indonesia, Philippines, Taiwan Tindale and G. pindanica Tind. & Craven H 40 Australia 4 Craven, 1993 Doyle et al., G. stenophita4 B.E. Pfeil & Tind. B 40 Australia 27 2000 Pfeil et al., 2001 G. peratosa B.E. Pfeil & Tind. A 40 Australia 8 G. rubiginosa Tind. & B.E. Pfeil A 40 Australia 39 Pfeil and G. aphyonota B.E. Pfeil I ? Australia 0 Craven, G. pullenii B.E. Pfeil, Tind. & H ? Australia 0 2002 Craven Pfeil et al., 2006 G. gracei B.E. Pfeil & Craven A 40 Australia 0 G. montis‐douglas B.E. Pfeil & Craven A 40 Australia 0 G. pescadrensis Hayata A/B 40 Australia, China, 68 Taiwan G. syndetika5 B.E. Pfeil & Craven A 40 Australia 6 Barrett and G. remota M.D. Barr. & R.L. Barr I6 ? Australia 0 Barrett, 2015

35 Table 1.1. (cont.)

†Adapted from Hartman et al. (2015a) and Sherman-Broyles et al. (2014).

2 Genome group: species in the same letter group have more genomic similarities than species in different letter groups.

3 Diploid (2n= 40), tetraploid (2n= 80), aneudiploid (2n= 38) and aneutetraploid

(2n= 78) chromosomes.

4 Segregated from G. tabacina.

5 Segregated from G. tomentella.

6 Not confirmed.

36

Fig. 1.1. Field showing a large area of SDS in late season. Severely affected plants develop chlorotic spots which leads to necrosis and defoliation.

Fig. 1.2. Brown-colored (mature) cysts of soybean cyst nematode (Heterodera glycines) after collection from soybean (Glycine max) roots. Photo credit: G. Hartman.

Fig. 1.3. A highly susceptible genotype showing lesions due to infection by soybean rust caused by Phakopsora pachyrhizi.

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54 CHAPTER 2: EVALUATION OF OVER TEN THOUSAND SOYBEAN (GLYCINE MAX)

PLANT INTRODUCTIONS FOR RESISTANCE TO FUSARIUM VIRGULIFORME

ABSTRACT

Sudden death syndrome (SDS) is one of the most important yield limiting diseases of soybean. The most common causal species are Fusarium virguliforme in North America and F. tucumaniae in South America, though other causal species continue to be reported and disease occurrence continues to expand in soybean growing areas around the world. Yield losses of up to 80% have been reported. Host resistance is among the most sustainable ways to reduce losses to SDS, and screening soybean accessions for sources of resistance is a fundamental part of integrated management of SDS. Evaluating soybeans for resistance to SDS began in the early

1990’s about a decade after the causal organism was described. Better sources and unique sources of resistance may be useful to increase the level of partial resistance available. The

USDA Soybean Germplasm Collection (SGC) is part of the National Plant Germplasm System

(NGPS), a collaborative effort to protect the genetic diversity of agriculturally important plants.

The SGC contains over 20,000 plant introductions (PIs), 10,144 of which were not previously evaluated for resistance to F. virguliforme. Additionally, a core set of 350 PIs was assembled to represent broad genetic diversity within the SGC using the SoySNP50K and 3.7 M SNP dataset and was not previously evaluated for F. virguliforme. This study evaluated over 10,000 soybean

PIs for reaction to F. virguliforme and identified new sources of resistance which can be useful in breeding efforts as well as in ongoing investigations into the nature of resistance to SDS, including in investigations characterizing other Fusarium species causing SDS in other regions

55 of the world. Furthermore, this study demonstrates the importance of the plant genetic resources curated in the NPGS and in similar collections around the world.

INTRODUCTION

Soybean [Glycine max (L.) Merr.] is the leading oilseed crop in the world with approximately 349 million metric tons (MMT) produced in 2018 (faostat.fao.org). Soybean production is expanding worldwide (ERS 2020). There are numerous drivers including economic opportunity, crop diversification, nutritional/protein needs, and/or changing climate conditions. Examples include efforts in Canada (Saavedra 2019), Africa (Hartman and Murithi

2019; Santos 2019) and Europe (Fogelberg and Recknagel 2017) to advance the crop in those regions and where planted acreage has doubled or even tripled from 2000 to 2018

(www.fao.org). In particular, FAO reports tripling of soybean acreage in “least developed countries” in the same period. Additionally, markets for niche grain soybeans, including organic grain and food grade soybeans are expanding (Hartman et al. 2016), and consumption of vegetable soybean continues to increase in the USA and around the world (Djanta et al. 2020;

Reiter et al. 2019). The historical and current importance of soybean and some of its major pathogen and pest constraints were reviewed (Hartman et al. 2011).

Sudden death syndrome (SDS) is one of the most important yield limiting diseases of soybean (Hartman et al. 2015b). SDS was first observed affecting soybean in the USA in

Arkansas in 1971 (Hirrel 1983; Roy 1997). The disease is caused by Fusarium virguliforme

(Aoki et al. 2003), a soil inhabiting fungus. The disease was discovered in several additional

U.S. states by 1986 and determined to be caused by the fungus F. solani (Mart.) Sacc., later amended to F. solani (Mart.) Sacc. f. sp. glycines (Roy 1997; Roy et al. 1997) and then changed

56 to F. virguliforme (Aoki et al. 2003). Occurrence of SDS has increased steadily since the first report of the disease in the USA and Canada (Anderson and Tenuta 1998) and SDS is consistently among the most impactful yield-limiting diseases in any year. The disease was second in estimated losses to SCN from 2010 to 2014 across 99% of soybean production in the

United States, and one province of Canada. The majority of losses reported due to SDS in this period, 76% to 81% on average, were recorded in northern states. This is in agreement with long-standing risk assessments based on temperature and moisture, which projected that areas in the north central region were the most vulnerable to the disease (Scherm and Yang 1999). SDS has been reported in Brazil and Argentina (Aoki et al. 2012) as well as Malaysia (Chehri et al.

2014), and South Africa (Tewoldemedhin et al. 2015). While F. virguliforme is responsible for the disease in North America (Aoki et al. 2003), in South America, F. tucumaniae, F. brasiliense, F. cuneirostrum, and F. crassistipitatum have been reported in South America (Aoki et al. 2003; Aoki et al. 2005; Aoki et al. 2012). F. brasiliense was recently reported in Michigan

(Wang et al. 2019b).

Roots infected with F. virguliforme or other SDS-causing species often are necrotic and rot (Fig. 2.1). Foliar symptoms, most typically interveinal chlorosis and necrosis, result from translocation of fungal toxin (Brar et al. 2011) from affected roots upward. In the field, plants often remain asymptomatic until after flowering, however, at late reproductive phases, increased temperatures promote toxin transport through xylem (de Farias Neto et al. 2006; Leandro et al.

2013), causing foliar symptoms to become visible. Premature defoliation due to SDS results in reduced seed size, increased flower and pod abortion, and slight to 100% yield losses, with greater losses associated with earlier onset (Gongora-Canul and Leandro 2011; Navi and Yang

2008; Wang et al. 2019a).

57 Host resistance has been on the forefront for a sustainable solution to SDS. Since the discovery of SDS in the USA, multiple evaluations of germplasm against SDS have been conducted (Chang et al. 1996; Hartman et al. 1997; Hnetkovsky et al. 1996; Mueller et al. 2002;

Mueller et al. 2003; Rupe et al. 1991; Stephens et al. 1993) and reviewed (Hartman et al. 2015a).

Sources of resistance were identified that included public cultivars like Forrest, Ripley. PI

520733, a large seeded Korean accession, had one the lowest SDS severities in field trials in

1995 (P. Gibson, personal communication; reported in Hartman et al. 1997). Hartman et al.

(1997) screened 800 PIs from MG II to V in the growth chamber and greenhouse and reported multiple PIs (PI 567374, PI 567315, PI 567441C, PI 567650B, and PI 567664) with ratings lower than the resistant check, PI 520733. PI 567374 (MG IV) has subsequently been used in many studies as the partially resistant check. Mueller et al. (2002) evaluated 6037 PIs from MG

II-IV originating from 38 countries and found six and eight PIs that had significantly lower disease severity than partially resistant checks PI 567374 and PI 520733. These sources have been utilized in breeding programs (Cianzio et al. 2014; Cianzio et al. 2016; de Farias Neto et al.

2007; Luckew et al. 2013).

Genetic resistance to F. virguliforme is complex and considered partial or quantitative, as resistance is encoded by a large number of quantitative trait loci (QTL) and each of which contributes only a small amount of resistance. Chang et al. (2018) reviewed research progress in genetic mapping of resistance to F. virguliforme in soybean, including discovery of more than 80

QTL and dozens of single nucleotide polymorphisms (SNPs) associated with soybean resistance to SDS. Breeding efforts have been reviewed including the use of plant genomic resources to aid in breeding selection for resistance to SDS in two main areas: resistance to foliar degradation by phytotoxins and root resistance to pathogen invasion, colonization and subsequent root rot

58 (Lightfoot 2015). Subsequently, additional QTL for foliar and root resistance were reported

(Swaminathan et al. 2019; Tan et al. 2019). Another study (Chang et al. 2019) reported resistance due to loss of susceptibility associated with STAY-GREEN genes, a new group of R genes based on loss-of-susceptibility mechanism. Two soybean STAY-GREEN genes were found to be associated with development of chlorosis, and resistance to SDS foliar chlorosis was attributed to a double mutation.

The USDA Soybean Germplasm Collection (SGC) consists of over 20,000 PIs, 10,000 of which have not been evaluated for resistance to F. virguliforme. The entire SGC has been genotyped using the SoySNP50K iSelect BeadChip, containing over 50,000 single nucleotide polymorphisms (SNPs) (Song et al. 2015), and a more extensive 3.7 M SNP dataset created at the Soybean Genetics and Genomics Laboratory at the University of Missouri from a whole- genome resequencing (WGRS) was used to create a subset of the SGC, 350 PIs, representing broad genetic diversity of the collection (Pawlowski et al. 2020). This diverse subset includes a range of soybean genotypes, including wild soybean, soybean landraces, and elite soybeans, a wide range of maturity groups (MG), from 000 to X, and PIs originating from 28 different countries.

Multiple sources of resistance in soybean to F. virguliforme will be helpful in the development of resistant cultivars for various uses in differing geographic regions and may be of use in furthering our understanding of the genetic and molecular nature of resistance in soybean to F. virguliforme. The objective of this work was to screen over 10,000 PIs for resistance to F. virguliforme in a series of elimination experiments based on foliar severity using a modified layer test and then test a small set of selected lines in replicated experiments comparing foliar severity as well as the percent dry root, shoot and total weights to a non-inoculated control.

59 Additionally, the diverse set of 350 PIs was tested for foliar severity and for percent of the non- inoculated control dry weight when inoculated with F. virguliforme.

MATERIALS AND METHODS

Sequence of Testing

Soybean germplasm not previously screened for SDS was evaluated in series of seedling screens in the greenhouse (Fig. 2.2). Material was evaluated in preliminary tiers using single plant tests in tiers I-IV followed by one tier (V) of multi-plant screening. Advanced testing included evaluation of remaining PIs (n = 127) in a multi-plant replicated test, followed by the final tier evaluation (VII) of PIs (n = 20) selected as highly resistant, and a “maturity group” experiment including PIs (n = 40) representing all soybean MGs. Finally, the diverse set of 350

PIs representing a collection of maximum soybean genetic diversity was evaluated.

Preliminary Germplasm Evaluation

Purpose and design

Germplasm was evaluated in a series of tiers to narrow the test set and identify resistant

PIs. Initial evaluations were intended to quickly eliminate the most susceptible PIs and were arranged as single plant eliminations in flats (26 x 92 x 130 cm) that contained 72 seeds (68 test entries and four checks) in an 8 x 9 row by column grid. PIs were randomly arranged in multiple sets of 10 to 14 trays per tier, evaluated over time, with each tier including all the PI entries not yet eliminated. In Tier V, plots of five seeds per PI (720 PIs total) were randomly arranged throughout the set. Tier VI was a randomized complete block design with four replications blocked by position across a greenhouse bench. Each flat contained 22 of 127 test entries and two checks, PI 567374 (PR) and Spencer (S).

60 Plant material

Seeds of 10,144 PIs was received from the USDA Soybean Germplasm Collection located at the University of Illinois in Urbana, IL. Test material represented all soybean MGs

(Fig. 2.3) collected from 80 countries and 6 continents (Fig. 2.4), with the largest portion of material, 33%, originating from China. Seed weight ranged from 1.2 g to 39.5 g per 100 seeds, protein and oil ranged from 35.4% to 54.4% and 8.1% to 25.1%, respectively. Four soybean checks were used in tiered single plant evaluations: Spencer (susceptible); Stephens et al 1993,

LS94-3207 (moderately susceptible; Chawla et al. 2013), Cordell (moderately resistant; Chawla et al. 2013) and PI 567374 (partially resistant; Hartman et al. 1997). Advanced testing of 127 PIs

(tier VI) used two checks, Spencer and PI 567374.

