FROM CELL TO FIELD: UNDERSTANDING HERBICIDE RESISTANCE MECHANISMS IN KEY BROADLEAF WEEDS IN MICHIGAN TO PREDICT AND PROPOSE A SUSTAINABLE INTEGRATED WEED MANAGEMENT APPROACH By Juliano Ricardo Marchi Sulzback A THESIS Submitted to Michigan State University in partial fulfillment of the requirements for the degree of Crop and Soil Sciences – Master of Science 2024 ABSTRACT Herbicide resistance is a constant threat to agriculture that heavily rely on chemical weed control. Traditionally, weed managers use a reactive approach to failures in weed control, where first a problem occurs and then the issue is remediated (Robert et al., 2016). However, it is possible to take a proactive approach to weed management, by predicting weed control issues using epidemiological approaches and/or rapidly identifying using modern diagnostics to reduce the impact of weeds on production. To this end, laboratory experiments and field validations were conducted to 1) optimize rapid molecular assays that identify resistant individuals of horseweed (Erigeron canadensis L.), Palmer amaranth (Amaranthus palmeri S. Watson), waterhemp (Amaranthus tuberculatus (Moq.) Sauer), and common ragweed (Ambrosia artemisiifolia L.), and 2) identify mechanisms conferring resistance to acetolactate synthase (ALS) and 5- enolpyrovylshikimate-3-phosphate synthase (EPSPS) inhibiting herbicides. Nine single nucleotide polymorphisms (SNPs) were identified in five ALS positions known to confer herbicide resistance among all species surveyed. One SNP in EPSPS gene in horseweed, and increased EPSPS copy numbers in Palmer amaranth (20-160 copies) and waterhemp (2-7 copies) accessions were identified, which are known to confer resistance to glyphosate. The genotyping assays identified resistance mutations in >98% of cases and could be generated in two days. We confirm that rapid molecular resistance diagnostics is a valuable tool in herbicide resistance diagnostics, helping growers to confirm herbicide resistance in Michigan weeds. In another study, we set out to understand the relationship between management practices and herbicide resistance evolution in horseweed to glyphosate, dicamba and 2,4-D. Greenhouse experiments were conducted to 1) assess current resistance spectrum of horseweed in Michigan to those herbicides, and to 2) determine main factors that contribute to the presence of resistance in horseweed. Out of the 20 accessions screened, 60% were resistant to glyphosate, 35% to 2,4-D, and 20% to dicamba. Dose- response data were integrated with previous management history and environmental factors using odds-ratio analyses to rank which factors influenced the presence of resistance. Out of all significant pairwise comparisons, 44% were related to crop rotation frequency, 33% to previous herbicide-resistance status, and 22% to location. Results highlight that growers can proactively manage herbicide-resistance evolution of horseweed in Michigan by adopting integrated weed management techniques, especially crop rotations and herbicide rotations, to prevent the successive selection events that occur in low diversity management systems. Dedicated to my Biggest Cheer Section: Julio Cezar Sulzback. Angelita Matilde Marchi Sulzback, Gabriela Camila Marchi Sulzback, Paula Fernanda Sulzbach, Adria Fontana Marchi, and Aline Rohden. Thank you for always believing in me. iii ACKNOWLEDGEMENTS First, I would like to acknowledge my professors and mentors Dr. Eric Patterson and Dr. Erin Burns for giving me the opportunity to pursue a Master’s of Science degree at Michigan State. Being an international student in a country with such a different culture may be hard sometimes, but their knowledge regarding all things weed science and life, along with friendly interactions, patience in mentoring me, and constant encouragement have been a great help to me over the past years. I cannot put in words what this opportunity meant to me; all I can say is that their simple “YES” has dramatically changed my life, and I am eternally grateful for them. Thanks to them and Dr. Martin Chilvers for serving on my committee and reading this whole thesis. None of my research would be possible without the assistance of the postdocs. I would like to acknowledge Ednaldo Borgato for serving me as a great friend, and consistently providing me insights on my research and how to better approach to resolve any issues. Thanks all my family who offered constant support and encouragement. Special thanks to my parents Julio and Angelita, and my sister Gabriela – they taught me that anything is possible if you believe. Special thanks to my partner Aline Rohden for her constant love and support, even in my darkest period as a MS student – she taught me that, regardless of what our goals are, we need to focus on the process. Thanks to my pets for the emotional support, especially Lili, who was a dog trapped in a cat’s body and now is the most shining star in the sky – she taught me how to live life intensively, regardless on the time we have on Earth. Thanks to my Brazilian fellows for friendship and support. Thanks to my lab mates for sharing their knowledge with me and growing our learning curves together. I would also like to thanks to all the people who directly or indirectly helped me to be where I am, I would never be able to make it alone. iv TABLE OF CONTENTS CHAPTER I: REACTIVE VERSUS PROACTIVE APPROACHES TO HERBICIDE RESISTANCE MANAGEMENT ...................................................................................................1 INTRODUCTION .......................................................................................................................1 WHAT ARE WEEDS? ...............................................................................................................1 NON-CHEMICAL CONTROL ..................................................................................................2 CHEMICAL CONTROL ............................................................................................................3 RESISTANCE IN WEED SPECIES ..........................................................................................5 ACETOLACTATE SYNTHASE INHIBITOR (ALS; GROUP 2) RESISTANCE ...................7 5-ENOLPYRUVYHLSHIKIMATE-3-PHOSPHATE SYNTHASE INHIBITOR (EPSPS; GROUP 9) RESISTANCE ........................................................................................................8 SYNTHETIC AUXIN (GROUP 4) RESISTANCE ...................................................................9 BROADLEAF WEED SPECIES IN MICHIGAN ...................................................................10 METHOD FOR A MORE SUSTAINABLE WEED MANAGEMENT PROGRAM .............12 BIBLIOGRAPHY .....................................................................................................................14 CHAPTER II: OPTIMIZING MOLECULAR ASSAYS FOR GLYPHOSATE AND ALS- INHIBITOR RESISTANCE DIAGNOSTICS IN FOUR WEED SPECIES ............................... 22 ABSTRACT ............................................................................................................................. 22 INTRODUCTION .................................................................................................................... 23 MATERIALS AND METHODS ............................................................................................. 25 RESULTS ..................................................................................................................................28 DISCUSSION ......................................................................................................................... 30 CONCLUSIONS ...................................................................................................................... 34 BIBLIOGRAPHY .................................................................................................................... 35 APPENDIX .............................................................................................................................. 41 CHAPTER III: AGRONOMIC PREDICTORS OF HERBICIDE-RESISTANCE FOR PROACTIVE MANAGEMENT IN MICHIGAN .........................................................................57 ABSTRACT ..............................................................................................................................57 INTRODUCTION .....................................................................................................................58 MATERIALS AND METHODS ............................................................................................. 60 RESULTS AND DISCUSSION .............................................................................................. 62 BIBLIOGRAPHY .....................................................................................................................69 APPENDIX .............................................................................................................................. 73 v CHAPTER I: REACTIVE VERSUS PROACTIVE APPROACHES TO HERBICIDE RESISTANCE MANAGEMENT INTRODUCTION Herbicide resistance is a constantly growing threat to agriculture in the parts of the world that heavily rely on them for weed control. In Michigan agroecosystems, horseweed (Erigeron canadensis L.), Palmer amaranth (Amaranthus palmeri S. Watson), waterhemp (Amaranthus tuberculatus (Moq.) Sauer), and common ragweed (Ambrosia artemisiifolia L.) are among the most troublesome herbicide resistant weed plants (MSU-PPD, 2024). Traditionally, weed managers use a reactive approach to failures in weed control, including herbicide resistance, where first a problem occurs and then the issue is remediated (Robert et al., 2016). However, it may be possible to take a proactive approach to weed management where weed control issues are predicted using a combination of epidemiological approaches and rapid diagnostics to predict problems and then adjust agricultural practices to reduce the likelihood of weed control failure. This thesis aims to develop molecular assays for rapid detection of common herbicide resistance mechanisms in Michigan dicot weeds so that farmers can make in-season decisions on weed control practices (Rapid, but still reactionary methods for herbicide resistance management) as well as understand and predict the main agronomic drivers of herbicide resistance so that farmers can take proactive measures to avoid the development of herbicide resistance in their properties and regions. WHAT ARE WEEDS? Weeds can be any plant that is unwanted by humans and this designation can be prescribed for any number of reasons. Weeds have been present in agriculture since it began 12000 years ago when humans began selecting some plants for food while others as undesirable (Zeder, 2011). Ultimately, their negative effects on crops include reducing crop emergence and establishment (Felton, 1976), reducing grain quality, and, most importantly reduced crop yield (Mousa et al., 2022), which directly results in economic losses for farmers (Gawęda et al., 2020; Latinia & Eisvand, 2021). Primarily, weeds are detrimental because they compete for water, soil nutrients, sunlight, and space, and are often more efficient than their crop counterparts (Gawęda et al., 2020; Latinia & Eisvand, 2021). In the United States, competitive weed species span a wide taxonomic range including both dicotyledonous and monocotyledonous plants. The most common troublesome weeds for row crops in North America include horseweed (Erigeron candensis), 1 common lambsquarters (Chenopodium album), giant, green, and yellow foxtail (Setaria faberi, Setaria viridis, and Setaria pumila, respectively), Palmer amaranth, redroot pigweed (Amaranthus retroflexus), waterhemp, common ragweed, and barnyardgrass (Echinochloa spp) to date (Heap, 2023). High levels of crop production are not possible without weed control. If left unchecked, weeds can cause entire crop loss and therefore weed control is a multibillion-dollar industry (Abusteit, 1993; Soltani et al., 2017). For instance, weed species can cause yield loss up to 80% in soybean (Glycine max (L.) Merr.) (Keramati et al., 2008; Sebayang & Rifai, 2018), and 69% in corn (Zea mayz L.) (Ford et al., 2014; Soltani et al., 2021). There is a wide range of weed control practices, but broadly speaking they are broken into non-chemical control which includes mechanical, cultural, and biological control practices and chemical control (i.e. the use of high efficiency herbicides). Best practice for weed control integrates several practices from both chemical and nonchemical control as this delays weed evolution and maximized crop yield (Abbas et al., 2018; Hamill et al., 2004). For each crop/weed combination there exists a critical period of weed control (CPWC) which provides a timeframe for farmers to remove weeds in their fields. Before this period, weeds have yet to emerge and control practices may be ineffective and afterward this period, the weeds have already begun to decrease crop yield (Mousa et al., 2022). The critical period for weed management is critical to understand as it minimizes establishment and resource usage by weeds (Dang et al., 2020) and thus preventing negative effects of weed species (Ferrell et al., 2021). This is especially important in situations where initial weed control practices are performed but fail. The time between identifying a weed control failure and being able to respond with an alternative strategy and stay within the CPWC is very short. NON-CHEMICAL CONTROL The first methods for non-chemical control are changes in agricultural practices