DIVERSITY OF THE FUNGAL PATHOGEN RHIZOCTONIA SOLANI AG2 - 2 By Douglas H. Minier A THESIS Submitted to Michigan State University in partial fulfillment of the requirements for the degree of Plant Pathology - Master of Science Ecology, Evolutionary Biology and Behavior - Dual Major 2019 ABSTRACT DIVERSITY OF THE FUNGAL PATHOGEN RHIZOCTONIA SOLANI AG2 - 2 By Douglas H. Minier Rhizoctonia solani AG2 - 2 is a diverse group of fungi that ca n cause disease on several economically important c rops including sugar beet ( Beta vulgaris ) and dry bean ( Phaseolus vulgaris ). Three projects were conducted to help improve understanding of the diversity within the AG2 - 2 complex. The first project examined the virulence of 44 R. solani AG2 - 2 isolates on d ry b eans at both the seedling and adult growth stages. Disease severity ranged from 0.81 to 6.00 for seedlings and from 1.35 to 3.48 on adult plants where 0 = no disease and 6 = plant dead. Isolates in phylogenetic group 1 were, on average, more aggressiv e at both growth stages. The second project tested the abili ty of R. solani AG2 - 2 to cause disease on sugar beets Our results indicate that some isolates can cause considerable disease at temperatures as low as , which is well below the previo usly stated minimum of . Disease severity at , where 0 = no disease and 5 = plant dead. The third project involved development of a set of microsatellite markers for R. solani AG2 - 2. Ten microsatellite loci were identified that were able to distinguish 20 unique genotypes among the 23 representative isolates tested. Groupings based on microsatellite distances largely agree d with the multigene phylogeny of Martin et al. (2014). Overall , R. solani AG2 - 2 is a h ighly diverse gro up and research that examines issues related to host response need to consider this variability . Additionally, knowledge of diversity may be useful in predict ing the risk of disease in the field and assist in management decisions such as crop rotation. iii To my Mom iv ACKNOWLEDGMENTS I would like to take this opportunity to thank my major professor, Dr. Linda Hanson, for her patience and support through this process. I would also like to thank the other members of my guidance committee, Dr. Martin Chilvers and Dr. Greg Bonito for their encouragement and willingness to help me through this process . I also appreciate the help and support I received from my fellow lab mates, Tom Goodwill, Qianwei (Jane) Jiang, Hailey Haist , and Celeste Dmytryszyn as we ll as many others. Finally, I want to express my appreciation to my family for their understanding and support the last several years as I pursue a major career change. I realize that this journey has not been easy and I am very grateful for your sacrifice . v TABLE OF CONTENTS LIST OF TABLES ................................ ................................ ................................ ...................... viii LIST OF FIGURES ................................ ................................ ................................ ....................... x KEY TO ABBREVIATIONS ................................ ................................ ................................ ......... xii CHAPTER 1: REVIEW OF LITERATURE ................................ ................................ ...................... 1 Introduction ................................ ................................ ................................ ....................... 2 History of the G enus Rhizoctonia ................................ ................................ ................ 2 Classification of Rhizoctonia solani ................................ ................................ .............. 4 Separation of Rhizocton ia solani Subgroups by Anastomosis Reaction ...................... 8 Categorization of Anastomosis Reactions ................................ ................................ . 12 Classification of AG2 ................................ ................................ ................................ .. 16 Bridging Reactions ................................ ................................ ................................ ...... 17 Anastomosis Group Cultural Types ................................ ................................ ............ 18 Cultural Types of AG2 - 2 ................................ ................................ ............................. 19 Pathogenicity and Host Range ................................ ................................ ................... 20 Methods of Identification ................................ ................................ ................................ 21 Introduction to Identification ................................ ................................ .................... 21 Obtaining Pure Cultures ................................ ................................ ............................. 2 1 Nuclear Staining ................................ ................................ ................................ ......... 22 Anastomosis Testing ................................ ................................ ................................ .. 24 rDNA - ITS Sequencing ................................ ................................ ................................ . 27 Diver sity of the Anastomosis Group 2 - 2 ................................ ................................ .......... 29 Problems with Traditional AG2 - 2 Subgroup Designations ................................ ........ 29 Classification Proposed by Martin et al. (2014) ................................ ......................... 29 Objectives ................................ ................................ ................................ ......................... 30 APPENDIX ................................ ................................ ................................ ............................... 32 REFERENCES ................................ ................................ ................................ ........................... 3 5 CHAPTER 2: VIRULENCE OF RHIZOCTONIA SOLANI AG2 - 2 ISOLATES ON DRY BEAN ( PHASEOLUS VULGARIS ) ................................ ................................ ............................ 4 3 Introduction ................................ ................................ ................................ ..................... 4 4 Objectiv es ................................ ................................ ................................ ......................... 4 9 Methods ................................ ................................ ................................ ........................... 50 Results ................................ ................................ ................................ .............................. 5 5 Discussion ................................ ................................ ................................ ......................... 62 Conclusions ................................ ................................ ................................ ...................... 6 7 REFERENCES ................................ ................................ ................................ ........................... 6 8 vi CHAPTER 3: VARIABILITY IN THE VIRULENCE OF RHIZOCTONIA SOLANI AG2 - 2 ISOLATES ON SUGAR BEET SEEDLINGS IN RESPONSE TO LOW TEMPERATURE ........................ 7 4 Introduction ................................ ................................ ................................ ..................... 75 Objectives ................................ ................................ ................................ ......................... 80 Methods ................................ ................................ ................................ ........................... 80 Selection of AG2 - 2 Isolates ................................ ................................ ........................ 80 Preparation of Inoculum ................................ ................................ ............................ 82 Analysis of the Virulence of AG2 - 2 Isolates on Sugar Beet Seedlings ....................... 82 Growth Rate of AG2 - 2 Isolates in vitro ................................ ................................ ....... 84 Results ................................ ................................ ................................ .............................. 8 5 Selection of Isolates ................................ ................................ ................................ ... 8 5 Virule nce of AG2 - 2 Isolates on Sugar Bee t Seedlings at ...................... 85 Virulence of AG2 - 2 Isolates Related to Sub - groups IIIB and IV ................................ . 91 Growth Rate of AG2 - 2 Isolates in vitro ................................ ................................ ...... 91 Relationship between Growth Rate, Temperature and Virulence ............................ 9 4 Discussion ................................ ................................ ................................ ......................... 9 6 Conclusions ................................ ................................ ................................ .................... 100 APPENDIX ................................ ................................ ................................ ............................. 101 REFER ENCES ................................ ................................ ................................ ......................... 103 CHAPTER 4: IDENTIFICATION AND VALIDATION OF MICROSATELLITE MARKERS FOR USE IN RHIZOCTONIA SOLANI AG2 - 2 POPULATON ANALYSIS ................................ ......... 10 8 Introduction to Microsatellites ................................ ................................ ...................... 10 9 Mutational Mechanisms ................................ ................................ .......................... 110 Mutation Models ................................ ................................ ................................ ..... 1 13 Microsatellite Applicati ons ................................ ................................ ...................... 11 5 Drawbacks to Microsatellite Markers ................................ ................................ ...... 11 6 Narrow Taxonomic Range ................................ ................................ .................. 11 6 Hidden Allelic Diversity ................................ ................................ ...................... 11 7 Null Alleles ................................ ................................ ................................ .......... 1 20 Mitigating Scoring Errors ................................ ................................ ................... 1 21 Objectives ................................ ................................ ................................ ....................... 1 23 Methods ................................ ................................ ................................ ......................... 1 23 In - Silico Identification and Evaluation of Potential Loci ................................ .......... 1 23 DNA Extraction ................................ ................................ ................................ ......... 1 24 PCR Amplification and Marker Evaluation ................................ ............................... 12 6 Data Analysis ................................ ................................ ................................ ............ 12 9 Results ................................ ................................ ................................ ............................ 1 30 In - Silico Identification of Potential Loci ................................ ................................ ... 1 30 PCR Amplification and Marker Evaluation ................................ ............................... 1 31 Data Analysis ................................ ................................ ................................ ............ 1 32 Discussion ................................ ................................ ................................ ....................... 1 41 Concl usions ................................ ................................ ................................ .................... 14 9 APPENDIX ................................ ................................ ................................ ............................. 150 vii REFERENCES ................................ ................................ ................................ ......................... 1 52 viii LIST OF TABLES Table 1.1 Summary of terminology and descriptions used to define categories of anastomosis reactions in Rhizoctonia solani ................................ ......................... 10 Table 1.2 Historic groupings of Rhizoctonia solani based on hyphal anastomosis reactions ................................ ................................ ................................ ................ 11 Table 1.3 Currently recognized AG and cultural types ................................ .......................... 15 Table 1.4 Anastomosis groups with bridging capability ................................ ........................ 18 Table 2.1 Disease severity of 36 Rhizoctonia solani AG2 - 2 isolates on the dry bean variety RedHawk ................................ ................................ ................................ .... 52 Tab le 2.2 Disease severity of 8 international Rhizoctonia solani AG2 - 2 isolates on the dry bean variety RedHawk ................................ ................................ .................... 53 Table 3.1 Rhizoctonia solani AG 2 - 2 isolates used in the current study ................................ 81 Table 3.2 Mean disease severity scores of 35 Rhizoctonia solan i AG2 - 2 isolates on sugar ................................ ................................ .............. 8 6 Table 3.3 Growth rate of 24 Rhizoctonia solani AG2 - ................... 92 Table 4.1 Twenty - three isolates of Rhizoctonia solani AG2 - 2 used in the current study ... 12 5 Table 4.2 Micros atellite loci evaluated in the current study for use on Rhizoctonia solani AG2 - 2 ................................ ................................ ..................... 12 8 Table 4.3 Results of NextGen sequencing and assembly for three isolates of Rhizoctonia solani AG2 - 2 ................................ ................................ ..................... 1 31 Table 4.4 Microsatellite alleles detected in 23 Rhizoctonia solani AG2 - 2 isolates ............. 1 33 Table 4.5 Scoring errors for the 13 microsatellite loci evaluated in the current study ....... 13 5 Table 4.6 Pairwise distances of 23 Rhizoctonia solani AG2 - 2 isolates based on 13 microsatelli te loci ................................ ................................ ........................... 13 7 Table 4.7 Simpson diversity index by group for 23 Rhizoctonia solani AG2 - 2 isolates ....... 13 9 ix Table 4.8 Genotypic differentiation (exact G test) for each population pair of Rhizoctonia solani AG2 - 2 ................................ ................................ ..................... 13 9 Table 4.9 Genic differentiation (exac t G test) for each population pair of Rhizoctonia solani AG2 - 2 ................................ ................................ ..................... 1 40 Table 4.10 Cost comparison for Illumina sequencing and microsatellite analysis .............. 1 42 Table 4.11 Hypothetical polymorphism information content (PIC) values for loci with a diffe ring number of alleles and frequencies ................................ ....................... 14 6 Table 4.8 Genotypic differentiation (exact G test) for each population pair of Rhizoctonia solani AG2 - 2 ................................ ................................ ..................... 13 9 Table 4.9 Genic differentiation (exact G test) for each population pair of Rhizoctonia s olani AG2 - 2 ................................ ................................ ..................... 1 40 Table 4.10 Cost comparison for Illumina sequencing and microsatellite analysis .............. 1 42 Table 4.11 Hypothetical polymorphism information content (PIC) values for loci with a differing number of alleles and frequencies ................................ ....................... 14 6 x LIST OF FIGU RES Figure 1.1 Micrographs of characteristic structures of Rhizoctonia solani ............................. 7 Figure 1.2 Micrographs of Rhizoctonia solani hyphae showing stained nuclei ..................... 2 3 Figure 1.3 Schematic illustrating the organization of ribosomal RNA genes in fungi ........... 28 Fi gure A1.1 Neighbor - joining tree from Carling et al. (2002b) ................................ .............. 33 Figure A1.2 Multigene phylogeny of 63 Rhizoctonia solani AG2 - 2 isolates according to Martin et al. (2014) ................................ ................................ ........ 34 Figure 2.1 Comparison of phylogenetic groups when inoculated at planting ....................... 5 6 Figure 2.2 Distribution of disease severity scores when inoculated at planting ................... 5 6 Figure 2.3 Side - by - side boxplot comparison of phylogenetic groups when inoculated at planting ................................ ................................ ................................ ................ 5 7 Figure 2.4 Comparison of phylogenetic groups when inoculated 14 day s after planting ..... 5 8 Figure 2.5 Distribution of disease severity scores when inoculated 14 days after planting ................................ ................................ ................................ ........ 5 9 Figure 2.6 Side - by - side boxplot comparison of phylogenetic groups when inoculated 14 days after planting ................................ ................................ .......................... 5 9 Fig ure 2.7 Comparison of phylogenetic groups for international isolates ............................ 60 Figure 2.8 Scatterplot comparing disease severity on dry bean when inoculated at planting and at 14 days after planting ................................ ................................ . 61 Figure 2.9 Comparison of disease severity by traditiona l subgroups AG2 - 2IIIB and AG2 - 2IV ................................ ................................ ................................ ................ 64 Figure 3.1 Sugar beet seedlings in various stages of decay from Rhizoctonia solani AG2 - 2 infection ................................ ................................ ...... 7 6 Figure 3.2 Disease severity of 35 Rhizoctonia solani AG2 - 2 isolates on sugar bee t ................................ .............................. 8 7 xi Figure 3.3 Disease severity of 35 Rhizoctonia solani AG2 - 2 isolates on sugar beet ................................ ................ 8 8 Figure 3.4 Average disease severity of 35 Rhizoctonia solani AG2 - 2 isola tes on sugar ................................ ....... 8 9 Figure 3.5 Proportion of 35 Rhizoctonia solani isolates in each virulence category ................................ ............................. 90 Figure 3.6 Average growth rate of 24 Rhizoct onia solani AG2 - 2 isolates by phylogenetic ................................ ............................... 93 Figure 3.7 Scatterplots comparing growth rate and virulence of Rhizoctonia solani AG2 - ................................ .............. 9 5 Figure 3.8 Proportion of plants in each disease severity category ................................ ........ 9 7 Figure A3.1 Multigene phylogeny of 63 Rhizoctonia solani AG2 - 2 isolates according to Martin et al. (2014) ................................ ................................ ....... 102 Figure 4.1 Schematic illustrating the stepwise mutational model ................................ ...... 1 11 Figure 4.2 Multistep mutational models for microsatellite loci ................................ .......... 1 14 Figure 4.3 Schematic illustrating convergent evolution of microsatellites ......................... 11 9 Figure 4.4 Chromatograms of locus 5877 and 8224 showing stutter - like patterns ............ 13 6 Figure 4.5 Neighbor - joining tree of 23 Rhizoctonia s olani AG2 - 2 isolates based on 13 microsatellite loci ................................ ................................ .......................... 13 8 Figure A 4 . 1 Multigene phylogeny of 63 Rhizoctonia solani AG2 - 2 isolates according to Martin et al. (2014) ................................ ................................ ..... 15 1 xii KEY TO ABBREVIATIONS 6 - FAM Fluorescein A G Anastomosis group ANOVA Analysis of variance statistical test C0 C1 C2 protoplasm fusion plus cell death) C3 CWDE Cell wall degrading enzymes CVE Coefficient of velocity of emergence D DAPI - - diamidino - 2 - phenylindole DS Disease severity score ddH 2 O Doubl e distilled water dNTP Deoxyribonucleotide triphosphate HEX Hexachlorofluorescein fluorescent dye HSD ISG Intraspecific groups ITS Internal transcribed spacer LpBS Lactophenol blue staining solution MEB Ma lt extract broth xiii MgCl 2 Magnesium Chloride MSU Michigan State University N50 minimum contig length needed to cover 50% of the genome PCR Polymerase chain reaction PDA Potato dextrose agar PIC Polymorphism information content PG Phylogenetic group rDN A Ribosomal DNA RRCR Rhizoctonia root and crown rot SMM Stepwise mutational model SSR Simple sequence repeats STR Short tandem repeats T a Annealing temperature TPM Two phase model Tris - EDTA Tris(hydroxymethyl)aminomethane - ethylenediaminetetraaceti c acid UV Ultra violet VCG Vegetative compatibility group 1 CHAPTER 1 : REVIEW OF LITERATURE 2 Introduction History of the G enus Rhizoctonia The genus Rhizoctonia, meaning Candolle (1815) to a ccommodate the violet root rot pathogen, R. crocorum D.C. (Par meter & Whitney, 1970). The basic characters that deCandolle used to define the genus were the production of sclerotia of uniform texture with hyphae originating from them, the association of th e mycelium with plant roots, and a lack of conidia. These features were so general that nearly 100 species hav e since been assigned to the genus which has led to a mixture of unrelated species being classified as Rhizoctonia spp. (Parmeter & Whitney, 1970; Sneh et al., 1991). Many of these species have little in common with one another except for the lack of conidia. The review of Ogoshi (1987) provided clarity on the characteristics of the Rhizoctonia genus. Ogoshi (1987) defined the genus Rhizoctonia as a group of imperfect fungi within the Basidiomycota and of the order Cantharellales with the following characteristics: ( a) branching near the distal septum in young, vegetative hyphae ; ( b) formation of a septum in the branch near the point of origin ; ( c) constriction of the branch ; ( d) dolipore septum ; ( e) no clamp connections ; ( f) no conidi a , except moniliod cells ; ( g) sclerotia not differentiated into medulla and rind and ( h) no rhizomorph . (Ogoshi, 1987 pg. 126). Furthermore , Ogoshi (1987) considered Rhizoctonia spp. to be sub - divided into three major groups based on the number of nuclei in each cell and the identity of the teleomorph. One group was the binucleate Rhizoctonia , with two nuclei per cell (rarely one or three) and teleomorph s in the genus Ceratobasidium D.P. Rogers . The second wa s the multinucleate Rhizoctonia , which hav e three 3 or more nuclei per cell , with teleomorphs in the genus Waitea Warcup and Talbot . The third group included the multinucleate Rhizoctonia with teleomorphs in the genus Thanatephorus Donk. concept of the genus reduced legitimate Rhizoctonia spp. to forty - nine out of the approximately one - hundred species that had been reported at the time . That same year, Moore (1987) proposed a new classification system for Rh izoctonia - like fungi. Moore (1987) argued that Rhizoctonia - like anamorphs represented four distinct groups of higher fungi that could be distinguished by their septal morphology . These included the ascomycetes (large septal pores and associated Woronin b odies) , ustomycetes ( simple septa with small pores ), homobasidiomycetes (dolipore/parenthesome septal complexes with perforate parenthesomes ) , and heterobasidiomycetes (dolipore/parenthesome septal complexes with imperforate parenthesomes) . R. crocor um (Pers.) DC., the type species of the Rhizoctonia genus at the time , had a simple pored septum and was therefore, an ustomycete . Thus in his proposed system, Moore (1987) reserved the genus Rhizoctonia for anamorphs of ustomycetous fungi . The remainder of the Rhizoctonia - like basidiomycetes were then assigned to one of three genera, two of which were newly formed . The binucleate Rhizoctonia spp. with the teleomorph Tulasnella J. S chröt were assigned to the new genus Epulorhiza R.T. Moore. Those binucl eates with the teleomorph Ceratobasidium D.P. Rogers were assigned to Ceratorhiza R.T. Moore. The anamorphs of Thanatephorus Donk and Waitea Warcup & P.H.B. Talbot with dolipore septal complexes with perforate parenthesomes (e.g. Rhizoctonia solani) were p laced in the genus Moniliopsis Ruhland due to the already accepted synonymy of R. solani with Moniliopsis aderholdii Ruhland ( Moore, 1987). 