Inoculum production

F. virguliforme isolate Mont-1 (Hartman et al. 1997) was used in all tests. The isolate was maintained on potato dextrose agar (PDA) in polystyrene petri dishes (100 mm x 15 mm;

Fisher Scientific) at 24°C in the dark, and transferred as needed. To propagate the pathogen, plugs measuring 8 mm diameter were cut from the outer edge of actively growing cultures, transferred to new PDA plates, and grown for 2 weeks. Sorghum grain was soaked overnight in tap water and then placed into bags (large autoclavable gusseted bult spawn bags 0.2 micron,

Everything Mushrooms, Knoxville, TN), at a rate of two liters of soaked grain per bag. The bags were sealed with a foam plug secured with a plastic zip tie. The bags were autoclaved twice, once on successive days for 30 minutes, cooling completely overnight between and after steaming. One 14-day-old plate of F. virguliforme, sliced into 1-cm squares, was placed into each bag of autoclaved sorghum. Bags were heat sealed, shaken gently to disperse the fungus, and incubated at room temperature. Bag contents were mixed every other day, until fully

61 infested after approximately 14 days. Inoculum was then removed from bags, air dried on racks at room temperature for 48 hours and stored at 6°C until used.

Planting, Inoculation, Environment and Maintenance

Test flats were prepared using a modified inoculum layer method (Chawla et al. 2013).

In this method, plants roots contact an even and uninterrupted layer of concentrated inoculum which runs through the middle of the planting medium. Plants contact the inoculum as roots grow through the inoculum layer approximately 5 cm below furrows. To prepare the test flats,

25.5 x 91.5 x 129.5 cm heavy-duty plastic trays with holes were lined with a layer of paper towels and filled with 3200 ml of soil mix, a 1:1:1 pasteurized mix of topsoil, torpedo sand and a peat-perlite product (SunshineÒ mix #1 FafardÒ -1P, Sun Gro Horticulture, Agawam, MA).

Next, 1600 ml of inoculum:soil mix (336 ml infested sorghum and 1,264 ml soil mix) was distributed evenly over the first layer. An additional 3200 ml of soil mix was added over the top of the inoculum:soil mix and leveled before planting. For single plant tests in Tiers I-IV, 68 entries and 4 checks were planted in each tray, evenly spaced in an 8 x 9 grid pattern. For multi- plant screening in tier V, eight furrows approximately 0.5 cm deep were made with a straight edge, spaced evenly across and perpendicular to the longer side of the tray and three plots of 5 seeds per entry and each check were planted (in-furrow seed spacing = 5 cm) in each furrow and covered with an additional 500 ml of soil mix. Flats were placed on a greenhouse bench and kept at 26°C day, 24°C night under a 16 h photoperiod, and watered twice daily for the duration of the experiment.

Rating

Foliar severity was rated using a 1-8 scale previously described (Chawla et al. 2013), where 1 = no symptoms, 2 = general slight yellowing and/or chlorotic flecks or blotches, 3 =

62 distinct pattern of interveinal chlorosis, 4 = necrosis along a portion of leaf margin (generally, leaf has necrosis in addition to symptoms described in “3”), 5 = necrosis along the entire margin of a leaf, 6 = interveinal necrosis, >50% of leaf area is necrotic, 7 = defoliation of at least one leaflet, 8 = dead plant. In preliminary single plant tests, tiers I-IV, plants were rated once for foliar severity at the peak of symptoms when the susceptible check was severely affected. In multi-plant and replicated testing, tiers V and VI, respectively, plants were rated three times: at symptom onset, as symptoms progressed, and again a few days later. These ratings were done at approximately 18, 21 and 28 days after planting. In tiers I-IV, accessions with severity less than

3.0 were advanced to the next tier. After tier V, entries with mean lower than PI 567374 were advanced to replicated testing. Overall foliar means and error were computed for entries in tier

VI; entries with less than 50% of plants in any replication were excluded.

Final tier evaluation

Plant material

For the final tier (VII) of germplasm evaluation, twenty PIs were selected with the lowest foliar severity in tier VI, all lower than PI 567374. Four checks were used: Spencer, PI 567374,

Forrest (Iqbal et al. 2001), and Ripley (Stephens et al. 1993).

Planting, Inoculation, Environment and Maintenance

Inoculum, tests flat preparation, and planting were as previously described for the tier VI in the preliminary germplasm evaluation except for a few differences. For each inoculated flat, a non-inoculated flat was prepared, with the same randomization of entries and otherwise identical to the inoculated flat except for the substitution of soil mix for the sorghum inoculum volume.

To enable root washing, the planting medium was a 2:1 mixture of soil to torpedo sand, pasteurized twice before use. Six seeds were planted per plot, and plots were thinned after

63 emergence to ensure more even plant number and plant developmental stage among inoculated and non-inoculated plots per PI; flats were placed on a greenhouse bench and kept at 26°C day,

24°C night under a 16 h photoperiod, and watered twice daily for the duration of the experiment.

Twelve replications were conducted.

Rating and Data Analysis

Foliar severity ratings were made per plant using the scale and schedule previously described. Dry root and shoot weights were also obtained for each plot as follows. After the final foliar rating, all plant material from inoculated and non-inoculated trays was removed by flooding the trays with water, soaking for 15 minutes, and then extracting each plot

(experimental unit) from the flat. Roots were thoroughly rinsed to remove all planting medium, plants in each plot were cut at the soil line. Roots were visually rated to record the number of plants per plot with rotted roots and to quantify severity of root damage per plot using a scale from 1 to 5 for percent rotted (1=0-19%; 2=20-39%; 3=40-59%; 4=60-79%; 5=80-100%). After visual ratings, roots and shoots were placed in a drying oven until completely desiccated and dry weights were recorded. The percent of the non-inoculated control root and shoot weight (g) for each plot was calculated by first obtaining per plant weight for each inoculated and non- inoculated plot (dry weight per plot divided by the plant number per plot) and then dividing the inoculated dry weight (g) by corresponding non-inoculated dry weight (g) for roots and shoots, respectively. Percent of the non-inoculated control total weight (g) was obtained as the sum of dry per plant root and shoot weights per plot. Data were analyzed using Fit Model procedure in

JMP Pro 15.0® (SAS Institute Inc., Cary, NC) and means were separated using the JMP

LSmeans Student’s t procedure at α = 0.05.

64 Maturity group experiment

Purpose and design

This evaluation was conducted to investigate the effect of MG under controlled conditions as well as to compare PIs with lowest foliar severity from tier VII with PIs identified with resistance in a previous study (Mueller et al. 2002). Four PIs each from MGs II – IV were selected from Mueller et al. (2002) based on lowest foliar severity by MG. In total, forty plant introductions (PIs) representing all 13 soybean MGs that were previously less severe than the partially resistant check were assessed in two environments, greenhouse and growth chamber, to study the effect of MG across partially resistant reactions and understand the usefulness of the controlled environment and/or seedling test for evaluating resistance in soybean PIs. The experiment was designed, conducted, rated, and analyzed in an identical manner to tier VII. Two replications were conducted, blocked by environment (greenhouse and growth chamber).

Plant material

Resistant material in each MG, 000-X, was identified based on the foliar mean score in the final replicated tier (tier VII) of germplasm screening. Because a large proportion of the MG

II-IV PIs in the USDA Soybean Germplasm Collection had been previously tested (Mueller et al.

2002), four PIs from each of those MGs reported to have resistance in that study were included in the entry list. Four soybean checks were used: Spencer (susceptible), LS94-3207 (moderately susceptible), Cordell (moderately resistant) and PI 567374 (partially resistant).

Planting, Inoculation, Environment and Maintenance

Inoculum, test flat preparation, planting, and rating were done as previously described for the replicated test (tier VI) in the preliminary germplasm evaluation. After planting, flats of one

65 replication were placed in a greenhouse set at 26°C day, 24°C night and 16 h photoperiod and watered twice daily and one replication was placed in a growth chamber at the same settings.

Rating and data analysis

Data were collected and analyzed similar to the final tier germplasm except for that visual root severity per plot was not measured and that the effect of PI on the effect MG class on foliar and weight variables was measured. For the latter, PIs (excluding checks) were grouped as follows: early = MG 000-I, mid = MG II-VI, and late = MG VII-X.

Diverse set evaluation

The diverse set of 350 soybean PIs (previously described) was evaluated for reaction to

F. virguliforme. The experiment was designed, conducted, rated, and analyzed in an identical manner to the final tier of germplasm evaluation. Two replications were conducted, blocked by replication over time. Means and error for foliar severity were computed for all entries.

RESULTS

Preliminary Germplasm Evaluation

Preliminary plant evaluations from tiers I-IV reduced the number of test accessions from

10,144 PIs to 720 PIs. Each tier reduced the total by about 50%, with 7% of the original entry number remaining after to be tested in tier V (Fig. 2.2). Tier V results showed only 3% of accessions more severe than the susceptible check; 18% (127 PIs) had lower foliar severity than the resistant check, PI 567374, which had mean foliar severity of 1.6. In this group of 127 PIs,

31% were MG V, 26% were MG IX, and 9% and 8% were MG IV and MG VI, respectively.

There were no PIs from MG II or III as most of the PIs in the SGC in these two MGs had been

66 tested previously. Chi-square analysis (Table 2.1) for PIs by MG with lowest foliar severity

(mean < 2.0) indicated an association of MG and low severity (P < 0.00001).

Means for foliar severity and standard error of the means were computed, excluding PIs with low plant number (< 50%), for the tier VI evaluation of 127 PIs in four replications (Table

2.2). Foliar severity means ranged from 1.0 to 4.9, with checks PI 567374 and Spencer at 1.5 and 4.4, respectively, and an overall trial mean of 2.2. Only two PIs had foliar severity rating greater than Spencer. Thirty-seven entries had lower foliar means than PI 567374, 11 of which showed no foliar symptoms (mean severity = 1.0). Fifty-one PIs had very low severity, showing only slight chlorosis (foliar mean < 2.0). Of the 37 entries less severe than PI 567374, MG IX was the most represented MG with 20 PIs, representing 16% of the total tested in tier VI, while all other MGs had 1-4 accessions lower than PI 567374, except for MG II and III with no accessions. Accessions with low foliar severity (mean < 2.0) originated from 11 countries but, notably, almost 50% PIs (n = 17) in this group were from India (Table 2.3).

Final Tier Germplasm Evaluation

Foliar severity

Foliar severity means ranged from 1.15 to 5.5, with a mean severity of 2.3 (Table 2.4).

Spencer had the highest mean foliar severity at 5.5, while PI 567374 had a mean of 1.7. Ten PIs had foliar severity not significantly different (P < .0001) than PI 567374 and PI 506757, which had the lowest mean foliar severity. Forrest and Ripley with means of 2.8 and 3.4 were among the PIs with greater severity.

Root severity

For root severity, there was no effect of PI on root severity (Table 2.4), which ranged from 3.3 (Spencer) to 2.4 (PI 506757) with a mean of 2.8. Twelve PI entries and two checks had

67 severity lower than or equal to the mean; PI 567374, Ripley and Forrest had mean severity of

2.7, 2.8 and 2.9, respectively. Ninety-six percent of plots across both experiments had visible root symptoms on all plants.

Percent of non-inoculated control shoot, root, and total weights

There was a significant (P < 0.0001) effect of PI on all percent of non-inoculated control weight variables (Table 2.4). Percent control shoot weight ranged from 40% to 89% with an overall mean of 66%. Spencer had the lowest mean percent control shoot weight (40%) and two

PIs (567210 and 307856) were not significantly different. PI 567374 had significantly greater percent control shoot weight, 60%, compared to Spencer and most PIs, as well as Ripley and

Forrest were not significantly different. Three PIs, PI 507568, PI 279081 and PI 506757 had significantly greater percent control shoot weight, 80%, 82% and 89%, respectively, than PI

567374.

Percent control root weight ranged from 29% to 73% with an overall mean of 43% (Table

2.4). Spencer, Ripley, Forrest, PI 567374 and 13 PI entries were not significantly different from the lowest scoring entry with percent of the control root weight ranging from 29% to 46%. PI

567374 (32%), Ripley (33%), Spencer (36%) had among the lowest means while Forrest (45%) was slightly above the overall mean. Three PIs, PI 507568, PI 279081 and PI 506757 had significantly greater percent control root weight, 60%, 61% and 73%, respectively, than other entries.

Percent control total weight ranged from 37% to 80% with an overall mean of 52%.

Spencer had the lowest mean percent control shoot weight, 37% (Table 2.4); 11 PIs with percent control root weight ranging from 40-52% were not significantly different from Spencer. PI

567374 and Ripley, with 44% and 42% of the control root weight, respectively, were also not

68 different from Spencer and were below the mean. Three PIs, PI 507568, PI 279081 and PI

506757 had significantly greater percent control root weight, 71%, 72% and 80%, respectively, than other entries.

Correlations

Percent control weights were positively correlated (Table 2.5). Foliar severity was negatively correlated to percent control shoot and percent control total weight, but not correlated to percent control root weight or root severity. There was no correlation between root severity and any percent control weights.

Maturity Group Experiment

Mean foliar severity ranged from 1.0 to 5.1 with an overall mean of 2.0 (Table 2.6).

Spencer had the highest mean foliar severity of 5.1, while PI 567374 had a mean of 1.3. Five

PIs, 232997, 243518, 281893, 467320, and 497953, MG 00, IV, X, I, and X, respectively, had lower foliar severity than PI 567374. Additionally, 15 PIs from 9 MGs representing all MG classes showed low average severity (< 2.0).