broadly defined as “cultural practices”. Cultural control practices are management strategies that support crop fitness so that they can outcompete weeds, or at least put up a fight. These strategies include: maintaining optimal pH for the crop plant, fertilization, crop rotation, and reduced fallowing (Rabin, 2012), all of which support crop fitness and help outcompete weeds for resources. For example, previous research has found that weed infestations are increased when crops are grown in monoculture in contrast when grown in crop rotation (Gawęda et al., 2020). Monoculture 2 systems have less crop diversity as well as a decreased diversity of weed control practices, these systems are less resilient and far less likely to outcompete weeds. These monoculture systems reduces herbicide rotation options, which also reduces site of action rotation, thus increasing selection pressure on a few sites-of-action and increasing issues with herbicide resistance. When crop rotation is adopted, the diversity of plants increases, as does the types of weed control practices available. This makes the cropping system more resilient making weed control more tractible both in the short and long term. Additionally, by adopting crop rotation, it is possible to rotate herbicides sites of action, and decreasing the likelihood of herbicide resistance issues. Ultimately, crop rotation interrupts the life cycle of weeds, thus depleting seeds from the seedbank, and suppressing weed competition. Therefore, the impacts of crop rotation on weed control can be massive and synergize with chemical weed control techniques for increasing weed control technique diversity (Gawęda et al., 2020). Another non-chemical control method that is widely adopted are various forms of mechanical control. Mechanical control techniques physically destroy or inhibit weeds with mechanical implements such as plows, mowers, tillers, etc. Mechanical control methods can be a cheap, low tech, practice that both conventional and organic farmers can employ (Fang et al., 2023). Common implements that are used for mechanical weed control are harrows, weeders, and cultivators (Abbas et al., 2018). Studies from Gawęda et al. (2020) and Donald et al. (2001) evaluated the effect of mechanical control via tillage; results showed that there is a considerable increase in weed infestation under no-tillage compared to tillage conditions. Mechanical control techniques can both synergize and antagonize the efficacy cultural and chemical control practices as well as interact with other agronomic factors such as soil health and therefore should be carefully considered and implemented. CHEMICAL CONTROL Chemical weed control is the use of herbicides to control weedy plants. Each herbicide works by inhibiting an essential physiological process in a plant, their so-called mode-of-action. Within each mode-of action there are one or more specific protein targets, called the site-of-action (Gaines et al., 2020). Generally, the binding of the herbicide to the protein is irreversible, or at least much stronger than the native substrate of the protein (Gaines et al., 2020). The interference with the proteins normal function unbalances metabolic reactions and causes physiological anomalies such as dwarfing, wrinkling and twisted leaves, chlorosis and necrosis, and ultimately 3 death (Gunsolus & Curran, 1991). The first herbicide ever discovered was 2,4,5- Trichlorophenoxyacetic acid (2,4,5-T) after World War II, another auxin-mimicking herbicide (Grossmann, 2010; Peterson et al., 2016). Therefore, the introduction of chemical control is relatively new (approximately 80 years) when compared to the entire history of weed control (Duke & Powles, 2008). While Herbicides can be classified based on which types of plants they affect, how they injure the plant, when they are applied, their site of action, their mode of action, chemical family, etc., one of the most important features is selectivity (Gwatidzo et al., 2023). Herbicides are classified according to their mode of action in the plant, which is then separated into different sites of action. This classification and attributed a number to them, which indicates different sites of action (i.e. glyphosate group 9, ALS group 2 etc.). Herbicides can be broadly classified as selective or non-selective, where selective herbicides are herbicides that control specific weeds without injuring crops while non-selective herbicides control a broad-spectrum of plants in the fields, injuring both weedy plants and crops alike (Duke & Powles, 2008). There are many selective products as they are the safest to use in protecting specific crops while controlling specific weeds. For example, it is relatively common to control broadleaf weeds in grass crops or grass weeds in broadleaf crops. Examples of selective broadleaf herbicides are 2,4-D and dicamba as well as many other members of the Auxin-mimicking herbicides while an example of a grass herbicide is clethodim as well as many other members of the acetyl-CoA carboxylase (ACCase) inhibiting herbicides (Grossmann, 2010). An example of a non-selective herbicide is glyphosate (Duke & Powles, 2008; Gunsolus & Curran, 1991; Gwatidzo et al., 2023). This herbicide was relegated to bare-ground, burndown, and other total-vegetation control needs until the invention of genetically modified crops (GM crops) that resistant the herbicide which makes it highly selective for resistant crops (Duke & Powles, 2008; Gunsolus & Curran, 1991; Gwatidzo et al., 2023). Farmers in North America have heavily adopted chemical control because it was efficient, inexpensive, and greatly simplifies weed control (Duke & Powles, 2008b; Norsworthy et al., 2012; Pingali, 2012) This adoption has made herbicides more-or-less essential to high-production row- crop agriculture (Heap, 2014). GM crops has further increased dependence on herbicides – simplifying weed control even further and making it even more cost-efficient (Sprent, 2011). These GM herbicide resistance traits have other benefits for growers such as the ability to do no-till agriculture which has been shown to improve soil health and fertility. The use of GM crops directly 4 affected herbicide usage worldwide because GM crops enable producers to change management strategies, such as using the nonselective herbicide glyphosate in established crops (Green, 2014). To date, 93% of soybean and 92% of corn acreage have the GM trait known as Roundup Ready®, making them resistant to glyphosate (USDA, 2023). The adoption of GM crops has also been international with countries such as Brazil and Argentina widely adopting GM soybeans for example (Duke & Powles, 2008). Unfortunately, GM crops have also decreased the diversity of herbicides used in many row-crop systems, leading to an over-reliance on a few chemicals, which, in turn, has led to a drastic increase in herbicide resistance evolution (Gunsolus & Curran, 1991; Heap, 2014). RESISTANCE IN WEED SPECIES According to the international herbicide resistance weed database, there are over 500 confirmed unique cases of herbicide resistance to 21 herbicide sites of action (Heap, 2023). Simply speaking, resistance is the evolved ability to survive field-level doses of an herbicide. Generally, resistant individuals have one or more alterations in their physiology that reduce the effectiveness of a given herbicide to control it. These alterations are due to mutation in their DNA which are therefore inheritable and selectable. Generally, it is assumed that these mutations occur naturally within weed population, but their frequency in the population is initially low (Gaines et al., 2020; Powles, 2008). When the same herbicide is used repeatedly, the initially rare mutant individuals (Gaines et al., 2020), increase in frequency and begin competing with crops (Duke & Powles, 2008b; Gaines et al., 2020; Gould et al., 2018; Hamill et al., 2004; Tranel et al., 2002). The speed of herbicide resistance evolution depends on several factors including mutation rate, population size, outcrossing frequency, allele dominance, and fitness (Gould et al., 2018; Yang & Kim, 2016). Perhaps the biggest determiner of resistance is the nature of the chemical-protein interaction. Some herbicides are prone to resistance from several common target site mutations (e.g. ALS-inhibitors) while other chemistries tend to require more complex or rare traits such as copy number variation of the target site (e.g. Glyphosate resistance). The factors that govern what specific mutations cause resistance to which herbicide are complex, leading to a case-by-case understanding of resistance mechanisms. Resistance mechanisms are separated into two broad categories: target-site resistance (TSR) and non-target-site resistance (NTSR) (Gaines et al., 2020). Target-site resistance mechanisms include single nucleotide polymorphisms (SNPs) and insertions/deletions (In/Dels) 5 in the target protein or overexpression of herbicide-targeted enzyme, usually facilitated by gene amplification (Gaines et al., 2020). Target-site resistance mutations are generally rare as they can cause fitness penalties by changing the efficacy of the target enzyme, which are always critical enzymes for the plant to survive – that’s what makes them good herbicide targets (Tranel et al., 2002). SNPs in the DNA of an organism change amino acids which in turn change the shape and efficiency of a protein. These usually decrease binding affinity of the enzyme for the herbicide while maintaining a certain level of affinity for its natural substrate (Gaines et al., 2020; Knezevic et al., 2016), reducing the herbicide’s affinity for the herbicide relative to the normal substrate. In/Dels are insertions or deletions of nucleotide sequence in the DNA sequence that change amino acids (Gaines et al., 2020). Indels, however, are even less common as SNPs, as the changes they make in the amino acid sequence are larger and potentially carry large fitness penalties. Another TSR mechanism is gene amplification, which consists of multiple copies of the herbicide’s target gene, and it is often referred as copy number variation (CNV). Copy number variation results in overexpression of the target-site enzyme, so the amount of herbicide applied is not sufficient to inhibit the overexpressed enzymes, thus the resistant plants are capable functioning normally in the presence of field rates of the herbicide (Gaines et al., 2020). Mechanisms that confer NTSR are often related to physiological processes that reduce the amount of herbicide that reaches its target in the plant such as herbicide metabolism (the increase of herbicide’s active ingredients degradation by metabolic pathways), overexpression of genes and proteins production that are not the herbicide target, reduced uptake and/or translocation (regulation of herbicide uptake by the plant, or the reduction of translocation of these molecules), and compartmentalization (the increase of sequestration and storage of these molecules in vacuoles) (Gaines et al., 2020; Jugulam & Shyam, 2019). Metabolism is the ability of the weed to break down the herbicide, generating metabolites that are less toxic or inactive (Dimaano & Iwakami, 2021). It is usually associated with the increased activity of enzymes (induced or not) that are part of detoxification pathways, including: cytochrome P450 monooxygenases, glutathione S-transferases (GSTs), and esterase (Gaines et al., 2020). Herbicide metabolism usually involves three phases: (I) initial reactions such as oxidation, reduction, or hydrolysis, (II) primary conjugation with internal substrates such as sugars, amino acids, or glutathione, and (III) secondary conjugation, the generation of insoluble residues, or storage in the vacuole. The first step involves processes to remove electrons (oxidation), add electrons (reduction), or breaking 6 down the molecule by adding water (hydrolysis). The second/third step, conjugation, is the process in which the primary metabolites are combined with sugars or amino acids resulting in reduced toxicity and greater solubility in water (Délye, 2013). This enables the herbicide to be transported out of the plant and eliminated or integrated in macro-structures like the cell wall. Reduced absorption and translocation are generally associated with genetic or physiological alterations that change the ability of the active ingredients to enter and move within the plant, reducing the herbicide’s effectiveness. Cuticle modification and changes in membrane transporters (e.g. ATP-binding cassette (ABC) transporters,) are examples of this type of herbicide resistance (Gaines et al., 2020; Menendez et al., 2023). The ABC transporters, specifically, perform active transport of a wide range of organic compounds through the membrane. Major facilitator superfamily transporters also perform transport through the membrane, whereas proton antiporters are involved in the exchange of protons of H+ to other ions that can pass through the membrane (Menendez et al., 2023). One of the most notorious cases of herbicide resistance is with the ABC transporter activity inhibition and the herbicide 2,4-D. ABC transporters’ activity is reduced, resulting in lower intracellular concentrations of 2,4-D, which reduces the efficacy of the herbicide (Goggin et al., 2016). ACETOLACTATE SYNTHASE INHIBITOR (ALS; GROUP 2) RESISTANCE Branched-chain amino acids are crucial for all organisms to survive and grow, as they are precursors of many metabolic reactions and essential for building proteins. A key protein in the formation of these amino acids is acetolactate synthase (ALS). ALS is directly responsible for the biosynthesis of acetolactate the precursor of branched-chain amino acids leucine, isoleucine, and valine (Umbarger, 1978). When branched-chain amino acid metabolic pathway is interrupted by the inhibition of ALS, the plant will die by amino acid starvation (Tranel et al., 2002). ALS- inhibitors (group 2 herbicides) (Gunsolus & Curran, 1991) are an important herbicide group that vary greatly in selectivity and may control annual and perennial broadleaf or grass weeds. ALS- inhibitors were first introduced in agriculture in 1982, with the usage of the herbicide chlorsulfuron, an herbicide that controls broadleaf weed species in cereal crops. Their diversity and high efficacy in controlling weeds at low rates (Ray, 1984), made these herbicides common for many crops. To date, there are five chemical families that have ALS as a site of action; the sulfonylureas (SUs), imidazolinones (IMIs), triazolopyrimidines (Types 1 and 2), pyrimidinyl benzoates, and triazolinones. 