4 received nor was it followed in practice. Sneh et al. ( 1991 ) argued that due to the familiarity of the name Rhizoctonia solani and the extensive published literature , a name change would cause unnecessary confusion. Therefore in their monograph, Sneh et al. (1991) retained the name R hizoctonia Epulorhiza spp., Ceratorhiza spp., and Moniliopsis spp . Vi lgalys and Cubeta (1994) followed Ogoshi (1987) and Sneh et al. (1991) by ascribing Rhizoctonia spp. to three groups: multinucleate species having a Thanetphorus teleomorph; binucleate species having a Ceratobasidium teleomorph; and multinucleate species having a Waitea teleomorph. Stalpers et al. (1998) proposed that the name Rhizoctonia should be conserved and re - typif ied with R. solani as the type species. Stalpers et al. (1998) agreed with Sneh et al. (1991) the nomenclature code , the changes were not bei ng followed in practice and the name R. solani was so familiar in the literature that it should not be c hanged. The proposal was approved unanimously by the International Association of Plant Taxonomy (IAPT) Committee for Fungi in 2001 (Gams, 2001) and Rhizoctonia solani established as the current type species of the genus Rhizoctonia. Classification of Rhi zoctonia solani Julius Kühn first identified Rhizoctonia solani while viewing potato tubers under his microscope where h e observed dark sclerotia adhered to the surface of the tuber that were connected with dark fungal hyphae ( Menzies, 1970 ) al description and illustrations appeared in his book on crop diseases in 1858 (Kühn, 1858; Menzies, 1970 ). his depictions of the hyphae and sclerotia were hardly diagnostic of what we consider R. solani 5 today . In addition, the disease symptoms that Kühn described were more characteristic of scab than the stolon and stem lesions that are actually caused by R. solan i (Menzies, 1970 ) . Th e next major development in o ur understanding of the concept of Rhizoctonia solani came with the review of Duggar (1915). of including structures from more than one fungus, Duggar (1915) agreed that the fungus he was studying in con nection with damping off and other root diseases was the same fungus Kühn had described. This conclusion has been generally accepted by later workers and Kühn has been recognized as the first to publish Rhizoctonia solani as a valid name. Although Duggar ( 1915) provided a respectable description of R. solani and the diseases known at the time to be associated with the fungus, his review still lacked definitive diagnostic characteristics. The lack of conidia and rarity of the sexual stage coupled with the hi ghly variable nature of this group of fungi makes an adequate species concept difficult to formulate. No single character or feature is able to distinguish R. solani isolates from other similar fungi, except that the teleomorph is Thanatephorus cucumeris (Frank) Donk (Parmeter & Whitney, 1970) . Instead, recognition of the species depends on the presence and absence of a combinat ion of several characteris tics (Parmeter & Whitney, 1970 ). Unfortunately, i t can be difficult to describe mycelium in a sufficient ly detailed way to assure that all workers will come to the same conclusion based on a written description (Parmeter & Whitney, 1970) . In addition, because of the highly variable nature of the R. solani group, some characters are more reliable diagnostic f eatures than others (Parmeter & Whitney, 1970) . Parmeter and Whitney (1970) provided the description that forms our current species concept of Rhizoctonia solani and presented the following criteria as defining the species (adapted from Parmeter & Whitney, 1970) : 6 Characters c onsistently present in R. solani isolates: 1. Actively growing hyphae are multinucleate with three or more nuclei per cell (Fig . 1. 1 A ). 2. Presence of a prominent dolipore septa apparatus (Fig. 1. 1B ). 3. Branching near the distal septum in young vegetative hyphae (Fig. 1. 1B ) 4. Distinct constriction at the branch point and a septum that forms in the branch near the point of origin (Fig. 1. 1B ). 5 . Some shade of brown. While young colonies may be white or nearly white, they will become bro wn as they age. There is, however, much variation in the shade of brown that is possible as some colonies may be pale brown and others, particularly the sclerotia, will be so dark brown as to be almost black. C haracters usually present in R. solani but one or more may be absent in some isolates: 6. Mycelium is fairly fast growing and large diameter (6 - 10 7. Moniliod cells (Fig. 1. 1C ) 8. Sclerotia, when present, are not differentiat ed into rind and medulla (Fig. 1. 1D ). 9. Phytopathogenicity Characteristics never present in R. solani isolates : 1 0 . Clamp connections 11 . Conidia 7 12 . Rhizomorphs 13 . Any pigment other than brown 14 . Any perfect stage other than Thanatephorus cucumeris (A.B. Frank) Donk Th us th e review of Parmeter and Whitney (1970) provided a solid taxonomic foundation for the classification of R. solani . Nevertheless , diffic ulties with t he species concept still remained . High levels of phenotypic variation and the lack of unequivocal characteristics in the Figure 1.1 Micrographs of characteristic str uctures of Rhizoctonia solani . (A) Hyphum stained with safranin O showing multiple nuclei in a cell (400X). (B) Hyphae stained with Safranin O showing the dolipore septum, lack of clamp connection, branch close to the distal septum and conspicuous constric tion at the branch (400X). (C) Moniliod cells stained with lactophenol blue solution (200X). (D) Sclerotum from a culture of AG1 - 1B grown on potato dextrose agar (40X). B D C A 8 anamorph made con ventional taxonomy difficult . The most certain way to avoid confusion in communicating the identity of a n R. solani i solate is to a ssociate the strain with its perfect state, Thanatephorus cucumeris . However, not only is this in feasible for many strains ( Vilgalys & Cubeta, 1994) but it has also had the additional effect of adding confusion regarding the proper name to u se . Uncertainty surrounding the correct name to use for R. solani still appears to be abundant d espite t effective as of 1 January 2013 (Hawksworth, et al., 2011; Article 59, International Association of Plan t Taxonomists, http://www.iapt - taxon.org/nomen/main.php). According to the current rules, it should be fairly straightforward that the name R. solani has taxonomic pr iority given that Rhizoctonia was described by de Candolle in 1815 and Rhizoctonia solani was described by Kühn in 1858 while Thanatephorus was described much later by Donk (1956). Yet as recently as 2018, Ajayi - Oyetunde & Bradley (2018) reported that Index Fungorum (www.indexfungorum.org) had Thanatephorus cucumeris listed as the current name . However, when I referenced Index Fungorum in March of 2018 , R. solani was properly listed as the current name. A search of Google Scholar (https://scholar.google.com/) reve aled a sizable number of journal articles published between 2013 and 2018 that used T. cucumeris as the accepted name (e.g. Gonzalez et al., 2016) . The continuing confusion regarding the taxonomy of the Rhizoctonia genus is not unexpected considering the history of its c lassification and the varying classification systems. Separation of Rhizoctonia solani S ubgroups by Anastomosis R eaction It should be clear that the taxonomy of the Rhizoctonia genus is comp lex and controversial. It is now recognized that R. solani is a species complex composed of a number of 9 genetically distinct groups (C ubeta & Vilgalys, 1997). A species complex, al so known as sibling species, is a closely related group of distinct, reproductively isolated organisms that cannot adequately be distinguished morphologically (Mayr, 1963). Within th e group of fungi known as Rh izoctonia solani , t here are a number of distinct groups with diverse life - histor ies (Cubeta & Vilgalys, 1997) but elucidating those relationships has been problematic for researchers. Current classification of subgroups within the R. solani species comple x relies on the c oncept of anastomosis groups (AG) . Anastomosis groups are based on the premise that the hyphae of closely related isolates are able to recognize and fuse, or anastomose, with one another (Carling, 1996) . Isolates that are able to anastomos e are considered to be part of the same anastomosis group (AG) and isolates that are unable to fuse with one another are considered part of different AG. To date, at least 13 AG have been described in R. solani , designated as AG followed by a number, AG1 t o AG13 (Sneh et al.,1991; Gonzalez et al . , 2016) . A nastomosis of compatible strains of R. solani was first reported more than 80 years ago by Matsumoto et al. (1932) who used the concept to differentiate strains of Hypochnus sasakii Shirai (syn. R hizoctoni a solani ) from on e another. Criteria for distinguishing between hyphal anastomosis reactions described by Matsumoto are shown in Table 1. 1 . Shultz (1936) first introduced the concept of grouping isolates based on anastomosis reactions , which he termed ru (Table 1. 2) . Richter and Schneider (1953) further refined and added to the concept, using somewhat different terminology for their grouping s , and F (Table 1. 2 ). 10 These earl y reports on anastomosis groupings did not describe the cell death that commonly occurs after anastomosis (Carling, 1996) . Flentje and Stretton (1964) were the first to report cell death as a criterion for the categorization of a nastomosis reactions and te rmed this category the Although this reaction is similar to the imperfect fusion of Matsumoto et al. (1932), it is not completely equivalent as cell death was not reported by Matsumoto et al . (1932). When microscopic observation suggested that cell wall fusion had occurred, Flentje and Stretton (1964) punctured one of the two anastomosed cells using a glass needle to determine if a cytoplasmic connection had occurred. Reactions where both the punctured cell and the neighboring cel l collapse d were considered eviden ce that membrane Table 1.1 Summary of terminology and descriptions used to define categori es of anastomosis reactions in Rhizoctonia solani . Terms towards the top of the table indicate close relationships and those towards the bottom indicate more distant relationships. Table adapted from Carling (1996) p. 40. Matsumoto et al. (1932) Flentje & Stretton (1964) Parmeter et al. (1969) Carling et al. (1988) Perfect Hyphae are from same parental strain S (Self reaction) Cell wall and membrane fusion; no cell death 2 (perfect) Cell wall and cytoplasmic fusion; cell death Cell wall and me mbrane fusion; no cell death Imperfect Membrane not completely fused; no mixing of cytoplasm K (Killing reaction) Cell wall and membrane fusion; cell death 2 (imperfect) Cell wall but no cytoplasmic fusion; cell death Cell wall fusion obv ious; membrane fusion probable; cell death Contact Hyphal contact but no fusion of cell wall or cytoplasm WF (Wall fusion) Cell wall fusion but no fusion of membrane or cytoplasm 1 Hyphal contact but no fusion of cell wall or cytoplasm; no cell deat h Hyphal contact and attachment; no membrane fusion; no cell death No reaction No reaction NR (No reaction) No reaction 0 No reaction No reaction 11 fusion had occurred. Those reactions where only the punctured cell collapsed but the connection between the hyphae was not easily separated were consider ed or wall fusion in their syst em (Table 1. 1). The next major advancement in anastomosis grouping was made by Parmeter et al. al. (1969) made use of the terminology of Matsumoto et al. (1932), which c reated some confusion since descriptions of the criteria for each category were not equivalent; particularly with the inclusion of cell death as a condition (Table 1. 1). Parmeter et al . (1969) defined three Table 1.2 Historic groupings of Rhizoctonia solani based on hyphal anastomosis reactions. Ta ble adapted from Carling (1996). Year Author Proposed groups Present day equivalent 1936 Schultz Gruppe I ( hortensis ) Gruppe II ( brassicae ) Gruppe III ( typica ) Gruppe IV ( chicorii - endiviae ) Group V ( fuchsiae ) AG 1 AG 2 AG 3 AG 4 binucleate 1953 Richter & Schneider Fusion gruppe A Fusion gruppe B Fusion gruppe C cruciferen Fusion gruppe E kartoffel AG 1 AG 5 AG 4 AG 2 binucleate AG 3 1969 Parmeter et al. AG 1 AG 2 AG 3 AG 4 AG 1 AG 2 AG 3 AG 4 12 They also identified the anastomosis groups AG1, AG2, AG3 and AG4, which are still in use today. Categor ization of Anastomosis Reactions R. solani into more consistent groups was gaining some acceptance but there were still doubts as to how meaningful the grouping s were. I solates that were gro uped by anastomosis reactions did not always correspond with groupings based on morphology or pathogenicity (Parmeter & Whitney, 1970). Furthermore, many isolates would not anastomose with members of any of the anastomosis groupings recognized at the time (Carling, 1996). These uncertainties were further amplified because t he process of anastomosis was not well understood and even less was known about the genetic mechanisms that regulated anastomosis success. In an attempt to overcome the confusion associa ted with the varied definitions and terminologies related to anastomosis groupings, Carling et al. (1988) developed a system of four categories for describing anastomosis reactions. This system combined information from the previous three systems and clari fied some definitions and descriptions (Table 1. 1) . In a action (C0), no reaction occurs and the hyphae generally grow right past one another without recogn ition. This indicates that the isolates are in separate AG n (C1), hyphal contact occurs and hyphal attachment is apparent, but no membrane fusion occurs. A C1 reaction indicates that isolates are only distantly related perhaps within on (C2) occurs when cell wall fusion is obvious, membrane fusion is probable and anastomosing cells frequently die. This reaction category is an indication that isolates are in the same AG but are in 13 fusion of the cell wall and of the membrane and the anastomosing cells frequently remain alive. This reaction is an indication that isolates are very closely related and not only in the same AG but also in the same VCG. Se lf - Although it is tempting to consider the categories defined by Matsumoto et al. (1932), Flentje and Stretton (1964), Parmeter et al. (1969), and Carling et al. (1988) to be analogous to one ano ther, a more careful examination of Table 1. 1 reveals this to not be the case. Significant differences between the definitions make direct comparison difficult and reveal that the categories presented by the four authors are not equivalent. The most obviou s difference is the use of cell death as a descriptive criteri on. Matsumoto et al. (1932) did not mention cell death in any of his descriptions while Parmeter et al . (1969) include s cell death as part of his In contrast, Fl entje and Stretton (1964) and Carling et al . (1988) to include cell wall and membrane fusion with no cell death. The terminology used to describe anastomosis re actions can cause some confusion among researchers unfamiliar with the classification system . It is not un common to hear the perfect imperfect contact (1988) but this has the potential of be ing imprecise s ince Carling et al. (1988) made no use of those terms and the descriptions of Carling et al. (1988) are not exactly equivalent to those presented by Matsumoto et al. (1932) or Parmeter et al. (1969). roughly corresponds typically refers to anastomosis between hyphae of the same isolate or very closely related isolates . fusion refers to 14 the anastomosis of isolates l. (1988) where paired isolates are in the same AG but not the same vegetative compatibility group (VCG). The term s to the anastomosis reaction where cell wall fusion occurs but there is no mixing of cytoplasm. This category is somet although that terminology c ould also be imprecise . An isolate pairing with a high proportion of reactions may be said to have a bridging relationship or considered to be a bridging isolate, but the anastomosis The categories as described by Carling et al. (1988) are currently the most widely used method of evaluating anastomosis reactions and authors should be careful that they unders tan d the appropriate way to use the terminology . Probably the most accurate and least confusing way informally and employ the terminology of Carling et al. (1988) for more formal reporting. Since 1969 , when Parmeter et al. (1969) character ized AGs 1 through 4, as many as 10 other AGs have been described (Table 1. 3 ) including AG5 (Ogoshi , 1975), AG 6 and AG BI (Kuninaga et al., 1979), AG 7 (Homma et al., 1983), AG 8 (Ne ate & Warcup, 1985; Rovira et al., 1986), AG 9 (Carling et al., 1987), AG 10 (MacNish et al., 1995), AG 11 (Carling et al., 1994), AG 12 (Carling et al., 1999) and AG 13 (Carling et al., 2002 a ). These groups have diverse host ranges, cultural characteristics, thiamine requirements and temperature optima. Since their hyphae do not fuse, there is limited opportunity for exchange of genetic material. Thus, these anastomosis groups basically represent reproductively isolated lineages and therefore, can be thought o f as separate species. Whether the groups that are currently recognize d as anastomosis groups will eventually be elevated to independent species remains to be seen. 15 AG Cultural Types Tester strain Characteristics of cultural types References AG 1 IA IB IC ATCC 76121 ATCC 76122 ATCC 76123 sclerotial form, cultural characteristics, DNA base sequence homology Parmeter et al., 1969 Kuninaga & Yokosawa, 1985 AG 2 - 1 - 2t Nt ATCC 76168 fusion frequency ITS1 sequence similarity Ogoshi, 1975 Schneider et al., 1997 Kuninaga et al., 2000b AG 2 - 2 IIIB IV LP WB ATCC 76124 ATCC 76125 morphological characteristics host range, symptoms Sneh , et al., 1991 Hykumachi et al., 1998 Godoy - Lutz et al., 2008 AG 2 - 3 Naito and Kanematsu, 1994 AG 2 - 4 Carling et al., 2002b AG 3 TB PT ATCC 76167 Parmeter et al., 1969 Kuninaga et al., 2000a AG 4 HGI HGII HGIII ATCC 76126 DNA base sequence homo logy, sclerotia form Parmeter et al., 1969 Kuninaga & Yokosawa, 1985 AG 5 ATCC 76128 Ogoshi, 1975 AG 6 HG - 1 GV ATCC 76129 ATCC 76130 DNA base sequence homology Kuninaga et al., 1979 Kuninaga & Yokosawa, 1985 AG 7 ATCC 76131 Homma et al., 1983 AG 8 ZG1 ZG2 ZG3 ZG4 ZG5 ATCC 76106 Neate & Warcup, 1985 Rovira et al., 1986 Neate et al., 1988 AG 9 TP TX ATCC 62804 ATCC 62804 Thiamine requirement, DNA base sequence homology Carling et al, 1987 Carling & Kuninaga, 1990 AG 10 ATCC 76107 MacNish et al., 1995 AG 11 Carling et al., 1994 AG 12 Carling et al., 1999 AG 13 Carling et al., 2002a AG BI ATCC 76132 Kuninaga et al., 1979 Table 1.3 Currently recognized AG and cultural types. Table provides a summary of information related to anasto mosis groups (AG) and the associated cultural types. Data was taken from literature cited in the references column and from Sneh et al. (1991). Anastomosis groups are differentiated by hyphal anastomosis whereas cultural types are differentiated by the cha racteristics listed in the applicable column. Tester strains are used for anastomosis testing and not for differentiating cultural types by hyphal fusion. 16 C lassification of AG 2 Rhizoctonia solani AG 2 has been further separated into two major subgroups , t ype 1 and type 2 , and designated as AG 2 - 1 a nd AG 2 - 2 (Ogoshi, 1976 ). These subgroups were differentiated by hyphal fusion frequenc y, where members of AG2 - 1 anastomose at low frequencies with members of AG 2 - 2 (Sneh et al.,1991). Ogoshi (1976) co nsidered AG2 - 1 and AG 2 - 2 to be independent anastomosis groups even though they anastomose at low rates. Adams (1988) argued that based on DNA homology, AG2 - 1, AG2 - 2 and AG BI should be merged in to a single group designated AG 2. Carling et al . (2002b ) also a rgued that AGBI should be included in AG 2 based on strong hyphal anastomos is reactions with AG2 - 1 and AG 2 - 2 and pr oposed it be designated as AG 2 BI. Additional subsets of AG2 were characterized by Naito and Kan ematsu (1994), who described AG 2 - 3, and Carlin g et al. ( 2002b), who described AG 2 - 4. A neighbor joining tree illustrated in Carling et al . (2002b) , showed subsets 2 - 1, 2 - 2, 2 - 3, 2 - 4 and 2 - BI as well s upported, separate groups (Fig . A 1 .1 ) an d was intended to support the concept that AG 2 wa s a unified g roup with distinct subsets . Similar results were found by Salazar et al. (1999) . However, without including representative AG outside of the AG2 complex, it is diffic ult to determine if these groups truly represent subsets within a larger, monophyletic gro up or if they are actually entirely separate groups. When phylogenetic analysis included a larger number of AG, both Kuninaga et al. (1997) and Vilgalys and Cubeta (1994) showed that AG2 - 1 is genetically closer to AG9 and AGBI than it is to AG2 - 2. Likewise , AG 2 - 2 is genetically close r to AG5 than it is to AG 2 - 1 lending support to the hypothesis that AG2 - 1 and AG 2 - 2 should be considered separate AG. 17 I agree with the argument that AG2 - 1 and AG2 - 2 should be considered separate anastomosis groups. First is the fact that they are genetically distinct and more closely related to other AG than to each other (Kuninaga, et al., 1997; Vilgalys & Cubeta, 1994) . Secondly, while the two groups do have some overlap in host range, the primary hosts are diverse . Members o f AG2 - 1 are considered to be slow growing isolates that are pathogens of winter crops, primarily the in Brassicaceae while AG2 - 2 are faster growing and primarily infect members of the Chenopodiaceae , Fabaceae and Poaceae ( Ogoshi, 1987; Salazar et al., 2000 a ; Sneh, 1991). Another issue is that several AG are capable of fusing with other AG at low levels (Table 1. 4) and are still considered separate groups. As discussed below, low levels of anastomosis is common within R. solani and does not signify isolates are of the same anastomosis group. Finally, considering AG2 - 1 and AG2 - 2 to be subgroups of AG2 simply adds another level of confusion, since both groups have additional subgroups or cultural types. There is sufficient evidence that AG2 - 1 and AG2 - 2 are gene tically diverse ( Carling et al., 2000; Salazar et al, 1999 ; Vilgalys & Cubeta, 1994 ) and there is not a satisfactory reason to add to an already confusing situation. Bridging Reactions I solates within some established AG are able to fuse at low levels wit h members of other AG and are considered to be bridging isolates (Carling, 1996) . The most well - known g roup of bridging isolates is AG BI ( alternately AG 2BI) but s everal other groups, such as AG6, AG8 and AG 11 can also fuse with other AG at low levels ( T abl e 1. 4 ) . Bridging reactions are generally but they can make placing an isolate into the proper AG a difficult task. The fate of isolates that undergo a bridging reaction, whether they exchange genetic 18 material or create a hybrid state, is uncertain . However , since most bridging reactions involve cell wall fusion and not membrane fusion, the exchange of genetic material seems unlikely . Anastomosis Group Cultural Types Adding to the complexity of Rhizoctonia solani classification , many of the recognized AG have identifiable cultural types for which Ogoshi (1996) proposed the term intraspecific groups (ISG). The use of the term in the literature resulted in some confusion; probably due to a misunder standing of what was meant by sub group since the AG themselves could be considered subgroups . So , even though review , I will refer to the subgroup s of the AG . Rhizoctonia solani c ultural typ es are not distinguishable from other cultural types within the same AG on the basis of hyphal anastomosis reactions. Instead they are identified by cultural or physiological properties such as colony morphology, pathogenicity, nutrient utilization, sclero tia size and shape, DNA - DNA complementarity, zymogram patterns , DNA sequence and temperature tolerance (Sneh, et al., 1991; Vilgalys & Cubeta, 1994). Currently recognized AG cult ural types are listed in Table 1. 3 . AG Capable of bridging with these groups AG BI AG 2, AG 3, AG 6, AG 8, AG 11 AG 2 AG 3, AG 8, AG 11, AG BI AG 3 AG 2, AG 8; AG BI AG 6 AG 8, AG BI AG 8 AG 2, AG 3, AG 6, AG 11, AG BI AG 11 AG 2, AG 8, AG BI Table 1.4 Anastomosis groups with bridging capability . Isolates within these bridging groups are known to be able to fuse with isolates in some other groups at low levels. 19 While these cultural types do have releva nce to the study and management of Rhizoctonia - induced diseases, they can create additional confusion in an already complex classification scheme. Nomenclature associated with cultural types can be a source of some confusion. As already mentioned, there ca n be misunderstanding as to what should be considered a subgroup. For example, AG2 - 1 and AG 2 - 2 both have several cultural types an d if t hey are considered to be subgr oups of AG 2 then the cultural types would be subgroups of subgroups . In addition, some of the cultural types have designations that are similar to names of other groups within R. solani . For instance , there is the group AG 4 and there is also a cultural type AG2 - 2 IV (Table 1. 3) . It would be beneficial if standardized terminology were developed f or cultural type designation within R. solani . Part of the problem lies in the fact that anastomosis groups are not a taxonomically recognized ranking although some have suggested that the AG should be accorded species status ( Carling, 1996 ) . Cultural Typ es of AG 2 - 2 Rhizoctonia solani AG 2 - 2 has three widely recognized cultural types: AG2 - 2IIIB (mat rush type), AG2 - 2IV (root rot type) and AG 2 - 2LP (large patch type) (Hyakumachi et al., 1998) . A fourth cultural type, AG 2 - 2WB (web blight type) has been describ ed by Godoy - Lutz et al. (2008), but reports are limited and acceptance is uncertain. Cultural types AG2 - 2IIIB and AG 2 - 2IV were separated based on pathogenicity and cultural morphology (Ogoshi, 1987), but cannot be distinguished based on hyphal fusion. The traditionally accepted criterion used for differentiating these cultural types is where AG 2 - 2IIIB isolates C and AG 2 - 2IV isolates do not (Sneh et al., 1991). 20 Pathogenicity and Host R ange Although Rhizoctonia solani is commonly described as having a broad host range (Brooks, 2007; Carling et al., 2002a; Liu & Sinclair, 1992), this attribution tends to be somewhat exaggerated. If anastomosis grou ps are thought of as independent evolutionary units, the host range of these ind ividual units is much more restricted (Sneh et al., 1991) . For examp le, the host range of R. solani AG3 is primarily confined to the Solanaceae (Sneh et al., 1991). Isolates in AG8 are primarily isolated from cereal roots (MacNish et al., 1988; Neate & Warcup, 1985) while the groups AG10 and AG13 are considered non - pathoge nic (Carling et al., 2002; MacNish et al., 1995), and those in AG12 are mycorrhizal on orchids (Carling et al., 1999). Although technically it is correct to suggest that the R. solani species complex , as a whole, has a broad host range, researchers should be mindful that doing so could be, to some extent, misleading. Instead, discussion of host range should be confined to the anastomosis group, or groups, under consideration. Rhizoctonia solani AG2 - diseases of plant parts in contact with the ground or close to the soil surface ( Ogoshi, 1987; Sneh, 1991) , although there are diseases that affect above ground parts as well ( Godoy - Lutz et al., 2008; Herr, 1996 ) t rush, R. solani AG2 - Oryza sativa - Lutz et al., 2008). R. solani AG2 - Zoysia grass, but these isolates are distinct from the main subgroups an d have been designated as AG2 - 2 LP (Hyakumachi et al., 1998). 