Percent of the non-inoculated control shoot weight ranged from 30% to 93% with a mean of 56% (Table 2.6). Spencer had the lowest value for percent of the control shoot weight at 30% and PI 567374 had a value of 60%. Ten PIs from six MGs representing all MG classes had percent of the control shoot weight greater than that of PI 567374. Percent control root weight ranged from 36% to 96% with a mean of 69%. Spencer had the lowest value for percent of the control root weight at 36% and PI 567374 had a value of 72%. Fifteen PIs from seven MGs and all MG classes had percent of the control shoot weight greater than that of PI 567374. Percent control total weight ranged from 31% to 93% with a mean of 59%. Spencer had the lowest value for percent of the control shoot weight and PI 567374 had a value of 63%. Eleven PIs from

69 seven MGs and all MG classes had percent of the control shoot weight greater than that of PI

567374. There were significant positive correlations (Table 2.7) among all percent control dry weights. Foliar severity was negatively correlated with percent control dry shoot and total weights; there was no correlation between foliar severity and percent control root weight.

There was a significant effect of MG class [early (MG 000-I), mid (MG II-V), late (MG

VII, VIII, IX, X)] on percent of the non-inoculated control dry root (0.0106*) or total weight

(0.0403*) (Table 2.8); the early MG class had significantly lower values (58% and 52%) for root and shoot variables compared to mid (74% and 64%) and late (84% and 69%) classes. There was a significant interaction of MG class with environment for percent control root (P=0.0059) and total weights (P=0.0393), but not for percent control shoot weight or foliar severity. MG class mean percent control root and total weight was greater in the growth chamber compared to the greenhouse.

Diverse set evaluation

Mean foliar severity of 350 PIs ranged from 1.0 to 6.3, with an overall mean of 4.0

(Table 2.9). Spencer had mean foliar severity of 5.5, while PI 567374 had a mean of 2.1.

Eighteen PIs had lower foliar severity than PI 567374; two PIs (587588B and 567238) mean foliar severity of 1.0. Results for percent control dry weights were not significant for root, shoot or total weight (data not shown). Chi square analysis for PIs with means lower than 2.0 (n=16) and means lower than 3.0 (n=57) (Table 2.10) shows MG associated with lower mean (<2.0; P £

.0003 at alpha = 0.01), but MG was not significant for a higher mean threshold (< 3.0). Of the

PIs with means lower than 2.0, most (ten or 63%) were from China.

70 DISCUSSION

Limiting crop losses to disease is a critical part of maintaining yields as well as upholding efficient use of valuable agricultural land. Host resistance is among the most sustainable ways to reduce losses to diseases, such as sudden death syndrome of soybean. My study evaluated over

10,000 soybean PIs for resistance to F. virguliforme and identified new sources of resistance that may be useful in breeding efforts as well as in ongoing investigations into the nature of resistance to SDS. My study identified several sources in multiple evaluations: PI 307847 (IX),

PI 232997 (MG 00), and PI 497953 MG (X) which were among the five least severe PIs for foliar severity in two, three and four experiments, respectively; PI 506757 (MG V) which was among the least severe for foliar severity in tier VII and had highest percent control weights; and the partially resistant check PI 567374, which was included in hundreds of flats and showed a consistent level of foliar resistance.

Resistant responses have been reported to be due to foliar response to phytotoxin and/or root response to pathogen infection (Fig. 2.1) (Kazi et al. 2008; Lightfoot 2015; Ortiz-Ribbing and Eastburn 2004; Swaminathan et al. 2019; Tan et al. 2019). My study utilized inoculation of plants with the fungus in a controlled environment to ensure infection and symptom development and to provide ample space to accommodate large test sets. Five tiers of single plant testing reduced the number of test flats and resources needed to narrow a large set of PIs to 1% of the original number that showed lower mean foliar severity than the partially resistant check, PI

567374. Replicated testing showed resistance in a number of PIs, 11 which showed no foliar symptoms, 37 with lower foliar severity than PI 567374, and 51 PIs with low foliar severity overall (mean less than 2.0), indicating little or no chlorosis.

71 Accessions in this study were inoculated with F. virguliforme isolate Mont-1, an isolate used in the two previous germplasm evaluations at the University of Illinois (Hartman et al.

1997; Mueller et al. 2002). Mont-1 has previously caused the greatest disease severity of five isolates used in Mueller et al. (2002) and caused the greatest reduction in shoot weight and shoot length compared to the non-inoculated control plants in most disease in a study evaluating aggressiveness of 123 isolates (Li et al. 2009). The PIs reported in this study may prove to be useful sources of resistance to multiple SDS-causing species in a range of geographical areas where SDS has been reported.

Previous studies have used controlled environments (Hartman et al. 1997; Mueller et al.

2002) or inoculated field studies (Chang et al. 1996; Hnetkovsky et al. 1996) to evaluate soybean genotypes for phenotypic response to F. virguliforme. Besides ensuring homogenous exposure to the pathogen, controlled environment testing allows PIs to be included regardless of MG, whereas field testing limits entries to PIs that are locally adapted. Replicated testing showed no effect of PI or MG class on foliar severity or percent shoot weight, indicating testing was valid for the range of MGs based on foliar severity ratings. While preliminary screening eliminated all entries in MG II and MG III, seven of 12 PIs previously reported to have resistance (Mueller et al. 2002) had foliar means less than 2.0 in the maturity group test. After replicated testing, Chi- square analysis of low foliar severity PIs by MG was not significant. However, Chi-square analysis of the results after tier V of the germplasm evaluation (Table 2.1) showed an effect of

MG among PIs with foliar severity lower than PI 567374. MG IX showed the most unexpected values, as did MG V to a lesser degree, while MG I and 000 both had a lower than expected number of accessions after tier V. Overall there was no linear relationship between MG and Chi- square value and these results do not point to either early or late MG classes that might interact

72 with environment, for example photoperiod. Seed quality could be one explanation for differences among MGs. Early infection has been shown to increase SDS severity (Gongora-

Canul and Leandro 2011; Navi and Yang 2008). Lower seed vigor of PIs sourced from the

USDA Soybean Germplasm Collection could result in later germination and slower growth rate, possibly delaying infection time and symptom development in short-duration (<30 days) seedling evaluations. Additional studies would be needed to explain the reason for this MG distribution result at the end of preliminary testing.

Two cultivars reported to have resistance, Forrest (Hnetkovsky et al. 1996; Iqbal et al.

2001) and Ripley (Cooper et al. 1990; Stephens et al. 1993), were included in my study, but were not among those lines with the lowest foliar severity. Ripley was also not among the lowest in

Hartman et al. (1997) and Forrest was not among the lowest in Mueller et al (2003), both greenhouse studies. Reports of resistance in Forrest were associated with inoculated field experiments (Chang et al. 1996; Hnetkovsky et al. 1996) as well as uninoculated (Njiti et al.

1998). Inoculum density has been reported to affect results in tests of SDS resistance and may be a factor in the comparatively lower level of foliar resistance in these two cultivars in my study and previous greenhouse studies. Variation in inoculum density affected results specifically when comparing PIs in resistance classes and lowering inoculum density in greenhouse testing resulted in stronger correlations with field testing (Njiti et al. 2001). Other studies have suggested that higher inoculum rates may be responsible for breakdown of field SDS resistance in the greenhouse (Gray and Achenbach 1996; Hartman et al. 1997). Because the purpose of my study was to identify the most resistant material in a large set, a consistent and evenly dispersed volume of infested grain was used, and the inoculum density was not quantified per gram of infested grain. Rather, intensity of infection was judged by the foliar severity of susceptible

73 cultivar Spencer, which was consistently between 5.0 and 6.0. Future testing at varying inoculum levels, including at increased pathogen pressure in greenhouse testing or at more difficult to control levels in field environments, would be useful to understand the degree of resistance found in this study as well as function of resistance in yield performance.

Over half of the entries in the final (tier VII) set of the my study showed low average foliar severity, visually quite asymptomatic in leaves, while infection was confirmed via almost

100% incidence of necrosis on individual plant roots. There may be common underlying genetics for this, as a recent study reported that soybean plants with a double mutation of two

STAY-GREEN genes resist visual damage due to toxin (Chang et al. 2019). My study did not conduct molecular comparisons, but measured additional differences in phenotypic responses, root severity and as percent of the inoculated control weights, to further characterize genotypes with low foliar severity. In tier VII, final testing of germplasm, root severity was measured as percent necrosis visible on each plot of five plants over 12 replications and, though susceptible check Spencer was the most severe, there was no significant difference among PIs, including Forrest previously reported with root resistance to SDS (Kazi et al. 2008; Njiti et al.

1998). Differences among PIs might have been reduced by the fact that all were selected for foliar resistance.

A previous study found some degree of susceptibility in “asymptomatic” hosts of F. virguliforme via significant differences in dry weights of inoculated plants compared to non- inoculated control plants even in absence of visual symptoms (Kolander et al. 2012). In my study, percent control weights were positively correlated in the final germplasm evaluation as well as in the maturity group. Root and shoot mass affected similarly due to infection does not support root resistance. Significant differences were seen by PI for percent control weights,

74 including percent root weight in the final germplasm evaluation, but not in MG experiment. This is most likely related to more even plant number between inoculated and non-inoculated treatments in the final tier evaluation. In both cases, percent weights were the lowest for Spencer while at the other end of the spectrum a few PIs had over 80 percent of the non-inoculated control weights. These differences in growth response merit further investigation. Follow up testing is needed to compare a small number of PIs showing higher percent control weights in an experiment with a greater number of known susceptible cultivars. Results might have been hampered by the layout of multiple plots of PIs per flat and conducting single plant (to ensure even plant number) testing in cones. Advanced studies are needed to further investigate any percent weight differences. Also, larger cones, specifically Deep pots D60L (36 cm height and

6.4 cm inner diameter) were shown to allow for better expression of significant differences in root architecture (Manavalan et al. 2010) and might offer better comparison of root response to

SDS infection in the greenhouse and could help clarify possible MG class differences shown in the MG experiment. Stem cutting assays will also be helpful to determine whether foliar severity is increased when toxin goes directly to foliage without roots (Huang and Hartman 1998).

In conclusion, my study reports a number of new sources of resistance to SDS based on foliar severity under greenhouse conditions. Accessions with low foliar severities may limit infection, limit damage due to infection and/or limit yield loss due to infection and colonization.

Field testing in complex environments will be required to confirm this before going forward with breeding efforts. Moreover, this set of PIs can be useful in studies on the genetics of resistance, pathogen biology, and the interaction of the soybean host and Fusarium species causing SDS.

Finally, my study was made possible by the resources curated in the USDA Soybean Germplasm

75 Collection, and demonstrates that efforts to preserve the physical and informational resources of the collection are important and consequential to improving germplasm.

76 TABLES AND FIGURES

Table 2.1. Number of plant introductions (PIs) per maturity group (MG) in a set of 10,144 test entries, number of PIs per MG after five tiers of preliminary screening with mean score lower than PI567374, and Chi-square value for the set.

# of PIs # of PIs in after five Chi- MG test set tiers† Expected‡ square 0 127 3 2 1 00 464 5 6 0 000 1052 5 13 5 I 1533 5 19 10 II 67 0 1 1 III 79 0 1 1 IV 527 11 7 3 V 2315 40 29 4 VI 1413 10 18 3 VII 847 6 11 2 VIII 918 7 11 2 IX 701 33 9 67 X 101 2 1 0 Total 10144 127 127 100§

† Mean foliar rating lower than that of PI567374 (1.64); Foliar severity was rated using a 1-8 scale, where 1 = no symptoms, 2 = general slight yellowing and/or chlorotic flecks or blotches, 3 = distinct pattern of interveinal chlorosis, 4 = necrosis along a portion of leaf margin (generally, leaf has necrosis in addition to symptoms described in “3”), 5 = necrosis along the entire margin of a leaf, 6 = interveinal necrosis, >50% of leaf area is necrotic, 7 = defoliation of at least one leaflet, 8 = dead plant.

‡ Expected value = remaining number of PIs/total entries (0.012) x number of entries per MG.

§ P < .00001 at alpha .01.

77 Table 2.2. Mean foliar severity of 127 plant introductions (PIs) evaluated in advanced germplasm screening (tier VI) for resistance to F. virguliforme in four replications.

Foliar Foliar PI MG severity Std Err PI (cont.) MG severity Std Err PI175188† VII 1.0 0.00 PI307889A IX 1.3 0.30 PI232997 00 1.0 0.00 PI506552 V 1.3 0.33 PI279081 VII 1.0 0.00 PI506743 VI 1.3 0.33 PI281897A† IX 1.0 0.00 PI281901A IX 1.4 0.21 PI307846 IX 1.0 0.00 PI307856 IX 1.4 0.21 PI307847 IX 1.0 0.00 PI340903 IX 1.4 0.24 PI307882B IX 1.0 0.00 PI307878A IX 1.4 0.29 PI407785 V 1.0 0.00 PI423782 V 1.4 0.38 PI424251B† V 1.0 0.00 PI639573 VIII 1.4 0.22 PI424378† VI 1.0 0.00 PI578307C VII 1.4 0.24 PI458162† V 1.0 0.00 PI307855 IX 1.4 0.44 PI467320 I 1.0 0.00 PI307837 IX 1.5 0.29 PI497953 X 1.0 0.00 PI307886 IX 1.5 0.21 PI506757 V 1.0 0.00 PI281899B IX 1.5 0.33 PI507545 V 1.0 0.00 PI567374‡ IV 1.5 0.22 PI507575† VI 1.0 0.00 PI594696A IV 1.6 0.19 PI509110B† V 1.0 0.00 PI340900A IX 1.6 0.55 PI549025† V 1.0 0.00 PI506834 V 1.6 0.38 PI567105 VIII 1.0 0.00 PI437586C V 1.6 0.22 PI507568 VII 1.1 0.08 PI215688 IX 1.7 0.29 PI205901B IX 1.2 0.15 PI509092 V 1.7 0.47 PI341259 IX 1.2 0.15 PI603712 0 1.7 0.61 PI594696B IV 1.2 0.12 PI307863 IX 1.7 0.45 PI281911B IX 1.2 0.14 PI374191 X 1.7 0.47 PI340902 IX 1.2 0.20 PI201422 VI 1.7 0.37 PI567210 000 1.2 0.18 PI205911 VIII 1.8 0.13 PI307892 IX 1.3 0.25 PI189955 0 1.8 0.32 PI445683 VII 1.3 0.16 PI281911C IX 1.8 0.37 PI205901A IX 1.3 0.24 PI549023A V 1.9 0.52 PI307874 IX 1.3 0.24 PI417166 V 1.9 0.55 (cont.)