7 Even though ALS-inhibitor chemical families are diverse, there are 21 weed species described with resistance (Gaines et al., 2020), via both TSR and NTSR mechanisms. The mechanisms involved in TSR to group 2 herbicides are CNV (Iwakami et al., 2017) and SNPs in the ALS gene (Küpper et al., 2017). Iwakami et al. (2017) reported that ALS resistance in a population of shortawn foxtail (Alopecurus aequalis) was conferred by gene amplification. Furthermore, there are eight reported SNP mutations in ALS gene that confer resistance in positions Ala-122, Pro-197, Ala-205, Asp-376, Arg-377, Trp-574, Ser-653, and Gly-654 (Heap, 2023). For instance, the Pro197Ser mutation is often found in Group 2 resistant horseweed; this substitution has been shown to confers resistance to three chemical families of group 2 herbicides (imidazolinone, pyrimidinylthiobenzoic acid, and sulfonylurea) (Zheng et al., 2011). NTSR resistance to group 2 herbicides has be reported in only a few species, such as rigid ryegrass (Lolium rigidum Gaud.), and large crab-grass (Digitaria sanguinalis (L.) Scop.), which is conferred by an enhanced detoxification (Corbett & Tardif, 2006). 5-ENOLPYRUVYHLSHIKIMATE-3-PHOSPHATE SYNTHASE INHIBITOR (EPSPS; GROUP 9) RESISTANCE Aromatic amino acids are also critical for plants, as plants use them as precursors to other molecules, including other amino acids, proteins, plant defense, lignin, and hormones as well as building blocks for proteins (Tzin & Galili, 2010). Aromatic amino acids are the product of the shikimate pathway, one of the largest secondary metabolite pathway in plants in terms of net carbon flow (Ghosh et al., 2012). Inhibiting any enzyme in this pathway results in a lack of aromatic amino acid production which causes a systemic dysregulation of the subsequent metabolic pathways and eventual death (Wang & Ching-Yuh, 2001). The only enzyme in this pathway that is an herbicide target is 5-enolpyruvylshikimate-3-phosphate synthase inhibitor (EPSPS), which converts phosphoenolpyruvate (PEP) and 3-phospho shikimate (S3P) into EPSP (Gunsolus & Curran, 1991). Glyphosate is the only registered disruptor of EPSPS and therefore the only member of a group 9 herbicides (Shaner et al., 2005). To date, there is a total of 355 weed species with resistance to glyphosate, and the mechanisms of resistance are both TSR and NTSR (Heap, 2023). EPSPS TSR mechanisms commonly identified in weed species are SNPs (Takano et al., 2019), gene amplification (Gaines et al., 2011), and overexpression (Tani et al., 2015). The SNPs Pro106Ser and Thr102Ile as well as their double-mutation termed ‘TIPS’ (Thr102Ile & Pro106Ser) in the EPSPS gene can confer 8 resistance to glyphosate, as observed in goosegrass (Eleusina indica L. Gaertn.) (Takano et al., 2019). However, these SNPs often come with a mild to moderate fitness penalty, due to loss of efficiency of catalytic reactions, and accumulation of shikimate (Han et al., 2017; Sammons & Gaines, 2014). CNV of the EPSPS gene is the second most common TSR mechanism for glyphosate, occurring in both broadleaf and grass weeds (Gaines et al., 2010; Patterson et al., 2018). EPSPS is overexpressed due to these CNVs which in turn increases EPSPS concentration, and therefore it requires a higher amount of glyphosate to control these individuals compared to what is required to control a susceptible individual (Gaines et al., 2011, 2020). EPSPS resistance can also be conferred via NTSR mechanisms, including reduced absorption and translocation (De Prado et al., 2005; Tani et al., 2015), rapid necrosis (Moretti et al., 2018; Van Horn et al., 2018), and metabolism (Pan et al., 2019). Tani et al. (2015) observed that the TSR and NTSR mechanism act together to confer glyphosate resistant horseweed, due to reduced translocation via ABC transporters and the overexpression of EPSPS. Also, rapid necrosis a novel mechanism of glyphosate NTSR has been reported in giant ragweed (Ambrosia trifida L.) (Moretti et al., 2018; Van Horn et al., 2018). These studies showed that rapid necrosis resulted in reduced translocation of glyphosate to its target site. SYNTHETIC AUXIN (GROUP 4) RESISTANCE Synthetic auxins are another important herbicide group in row crop production. These herbicides are part of group 4 and are frequently used in small grains, corn, and sorghum due to their natural selectivity in grass crops against broadleaves as well as in GE soybean (Enlist E3™soybean, Roundup Ready 2 XtendiMax®)(Todd et al., 2020). These herbicides mimic auxin molecules (Gunsolus & Curran, 1991), the main plant hormone responsible in regulating plant growth. When synthetic auxin herbicides are absorbed by the plant, the herbicide is translocated throughout the plant and they are thought to bind members of the Aux/IAA protein family. Aux/IAA is a protein that suppresses auxin response factors (ARF), and this suppression inhibits the transcription and expression of the plant hormone auxin (indole-3-acetic acid, or IAA) (Hagen & Guilfoyle, 2002). Herbicide binding releases Aux/IAA from ARFs and the auxin responsive gene starts to be expressed which leads to several abnormal plant growth phenotypes. Ultimately, synthetic auxin herbicides cause tissue necrosis, abnormal cell division and growth, and death (Gaines et al., 2020; Mockaitis & Estelle, 2008). 9 Resistance has been shown to be conferred by both TSR and NTSR mechanisms to group 4 herbicides. A few polymorphisms have been described that cause TSR, primarily in members of the Aux/IAA protein family (Walsh et al., 2006). For example, LeClere et al. (2018) found a mutation in the coreceptor IAA16 (Aux/IAA16) that confers resistance to dicamba in kochia while Figueiredo et al. (2022) identified a deletion of 27 nucleotides (9 amino acids) in the degron tail of IAA2 (Aux/IAA2), that caused resistance to 2,4-D in waterhemp. In both cases. AuX/IAA proteins became less sensitive to their Group 4 partners. To date, both metabolism and reduced translocation mechanisms have been found that cause NTSR to auxin mimic herbicides. These processes can be complex and variable depending on the herbicide and plant species. One example is reduced activity of ABC transporters, which results in decreased mobility of 2,4-D, thus diminishing the amount of active ingredient reaching the target tissue (Goggin et al., 2016). The resistance to group 4 herbicides is obviously advantageous in agronomic systems where they are used frequently; however, resistance mechanisms for synthetic auxins often carry severe fitness penalties as they change the regulation of critical plant hormones, mainly indole acetic acid. LeClere et al. (2018) determined that mutation in BsIAA16 that confers cross resistance to dicamba and 2,4-D in kochia reduces seed mass production to less than 50% when compared to a non-mutant individual. BROADLEAF WEED SPECIES IN MICHIGAN Globally speaking, grass weeds are generally the more damaging weed species; however, in North America, and especially in Michigan it is often broadleaves that are the most difficult to control, especially in terms of herbicide resistance. In Michigan, our primary herbicide resistant weeds include the broadleaf weed species horseweed, Palmer amaranth, waterhemp, and common ragweed (MSU-PPD, 2024). These weeds are problems in many of the major row, vegetable, and tree crops in Michigan (Felton, 1976), leading to losses in grain quality, biomass production, and yield (Mousa et al., 2022). Ultimately, these negative effects lead to economic losses for farmers (Gawęda et al., 2020; Latinia & Eisvand, 2021). Therefore, it is necessary to comprehend their biology in order to determine the best approach to effectively manage these species. Horseweed (family Asteraceae) is a C3 monoecious summer or winter annual weed species that can self-pollinating and reproduce sexually (Mulligan & Findlay, 1970). Horseweed is a cosmopolitan weed species and does not require specific climatic conditions to grow (Weaver, 2001). These plants have two forms during their life cycle, the vegetative stage (or rosette) and the 10 mature stage (or bolt) (Buhler & Owen, 1997). When in the rosette stage, their root system is aggressive, which promotes establishment and nutrient and water use (Weaver, 2001). During the bolting stage, each plant can produce 200,000 seeds (Buhler & Owen, 1997). Due to seed’s morphology, these seeds can be dispersed by wind to long distances (Bhowmik & Bekech, 1993). Herbicide resistance has been described for groups 2, 5, 9 and 22 in this horseweed (Heap, 2023). Palmer amaranth (family Amaranthaceae) is a C4 dioecious summer annual weed species, cross-pollinating and reproduces sexually (Jha et al., 2008; Sauer, 1955; Ward et al., 2013). Palmer amaranth is a cosmopolitan weed species and requires 24/10°C day/night (d/n) and 15 hour photoperiod to grow (Assad et al., 2017; Roberts & Florentine, 2022). Their deep root system is aggressive and quickly exhausts water and nutrients from the soil, causing severe damage to agricultural lands (Bensch et al., 2003; Menges, 1988). When photoperiod decreases, these plants start to emit their inflorescence, and during the reproduction stage, each plant can produce 200,000 to 1,000,000 seeds. Seeds are small and easily dispersed in shorts distances through gravity; but they can be dispersed to medium and long distances when field operation are done, such as harvesting (Menges, 1988). This weedy species is arguably the most troublesome weed plant to control worldwide due resistance to most major groups of herbicides including groups 2, 3, 4, 5, 9, 10, 14, 15, and 27 (Heap, 2023). Waterhemp (family Amaranthaceae) is a C4 dioecious summer annual weed species, cross- pollinating and reproduces sexually (Assad et al., 2017; Sauer, 1955). Waterhemp is a cosmopolitan weed species and requires similar conditions than Palmer amaranth to grow though better adapted to the cooler and wetter climates found I Michigan where it is endemic (Roberts & Florentine, 2022). Their root system are also similar to Palmer amaranth (deep and aggressive) and they quickly compete for water and nutrients from the soil, causing economic losses on agricultural lands (Weaver & McWilliams, 1980). When photoperiod become shorter, these plants start to emit their inflorescence, and during reproduction stage, each plant can produce 200,000 to 600,000 seeds (Assad et al., 2017). Similarly to Palmer amaranth, waterhemp’s seeds are small which is dispersed through gravity in short distances; but it can be dispersed in medium or long distances with the use of implements, such as a harvester (Menges, 1988). This weedy species has evolved resistance to various herbicides, including groups 2, 4, 5, 9, 14, 15, 27 (Heap, 2023). Common ragweed (family Asteraceae) is a C3 monoecious summer annual weed species, cross-pollinating and reproduces sexually (Essl et al., 2015). Common ragweed is a cosmopolitan 11 weed species and grows in a wide thermal range (8-30°C) and longer photoperiod of 14 hours to vegetatively grow (Deen et al., 1998). When photoperiod is less than 14 hours, these plants start their reproductive stage (Deen et al., 1998). During the reproductive stage, each plant can produce a wide range of seeds, varying from 3,000 to 62,000 (Dickerson & Sweet, 1971). Common ragweed seeds can be dispersed through several pathways, but dispersal is most significant via agricultural machinery and mowing machines (short to long distances) (Karrer & Vitalos, 2009). Ragweed is probably best known for being a major seasonal allergen as well as for its incredible seed longevity and dormancy (Fleming et al., 2023). This weedy species has adapted to herbicides of groups 2, 4, 5, 9, and 14 (Heap, 2023). METHOD FOR A MORE SUSTAINABLE WEED MANAGEMENT PROGRAM Weed control still relies heavily on chemical control, and the recurrent usage of herbicides will increase selection pressures and therefore herbicide-resistance evolution. The inevitability of this phenomena is now clear after the characterization hundreds of documented cases of resistance evolution, showing how fragile and non-sustainable chemical-only control really is. However, recent advance of agricultural technologies and our increased understanding of how plants evolve, has led to an understanding of the importance of diversified management strategies - an integrated weed management program seems to be able mitigate or at least delay future resistance issues. Perhaps most important for delaying resistance is crop rotation and diversity; this practice enables farmers to alternate herbicides’ SOA according to the crop, selecting weed populations in multiple different directions. In addition to crop rotation, supporting crop competitiveness with optimized fertilizing programs helps crops to outcompete weeds by quickly, most importantly reaching maximum crop canopy quickly and shading emerging weed seedlings. Fertilizing and fallowing also serve to restore nutrients and soil health, which are essential for a competitive advantage for crops. Chemistry will still continue to be essential in conventional agriculture. The development and adoption of new bioengineered crops (such as Roundup Ready 2 XtendiMax® - glyphosate and dicamba, Enlist E3™ - 2,4-D choline, glyphosate, and glufosinate tolerant) will broaden the usage of existing SOA, providing alternatives for farmers for control; furthermore, the discovery and development of new herbicides molecules will hopefully provide alternatives for farmers now that it is clear that glyphosate will no longer be a solo product. New technologies are also being developed that will heavily alter integrated weed management. Most importantly drone technologies that rapidly identify and map weeds may greatly impact future weed control. These 12 drones lead to technologies such as electric-weeding , see-and-spray (allows direct applications of herbicides not able to be broadcast), direct mechanical control, etc. that would be otherwise infeasible without robotic autonomy. 