21 Root rots and diseases of plant parts in contact with the ground are the most common and widespread result of R . solani AG2 - 2 infection . R. solani AG2 - ; (Goodwill & Hanson, 2011). Other crops reported to be affected by R. solani AG2 - 2 are carrot (Anderson, 1982); spinach (Naiki & Kanoh, 1978); cauliflower, lettuce and radish (Carling et al . , 2002b); and alfalfa (Rush & Winter, 1990). M ethods of Identification Introduction to Identification This section is provided as a brief overview for the process of identifying Rhizoctonia solani isolates. It is not intended to be an exhaustive examination of all such techniques nor is it a detailed description of the methodologies involved. Rather, it is meant to give the reader some guidance in identifying Rhizoctonia solani isolates using techniques that have worked well for this author . I will briefly describe the se techniques and discuss potential problems and difficulties in their application. For more information on different techniques see Sneh et al . (1991). Obtaining Pure C ultures Pure cultures of Rhizoctonia are best obta ined by growing the culture on a low nutrient medium such as 2% water agar and examining for hyphae with characteristic branching. Rhizoctonia - like hyphae are isolated by hyphal tip transfer ( Nelson et al., 1983; Whitney & 22 Parmeter, 1963) , where single gr owing tips are excised at the first branch point and transferr ed to a nutrient rich medium such as potato dextrose agar (PDA ; Sigma - Aldrich, St. Louis, MO ). Cultures are grown for 5 - 1 0 days at room temperature and examined for pigment; any color other than brown is an indication that the culture is not Rhizoctonia . A small amount of mycelium can be teased apart on a slide and examined microscopically to confirm Rhizoctonia - like branching , dolipore septa and that there are no clamp connections or conidia pre sent (Fig. 1. 1 ) . Nuclear S taining Rhizoctonia - like cultures are examined to determine nuclear condition (binucleate or multinucleate). The easiest way to accomplish this is to coat a sterile slide with 1 % water agar by placing five to seven drops of molte n ( >8 0 (Windels & Nabben, 1989; Jones & Belmar, 1989) . When the agar hardens, a small piec e of actively growing hyphae is placed on one end of the slide. The inoculated slides are kept in a humid chamber and the hyphae a re allowed to grow across the slide for 2 - 4 days. The hyphae are stained (see below) , covered with a cover slip and observed at 400x. An o il immersion lens should not be used since the surface of the agar will not be flat and it may result in the objective touching the surface of the agar or the cover slip . There are several staining protocols recommended for nuclear staining (Sneh et al., 1991). The simplest method uses a protocol modified from Herr (1979). Lactophenol blue s taining solution ( L p B S ) is pre pared by diluting with a wetting agent [ 47ml d d H 2 l actophenol blue solution (Sigma - Al drich, St. Louis, MO, USA) ] . Several drops of L p B S are placed on the hyphae and allowed to sit for one minute . Excess soluti on is 23 car efully removed with an absorbent tissue. The l actophenol blue stain is rather in discriminate in the structures it stains and it can be difficult to distinguish nuclei from other cytoplasmic bodies . This protocol does work but performs better as a g eneral h yphal stain than a nuclei specific stain . Safranin O stains nuclei much more selectively than l actophenol blue. One drop of s afranin O solution (6 ml of 0.5% (w/v) s afranin O, 10 ml 3.0% (w/v) KOH, 5 ml glycerine, 79 ml distilled water) and one drop of 3 .0% (w/v) KOH are placed on the slide and a cover slip is applied (Sneh et al., 1991) . The trick to making this technique work well is to create a gradient of staining intensity where the s afranin O solution and the KOH solutions intermix. This gradient sh ould be in the zone of hyphal interaction or where young growing hyphae are present. Nuclei will be stained red /orange and are readily visible at 400x magnification (Fig . 1. 2 A ) . A more - - diamidino - 2 - phenylindole (DAPI). Hyphae growing on a water agar slide are fixed by flooding with 3% formaldehyde for 2 min. and then rinsing with distilled water for 1 minute. Hyphae are then B A Figure 1.2 Micrograph s of Rhizoctonia solani hyphae showing stained nuclei. (A) Hyphae stained with Safranin O, nuclei appear red - orange (400X). (B) Hyphae stained with DAPI fluorescent stain. Nuclei appear as bri ght spots against a darker background (200X). Excitation/emission maximum: 358/461. 24 tion for 5 - 10 minutes and destai ned with distilled water for 3 minutes (Sneh et al., 1991) . Excess water is blotted dry and a drop of glycerol and a cover slip are added. Nuclei are viewed using fluorescence microscopy [excitation/emission maximum: 358/461] and nuclei are highly visible and easy to distinguish from other cellular structures (Fig . 1. 2 B ) . The major disadvantage of this method is that both formaldehyde and DAPI are hazardous chemicals that require proper disposal practices. The other difficulty with this method is that sinc e DAPI is so selective for the nucleus, it can be difficult to identify the extents of each cell, which can make it complicated to count the number of nuclei per cell. Alternating between fluorescent and standard light will usually help one identify the se pta and establish the boundaries of the cell. Anastomosis T esting In order to place an isolate in one or another anastomosis group, it must be paired with a recognized tester strain and evaluated for interactions between the confronted hyphae (Carling et al., 1988; Ogoshi , 1987) . Several methods have been described that allow the hyphae to interact in such a way that the anastomosis reactions can be visualized and assessed (Sneh et al., 1991) including water agar in petri plates (Parmeter , 1969; Rovira et al, 1986; Ogoshi, 1975) , cellophane overlaying agar media (Parmeter, 1969; Carling & Sumner, 1992) , agar coated slides (Windels & Nabben, 1989; Jones & Belmar, 1989) , and bare slides (Kronland & Stanghellini, 1988) . Thin cultures provide for a shallow dept h of field during microscopic examination and allow for easier visualization of hyphal interactions and therefore, techniques that produce thin cross sections are the most effective . The techniques that have worked best for this author are the water agar i n petri plates and agar coated slides, with the petri plate 25 method being slightly more favorable as it is often easier to trace the interacting hyphae to the parent colony source . Agar coated slides are prepared as above for nuclear staining by applying f ive to seven drops of molten 1% agar to a sterile slide . Small pieces of hyphal tissue from the growing margins of cultures of a known anastomosis tester strain and an unknown sample are placed on opposite ends of the agar coating and incubated until the h yphae of the two strains come into contact with one another. The hyphae are stained with a drop or two of L pBS and covered with a cover slip. Excess stain can be removed with an absorbent wipe. Hyphae are observed under 200x or 400x magnification and hypha l interactions are noted. The drawback to this method is that since the slide is rather narrow, the hyphae growing towards the edge of the slide will tend to turn back towards the center of the slide and it can be difficult to trace the hyphae back to the source. Performing the reaction in a petri dish can help overcome this problem by allowing the hyphae more room to grow laterally and limiting the tendency to double back upon itself . The bottom of a 60 mm petri dish is coated with a bout 1. 5 ml of 1% w ater agar to form a thin layer (Parmeter, 1969; Rovira et al, 1986) . Dropping the molten agar onto the plate and swirling the plate rapidly helps to distribute the agar onto the bottom of the plate. Small pieces of a tester strain and a sample are placed on op posite side of the dish and incubated until the hyphae of the two strains come into contact with one another. The surface of the plate is then flooded with L p BS and allowed to sit for 1 - 2 minutes . E xcess stain is removed with an absorbent tissue. Stained plates can be sealed with Parafilm (Bemis NA, Neenah, WI) and kept for several days 26 until they can be analyzed. Plates are placed on the microscope stage upside down or on an inverted microscope and viewed under 200x or 400x magnification. Regardless of the method used for confronting isolates, evaluation and interpretation of the r eactions is necessary. Contact points between hyphae of opposing isolates are counted and categorized according to the scheme of Carling et al. (1988) . Any place where opposing hyphae contact one another and have the opportunity to anastomose should be counted as a contact point . It is important that interacting hyphae are traced back to their source to ensure they originate from opposing isolates. The system of Carling et al. (1988) is the recommended method for categorizing anastomosis reactions . F our categories of reactions are identified cell death ( Chapter 1, pg. 12, this thesis). indicate isolates are in the same anastomosis group (AG) isolates are in different anastomosis groups . Therefore, when conducting AG testi ng, the categories could be reduced to just two categories; positive reactions ( + ) and negative reactions ( - ). However, since reactions can indicate a bridging relationship (Carling, 1996 actions in addit ion to positive reactions. For each microscopic field of view, the total number of contact points, the number of Ten to fifteen microscopic fields of view are examin ed and counted as described above and a fusion 27 fre quency (Ogoshi, 1975; Carling & Sumner, 1992) is calculated using the following formula : Equation 1.1 A fusion frequency of greater than 50% is consider to be high frequency, 30 - 50% moderate frequency and less than 30% is lo w frequency (Sneh et al., 1991) . Thus, isolates that are paired with a known AG tester that have a high frequency of fusion with that tester strain would be considered to be in the same anastomosis group as the tester. Those with moderate fusion frequency could be considered as probable member s of the same anastomosis group as the tester strain. Low fusion frequency generally indicates that the isolate is in a different anastomosis group than the tester strain but also could signify a bridging relationship. The reaction s c ould help reinforce this conclusion. rDNA - ITS S equencing Interpretation of anastomosis reactions can be complicated and time consuming (Sharon et al., 2006) . Furthermore, classifying anastomosis reactions into d iscrete categories can be rather subjective , especially considering that anastomosis reactions represent a continuum of hy phal interactions (Vilgalys & Cubeta, 1994). In contrast, m olecular methods have the advantage of being somewhat more objective and re producible (V ilgalys & Cubeta, 1994) . Ribosomal DNA (rDNA) sequences have been widely used for investigating evolutionary relationships of R. solani and have added support for the classical anastomosis classification system (Carling et al., 2001; Godoy - Lut z et al., 2006; Salazar et al., 1999; Sharon et al., 2007; Strausbaugh et al. , 2011). 28 Ribosomal genes are located in the mitochondria or the nuclei and contain regions of highly conserved sequences and regions of highly variable sequences (White et al., 1990) . Nuclear ribosomal genes are arranged in tandemly repeated units of up to several hundred copies ( Buckner et al., 1988; Rogers & Bendich, 1987) . Each unit contains the genes for the 18S (small subunit ), 5.8S and 28S (large subunit ) ribosomal subunits (Fig. 1. 3 ) which are highly conserved across closely related individuals ( Hamby & Zimmer, 1992 ; Salazar et al., 2000 a ; Vilgalys & Gonzlez, 1990) . The subunits are separated by internal transcribed spacer s (ITS) that are transcribed but not translated and because of this, display a high level of sequence variation (Gonzalez et al., 2001; Kuninaga et al., 1997) . This combination of features (large copy number and highly variable sequences interspersed between highly conserved sequences) make s rDNA - ITS genes desirable for many types of molecular studies ( Schoch et al., 2012) . Figure 1.3 Schematic illustrating the organization of ribosomal RNA genes in fungi. Primer sequences are from White et al., (1990) and are drawn as arrows indicating the d irection of orientation. ITS1 and ITS2 are internal transcribed spacers that are transcribed into mRNA but excised before translation. Subunits are highly conserved between groups while the ITS regions are highly variable (White et al., 1990) 29 Diversity of the Anastomosis G roup 2 - 2 Problems with Traditional AG2 - 2 S ubgroup D esignations The traditional subgroups AG2 - 2IIIB and AG2 - 2IV were first separated by host range, but i t was later found that the host range of both types was much broader than originally understood (Ogoshi, 1987). The groups were then distinguished based on ability to grow at - 2IIIB able to grow well at that temperature and AG2 - 2IV unable to g row (Sneh, so at a much slower rate than those that were identified as AG2 - 2IIIB ( Engelkes & Windels, 1996; Hanson, unpublished data). These have been designated as and their inclusion in groups AG2 - 2IIIB or AG2 - 2IV is uncertain . PCR based methods have been developed to help differentiate AG2 - 2IIIB and AG2 - 2IV (Bolton et al., 2010; Carling et al., 2002 b ; Salazar et al., 2000 b ). Primers specific to AG2 - 2 (Carling et al., 2002b) have worked well but those that were intended to differentiate the cultural types have shown inconsistencies (Brantner, unpublished data; Fenille et al . , 2003; Hanson, unpublished data; Martin et al . , 2014). C lassification P roposed by Martin et al. (2014) In order to clarify the relationships within Rhizoctonia solani AG2 - 2, Martin et al. (2014) sequenced four nuclear genes using markers that had been developed for the classification of Rhizoctonia fungi (Gonzalez et al., 201 6). Sixty - three R. solani isolates from diverse regions were analyzed and their phylogenetic relationships determined. Their work confirmed that the traditional sub groups AG2 - 2IIIB and AG2 - 2IV were not phylogenetically supported (Fig. A 1 .2 ). Instead, at le ast two major clades were observed with one containing two well supported sub - clades. They referred to these groups as clade 1, 2A and 2B and each contained a mix of AG2 - 30 2IIIB and AG2 - 2IV isolates. These results agree with previous findings that, based on ITS sequences, AG2 - 2IIIB and AG2 - 2IV were polyphyletic ( Carling et al., 2002b; Strausbaugh et al . , 2011). Objectives The main objective of this thesis is to examine the diversity within Rhizoctonia solani AG2 - 2 and examine the potential relationship of t h at variability to the newly identified phylogenetic groups of Martin et al. (2014) . A more accurate and comprehensive unde rstanding of the variability within this important group of pathogens can better inform management decisions. For this I have conduct ed three separate projects that will help to address these issues and provide a better understanding regarding the diversity with in the AG2 - 2 complex. The first project examines the virulence of R. solani AG2 - 2 isolates on dry beans ( Phaseolus vulgaris ) a nd contrasts th e three phylogenetic groups. To the best of my knowledge, this is the largest screening of AG2 - 2 isolates on dry beans to date and examines disease severity at both the seedling and adult life stages. It provides an alternative assessment of virulence diversity and distribution as compared to the traditional subgroups of AG2 - 2IIIB and AG2 - 2IV. The second project evaluates the ability of AG2 - 2 isolates to cause disease at low - existent. Since sugar beet ( Beta vulga ris ) is typically planted very early in the spring when soil temperatures 31 norm. My approach differs from previous studies in that it uses a broader range of is olates that are representative of the three phylogenetic groups. The third project involves the development of a set of microsatellite markers specifically for R. solani AG2 - 2. These markers can be used as a tool to address questions that involve the exte nt of genotype flow between regions, the effect of crop rotations on R. solani AG2 - 2 populations, and the presence of host preferences. The approach used for identifying potential markers involved NextGen sequencing of representative isolates and in silico selection of prospective loci. This approach made screening simpler and more efficient compared to more traditional methods of microsatellite isolation ( Glenn & Schable, 2005; Selkoe & Toonen, 2006) . The project is still ongoing and only preliminary resul ts are reported here. 32 APPENDIX 33 Figure A 1 .1 Neighbor - joining tree from Carling et al. (2002b). The tree illustrates estimated relationships of Rhizoctonia solani AG2 groups based on rDNA - ITS sequences. Bar indicates 1 base change per 100 nucleotide positions. Numbers at branches indicate the percen tages greater than 90% of congruent clusters in 1,000 bootstrap trials. 34 Figure A 1 .2 Multigene phylogeny of 63 Rhizoctonia solani AG2 - 2 isolates according to Martin et al. (2014). Genes sequenced included rpb2 , tef1 , ITS, and LSU as reported in Gonzalez e t al. (2016) with minor modifications to improve reliability and specificity for AG2 - 2 (unpublished data). Isolates in blue were originally identified as AG2 - 2IIIB, those in red identified as AG2 - 2IV, and those in green were intermediates based on growth a - where AG2 - - 2IV do not. An AG2 - 1 isolate was used for the outgroup. Phylogram used curtesy of Martin et al. (2014). 35 REFERENCES 36 REFERENCES Adams, G.C. jr. (1988). Thanatephorus cucumeris ( Rhizoctonia solani ) a species complex of wide host range. Advances in Plant Pathology, 6: 535 - 5 52. Ajayi - Oyetunde, O.O. and Bradley, C.A. (2018). 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Windels, C.E. and Nabben, D .J. (1989). Characterization and pathogenicity of anastomosis groups of Rhizoctonia solani from Beta vulgaris . Phytopathology, 79: 83 - 88. Whitney, H.S. and Parmeter, J.R. Jr. (1963). Synthesis of heterokaryons in Rhizoctonia solani Kühn. Canadian Journal of Botany, 41: 879 - 886. 43 CHAPTER 2 : VIRULENCE OF RHIZOCTONIA SOLANI AG2 - 2 ISOLATES ON DRY BEAN ( PHASEOLUS VULGARIS ) 44 Introduction Rhizoctonia solani Kühn is a ubiquitous soilborne fungus that causes disease on many economically important crops throughout the world (Anderson, 1982; Ogoshi, 1987; Sneh et al., 1991). It is one of the most prevalent and damaging root pests of sugar beet ( Beta vulgaris L.) in Michigan, Minnesota and North Dakota (Windels & Nabben, 1989; Poindexter, 2014) causing yie ld loss, reduced sucrose content, and increased susceptibility to storage rots (Strausbaugh et al., 2011b; Windels et al., 2009). Furthermore, many of the crops that are grown in rotation with sugar beet are also susceptible to the same strains of R. solan i (Ruppel, 1985) making cultural management challenging. Understanding how different crops are affected by R. solani can help inform management decisions and improve the effectiveness of disease control measures. One of the most common and important strat egies in managing disease caused by R. solani is crop rotation (Buhre et al., 2009). Increased disease pressure as a result of continuous monocultures has been shown for several cropping systems, including potato ( Solanum tuberosum ) (Gilligan et al., 1996, Larkin & Honeycut, 2006), wheat ( Triticum aestivum ) (Schillinger & Paulitz, 2006) and sugar beet (Maxson, 1938; Schuster & Harris, 1960). Since the primary objective of crop rotation is to reduce pathogen impact over successive growing seasons, it is impo rtant to understand how rotational crops influence population structure and persistence of the pathogen (Boine et al., 2014). Crop types that are hosts to the same virulent strains are likely to cause increased damage when grown in close rotation ( Buhre et al., 2009, Engelkes & Windels, 1996). 45 The effect of crop rotation on disease can be difficult to interpret and is highly dependent on the pathogen/host system (Sumner et al., 1981). R. solani - induced diseases and the effect of rotational crops have been examined for several systems including potato (Emmond & Ledingham, 1972), wheat (Rovira, 1986), corn (Sumner & Bell, 1986), soybean (Nelson et al., 1996), and sugar beet (Buhre et al., 2009; Ruppel, 1985; Rush & Winter, 1990). However, conclusions regardin g the contribution of rotational crops to disease severity have not always been consistent (Ruppel, 1985; Windels & Brantner, 2004). For example, Ruppel (1985) found that alfalfa ( Medicago sativa ) was not a host of strains of R. solani that had been isolat ed fom sugar beet, which was in contrast to previous findings by Maxson (1938). Maxson (1938) also found that a rotation including small grains decreased disease severity in a subsequent sugar beet crop. In contrast, Ruppel (1985) determined that although barley reduced disease on a subsequent beet crop, it was a host of R. solani AG - 2. Coons and Kotila (1935) showed corn decreased disease severity while Windels and Brantner (2004) showed that corn increased disease severity on a following beet crop. Sumner & Minton (198 9 ) confirmed corn was a host for Rhizoctonia solani AG2 - 2. One possible reason for these discrepancies is that there is more than just susceptibility to be considered when selecting a suitable rotational crop. For example, R. solani can survi ve saprophytically on crop residues (Papav i zas, 1970). Persistence in the soil may depend on how well a particular crop residue contributes to pathogen survival (Frank & Murphy, 1977; Ruppel, 1985). There may also be a connection between residual NO 3 - N and disease incidence (Rush & Winter, 1990). Crops that deplete residual NO 3 - N could increase vulnerability of the following crop by slowing plant development. Fertilizer applications reduced disease severity in 46 continuous sugar beet cropping in trials and th is and may be due, at least in part, to the seedlings maturing faster and thus escaping early stages of infection (Schuster & Harris, 1960). However, the connection between soil nitrogen and Rhizoctonia - induced disease has not been fully explored. Another possible reason for some of the discrepancies in the assessment of rotational crops is the variability of the pathogen. R. solani is a heterogeneous species complex consisting of at least 14 subgroups (Carling et al., 2002a) which are distinguish ed based on the ability of the hyphae to fuse or anastomose (Ogoshi, 1987; Sneh et al., 1991). Although R. solani as a whole has a very broad host range, affecting more than 200 plant species (Baker, 1970; Salazar et al., 2000), the various anastomosis groups (AG) represent genetically isolated groups and each AG has a more restricted host range (Cubeta & Vilgalys, 1997; Ogoshi, 1987; Parmeter et al, 1969). Still, some individual AGs can affect a large number of plant species (Ogoshi, 1987) and make crop rotation ch oices difficult. The anastomosis group 2 - 2 (AG2 - 2) is the primary AG that attacks adult sugar beet and typically causes a rot of the crown and root, known as Rhizoctonia root and crown rot (RRCR) (Ogoshi, 1987; Windels & Nabben, 1989). Moreover, many of th e crops commonly grown in rotation with sugar beet are also susceptible to R. solani AG2 - 2. These rotational crops include corn ( Zea mays ) (Sumner & Minton, 1989; Windels & Brantner, 2006), soybean ( Glycine max ) (Fenille et al., 2002; Nelson et al., 1996) and common bean ( Phaseolus vulgaris ) (Muyolo et al., 1993; Peña et al., 2013). In addition to the divisions based on anastomosis grouping, several AG within R. solani are further divided into cultural types, commonly known as intraspecific groups (ISGs). T hese cultural types have been identified using physiological or genetic characteristics such as host 47 range, sclerotial form, differential auxotrophy or DNA homology (Ogoshi, 1987; Sneh et al., 1991). R. solani AG2 - 2 is one of the anastomosis groups that ha ve been subdivided into several cultural types and these include AG2 - - - AG2 - 2 1998). AG2 - 2IIIB and AG2 - 2IV are the prim ary groups that are responsible for economic losses in sugar beet, while AG2 - 2LP causes disease primarily on warm season turf grasses (Hyakumachi et al., 1998; Ogoshi, 1987). Originally, AG2 - 2IIIB and AG2 - 2IV were separated based on host range with AG2 - 2II IB causing sheath blight of mat rush ( Juncus effuses ) and AG2 - 2IV causing root rot of sugar beet (Ogoshi, 1987). It is now recognized that both types have a wider host range than originally described and both types have been reported to cause disease on su gar beet (Engelkes & Windels, 1996; Nelson et al., 1996; Strausbaugh et al., 2011a), although they are still reported to sho w some variability in host range and virulence (Carling et al., 2002b; Engelkes & Windels, 1996; Strausbaugh et al., 2011a). These c ultural types are now and the IV type does not (Sneh et al., 1991). Despite the lack of host range differentiation originally used to define them, the subgroup s of AG2 - 2 have remained as important divisions. Differences in virulence have been noted by several workers where AG2 - 2IIIB was found to be more aggressive on sugar beet roots than AG2 - 2IV (Carling et al., 2002b; Kuninaga et al., 1997; Strausbaugh et al., 2011a). Windels and Brantner (2006) showed that corn increased the prevalence of AG2 - 2IIIB (but not AG2 - 2IV), which resulted in greater disease severity on a following sugar beet crop compared to soybeans or wheat. Similar variability in aggressiveness an d host preference are also recognized in other 48 R. solani AG subgroups with other hosts, such as AG1 - 1A, AG1 - 1B and AG1 - 1C (Ogoshi, 1987; Priyatmojo et al., 2001). This ability to at least somewhat predict aggressiveness from cultural type and the tendency for certain crop rotations to increase the more virulent groups helped maintain interest in separating AG2 - 2IIIB and AG2 - 2IV. In work by Carling