† n < 50%.

‡ Partially resistant check.

78 Table 2.2. (cont.)

Foliar Foliar PI MG severity Std Err PI (cont.) MG severity Std Err PI423742 V 1.9 0.18 PI567087A VIII 3.0 0.20 PI458168 V 2.0 0.48 PI509091A V 2.1 0.56 PI522192B 0 2.0 0.42 PI407993 V 3.0 0.44 PI605839A IV 2.1 0.61 PI612621 000 3.0 0.71 PI240670 IX 2.1 0.48 PI506686 VIII 3.0 0.49 PI495018 IX 2.1 0.56 PI243547 0 3.1 0.64 PI341261 IX 2.1 0.66 PI603424D I 3.1 0.41 PI506558 V 2.1 0.59 PI593953 I 3.1 0.25 PI507290 V 2.1 0.44 PI509102 VI 3.1 0.47 PI408098 V 2.1 0.25 PI587980A IV 3.1 0.84 PI417404 V 2.1 0.83 PI253658C I 3.1 0.73 PI458285 V 2.1 0.43 PI566966B IX 3.2 1.00 PI307860 IX 2.2 0.42 PI605846C IV 3.2 0.46 PI307882E IX 2.2 0.79 PI587671 VII 3.3 0.50 PI424448 V 2.2 0.44 PI561372 V 3.3 1.04 PI561387 V 2.2 0.37 PI561290 V 3.3 1.08 PI423773 VI 2.2 0.83 PI506666 V 3.4 0.52 PI507263 VI 2.3 0.83 PI507275 V 3.4 0.28 PI509099 V 2.3 0.69 PI561380 VI 3.4 0.27 PI358316C 0 2.3 0.43 PI605804B IV 3.4 0.44 PI509101 V 2.3 0.33 PI603784 IV 3.4 0.34 PI434976 IX 2.3 0.84 PI424182B VI 3.6 0.72 PI567171 00 2.4 0.81 PI592915 00 3.6 0.38 PI239484 IX 2.4 0.28 PI605846A IV 3.8 0.14 PI408311-2 V 2.4 0.68 PI438461 00 3.9 0.59 PI423875 V 2.4 0.15 PI423799C V 3.9 0.17 PI507117B VI 2.5 0.21 PI509109 V 4.1 0.33 PI424183 V 2.5 0.54 PI424269B V 4.1 0.19 PI424446 V 2.5 0.31 PI605842B IV 4.1 0.29 PI567107A VIII 2.6 0.18 PI549074 00 4.3 0.50 PI587998C IV 2.7 0.62 Spencer§ IV 4.4 0.22 PI398343 V 2.7 0.55 PI423760 V 4.6 0.41 PI290156 000 2.8 0.51 PI567121A VIII 4.9 0.29

PI603706B IV 2.8 0.51

§ Susceptible check.

79 Table 2.3. Mean foliar severity by country of origin of 127 PIs in advanced germplasm screening (tier VI) over four replications.

Foliar Origin N severity Germany 1 1.0 Russia 1 1.2 Nepal 2 1.4 Thailand 7 1.4 Burundi 1 1.4 Malaysia 2 1.5 India 17 1.5 Tanzania 2 1.6 Israel 1 1.7 Philippines 3 1.7 France 1 1.8 Moldova 1 2.0 Japan 20 2.2 Nigeria 1 2.3 Poland 2 2.5 Korea 26 2.6 China 23 2.6 Hungary 1 2.8 Indonesia 6 2.9 Vietnam 5 3.3 Taiwan 1 3.3 Romania 1 3.9 USA 1‡ 4.4

† Foliar severity was rated using a 1-8 scale, where 1 = no symptoms, 2 = general slight yellowing and/or chlorotic flecks or blotches, 3 = distinct pattern of interveinal chlorosis, 4 = necrosis along a portion of leaf margin (generally, leaf has necrosis in addition to symptoms described in “3”), 5 = necrosis along the entire margin of a leaf, 6 = interveinal necrosis, >50% of leaf area is necrotic, 7 = defoliation of at least one leaflet, 8 = dead plant.

‡ Susceptible check.

80 Table 2.4. Mean foliar and root severity as well as percent of the non-inoculated control for shoot, root and total dry weight for 20 soybean plant introductions (PIs) and four checks (Forrest,

Ripley, Spencer, and PI 567374), 25 days after planting and inoculating with Fusarium virguliforme.

Mean percent of non-inoculated control weight§ Maturity Mean foliar Std Mean root PI Group severity† error severity‡ Shoot†† Root†† Total†† Spencer IV 5.5A 0.25 3.3 40H 36CDE 37G PI 567210 000 3.6B 0.25 2.8 47GH 38CDE 40FG Ripley IV 3.4BC 0.25 2.8 60DEFG 33DE 42EFG PI 467320 I 3.0BCD 0.25 3.0 59DEFG 35CDE 44DEFG PI 567105 VIII 3.0BCD 0.28 3.1 71BCDEF 46BCDE 55CDEF Forrest V 2.8CD 0.25 2.9 61DEFG 45BCDE 54CDEF PI 281911B IX 2.5DE 0.25 2.5 70BCDEF 37CDE 50CDEFG PI 506552 V 2.3DEF 0.25 3.3 73BCDE 40CDE 54CDEF PI 307882B IX 2.1EFG 0.25 3.2 57EFG 47BCD 49CDEFG PI 307856 IX 2.0EFG 0.25 2.5 56FGH 31DE 40FG PI 507545 V 2.0EFG 0.26 3.2 71ABCDE 36CDE 51CDEFG PI 507568 VII 2.0EFG 0.25 2.6 80ABC 60AB 71AB PI 594696B IV 1.9EFG 0.25 2.8 68BCDEF 51BC 59BC PI 205901B IX 1.8EFGH 0.25 2.9 67BCDEF 40CDE 52CDEFG PI 232997 00 1.7FGH 0.25 2.5 75ABCD 40CDE 58BCD PI 279081 VII 1.7FGH 0.28 3.2 82AB 61AB 72AB PI 307892 IX 1.7FGH 0.25 2.8 66CDEF 39CDE 49CDEFG PI 407785 V 1.7FGH 0.25 2.6 63DEFG 29E 41EFG PI 445683 VII 1.7FGH 0.25 2.6 64DEF 44BCDE 49CDEFG PI 567374 IV 1.7FGH 0.25 2.7 60DEFG 32DE 44DEFG PI 497953 X 1.6GH 0.25 3.2 68BCDEF 41CDE 52CDEFG PI 506743 VI 1.6FGH 0.26 3.1 70BCDEF 40CDE 55CDE PI 307847 IX 1.5GH 0.25 2.7 71BCDEF 51BC 61BC PI 506757 V 1.2H 0.25 2.4 89A 73A 80A Overall mean 2.3 2.8 66 43 52

† Levels not followed by same letter are significantly different P ≤ 0.0001. Foliar severity was rated using a 1-8 scale, where 1 = no symptoms, 2 = general slight yellowing and/or chlorotic flecks or blotches, 3 = distinct pattern of interveinal chlorosis, 4 = necrosis along a portion of leaf margin (generally, leaf has necrosis in addition to symptoms described in “3”), 5 = necrosis along the entire margin of a leaf, 6 = interveinal necrosis, >50% of leaf area is necrotic, 7 = defoliation of at least one leaflet, 8 = dead plant. ‡ Not significant; percent of necrosis visible on roots per plot, was rated 1-5 where :1=0-19%; 2=20-39%; 3=40-59%; 4=60-79%; 5=80-100% damage. § Inoculated dry weight (g)/non-inoculated dry weight (g) x 100. ††P ≤ 0.05

81 Table 2.5. Correlations coefficients of foliar severity and root severity, and percent of the non- inoculated control root, shoot and total weights, in a selected set of partially resistance soybean plant introductions (n=24, including checks) that were inoculated with Fusarium virguliforme.

Root Shoot Root Total severity†‡ weight‡§ weight‡§ weight‡§

Foliar severity¶ NS -0.7*** NS -0.5* Root severity NS NS NS Shoot weight 0.7** 0.9*** Root weight 0.9***

† Root severity refers to necrosis visible on roots per plot and was rated 1-5 where :1=0-19%; 2=20-39%; 3=40-59%; 4=60-79%; 5=80-100% damage.

‡ NS = not significant; *, **, and *** indicate P ≤ 0.01, 0.001, and 0.0001, respectively.

§ All weight variables were the percent of the non-inoculated control, computed as inoculated dry weight (g)/non- inoculated dry weight (g) x 100, respectively, for shoot, root, and total weight.

¶ Foliar severity was rated using a 1-8 scale, where 1 = no symptoms, 2 = general slight yellowing and/or chlorotic flecks or blotches, 3 = distinct pattern of interveinal chlorosis, 4 = necrosis along a portion of leaf margin (generally, leaf has necrosis in addition to symptoms described in “3”), 5 = necrosis along the entire margin of a leaf, 6 = interveinal necrosis, >50% of leaf area is necrotic, 7 = defoliation of at least one leaflet, 8 = dead plant.

82 Table 2.6. Mean foliar severity and the percent of the non-inoculated control for shoot, root and total dry weights for 36 soybean plant introductions (PIs), representing all soybean maturity groups (MG) and MG classes, and four soybean checks 25 days after planting and inoculating with Fusarium virguliforme.

Mean percent of the non- Mean foliar Std MG inoculated control weight¶ PI† severity‡ Error MG class§ Shoot Root Total Spencer 5.1 0.09 IV mid 30 36 31 PI 561377 3.2 0.02 II mid 54 72 58 PI 423940* 2.9 0.50 II mid 42 61 46 PI 468382 2.9 0.10 0 early 56 54 55 PI 507531* 2.9 0.30 II mid 54 84 61 Cordell 2.7 0.20 V mid 44 55 47 PI 567171 2.7 0.15 00 early 54 52 53 PI 567105 2.6 1.08 VIII late 44 66 50 PI 290156 2.5 0.30 000 early 49 58 51 LS94-3207 2.3 0.43 IV mid 49 50 50 PI 437934A 2.3 0.75 I early 40 58 45 PI 445683 2.3 0.75 VII late 54 77 60 PI 458021* 2.3 0.75 IV mid 55 46 52 PI 307882E 2.2 0.17 IX late 59 90 69 PI 374192B 2.2 0.50 X late 45 69 52 PI 393535* 2.2 0.40 III mid 75 87 78 PI 408311-2 2.2 0.83 V mid 40 66 47 PI 587998C 2.2 0.35 IV mid 54 75 60 PI 518711* 2.1 0.58 II mid 84 78 82 PI 612742 2.1 0.88 II mid 75 82 77 PI 082278* 2.0 1.00 III mid ND†† ND†† ND†† PI 243530* 1.9 0.27 IV mid 93 93 93 PI 416748* 1.8 0.20 II mid 46 62 51 PI 594401C 1.8 0.20 III mid 63 96 72 PI 175188 1.5 0.50 VII late 64 86 70 PI 205911 1.5 0.00 VIII late ND†† ND†† ND†† PI 358316C 1.5 0.25 0 early 59 66 60 PI 423740* 1.5 0.50 IV mid 62 61 61 PI 603712 1.5 0.30 0 early 50 52 50 PI 205090 1.4 0.40 000 early 61 90 68 PI 205901B 1.4 0.20 IX late 50 70 56 PI 088310* 1.3 0.10 III mid 59 67 62 PI 253658C 1.3 0.10 I early 46 45 46 PI 423936* 1.3 0.33 III mid 54 85 64 PI 567374 1.3 0.05 IV mid 60 72 63 PI 243518* 1.2 0.00 IV mid 50 75 57 PI 232997 1.2 0.20 00 early 55 53 54 PI 281893 1.0 0.00 X late 87 88 87 PI 467320 1.0 0.00 I early 37 51 41 PI 497953 1.0 0.00 X late 62 74 65 Overall mean 2.0 0.34 56 69 59

† Selected for lower foliar disease severity in tier V testing unless noted; *selected from Mueller et al. 2002.

83 Table 2.6. (cont.)

‡ Not significant; Foliar severity was rated using a 1-8 scale, where 1 = no symptoms, 2 = general slight yellowing and/or chlorotic flecks or blotches, 3 = distinct pattern of interveinal chlorosis, 4 = necrosis along a portion of leaf margin (generally, leaf has necrosis in addition to symptoms described in “3”), 5 = necrosis along the entire margin of a leaf, 6 = interveinal necrosis, >50% of leaf area is necrotic, 7 = defoliation of at least one leaflet, 8 = dead plant.

§ MG classes were designated early (MG 000-I), mid (MG II-IV) and late (VII-X)

¶ Not significant; inoculated dry weight (g)/non-inoculated dry weight (g) x 100.

†† ND = no data due to insufficient plant number.