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Weed Technology, 15(4), 628–635. https://doi.org/10.1614/0890 Ward, S. M., Webster, T. M., & Steckel, L. E. (2013). Palmer Amaranth (Amaranthus palmeri): A Review. Weed Technology, 27(1), 12–27. https://doi.org/10.1614/wt-d-12-00113.1 Weaver, S. E. (2001). The biology of Canadian weeds. 115. Conyza canadensis. Canadian Journal Plant Science, 81, 867–875. https://doi.org/https://doi.org/10.4141/P00-196 Weaver, S. E., & McWilliams, E. L. (1980). The Biology of Canadian Weeds. 44. Amaranthus retroflexus L., A. powellii S. Wats. and A. hybridus L. Can. J. , 60, 1215–1234. Yang, Y. Y., & Kim, J. G. (2016). The optimal balance between sexual and asexual reproduction in variable environments: A systematic review. In Journal of Ecology and Environment (Vol. 40, Issue 1). BioMed Central Ltd. https://doi.org/10.1186/s41610-016-0013-0 Zeder, M. A. (2011). The origins of agriculture in the Near East. Current Anthropology, 52(SUPPL. 4). https://doi.org/10.1086/659307 Zheng, D., Kruger, G. R., Singh, S., Davis, V. M., Tranel, P. J., Weller, S. C., & Johnson, W. G. (2011). Cross-resistance of horseweed (Conyza canadensis) populations with three different ALS mutations. Pest Management Science, 67(12), 1486–1492. https://doi.org/10.1002/ps.2190 21 CHAPTER II: OPTIMIZING MOLECULAR ASSAYS FOR GLYPHOSATE AND ALS- INHIBITOR RESISTANCE DIAGNOSTICS IN FOUR WEED SPECIES ABSTRACT Herbicide-resistant weeds pose a threat to food production in modern agriculture, causing US$32 billion dollars in crop production losses worldwide. In Michigan, highly troublesome and widespread weeds include waterhemp, Palmer amaranth, common ragweed, and horseweed, with accessions that are resistant to glyphosate (Group 9) and ALS-inhibitors (Group 2), major herbicide sites of action utilized in soybean and corn cropping systems. Molecular assays for rapid resistance diagnostics to confirm the in-field status of herbicide resistance can assist with more effective, timely, and proactive management. In this research, we developed and tested PCR-based assays to identify target-site resistance mechanisms to both herbicide groups through Sanger sequencing and EPSPS copy number variation. Nine different SNPs were identified in five ALS positions known to confer herbicide resistance among all species surveyed. Pro197Ser was the most frequent in horseweed and common ragweed accessions, whereas Trp574Leu was the predominant mutation in Palmer amaranth and waterhemp. Four horseweed accessions contained the Pro106Ser mutation in the EPSPS gene, which confers resistance to glyphosate. Additionally, waterhemp and Palmer amaranth had 2-7 and 20-160 copies of EPSPS, respectively. The assays were validated by comparing genotyping of several field-collected accessions of unknown resistance status with known resistant and susceptible accessions. The efficacy of genotyping assays was > 98%, and required only two days, confirming that molecular assays are a robust tool for rapid resistance diagnostics. These assays can help growers evaluate herbicide resistance status in weed populations within the same growing season, allowing them to adopt effective management practices. KEYWORDS Amaranthus, Diagnostics, Herbicide Resistance, Horseweed, Molecular Biology, Ragweed 22 INTRODUCTION Herbicide-resistant weeds are one of the major threats to sustainable, profitable agriculture, causing approximately 32 billion dollars in crop production losses annually in the United States (Pimentel et al., 2000; USDA, 2015). Currently, there are 272 species of weeds with resistance to at least one site of action, with many populations displaying multiple and/or cross-resistance (Heap, 2023). Furthermore, resistance has evolved at least once to 21 of the 31 known herbicide sites of action (Heap, 2023). The causes of herbicide resistance are broadly classified into two major categories: target- (TSR) and non-target-site resistance (NTSR) mechanisms. TSR mechanisms include mutations in the gene that codifies the herbicide target enzyme which in turn leads to reduced herbicide binding, or increased production of the herbicide target enzyme, often caused by gene copy number variation (CNV) (Gaines et al., 2020). NTSR mechanisms include reduced or enhanced herbicide detoxification, vacuolar sequestration, and reduced absorption/translocation (Jugulam & Shyam, 2019). Herbicide resistance evolves when relatively rare alleles in a population are selected for by the repeated use of the same chemistry or chemistries with the same target enzyme. Due to their high efficiency, relatively low cost, enhanced crop safety, and ease of use, herbicides are ubiquitous in row crop farming in the United States making herbicide resistance all but inevitable in weeds that compete with those crops. In Michigan row crops some of the most troublesome weeds are horseweed (Conyza canadensis), Palmer amaranth (Amaranthus palmeri), waterhemp (Amaranthus tuberculatus), and common ragweed (Ambrosia artemisiifolia). In the past, these weeds were effectively controlled in other United States regions and countries with herbicides that inhibit the acetolactate synthase (ALS, Group 2) and 5- enolpyrovylshikimate synthase (EPSPS, Group 9). However, the repeated use of these herbicides has led to resistance to these site-of-action, with first report in Michigan in 2004 by the Michigan State University’s Plan and Pest Diagnostics (MSU-PPD, 2024). TSR to glyphosate and ALS-inhibitors is often found in Palmer amaranth, waterhemp, common ragweed, and horseweed. To date, nine amino acids positions in the ALS enzyme were discovered in weed species conferring resistance to ALS-inhibiting herbicides (Table 2.1). The most common ALS mutations are a Tryptophan to Leucine replacement at amino acid position 574 (Trp574Leu) and several changes to the Proline at position 197 (Pro197---). TSR to ALS-inhibitors have previously been identified in horseweed, common ragweed, Palmer amaranth, and waterhemp, and several mutations have been previously reported for each species (summarized in 23 Table 2.1). Resistance to glyphosate (the only commercially used Group 9 herbicide) can also be caused by mutations in its target protein, EPSPS (Table 2.1). A mutation in Proline to Serine at position 106 (Pro106Ser) is the most common and has been identified in horseweed (Beres et al., 2020), Palmer amaranth (Kaundun et al., 2019), and waterhemp (Nandula et al., 2013). However, the most common glyphosate resistance mechanism for Palmer amaranth and waterhemp is extra EPSPS gene copies, which results in an overproduction of EPSPS protein and therefore the recommended dose is no longer sufficient to control these plants (Dillon et al., 2017; Koo et al., 2018). It should be noted that the presence of TSR does not eliminate the co-occurrence of NTSR mechanism in the same plant, and that different mechanisms can be additive (Laforest et al., 2021; Page et al., 2018). One of the most important tasks in the battle against herbicide-resistant weeds is to quickly and accurately diagnose resistant populations, so that proper control measures can be implemented – the faster resistance can be determined and management practices altered, the greater the chances of delaying its spread. This is similar to epidemiological principles of disease control (Comont & Neve, 2021). We distinguish diagnostics methodologies into two large groups, so-called ‘traditional diagnostics’ and ‘molecular diagnostics’. The traditional dose-response curve (DRC) method to diagnose herbicide resistance (Burgos et al., 2013) has been used for almost 40 years (Carpenter, 1986), but it can have severe time and space limitations, besides being labor-intensive. One DRC experiment takes at minimum 30 days from the time of seed germination until the final evaluation, thus it is not a suitably quick diagnostic method to inform critical periods for weed control. Generally, results of DRC experiments cannot be utilized in the same growing season for weed control, resulting in economic consequences, such as the need of additional herbicide applications, and contribution of herbicide-resistant seeds into the soil seedbank. Molecular diagnostic tools can be a remedy for this limitation. These assays are becoming more cost- effective, can be run on any tissue with DNA (even seeds from the seedbank), and are effective for several common mechanisms, especially TSR. The speed of molecular diagnostics allows growers to take action immediately, reducing the negative economic and environmental costs associated with herbicide-resistant weeds. Molecular diagnostics provide the additional benefit of describing the mechanism of resistance (TSR and NTSR) which may be useful from a basic biology or evolutionary standpoint (Sarangi et al., 2017). TSR mechanisms are common and relatively easy to diagnose. For TSR mechanisms, DNA is extracted followed by either PCR diagnostics like 24 KASP or TaqMan or simply by Sanger sequencing of the target gene (Cutti et al., 2021; Kutasy et al., 2021). NTSR diagnostics on the other hand may require careful plant tissue collection, gene expression detection through qPCR, or biochemical work such as high-pressure liquid chromatography (Han et al., 2021; Pan et al., 2019). It should be noted that molecular diagnostic methods can only detect if the herbicide target is altered or overexpressed; if individuals tested have a resistance mechanism different than the one tested, for instance as NTSR, it is possible to call a false negative. Molecular diagnostics should only be used for confirming resistance, not confirming susceptibility. Scientists have developed many non-molecular, quick herbicide resistance diagnostic tests for different herbicides and weed species, such as leaf-disc assays in Palmer amaranth (Wu et al., 2021), or the quick agar assay (RISQ test) in Lolium spp. (Kaundun et al., 2011). These tests, however, do not provide any herbicide resistance mechanism information (TSR or NTSR) and need to be thoroughly validated with reference lines. Molecular diagnostic techniques can provide faster results, in addition to providing information on DNA mutations or genomic rearrangements. Considering the importance of early herbicide resistance detection and the reproducibility of molecular markers, the objective of this study was to design and optimize a few molecular diagnostics assays to identify glyphosate and ALS resistance in horseweed, Palmer amaranth, waterhemp, and common ragweed, the most prevalent resistant species in Michigan. Additionally, this study presents improved primers and protocols for these target sites to robustly work on all field-collected samples in the state and all greenhouse-grown plants, valuable information for the adoption of these assays as reliable tools for resistance identification. MATERIALS AND METHODS Plant material and DNA extraction Five accessions of Palmer amaranth, waterhemp, horseweed, and common ragweed were collected from soybean and corn producing areas across multiple counties in Michigan (hereafter referred as “greenhouse accessions”). Accessions are defined as seeds from one individual on a farmer’s property. These accessions were stored at 4°C and further used to develop and test molecular markers to confirm the occurrence of common TSR mechanisms for glyphosate and ALS-inhibitors reported in each species (Table 2.1). Previously, these accessions were phenotypically characterized as either resistant or susceptible to the labeled rate of glyphosate (1090 g a.e. ha-1, Roundup PowerMax®), thifensulfuron (4.5 g a.e. ha-1, Harmony SG®), and 25 cloransulam (17.64 g a.e. ha-1, FirstRate®) by Michigan State University (MSU) Plant & Pest Diagnostics (MSU-PPD, 2024). For the genotyping experiments, seeds were broadcast in plastic trays filled with potting soil, and upon emergence, seedlings were transplanted into individual pots. Ten individuals from five collections of each species were sampled for DNA extraction. Approximately 100 mg of young leaf tissue was collected from each individual plant, and the DNA was extracted using the DNeasy® Plant Pro kit (Qiagen, Strasse 1, 40724 Hilden, Germany) with one modification to the manufacturer protocol. The lysis buffer was