et al. (2002b) and Strausbaugh et al. (2011a), the genetic relationship of AG2 - 2IIIB and AG2 - 2IV was found to be questionable. In order to clarify these relationships, Martin et al. (2014) analyzed the phylogenetic relationships of 63 AG2 - 2 isolates using four nuclear gene regions and confirmed that the cultural types AG2 - 2IIIB and AG2 - 2IV are not phylogenetically supported. Instead, at least two major clades were observed with one of them containing two well supported sub - clades. These phylogenetic groups were referred to as clades 1, 2A and 2B and contained a mix of AG2 - 2IIIB and AG2 - 2IV isolates. Therefore, infe rences based on the subgroups AG2 - 2IIIB and AG2 - 2IV need to be reexamined. without the current understanding of anastomosis groupings and it is not always clear what AG we re present. Recent analysis often relied on a small number of isolates to test for pathogenicity on rotational crops and may not have adequately considered the variability of the pathogen. With these considerations, studies that examine the variation in vi rulence within AG2 - 2 are fairly limited. Those that have been reported show considerable variability among isolates. For example, the severity of root rot on adult sugar beet varied from 19% to 100% among 47 AG2 - 2IIIB isolates and from 34% to 71% among 4 A G2 - 2IV isolates in a study by Strausbaugh et al. (2011a). Nelson et al. (1996) tested 28 isolates of R. solani AG4 on soybean seedlings and disease severity in two separate experiments varied from 1.77 to 3.37 and 2.09 to 49 3.46 (1 to 5 scale where 1 = no di sease, 5 = 75% leaves wilted or plant dead). Ohkura et al. (2009) also showed variability in disease severity on corn caused by AG2 - 2 isolates with median scores ranging from 1 to 4 on a scale of 0 to 5 (0 = no disease, 5 = plant dead), although no indicat ion of cultural type was given. From these results it can be concluded that the specific isolate, or isolates, selected for screening can have an effect on the determination of host susceptibility. Clarification of the range in variability on common rotat ion crops and the association of that variability to phylogenetic group could promote more informed management decisions. In the current study, we examined the virulence of AG2 - 2 isolates from sugar beet on common bean ( Phaseolus vulgaris L.), which is of ten grown in rotation with sugar beet (Buhre et al., 2009). Symptoms of Rhizoctonia root rot on common bean include reddish brown sunken lesions on the hypocotyl beginning below the soil line and extending downward (Hagedorn & Hanson, 2005). Above ground s ymptoms resemble drought stress and can be difficult to distinguish from other root diseases and abiotic conditions. Yellowing, wilting, stunting and leaf drop are typical above ground symptoms and are indicative of root tissue damage that has resulted in reduced water and nutrient uptake (Hagedorn & Hanson, 2005). Field level symptoms appear as patchy areas of dead plants or bare soil that tends to spread up the rows. Objectives Crop rotation is an integral part of Rhizoctonia - induced disease control in sugar beet as well as in other crops. Variability in virulence among isolates can confound studies of host susceptibility and produce inconsistent conclusions (Strausbaugh et al., 2013). The current 50 study examined the variability in virulence of 36 R. sola ni AG2 - 2 isolates on common bean. Virulence was assessed at both the seedling stage and 14 days after planting to determine age related effects. The relationship of that virulence to phylogenetic group was also analyzed to determine if subgroup association might give an indication of aggressiveness. Methods Thirty - six Rhizoctonia solani AG 2 - 2 isolates from North America (Table 2 - 1) and eight isolates from Europe and Japan (Table 2 - 2) were selected from those included in the phylogenetic analysis of Marti n et al . (2014) and grown on potato dextrose agar (PDA) (Sigma - Aldrich Corp., St Louis, MO). Inoculum was prepared in 100 x 20 mm plastic petri dishes using the whole grain method (Sneh et al., 1991). Hull - OR) were soaked overnight in distilled water and autoclaved for 40 minutes. Sterile barley was inoculated with 6 mm plugs cut with a #2 cork borer from actively growing cultures and incubated at room temperature until all grains were infested. Infested barley was air dried overnight in a biosafety cabinet and ground in a Waring grinder (Conair Corp., Stamford, CT) prior to use. Uninfested sterile barley was ground and used as a mock - inoculated control. Screening of U.S. isolates was conducted in a greenhouse w ith ambient temperatures incomplete block design with each isolate replicated four times per block and repeated once for a total of at least eight experimental units per isolate. Eight isolates collected from Europe and Japan were screened in a growth chamber (Conviron PGW36; Controlled Environments Inc., 51 methodology as above except th e experimental units were arranged in a completely randomized design. soaking in 0.6% sodium hypochlorite plus 0.1% Tween 20 for 15 minutes and then rinsed twice with sterile distilled water. Disinfested seed was treated with a 2% solution of metalaxyl (Allegiance - FL; Bayer Crop Science, Research Triangle Park, NC) prior to planting to protect against Pythium seed rot. Plants were grown in 1.75 liter (15 cm diameter) pl astic pots filled with commercial potting mix (SureMix Pearlite; Michigan Grower Products, Inc., Galesburg, MI). Prior to planting, potting mix was drenched with Gnatrol ® WDG (Valent USA Corp., Walnut Creek, CA) according to label instructions for control of fungal gnats. Plants were watered when the surface of the potting mix was dry to the touch. To test the virulence of the R. solani isolates on dry bean when inoculated at planting, pots were filled approximately 3/4 full with potting mix and three seed s placed on the surface. Ground inoculum was combined with additional potting mix at a rate of 1:500 (inoculum: potting mix; v/v) and the mix was used to finish filling pots so that seeds were covered to a depth of 1.5 - 2 cm. Plants were grown as above an d experiments were harvested 21 days after planting/inoculation. 52 Table 2.1 Disease severity of 36 Rhizoctonia solani AG2 - 2 isolates on the dry bean variety RedHawk showing state or phylogenetic group (PG) as determined by Martin et al. (2014). Plants inoculated at planting were rated for root rot 21 days after inoculation. Plants inoculated 14 days after planting were rated for root rot 14 days after inoculation. All plant s were rated on a scale of 0 to 6 where 0 = no disease and 6 = plant dead. Control was mock - inoculated with sterile barley. Expe riment was conducted in a greenhouse at 20 - Isolate Origin Collector ISG (4) PG Mean Disease Severity Inoculate at planting (3) Inoculated 14 days after planting (3) Rs1146 Minnesota, USA C. Windels III B 2B (2) 6.00 (1) a 3.17 ab Rs890 Minnesota, USA C. Windels IIIB 2A 6.00 (1) ab 2.27 c - f F30 Idaho, USA C. Strausbaugh IIIB 1 6.00 (1) ab 3.08 ab Rs393 Minnesota, USA C. Windels IV 1 6.00 (1) ab 3.45 a F503 Idaho, USA C. Strausbaugh IIIB 1 6.00 ab 3.16 a b F548 Idaho, USA C. Strausbaugh IIIB 1 5.96 ab 3.48 a R09 - 23 Michigan, USA L. Hanson IV 1 5.92 ab 2.28 c - f R09 - 25 Michigan, USA L. Hanson Int 2A 5.92 ab 2.23 c - f Rs1012 Minnesota, USA C. Windels IIIB 1 5.91 ab 3.08 ab F551 Idaho, USA C. Strausbaugh I IIB 1 5.88 ab 2.77 a - c 87 - 36 - 2 N. Dakota, USA C. Windels IIIB 1 5.70 a - c 3.11 ab F36 Oregon, USA C. Strausbaugh IIIB 1 5.68 a - c 2.05 c - g R09 - 2 Michigan, USA L. Hanson IIIB 1 5.64 a - c 3.19 ab Rs255 Minnesota, USA C. Windels IIIB 1 5.58 a - c 2.77 a - c F51 7 Idaho, USA C. Strausbaugh IIIB 1 5.47 a - c 3.32 ab F321 Idaho, USA C. Strausbaugh IIIB 1 5.45 a - c 2.69 bc Rs1090 Minnesota, USA C. Windels IV 2B 5.37 a - c 2.27 c - f Rzc35 (R4) Texas, USA C. Rush IIIB 2A 5.34 a - c 1.86 d - g 39AR Ontario, CAN C. Truman Int 1 5.12 a - c 2.76 a - c 24BR Ontario, CAN C. Truman Int 1 4.93 a - c 2.28 c - f Rs866 Minnesota, USA C. Windels IIIB 2A 4.91 a - d 1.72 e - g Rs106 Minnesota, USA C. Windels IV 2B 4.79 a - e 1.72 e - g Rzc16 (R9) Colorado, USA E. Ruppel IIIB 2A 4.65 b - e 2.02 c - g F508 Idaho, USA C. Strausbaugh IIIB 2A 4.55 b - e 2.24 c - f R09 - 28 Michigan, USA L. Hanson IV 2A 4.38 b - e 2.70 a - c R1 Colorado, USA E. Ruppel IIIB 2A 4.18 c - e 1.64 fg 2C13 Montana, USA B. Bugbee IV 2B 4.14 c - f 1.94 c - g F521 Idaho, USA C. Strausbaugh IIIB 2A 3 .50 d - g 1.88 c - g Rs200 Minnesota, USA C. Windels IV 2B 3.29 e - h 2.23 c - f Rs496 Minnesota, USA C. Windels IV 2B 2.75 f - i 2.52 b - d Rs599 Minnesota, USA C. Windels IV 2B 2.54 f - i 2.34 c - e Rzc21 (W - 22) Colorado, USA R.T. Sherwood IIIB 2A 2.29 g - i 1.57 fg Rs481 Minnesota, USA C. Windels IV 2B 1.79 h - j 2.33 c - e Rs296 Minnesota, USA C. Windels IV 2B 1.65 h - k 1.88 c - g Rs542 Minnesota, USA C. Windels IV 2B 1.38 i - k 1.35 g Rs588 Minnesota, USA C. Windels IV 2B 0.81 jk 1.67 e - g Control - - - - 0.22 k 0.55 h 53 Table 2.1 Disease severity of 36 Rhizoctonia solani AG2 - 2 isolates on the dry bean variety RedHawk Footnotes: (1) Values shown were adjusted t o reflect the maximum value of the 0 - 6 rating scale used. Actual least square estimate values were as follows: Rs1146 = 6.17; Rs890 = 6.15; F30 = 6.04; and Rs393 = 6.04. (2) Martin et al. (2014) identified isolate Rs11 46 as being in group 2B. Evidence f rom the current study and from microsatellite markers (this thesis, chapter 4) indicate that Rs1146 is probably in group 1 and will need to be reexamined. (3) Means within the same inoculation timing with the same letter are not significant ly different f Isolate Origin Collector ISG PG Mean Disease Severity Inoculated at planting (2) Inoculated 14 days after planting (2) Rickard Europe B. Holtschulte IIIB (1) 1 5.42 a 2.40 b Italian Europe B. Holtschulte IIIB ( 1) 2A 4.67 ab 3.33 a Cavallie Europe B. Holtschulte IIIB (1) 1 4.58 ab 3.17 ab Slovakia Europe B. Holtschulte IIIB (1) 1 4.08 ab 3.36 a R1 Colorado, USA E. Ruppel IIIB 2A 3.50 b 2.50 b Rzc89 (RH193) Japan H. Uchino IV 2B 1.75 c 3.30 a Rzc91 (RH65) Japan H. Uchino IV 2B 1.50 cd 2.64 ab Rzc6 (R - 164s)) Japan A. Ogoshi IV 2B 1.08 cd 2.45 b Rzc94 (RH188) Japan H. Uchino IV 2B 0.92 cd 2.45 b Control - - - - 0.08 d 0.08 c Table 2.2 Disease severity of 8 international Rhizoctonia solani AG2 - 2 isolates on the dry bean variety RedHawk showing phylogenetic group (PG) as determined by Martin et al. (2014). Plants inoculated at planting were rated for root rot 21 days afte r inoculation. Plants inoculated 14 days after planting were rated for root rot 14 days after inoculation. All plants were rated on a scale of 0 to 6 where 0 = no disease and 6 = plant dead. Control was mock - inoculated with sterile barley. Isolate (1) The Europeans claim to have only AG2 - within the same in 54 The virulence of AG2 - 2 isolates on dry bean when inoculated 14 days after planting was tested by sowing three seeds to a depth of 1.5 - 2 cm in pots filled with potting mix. Fourtee n days after planting, plants were inoculated by pulling the potting mix back from the stem and adding 0.62 cc of ground inoculum using a 1/8 tsp. measuring spoon. After adding inoculum, potting mix was filled in around the stem. Plants were grown as above and experiments were harvested 14 days after inoculation. Upon harvesting, roots were washed with tap water and rated for root rot on a scale of 0 to 6 where 0 = no disease; 1 = small lesions covering < 20% root tissue area; 2 = larger lesions covering 2 0 - 50% of the root tissue area; 3 = 50 - 90 % root tissue area affected; 4 = more than 90% root tissue area affected but pith still solid; 5 = more than 90% root tissue area affected and pith rotted; and 6 = plant dead. Disease severity (DS) score was calcula ted as the average of all disease severity ratings for a given isolate. Data was analyzed using the Proc GLIMMIX procedure in SAS 9.4 (SAS Institute, Inc., Cary, NC.) with replication and block considered random effects and the model set for unequal varia nce using the Kenward - Roger degrees of freedom approximation. Pairwise comparisons of severity of the phylogenetic groups. Linear regression analysis and box plot gra phics were generated using R Version 3.4.0 (R Core Team, 2017). 55 Results A total of 36 R. solani AG2 - 2 isolates, including 15 isolates from group 1, 10 from group 2A and 11 from group 2B, were inoculated at planting on dry beans and screened in a green house. Disease severity scores ranged from 0.81 to 6.00 with a mean score of 4.61 and a median score of 5.23 (Table 2. 1). When inoculated at planting, isolates in phylogenetic group 1 (mean DS = 5.64) were, on average, more aggressive (Tukey, p < 0.00 1) th an isolates in group 2A (mean DS = 4.36) and isolates in group 2A were more aggressive (Tukey, p < 0 .001) than isolates in group 2B (mean DS = 3.01) (Fig. 2. 1). Disease severity scores for isolates in group 1 ranged from 4.93 to 6.17 (Fig. 2. 2). Disease se verity scores for group 2A isolates ranged from 2.29 to 6.15 and group 2B isolates ranged from 0.81 to 5.37 (Fig. 2. 2). Group 2B isolates had the most variable disease severity scores with a range of 4.56 while group 1 isolates had the least variable disea se severity scores with a range of 1.24. Fourteen of the 15 isolates (93%) in group 1 had disease severity scores greater than 5.00 whereas group 2A and 2B had only 3 isolates out of 10 (30%) and 2 isolates out of 11 (18%), respectively, with disease score s over 5.00 (Fig. 2. 2). Side - by - side boxplot comparison (Fig. 2. 3) shows the three phylogenetic groups c learly differentiated from one another with group 1 having the highest median disease severity score and the smallest interquartile range. Isolate Rzc21 (W - 22) was identified as an outlier in group 2A with a DS value of 2.29. 56 a b c d 0.0 1.0 2.0 3.0 4.0 5.0 6.0 Control PG2B PG2A PG1 Disease Severity Phylogenetic Group Figure 2.1 Comparison of phylogenetic groups when inoculated at planting . Average disease severity by phylogenetic group (PG) of 36 R hizoctonia solani AG2 - 2 isolates inocul ated at planting on the dry bean variety RedHawk. Disease severity scores range from 0 to 6, where 0 = no disease and 6 = plant dead. Means with the same letter are - inoculated with sterile bar ley. Phylogenetic group was determined according to Martin et al. (2014). Error bar indicate standard error. 0% 20% 40% 60% 80% 100% Proportion of isolates Disease severity category Group 1 Group 2A Group 2B Figure 2.2 Distribution of disease severity scores when inoculated at planting. Thirty - six isolates of R hizoctonia solani AG2 - 2 were inoc ulated at planting on the dry bean variety RedHawk. Disease severity scale ranged from 0 to 6 where 0 = no disease and 6 = plant dead. Disease severity category designation was arbitrary and intended only to permit visualization of the distribution pattern s. Group designation is the phylogenetic group according to Martin et al. (2014). 57 T he same 36 isolates as above were inoculated on dry beans 14 days after planting and screened in the same greenhouse. Disease severity (DS) scores ranged from 1.35 to 3.48 with a mean score of 2.42 and median score of 2.28 (Table 2. 1). Isolates in phylogenetic group 1 (mean DS = 2.83) were, on average, more aggressive (Tukey, p < 0 .001) than isolates in group s 2A (mean DS = 1.97) or 2B (mean DS = 2.02) (Fig. 2. 4). Disease se verity scores for isolates in group 1 inoculated 14 days after planting ranged from 2.05 to 3.48 (Fig. 2. 5). Disease severity scores for isolates in group 2A inoculated 14 days after planting ranged from 1.57 to 2.70 and group 2B isolates ranged from 1.35 to 2.52 (Fig. 2. 5). Phylogenetic group 2A and group 2B had Figure 2.3 Side - by - side boxplot comparison of phylogenetic groups when inoculated at planting. Thirty - six isolates of Rhizoctonia solani AG2 - 2 wer e inoculated on the dry bean variety RedHawk with group 1: n = 15; group 2A: n = 10; group 2B: n = 11. Disease severity scale ranged from 0 to 6 where 0 = no disease and 6 = plant dead. Phylogenetic group is according to Martin et al. (2014). 58 similar median disease severity scores and range. Side - by - side boxplot comparison (Fig. 2. 6) indicated that group 1 was clearly differentiated from group s 2A and 2B, but had a similar range of dise ase severity values. There were no outliers identified in the isolates inoculated 14 days after planting. a b b c 0.0 1.0 2.0 3.0 4.0 5.0 6.0 Control PG2B PG2A PG1 Disease Severity Phylogenetic Group Figure 2.4 Comparison of phylogenetic groups when inoculated 14 days after planting. Average disease severity by phylogenetic group (PG) of 36 R hizoctonia solani AG2 - 2 isolates inoculated 14 days after planting on the dry bean variety RedHawk. Disease severity scale ranged from 0 to 6, where 0 = no disease and 6 = plant dead. Means with - inoculated with sterile barley. Phylogenetic group is according to Martin et al. (2014). Error bars indicate standard error. 59 0% 20% 40% 60% 80% 100% Proportion of isolates Disease Severity category Group 1 Group 2A Group 2B Figure 2.5 Distribution of disease severity scores when inoculated 14 days after planting. Thirty - six isolates of R hizoctonia solani AG2 - 2 isolates were inoculated 14 days after planting on the dry bean variety RedHawk. Disease se verity scale ranged from 0 to 6 where 0 = no disease and 6 = plant dead. Disease severity category designation was arbitrary and intended only to permit visualization of the distribution patterns. Group designation is the phylogenetic group according to Ma rtin et al. (2014). Figure 2.6 Side - by - side boxplot comparison of phylogenetic groups when inoculated 14 days after planting. Thirty - six isolates of Rhizoctonia solani AG2 - 2 were inoculated on the dry bean variety RedHawk with group 1: n = 15; group 2A: n = 10; group 2B: n = 11. Disease severity scale ranged from 0 to 6 where 0 = no disease and 6 = plant dead. Phylogenetic group is according to Martin et al. (2014). 60 Four isolates each from Europe and Japan had similar results with disease severity scores ranging from 0.92 to 5.42 for isolates inoculated at planting and from 2.40 to 3.36 for isolates inoculated 14 days after planting (Table 2. 2). Isolates in group 1 were, on average, more aggressive (Tukey, p < 0 .001) than isolates in group 2B when inoculated at planting (Fig. 2. 7). The correlation betwe en disease severity on plants inoculated at planting and disease severity on plants inoculated 14 days after planting had a significant linear component with a correlation coefficient of 0. 618 (F = 20.97, p < 0 .001) and an R 2 value of 0. 382 (Fig. 2. 8). The coefficient for disease severity on plants inoculated at planting was 1.63 which indicates that disease severity on plants inoculated at planting increases 1.63 points for every 1.0 point increase in disease severity on plants inoculated 14 days after pla nting. A B BC C a b c d 0.0 1.0 2.0 3.0 4.0 5.0 6.0 Control PG2B PG2A PG1 Disease Severity Phylogenetic Group Inoculated 14 d. after planting Inoculated at planting Figure 2.7 Comparison of phylogenetic groups for international isolates. Eight internati onal isolates of Rhizoctonia solani AG2 - 2 from Europe and Japan were inoculated on the dry bean variety RedHawk at planting or 14 days after planting. Disease severity scale ranged from 0 to 6 where 0 = no disease and 6 = plant dead. Means with the same le tter were not significantly lowercase letters are for inoculations at planting. Control was mock - inoculated with sterile barley. Isolate R1 was used as a positiv e control. Phylogenetic group is according to Martin et al. (2014). Error bars indicate standard error. 61 C omparison of the traditional subgroups AG2 - 2IIIB and AG2 - 2IV produced different results for plants inoculated at planting and for those inoculated 14 days after planting (Fig. 2. 9). Plants inoculated at planting had significant differences betwee n the groups (p = 0 .004) with average disease severity scores of 5.23 for AG2 - 2IIIB isolates and 3.44 for AG2 - 2IV isolates. Plants inoculated 14 days after planting showed no significant differences between the groups (p = 0 .100) with average di sease severity scores of 2.55 for AG2 - 2IIIB isolates and 2.21 for AG2 - 2IV isolates. 0 1 2 3 4 5 6 7 1 2 3 4 Disease severity on plants inoculated at planting Disease severity on plants inoculated 14 days after planting Figure 2.8 Scatterplot comparing disease severity on dry bean when inoculated at planting and at 14 days after planting. Thirty - six isolates of Rhizoc tonia solani AG2 - 2 were inoculated on the dry bean variety RedHawk. Disease severity scale ranged from 0 to 6 where 0 = no disease and 6 = plant dead. Trendline is a linear regression (p < 0.001) with a slope of 1.63 and an R 2 of 0.38. 62 Discussion There was considerable variation in virulence among the R. solani AG2 - 2 isolates tested, which was consistent with what other researchers have found (Carli ng et al., 2002b; Kuninaga et al., 1997; Strausbaugh et al., 2011). Disease severity scores for plants inoculated at planting ranged from 0.81 to 6.00 with three of thirty - six (8%) isolates not significantly different than the mock - inoculated control and f ive (14%) isolates that killed all plants they were tested on. Although disease severity scores were lower for plants inoculated 14 days after planting there was less variability. Disease severity scores ranged from 1.35 to 3.48 with all isolates significa ntly different than the mock - inoculated control. These results are consistent with other studies of variability in virulence such as Strausbaugh et al. (2011a) that reported disease severity from 19% to 100% on sugar beet roots. Isolates in phylogenetic g roup 1 were, on average, significantly more aggressive than group 2A or group 2B isolates on both beans inoculated at planting and those inoculated 14 days after planting (Fig. 2. 1 & Fig. 2.4 ). Group 2A isolates were, on average, more aggressive than isola tes in group 2B but only on plants inoculated at planting. In general, isolates in group 2B were less aggressive than isolates in the other two groups, although they were statistically similar to isolates in group 2A when inoculated 14 days after planting. Since group 2B isolates are primarily type IV and group 1 isolates are primarily type IIIB, these results are consistent with previous reports that identified AG2 - 2IIIB isolates as being more aggressive th an AG2 - 2IV isolates (Engelkes & Windels, 1996; Str au sbaugh et al., 2011a; Windels & Brantner, 2006). In the current study, there were significant differences in virulence between isolates identified as AG2 - 2IIIB and those identified as AG2 - 2IV by temperature response, but only when 63 inoculated at planting (Fig. 2. 9 ). On seedlings, disease severity scores of isolates identified as AG2 - 2IIIB were clustered towards the high end of the scale with 70% having disease severity scores greater than 5.00 (Table 2.1 ). Disease severity scores of isolates identified as AG2 - 2IV were much more evenly distributed among the severity classes with some isolates being very weak and some very aggressive (Table 2.1 ). For example, isolates Rs393, Rs1090 and R09 - 23 were identified as type IV, but had disease severity scores that we re not significantly different than the type IIIB isolate with the highest disease severity score on plants that were inoculated at planting. Conversely, the only isolates that did not cause significantly more disease symptoms than the mock - inoculated cont rols were type AG2 - 2 IV. Phylogenetic group appears to provide a potential prediction of virulence with group 1 being consistently more virulent than group s 2A and 2B when inoculated both at planting and at 14 days after planting. However, in this study, av erage virulence of group s 2A and 2B was only significantly different when inoculated at planting. Identification of the phylogenetic group for isolates present in a specific field could aid in management decisions by predicting risk associated with plantin g a particular crop. For example, the presence of group 1 isolates in a field could indicate that planting dry beans would be risky and high levels of disease are likely to develop. Unfortunately, since several isolates in group s 2A and 2B had disease seve rity scores greater than 5.00 when inoculated at planting, the presence of particular isolates in group 2A or 2B would still pose an elevated risk. Therefore, phylogenetic group is only marginally better at predicting virulence than the original designatio ns of AG2 - 2IIIB and AG2 - 2IV. Ultimately, risk depends on the individual isolates present and the identification of specific virulence factors would be recommended in order to accurately predict disease risk. 64 Regardless of the risk associated with phylog enetic group, most of the isolates tested in the current study caused considerable disease symptoms on the dry bean variety RedHawk. The current study is certainly not the first to report the susceptibility of dry beans to Rhizoctonia solani AG2 - 2 (Engelke s & Windels, 1996; Galindo et al., 1982; Muyolo et al., 1993). However, most studies only examined a limited number of isolates and so did not represent the full range of variability present in R. solani AG2 - 2. Our data includes representatives of differen t genetic groups and provides a more comprehensive assessment of the variability within the AG2 - 2 group. Other researchers have concluded that beans and sugar beet should not be grown in close rotation (Engelkes & Windels, 1996; Ruppel, 1985; Windels & Br antner, 2004) because both crops were susceptible to AG2 - 2IIIB and AG2 - 2IV isolates. The results of the current study generally agree with that conclusion since many of the isolates recovered from sugar beet were also aggressive on dry beans. Some isolates were non - virulent or caused low - levels of disease a c b c 0.0 1.0 2.0 3.0 4.0 5.0 6.0 Inoculated at planting Inoculated 14 days after planting Average Dissease Severity AG2-2IIIB AG2-2IV Figure 2.9 Comparis on of disease severity by traditional subgroups AG2 - 2IIIB and AG2 - 2IV. Thirty - six isolates of Rhizoctonia solani were inoculated on the dry bean variety RedHawk. Disease severity scale ranged from 0 to 6, where 0 = no disease and 6 = plant dead. Traditiona l subgroups, also referred to as intraspecific groups (ISG), different. Error bars indicate standard error. 