84 Table 2.7. Correlation coefficients of foliar severity and percent of the non-inoculated control root, shoot and total weight variables in an experiment evaluating soybean plant introductions

(n=40) from 13 maturity groups (MGs) inoculated with Fusarium virguliforme.

Shoot Root Total weight†‡ weight†‡ weight†‡

Foliar severity§ -0.36* NS -0.39* Shoot weight 0.66*** 0.97*** Root weight 0.90***

† NS = non-significant, and *, **, and *** indicate P ≤ 0.05, 0.001, and 0.0001 respectively

‡ All weight variables were the percent of the non-inoculated control, computed as inoculated dry weight (g)/non- inoculated dry weight (g) x 100, respectively, for shoot, root, and total weight.

§ Foliar severity was rated using a 1-8 scale, where 1 = no symptoms, 2 = general slight yellowing and/or chlorotic flecks or blotches, 3 = distinct pattern of interveinal chlorosis, 4 = necrosis along a portion of leaf margin (generally, leaf has necrosis in addition to symptoms described in “3”), 5 = necrosis along the entire margin of a leaf, 6 = interveinal necrosis, >50% of leaf area is necrotic, 7 = defoliation of at least one leaflet, 8 = dead plant.

85 Table 2.8. Mean foliar severity and the percent of the non-inoculated control for shoot, root and total dry weights for early, mid and late maturity group (MG) classes, MG 000-I, II-IV, VII-X, respectively, 25 days after planting and inoculating with Fusarium virguliforme.

Mean percent of the non-inoculated control weight† Mean MG foliar class‡ severity§¶ Shoot¶ Root†† Total †† Late 1.7 63 84A 69A Mid 2.0 60 74A 64A Early 1.8 51 58B 52B

† Inoculated [dry weight (g)/non-inoculated dry weight (g)] x 100.

‡ MG classes were designated early (MG 000-I), mid (MG II-IV) and late (VII-X)

§ Foliar severity was rated using a 1-8 scale, where 1 = no symptoms, 2 = general slight yellowing and/or chlorotic flecks or blotches, 3 = distinct pattern of interveinal chlorosis, 4 = necrosis along a portion of leaf margin (generally, leaf has necrosis in addition to symptoms described in “3”), 5 = necrosis along the entire margin of a leaf, 6 = interveinal necrosis, >50% of leaf area is necrotic, 7 = defoliation of at least one leaflet, 8 = dead plant.

¶ Not significant.

†† Levels not connected by same letter are significantly different P ≤ 0.05.

86 Table 2.9. Mean foliar severity for a set of 350 plant introductions (PIs) evaluated for resistance to F. virguliforme in two replications.

Foliar Std Foliar Std PI MG Severity Error PI (cont.) MG Severity Error PI587588B V 1.0 0.67 PI324924 V 2.5 0.47 PI567238 IX 1.0 0.53 PI549028 V 2.6 0.57 PI507017 VII 1.2 0.50 PI578493 II 2.6 0.47 PI068732_1 III 1.4 0.67 PI587804 IV 2.6 0.47 PI497953 X 1.4 0.50 PI594880 V 2.6 0.47 PI475820 II 1.5 0.53 PI274453 X 2.6 0.47 PI561318A I 1.6 0.50 PI603675 III 2.6 0.45 PI567074B IX 1.6 0.53 PI437500A I 2.7 0.50 PI424078 III 1.7 0.50 PI081041 III 2.7 0.47 PI567408 V 1.7 0.61 PI532463B III 2.7 0.47 PI593953 I 1.7 0.47 PI548479 VIII 2.7 0.47 PI438347 VII 1.7 0.47 PI567604A IV 2.7 0.57 PI561389B 0 1.8 0.53 PI507467 IV 2.8 0.50 PI549018 V 1.8 0.50 PI567439 V 2.8 0.50 PI468908 000 1.9 0.53 PI548582 00 2.8 0.47 PI458510 III 1.9 0.47 PI417529 0 2.8 0.47 PI548171 III 2.0 0.67 PI464923 I 2.8 0.47 PI068521_1 III 2.0 0.50 PI507293B III 2.8 0.47 † PI567374 IV 2.1 0.12 PI549017 IV 2.8 0.47 PI438083 II 2.1 0.47 PI391583 II 2.8 0.61 PI548411 II 2.1 0.57 PI567435B III 2.9 0.50 PI587811A VIII 2.2 0.47 PI468408B III 2.9 0.47 PI361080 II 2.2 0.50 PI561387 V 2.9 0.47 PI578375B I 2.3 0.45 PI587712B V 2.9 0.47 PI567418A II 2.3 0.47 PI095860 VI 2.9 0.47 PI437814A II 2.4 0.53 PI504288 V 2.9 0.45 PI372403B 00 2.4 0.47 PI437240 0 3.0 0.87 PI342619A 0 2.4 0.47 PI407701 I 3.0 0.87 PI084946_2 IV 2.4 0.47 PI437485 II 3.0 0.53 PI592937 IV 2.4 0.47 PI603555 IV 3.0 0.47 PI209333 VI 2.4 0.47 PI086904 VI 3.0 0.50 PI068604_1 III 2.5 0.47 PI322692 IX 3.0 0.45 (cont.)

† Partially resistant check.

87 Table 2.9. (cont.) Std Std PI MG Mean Error PI (cont.) MG Mean Error PI240664 X 3.0 0.50 PI054614 IV 3.4 0.50 PI424038B V 3.1 0.45 PI180501 0 3.5 0.47 PI291294 I 3.1 0.47 PI548561 I 3.5 0.53 PI086972_2 IV 3.1 0.47 PI088313 II 3.5 0.47 PI165563 VII 3.1 0.47 PI437662 II 3.5 0.47 PI497967 VII 3.1 0.47 PI437793 II 3.5 0.47 PI261272C IX 3.1 0.47 PI597471A VII 3.5 0.47 PI567343 V 3.1 0.50 PI594307 VIII 3.5 0.47 PI437695A I 3.1 0.57 PI497964A IX 3.5 0.53 PI612754 I 3.2 0.47 PI594456A III 3.6 0.50 PI437838 II 3.2 0.47 PI506862 IV 3.6 0.50 PI578412 II 3.2 0.47 PI639559B II 3.6 0.57 PI548256 VII 3.2 0.47 PI639543 I 3.6 0.47 PI603722 VIII 3.2 0.47 PI054608_1 II 3.6 0.47 PI548383 III 3.3 0.53 PI437112A II 3.6 0.47 PI567410B VII 3.3 0.53 PI549041A III 3.6 0.47 PI548524 I 3.3 0.47 PI087620 III 3.6 0.47 PI054615_1 III 3.3 0.47 PI479735 III 3.6 0.47 PI253661B III 3.3 0.47 PI342434 V 3.6 0.47 PI507458 IV 3.3 0.47 PI548571 I 3.6 0.53 PI567426 IV 3.3 0.50 PI612730 II 3.6 0.45 PI548427 IV 3.3 0.50 PI628963 VII 3.6 0.45 PI297520 0 3.4 0.53 PI083881 IV 3.7 0.61 PI548360 II 3.4 0.47 PI437160 I 3.7 0.47 PI578499A II 3.4 0.47 PI467347 II 3.7 0.47 PI490766 III 3.4 0.47 PI597476 V 3.7 0.47 PI062203 V 3.4 0.47 PI379618 V 3.7 0.47 PI548978 VI 3.4 0.57 PI089005_5 II 3.7 0.57 PI179935 VII 3.4 0.57 PI567383 V 3.7 0.57 PI417242 II 3.4 0.50 PI437505 II 3.7 0.45 PI153231 III 3.4 0.50 PI574477 IV 3.7 0.45 PI549021A III 3.4 0.50 PI628812 VI 3.7 0.45 (cont.)

88 Table 2.9. (cont.) Std Std PI MG Mean Error PI (cont.) MG Mean Error PI632650 VI 3.7 0.45 PI189873 0 4.1 0.47 PI559932 IV 3.8 0.53 PI437991B 0 4.1 0.47 PI567262A II 3.8 0.50 PI416751 I 4.1 0.47 PI436684 III 3.8 0.50 PI417479 IV 4.1 0.47 PI561371 IV 3.8 0.50 PI567489A IV 4.1 0.47 PI438500 III 3.8 0.47 PI628913 VII 4.1 0.47 PI567416 IV 3.8 0.67 PI464896 I 4.1 0.50 PI592940 IV 3.8 0.67 PI567558 III 4.1 0.50 PI561701 IV 3.8 0.47 PI090486 III 4.1 0.50 PI578309 VI 3.8 0.47 PI603397 IV 4.1 0.50 PI567171 00 3.9 0.50 PI081785 III 4.2 0.45 PI592952 III 3.9 0.50 PI088468 II 4.2 0.47 PI549040 IV 3.9 0.50 PI423926 IV 4.2 0.47 PI548473 VII 3.9 0.50 PI507480 IV 4.2 0.47 PI592523 00 3.9 0.47 PI548696 V 4.2 0.47 PI578504 II 3.9 0.47 PI291309D II 4.2 0.50 PI603549 III 3.9 0.47 PI391577 II 4.2 0.50 PI070466_3 IV 3.9 0.47 PI438336 0 4.3 0.53 PI094159_3 IV 3.9 0.47 PI232992 III 4.3 0.53 PI398633 V 3.9 0.47 PI567415A IV 4.3 0.53 PI445824A 000 4.0 0.47 PI567780B IV 4.3 0.53 PI631123 0 4.0 0.75 PI438335 III 4.3 0.57 PI438239B I 4.0 0.47 PI424195A 0 4.3 0.47 PI603345 II 4.0 0.53 PI578503 I 4.3 0.47 PI437685D III 4.0 0.50 PI438112B III 4.3 0.47 PI548178 III 4.0 0.50 PI548198 III 4.3 0.47 PI438496B III 4.0 0.47 PI171451 VII 4.3 0.47 PI507180 IV 4.0 0.47 PI548474 VIII 4.3 0.47 PI092651 IV 4.0 0.47 PI404187 II 4.3 0.87 PI602993 IV 4.0 0.47 PI548356 II 4.3 0.50 PI166105 VII 4.0 0.50 PI084631 III 4.3 0.61 PI639550E II 4.1 0.45 PI437127A IV 4.3 0.50 (cont.)

89 Table 2.9. (cont.) Std Std PI MG Mean Error PI (cont.) MG Mean Error PI548162 IV 4.3 0.50 PI602502B IV 4.5 0.47 PI567488A IV 4.3 0.50 PI548447 VIII 4.5 0.47 PI603162 IV 4.3 0.50 PI374207 X 4.5 0.61 PI632418 V 4.3 0.50 PI606374 III 4.5 0.45 PI548169 IV 4.4 0.53 PI548521 II 4.6 0.50 PI360957 00 4.4 0.47 PI430595 IV 4.6 0.50 PI291310C II 4.4 0.47 PI567407 V 4.6 0.50 PI597464 II 4.4 0.47 PI378680E I 4.6 0.47 PI091100_3 III 4.4 0.47 PI084637 II 4.6 0.47 PI538386A III 4.4 0.47 PI054591 III 4.6 0.47 PI080837 IV 4.4 0.47 FC031697 IV 4.6 0.47 PI171428 IV 4.4 0.47 PI495020 IV 4.6 0.47 PI542972 VII 4.4 0.47 PI548520 II 4.6 0.53 PI417215 VIII 4.4 0.47 PI476352B II 4.6 0.53 PI416838 V 4.4 0.57 PI123440 VI 4.6 0.45 PI603463 II 4.4 0.50 PI361093 I 4.7 0.50 PI084973 III 4.4 0.50 FC029333 III 4.7 0.50 PI058955 IV 4.4 0.50 PI603559 IV 4.7 0.50 PI548452 V 4.4 0.50 PI154189 0 4.7 0.47 PI153281 0 4.5 0.45 PI417381 0 4.7 0.47 PI639528B II 4.5 0.45 PI437265D 0 4.7 0.47 PI361070 0 4.5 0.47 PI361066B I 4.7 0.47 PI438309 I 4.5 0.53 PI567782 I 4.7 0.47 PI372418 I 4.5 0.47 PI548200 IV 4.7 0.47 PI548313 III 4.5 0.47 PI567685 IV 4.7 0.47 PI088788 III 4.5 0.47 PI083942 V 4.7 0.47 PI593258 III 4.5 0.47 PI603495B V 4.7 0.47 PI209332 IV 4.5 0.47 PI159925 VIII 4.7 0.47 PI398965 IV 4.5 0.47 PI567788 VIII 4.7 0.47 PI464912 IV 4.5 0.47 PI070080 III 4.8 0.53 PI548619 IV 4.5 0.47 PI548193 IV 4.8 0.53 PI567352A IV 4.5 0.47 PI603458A IV 4.8 0.50 (cont.)