added to the tubes containing the leaf sample and two metal beads, followed by a grinding step using a Tissue Lyzer II (Qiagen) with frequency of 30 oscillations per second (30/s) for 2 mins. The subsequent steps were performed following the protocol without modifications. DNA was quantified in a Nanodrop One (Thermo Scientific, 5225 Verona Rd., Madison, WI 53711) and diluted to 50 ng µL-1. To verify the robustness of the assays and their applicability to field collections, 14, 3, 21 and 19 additional field samples of horseweed, Palmer amaranth, waterhemp, and common ragweed, respectively, were tested with the molecular assays developed. These samples were collected and sent by growers and MSU Extension Educators from different counties in Michigan, and hereafter are referred to as “field collections”. ALS and EPSPS gene sequencing Several primers pairs were designed to amplify large fragments of the ALS gene from each species so that it could be sequenced, covering the most frequent known herbicide-resistance mutations in each species. Primers were designed for waterhemp, horseweed, and common ragweed based on the sequences available in GenBank (EF157821.1, HM067014.1, MT415954.1, and KX870184.1, respectively), and for Palmer amaranth we used the same primers described in Whaley et al. (2006) (Figure 2.1, Table 2.2). After trying several combinations, primers that worked most robustly (i.e. on all samples, greenhouse and field accessions) are reported here (Table 2.2). To investigate the occurrence of SNPs in horseweed, , we identified three EPSPS genes in the published genome by protein function annotation, EPSPS1, EPSPS2, and EPSPS3 (Genbank: AY545666.1, AY545667.1, and AY545668.1) (Laforest et al, 2020). One of the copies (EPSPS3) was incomplete, missing four of the expected 8 exons, and therefore not a functional copy of EPSPS. To the best of our knowledge, it was unclear whether mutations in the EPSPS1, EPSPS2, 26 or both, cause resistance in horseweed. We tested the primers from Beres et al. (2020), and observed sequence similarity with EPSPS2, and then designed new primer set to amplify EPSPS1 (Table 2.2).The EPSPS1 and EPSPS2 specificity was checked based on fragment size in agarose gel (Figure 2.8). Glyphosate resistance in Palmer amaranth and waterhemp were tested for CNV (next section). Additionally, we sequenced EPSPS gene of three individuals from five accessions of waterhemp in order to find Pro106 mutation (as previously found and indicated in Table 2.1), which was not found. Common ragweed was not tested for TSR because the mechanism in this species had not been clarified until recent description, where Laforest et al. (2024) found that the TSR in EPSPS is through CNV. All PCR were made with 12.5 µL of GoTaq G2 Green Master Mix (Promega, 2800 Woods Hollow Road, Madison, WI 53711), 1 µL of forward and 1 µL reverse primers (10 mM), 8.5 µL of molecular grade water, and 2 µL of DNA (50 ng µL-1). PCR cycles were as follows: 95°C for 5 min, and 39 cycles of 95°C for 30 s, annealing temperature (Table 2.2) for 30 s, 72°C during the extension time (Table 2.2), and 72°C for 8 min. The amplification was verified using agarose gel electrophoresis at 1.5%. Further, PCR products were purified using Wizard SV Gel and PCR Clean-up System (Promega), and samples were sent to the MSU Genomics Core for Sanger sequencing. ALS and EPSPS sequences were translated using Expasy and aligned using ApE (Davis & Jorgensen, 2022). The same sequence used to design primers from the GenBank were included as reference when aligning for comparisons. EPSPS copy number variation Palmer amaranth and waterhemp samples were tested for EPSPS CNV. The reactions were prepared with 10 µL of SsoAdvanced Universal SYBR Green Supermix (Bio-Rad, 1000 Alfred Nobel Drive Hercules, California 94547), 1 µL of forward and 1 µL of reverse primers (10 mM), 2 µL of DNA (10 ng µL-1), and 6 µL of molecular grade water, totaling 20 µL reactions. Forward and reverse primers of EPSPS, and housekeeping control (ALS and β-tubulin) were previously published (Gaines et al., 2010, Godar et al., 2015) and are listed in Table 2.3. The real-time qPCR cycles started with 3 min at 95°C, followed with 30 cycles of 95°C and 1 min at 60°C, with a standard melting curves included in a CFX 96 Real-time system thermocycler (Bio-Rad). The assay was performed with five biological replicates per accession, and two technical replicates. A known susceptible sample was included in each run for comparison. The EPSPS copy number was estimated as relative to ALS and/or β-tubulin in a known susceptible sample. 27 RESULTS ALS sequencing Nine different SNPs were identified in five ALS positions known to confer herbicide resistance among all greenhouse accessions and species sequenced (Figure 2.2). The Pro197 substitution showed more diversity of amino acid replacement, Pro197Ile, Pro197Thr, Pro197Leu, and Pro197Ser than others identified. Overall, 36% of Palmer amaranth contained the ALS wild- type (WT) susceptible allele. One greenhouse accession of Palmer amaranth did not have any ALS mutations, and the remaining four accessions showed a mixture of resistant plants carrying different mutations and susceptible plants. The ALS mutations identified in Palmer amaranth were Pro197Thr, Pro197Ile, Pro197Ile/Thr, Asp376Glu, Trp574Leu, and Ser653Asn (Figure 2.2; Figure 2.3; Table 2.4). Heterozygosity for ALS mutation was present in 42% of the Palmer amaranth plants screened (Figure 2.3). Waterhemp greenhouse accessions did not show any completely susceptible accession. Four out of five accessions had a mixture of resistant and susceptible plants, and one accession had only resistant plants (Figure 2.2). The presence of resistant alleles was observed in 74% out of 50 plants sequenced. The ALS mutations identified in waterhemp were Pro197Thr, Pro197Ser, and Trp574Leu. ALS heterozygosity was present in 53% of resistant waterhemp plants screened (Figure 2.3). Two common ragweed greenhouse accession out of five showed all plants with ALS WT allele, while the other three showed a mixture of ALS mutations and WT allele. The mutations identified in common ragweed were Pro197Leu, Pro197Ser, Ala205Val, and Trp574Leu (Figure 2.2; Table 2.4). ALS heterozygosity was present in 28% of the plants screened (Figure 2.3). Horseweed, the only self-pollinated species studied here, showed two accessions with all plants carrying ALS WT allele and three accessions with all plants carrying ALS mutations (Figure 2.2). The ALS mutations identified were Pro197Ser and Pro197Thr (Figure 2.2; Table 2.4). No genotype mixture and heterozygosity were identified in horseweed accessions. Horseweed EPSPS sequencing Three copies of EPSPS gene were identified in the horseweed genome (Laforest et al., 2020) (GenBank: AY545666.1, AY545667.1, and AY545668.1). Two of these (EPSPS1 and EPSPS2) were deemed potentially functional as they were complete with the requisite eight exons and had the proper start and stop codons (Figure 2.7), while one (EPSPS3) was considered a pseudogene as it did not encode a full-length EPSPS protein. EPSPS1 sequencing did not show any mutation in all greenhouse accessions sequenced; however, four out of five accessions showed 28 the Pro106Ser mutation in EPSPS2, no heterozygosity was identified (Table 2.4; Figure 2.4). One accession had EPSPS1 and EPSPS2 WT allele for all 10 plants sequenced and was susceptible. Palmer amaranth and waterhemp EPSPS copy number variation EPSPS copy number was analyzed using both ALS and β-tubulin as housekeeping genes for Palmer amaranth (Figure 2.5A) and waterhemp (Figure 2.5B). Consistently, when the ALS gene was used as a control, it predicted twice as many EPSPS copies when compared to β-tubulin when running on the same DNA sample (Figures 2.5A and 2.5B). The β-tubulin gene was therefore rejected as a control gene, due to presence of multiple copies in the genome and the potential for multi-locus priming, ALS was used in further EPSPS CNV prediction. In Palmer amaranth individuals from the greenhouse accessions, an EPSPS copy number increase was found in all plants in four out of the five accessions, with 20 individuals out of 25 tested in total, with CNV ranging between 20-160 additional copies (Figure 2.5C), and one population being fully susceptible. EPSPS copy numbers varied across accessions and within individuals from the same accession. In waterhemp greenhouse accessions, an EPSPS copy number increase was found in seven individuals (across three accessions) out of the total 25 individuals (five accessions), ranging from 2-7 copies. The EPSPS CNV varied within and across waterhemp accessions (Figures 2.5D). Validation of assays in field collections Palmer amaranth, waterhemp, common ragweed, and horseweed were collected from fields spanning eight counties around Michigan to validate the molecular markers. First, the ALS gene from all individuals from all four species was sequenced to detect mutations (Figure 2.6A), while Palmer amaranth and waterhemp individuals were used to validate the EPSPS-CNV (Figure 2.6B). Individuals with and without ALS mutations were detected in the field for all four studied species. Palmer amaranth was collected in Allegan county and two collections carried the ALS gene with the Trp574Leu mutation and one with the WT allele (Table 2.5). Out of 19 waterhemp collections across seven counties, 14 did not show any ALS mutation, while five had Trp574Leu or Ser653Asn, and no Pro197 substitutions (Table 2.5). The Ser653Asn had not been detected in any waterhemp greenhouse accessions. Out of 19 common ragweed collections, two contained the Trp574Leu mutation, one the Ala205Val mutation, and none had the Pro197 substitution (Table 2.5). Out of 14 horseweed collections, eight had mutations at the Pro197 position, either Pro197Ser or Pro197Leu (Table 2.5). The Pro197Leu substitution was not detected in the greenhouse accessions. 29 The EPSPS-CNV assay showed that two out of three field collections of Palmer amaranth had low CNV, varying between 1 and 7 copies of EPSPS (Table 2.5, Figure 2.6B), and one collection was resistant with 21 copies of EPSPS (Table 2.5, Figure 2.6B). All populations tested were from Allegan county, as Palmer amaranth incidence is predominantly in the southwest region of Michigan. Five of the 21 field collections of waterhemp had more than five EPSPS copies which we consider resistant (Table 2.5, Figure 2.6B), varying between one to eight EPSPS copies. Glyphosate-resistant waterhemp individuals were primarily found in Allegan county as well. DISCUSSION ALS sequencing SNPs that confer resistance to ALS-inhibitors were found in most greenhouse grown accessions and many of the field collections for Palmer amaranth, waterhemp, common ragweed, and horseweed. The frequency and nature of these SNPs vary from species to species and accession to accession. Overall, mutations at the Pro197 and Trp574 positions predominated all others, however rare mutations at Ala205 and Asp376 were also detected in some individuals. Populations that had these rare mutations generally had another SNP as well, with Ala205 and Asp376 being less frequent. There are biological variations regarding the phenotype that each allele results in different species; however, having several SNPs in a population may result in a greater evolutionary advantage if several ALS chemistries are being used as some may be favored by certain chemistries over others. Mutations at Pro197 are known to confer high-level resistance (greater than 10-fold) to sulfonylurea (Guttieri et al., 1992), pyrithiobac-sodium (pyrimidinyl benzoates), and triazolopyrimidine chemical families (Matzrafi et al., 2015; Zheng et al., 2011). Pro197Thr confers high resistance to sulfonylureas and triazolopyrimidines (greater than 10-fold) in kochia (Bassia scoparia) (Guttieri et al., 1995), but remains susceptible to imidazolinones. However, the same mutation in prickly lettuce (Lactuca serriola), confers moderate resistance (lower than 10-fold) to imidazolinones and triazolopyrimidine, and high resistance (greater than 10-fold) to sulfonylureas (Preston et al., 2006). The Ala205Val mutation is relatively unique among the plants we sequenced; however, it has been previously observed in common ragweed (Loubet et al., 2021). It has been also reported for other species, including common cocklebur (Xanthium strumarium) (Bernasconi et al., 1995), common sunflower (Helianthus annuus) (Kolkman et al., 2004), redroot pigweed (Amaranthus retroflexus) (McNaughton et al., 2005), eastern black nightshade (Solanum ptycanthum) (Ashigh & Tardif, 2009), horseweed (Matzrafi et al., 2015), and 30 annual bluegrass (Poa annua) (Brosnan et al., 2016), causing at least moderate resistance to all chemistry families. Palmer amaranth populations had a relatively unique mutation at Asp376, however, this SNP was previously reported in Kohrt et al. (2017) and Palmieri et al. (2022). Asp376Glu confers high level resistance to all ALS chemistries (imidazolinones, pyrimidinyl benzoates, sulfonylureas, triazolopyrimidines, and triazolinones) in Powell amaranth (Amaranthus powellii) according to Ashigh et al. (2009), and high levels of resistance to imidazolinones in redroot pigweed (Huang et al., 2016). The mutation Trp574Leu confers high level resistance to imidazolinone, sulfonylurea, and triazolopyrimidine chemical groups in waterhemp (Patzoldt et al., 2001). This mutation is relatively common in weeds in general, as it is reported in 41 species to date (Heap, 2023), including waterhemp (Patzoldt & Tranel, 2007), kochia (Foes et al., 1999), Palmer amaranth (Molin et al., 2016), and annual bluegrass (Poa annua) (McElroy et al., 2013). One Palmer amaranth greenhouse accession contained the mutation Ser653Asn (Figure 2.2, Tables 2.4 and 2.5). This SNP confers moderate to high level resistance to all chemical families in the ALS group (such as imidazolinones, sulfonylureas, triazolinones, and others) across narrow and broadleaf species including Palmer amaranth (Molin et al., 2016), waterhemp (Patzoldt & Tranel, 2007), and wild oat (Avena fatua) (Beckie et al., 2012); this mutation is currently reported in six species to date (Heap, 2023). In horseweed, all individuals with an ALS mutation were homozygous and furthermore, all populations were homogenously resistant or susceptible. This is in stark contrast to Palmer amaranth, waterhemp, and common ragweed, where heterozygosity was reported at 42%, 64%, and 28% respectively, with no collections being homogeneous. In fact, several of these populations still had high proportions of susceptible individuals. This is most likely due to horseweed being primarily self-pollinating while the others can or must obligately outcross. Specifically, we would like to point out the importance of manually looking at Sanger sequencing chromatograms when calling resistance SNPs, as heterozygous locations are often miscalled WT by sequence calling software, although they would still be resistant as these mutations are known to be dominant (Figure 2.3B). Misinterpretation of heterozygous loci as WT would lead to false negatives and overpredict the number of susceptible individuals from field collections. Overall, the most frequent SNPs were in the Pro197 and Trp574 positions which suggests that selection with ALS chemistry favors these mutations over others, as they provide broad spectrum ALS resistance. 