65 but unfortunately, these weak strains do not correlate well enough with a particular group to allow the designation of a low risk group. Overall, group s 2A and 2B may not be as aggressive as group 1 on dry beans, but, individual isolates can still pose a substantial risk to dry beans. In addition, more testing is needed on additional rotational crops. The intent would be to identify rotational crops that increase the prevalence of highly aggressive strains of R. solani AG2 - 2 and to avoid using those crops in rotation. For example, including corn in the rotation has been shown to increase the prevalence of AG2 - 2IIIB strains, which have been considered more aggressive on sugar beet (Windels & Brantner, 2004; Windels & Brantner, 2006). However, these conclusions need to be reassessed in order to accommodate the revised genetic groups of Martin et al. (2014). Moreover, the role that rotational crops play in influencing inoculum levels and strain prevalence is co mplex. Host susceptibility alone is an incomplete indicator of how crop rotation will affect populations of R. solani (Ruppel, 1985). Instead, there are several factors that need to be considered when determining suitable crops for rotation including: how well residues are colonized; soil conditions, such as nitrogen levels; and regional differences in climate, soil type, and variety choices (Ruppel, 1985; Rush & Winter, 1990). For these reasons, it is not prudent to make management decisions based on susce ptibility data alone. Field experiments that assess the effects of rotation crops on subsequent crops need to be conducted in each growing region. To my knowledge, comprehensive testing of crop rotations in relation to RRCR of sugar beet has not been condu cted in Michigan. The virulence of isolates when inoculated at planting was significantly correlated to virulence when inoculated 14 days after planting indicating that those isolates that were 66 aggressive on young plants were also aggressive on older plan ts. However, the R 2 value of this relationship was only 0. 382 indicating that only 38% of the variance is due to general aggressiveness of the isolate under these conditions. The majority of the variation in virulence may be explainable as a differential r esponse to host age. Age - related resistance has been described for several pathosystems (Develey - Rivière & Galiana, 2007; Panter & Jones, 2002; Kus et al., 2002) including common beans (Bateman & Lumsden, 1964). The cuticle appears to play an important rol e in age - related resistance of common bean, becoming more resistant to invasion as the plant ages (Stockwell & Hanchey, 1984). However, since seedling bean plants are especially susceptible to R. solani AG2 - 2, management practices that delay or slow diseas e progress, such as fungicide treatments, may be needed to allow the plants to develop to the stage where they have a greater resistance to infection. Another potential explanation for the differential response between inoculation at planting and inoculat ion 14 days after planting may be that the specific combination of cell wall degrading enzymes (CWDE) produced by a particular isolate could affect the ability of the isolate to penetrate the c ell wall at different growth stages (Bellincampi et al., 2014; Scala et al., 1980). The R. solani AG2 - 2IIIB genome has been predicted to have over 1,000 putative CWDE (Wibberg et al., 2016) providing substantial enzymatic variations with which to overcome physical barriers. Variation in the structure or regulation of these enzymes could affect the ability of the pathogen to overcome variations in plant defensive str ategies such as polygalacturonase - inhibitor proteins (Bergmann et al., 1994; Matteo et al., 2006). Thus, identification and characterization of the interact ions between pathogen cell wall degrading enzymes and host defenses could provide insight into host resistance. 67 Conclusions Rhizoctonia solani AG2 - 2 is highly variable in its virulence on dry beans ( Phaseolus vulgaris ), with strains ranging from very ag gressive to non - pathogenic. Although most strains cause substantial disease symptoms on the dry bean variety RedHawk, phylogenetic group 1 was significantly more aggressive on plants inoculated both at planting and 14 days after planting than were groups 2 A and 2B. There was little difference in virulence between group s 2A and 2B in regard to virulence on dry beans. Because both beans and sugar beet are susceptible to R. solani AG2 - 2, care should be taken when growing them in rotation in fields with a histo ry of Rhizoctonia disease. 68 REFERENCES 69 REFERENCES Anderson, N.A. (1982). The genetics and pathology of Rhizoctonia solani . 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Rhizoctonia inoculum and rotation crop effects on a following sugarbeet crop. Sugarbeet Research and Education Board of Minnesota and North Dakota. 37: 182 Windels, C.E., Jacobsen, B.J. and Harveson, R.M. (2009). Rhizoctonia r oot and c rown rot. Pages 33 - 36 in Compendium of Beet Diseases and Pe sts. Edited by Harveson, R.M., Hanson, L. E. and Hein, G.L. , APS Press, St. Paul, MN. Windels, C. and Nabben, D. (1989). Characterization and pathogenicity of anastomosis group or Rhizoctonia sola ni isolated from Beta vulgaris . Phytopathology, 79: 83 - 88. 74 CHAPTER 3 : VARIABILITY IN THE VIRULENCE OF RHIZOCTONIA SOLANI AG2 - 2 ISOLATES ON SUGAR BEET SEEDLINGS IN RESPONSE TO LOW TEMPERATURE 75 Introduction Rhizoctonia solani Kühn is a ubiquitous, soilborne fungus that can cause disease on several economically important crops (Anderson, 1982; Ogoshi, 1987; Sneh, 1991). Traditionally, strains of R. solani have been categorized into anastomosis groups (AG) based on the ability of the hyphae to fuse ( Ogoshi, 19 87; Sneh, 1991) with at least 13 AG presently recognized (Carling et al., 2002b; Cubeta & Vigalys, 1997). R. solani AG2 - 2 is the primary causal agent of Rhizoctonia root and crown rot (Windels, et al. 2009) in sugar beet ( Beta vulgaris L.) but ca n also cause significant seedling disease, typically referred to as damping - off (Harveson, 2009; Kirk et al., 2008; Windels & Brantner, 2005). Substantial economic losses due to damping - off can occur in all regions where sugar beets are grown (Harveson, 20 09; Herr, 1996). Damping - off can present itself as a seed or pre - emergence decay which is usually recognized by poor stand establishment (Baker, 1970). More commonly, R. solani is associated with post - emergent damping - off, which can occur at any time aft er emergence until the seedling is past the juvenile stage (Baker, 1970; Harveson, 2009; Herr, 1996) . Post - emergent decay caused by R. solani usually begins at or near the soil line and primarily affects the area of the hypocotyl just below the soil surfac e, although the disease can progress further down into the root (Fig. 3. 1). Lesions are dark brown to black and can weaken the stem, causing the seedling to wilt and collapse , often resulting in death of the plant. Field level symptoms tend to occur in ir regular patches or down the rows as the pathogen spreads (Herr, 1996; Windels et al., 2009). 76 One of the recommendations for managing losses from Rhizoctonia is to plant early when there is a reduced risk of infection (http://cropwatch.unl.edu/plantdis ease/sugarbeet /rhizoctonia - root - crown - rot ; Leach, 1986 ; Leach & Garber, 1970; Windels & Brantner, 2005). However, there are diverse reports as to what soil temperature presents a reduced risk. The most widely cited temperature below which R. solani becom Crystal Sugar Company, 2016; Harveson, 2009; Neher & Gallian, 2011) but other sources have R. solani activity (Harveson, 2008; Windels & Brantner, 2005). Sugar beet is typically planted wh al., 2008) making it important to understand when risk of infection begins so that appropriate management practices can be implemented. For example, the American Crystal Sugar Company (2016) recommends f Figure 3.1 Sugar beet seedlings in various stages of decay from Rhizoctonia solani AG2 - 2 infe ction. Dark brown to black lesion extends downward from the soil surface. As the disease progresses, it can cause leaves to wilt and yellow, the stem to become weakened and the plant to collapse, and finally die. Plants were rated on a scale of 0 to 5 whe from left). 77 could be vulnerable to infection for three to four weeks before initial fungicide application . In general, R. solani being optimal for disease progression (Baker & Martinson, 1970; Bolton et al., 2010; Kirk et al., 2008; Windels et al., 2009 ). However, R. solani AG2 - 2 is traditional ly subdivided into two main subgroups that are distinguished by temperature tolerance. AG2 - 2IIIB is recognized as a high - R. solani AG2 - h et al., 1991). This separation of groups based on temperature suggests the possibility that th ere could be some differential response to low temperatures as well and that the group AG2 - 2IV may have a lower temperature range than the group AG2 - 2IIIB. Exp eriments conducted by Bolton et al. , (2010) indicate that R. solani AG2 - 2 does not lthough there was no significant difference in disease severity between isolates of AG2 - 2IIIB and AG2 - 2IV under those conditions. Based on these experiments, it appears the minimum temperature for infection of AG2 - 2 isolates in either sub - ich is the value most commonly cited as below which R. solani is inactive. It should be noted, however, that these experiments were conducted with a single isolate of AG2 - 2IIIB and a single isolate of AG2 - 2IV, both collected in the Minnesota beet growing r egion. Since R. solani is such a diverse group (Chapter 2, this thesis; Ohkura et al., 2009; Strausbaugh et al., 2011), conclusions based on tests using a single isolate may be questionable. 78 In contrast to the above report, some work out of Ireland showed that there were differential responses to low temperatures in AG2 isolates, with one of the AG2 isolates they tested being mo 1991). The authors did not classify the isolates as to whether they belonged to the subgroups AG2 - 1 or AG2 - 2, and so the relationship of the isolates they tested to those tested by B olton et al. (2010) is uncertain. AG2 - al., 1991) and have been isolated from sugar beet seedlings (Naito et al., 1975 as referenced b y Sneh et al., 1991; Windels & Nabben, 1989). Kaminski & Verma (1985) reported that optimal temperature for growth of AG2 - 1 isolates from rapeseed ( Brassica napus L. and B. campestrus L.) was lower than for AG4 isolates and that AG2 - 1 isolates exhibited growth at temperatures as - 1 caused a significant reduction in stand counts on sugar beet seedlings, although it was a we ak pathogen on adult and Kavanagh (1991) was an AG2 - 1 strain, rather than an AG2 - 2, but this is uncertain. Studies on the virulence of AG2 - 2 isolates generally compare ratings between sub groups (Carling et al., 2002a; Kuninaga et al., 1997; Strausbaugh et al., 2011) with broad agreement that AG2 - 2IIIB, as a whole, is more virulent than AG2 - 2IV. Although studies that examine variation in virulence within AG2 - 2 ar e limited, those studies that have been reported show considerable variation among AG2 - 2 isolates. Strausbaugh et al. (2011) reported that root rot on adult sugar beet varied from 19% to 100% among 47 AG2 - 2IIIB isolates and from 34% to 71% among 4 AG2 - 2IV isolates. Virulence trials on corn also showed variability in disease severity, with median scores ranging from 1 to 4 on a scale of 0 to 5 (Ohkura et al., 2009). Minier 79 (Chapter 2, this thesis) found significant differences in virulence among AG2 - 2 isola tes on dry beans ( Phaseolus vulgaris ). Isolates classified as AG2 - 2IIIB ranged in virulence from 26% to 58% on adult plants and 38% to 100% on seedlings; whereas AG2 - 2IV isolates ranged from 22% to 58% on adult plants and 14% to 100% on seedlings. Sequenc e analysis of the internal transcribed spacer (ITS1 and ITS2) and 5.8S subunit of the ribosomal DNA (rDNA) region has also demonstrated variability within as well as between AG2 - 2 subgroups (Gonzalez et al., 2001; Salazar et al ., 2000; Strausbaugh et al ., 2011). In general, classification using rDNA sequences supports the classic groups based on anastomosis (Gonzalez et al., 2001; Sharon et al., 2008), although the relationships within the group AG2 - 2 are not as clear, particularly when based solely on rDNA - ITS analysis (Carling et al., 2002b; Liu & Sinclair, 1992; Strausbaugh et al., 2011). The phylogenetic analysis of the anastomosis group AG2 1 presented by Carling et al. (2002a) showed that subgroup AG2 - 2IV was polyphyletic with at least two clusters of AG2 - 2IV isolates surrounding a cluster of AG2 - 2IIIB isolates. Strausbaugh et al. (2011) had similar results, with AG2 - 2IIIB isolates mixed in with and surrounding a cluster of AG2 - 2IV isolates. A multi - gene phylogenetic analysis by Martin et al. (2014) con firmed that the traditional sub - groups known as AG2 - 2IIIB and AG2 - 2IV were not phylogenetically supported (Fig. A 3 . 1 ) . Instead, there are at least three genetic groups within AG2 - 2 that contain a mix of AG2 - 2IIIB and AG2 - 2IV isolates. This finding raises q uestions regarding studies on virulence and other screenings that ascribe phenotypic characteristics to the traditional sub - groups. 1 Whether AG2 - 1 and AG2 - 2 are sub - types of a single anastomosis group, AG2, or separate and independent anastomosis groups has been controversial since they can anas tomose with each other at low rates. Current evidence indicates that they are, in fact, separate and independent groups (Gonzalez et al. , 2016; Veldre et al. , 2013). 80 Objectives Little has been reported on the variability in virulence within Rhizoctonia solani AG2 - 2, especially regarding t he effect of low temperature on virulence and sugar beet seedling diseases. In addition, the work by Martin et al. (2014) indicates that traditional sub - group designations within AG2 - 2 are not ph ylogenetically supported (Fig. A 3 . 1 ) and therefore, inference s regarding group characteristics need to be reexamined. In the current study, we evaluate the virulence of 35 AG2 - 2 isolates in response to low temperature and the relationship of that response to the phylogenetic groupings. Methods Selection of AG2 - 2 I solates Isolates were chosen from the culture collection of Linda Hanson (USDA - ARS, East Lansing, MI) as representatives of the three phylogenetic groups identified by Martin et al. (2014). All isolates screened in this study (Table 3. 1) had been isolated previously from sugar beet ( Beta vulgaris ) from diverse growing regions and stored on whole barley grains (Sneh et al., 1991) at - potato dextrose agar (PDA; Sigma - Aldrich, St. Louis, MO) for 10 - 14 d ays to verify culture characteristics. 81 Isolate Phylogenetic group ISG designation Origin Original collector 24 BR 1 Intermediate Ontario C. Truman C116 1 IIIB Japan A. Ogoshi F30 1 IIIB ID C. Strausbaugh F36 1 IIIB OR C. Strausbaugh F503 1 IIIB ID C. Strausbaugh F548 1 IIIB ID C. Strausbaugh F551 1 IIIB ID C. Strausbaugh R09 - 2 1 IIIB MI L. Hanson R09 - 23 1 I V MI L. Hanson Rs1012 1 IIIB MN C. Windels Rs331 1 IIIB MN C. Windels Rs393 1 IV MN C. Windels Rs470 1 IIIB MN C. Windels Rs571 1 IIIB MN C. Windels Slovakia 1 IIIB (1) Europe B. Holtschulte F508 2A IIIB ID C. Strausbaugh F521 2A IIIB ID C. Strausb augh Italian 2A IIIB (1) Europe B. Holtschulte R09 - 25 2A Intermediate MI L. Hanson R09 - 28 2A IV MI L. Hanson R1 2A IIIB CO E. Ruppel Rs866 2A IIIB MN C. Windels Rzc16 (R9) 2A IIIB CO E. Ruppel Rzc21 (W - 22) 2A IIIB WI R.T. Sherwood 2C13 2B IV MT B. Bugbee Rs106 2B IV MN C. Windels Rs1090 2B IV MN C. Windels Rs1146 2B IIIB MN C. Windels Rs200 2B IV MN C. Windels Rs481 2B IV MN C. Windels Rs496 2B IV MN C. Windels Rs588 2B IV MN C. Windels Rs599 2B IV MN C. Windels Rzc6 (R164S) 2B IV Japan A. Ogoshi Rzc94 (RH188) 2B IV Japan H. Uchino Table 3.1 Rhizoctonia solani AG 2 - 2 isolates used in the current study. Phylogenetic group shown Locale indicates state or region of isolation. All isolates were originally isolated from sugar beet roots. reported from Europe. 82 Preparation of Inoculum Inoculum was prepared in 100 x 20 mm plastic petri dishes using the whole grain method (Sneh, et. al., 1991). Hull - soaked overnigh t in distilled water and autoclaved for 40 minutes. Sterile barley was added to a petri dish so that the dish was about half full. Barley was inoculated with four 6mm plugs cut from actively growing cultures with a #2 cork borer and incubated at 21 - 7 days until all grains were infested. Infested barley was air dried overnight in a biosafety cabinet and ground in a Waring grinder (Conair Corp., Stamford, CT) prior to use. Uninfested, sterile barley was ground as above to be used as a mock - ino culated control. Analysis of the Virulence of AG2 - 2 Isolates on Sugar Beet Seedlings The virulence of thirty - five Rhizoctonia solani AG2 - 2 isolates (Table 3. 1) was evaluated n, 2004), a monogerm, R. solani - susceptible germplasm. Experiments were conducted in a growth chamber (Conviron PGW 36, Controlled Environments Inc., Pembina, ND) set to a 14 hour photoperiod and were arranged in an incomplete block design. Each isolate wa s replicated three times per block and repeated once for a total of at least six experimental units per isolate. Each block included a mock - inoculated control using uninfested, sterile barley as the inoculum. Sugar beet seed was surface sanitized by soaki ng in 0.6% sodium hypochlorite plus 0.1% Tween 20 solution for 15 minutes and then rinsed twice in sterile water. To enhance germination, sanitized seed was soaked overnight in a 0.3% hydrogen peroxide solution ( McGrath et al., 2000 ) with shaking at 120 rp m. Disinfested seed was treated with a 2% solution of metalaxyl (Allegiance - FL; Bayer Crop Science, Research Triangle Park, NC) prior to planting to 83 protect against Pythium seed rot. Seed was sown, in excess, in 1.75 L (15 cm diameter) plastic pots partial ly filled with potting mix (Suremix Pearlite; Michigan Grower Products, Galesburg, MI) and covered with about 1.0 to 1.5 cm of additional potting mix. Initia l experiments where hed the two leaf stage (about 7 - 10 days after planting), pots were thinned or transplanted as needed to five plants per pot. When the chamber was at the desired temperature, 0.62 cc of ground inoculum was sprinkled C for 7 days and then removed from pots and the potting mix was rinsed from roots using tap water. The root and hypocotyl were examined for disease symptoms, as described above (Fig. 3. 1), and rated on a scale of 0 to 5 where 0 = no disease, 1 = lesion cov ered less than 20% of the tissue, 2 = lesion covered about 20 - 60% of the tissue, 3 = lesion covered 60 - 90% of the tissue but tops still appear healthy, 4 = lesions covered more than 90% of the tissue and the plant was wilted but not completely dead, 5 = plant was completely dead. Representative plants with characteristic infection symptoms were surface sanitized and plated on 2% water agar plates to confirm the presence of R. solani . Data was analyzed using PROC MIXED (SAS 9.4; SAS Institute Inc., Cary , NC) with block one - 0. 05) was used to 84 identify isolates that caused disease as compared to the mock - inoculated controls. Average - test assuming unequal variances w as used to compare means based on previous sub - group Growth Rate of AG2 - 2 Isolates in vitro To determine if the virulence of R. solani isolates is related to fung al growth rate, particularly at low temperatures, 12 isolates were selected from those that had been screened and selecting every third isolate. A second set of 1 2 isolates were selected in the same manner starting with the isolate that had the second highest average disease severity rating. Two isolates used on the first run (R1 and F503) representing moderate and fast growth rates at ond run to ensure consistency of the two runs. Fungal isolates were grown on PDA for 5 - 7 days at 2 1 borer from near the margin of the growing cultures was transferred to a fresh 100 x 15 mm PDA plate. Each isolate was rep licated three times. Plates were sealed with Parafilm (Bemis Flexible Packaging, Oshkosh, WI) and maintained in an incubator (New Brunswick Innova 44R; Eppendorf, Hauppauge, 4 days by measuring with calipers from the edge of the plug to the margin of the growing and the margin of the growing mycelium was marked on the plate with an ultra - fine point marker (Sharpie, Chicago, IL). Measurements were taken from this reference mark to the 85 Data was analyzed using PROC MIXED (SAS 9.4; SAS Institute Inc., Ca ry, NC) with block and replication considered random effects. Regression analysis was performed using PROC REG (SAS 9.4; SAS Institute Inc., Cary, NC). Results Selection of Isolates The phylogenetic analysis of Martin et al. (2014) identified two well su pported clades, one of which consisted of two sub - clades. These clades were labeled as group 1, group 2A and group 2B (Fig. A 3 . 1 ). Fifteen of the 29 (52%) isolates identified as group 1, nine of the 11 (82%) identified as group 2A, and 11 of the 16 (69%) i n group 2B were selected for this study for a total of 35 isolates (Table 3. 1). Eighteen (51%) were previously designated as AG2 - 2IIIB and 13 (37%) as AG2 - 2IV. Two isolates (6%) were previously designated as intermediate, with a growth de designation of AG2 - 2IIIB and AG2 - 2IV uncertain and two isolates (6%) 2 Virulence of AG2 - .47 to 3.92 (Table 3. 2 ) with 27 isolates (77%) having disease severity (DS) significantly higher than the mock - 0 nce scores (DS = 1.2 to 2.0) had the greatest number of isolates (34%) while 3. 2 ). 2 Both isolates were from Europe where it is stated they have only isolates from cultural type AG2 - 2IIIB; but they were not tested for growth at and so were treated as undesignated for the purposes of this study. 86 Isolate PG Previous sub - group N 11C 21C Reduction in rate Mean Std Err Mean Std Err Control - - 60 0.17 0.239 0.22 0.205 - Rzc21 2A IIIB 30 0.47 0.306 2.18 0.229 93% Rs588 2B IV 30 0.48 0.306 1.13 0.267 86% F551 1 IIIB 30 0.71 0.306 3.83 0.272 94% Slovakia 1 - 30 0.88 0.264 3.51 0. 267 92% Rs331 1 IIIB 30 0.94 0.306 1.20 0.272 74% R09 - 25 2A Intermediate 15 0.98 0.406 2.84 0.272 88% C116 1 IIIB 45 1.04 0.264 2.36 0.272 85% Rzc6 2B IV 30 1.17 0.306 1.10 0.272 85% R09 - 23 1 IV 30 1.24 0.306 3.77 0.272 65% Rs106 2B IV 30 1.27 0.306 3.97 0.272 89% Rs866 2A IIIB 30 1.30 0.306 4.24 0.272 90% Rzc94 2B IV 30 1.30 0.306 3.66 0.272 88% Rs599 2B IV 30 1.36 0.304 3.71 0.267 88% 2C13 2B IV 30 1.52 0.306 4.04 0.272 87% Rs481 2B IV 30 1.53 0.304 3.55 0.267 86% Rs1012 1 IIIB 30 1.73 0.306 4 .26 0.272 86% Rs571 1 IIIB 30 1.76 0.304 3.63 0.272 84% Rs200 2B IV 15 1.78 0.406 3.93 0.267 85% R1 2A IIIB 60 1.90 0.239 4.12 0.205 85% 24BR 1 Intermediate 30 1.93 0.306 4.17 0.272 85% F548 1 IIIB 30 2.10 0.306 3.87 0.272 82% F503 1 IIIB 30 2.42 0.3 06 4.17 0.272 81% R09 - 2 1 IIIB 30 2.59 0.306 2.87 0.272 70% Rs1146 2B IIIB 30 2.77 0.306 2.91 0.267 68% Rs496 2B IV 30 2.77 0.306 3.25 0.267 72% R09 - 28 2A IV 30 2.80 0.306 4.17 0.272 78% F508 2A IIIB 30 2.82 0.306 4.31 0.267 78% Rs470 1 IIIB 30 3.01 0.306 5.00 (1) 0.272 80% Rzc16 2A IIIB 30 3.12 0.306 4.50 0.272 77% Italian 2A - 30 3.14 0.306 4.50 0.272 77% F30 1 IIIB 30 3.30 0.306 3.77 0.272 71% F36 1 IIIB 30 3.33 0.306 1.90 0.272 42% Rs1090 2B IV 30 3.44 0.306 4.05 0.267 72% F521 2A IIIB 30 3.4 6 0.306 2.61 0.362 56% Rs393 1 IV 30 3.92 0.306 3.90 0.272 66% Table 3.2 Mean disease severity scores of 35 Rhizoctonia solani AG2 - Bolding indicates means that are not significantly different than the mock - Phylogenetic group (PG) designation is according to Martin et al. (2014). Previous sub - group is the traditional e indicates is considered and is calculated by the formula: (R21 - R11) / R21 where Ry = rate of disease progress at temperature y (see text; equations 3.1 & 3.2). Note: (1) Value was adjusted to reflect the maximum value of the 0 - 5 rating system used. Least square means estimate 87 There were 174 plants out of a total of 1110 observations (16%) that were scored as a . Those plants that were 37%, group 2A at 26% and group 2B at 37%. Mean disease scores ged from 1.10 to 5.00 (Table 3. 2 ) with 34 isolates (97%) having disease severity significantly higher than the mock - 0 f categories (Fig. 3. 3 - 3. 2 ). Figure 3.2 Disease severity of 35 Rhizoctonia solani AG2 - 2 isola tes on Plants were rated on a 0 to 5 scale where 0 = no disease and 5 = plant dead. Virulence - - the mock - 0 2 4 6 8 10 12 14 Number of Isolates 88 group 2A were, on average, more aggressive than isolates in group 0 .05) while isolates in group 1 were intermediate between group 2A and group 2B (Fig. 3. 4 ). All three phylogenetic groups had significantly higher average disease severity scores than the mock - (Fig. 3. 4 ). 0 2 4 6 8 10 12 14 Number of Isolates Figure 3.3 Disease severity of 35 Rhizoctonia solani AG2 - 2 isolates on sugar beet Plants were rated for disease on a scale of 0 to 5 where 0 = no disease and 5 = plant - - different than the mock - 89 ic group (Fig. 3. 5 ) shows that group 1 and group 2A had about an equal proportion of isolates in each virulence category Group 2B had a large proportion of isolates (55%) in th Figure 3.4 Average disease severity of 35 Rhizoctonia solani AG2 - 2 isolates on sugar beet seedlings Plants were rated for disease severity on a scale of 0 to 5, where 0 = no disease and 5 = plants dead. upper case le et al. (2014). Error bars indicate standard error of the means. A B BC C a b bc c 0.0 1.0 2.0 3.0 4.0 5.0 Control PG 2B PG 1 PG 2A Average Disease Severity Phylogenetic Group 11C 21C 90 the time of exposure to severity scores difficult . In this situation, we as sumed Rhizoctonia damping - off would behave like a monocyclic disease and therefore disease progress was considered to be linear according to the following model (Arneson, 2001): Equation 3. 1 where R y = ra te of disease progress at temperature y; x = disease severity; t = time; and Q = initial amount of inoculum. Figure 3.5 Proportion of 35 Rhizoctonia solani isolates in each virul ence category at Plants were rated for disease on a scale of 0 to 5 , where 0 = no disease and 5 = plant dead. Virulence categories are defined as: - 01 to 3.00), high (DS = 3.01 to - than the mock - Phylogenetic grouping (PG) is according to Martin et al. (2014). 