90 Table 2.9. (cont.) Std Std PI MG Mean Error PI (cont.) MG Mean Error PI548400 IV 4.8 0.50 PI603488 III 5.1 0.47 PI548633 IV 4.8 0.50 PI090763 IV 5.1 0.47 PI514671 0 4.8 0.47 PI090479P IV 5.1 0.47 PI548336 I 4.8 0.47 PI437376A I 5.1 0.50 PI458505 II 4.8 0.47 PI540552 II 5.1 0.50 PI578495 IV 4.8 0.47 PI567576 III 5.1 0.50 PI567746 IV 4.8 0.47 PI567307 IV 5.1 0.50 PI587588A IV 4.8 0.47 PI417500 VIII 5.1 0.50 PI567226 00 4.8 0.61 PI567346 V 5.1 0.57 PI266806C II 4.9 0.53 PI567225 0 5.2 0.47 PI592960 I 4.9 0.50 PI548316 III 5.2 0.47 PI567173 00 4.9 0.47 PI103088 III 5.2 0.47 PI407708A 0 4.9 0.47 PI556511 III 5.2 0.47 PI438019B II 4.9 0.47 PI567698A IV 5.2 0.47 PI506942 II 4.9 0.47 PI518727 VI 5.2 0.47 PI603497 III 4.9 0.47 PI592954 II 5.2 0.50 PI548359 IV 4.9 0.47 PI567361 III 5.2 0.50 PI603494 IV 4.9 0.47 PI089772 IV 5.2 0.50 PI548572 I 5.0 0.53 PI549026 V 5.2 0.50 PI437788A II 5.0 0.50 PI603526 IV 5.3 0.75 PI437654 III 5.0 0.50 PI438496C IV 5.3 0.53 ‡ PI437110A III 5.0 0.47 Spencer IV 5.3 0.12 PI437776 III 5.0 0.47 PI361087 I 5.3 0.47 PI597478B III 5.0 0.47 PI438230A I 5.3 0.47 PI603492 IV 5.0 0.61 PI603426G II 5.3 0.47 PI417345B IV 5.0 0.53 PI437956B II 5.3 0.47 PI548364 IV 5.0 0.47 PI603399 II 5.3 0.47 PI567428 IV 5.0 0.47 PI548656 VI 5.3 0.47 PI071465 V 5.0 0.57 PI567231 VIII 5.3 0.47 PI598358 V 5.0 0.47 PI518668 IV 5.3 0.50 PI165675 VII 5.0 0.47 PI091159_4 IV 5.3 0.50 PI084656 III 5.1 0.47 PI567726 IV 5.3 0.50 (cont.)

‡ Suceptible check.

91 Table 2.9. (cont.) Std Std PI MG Mean Error PI (cont.) MG Mean Error PI407742 V 5.3 0.50 PI089775 VI 5.6 0.50 PI605765B I 5.4 0.53 PI091160 III 5.6 0.47 FC033243 IV 5.4 0.53 PI548658 VI 5.6 0.47 PI378658 0 5.4 0.47 PI603698J 0 5.6 0.45 PI297505 I 5.4 0.47 PI603442 III 5.7 0.50 PI603389 II 5.4 0.47 PI507471 III 5.7 0.50 PI603556 III 5.4 0.47 PI567532 IV 5.7 0.50 PI639570 VIII 5.4 0.47 PI437165A I 5.7 0.57 PI594922 V 5.4 0.50 PI567353 IV 5.7 0.57 PI378663 I 5.5 0.47 PI594170B I 5.8 0.53 PI567525 II 5.5 0.47 PI548325 00 5.8 0.67 PI548402 IV 5.5 0.47 PI507088 VI 5.8 0.47 PI417581 V 5.5 0.47 PI548490 VII 5.9 0.50 PI567548 IV 5.5 0.45 PI438323 I 5.9 0.47 PI603290 I 5.6 0.50 PI506933 IV 6.0 0.47 PI209334 III 5.6 0.50 PI567675 IV 6.3 0.47 Overall mean 4.0 0.50

92 Table 2.10. Number of entries by maturity group (MG) in a set of 350 plant introductions (PIs); observed number and expected number of PIs by MG with mean foliar severity at two threshold levels, lower than 2.0 and 3.0, and chi-square values by MG for each subset.

Mean score† < 2.0 Mean score† < 3.0 Chi- Chi- MG N‡ n Expected§ n Expected§ square square 0 2 1 0 9 1 0 1 00 8 0 0 0 2 1 0 000 21 1 1 0 3 3 0 I 37 2 2 0 5 6 0 II 53 1 2 1 8 9 0 III 64 3 3 0 12 10 0 IV 83 0 4 4 6 14 4 V 32 3 1 2 10 5 4 VI 13 0 1 1 2 2 0 VII 16 2 1 2 2 3 0 VIII 12 0 1 1 2 2 0 IX 5 2 0 14 2 1 2 X 4 1 0 4 2 1 3 Total 350 16 36¶ 57 16††

† Foliar severity was rated using a 1-8 scale previously described (Chawla et al. 2013), where 1 = no symptoms, 2 = general slight yellowing and/or chlorotic flecks or blotches, 3 = distinct pattern of interveinal chlorosis, 4 = necrosis along a portion of leaf margin (generally, leaf has necrosis in addition to symptoms described in “3”), 5 = necrosis along the entire margin of a leaf, 6 = interveinal necrosis, >50% of leaf area is necrotic, 7 = defoliation of at least one leaflet, 8 = dead plant.

‡ Total number of entries per group in set.

§ Expected value is computed as total selected/total entries in set x number of entries per MG, 16/350 = 0.05 for mean < 2.0; 57/350 = 0.16 for mean < 3.0.

¶ P £ .0003 at alpha .01.

†† Not significant at alpha .10.

93

Fig. 2.1. Foliage and roots infected with sudden death syndrome. Soybean PI roots inoculated (top left) and non-inoculated (top center) and characteristic soybean sudden death syndrome leaf symptom (top right); variable reactions of soybean seedlings to inoculation in a sudden death syndrome layer test (bottom).

94 Summary of Testing

Preliminary I. 10,144 PIs -- 150 test flats II. 5440 PIs -- 80 test flats III. 2752 PIs – 41 test flats IV. 1193 PIs – 18 test flats V. 720 PIs – 36 test flats

Advanced VI. 127 PIs – 24 test flats

VII. 20 PIs – 12 test flats

Fig. 2.2. Progression of testing 10,144 plant introductions (PIs), showing number of PIs per tier and number of test flats (26 x 92 x 130 cm heavy duty flats with holes). Preliminary non- replicated testing comprised tiers I-IV, which included 72 single plants per flat, and tier V, which included 24 plots of 5 plants each (20 PIs and 4 checks) per flat. Advanced testing comprised tier VI with 24 plots of 5 plants each (22 PIs and 2 checks) per flat, in four replications and tier VII, 24 plots of 5 plants each (22 PIs and 2 checks) per flat, in twelve replications.

95 VII VI 8% VIII 14% 9%

IX 7% 000 1% 00 Other 5% 9% II V 1% 23% III X 1% 0 1% 10%

IV I 5% 15%

Fig. 2.3. Maturity group (MG), from MG 000 – MG X, of 10,144 plant introductions from the

USDA Soybean Germplasm Collection not previously screened for reaction to F. virguliforme.

96 Vietnam Asia - other 8% 15% South Korea Europe Eurasia… 13% 8% Other South 7% America Japan 2% 16% Africa North 2% America, China Australia, 33% Unknown 1%

Fig. 2.4. Countries of origin of 10,144 plant introductions from the USDA Soybean Germplasm

Collection not previously screened for reaction to F. virguliforme.

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101 CHAPTER 3: EVALUATION OF WILD PERENNIAL GLYCINE SPECIES FOR

RESISTANCE TO SOYBEAN CYST NEMATODE AND SOYBEAN RUST1

ABSTRACT

The genetic base for soybean [Glycine max (L.) Merr.] cultivars is narrow compared to most other crop species. Twenty-seven wild perennial Glycine species comprise the tertiary gene pool to soybean that may contain many genes of economic importance for soybean improvement.

We evaluated 16 accessions of G. argyrea, G. clandestina, G. dolichocarpa, and G. tomentella for resistance to Heterodera glycines (HG), also known as the soybean cyst nematode (SCN), and to multiple isolates of Phakopsora pachyrhizi, the causal fungus of soybean rust. All 16 accessions were classified as resistant to H. glycines HG Type 2.5.7, based on number of cysts per root mass with plant introductions (PIs) 483227, 509501, 563892, and 573064 (all G. tomentella) void of any cysts indicating no reproduction by this pest. All 16 accessions had an immune reaction to one isolate of P. pachyrhizi. Sporulating uredinia of any of the P. pachyrhizi isolates were not observed on G. argyrea (PI 505151) and G. tomentella (PIs 483227, 509501, and 573064). These results demonstrate that some accessions within the perennial Glycine species harbor resistance to both H. glycines and P. pachyrhizi and would be good candidates for wide hybridization programs seeking to transfer potentially unique multiple resistance genes into soybean.

______

1Accepted for publication as “Herman, T. K., Han, J., Singh, R. J., Domier, L. L., and Hartman, G. L. 2020. Evaluation of wild perennial Glycine species for resistance to soybean cyst nematode and soybean rust. Plant Breeding 0:1-9. doi: https://doi.org/10.1111/pbr.12834” and reprinted with the permission of the publisher. Table 3.2 was contributed by Mr. Jae Yeong Han.

102 INTRODUCTION

To improve soybean [Glycine max (L.) Merr.] resistance to biotic stresses, soybean breeders are confined to utilizing germplasm in the primary gene pool (Chung and Singh 2008) consisting of G. max and G. soja Sieb. and Zucc. The genetic base for soybean cultivars is extremely narrow because of the small number of contributing ancestors pointed out by studies done in North America (Delannay et al. 1983; Gizlice et al. 1994; Cui et al. 2001), Brazil

(Miranda et al. 2001), China (Cui et al. 2000), India (Satyavathi et al. 2006), and Japan (Zhou et al. 2000).

Wild perennial Glycine species belong to the G. max tertiary gene pool (Harlan and deWet 1971) with one new species recently added (Barrett & Barrett 2015) making 27 species in this group. Indigenous to Australia and various Pacific islands, these species are morphologically distinct, adapted to diverse agro-climatic conditions, and may harbor genes of economic importance for soybean (Singh 2019). Evaluations of accessions of perennial Glycine species for useful disease and pest resistance traits have focused on resistance to important diseases affecting soybean, including those caused by fungi, nematodes, and viruses. For example, accessions of perennial Glycine species were reported to be resistant to alfalfa mosaic virus

(Horlock et al. 1997), bean pod mottle virus (Zheng et al. 2005), brown spot (Septoria glycines

Hemmi) (Lim and Hymowitz 1987), powdery mildew caused by Erysiphe diffusa (Cooke &

Peck) U. Braun & S. Takam. (Mignucci and Chamberlain 1978), soybean cyst nematode

(Heterodera glycines Ichinohe; SCN) (Bauer et al. 2007; Riggs et al. 1998; Wen et al. 2017b), soybean rust (Phakopsora pachyrhizi Syd.) (Burdon and Marshall 1981; Hartman et al. 1992), and with partial resistance to Sclerotinia stem rot (Sclerotinia sclerotiorum (Lib.) de Bary) and sudden death syndrome (Fusarium virguliforme O’Donnell & T. Aoki) (Hartman et al. 2000).

103 There have been several large evaluations of accessions of perennial wild Glycine species for resistance to SCN and soybean rust. Riggs et al. (1998) reported that 12 accessions from 9 perennial Glycine species were resistant to four races of H. glycines. Bauer et al. (2007) reported that 56% of 491 accessions representing 12 perennial Glycine species were highly resistant or immune to HG Type 0. Evaluating 282 perennial accessions from 13 species against several HG types, Wen et al. (2017b) reported high levels of resistance, including 16 accessions that showed no SCN reproduction when inoculated with HG Type 1.2.3.4.5.6.7.

One of the earliest studies to evaluate perennial Glycine species for resistance to the leaf rust fungus, P. pachyrhizi, was conducted by Burdon and Marshall (1981) in Australia. They found variable reactions against P. pachyrhizi among 189 accessions in six Glycine species with resistant reactions noted in accessions of four species tested. Hartman et al. (1992) in Taiwan identified 23% of 294 accessions representing 12 perennial Glycine species as resistant to P. pachyrhizi.

The objective of this study was to confirm and further evaluate 16 accessions, representing four perennial Glycine species, for resistance to SCN HG Type 2.5.7 and isolates of

P. pachyrhizi. These accessions have not been tested to SCN HG Type 2.5.7. and not to the specific isolates of P. pachyrhizi used in this study. Some of the 16 accessions were found to contain resistance to both SCN and P. pachyrhizi and their virulence variants.

MATERIALS AND METHODS

Plant materials

Seeds of 16 PIs from four perennial Glycine species were obtained from the USDA

Soybean Germplasm Collection in Urbana, Illinois (https://www.ars-grin.gov/). Test material

104 included 11 entries from Glycine tomentella Hayata, two entries from G. clandestina Wendl. and

G. argyrea Tindale, and one entry from G. dolichocarpa Tateishi and Ohashi. The soybean cv.

‘Williams 82’ served as the susceptible check in both SCN and rust evaluations (Table 3.1).

Pathogen isolates

A SCN population of HG Type 2.5.7 was used for SCN evaluations. Based on a revised classification scheme (Niblack et al. 2002) this HG type overcomes resistance in PI 88788 (the source of resistance available in more than 95% of currently available SCN-resistant soybean cultivars; Tylka and Mullaney, 2015), PI 209332, and PI 448316. Prior to testing, the pathogen had been continuously maintained and then increased on ‘Williams 82’ at 28°C under a 16-hr photoperiod in a growth chamber. SCN cysts were harvested for testing (Riggs and Schmitt

1991). Briefly, infected roots were rinsed thoroughly with water over a #20 (850-µ mesh) sieve and onto #60 (250-µ mesh) sieve to separate debris and collect cysts. To extract eggs, cysts were transferred to a #100 (150-µ mesh) sieve nested over #200 (75-µ mesh) and #500 (25-µ mesh) sieves. Cysts were crushed using a rubber stopper and rinsed through the nested sieves to collect eggs and remove any remaining debris. The egg suspension was centrifuged, and the supernatant was poured off. The remaining eggs and liquid were re-suspended and transferred gently using a pipette onto 30 ml of 45.4% sucrose solution in a 50 ml centrifuge tube. The tube was centrifuged for about 5 minutes at 2500 rpm to separate debris to the bottom and leave eggs visible above the sucrose layer. The sucrose suspension was poured through the #500 (25-µ mesh) sieve and washed with water to harvest eggs from the top of the sieve into a 50 ml centrifuge tube; the concentration of eggs was adjusted to 2,000 eggs/ml for immediate use in plant inoculation.