31 Glyphosate resistance mechanisms in horseweed Despite horseweed being among the first weeds to evolved resistance to glyphosate (VanGessel, 2001), the molecular basis of resistance in this species is still somewhat ambiguous. Glyphosate resistance in horseweed is thought to be primary due to decreased translocation to the growing points through sequestration in the vacuole (Xe et al. 2010), however, the genetic mechanisms of this phenotype have not yet been identified (Cardinali et al., 2015; Feng et al., 2004; Koger & Reddy, 2005). Furthermore, a mutation in EPSPS at the Pro106Ser locus has also been reported in horseweed to cause resistance to glyphosate, as well as in eleven other species including moderate resistance in goosegrass (Eleusine indica) (Kaundun et al., 2008) waterhemp (Amaranthus tuberculatus (=A. rudis)) (Nandula et al., 2013), and high levels in Palmer amaranth (Dominguez-Valenzuela et al., 2017). Recently the genome of horseweed has been published, which revealed that horseweed has three copies of EPSPS, two of which seem functional, while a third seems to be incomplete and, therefore, pseudogenized (Laforest et al., 2020). Many Asteraceae have three copies due to two polyploid events in the family’s evolutionary history (Huang et al., 2016). In this project we developed EPSPS-copy-specific primers that amplify either EPSPS1 or EPSPS2 but not both simultaneously, so that resistance SNPs can be properly attributed to each of these homologs. The Pro106Ser in the EPSPS2 gene was found in four out of five greenhouse populations with only one being glyphosate-resistant without an EPSPS SNP in either EPSPS1 or EPSPS2 (Table 2.4). The Pro106 SNP in EPSPS2 has been shown to cause intermediate resistance to glyphosate in horseweed (Page et al., 2018). In contrast to the CNV resistance mechanisms in the Amaranthus species, a mutation in the Pro106 locus changes EPSPS’s interaction with glyphosate, decreasing binding. It also changes EPSPS’s affinity for its native substrate, phosphoenolpyruvate (PEP) carboxylase, sometimes causing a fitness penalty (Vila- Aiub, 2019); however, with a still unmutated copy of EPSPS (i.e. EPSPS1), it is unclear whether that would be the case in horseweed. Regardless, the EPSPS2 mutation seems to be more frequent in glyphosate-resistant horseweed populations in Michigan than previously thought and is either complimenting NTSR mechanisms previously described or possibly the sole source of resistance in some cases (Fisher et al., 2023). More work into glyphosate resistance mechanisms in horseweed are needed for robust molecular diagnostics to be viable in this species. The methods developed and optimized here for early TSR detection of resistance to ALS and EPSPS-inhibitor herbicides were proven to be robust and reliable. Our assays worked nearly 32 100% of the time, with the major limitation being the reliability of accurate Sanger sequencing reactions, which works between 93% and 99% of the time. Also, genotyping multiple individuals from a single accession can provide insights regarding the frequency of resistant alleles at the population level. Modern use of Oxford Nanopore Technology (ONT) for amplicon sequencing may reduce this unreliability severely as ONT amplicon sequencing provides hundreds or thousands of reads of single molecules that are very long. Even though ONT is error prone, they are random and through consensus it is easy to access the true sequence at any locus. The primary drawback with target site mutation sequencing ALS and EPSPS2 is that the results can only prove that individuals are resistant in the case where a SNP is found; however, the lack of a target site SNP does not guarantee that the plant is susceptible, as NTSR mechanisms or unidentified mechanisms could contribute to herbicide resistance. Therefore, target site molecular diagnostics should still be complimented with traditional diagnostics, or non-molecular, quick tests, such as leaf-disc-assays (Wu et al. 2021), mentioned earlier to access whether a population is herbicide susceptible or resistant. EPSPS CNV in Palmer and waterhemp Glyphosate resistance in waterhemp and Palmer amaranth are commonly attributed to increased EPSPS copy number, which causes an overexpression of the EPSPS protein so that the protein pool becomes greater than reasonably inhibited by glyphosate (Gaines et al., 2010; Lorentz et al., 2014). The EPSPS CNV is easily diagnosable using standard genomic qPCR methodologies that has been previously described for both species. The estimation of EPSPS CNV was determined through the 2–∆Ct method (Livak & Schmittgen, 2001). Our results showed that the amplification of the EPSPS gene in our populations varied between 1 to 160 in Palmer amaranth and 1 to 8 in waterhemp populations (Table 2.3, Figure 2.5C, Figure 2.9A-D); similar to findings by Gaines et al. (2010) for Palmer amaranth, and Chatham et al. (2015) for waterhemp. In their work, Gaines et al. (2010) and Chatham et al. (2015) suggest a baseline of 30 EPSPS copies to prescribe resistance in Palmer amaranth and four copies for resistance in waterhemp respectively; however, more work should be done to identify exactly how many copies is needed for each species to survive the recommended field dose of glyphosate. In kochia, another EPSPS-CNV glyphosate- resistant species, more than four copies can confer field-level resistance (Gaines et al., 2016). Therefore, in this work any individual with copy number equal or greater than four was considered resistant or at least moderately resistant. With this as our baseline, four out of five greenhouse 33 Palmer amaranth populations and three out of five waterhemp populations were classified as resistant. In the field, two of three Palmer amaranth individuals and six of twenty-one waterhemp individuals showed resistance through EPSPS CNV. Several housekeeping genes have been proposed for the genomic qPCRs for EPSPS-CNV assays. Originally, others have used ALS but this practice has been questioned as ALS is an herbicide target and theoretically may become a CNV as well (Gaines et al., 2010). To this end, others have used housekeeping genes like β-tubulin as they may be more stable in copy number (Godar et al., 2015). In our work, we compared ALS and β-tubulin as housekeeping genes and we rejected β-tubulin as a control gene for qPCR assays, as it underestimates the actual CNV of the tested species. β-tubulin is part of a multi-gene family and the primers previously reported bind to at least two of these genes and therefore underestimates the number of amplified copies of EPSPS by half. ALS performed as expected and was a stable single-copy gene in our plants, therefore, provide an accurate estimation on the EPSPS CNV. CONCLUSIONS Molecular diagnostics can be an effective tool for the development of integrated pest management plans, especially when controlling herbicide resistance is critical. They allow for rapid and empirical detection of resistance mechanisms and can support real-time management changes within the growing season. One of the benefits of the SNPs sequencing using molecular diagnostics for the farmers is the timeframe reduction for ALS and EPSPS-resistance detection. By performing molecular diagnostics, the drastic reduction of time allows farmers to act in the same cropping season, potentially avoiding further herbicide resistance selection in their areas. Additionally, the low costs attributed to detecting herbicide resistance early in the cropping season is another advantage of molecular diagnostics as compared with traditional phenotyping assays. Farmers may be able to avoid spraying herbicides that are fated to fail in controlling target weeds. However, molecular diagnostics require large amounts of knowledge about dominant resistance mechanisms for a given weed and herbicide combination as well as the expertise to develop, optimize, run, and interpret the results. In this work, we present a tested and robust set of PCR- based assays for detecting TSR mechanisms for ALS and EPSPS inhibiting chemistries in the major broadleaf weeds of the upper Midwest, as well as detailed methodology for others to adopt these assays in their resistance surveys. In some cases, these assays were previously developed but were redesigned here to be robust, working on nearly all individuals in the greenhouse or field, and in other cases we designed the assays de novo. 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R., Singh, S., Davis, V. M., Tranel, P. J., Weller, S. C., & Johnson, W. G. (2011). Cross-resistance of horseweed (Conyza canadensis) populations with three different ALS mutations. Pest Management Science, 67(12), 1486–1492. https://doi.org/10.1002/ps.2190 40 APPENDIX Figure 2.1. Primers (forward, middle, and reverse) covering ALS positions known to confer herbicide resistance. A middle primer was used to sequence the Palmer amaranth fragment. Horseweed primers skip the Ala122, Ser653, and Gly654 positions, while waterhemp primers skip the Ala122. 41 Figure 2.2. Frequency of ALS mutations in horseweed (ERICA), common ragweed (AMBEL), waterhemp (AMATU), and Palmer amaranth (AMAPA). Five greenhouse accessions of each species had 10 plants sequenced. Field plants were collected in soybean and corn fields in Michigan to address the efficiency of the molecular markers tested in the greenhouse accessions. 42 Figure 2.3. Chroma of all ALS mutations found in accessions of four weed species, Palmer amaranth (A), waterhemp (B), common ragweed (C), and horseweed (D) resistant and susceptible. 43 Figure 2.4. Chroma of EPSPS positions known to confer herbicide resistance in EPSPS1 and EPSPS2 from resistant and susceptible accessions of horseweed (Conyza canadensis). There is the mutation Pro106Ser in EPSPS2. 44 Figure 2.5. EPSPS copy number variation analysis for three Palmer amaranth (A) and waterhemp (B) accessions using two different housekeeping genes, ALS and β-TUB. EPSPS copy number variation analysis in five plants of five Palmer amaranth (C) and waterhemp (D) greenhouse accessions using housekeeping ALS gene. 45 Figure 2.6. Michigan State map showing the location of field collections of four weed species used to validate the molecular markers. (A) Collections showing ALS-inhibitors resistance or susceptibility based on mutations detected with molecular markers. (B) Collections of Palmer amaranth and waterhemp showing glyphosate resistance or susceptibility based on EPSPS copy number variation. 46 Figure 2.7. Alignment of translated EPSPS1 and EPSPS2 genes from horseweed showing the identity between both. Amino acids in red refer to known positions where mutations confer glyphosate resistance. 47 Figure 2.8. Agarose gel showing specific fragment size produced by EPSPS1 and EPSPS2 primer pairs used to sequence and address the mutations. 