0% 10% 20% 30% 40% 50% 60% Proportion of isolates Mean Disease Severity Group 1 Group 2A Group 2B 91 Equation 3. 2 where R 21 d R 11 Reduction in virulence ranged from 42% to 94% (Table 3. 2 ) with an average reduction of 80%. (ANOVA, p = 0 .787) or by t - test, df = 29, p = 0 .206). Virulence of AG2 - 2 Isolates Related to Sub - groups IIIB and IV There were 18 isolates that were previously designated as sub - previously designated as sub - and 4 isolates whose sub - group designation was either unknown or classified as intermediate. Comparison of means based on previous sub - group designations was not significant for - test, df = 25, p = 0 screen (t - test, df = 26, p = 0 .939) . At e were a greater number of AG2 - 2IIIB isolates with disease severity ratings higher than the median value (median = 1.78) compared to AG2 - 2IV i 2 = 1.70, df = 1, p = 0.192). Isolates whose sub - group designation was unknown or intermediate were not included in this comparison. Growth Rate of AG2 - 2 Isolates in vitr o Twenty - isolates were selected from group 1, six from group 2A and nine from group 2B (Table 3. 3 ). fference between runs (ANOVA, p = 0. 0. together. 92 Table 3. 3 Growth rate of 24 Rhizoctonia solani AG2 - growth rate expressed in mm/day. Phylogenetic group (PG) is according to Martin et al. (2014). Reduction in growth rate indicates the percent reduction 21 - R 11 ) / R 21 where R y is the growth rate at temperature y. Isolate PG Growth rate 11C Growth rate 21C Reduction in growth rate 24BR 1 0.024 0. 396 94% C116 1 0.058 0.357 84% Rs393 1 0.087 0.400 78% R09 - 2 1 0.091 0.420 78% F36 1 0.097 0.418 77% F30 1 0.108 0.407 74% F503 1 0.115 0.406 72% Slovakia 1 0.116 0.413 72% R09 - 28 2A 0.050 0.314 84% F508 2A 0.056 0.394 86% Rzc16 2A 0.061 0.315 81 % R1 2A 0.077 0.351 78% Rs866 2A 0.084 0.316 74% R09 - 25 2A 0.092 0.355 74% Italian 2A 0.107 0.377 72% Rs588 2B 0.036 0.214 83% Rzc94 2B 0.041 0.366 89% Rs599 2B 0.073 0.386 81% Rs106 2B 0.079 0.411 81% Rs1146 2B 0.088 0.413 79% Rs481 2B 0.089 0.3 68 76% 2C13 2B 0.122 0.373 67% Rs200 2B 0.131 0.375 65% Rs1090 2B 0.137 0.393 65% 93 3. 3 ). Average growth rates of the three phylogenetic groups (Fig. 3. 6 ) were signific antly different from one another 0. 05) at this temperature. Group 1 had the highest average growth rate (0.402 mm/day), followed by group 2B (0.370 mm/day) with group 2A having the slowest growth rate (0.347 mm/day). ged from 0.024 to 0.137 mm/ day. Similar to growth rates at , group 2A had the lowest average growth rate at 0.075 mm/day (Fig. 3.6) , which was significantly l 0 .05) than group 1 and group 2B (0.090 and 0.089 mm/day respectively). Growth but the amount of reduction varied from 65% to 94% (Table 3. 3 ). There was no significant difference in the amount of reduction based on phylogenetic group (ANOVA, p = 0 .762). Figure 3.6 Average growth rate of 24 Rhizoctonia solani AG2 - 2 isolates by . Isolates were grown on potato dextrose agar (PDA) for 4 mm/day. Phylogenetic group (PG) is according to Martin et al. (2014). Means upper case letters compare means at 21 Error bars indicate standard error of the means. a b b A B C 0.00 0.10 0.20 0.30 0.40 0.50 PG 2A PG 2B PG 1 Avg. Growth Rate (mm/day) Phylogenetic Group 11C 21C 94 Relati onship between Growth Rate, Temperature and Virulence 1,22 = 5.91, p = 0 .024) with an R 2 value of 0. 212 (Fig. 3. 7 linear component (F 1,33 = 5.13, p = 0 .030) with an R 2 v alue of 0. 135 (Fig. 3. 7 B ). The coefficient There was no si 1,22 = 1.31, p = 0 .264) (Fig. 3. 7 C (F 1,22 = 2.75, p = 0 .112) (Fig. 3. 7D). 95 Figure 3.7 Scatterplots comparing growth rate and virulence of Rhizoctonia solani AG2 - Disease severity was rated on a scale of 0 to 5, where 0 = no disease and 5 = plant dead. A) Comparison of the growth the growth rate and disease severity of 24 isolates at 11 A B C D F 1,22 = 5.91 p = 0.024 R 2 = 0.212 F 1,33 = 5.13 p = 0.030 R 2 = 0.135 F 1,22 = 1.31 p = 0.264 F 1,22 = 2.75 p = 0.112 96 Discussion he isolates tested caused moderate or high levels of disease and 16% of the inoculated plants were dead by the end of the experiment. Virulence ratings ranged from 0.47 (non - virulent) to 3.92 (highly virulent) (Table 3. 2 ), and distribution among the phylog enetic groups was fairly evenly distribu ted (Fig. 3. 4 ). Group 2B had a lower group 2A (1.78 vs. 2.22) due to the high proportion of group (Fig. 3. 5 ). While the difference in virulence between group 2A and group significance of that difference is questionable . In other words, the difference between the groups is unlikely to result in noticeable differences in a field level situation. Therefore, our data indicates that phylogenetic group is not diagnostic for virulence at low temperature as there was a wide range of virulence within the groups and the eight non - virulent isolates had representatives from each of the phylogenetic groups with a group 2A isolate having the lowest distributed among the three genetic groups. The expression of disease symptoms can lag pathogen spread and infection resulting in sub stantial underestimation of disease progress (Leclerc et al., 2014). This problem can be exacerbated for pathosystems that primarily cause disease on underground plant parts, as these symptoms are not readily visible without destructive sampling. Detection in these systems generally relies on the development of symptoms on above ground parts (Leclerc et al., little or no above ground symptoms and any damage to t he hypocotyl was not visible without 97 a disease 3. 8 ), indicating substantial disease progression; yet, less than 25% had ratings tha t included the presence of above ground symptoms (DS = 4 or 5). We hypothesize that early season infection may allow the pathogen to initiate disease largely undetected but that the rate of disease progression would increase substantially once temperature s rise to a more favorable level. having a reduction in virulence of at least 70% (Table 3. 1). This would most likely translate into reduced symptoms in the field and infected plants might not display a ny visible above - ground symptoms. It could be tempting to consider the lack of visible symptoms in the field to be an indication that there is no infection in the field and therefore, no risk. However, given the clear Figure 3.8 Proportion of plants in each dise ase severity category rated 21 days after inoculation with Rhizoctonia solani . A total of 1110 plants were inoculated using 35 strains of R. solani and were rated on a scale of 0 to 5; where 0 = no disease; 1 = lesion covering < 25% of the tissue; 2 = lesi on covering 20 - 60% of the tissue; 3 = lesion covering 60 - 90% of the tissue and top still healthy; 4 = lesion covering > 90% and plant not dead; 5 = plant dead. 98 evidence that at least some isolates o f AG2 - 2 are moderately to highly virulent at low temperatures, it would be a mistake to ignore the potential for early season infection. The virulence of the R. solani AG2 - 2 isolates in this study does not appear to be related to hyphal growth rate on art ificial media (Fig. 3. 7 C & D ). For instance, group 2A had an average growth rate that was significantly lower than that of group was significantly more virulent than group 2B at both temperatures (Fig. 3. 4 ). This agrees with Leach (1947) who found that the incidence of damping - off did not correlate with either growth rate of the pathogen or the host. Instead, disease incidence was inversely related to the ratio between how rapidly the seedlings emerged (coefficient of ve locity of emergence, CVE) and the growth rate of the pathogen (Leach, 1947). Disease was more severe when temperatures were relatively less favorable to the host than to the pathogen (Baker & Martinson, 1970; Leach, 1947). Temperature alone has been shown to be insufficient as a predictor of disease severity (Dorrance et al., 2003; Leach, 1947; Kirk et al., 2008) and our results support this conclusion. While there was a significant linear component (p = 0 .030) in the relationship between disease severity 2 value was only 0. 135 (Fig. 3. 7 B ), which indicates that less than 14% of the variability in virulence can be explained by differences in temperature. Some of the variability in our experiments might be explained by slight differences in moisture, inoculum density, and distance from inoculum source to host plant, which are factors known to influence disease severity (Bolton et al., 2010; Dorrance et al., 2003; Kirk, et al., 2008). However, the majority of the varia bility in disease severity should be attributed to differences in how the isolates responded to low temperatures. 99 Certain strains of R. solani Kavanagh (1991), have been reported to cause more severe disease at low temperatures than at higher temperatures (Baker & Martinson, 1970). While none of the isolates in the current exposure to the pathogen is considered ), at least one isolate was much less affected by lower (Table 3. 2 (Fig. 3. 3 ), but had a disease severity sc (Table 3. 2 (Fig. 3. 2 ). When length of time of exposure to pathogen was taken into consideration (Eq. 3. 1), ature of the isolates tested (Table 3. 2 ). Low temperature does reduce the severity of disease but the amount of reduction depends on the response of the specific isolate. Rhizoctonia solani cannot be thought of as a single entity but as a complex collec tion of related fungi that cause a range of diseases in a variety of crops (Baker, 1970; Cubeta & Vilgalys, 1997; Sneh et al., 1991). It also appears that R. solani AG2 - 2 should not be considered a single, homogeneous entity. The variability identified in this study agrees with previous studies that report R. solani AG2 - 2 to be a diverse group that has a wide range of virulence on sugar beet seedlings (Strausbaugh et al., 2011). Studies that examine the effects of R. solani AG2 - 2 on cropping systems need to take that variability into consideration. Unfortunately, the risk of early season disease development does not appear to be linked to a particular group within AG2 - 2 but rather is dependent on the specific isolate(s) present. This makes detection and iden tification of risk more difficult and it may be safer to consider all AG2 - 2 types capable of 100 causing early season damping - off. A set of microsatellite markers is currently being developed by our research group and we are investigating a possible connection between microsatellite genotype and low temperature virulence. Conclusions Early planting still remains an important part of sugar beet agronomics as it has been shown to provide increased yields (Scott, 1973) and does offer some measure of protection ag ainst Rhizoctonia induced damping - off (Leach, 1986). However, g rowers and agronomists Rhizoctonia solani infection . Rather, the risk in any particular field will dep end on the specific isolates present, the amount of inoculum, soil and moisture conditions, and how quickly the soil warms (Baker, 1970; Bolton et al., 2010; Dorrance et al., 2003). W hile this report cannot directly address the use of fungicides, our findi ngs indicate that soil temperature should not be considered the determining factor for fungicide application timing. Instead, growers should consider including a protectant at planting that is effective against Rhizoctonia solani , especially in fields wher e there has been a history of disease . 101 APPENDIX 102 Figure A 3.1 Multigene phylogeny of 63 Rhizoctonia solani AG2 - 2 isolates according to Marti n et al. (2014). Genes sequenced included rpb2 , tef1 , ITS, and LSU as reported in Gonzalez et al. (2016) with minor modifications to improve reliability and specificity for AG2 - 2 (unpublished data). Isolates in blue were originally identified as AG2 - 2IIIB, those in red identified as AG2 - 2IV, and those in green were inter mediates - where AG2 - - 2IV do not. An AG2 - 1 isolate was used for the outgroup. Phylogram used curtesy of Martin et al. (2014). 103 REFERENCES 104 REFERENCES American Crystal Sugar Company (2016). Pest alert - Rhizoctonia fungicide application: Soil temp charts. Retrieved from: https://www .crystalsugar.com/sugarbeet - agronomy/pest - alert/ on 6/24/2017. Anderson, N. A. 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J. and Harveson, R. M. (2009). Rh izoctonia root and crown rot. Pages 33 - 36 in Compendium of Beet Diseases and Pests. Edited by Harveson, R.M., Hanson, L.E. and Hein, G.L. APS Press, St. Paul, MN. Windels, C.E. and Nabben, D. J. (1989). Characterization and pathogenicity of anastomosis groups of Rhizoctonia solani isolated from Beta vulgaris . Phytopathology 79: 83 - 88. 108 CHAPTER 4 : IDENTIFICATION AND VALIDATION OF MICROSATELLITE MARKERS FOR USE IN RHIZOCTONIA SOLANI AG2 - 2 POPULATION ANALYSIS 109 Introduction to Microsatellites Microsatellites, also known as simple sequence repeats (SSR) or short tandem repeats (STR), are comprised of nucleotide motifs of one to six base pairs that are tandemly repeated between five and fift y times (Oliveira et al., 2006). They are widespread in all eukaryotic genomes (Katti et al., 2001) and have been shown to be invaluable for use in many areas of biology that include genome mapping (Shimoda et al., 1999), parental analysis (Jones et al., 2 010), population genetics (Biasi et al., 2016; Coupat - Goutaland et al., 2016; dos Santos Pereira et al., 2016) and resource conservation (Perez - Enriquez et al., 1998; Ernest et al., 2000). Microsatellites have become one of the most widely used and highly versatile genetic markers available for the study of plant pathogen populations (Benali et al., 2011). The versatility of microsatellites can be attributed to the fact that they are ubiquitous, relatively abundant, co - dominant, and exhibit high levels of p olymorphisms (Bhargava & Fuentes, 2009; Ellegren, 2004; Selkoe & Toonen, 2006). These characteristics give properly designed microsatellite marker sets sufficient statistical power and resolution for discriminating between closely related genotypes (Olivei ra et al., 2006). Therefore, microsatellites can be powerful tools in addressing important problems in plant pathology such as identifying sources of primary inoculum, determining spatial and temporal patterns of genotypes, providing evidence for sexual or asexual recombination, tracking the dispersal of inoculum, and examining the evolution of virulence, host range and pesticide resistance (Milgroom & Peever, 2003). 110 Mutational Mechanisms Although microsatellites have gained wide acceptance as an effectiv e marker for use in population genetics, the mechanisms behind microsatellite mutations are still not well understood. Two major aspects of microsatellites need to be considered in a mutation mechanism model. One is that mutation rates for microsatellite r egions are very high compared to the rates of mutation in coding regions (Bhargava & Fuentes, 2010; Fan & Chu, 2007). The other is that microsatellite alleles vary in the number of repeat units, indicating that mutations involve groups of nucleotides that are added or subtracted from the repeat array (Bell & Jurka, 1997). Several potential mechanisms have been proposed to explain the mutation process in microsatellite regions (Fan & Chu, 2007) and these are discussed in the following sections. Unequal cross ing over during meiosis is a well - known mechanism that can generate large scale mutational changes (Brown, 2002). This process has been proposed as a possible explanation for expansions and contractions in repeat arrays (Bhargava & Fuentes, 2009; Treco & A rnheim, 1986). However, since recombination involves the exchange of units between different chromosomes, it is unlikely to play a primary role in microsatellite expansion and contraction (Bhargava & Fuentes, 2009; Fan & Chu, 2007). It is still possible th at this mechanism plays a role in some large scale changes and multistep mutations in microsatellites (Fan & Chu, 2007). DNA replication slippage, also known as polymerase slippage or slipped strand mispairing, is widely accepted as the main mechanism for microsatellite mutation (Ellegren, 2004; Fan & Chu, 2007; Selkoe & Toonen, 2006). During DNA replication, the polymerase and the nascent strand may become temporarily disassociated from the template strand (Fig. 4.1B). 111 When the strands re - associate they ca n become mispaired because the repeat units can readily pair with the wrong repeat units on the template strand (Fig. 4.1C). If this happens, the DNA strand is forced to loop out at the mismatched sites. When DNA synthesis continues, the number of repeat u nits will be altered, increasing in number if the loop is on the nascent strand and decreasing in number if the loop is on the template strand (Fig. 4.1D). DNA replication slippage occurs at high rates in vitro, but in vivo , most loops are recognized and r emoved by the mismatch repair system (Schlötterer & Tautz, 1992). Therefore, the observed mutation rate depends on the rate of slippage and the efficiency of the repair system. Figure 4.1 Schematic illustrating the stepwise mutational model. (A) DNA polymerase copying a section of a microsatellite locus. Nascent strand is shown in blue and template strand is shown in green. Each blo ck represents identical repeat units of 3 to 6 base pairs. (B) Polymerase and nascent strand become disassociated and replication pauses. (C) When the nascent strand re - associates with the template strand, it can become misaligned since repeat units are id entical. (D) When replication resumes, the nascent strand has one extra repeat unit compared to the original. If it had been the template strand that looped out, the newly replicated strand would be one repeat unit shorter. Figure adapted from Fan & Chu (2 007). 112 Indel slippage was first proposed by Zhu et al. (2000) to expla in patterns of microsatellite distributions that were not well supported by the mechanisms of base substitution and DNA replication slippage alone. This mechanism is based on the observation that indel - like processes tend to duplicate short flanking sequen ces, which creates a short microsatellite (Bhargava & Fuentes, 2009; Zhu et al., 2000). The indel slippage process is not length dependent, as is replication slippage, but is presumed to occur at a constant rate. Further support for this mechanism was prov ided by Dieringer and Schlötterer (2003) using computer simulations that demonstrated the need for a model that combined the mechanisms of base substitution, length dependent DNA replication slippage and a length - independent process in order to explain the observed pattern of microsatellite distribution. It is important to recognize that the divergent patterns of microsatellite distribution among species and higher taxonomic groups implies that different rates of these processes work to shape microsatellit e distributions (Bhargave & Fuentes, 2009; Dieringer & Schlötterer, 2003). In addition, the rates of all these processes are species dependent and also vary according to repeat unit size and type (Dieringer & Schlötterer, 2003; Ellegren, 2004; Fan & Chu, 2 007; Katti et al., 2001). It is also likely that other factors that have yet to be described are involved. However, despite these other factors that may contribute to microsatellite distribution patterns, it is still widely accepted that replication slippa ge is the primary mechanism involved in microsatellite mutation (Ellegren, 2004; Fan & Chu, 2007; Selkoe & Toonen, 2006). 113 Mutation Models In order to determine genetic distance between groups of individuals using microsatellite allele frequency data, a mutational model is needed. Several mutational models have been proposed to describe the evolutionary dynamics of microsatellites (Fan & Chu, 2007; Selkoe & Toonen, 2006). The original model that was applied to microsatellites was the stepwise mutational m odel (SMM; Ohta & Kimura, 1973). The SMM describes microsatellite mutation as occurring one repeat unit at a time with an equal probability of an increase or decrease (Fig. 4.2A). This model assumes independence of the rate and size, with no limit to allel e size. The SMM is in agreement with the primary mutational mechanism of replication slippage. (Ellegren, 2004; Fan & Chu, 2007; Selkoe & Toonen, 2006). Several observations have led to the conclusion that a simple SMM is inadequate to fully explain the d istribution of microsatellite alleles. For example, microsatellites seem to show an upper limit on allele size (Naula & Weissing, 1996; Stefanini & Feldman, 2000). Additionally, mutational changes that involve more than one repeat unit are possible (Bharga va & Fuentes, 2009; Di Rienzo et al, 1994; Ellegren, 2004) and would still be consistent with the replication slippage mechanism. Therefore, more complex variations of the stepwise model have been proposed to account for these features. The two - phase mutat ion model (TPM; Di Rienzo et al, 1994) allows for mutations that change the array length by more than one repeat unit (Fig. 4.2B). There is still an equal probability of expansion or contraction, but steps larger than one repeat unit may occur at some freq uency. Another modification of the standard SMM involves the tendency for there to be an upper limit on allele size. In this model, the mutation rates for long alleles are biased towards the contraction of allele size (Fig. 4.2C). The same type of 114 modifica tion can be made for short alleles since short alleles tend towards expansion (Fig. 4.2D). Other more complex models have been proposed and tested against microsatellite distributions in genomic datasets (Dieringer & Schlotterer, 2017; Ellegren, 2004; Krug lyak et al., 1998; Renwick et al., 2001). Despite their fitting the data better than the SMM, these models still have difficulty with distance comparisons (Calabrese et al., 2001; Ellegren, 2004). Thus microsatellites are not the preferred marker for study ing phylogenetic relationships (Estoup et al., 2002). -3 -2 -1 +1 +2 +3 Frequency -3 -2 -1 +1 +2 +3 -3 -2 -1 +1 +2 +3 Frequency -3 -2 -1 +1 +2 +3 Change in number of repeat units Figure 4.2 Multistep mutational models for microsatellite loci. (A) In the strict stepwise mutational model, there is an equal probability for the addition or subtraction of 1 repeat unit. (B) The two - phase model al lows for mutations of more than 1 step to occur at some frequency but with expansion or contraction occurring with equal probability. Variations of the two - phase model can take into account that (C) long microsatellite alleles have a tendency to contract i n size and (D) short alleles have a tendency to expand. B . C . D . A. 115 Microsatellite Applications Microsatellites have become a popular marker for population studies in recent years due to properties such as being relatively abundant, codo minant, highly polymorphic and selectively neutral (Fan & Chu, 2007). Because microsatellites are DNA based and small in size, they are capable of being utilized even in degraded and challenging samples such as mountain lion feces (Butler, 2007; Ernest et al., 2000) and human forensic practices (Su et al., 2016). Another valuable characteristic of microsatellites is their substantial resolving power. Because of the relative instability of the molecular structure of microsatellites, they have a high mutation rate (Ellegren, 2004; Fan & Chu, 2007; Selkoe & Toonen, 2006). This allows researchers to discriminate amongst closely related genotypes and can provide answers to fine - scale ecological questions (Selkoe & Toonen, 2006). A common application for microsatellites is the determination of population structure (Moges et al., 2016). Properly designed microsatellite panels are discriminating enough to detect differentiation even in very closely related populations (Balloux & Lugon - Moulin, 2002). For example, Coupat - Goutland et al. (2016) us ed microsatellites to examine genetic variation in Naegleria fowleri , an amoeboic human pathogen, and stated that the six microsatellite markers they used provided a level of discrimination better than any marker to that point. Wang and Chilvers (2016) wer e able to identify genetic diversity among a population of Fusarium virguliforme that previously were thought to be genetically identical using standard phylogenetic markers such as ribosomal RNA internal transcribed spacer (ITS) and transcription elongati on factor 1 alpha (EF - closely related populations. 