105 Because reactions to P. pachyrhizi can be isolate specific, we used a panel of isolates of

P. pachyrhizi for rust evaluation that included isolates from Ethiopia (ETH14), Florida (FL07-1),

Malawi (MAL14 and MAL19), and Tanzania (TZ14). The number associated with the isolate name refers to the year of collection. Isolates collected in 2014 were obtained from -80°C storage. To revive these isolates, frozen microtubes were immersed in a 39°C water bath for 1 minute and contents were mixed with .02% Tween 20 in distilled water to enable dispersal onto detached soybean leaflets. FL07-1 and MAL19 had been in continuous maintenance on detached leaflets. All isolates were increased on soybean ‘Williams 82’ before inoculating experimental material.

Planting and experimental design

Seeds of Glycine species were scarified with a sharp razor blade opposite the hilum and placed in Petri dishes on moistened paper towels for a week at 25°C in a growth chamber. One week after scarification, germinated seeds were transplanted 1 cm deep in SC10 Cone-tainers

(Stuewe and Sons, Tangent, Oregon) filled with sterilized torpedo sand. One seed was transplanted per Cone-tainer. To synchronize developmental stages, seeds of ‘Williams 82’ were sown in Cone-tainers one week prior to inoculation. Entries and check plants were then arranged in a completely randomized design in a growth chamber (Percival PCG-105; Percival Scientific

Inc., Perry, IA) set at 28°C and a 16-hr photoperiod and fertilized weekly with a 100 ppm solution of general purpose fertilizer (Peter’s Professional 20-20-20; Hummert International,

Earth City, MO). All plants were inoculated with SCN three weeks after transplanting. Leaflets were excised from plants 50 days after planting (DAP) for use in rust reaction testing as described below.

106 SCN inoculation and cyst counts

Plants were inoculated with 2,000 SCN eggs 3 weeks after transplanting by pipetting 1 ml of egg suspension (2,000 eggs/ml water) into a 2.5-cm deep hole made 1.5 cm away from each plant. Inoculated plants were incubated in a growth chamber at 28°C and 16-h photoperiod for 35 days when the plant roots were removed from Cone-tainers and cysts were extracted, as previously described, prior to enumeration. Washed roots were kept in 50 ml tubes and weighed.

Cysts extracted from each plant were counted using a Leica M205 FA (Leica Microsystems Inc,

Buffalo Grove, IL) fluorescence stereo microscope at ×20 magnification. The tests were conducted twice with two replications for the first test and five replications for the second.

Adjusted female index (AFI) was determined based on five replications in the second run and was calculated as follows: mean number of females on tested plants per root fresh weight (g) / mean number of females on ‘Williams 82’ per root fresh weight (g) × 100 (Wen et al., 2017b).

Resistant and susceptible reactions were classified as follows: AFI 0-10 = resistant; AFI 11-30 = moderately resistant; AFI 31-60 = moderately susceptible; AFI 61 or greater = susceptible.

Rust inoculation and evaluations

At 50 DAP, leaves were excised from plants grown for the SCN experiment. Plants had variable amount of vegetative growth, but all plants had more than five trifoliolate leaves.

Leaflets from fully expanded trifoliolates in the middle canopy were selected. Two leaflets from each PI were removed from different plants for testing against each isolate. Leaflets were placed on top of a double layer of moistened filter paper in glass Petri dishes, abaxial side up, and with the excised end of each leaflet secured under moist cotton (Fig. 3.1). Leaflets were arranged in a randomized complete block, with two replications per PI per isolate, and with material blocked by replication. Each Petri dish had a different randomization and each replication included one

107 leaflet from each entry. Spores of each isolate were rinsed from freshly sporulating detached leaflets of cultivar Williams 82 and were adjusted to a concentration of 1 x 104 spores/ml in distilled water and 0.02% Tween 20. Inoculum was applied with a hand mister until leaflets of test accessions were evenly saturated. Tests of each isolate were separate experiments and two replications of each PI per isolate were placed together in a transparent plastic box and incubated in the dark overnight in a chamber set at 22°C day/night. Leaves were incubated thereafter at

22°C under a 14-hr photoperiod. This experiment was conducted once.

Responses of the PIs to P. pachyrhizi were noted in terms of reaction type and counts of lesions and sporulating uredinia with the aid of a stereo microscope (Olympus SZX16; Olympus

Corp., Tokyo). Reaction type to infection by P. pachyrhizi as described on soybean was used

(Bromfield et al. 1980): susceptible genotype = tan-color, highly sporulating lesions (TAN), resistant genotype = either reddish-brown (RB) lesions with little, if any sporulation (0-2 uredinia), or a complete lack of visible signs or symptoms described as Type 0 and also known as an immune reaction (IM) (Miles et al. 2006). Reaction type for all entries per isolate was recorded and observations were made as soon as symptoms appeared, starting at 13 days after inoculation, and continuing every other day until 21 days after inoculation. The number of lesions and the number of sporulating uredinia were counted in a 1-cm-diameter circle (0.785 cm2) identified as the most severely affected leaf area. Number of lesions, number of sporulating uredinia, and sporulating uredinia per lesion for each PI were analyzed by isolate using JMP Fit

Model and excluding Williams 82. Entries with no symptoms or no uredinia were considered completely resistant.

108 RESULTS

SCN evaluation

All of the 16 entries were identified as resistant to HG 2.5.7 with AFIs less than 10

(Table 3.2). Four entries of G. tomentella (PI 483227, PI 509501, PI 563892, and PI 573064) had no cyst reproduction in either of two runs. The mean number of cysts over two runs on ‘Williams

82’ was 259 cysts per plant.

Rust evaluation

The susceptible check, ‘Williams 82’, had a TAN reaction and abundant sporulation when inoculated with all isolates (Tables 3.3 and 3.4). In addition, PI 446996, PI 446998, PI

505286, and PI 563892 had a TAN reaction to three, two, two, and one isolate, respectively

(Table 3.3; Fig. 3.1). All PIs had an IM reaction to isolate MAL19 and had either IM or RB reactions for the rest of the isolates except those mentioned above with TAN. Additionally, 7 of the 80 interactions were not classified according to the Bromfield et al. (1980) classification because of lesion color aberrations that included dark brown and black lesion colors.

Number of lesions, number of sporulating uredinia, and sporulating uredinia per lesion on the 16 perennial Glycine accessions inoculated with five isolates of P. pachyrhizi were significantly different among the entries for FL07-1 but not the other isolates except for ETH14 for uredinia per lesion only (Table 3.4). For susceptible ‘Williams 82’, lesion numbers ranged from 9 to 23, sporulating uredinia from 20 to 39, and uredinia per lesion from 1.0 to 2.2. For isolate FL07-1, lesion number (P < 0.0052) ranged from 0.5 (PI 573074) to 15.0 (PI 505151) and sporulating uredinia (P < 0.0001) ranged from 0 (PI 505151, PI 339657, PI 441008, PI 483227,

PI 505235, PI 509501 and PI 573064) to 25.5 (PI 509451). Sporulating uredinia per lesion for isolates FL07-1 and ETH14 ranged from 0 to 1.9 (P < 0.0001) and 0 to 2.1 (P < 0.0032),

109 respectively. For isolates FL07-1 and ETH14, six and five accessions, respectively, had higher than 0 sporulating uredinia per lesion.

Four isolates, ETH14, TZ2014, MAL2014, and MAL2019, did not differ for mean number of lesions or mean number of sporulating uredinia over accessions, and results were combined for presentation (Table 3.4). Response of PIs to these isolates shows mean lesion number ranging from 0 to 3.8 and mean number of sporulating uredinia ranging from 0 to 6.3.

While isolate MAL19 was the most recently collected isolate used in our study, none of the accessions tested were susceptible to this isolate, although ‘Williams 82’ was fully susceptible

(Tables 3.3 and 3.4). It is not known if this isolate overcomes any of the known Rpp resistance genes in soybean. Two other isolates, MAL14 and TZ14, were associated with TAN and IM reaction types. Similar isolates to these collected from the same location and year, caused a susceptible TAN reaction on plants with Rpp1 and Rpp4, and a resistant reaction on plants with

Rpp1b, Rpp2 or Rpp3 (Murithi at al., 2017). The isolate FL07-1, maintained continuously on detached leaves since 2007, was associated with one TAN reaction (PI 446996) while isolate

ETH14, stored for over three years at -80°C, was associated with the most TAN reactions (PI

446996, 446998, and 505286).

DISCUSSION

Wild relatives closely related to cultivated crops can provide novel genetic resources to enhance desirable traits in crop plants that are often needed due to the loss of genetic diversity during domestication (Munoz et al. 2017; Smykal et al. 2015). The 27 perennial Glycine species consists of a diverse group of wild plants that survive in many niches primarily in Australia

(Sherman-Broyles et al. 2014). Unlike other crops where wide hybridization has occurred to

110 bring in genes from wild relatives of crop species (Hajjar & Hodgkin 2007), this has been a difficult process in soybean using perennial Glycine species (Chung and Singh 2008). In recent years, wide hybridization in the genus Glycine was successful in producing derived fertile lines selected to avoid undesirable traits from the Glycine species, such as stem vining, stem lodging, lack of complete leaf abscission and seed shattering (Singh 2019). Specifically, there has been some successful hybridizations among a few soybean cultivars and PI 441001 (G. tomentella; 2n

=78) resulting in amphidiploid (2n = 118) plants (Singh, 2010). By backcrossing with ‘Dwight’ fertile 2n = 40, 41, 42 chromosome plants have been isolated in the BC3-BC6 generations (Singh and Nelson 2014; Singh and Nelson 2015). Some progeny from this cross were resistant to soybean rust, and it was hypothesized that resistance was transferred from PI 441001 since

Dwight has no known rust resistance (Singh 2019).

To expand the utility of perennial Glycine species in soybean improvement, additional efforts will need to focus on enhancing exchanges between perennial Glycine and soybean chromosomes. In wheat (Triticum aestivum L.), deletion of the Ph1 gene has facilitated recombination between homoeologous domestic and wild chromosomes. In dicotyledonous plants, silencing of a putative Ph1 homologue in Arabidopsis thaliana produced relaxation in the stringency of chromosome pairing, which led to the formation of multivalents similar to those observed in wheat Ph1 deletion lines (Bhullar et al. 2014). If expression of soybean genes involved in regulating chromosome pairing could be altered in hybrids between perennial and annual Glycine species, the frequencies of genetic exchange could be significantly enhanced (Qi et al. 2017).

With the presumptive success of transferring rust resistance from G. tomentella (PI

441001), there was interest to test or re-test more accessions of perennial Glycine species so that

111 selected parents used for crosses with soybean may have SCN and P. pachyrhizi resistance. We evaluated 16 accessions representing G. argyrea, G. clandestina, G. dolichocarpa, and G. tomentella for resistance to SCN HG Type 2.5.7 and to five isolates of P. pachyrhizi. All entries were classified as resistant to SCN HG Type 2.5.7. Previously, these PIs were reported to have a high to moderate level of resistance to various HG types (Riggs et al. 1998; Bauer et al. 2007;

Wen et al. 2017b) but these 16 had not been tested to HG Type 2.5.7. Our results confirm that these 16 accessions have a high level of resistance and would be good parental sources with potential resistance to multiple HG types. There could be syntenic regions similar to the syntenic region we found in common bean for SCN resistance that was associated with the Rgh1 locus in soybean (Wen et al. 2019).

While SCN has not been reported to date in Australia or Papua New Guinea, other plant parasitic nematodes including Rotylenchulus reniformis, Meloidogyne incognita, M. javanica, and M. halpa occur in various locations in Australia, including in the coastal areas where the accessions were collected (Stirling, 2007). In addition, over 60 species of plant parasitic nematodes, including Heterodera spp., have been reported in Papua New Guinea (Bridge 1988;

Bridge and Paige 1984). Further investigations into understanding the development of the high level of resistance shown in the perennial accessions to SCN is warranted.

Evaluation of the 16 accessions for resistance to P. pachyrhizi showed a range of reaction types that included TAN, RB, and IM. Eleven of the accessions did not produce a susceptible reaction type, while five accessions had both a susceptible and resistant reaction that was isolate dependent. There were six reactions that had lesion color variants that were previously described on hosts other than soybean (Slaminko et al. 2008) or on soybean genotypes that were further divided into six color classes from dark to light (Yamanaka et al. 2010). Previously, PI 446998

112 (G. dolichocarpa), 505151 (G. argyrea), and 509501 (G. tomentella) were reported resistant to

P. pachyrhizi (Hartman et al. 1992). In our test, PI 446998 was resistant to two out of the five isolates, while PIs 505151 and 509501 were resistant to all the isolates. PIs 483227 and 573064, both G. tomentella, are reported here as resistant to P. pachyrhizi for the first time.

Of the 16 accessions used in our study, 14 were from Australia and two were from Papua

New Guinea. These few accessions are not great enough to make any inference about accession origin and reaction to rust, although out of the four accessions that had a differential response

(resistance versus susceptibility), two of them were from Papua New Guinea. Schoen et al.