48 Figure 2.9. EPSPS and ALS qPCR amplification curves. (A) Amaranthus palmeri S. Watson individual without EPSPS CNV; (B) Amaranthus palmeri S. Watson individual with EPSPS CNV; (C) Amaranthus tuberculatus (Moq.) Sauer individual without EPSPS CNV; (D) Amaranthus tuberculatus (Moq.) Sauer individual with EPSPS CNV. A C B D 49 Table 2.1. Known mutations in the ALS and EPSPS genes conferring ALS- and EPSPS-inhibitors herbicide resistance in horseweed, common ragweed, Palmer amaranth, and waterhemp. Species Mutation Common ragweed Palmer amaranth Waterhemp Horseweed Ala122 Pro197 Ala205 Phe206 Asp376 Arg377 Trp574 Ser653 Gly654 No Yes Yes No No No Yes No No ALS Yes Yes Yes No Yes No Yes Yes No No No No No No No Yes Yes No No Yes Yes No Yes No Yes No No (Loubet et al., (Küpper et al., 2017; References 2021; Rousonelos Palmieri et al., 2022; et al., 2012) Singh et al., 2019) (Patzoldt & (Matzrafi et al., 2015; Tranel, 2007) Zheng et al., 2011) Thr102 Ala103 Pro106 No No No EPSPS No No Yes No No Yes No No Yes References (Kaundun et al., 2019) (Nandula et al., 2013) (Beres et al., 2020) 50 Table 2.2. Molecular markers and PCR conditions utilized to sequence ALS gene from four weed species, horseweed, common ragweed, Palmer amaranth, and waterhemp, and EPSPS gene from horseweed. Species Primer Sequence (5' - 3') Fragment Annealing Extension References size (bp) temperature (°C) time (min) Common Forward AGCTTTGGAACGTGAAGGC ragweed Reverse ATTTCGTTCTGCCATCGCC 1677 ALS Palmer amaranth Waterhemp Horseweed Forward TCCTCGCCGCCCTCTTCAAATC Middle AGGTTGCCTAAACCCAC 1990 Reverse CAGCTAAACGAGAGAACGGCCAG Forward GGTTTTCGCTGCTGAAGG Reverse AGCCCTTCTTCCATCACC Forward AGATCCACCAAGCTCTCACG Reverse CTTCGGCAAACTTCAACATGTTTGG EPSPS1 Horseweed Forward TCAGAGCAACATTCGAGGAGTC Reverse CAATTGGTTAAAGGTAGAAGGAGG EPSPS2 Horseweed Forward GGACTACTGTTGTAGACAACTTG 986 Reverse GTGGGCAGTTTGTACCGAGA 51 1584 1400 551 56 56 60 60 60 54 54 57 57 62 62 62 62 (Whaley et al., 2006) 1:30 2:00 1:45 1:45 1:00 1:00 Table 2.3. EPSPS, ALS, and β-TUB molecular markers utilized to address EPSPS copy number variation genes in Palmer amaranth, and waterhemp. Primer Primer sequence (5' to 3') Fragment size (bp) temperature (°C) Annealing References Forward ATGTTGGACGCTCTCAGAACTCTTGGT Reverse TGAATTTCCTCCAGCAACGGCAA Forward GCTGCTGAAGGCTACGCT Reverse GCGGGACTGAGTCAAGAAGTG EPSPS 195 ALS 118 β-TUB Forward ATGTGGGATGCCAAGAACATGATGTG Reverse TCCACTCCACAAAGTAGGAAGAGTTCT 157 60 60 60 60 60 60 (Gaines et al., 2010) (Gaines et al., 2010) (Godar et al., 2015) 52 Table 2.4. Summary of molecular markers diagnostic for five greenhouse accession of four weed species targeting ALS and EPSPS genes. Species Population No. Horseweed Horseweed Horseweed Horseweed Horseweed Palmer amaranth Palmer amaranth Palmer amaranth Palmer amaranth Palmer amaranth Waterhemp Waterhemp Waterhemp Waterhemp Waterhemp Common ragweed Common ragweed Common ragweed Common ragweed 1 2 3 4 5 1 2 3 4 5 1 2 3 4 5 1 2 3 4 Sulfonylurea resistant? No No Yes Yes Yes No Glyphosate Resistant? Yes Yes Yes Yes Yes No Yes No Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes No No Yes Yes Yes No No No No 53 ALS Mutation No mutation+ No mutation+ Pro197Ser+ Pro197Ser+ Pro197Thr+ No mutation+ Pro197Ile* Trp574Leu* Ser653Asn* Pro197Leu* Trp574Leu* Pro197Ile* Pro197Thr* Trp574Leu*+ Pro197Ile/Thr* Pro197Thr*+ Asp376Glu* Trp574Leu+* Pro197Thr+* Trp574Leu+* Pro197Ser* Trp574Leu* Trp574Leu+* Trp574Leu+* No mutation+ No mutation+ Trp574Leu+* Trp574Leu+* EPSPS Mutation/CNV Pro106Ser+ Pro106Ser+ Pro106Ser+ Pro106Ser+ No mutation+ 1-2 Michigan County Shiawassee Kalamazoo Branch Montcalm Cass Jackson, TN 40-120 Hillsdale 40-160 Mason 55-95 Ottawa 20-100 Barry 1 1 1-7 1-5 1-7 - - - - St. Clair Sanilac Sanilac Lenawee - Montcalm Ingham Shiawassee Clinton Table 2.4. (cont’d) Common ragweed 5 Yes No - Shiawassee Pro197Leu* Pro197Ser* Ala205Val* Trp574Leu+* 54 Table 2.5. Summary of molecular markers diagnostic for field collections of four weed species targeting ALS and EPSPS genes. Species Horseweed Horseweed Horseweed Horseweed Horseweed Horseweed Horseweed Horseweed Horseweed Horseweed Horseweed Horseweed Horseweed Horseweed Palmer amaranth Palmer amaranth Palmer amaranth Waterhemp Waterhemp Waterhemp Waterhemp Waterhemp Waterhemp Waterhemp Waterhemp Waterhemp Waterhemp Field accession County ALS Mutation EPSPS 1 2 3 4 5 6 7 8 9 10 11 12 13 14 1 2 3 1 2 3 4 5 6 7 8 9 10 Allegan Allegan Allegan Allegan Allegan Clinton No mutation+ Pro197Ser+ Pro197Leu+ No mutation+ Pro197Leu+ Pro197Ser+ Montcalm No mutation+ Gratiot Gratiot Pro197Ser+ Pro197Ser+ Kalamazoo No mutation+ Kalamazoo Pro197Leu+ St. Joseph Pro197Leu+ St. Joseph No mutation+ St. Joseph No mutation+ Allegan Allegan Allegan Trp574Leu+ No mutation+ Trp574Leu* Washtenaw No mutation+ No mutation+ -* -* No mutation+ No mutation+ Ser653Asn* Trp574Leu* Trp574Leu* No mutation+ Clinton Gratiot Gratiot Allegan Allegan Allegan Allegan Allegan Allegan 55 - - - - - - - - - - - - - - 1.53 copies 7.10 copies 21.62 copies 2.6 copies 2.7 copies # # 4.2 copies 5.6 copies 7.3 copies 3.8 copies 1.5 copies 1.4 copies Table 2.5. (cont’d) Waterhemp Waterhemp Waterhemp Waterhemp Waterhemp Waterhemp Waterhemp Waterhemp Waterhemp Waterhemp Waterhemp Common Ragweed Common Ragweed Common Ragweed Common Ragweed Common Ragweed Common Ragweed Common Ragweed Common Ragweed Common Ragweed Common Ragweed Common Ragweed Common Ragweed Common Ragweed Common Ragweed Common Ragweed Common Ragweed Common Ragweed Common Ragweed Common Ragweed 11 12 13 14 15 16 17 18 19 20 21 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 8.4 copies 1.6 copies 1.6 copies 2.5 copies 6.7 copies 1.4 copies 1.6 copies 2.5 copies 6.7 copies 1.4 copies 0.9 copies Allegan Allegan Allegan No mutation+ No mutation+ No mutation+ Montcalm Trp574Leu+ Montcalm Ser653Asn+ Montcalm No mutation+ Ingham Ingham No mutation+ No mutation+ St. Joseph No mutation+ St. Joseph No mutation+ St. Joseph No mutation+ Allegan Allegan Allegan Allegan Allegan Allegan Allegan Allegan Allegan Ingham No mutation+ Trp574Leu+ No mutation+ Trp574Leu+ Trp574Leu+ No mutation+ No mutation+ No mutation+ No mutation+ No mutation+ St. Joseph No mutation+ St. Joseph No mutation+ St. Joseph No mutation+ St. Joseph No mutation+ St. Joseph Ala205Val* St. Joseph No mutation+ St. Joseph No mutation+ St. Joseph No mutation+ St. Joseph No mutation+ 56 CHAPTER III: AGRONOMIC PREDICTORS OF HERBICIDE-RESISTANCE FOR PROACTIVE MANAGEMENT IN MICHIGAN ABSTRACT Herbicide-resistant weeds threaten modern agriculture production. In Michigan, horseweed (Erigeron canadensis L.) is among the most troublesome weeds, and glyphosate was widely used to control E. canadensis. Due to extreme selection pressure imposed by heavy glyphosate usage, glyphosate-resistant E. canadensis is widespread. New technologies to control resistant E. canadensis are being introduced in the form of multiple herbicide-resistance traits into glyphosate- resistant soybean (e.g. dicamba or 2,4-D choline). These new soybean varieties will likely increase the use of 2,4-D and dicamba thus increasing the resistance selection pressure in E. canadensis. Predicting agronomic factors that drive herbicide-resistance evolution can serve as an effective proactive tool to advise practitioners to modify management strategies. Therefore, the objectives of this study are: 1) conduct dose-response assays to assess current resistance spectrum of E. canadensis collected in Michigan and 2) predict and determine the main factors in row crop production that contribute to resistance evolution in these accessions. Dose-response assays were conducted to evaluate the herbicide sensitivity spectrum to glyphosate, dicamba, and 2,4-D in 20 E. canadensis accessions collected from eight Michigan counties. Out of the 20 accessions, 60% were resistant to glyphosate, 35% to 2,4-D, and 20% to dicamba. Pearson’s correlation coefficient of dose-response values were positive in all comparisons (2,4-D-dicamba, r = 0.35; dicamba- glyphosate, r = 0.15; 2,4-D-glyphosate, r = 0.21). Dose-response data were integrated in odds ratio analyses to access the influence that previous management history had on the occurrence of resistance. Out of the significant pairwise comparisons, 44% were related to crop rotation frequency, 33% to previous herbicide-resistance status, and 22% to location collected. Results highlight that growers have the ability to proactively manage herbicide-resistance evolution progression of E. canadensis in Michigan by adopting integrated weed management techniques to slow successive selection events that occur in low diversity management systems. KEYWORDS: Herbicide-resistance evolution, multiple resistance, Erigeron canadensis, auxinic herbicides, glyphosate, resistance spectrum 57 INTRODUCTION Horseweed (Erigeron canadensis L.) is an agriculturally important weed worldwide (Holm et al., 1997). In the United States, it is found in annual and perennial crops, such as soybean (Glycine max (L.) Merr.), corn (Zea mays L.), cotton (Gossypium hirsutum L.), orchards, and vineyards (Moretti et al., 2016; Steckel & Gwathmey, 2009). Erigeron canadensis competition can reduce yield by 32-69% in corn (Ford et al., 2014; Soltani et al., 2021) and 40-90% in soybean (Agostinetto et al., 2018; Trezzi et al., 2013; Weaver, 2001). Erigeron canadensis is difficult to control due to numerous factors. First, E. canadensis is the most widespread glyphosate-resistant weed in the world and it is also resistant to other common sites of action (SOA) such as acetolactate synthase (ALS)-inhibitors (Heap, 2014). Second, E. canadensis has an extremely aggressive root system and plants can grow up to 2.30 m tall (Bhowmik & Bekech, 1993; Weaver, 2001). Third, E. canadensis is a highly prolific seed producer; a single plant can produce up to 200,000 windblown seeds per year (Bhowmik & Bekech, 1993; Weaver, 2001). Wind-mediated seeds can travel long-distances and infest a wide variety of different crops, even if they are relatively distant (Shields et al., 2006), which helps to explain the cosmopolitan nature of this species (Heap, 2014; Holm et al., 1997). Furthermore, the large amount of seed produced may also account for high amounts of genetic diversity both regionally and internationally despite E. canadensis being a primarily self-pollinating species (Gaines et al., 2020; Powles, 2008). Fourth, E. canadensis can emerge in either the fall or spring, making it both a summer and winter annual, depending on environmental conditions (Schramski et al., 2021). Taken together, these traits make E. canadensis one of the most troublesome weed species. Glyphosate has been widely used to control E. canadensis in both the fall and spring as part of burndown herbicide programs as well as in postemergence in-season applications to glyphosate-resistant crops (i.e. Roundup ReadyTM). Glyphosate-resistant E. canadensis was reported in the early 2000s, shortly after the widespread adoption of glyphosate-resistant crops, and is among the first glyphosate-resistant species identified (VanGessel, 2001). Due to the extreme selection pressure imposed by heavy glyphosate usage, glyphosate-resistant E. canadensis became frequent and has rapidly spread across the US, limiting the effective use of this chemistry and therefore glyphosate-resistant crop technology (Davis et al., 2008; Flessner et al., 2015; Heap, 2023; Koger et al., 2004). Erigeron canadensis accessions resistant to glyphosate, ALS, photosystem I (PSI), and photosystem II (PSII) inhibitors have all been identified in the United 58 States (Heap, 2023; Moretti et al., 2021). Several of these accessions are actually resistant to two SOA, termed multiple resistant. To date, multiple resistant E. canadensis accessions include resistance to: glyphosate and ALS, glyphosate and PSI, and triazine and ALS inhibitors (Byker et al., 2013; Davis et al., 2009; Matzrafi et al., 2015; Moretti et al., 2013). Specifically in Michigan, glyphosate-resistant E. canadensis accessions were first reported in 2007 in Mason county and have since become widespread, especially in combination with ALS inhibitors (MSU-PPD, 2024). New technologies to control resistant accessions of E. canadensis are currently being introduced in the form of multiple herbicide-resistance traits into glyphosate-resistant crops. Specifically, in soybean, new varieties include: Roundup Ready 2 Xtend® (glyphosate and dicamba-resistant), Roundup Ready 2 XtendFlex® (glyphosate, dicamba, and glufosinate resistant), Enlist E3™ (2,4-D choline, glyphosate, and glufosinate resistant), and LibertyLink GT27® (glyphosate, glufosinate, and isoxaflutole resistant). Roundup Ready 2 Xtend® was first commercially available in 2017 while Enlist E3™ was first available in 2020 (Dodson, 2022). The introduction of these multiple herbicide-resistant soybean varieties primarily enables farmers to apply auxin mimicking herbicides (group 4) after soybean emergence. These new soybean varieties will likely increase the use of 2,4-D or dicamba for in-season weed control in soybean in addition to applications already happening in corn which is naturally tolerant to these chemistries. This recurrent use of auxinic herbicides will increase the selection pressure for auxin resistance in E. canadensis. Due to the insurgence of herbicide-resistant E. canadensis in the United States, especially in a relatively small timeframe (Holm et al., 1997; VanGessel, 2001), and considering new crop- resistant technologies, we are in critical need of information pertaining to the main contributing factors that select for resistance and how growers can alter use practices to delay resistance evolution. One approach is to use epidemiology theory to proactively - not reactively – predict and manage herbicide-resistance evolution (Comont et al., 2019; Comont & Neve, 2021). By epidemiologically understanding the main drivers of herbicide-resistance evolution, we could educate growers and the agricultural industry as early as possible on how to avoid herbicide- resistance evolution and to preserve the use of group 4 resistant crops (Evans et al., 2016). Therefore, the objectives of this study are: 1) conduct dose-response assays to assess current resistance spectrum of E. canadensis accessions collected in Michigan and 2) predict and 59 determine the main factors in row crop production that contribute to herbicide-resistance evolution in these accessions. MATERIALS AND METHODS Dose-Response Assay Greenhouse dose-response experiments were conducted from August 2021 to September 2023 at Michigan State University in East