116 Other researchers have used the resolution that microsatellites can provide to examine gene flow among geographically distant populati ons (Moges et al., 2016; dos Santos Pereira, 2017). A microsatellite panel with a sufficient number of markers should be sensitive enough to detect even very low levels of gene flow (Selkoe & Toonen, 2006). Another area of ecological interest is to connect pathogen populations to a particular host (Biasi et al., 2016). Again, this may require a marker that can differentiate between very closely related genotypes. These and other population genetics problems are important to understanding the evolutionary pr ocesses in response to pressures exerted by management practices and changing distribution patterns (Milgroom & Peever, 2003). Drawbacks to Microsatellite Markers Despite the utility of microsatellites, they do have some challenges and drawbacks that can complicate data analysis and limit their utility (DeWoody et al., 2006; Selkoe & Toonen, 2006). However, their ability to address important ecological questions greatly outweighs their drawbacks and makes the effort to develop a suitable marker set worthwh ile. With careful selection of loci during the validation process and awareness of potential issues during the analysis process, the complications can be minimized or even avoided altogether (Selkoe & Toonen, 2006). It is, therefore, important to understan d the limitations and potential problems associated with microsatellites in order to reduce challenges in data analysis and minimize the possibility of reaching flawed conclusions. Narrow Taxonomic Range One of the major issues in developing a set of micr osatellite markers is identifying primer sequences that can amplify the selected loci over the entire range of taxa studied 117 (Selkoe & Toonen, 2006). Unlike single gene markers where primers are usually located in highly conserved regions, microsatellites a re more abundant in non - coding regions which tend to be highly variable (Sharopova, 2008; Katti et al., 2001). Because primers need to be located in the regions that flank the repetitive sequences, prior knowledge of the sequences in these flanking regions is necessary. Algorithms have been designed that can search genomic sequences for repetitive regions (Leclercq et al., 2007) and so suitable repeat sequences and associated flanking regions can be identified from whole genome sequence data. However, genet ically distinct individuals within the same taxa may have variation within these flanking regions and primers designed for one individual may not work for other individuals. This would necessitate identifying and testing significantly more loci than requir ed with the expectation that many of them will not work across all individuals within the considered taxa. Alternately, multiple individuals representing the range of genetic diversity in the taxa could be sequenced and evaluated for suitable loci and only those loci with consistency in the target region would be selected and tested against a larger set of individuals. This would potentially reduce the number of loci that need to be screened but would require a larger investment up front in sequencing and a ssembling multiple genomes (Biasi et al., 2015). For these reasons, microsatellite markers rarely work across broad taxonomic groups (Selkoe & Toonen, 2006). Hidden Allelic Diversity Microsatellites are typically scored by means of size - based identificatio n which reduces the time and expense of genotyping compared to sequencing each allele in each individual (Flores - Renteria & Krohn, 2013). However, not all genetic variation can be detected using this method. Alleles can be the same length but have a differ ent evolutionary history and sequence 118 variations that are not detectable by size - based identification alone (Estoup et al., 2002). This underestimation of allelic diversi ty (Taylor et al., 1999). Scoring microsatellite alleles by length relies on the assumption that all unique alleles differ in length and that length is a factor of the number of repeat units (Selkoe & Toonen, 2006). However, alleles can vary in ways other than the number of repeat units. These - Renteria & Krohn, Selkoe & Toonen, 2006). Detectable homoplasy is when two fragments are identical in length but are not identical in sequence. For example, a point mutation might represent genetic diversity that would not be revealed by size detection. Similarly, insertions or deletions in the flanking regions may create an allele of a different size without changing the number of repe at units. Detectable homoplasy can be discovered by sequencing alleles. Undetectable homoplasy occurs when two alleles are identical in sequence but have different genealogical histories (Selkoe & Toonen, 2006). The step - wise mutational process can both a dd and subtract repeat units and can result in convergence in size (Garza & Freimer, 1996). For instance, consider two copies of a locus that are identical by descent. If copy A undergoes a loss of one repeat unit and then a gain of two units while copy B a gain of two repeat units and then a loss of one unit, they would again be identical in length. Thus these alleles would appear identical, even by sequencing, but would be separated by four mutational steps. (Fig. 4.3). In general, homoplasy for size has a minimal effect on population studies involving groups with shallow evolutionary histories (Adams et al., 2004; Selkoe & Toonen, 2006). The 119 degree of homoplasy increases with the rate of mutation and time of divergence (Adams et al., 2004). In other word s , the chance of homoplasy increases with genetic distance. Because of this and other issues discussed in this section, microsatellites are generally unsuitable for more distantly related taxa (Estoup et al., 1995). However, the appropriate level of relate dness can differ by organism based on the varying rate of mutation. Figure 4.3 Schematic illustrating convergent evolution of microsatellites. Lineage A and lineage B start out identical by descent. Lineage A experiences a mutation event and loses 1 repeat unit but later gains 2 repeat units through another mutational event. In contrast, the mutational history of lineage B involves first a gain of 2 repeat units and then a loss of 1. Both alleles end up with a length of 8 repeat units and identical nu cleotide sequences. This type of would indicate these alleles were identical but they would actually be separated by 4 mutations. Figure adapted from Garza & Freimer ( 1996). Lineage A L ineage B 120 Null Alleles A null allele is any allele at a microsatellite locus that fails to amplify to detectable levels during polymerase chain reaction (PCR) (Dakin & Avise, 2004). Null allele s pose an important and persistent challenge for population geneticists. Because they fail to produce a visible product, null alleles are particularly difficult to detect. There are at least three potential causes for the occurrence of null alleles: (1) M utations in the priming regions, (2) inconsistent or poor DNA template quality and (3) large allele dropout due to the competitive nature of PCR (Dakin & Avise, 2004). Mutations in the priming regions can cause primers to bind inefficiently or not at all, particularly when they are near the degenerate bases at the sites of mutation can for allow amplification of alleles that would not amplify with more stringent primers (Pe mberton et al., 1995; Selkoe & Toonen, 2006). However, this approach requires knowledge of the specific mutations present which is not often plausible. Alternatively, adjusting PCR conditions can often improve the amplification success of recalcitrant loci (Selkoe & Toonen, 2006). Problems with template quality can be troublesome to detect because all loci may not be affected equally (Dakin & Avise, 2004; DeWoody et al., 2006). Therefore, it is advisable to start with the highest quality DNA template possi ble to provide the best chance of avoiding difficulties (Selkoe & Toonen, 2006). Re - extracting DNA from the sample in question is advisable for those loci that failed to amplify any product. Large allele dropout is a consequence of the competitive nature of PCR which can cause small alleles to amplify more efficiently than larger one (Wattier et al., 1998). In cases where 121 there are large size differences between alleles in an individual, only the smaller allele might be detected from a heterozygous individ detection can often be made possible by loading more sample or altering primer concentration (Dakin & Avise, 2004). In addition to these primary causes of null alleles, there are several populat ion genetic phenomena that can give the false impression that null alleles are present in a population. Certain biological factors, such as inbreeding, can cause a deficit in heterozygotes that might be interpreted as an indication that null alleles are pr esent (Chakraborty et al, 1992). Proper multilocus analysis should be able to distinguish this type of problem since population genetic factors should register more or less consistently across all loci. Another possible source of erroneous evidence for nul l alleles is sex linkage (Dakin & Avise, 2004). In diploid organisms, sex chromosomes carry only one allele at a locus and can result in the identification of a locus having a heterozygous deficit. Gender - specific analysis may be needed to identify sex lin ked loci and eliminate them as a potential source of error. Mitigating Scoring Errors Scoring errors can have a substantial impact on downstream analysis and it is important to take precautions to mitigate or minimize the effects of potential scoring er rors. The three types of scoring errors that are of primary concern are stuttering, large allele dropout and null alleles. These errors tend to create consistent scoring bias and can affect data interpretation (DeWoody et al., 2006). Re - amplification and r escoring of samples provides the opportunity to identify and quantify scoring errors (Dakin & Avise, 2004; DeWoody et al., 2006). This approach is 122 particularly important during the development of the marker set and an estimate of the error rate for each lo cus should be determined and reported. It may be necessary to abandon loci with excessive error rates. Once a marker set has been developed it is recommended that, given high quality DNA template, a random 10% of samples are reanalyzed at all loci (DeWoody et al., 2006). Loci with questionable peak patterns or samples with low quality DNA template may require additional resampling. Detecting scoring errors in microsatellite datasets typically relies on testing for heterozygote deficiencies using software su ch as Microchecker (DeWoody et al., 2006; van Oosterhout et al., 2006). Microchecker tests the microsatellite data for Hardy - Weinberg equilibrium and uses the presence of excess homozygotes to estimate the incidence of large allele dropout and null alleles . Loci with problems in these areas should be re - evaluated or eliminated. Several programs have been developed for the scoring of microsatellite data. It is recommended to use automatic allele calling to provide consistency and efficiency (DeWoody et al., 2006). Microsatellite scoring systems typically rely on binning, which creates a range of values which, when a peak falls within that range, it is assigned the allele size of that bin. This allows some flexibility in peak sizes since the peak values will not always match allele sizes exactly. In addition to automatic allele calling, each sample should be visually inspected to identify any novel alleles, potential mistypes or other problematic patterns. This combination of automatic scoring and visual inspe ction provides a suitable balance between efficiency and accuracy. 123 Objectives Rhizoctonia solani AG2 - 2 is a genetically diverse plant pathogen that causes disease on a number of economically important crops (Ogoshi, 1987; Sneh et al., 1991). In the cur rent study, the intent was to develop a set of microsatellite markers to use for the analysis of R. solani AG2 - 2 populations. We have identified a set of potential markers through in silico analysis and tested them for suitability for use in vitro . Thirtee n potential markers were fluorescently labeled and multiplexed for automatic allele sizing. Markers were evaluated for scoring errors, polymorphism information content, and genotypic diversity using 23 isolates of R. solani AG2 - 2 to verify suitability of s elected loci for use in population studies Methods In - Silico Identification and Evaluation of Potential Loci Potential microsatellite loci were identified by Frank Martin (USDA - ARS, Salinas, CA.) using an in - silico approach. Briefly, one isolate was sel ected from each of the three genetic groups within R. solani AG2 - 2 that were described by Martin et al. (2014). Rs850 was arbitrarily selected from group 1, Rs866 from group 2A and Rs588 from group 2B. These three isolates were sequenced on a HiSeq4000 (Il lumina Inc., San Diego, CA, USA) and raw sequences assembled using CLC Genomic Workbench (Qiagen, Redwood City, CA, USA). Since isolate Rs850 would be used as the initial sequence for marker selection, additional effort was used on this assembly. The assem bly was filtered to discard sequences with less than 15x coverage. The remaining contigs were exported to SeqMan NGen (DNASTAR, Inc., Madison, WI, USA) and 124 assembled de novo . Contigs were imported back into CLC Genomic Workbench and a second de novo assem bly was performed. Initial design of markers was done with isolate Rs850 using BatchPrimer3 (You et al., 2008). Search parameters were set to not search for dinucleotide repeats and to limit fragment size to between 100 and 250 bp. One locus was chosen for each contig of isolate Rs850 and evaluated for suitability. The assemblies of the other two isolates were checked to determine if there were differences in the number of repeats, no indels in the flanking regions and primer design was appropriate for all isolates. If there was a problem with one of the isolates, the locus was discarded and the next marker on the contig was evaluated until a suitable marker was identified. DNA Extraction Twenty three Rhizoctoni solani AG2 - 2 isolates (Table 4.1) representati ve of the three genetic clades as determined by Martin et al. (2014) were used to evaluate the in silico selected markers. Isolates were grown on malt extract broth (MEB ; Sigma - Aldrich, St. Louis, MO USA) without shaking for 5 to 7 days. The mycelial mat w as harvested using forceps, placed in a sterile 50 ml centrifuge tube, and rinsed with sterile distilled water. Tissue was lyophilized in a freeze drier (VirTis Genesis; SP Scientific; Warminster, PA) and ground in a modified paint shaker using 6 mm cerami c grinding beads (Zircoa, Inc.; Solon, OH). 125 Total DNA was extracted using the OmniPrep for Fungus kit (G - Biosciences; St. Louis, microcentrifuge tube, 20 to 25 mg of temperature and ex Isolate name Phylogenetic group Origin Multi - locus Genotype Rs850 * Undet. Minnesota, USA 1 Rs866 * 2A Minnesota, USA 2 Rs588 * 2B Minnesota, USA 3 R09 - 23 1 Michigan. USA 4 Rs1146 2B Minnesota, USA 4 F36 1 Oregon, USA 4 R09 - 2 1 Michigan, USA 5 2C13 Undet. Montana, USA 5 Rs1012 1 Minnesota, USA 6 F517 1 Idaho, USA 7 Cavalie 1 Europe 8 Roland 1 Europe 9 39AR 1 Canada 10 24BR 1 Canada 11 R - 9 2A Colorado, USA 12 F521 2A Idaho, USA 13 R - 1 2A Colorado, USA 14 W - 22 2 A Wisconson, USA 15 F508 2A Idaho, USA 16 Italian 2A Europe 17 RH193 2B Japan 18 Rs481 2B Minnesota, USA 19 R164S 2B Japan 20 * Initial isolates sequenced for preliminary marker identification Table 4.1 Twenty - three isolates of Rhizoctonia sola ni AG2 - 2 used in the current study. Phylogenetic group is according Martin et al. (2014). Multilocus genotype was determined from 13 microsatellite loci using Genotype version 1.2 (Meirmans & Van Teinderen, 2004). 126 on ice for 10 to 15 min. Precipitate was pelletized by centrifugation (12,000 x g for 5 min.) and pelletized by centrifugation (12,000 x g for 5 min.). The superna tant was poured off and the 2 O. At this point, the solution contained DNA and an unknown contaminant (possibly a charged polysaccharide, unpublished data) that was removed by ubation on ice for 15 min. The contaminant was collected by centrifugation at 2,500 x g for 2 min. The low speed was used to minimize the amount of DNA drawn out of solution in this step (unpublished data). The supernatant was poured into a clean tube and - EDTA buffer (doi:10.1101/pdb.rec11661Cold Spring Harb Protoc 2009). DNA quality wa s evaluated using a spectrophotometer (Nanodrop ND - 8000; Thermo Fisher; Waltham, MA) and DNA concentration measured using a fluorometer (Qubit 4; Thermo Fisher; 2 O. PCR Amplification and Marker Evaluation In order to reduce error from stuttering, Phusion II High - Fidelity polymerase (Thermo Fisher, Waltham, MA USA) was used for all PCR amplifications (Fazekas et al., 2010). Initially primer pairs were grouped by annealing temperature (T a ) a calculator (https://www.thermofisher.com). Thirty three primer pairs were categorized into four T a respectively. To determine optimum amplification conditions, DNA from isolates Rs850, Rs866 127 and Rs588 was amplified with the primer pairs that had a T a four MgCl 2 template, 1 x Phusion II HF buffer, 0.2mM dNTPs, 0.5mM of each primer and 1 unit of Phusion II HF polymerase with total MgCl 2 concentrations of 1.5mM, 2.0m M, 2.5mM or 3.0mM. products were separated on 4% agarose gels in - acetate buffer (Thermo Fisher; Waltham, MA) and visualized with UV light. No noticeable differences in amplification quality were observed between the various MgCl 2 concentrations; therefore, a total concen tration of 2.5mM MgCl 2 was used for all primer pairs were initially tested on 9 isolates using reaction conditions noted above and were evaluated for amplification across all isolates, band intensity, noticeable size differences between isolates, and suitability for multiplexing. Sixteen loci that amplified for all nine isolates and had observable polymorphisms were selected and fluorescently labeled for automatic fragment sizing (Table 4.2). Forward primers were labeled with either 6 - FAM or HEX fluorescent dyes (Integrated DNA Technologies, Coralville, IA USA) for use in duplex analy sis (Table 4.2). - PIG tail (Brownstein et al., 1996) to evaluate incidence of stutter peaks. Amplification of fluorescently labeled primers was conducted as described above. 128 Fluorescently labeled PCR products were evaluated for isolates Rs850, Rs588 and Rs866 using a genetic analyzer (Applied Biosystems 3130; Applied Biosystems; Foster City, CA). Samples were cleaned on gel filtration columns (Sephadex G - 50 superfine; GE Healthcare Life Sciences; P ittsburg, PA) and diluted 1:40, 1:60 or 1: 80 with sterile distilled water before submission. Analysis was performed by the Michigan State University Genomics Core (East - ROX ( Applied Biosystems, Foster City, CA) used as the size standard. Several runs were conducted and primer concentrations adjusted to provide similar levels of fluorescent signal for all loci (Table 4.2). Loci were evaluated for fragment length patterns incons istent with repeat unit length, stutter peaks, failure to amplify, and overlap in allele sizes of the duplexed loci. Three Table 4.2 Microsatellite loci ev aluated i n the current study for use on Rhizoctonia solani AG2 - 2. primers were labeled with either HEX or 6 - FAM fluorophores for automatic sizing. Loci with the same letter in parenthesis were run in duplex reactions. Amplicon length indic ates the range of fragment lengths across all 13 loci. Primer concentration s. Locus Repeat motif Amplicon length Dye Primer seque conc Forward Reverse 5402 (a) TCG 138 - 156 HEX CCATACGCTCATACTTGAGAC CGTAGACGAAAGTGGAMRTAG .30 7420 (a) CGA 170 - 176 6 - FAM TATCARGCAAACTTRACCAAT AGACCACTCTACGAACCTTGY .20 759 (b) CAG 131 - 170 6 - FAM CAACAGCACGCCMTYATG CAGAGGGYAATTGT TGTTGAA .35 2893 (c) GGTGTT 119 - 143 HEX CAGCTGGYGTAGTAGAAGTGG GAATCRACRCCRGCAGTAGA .45 8224 (c) CAAA 186 - 190 6 - FAM CCAAGACTCCGCTCATTG CTATCTATCACTCGTTCCGC .20 6150 (d) TTTC 130 - 158 HEX TGATATCACCACATTCTTTSA CRATTGACGGTCTACTGTTGY .25 5583 (d) AGA 183 - 19 8 6 - FAM CGTCGAGGATCTCAAATATGT TTGCTAATGGTTCCTTTACTG .10 6145 (e) CAG 146 - 158 HEX ATGCAGATGGTTTTGTACG CTAGAGATCGATGCTGTGTCT .30 4660 (f) CGA 132 - 159 HEX GTRATGGTGAGAGTGAGAGAA CTCSTCGTCTGAAGAGTCATA .45 8703 (f) GTT 201 - 216 6 - FAM TGRGGTGGKGGATGTATTG TCTCGG TCRAGTTACAATGG .20 5487 (g) ACG 132 - 141 HEX ATACCGAGAGTGTCTTTACSC AAAACGACTGGGGAGGAA .30 5877 (g) GTG 226 - 232 6 - FAM TACTTTGTACTCCCCGACG TTTGTCGTAACTTGGCTACA .35 2547 (h) AACA 214 - 222 6 - FAM AATCRCTCGAATCGGTAATT ATCGGGAATCATACTACCGG .10 129 loci had allele patterns inconsistent with repeat unit and were eliminated from further consideration. The remaining 13 markers were tested on a total of 23 isolates (including the nine original isolates referenced above) in two runs of 12 isolates with isolate Rs850 used as a positive control in template, 1 x Phusion II HF buffer, 0.2mM dNTPs, 2.5mM total MgCl 2 and 1 unit of Phusion II HF polymerase. Primer concentrations were as shown in Table 4.2. PIG - tailed reverse primer s were unnecessary for reducing stuttering and unmodified reverse primers were used. Final PCR min. PCR products were diluted 1:50 before submission to the MSU Genomics Core for analysis. Data Analysis Chromatograms were analyzed using Geneious 9.0.2 microsatellite plugin 1.4.4 (Biomatters, Inc.; Newark, NJ). Peaks were called using the Third Orde r Least Squares sizing algorithm. The first 12 isolates screened were used to predict bin sizes. Additional bins were added when needed as further samples were processed. Allelic data was analyzed for scoring errors using Micro - Checker (Van Oosterhout et a l., 2004). Scoring errors evaluated included homozygote excess, errors due to stuttering, large allele dropout and possible null alleles. Allelic diversity was evaluated using MSAnalyzer 4.05 (Dieringer & Schlotterer, 2003). 130 Diversity Index ( D; Simpson, 1949) was calculated using the formula: E quation 4.1 where R is the total number of alleles in the dataset and p i is the proportional abundance of the i - th allele. Genepop 4.5.1 (Rousset, 2008) was used for genotypic and genic differenti ation tests. The default settings were used for the Markov chain parameters in both analyses. Multi - locus genotypes and pairwise distances were determined with GenoType 1.2 (Meirmans & Van Tienderen, 2004) using the stepwise mutation model with missing dat a counted as one mutational step. Relationships of the isolates were inferred from pairwise distances using the neighbor - joining method (Saitou & Nei, 1987). Phylogenetic analyses were conducted in Mega 6.0 (Tamura, et al., 2013). Results In - Silico Ident ification of Potential Loci Whole genome sequencing of isolate Rs850 yielded 236 million reads that were assembled into 13,926 contigs over 1kb in length with a N50 value of 15.9. De novo assembly and clean up in SeqMan NGen (DNAStar; Madison, WI) and CLC Workbench (Qiagen; Redwood City, CA) improved assembly quality by reducing the number of contigs to 13,792 with a N50 value of 16.6 kb. Isolates Rs866 and Rs588 yielded 23,128 and 18,179 contigs respectively (Table 4.3). 131 Thirty three potential maker loci were identified using the BatchPrimer3 software (You et al., 2008) to analyze the genomes of isolates Rs850, Rs688 and Rs588. The most abundant microsatellites were trinucleotide (18), followed by tetra - (8), hexa - (6) and penta - (1). The number of repeat units for each locus for isolate Rs850 varied from 5 to 11 and the predicted fragment length varied from 104 to 244 bp. Primers were between 18 and 22 bp in length. PCR Amplification and Marker Evaluation Of the 33 potential markers initially identified in silico , six were omitted from further consideration because including them would have re sulted in annealing temperature when run in a single PCR reaction. Another eight loci were eliminated because they failed to amplify o r had weak amplification for one or more of the three initial isolates tested. Three loci had fragment sizes for isolate Rs850 that were inconsistent with predicted product size and were not tested further. Three additional markers were eliminated after au tomatic sizing analysis because they had allele patterns inconsistent with repeat unit. The remaining 13 markers and the primer concentrations used in final PCR reactions are shown in Table 4.2. Table 4.3 Results of NextGen sequencing and assembly for three isolates of Rhizoctonia solani AG2 - 2. Isolates were sequenced on a HiSeq4000 and assembled using CLC Workbench. Additional effort was used on isolate Rs850 and contigs were filtered an d de novo assembled using SeqMan NGen before an additional de novo assembly using CLC Workbench. Data is shown for isolates Rs850 before the additional assembly (raw) and after (final). Isolate # reads # contigs N50 (bp) Avg. length % identity Rs850 (raw ) 236 million 13,926 15.9 kb 7 kb 96% Rs850 (final) - 13,792 16.6 kb - 96% Rs866 245.5 million 23,128 6.1 kb 4.1 kb 96% Rs588 265 million 18,179 4.2 kb 3.1 kb 96% 132 Stutter was only a minor issue in a couple of loci with stut ter peaks generally 1 bp shorter than the actual allele with a peak intensity of less than 10 % of the main peak. By slightly increasing the peak threshold for allele calling, false allele calls were minimized. PIG - tailed reverse primers showed no improveme nt over standard primers in reducing stutter peaks and were not used in the final analysis. Data Analysis Genotyping of the 23 R. solani AG2 - 2 isolates using the selected 13 microsatellite markers confirmed a high level of diversity with a total of 20 mul ti - locus genotypes identified (Table 4.1). The number of genotypes at each marker ranged from 3 to 11 and 10 of the 13 loci (77%) had five or more unique genotypes (Table 4.4). Polymorphism information content (PIC; Anderson et al., 1993) ranged from 0. 332 to 0. 794 with an average value of 0. 618. Ten (77%) loci had a PIC value greater than 0. 50 which indicates those loci were highly informative (Anderson et al., 1993). A total of 61 alleles were detected, of which 16 (27%) were rare, having a frequency of l ess than 5%. The number of alleles per locus varied from 3 to 10 with an average of 4.7 alleles per locus. The total number of alleles for each isolate varied from 13 to 24 with an average of 19 alleles per isolate (Table 4.4). Significant deviations from Hardy - Weinberg equilibrium were found in four loci (8224, 5487, 2893 and 5877) indicating a deficiency of heterozygotes and the potential presence of null alleles. The calculated null allele frequency for each locus is listed in Table 4.5. There was no ev idence of large allele dropout in any loci (Table 4.5 ). 133 Isolate Allele Size by Locus 759 8224 2893 8703 4660 7420 5402 5877 5487 6145 5583 6150 2547 N a Group 1 Rs850 131/167 186/190 119/137 207/213 144/150 170/173 144/147 226 135 149/152 183/198 134 218 22 Roland 131/140 186/190 131 207/213 144/150 170 144 229 135/138 149 183/189 138 214/218 20 24BR 131/140 186/190 119/125 207/210 144/1 56 170 144 229 135/138 149/158 183/189 134/138 218/222 23 39AR 131/140 186/190 119/131 207/213 144/150 170 144 226/229 135/138 149/158 183/189 134/138 214/218 24 Rs1012 131/140 190 125 204/216 147/150 170 144/156 226 132 149 186 130/134 218/222 19 F5 17 131/140 190 125/131 204/210 150/159 170 144/156 226 132/135 146/149 183/186 130/142 218/222 23 Cavalie 131 190 125 204/216 150/159 170 144/156 - 132 146/149 186 130/134 214 17 R09 - 23 131/137 190 131/143 204/216 147/150 170 144/156 226 132 149 183/18 6 130/138 218/222 21 Rs1146 (a) 131/137 190 131/143 204/216 147/150 170 144/156 226 132 149 183/186 130/138 218/222 21 F36 131/137 190 131/143 204/216 147/150 170 144/156 226 132 149 183/186 130/138 218/222 21 R09 - 2 131/137 190 131/143 204/216 147/150 170 144/156 226/232 132 149 183/186 130/138 218/222 22 2C1 131/167 190 131/143 204/216 147/150 170 144/156 226/232 132 149 183/186 130/138 218/222 22 Group 2A R - 1 146/152 186 119 201/207 144 170/176 138/144 - 135 152/155 186 138/142 222 18 R - 9 152 18 6 119 201/207 144 176 141/144 226 135 152/155 186/198 138/142 222 18 F521 152 186 119 201/207 144 176 141/144 226 135 152/155 186 138/142 222 17 W - 22 149/158 186 119 204/207 144 170 141/144 226 138/141 152/155 198 134/142 222 19 F508 152/158 186 119 201/207 144 170/173 141/144 226 135 152/158 186/198 134/142 222 20 Rs866 152/170 186 119 201/207 144 170/173 141/144 226 135/138 149/158 186/198 142 222 20 Italian 152/161 186 119 201/207 144 170/176 141/144 226 135/138 149/158 186/198 142/158 222 21 Group 2B Rs588 140 186 119 207 144 170 144 229 132 152 189 138 218 13 R164S 140 186 119 207 144 170 144 229 135 152 189 138 218 13 RH193 140 186 119 207 132 170 144 229 138 152 189 138 218 13 Rs481 140 186 119 207 132 170 144 229 135 152/158 189 138 218 14 Statistics N a 10 2 5 6 6 3 5 3 4 5 4 5 3 N G 11 3 8 7 6 4 5 4 6 7 8 10 5 R a 1.81 1.50 1.65 1.76 1.70 1.34 1.54 1.50 1.65 1.71 1.73 1.73 1.59 H E .812 .502 .651 .761 .702 .339 .538 .501 .654 .706 .730 .728 .587 H O .696 .174 .391 .826 .522 .217 .696 .130 .348 .609 .609 .696 .435 PIC .794 .491 .637 .745 .687 .332 .526 .489 .640 .691 .715 .712 .575 Table 4.4 Microsatellite alleles detected in 23 Rhizoctonia solani AG2 - 2 isolates. Group designation is according to Martin et al. (2014). A llelic diversity was determined using MSAnalyzer 4.0. 