(1992) found no association of resistance to ploidy level among 163 G. tomentella accessions but noted a greater number of rust susceptible accessions from Western Australia and the Northern

Territory along with the Townsville/Cairns region of Queensland.

While previous studies have reported resistance to P. pachyrhizi in perennial Glycine accessions (Burdon and Marshall 1981; Hartman et al. 1992), the results of our study show potentially new sources of resistance to multiple P. pachyrhizi isolates. Pham et al. (2009) reported on the differential response of soybean entries to ten isolates of P. pachyrhizi and demonstrated the importance of using a panel of isolates for characterizing material of interest for breeding. Similarly, our results show variable responses of perennial Glycine species to P. pachyrhizi isolates and confirms the importance of using a panel of isolates for evaluating

Glycine species for sources of resistance. FL07-1 has been shown to cause TAN reactions on plants with Rpp1b, Rpp4, Rpp5b and Rpp6 and isolates from Africa have produced TAN reactions on Rpp1 and Rpp4. Regardless of the geographic origin of the isolates, the panel of isolates used in our study was, as a group, broadly challenging the known rust resistance genes in

113 soybean. Additional studies utilizing isolates that can overcome all known resistance genes in soybean will further elucidate the potential usefulness of the perennial accessions.

Along with reaction type other characteristics, like fungal sporulation, also are used to quantify resistance. In our study, most of the accessions had lower amounts of sporulation than

‘Williams 82’ with a few exceptions. Sporulation is probably one of the most important traits after infection that should be quantified since a rust epidemic depends on abundant sporulation

(Wen et al. 2017a). There are many factors that affect sporulation, like leaf age and microenvironment, making measurements of this trait only reliable under controlled conditions.

In our study, many of the accessions allowed no or very little sporulation. Accessions with an immune response should be the focus for transfer to soybean making sporulation a non-issue.

Genome comparisons between G. max and its legume relatives revealed extensive regions of conserved gene order among legume species (Cannon et al. 2009; Young et al. 2011).

Comparative mapping between G. max and G. latifolia (Benth.) Newell and Hymowitz showed that 12 chromosomes were highly collinear between the two species, but eight chromosomes displayed inter-chromosomal exchanges (Chang et al. 2014). Through this approach, genome- wide comparisons and phylogenetic relationships between G. max and perennial Glycine species have been studied (Chang et al. 2013, 2014; Sherman-Broyles et al. 2017). Since then, a complete draft genome assembly of G. latifolia was reported (Liu et al. 2018) that will be useful to identify, isolate, and validate promising genes for improvement of agronomic traits in soybean.

Because of the genetic relationship between G. max and the perennial Glycine species, it may be possible to alter genes using sequence information and CRISPR-Cas9 gene-editing technologies (Sun et al. 2015) to bypass genetic hybridization barriers. Furthermore, AgRenSeq

114 (Arora et al. 2019), a rapid gene cloning technique that exploits resistance genes from wild crop relatives for incorporation into crop species, could be used to enable transfer of resistance from perennial Glycine species to elite soybean lines. Using gene expression studies and transcriptome analysis of resistant and susceptible genotypes of G. tomentella, Soria-Guerra et al. (2010ab) reported that the predominant defense-related transcripts were chitanes and of the differentially expressed genes, those likely to be involved in rust resistance were associated with the flavonoid biosynthesis pathway or were coding for peroxidases and lipoxygenases. These and other genes would serve as good candidates for transfer by AgRenSeq which aims to transfer useful genes with reduced linkage drag and without the need for multiple backcrosses to eliminate undesirable traits associated with transfer through wide hybridization. More research in this area could increase the usefulness of traits found in the perennial Glycine species beyond what has been done so far in traditional wide hybridization programs, and knowledge about novel genes in wild relatives like Glycine perennial species will become more useful as gene transfer technologies develop.

115 TABLES AND FIGURE

Table 3.1. Accessions of perennial Glycine spp. with previous resistant (R) or susceptible (S) rating based on the literature to Heterodera glycines (soybean cyst nematode; SCN) and

Phakopsora pachyrhizi (soybean rust).

Previous disease reaction Plant Chromo- SCN§ Rust¶ Glycine spp. Accession Origin† Name‡ some # G. argyrea PI 505151 Queensland G1420 40 R R

PI 509451 Queensland G1622 40 R -

G. clandestina PI 509457 New South Wales G1500 40 R -

PI 509468 Queensland G1664 40 R -

G. dolichocarpa PI 441005†† Queensland G1188 80 R MR

G. tomentella PI 339657 New South Wales G1139 78 R S

PI 441008 New South Wales G1437 78 R R

PI 446996 Papua New Guinea G1367 78 R -

PI 446998 Papua New Guinea G1432 40 R R

PI 483219 Australia G1927 80 R‡‡ -

PI 483227 New South Wales G1292 80 R -

PI 505235 Queensland G1822 78 R -

PI 505286 Western Australia G1945 78 R -

PI 509501 New South Wales G1487 78 R R

PI 563892 New South Wales G2305 78 R -

PI 573064 Queensland G2328 38 R -

G. max ‘Williams 82’ USA N/A 40 S‡‡ S§§

† Australia unless otherwise stated.

‡ Alternative (original) identity number in USDA GRIN (https://www.ars-grin.gov/) when first catalogued.

116 Table 3.1. (cont.)

§ Reported by Bauer et al. (2007) using HG Type 0; PI 505151 and PI 441005 also reported by Riggs et al. (1998); and reported by Wen et al. (2017b) except PI 441008 was not tested, PI 446998 and PI 483219 were rated moderately resistant to HG Type 0, and PI 441005 was rated moderately resistant to HG 2 and HG 1.2.3

¶ Field tested in Taiwan (Hartman et al., 1992), except for PI 509501 (Chang et al., 2010).

†† Previously G. tomentella.

‡‡ Wen et al., 2017a.

§§ Miles et al., 2011.

117 Table 3.2. Accessions of perennial Glycine species evaluated for their response to Heterodera glycines HG Type 2.5.7 35 days after inoculation.

Glycine spp. Accession Mean cyst† AFI‡

G. argyrea PI 505151 0.9 0.91

PI 509451 0.3§ 0.28

G. clandestina PI 509457 0.6 1.32

PI 509468 0.8§ 0.95

G. dolichocarpa PI 441005 0.4 0.79

G. tomentella PI 339657 0.3 0.00

PI 441008 0.1 0.22

PI 446996 0.4 0.54

PI 446998 1 0.00

PI 483219 2§ 1.81

PI 483227 0 0.00

PI 505235 0.3 0.00

PI 505286 0.4 0.13

PI 509501 0 0.00

PI 563892 0 0.00

PI 573064 0 0.00

G. max ‘Williams 82’ 259.4 100

† Means based on two runs with two replications in the first and five replications in the second.

‡ Adjusted female index (AFI): mean number of females on tested plants per root fresh weight (g) / mean number of females on ‘Williams 82’ per root fresh weight (g) × 100. AFI 0-10 = resistant; AFI 11-30 = moderately resistant;

AFI 31-60 = moderately susceptible; AFI 61 or greater = susceptible. AFI was determined based on five replications in the second run.

§ Mean computed for second run only; no emergence in run one.

118 Table 3.3. Reaction types† of 16 perennial Glycine species accessions 21 days after inoculation with Phakopsora pachyrhizi.

Isolates

Glycine spp. Accession‡ ETH14 FL07-1 MAL14 MAL19 TZ14

G. argyrea PI 505151 ND ND IM IM ND

PI 509451 ND RB RB IM ND

G. clandestina PI 509457 ND RB RB IM ND

PI 509468 IM ND IM IM IM

G. dolichocarpa PI 441005 RB RB RB IM IM

G. tomentella PI 339657 RB RB IM IM IM

PI 441008 RB RB IM IM IM

PI 446996 TAN TAN RB IM TAN

PI 446998 TAN RB TAN IM IM

PI 483219 RB RB IM IM RB

PI 483227 RB RB RB IM RB

PI 505235 RB RB IM IM IM

PI 505286 TAN RB TAN IM IM

PI 509501 RB RB RB IM IM

PI 563892 RB RB RB IM TAN

PI 573064 IM RB IM IM IM

G. max ‘Williams 82’ TAN TAN TAN TAN TAN

† Reactions types based on Bromfield et al. (1980) on soybean genotypes with tan-colored, highly sporulating lesions (TAN), reddish-brown (RB) lesions with little, if any sporulation (0-2 uredinia), or complete lack of visible signs or symptoms described as Type 0 also known as an immune reaction (IM) (Miles et al., 2006). ND = not determined to fit into reaction type scheme, but color variants of B = black or DB = dark brown and not TAN or RB.

‡ Based on 10 leaflets for each accession except for ‘Williams 82’ had 5 leaflets.

119 Table 3.4. Mean number of lesions, sporulating uredinia and sporulating uredinia per lesion on leaves of 16 perennial Glycine accessions 21 days after inoculation with five isolates of

Phakopsora pachyrhizi.

Isolates ETH14, MAL14, MAL19, FL07-1 ETH14 and TZ14

Plant Uredinia Uredinia Species introduction Lesions† Uredinia† /lesion /lesion Lesions† Uredinia† G. argyrea PI 505151 15.0A‡ 0.0D 0.0C 0.0C 0.6 0.0

PI 509451 14.0AB 25.5A 1.8A 1.3AB 0.9 2.0

G. clandestina PI 509457 4.0CD 6.0BCD 1.5AB 0.3BC 1.0 2.4

PI 509468 1.0CD 1.5D 1.5 AB 0.0C 0.0 0.0

G. dolichocarpa PI 441005 7.5BC 3.0CD 0.4C 0.7BC 3.8 1.6

G. tomentella PI 339657 2.0CD 0.0D 0.0C 0.3BC 1.1 0.3

PI 441008 3.0CD 0.0D 0.0C 0.3BC 1.0 0.1

PI 446996 6.5CD 10.0B 1.5AB 2.1A 4.0 6.3

PI 446998 7.5BC 9.0BC 1.2B 1.1AB 1.9 2.4

PI 483219 14.0AB 2.0D 0.1C 0.0C 0.9 0.0

PI 483227 5.0CD 0.0D 0.0C 0.0C 1.9 0.0

PI 505235 5.0CD 0.0D 0.0C 0.4BC 1.0 0.3

PI 505286 6.0CD 2.5D 0.4C 1.3AB 0.5 0.5

PI 509501 1.5CD 0.0D 0.0C 0.0C 2.3 0.0

PI 563892 4.5CD 5.5BCD 1.2B 2.1A 1.8 3.6

PI 573064 0.5D 0.0D 0.0C 0.0C 1.5 0.0

G. max ‘Williams 82’§ 9.0 20.0 2.2 1.0 22.5 39.3

† Per 1-cm diameter circle (0.785 cm2) of the leaf surface.

‡ Levels not connected by same letter within a column are significantly different at α = 0.05.

§ Excluded from analysis of all parameters.

120

c d e c d e f f g b h b a

i h a j

k

k j g i

Fig. 3.1. Center: Sixteen accessions representing four Glycine species showing different reaction types surrounding the susceptible soybean cultivar ‘Williams 82’ showing TAN reaction when inoculated with Phakopsora pachyrhizi isolate FL07-1. Outer: The same accessions (indicated by matching letters) showing a variety of reactions types to isolate FL07-1.

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125 CHAPTER 4: CONCLUSION

Host resistance is the most sustainable, environmentally-friendly, and economical method of reducing crop damage to disease. Though occurrence of diseases and pests affecting soybean has increased as production of the crop has expanded around the world, damage due to disease and pest issues has the potential to be curtailed. Sudden death syndrome of soybean, soybean rust, and infection by nematodes, caused by fungal pathogens F. virguliforme and P. pachyrhizi, and the plant-parasitic nematode, H. glycines, respectively, are three major yield-limiting problems, that are among those that can be addressed through increased host resistance. Lack of partially resistant cultivars, in the case of SDS, and lack of durable genetic resistance to organisms that have high genetic variability, in the case of SBR and cyst nematode, can be mitigated through efforts to find, understand, and incorporate new sources of resistance into soybean germplasm.

My study investigated over 10,000 soybean accessions for resistance to sudden death syndrome, caused by Fusarium virguliforme, and found numerous sources of foliar resistance in a range of maturity groups, adaptable to wide geographic regions where the disease has been reported. These sources of resistance may also prove useful as sources of resistance to other

Fusarium species causing sudden death syndrome. In addition to providing sources of resistance for soybean breeders, an expanded set of resistant lines can play a critical role in further investigations into the nature of the resistance in soybean, and for studies that seek to understand of the host-pathogen interaction, including interactions with other pathogens of soybean that produce toxins.

126 Crop wild relatives are important sources of genetic diversity for domesticated crops, but are still not well investigated and are yet to be widely utilized. My study evaluated perennial wild relatives of soybean, and found accessions that are resistant to both SCN and to multiple isolates of SBR. These accessions are candidates for programs seeking to transfer multiple resistance genes into soybean via wide hybridization or molecular breeding methods. While obstacles still exist to readily incorporating potential resistance genes from Glycine perennial relatives into soybean, advancing gene transfer technologies are likely to make utilization of these novel genes a common reality.

Finally, plant germplasm resources are curated around the world and my study was made possible by the resources curated in the USDA Soybean Germplasm Collection, housed at the

University of Illinois, Urbana, IL. The discovery of resistance to three important yield-limiting pathogens demonstrates that efforts to preserve the physical and informational resources of the collection are important and consequential to improving crop germplasm and sustaining agricultural production.

127