5. 134 Two loci (8224 and 5877) also showed evidence of scoring errors due to stuttering as indicated by the significant shortage of heterozygote genotypes with alleles of one repeat unit differenc e (Table 4.5). Chromatograms of these loci were examined visually for stuttering patterns. Locus 5877 had peaks that were only one base pair apart but the longer allele was consistently called as it had the larger peak height (Fig. 4.4). The more problemat ic issue for locus 5877 was that isolates R - 1 and Cavalie failed to amplify any alleles. Locus 8224 had a more problematic pattern of peaks. Again, peaks within the same isolate differed in length by only one base pair, but which peak was called was incons istent between isolates (Fig. 4.4). Bin sizes had to be set asymmetrically ( - 1 to +2) in order to accommodate the variation in peaks. However, this type of pattern is not indicative of true stutter, in which peaks typically differ by one repeat unit, but i s more suggestive of the presence of indels. Cloning and sequencing of representative samples for affected loci will be required to confirm condition. Pairwise distances between the 23 isolates in this study are shown in Table 4.6. The neighbor - joining tre e generated from this data (Fig. 4.5) was generally consistent with the multi - gene phylogeny o f Martin et al. (2014) (Fig. A 4 . 1 ) with one exception (Fig. 4.5). Isolate Rs1146 was expected to cluster with group 2B isolates according to Martin et al. (2014), but was found to have a microsatellite genotype identical to two group 1 isolates (R09 - 23 and F36) (Table 4.4). Table 4.4 ( N a indicates the number of alleles detected in each isolate or at each locus. N G = number of genotypes at each locus, R a = allelic richness, H E = expected heterozygosity, H O = obs erved heterozygotes, PIC = polymorphism information content (Anderson et al., 1993). Footnote (a) isolate Rs1146 was identified as belonging to group 2B according to Martin et a l. (2014). Virulence data (Chapter 2, this thesis) and microsatellite data indi cate it likely belongs to group 1. Re - examination of original sequence data is necessary. 135 Although all four isolates in group 2B had unique multi - locus microsatellite genotypes, they were highly homogeneous. Except for a single isol ate at one locus, all isolates were completely homozygous (Table 4.4). Only three out of thirteen loci (23%) had more than one allele with an average of 1.31 alleles per locus while group 1 and group 2A had an average of 3.62 and 2.62 alleles per locus res pectively (Table 4.4). Simpson 1949) measures the probability that two alleles selected at random from the sample will be identical and the value increased from 0. 459 for group 1 to 0. 892 for group 2B (Table 4.7). This means that, on average, two alleles selected from a locus in group 2B are roughly twice as likely to be identical as two alleles selected from the same locus in group 1. Genotypic and genic differentiation of group s 2A and 2B indicate that the populations are highly similar with five and six loci respectively not significantly differentiated (Table 4.8 and 4.9). However, across all loci both tests returned significant differentiation between all three populations. Table 4.5 Scoring errors for the 13 microsatellite loci evaluated in the current study. Microsatellite data was collected on 23 isolates of Rhizoctonia solani AG2 - 2 and analyzed for scoring errors using Microchecker v. 2.2.3 (van Oosterhaut et al., 2004). Confidence interval was set to 95% with 1000x simulations. Locus Expected Homozygotes Observered Homozygotes Homozygote excess Scoring error due to stuttering Larg e allele dropout Null alleles Null allele frequency 7420 15.369 18 no no no no 0.086 5402 10.891 7 no no no no 0 759 4.739 7 no no no no 0.055 8224 11.695 19 yes yes no yes 0.213 5487 8.282 15 yes no no yes 0.178 4660 7.195 11 no no no no 0.098 2547 9.782 13 no no no no 0.089 2893 8.347 14 yes no no yes 0.150 6145 7.108 9 no no no no 0.049 6150 6.630 7 no no no no 0.009 5583 6.565 9 no no no no 0.062 8703 5.869 4 no no no no 0 5877 10.738 18 yes yes no yes 0.379 136 8224 5877 Figure 4.4 Chroma tograms of locus 5877 and 8224 showing stutter - like patterns . Forward primers were labeled with either HEX or 6 - FAM fluorescent dyes (both loci above were labeled with the 6 - FAM dye) and amplified with PCR. Resulting microsatellite fragments were automati cally sized on an Applied Biosystems 3130 genetic analyzer and chromatograms were analyzed using Genieous 9.0.2 microsatellite plugin 1.4.4. Shaded bands show the size and range of the bins used for automatic allele calling. Stutter - like peaks shown above are 1 base pair shorter (or longer) than the major peak and are not characteristic of true stutter which is typically 1 repeat unit shorter. Locus 5877 has a repeat unit of 3 nucleotides and locus 8224 has a repeat unit of 4 nucleotides. Bin range for locu s 8224 was set asymmetrically ( - 1 to +2 bp.) to accommodate the variation in peak sizes. 137 Table 4.6 Pairwise distances of 23 Rhizoctonia solani AG2 - 2 isolates based on 13 microsatellite loci. Pairwise distances were determined with Genotype 1.2 using the stepwise mutational model with missing data counted as 1 step. 138 Figure 4.5 Neighbor - joining tree of 23 Rhizoctonia solani AG2 - 2 isolates based on 13 microsatellite loci. Pairwise distances were determined with Genotype 1.2 using the stepwise mutation mode l with missing data counted as 1 mutational step. Relationship of the isolates was inferred from pairwise distances using the neighbor - joining method (Saitou & Nei, 1987). Analysis was performed using Mega 6.0. Region of origin is indicated in parentheses after the isolate name. Color of diamond signifies phylogenetic group according to Martin et al. (2014); green = group 1, blue = group 2A, red = group 2B and black = undetermined. Scale bar indicates number of mutational steps.Locale abbreviations are as f ollows: MI = Michgan, MN = Minnesota, OR = Oregon, MT = Montana, ID = Idaho, Eur = Europe, CAN = Canada, CO = Colorado, WI = Wisconson, Jap = Japan . 139 Total No. Alleles Alleles per locus Simpson Diversity Index by Locus 7420 5402 759 8224 2893 5583 6150 6145 8703 4660 5877 5487 2547 Overall 61 4.69 0.668 0.474 0.206 0.509 0.363 0.285 0.288 0.309 0.255 0.313 0.511 0.360 0.425 0.376 Group 1 47 3.62 0.920 0.503 0.382 0.722 0.264 0.365 0.316 0.642 0.247 0.309 0.525 0.469 0.389 0.459 Group 2A 34 2 .62 0.388 0.439 0.367 1.000 1.000 0.459 0.398 0.276 0.439 1.000 1.000 0.561 1.000 0.620 Group 2B 17 1.31 1.000 1.000 1.000 1.000 1.000 1.000 1.000 0.625 1.000 0.500 1.000 0.469 1.000 0.892 Table 4.7 Simpson diversity index by group for 23 Rhizoctonia s olani AG2 - 2 isolates. Simpson diversity index was calculated according to Simpson (1949) (see text for formula). Group designation is according to Martin et al. (2014). is the average diversity across all 13 loci. Shaded values are 1.00 and indicate the all alleles at that locus are identical for that group. Population pair p - value by Locus Across All Loci 759 8224 2893 8703 4660 7420 5402 5877 5487 6145 5583 6150 2547 Grp 1 & Grp 2A <.0001 <.0001 <.0001 .0002 .0002 .0008 <.0001 .1504 .0062 .0004 .0019 <.0001 <.0001 <.0001 Grp 1 & Grp 2B <.0001 <.0001 .0005 .0007 .0022 1.000 .0381 .0110 .1538 .0006 .0006 .0002 .0114 <.0001 Grp 2A & Grp 2B .0028 - - .0154 .1088 .0496 .0145 .0049 .8938 .1341 .0029 .0003 .0030 <.0001 Table 4.8 Genotypic differentiation (exact G test) for each population pair of Rhizoctonia solani AG2 - 2. Populations were separated by phylogenetic group according to Martin et al. (2014). Pairwise differentiation was determined using Genepop 4.5.1. Shaded values indicate non - - indicates no variability in allele size between populations at that locus. 140 Table 4.9 Genic differentiation (exact G test) for each population pair of Rhizoctonia solani AG2 - 2. Populations were separated by phylogenetic group according to Martin et al. (2014). Pairwise differentiation was determined using Genepop 4.5.1. Shaded values indicate non - significant relationshi - indicates no variability in allele size between populations at that locus. Population pair p - value by Locus Across All Loci 759 8224 2893 8703 4660 7420 5402 5877 5487 6145 5583 6150 2547 Grp 1 & Grp 2A <.0001 <. 0001 <.0001 <.0001 <.0001 .0001 <.0001 .0522 .0002 <.0001 0024 .0004 <.0001 <.0001 Grp 1 & Grp 2B .0003 <.0001 <.0001 .0004 .0002 1.000 .0927 .0002 .0625 <.0001 <.0001 .0077 .0005 <.0001 Grp 2A & Grp 2B <.0001 - - .0508 .0097 .0233 .0518 <.0001 .8446 .15 73 <.0001 .0013 <.0001 <.0001 141 Discussion The o bjective of the current study was to develop and validate a set of microsatellite markers for the fungal pathogen Rhizoctonia solani AG2 - 2. The initial in - silico selection of potential markers made validation relatively straightforward as all of the tested markers amplified in the three isolates that had been used for in - silico selection. More traditional methods for identifying potential microsatellite loci, such as restriction enzyme fragmentation and ligation into a plasmid vector, can be time - consuming and inefficient (Glenn & Schable, 2005; Squirrell et al., 2003; Zane et al., 2002). Generating microsatellite - enriched libraries can improve success rates and efficiency (Edwards et al., 1996; Zane et al., 2002), but can introduce selection bias as repeat motifs must be pre - defined (Leese et al., 2008; Zane et al., 2002). Thus, the initial in - silico identification of potential markers provided an efficient method for identifying microsatellite loci. One criticism that has been leveled against the methodolo gy presented in the current study is that since the cost of sequencing is relatively inexpensive, it would have been more efficient to just sequence all of the isolates as opposed to only a subset. While sequencing all 23 isolates would have provided more data on these individuals, the larger goal of this project is to use these markers on much larger populations. Microsatellites are still much less expensive per individual than whole genome sequencing and would be a more cost effective approach to larger s ample sizes (Table 4.10). The other issue in favor of microsatellites is the simplicity of analysis. Although there are some peculiarities of microsatellites that can make interpretation tricky (Selkoe & Toonen, 2006), analysis is fairly straightforward an d can typically be completed in a few hours. NextGen sequencing requires assembly and filtering of large amounts of data 142 which can require a high - performance computer system and a considerable amount of time. Often the services of a bioinformatician are em ployed to analyze NextGen sequence data which may incur additional expenses. Sequencing more isolates to use for initial selection of microsatellite loci may have reduced the number of rejected markers, but would not have eliminated the need for testing po tential markers in - situ . In short, NextGen sequencing does have the potential to enhance population studies but the cost and effort required have not yet made microsatellites obsolete. Furthermore, the methodology used in this study is comparable to that u sed in other recent studies involving the identification and validation of microsatellite markers (Biasi et al., 2015; Moges et al., 2016; Vaghefi et al., 2017a; Wang & Chilvers, 2016). The presence of stutter peaks can greatly complicate the interpretati on of microsatellite data and in extreme cases can result in improper or ambiguous results (DeWoody et al, 2006; Leclair et al., 2004). In order to minimize the occurrence of stuttering, we employed two approaches. The first was to utilize a high - fidelity proofreading polymerase. Stutter peaks are Table 4.10 Cost comparison for Illumina sequencing and microsatellite analysis. Estimates for Illumina sequencing cost is based on prices advertised by Michigan State University Genomics Core. Microsatellite cost estimates are based on expenses incurred in the course of the current study . Illumina sequencing Microsatellite analysis Coverage 80x 50x Number of samples 20 25 Number of samples 12 Library Prep $1850 $2300 PCR Materials $150 HiSeq 4000 (paired end) $2400 $ 2400 Labeled primers $12 ABI 3730 genetic analyzer $150 Cost per sample $215 $190 Cost per sample $26 143 thought to occur through a mechanism similar to that which causes the length polymorphisms in microsatellites, namely disassociation of the polymerase and subsequent slippage of the strands (Fan & Chu, 2007). The Phusion II polymerase is a Pyrococcus - like enzyme that is highly accurate and rapid (Fazekas et al., 2010; Lundberg et al., 1991; Uemori et al., 1997). There was virtually no observed stuttering in the amplicons generated with this polymerase. One explana tion for the reliability of the Phusion type polymerases in amplifying microsatellite regions is the increased contact surface provided by the addition of a non - specific dsDNA binding protein (Fazekas et al., 2010). This additional affinity is thought to m inimize polymerase stalling and disassociation that can allow mispairing and strand slippage (Fazekas et al., 2010). The second technique we employed to help eliminate stuttering problems was to - - fluoresce ntly labeled primers (reverse primers) (Brownstein et al., 1996). This additional tail is intended to decrease misalignments of the template and the generation of secondary structures that contribute to polymerase slippage. In the present study, there was no improvement with the PIG - tailed products compared to non - PIG - tailed products. This was presumably due to the use of the Phusion II polymerase (Fazekas et al., 2010), since there was no noticeable stuttering even in the non - PIG - tail products. However, n o comparison was made with other types of polymerases to conclusively connect the lack of stuttering in our study with the use of the Phusion II polymerase. Nonetheless, the final analysis was completed without the PIG - tailed primers. An important aspect o f the microsatellite panel developed in the current study is the suitability for duplex PCR reactions, which reduces the time and cost associated with setup (Biasi et al., 2015; Li et al., 2012). Since two marker sets are included in a single PCR reaction 144 and are run as a single sample through the bioanalyzer, the cost of this step is reduced to about half of what it would be for running them individually. The goal was to have each sample occupy a single column on a 96 - well plate, allowing up to 16 markers per sample and 12 samples per 96 - well plate. The intent was to make setup and loading of the samples as efficient as possible by enabling the use of multi - channel pipettes. Markers were sorted by fragment length and shorter fragments were paired with longe r fragments to minimize spectral overlap. The more difficult attribute to adjust for was that the 6 - FAM dye produces a more intense fluorescent signal than does the HEX dye. What this means for analysis is that when the dilution is sufficient so that the H EX signal is appropriate, the signal for the 6 - FAM is overly intense. To balance the signals from both dyes, the concentration of primers was varied to produce similar peak levels from each dye (Table 4.3). Twenty unique multi - locus genotypes were identif ied among the 23 isolates screened, indicating a high level of diversity. This level of diversity was not surprising as the isolates used in this study were specifically chosen from diverse regions (Table 4.1). What was unexpected was that several isolates from diverse regions were more closely related to one another than they were to isolates from similar regions (Fig. 4.5). For example, none of the European isolates cluster together. Both Japanese isolates (Rzc6 & Rzc89) have a microsatellite pattern more similar to isolates from Minnesota than to each other. Isolates from three states, Michigan (R09 - 23), Minnesota (Rs1146) and Oregon (F36) have identical microsatellite genotypes even though they are from diverse regions of the country. Likewise, an isolat e from Michigan (R09 - 2) and an isolate from Montana (Rzc47) are identical according to their microsatellite genotype. 145 Although a sample size of 23 isolates is insufficient to confidently draw conclusions regarding geographic distribution, the general obse rvation is that genotype had little relation to locale of isolation. Instead, the distribution is suggestive of individuals being translocated from one region to another, possibly through human activity. R. solani has been reported to be carried in and on some types of seeds (Baker, 1947; Baker & Martinson, 1970, Neergaard, 1958; Crosier, 1968) and this is a potential source of transport between regions. However, there is little or no evidence that R. solani is carried on sugar beet seeds. In addition, the AG of reported seed - borne R. solani is either uncertain or unspecified. Therefore, R. solani AG2 - 2 being transported across regions via contaminated seed is questionable and there is likely another explanation for the observed distribution. This leaves the pattern of distribution or the source of migration uncertain. Recently, Vaghefi et al. (2017b) found that another common pathogen of sugar beet, Cercospora beticola , also shared genotypes across distant states and even between the US and Europe. They also identified contaminated seed as a potential source of genotype flow, but cited mixed reports as to the presence of C. beticola on seed. How genotype flow occurs in C. beticola also remains uncertain. Polymorphism information content (PIC) is a measure of the usefulness of a genetic marker for detecting polymorphisms within a population (Anderson et al., 1993). The value ranges from zero to one and is dependent on the number of detectable alleles and the distribution of their frequencies. A value of zero i s the least informative and means there is only one allele at that locus. The closer the value is to one, the more informative that locus will be. The total number of alleles at a locus determines the maximum PIC for that locus, while allele frequency dete rmines the value between zero and the maximum (Table 4.11). Evenly 146 distributed alleles return the highest PIC values, while varied allele frequencies reduce the PIC value. In the current study, PIC values ranged from 0. 332 to 0. 794 with an average value of 0. 618. Ten loci had PIC values above 0. 500, which indicates those loci were considered to be highly informative (Botstein et al., 1980). The remaining three loci had PIC values between 0. 250 and 0. 500 and so were considered to be reasonably informative . Locus 7420 had a total of three alleles with one allele having a frequency greater than 0. 80 and one allele having a frequency of 0. 065. This combination made locus 7420 the least informative marker of the set with a PIC value of 0. 332. Locus 5877 had th e lowest observed heterozygosity ( 0 .130) of the loci in this study. In addition, two isolates failed to amplify for any allele at this locus. Of the three alleles detected, one was rare (frequency < 0 .05) and the other two alleles were unevenly distributed (frequency of 0. 643 and 0. 310). PIC value was slightly below 0. 50 ( 0 .489) and considered reasonably informative. For these reasons, locus 7420 and 5877 may not be suitable markers for the purposes of this microsatellite panel. Table 4.11 Hypothetical polymorphism information content (PIC) values for loci with a differing number of alleles and frequencies. Maximum PIC v alue occurs when all allele frequencies are equal. PIC value with 1 allele at 50% illustrates how the PIC value is affected when the frequency of 1 allele is 50% of the other alleles, which are evenly distributed. PIC value with 1 rare allele is the value when 1 allele has a frequency of 0.05 and the other alleles are equally distributed. Number of Alleles PIC value 1 2 3 4 5 10 Maximum value .000 .500 .667 .750 .800 .900 with 1 allele at 50% N/A .444 .640 .735 .790 .898 with 1 Rare Allele N/A .095 .546 .697 .772 .897 147 Locus 8224 had only two alle les but they were fairly evenly distributed ( 0 .565 / 0. 435). This pattern resulted in a marginal PIC value ( 0 .491). Heterozygosity at this locus was low ( 0 .174) with only four individuals out of twenty three identified as heterozygous. Due to the low numbe rs of heterozygotes, this locus was identified as having the possibility of null alleles with the second highest predicted null allele frequency of all the loci screened (Table 4.5). In addition, locus 8224 was identified as having the potential for scorin g errors due to stuttering. However, observations from the chromatograms are not indicative of stuttering but are more consistent with indels that have altered allele length by one base pair (Fig. 4.4). Screening of additional isolates and sequencing probl ematic alleles will be required to determine the suitability of this marker. The neighbor - joining tree based on the microsatellite data from the current study (Fig. 4.5) largely agree with the multigene phylogeny of Martin et al. (2014) (Fig. 4.6). Microsa tellites are not considered to be an effective marker type for reconstructing phylogenetic relationships (Estoup et al., 2002). However, the general agreement between the microsatellite tree and the multigene phylogeny indicates the selected microsatellite loci likely have a similar evolutionary history. The major disagreement between the microsatellite tree and the multigene phylogeny was isolate Rs1146. The analysis of Martin et al. (2014) placed isolate RS1146 in group 2B, but our microsatellite data inc ludes the isolate with others in group 1. Evidence from virulence tests show that isolate Rs1146 is more like other isolates from group 1 than isolates from group 2B as it is highly aggressive on dry beans and sugar beet and isolates from group 2B are gene rally weaker (Chapter 2, this thesis). Resequencing the markers used for the multigene phylogeny 148 and re - running the microsatellite panel for isolate Rs1146 will be needed to examine this discrepancy. Something that is unclear from the phylogeny of Martin et al. (2014) (Fig. 4.6) is whether the clades labeled 2A and 2B should be considered two separate clades or a single clade with two sub - clades. Data from pathogenicity studies indicate that group 2A is significantly more aggressive than group 2B on sugar beet and dry beans when inoculated at planting (Chapter 2 & 3, this thesis). Previously reported subgroups, AG2 - 2IIIB and AG2 - 2IV, have been associated with differences in virulence, with AG2 - 2IIIB identified as being more virulent on sugar beet (Engelkes & Windels, 1996; Panella, 2005; Strausbaugh et al., 2011). These distinctions can have a significant effect on management and resistance breeding efforts (Engelkes & Windels, 1996; Strausbaugh et al., 2013). Thus it may be prudent to consider phylogenetic groups 2A and 2B to be distinct, separate groups rather than subgroups. In addition, microsatellite data from th e current study indicate that group 2B is highly homozygous with only one locus in a single isolate being heterozygous. Average Simpson Diversi ty Index by group shows a decline in diversity within the groups with group 1 having the highest diversity and group 2B the lowest diversity (Table 4.7). Ten out of thirteen loci (77%) were fixed in group 2B while only five loci (38%) were fixed in group 2 A. Population differentiation tests indicate significant differences in allele distribution between groups 2A and 2B. Genic differentiation evaluates the distribution of alleles in the samples and uses a null hypothesis of H 0 same distribution in all loci (54%) and the comparison across all loci to have significant p - values (p < 0 .05). Genotypic 149 differentiation, which considers the distri bution of genotypes, had similar results (Table 4.8) with eight of thirteen loci (62%) and the comparison across all loci having significant p - values (p < 0 .05). The conclusion is that the distribution of alleles and genotypes in groups 2A and 2B come from different distributions and appear to represent distinct populations. Conclusions Rhizoctonia solani AG2 - 2 is a highly diverse group of fungi. In a representative group of 23 isolates, 20 unique genotypes were identified. Ten microsatellite markers eval uated in the current study have 5 or more unique genotypes at the given loci and have a PIC value greater than 0.50, indicating they are highly informative. Groupings based on microsatellite distances largely agree with the multigene phylogeny of Martin et al. (2104), which supports the three proposed genetic groups. Genotypic differentiation supports the position that group s 2A and 2B should be considered separate, independent clades. Thus, this set of microsatellite markers were effective at discriminatin g genotypes of Rhizoctonia solani AG2 - 2 isolates and have shown some utility for use in population genetics work by their ability to discriminate the three clades identified by Martin et al. (2014). 150 APPENDIX 151 Figure A 4.1 Multigene phylogeny of 63 Rhizoctonia solani AG2 - 2 isolates according to Martin et al. (2014). Genes sequenced included rpb2 , tef1 , ITS, and LSU as reported in Gonzalez et al. 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