Lansing, MI, USA. The experimental design consisted of a randomized complete block design with four replications repeated once. We utilized 20 E. canadensis accessions in this study collected from eight counties in Michigan (Table 3.1). Seeds were hand threshed from the plant material and cleaned. Once the seeds were cleaned, the accessions were planted in flats containing potting media and placed in the greenhouse (16h light at 26 C; 8h dark at 18 C). At the presence of two true leaves, each plant was transplanted into a 12 by 12 cm pot (Shuttle Pot®, East Jordan Plastics, Inc.) containing the same media. When transplants reached approximately 12 cm in diameter the below herbicide treatments were made. Plants were watered daily and fertilizer (NPK 15-07-25, ICL Specialty Fertilizers) was applied weekly. The dose-response experiment consisted of nine rates of the following herbicides: glyphosate (Roundup PowerMAX® 3, 575 g ae L-1, Bayer), dicamba (XtendiMax®, 350 g ae L-1, Bayer), and 2,4-D choline (Enlist One™, 455 g ae L-1, Corteva Agriscience) (Table 3.1). For glyphosate the dose treatments were: 0, 0.25, 0.5, 1, 2, 4, 8, 16, and 32 times the recommended labeled rate of 1.26 kg ae ha-1. For dicamba and 2,4-D the dose treatments were: 0, 0.016, 0.031, 0.062, 0.125, 0.25, 0.33, 0.5, and 1 times the recommended labeled rate of 0.56 kg ae ha-1 and 1.07 kg ae ha-1, respectively. Additionally, 2% v/v dry ammonium sulfate was included with glyphosate and 2,4-D treatments. Herbicide treatments were applied using a single-track sprayer (Generation 4, DeVries Manufacturing, Inc., Hollandale, MN) equipped with an 8001E TeeJet flat-fan nozzle (TeeJet Technologies, Wheaton, IL) calibrated to deliver 187 L ha-1 at 193 kPa of pressure. Visual injury ratings were performed in 7, 14, and 21 days after treatment (DAT). Aboveground dry biomass was obtained 21 DAT. Plants were cut at the soil surface and dried at 66 C for 7 days before dry biomass was recorded. Statistical Analysis Three and four-parameter log-logistic models as well as a three-parameter Weibull model were fit to the data to determine the pattern of biomass reduction per herbicide and accession 60 (Equations 1, 2 and 3), where the independent variable was herbicide rate, and the dependent variable was dry biomass using the DRC package in R (Ritz et al., 2015). Model fit was assessed using the DRC modelFit function in R, following the methods outlined in Knezevic et al. (2007). Models that have p-values >0.05 were chosen for the analysis with a few exceptions in which models that yielded the smallest standard error values were chosen for analysis (Table 3.2). 𝑓(𝑥) = ! "#[ ! (#$%&)( ] [1] 𝑓(𝑥) = 𝑑 + (’(!) "#[ ! (#$%&)( [2] ] 𝑓( 𝑥 ∣ 𝑐, 𝜆, 𝑘 ) = 1 − 𝑒 (!*+), * - + [3] For all the equations, f(x) represents the effect of the herbicide at a given dose x, a is the response level when the dose x is the highest, d is the response level when the dose x is the lowest, ED50 is the dose causing 50% biomass reduction, and b is Hill's slope, which is how steep the dose- response curve is (Muse et al., 2021). For the Weibull function, f (x∣c,λ,k) is the probability that the ED50 is either less than or equal to a given dose x, c is the location parameter, λ is the scale parameter, and k is the shape parameter (Hallinan, 1993). Accessions with ED50 values greater than the glyphosate recommended field use rate were considered resistant and lower than the field use rate were considered susceptible for subsequent analysis. Accessions with ED50 values greater than dicamba and 2,4-D recommended field use rates were considered reduced sensitivity and lower than field use rate were considered susceptible for subsequent analysis. To investigate the association amongst ED50 values from different herbicides, correlation analysis was performed using Pearson's correlation coefficient (Equation 4) using the Hmisc package in R (Harrell Jr, 2023). 𝑟 = (, ∑ / 0)((∑ /)∗( ∑ 0) 2[, ∑ /. ( ( ∑ /). ] ⋅[( , ∑ 0. ((∑ 0).] [4] 61 For this equation, r represents the correlation coefficient, x and y represent the individual data points for ED50 values to be correlated, and x2 and y2 represent the average of the respective sets of ED50 values. Dose-response data were further analyzed using logistic regression to access the influence previous management history had on the occurrence of resistant accessions. Odds ratio (OR) analysis was performed to verify the strength and direction of association between two variables. For this study, odds ratio analyses were performed using the herbicide ED50 values (glyphosate, dicamba, and 2,4-D) generated in the dose-response assays in objective 1, location the accession was collected, previous herbicide-resistance screening, and eight-year crop rotation history in the location the accessions were collected (Table 3.3). Michigan State University Plant and Pest Diagnostics previously evaluated these accessions for herbicide response (screened with one and four times the recommend field use rate) to glyphosate, 2,4-D amine, and cloransulam (MSU-PPD, 2024). Crop rotation data from 2015-2022 were collected from the USDA-NASS Cropland Data Layer using the CroplandCROS web application (USDA, 2022). Once crop rotation information was extracted the frequency of a particular crop grown in that rotation was calculated for each rotation and categorized as: high (greater than 50% of the years contained that crop), medium (20- 50% of the years contained that crop), and low (less than 20% of the years contained that crop). RESULTS AND DISCUSSION Dose-Response Assay - Glyphosate Out of the 20 E. canadensis accessions evaluated in this study, 12 (60%) were resistant to glyphosate (i.e. survived the recommended field use rate of 1.26 kg ae ha-1) (Table 3.1). Susceptible accession ED50 values varied substantially, ranging between <0.32 kg ae ha-1 (the lowest dose applied) to 1.15 kg ae ha-1 (~0.9 times the field use rate). Half of the susceptible accessions were collected from separate specific locations but within Ingham County, while the remaining accessions were distributed across Montcalm, Isabella, and Delta counties. Resistant accession ED50 values also varied widely; ranging between 1.85 kg ae ha-1 (1.5 times the field use rate) to >40.32 kg ae ha-1 (the highest rate applied). The accessions with ED50 values >40.32 kg ae ha-1 were collected from Macomb and Montcalm counties. Interestingly, out of the seven accessions collected in Montcalm country, six were resistant to glyphosate, with ED50 values ranging from 2.79 to >40.32 kg ae ha-1. 62 Adopting Roundup Ready® (i.e. glyphosate-resistant) soybean simplified weed management, was economical, and saved growers multiple passes through the field for weed management. The adoption rate of Roundup Ready® soybean increased dramatically since introduction in 1996, reaching nearly 90% of acreage in the United States by 2008 (Dodson, 2022). Michigan has followed suit, with 93% of soybean and 92% of corn hectarage being Roundup Ready® (USDA, 2023). Annual glyphosate usage in Michigan is approximately 8.06 and 6.43 million liters in soybean and corn, respectively. In the short term, this single SOA weed control tactic allowed for higher yields with greatly reduced cost (Duke & Powles, 2009); however, it also led to successive selection events which in turn selected for widespread resistance in many troublesome weed species, including E. canadensis (Green, 2007). Perhaps unsurprisingly then, from our initial dose-response results we observed that Michigan counties that are the largest producers of corn and soybean (Table 3.3) also have the highest level of glyphosate resistance (Table 3.1). Dose-Response- 2,4-D and Dicamba Out of the 20 accessions screened in our study, 7 (35%) had reduced sensitivity to 2,4-D (i.e. survived the recommended field use rate of 1.07 kg ae ha-1) and 4 (20%) had reduced sensitivity to dicamba (i.e. survived the recommended field use rate of 0.56 kg ae ha-1) (Table 3.1). These populations were considered as having ‘reduced sensitivity’ to 2,4-D and dicamba as they survived the highest dose applied; however, it is unclear since we did not apply a dose greater than the field use rate if they would be resistant in an agronomic setting. Overall, ED50 values for 2,4- D and dicamba varied widely across all 20 accessions, ranging between less than the lowest dose applied (<0.02 kg ae ha-1 and <0.01 kg ae ha-1for 2,4-D and dicamba, respectively) to the recommended field use rate (1.07 kg ae ha-1 and 0.56 kg ae ha-1 for 2,4-D and dicamba, respectively). Susceptible accessions for 2,4-D were found in all counties screened, except for Macomb and Cass, and in all counties for dicamba. Accessions with reduced sensitivity to 2,4-D were collected from Cass (1 accession), Ingham (1 accession), Isabella (1 accession), Macomb (1 accession), and Montcalm (3 accessions) counties, while accessions with reduced sensitivity to dicamba were collected from Ingham (1 accession), Isabella (1 accession), and Montcalm (2 accessions) counties. To combat the rise in glyphosate resistance, agricultural companies have recently developed and released soybean varieties, Xtend/XtendFlex® and Enlist E3™, that are resistant to 63 the auxinic herbicides dicamba or 2,4-D, respectively (Skelton et al., 2017). We screened our accessions of E. canadensis with 2,4-D and dicamba in an attempt to understand baseline sensitivity in this species in Michigan before these technologies are widely adopted. Our results show that in counties with high frequency of glyphosate-resistant E. canadensis we also see a corresponding decrease in auxinic herbicide sensitivity. Perhaps unsurprisingly, we see this pattern the most in Michigan counties that are the largest producers of corn and soybean (USDA, 2024). For instance, 45% of all accessions with reduced sensitivity to auxin herbicides were collected from Montcalm County (Table 3.1), which is the 22nd producer of corn and 26th in soybean out of 83 counties in Michigan (USDA, 2024). Auxin mimicking herbicides have been extensively used in corn for a long time due to its natural tolerance, therefore it is possible usage in corn started the selection process for auxinic resistance in E. canadensis that has the potential to be exacerbated by the future increased usage of auxinic herbicides in soybean. Dose-Response- Correlation Overall, 30% of collected accessions are resistant or have reduced sensitivity to two or more of the herbicides tested. Amongst these multiple resistant populations, five are resistant to glyphosate and 2,4-D (Cass, Macomb, and Montcalm counties), two are resistant to glyphosate and dicamba (Montcalm county), and three have reduced sensitivity to both 2,4-D and dicamba (Ingham and Montcalm counties) (Table 3.1). Furthermore, two of collected accessions are resistant to all three herbicides assayed (Montcalm county) while five are susceptible to all three herbicides tested (Delta, Ingham, and Montcalm counties). To investigate the relationship between herbicide response to each SOA tested, Pearson’s correlation analysis amongst ED50 values was performed. Pearson’s correlation coefficient (r) ranges from -1 to 1 (negative and positive correlation, respectively), where a value of: 0 indicates no, 0< r <±0.20 weak, ±0.20< r <±0.40 moderate, ±0.40< r <±0.80 strong, and ±0.80< r <±1.00 very strong correlation (Pearson, 1895). When comparing ED50 values amongst accessions treated with the auxinic herbicides 2,4- D and dicamba, Pearson’s correlation coefficient was moderately positive, r = 0.35, indicating that increases in the ED50 for 2,4-D corresponds to increases in the ED50 value for dicamba (Figure 1). Furthermore, when comparing ED50 values amongst accessions treated with 2,4-D and glyphosate, Pearson’s correlation coefficient was also moderately positive, r = 0.21, indicating glyphosate and 2,4-D resistance are positively correlated as well (Figure 1). Finally, when comparing ED50 values 64 amongst accessions treated with dicamba and glyphosate, Pearson’s correlation coefficient was weakly positive, r = 0.15 (Figure 1). The moderately positive Pearson's correlation coefficient between dicamba and 2,4-D is interesting, as these herbicides are both group 4 herbicides, but are from different chemical families and have been shown to have different protein binding partners, IAA16 and IAA2, respectively (LeClere et al., 2018; Todd et al., 2020). Even though these herbicides are from different chemical families, non-target-site resistance (NTSR) mechanism(s) could be responsible for the moderate, but positive, correlation between these herbicides. Although not reported yet in E. canadensis; these NTSR mechanisms have been implied in cross-resistance for group 4 herbicides in wild radish (Raphanus raphanistrum L.) (Goggin et al., 2016). The moderate and weak correlation between glyphosate and 2,4-D and glyphosate and dicamba and glyphosate is notable. Regardless of strength, it is interesting to find a correlation between glyphosate and auxin mimicking herbicides, as these herbicides are from different SOA and chemical families. Furthermore E. canadensis is a strongly self-pollinated species and thus lacks the ability to rapidly stack multiple resistance traits in a single individual or population which is predicted in outcrossing species such as Palmer amaranth (Amaranthus palmeri S. Watson) and waterhemp (Amaranthus tuberculatus (Moq.) Sauer) (Gaines et al., 2020; Powles, 2008). These positive correlations are particularly concerning from a management perspective where growers will likely turn to Xtend/XtendFlex® and Enlist E3® technologies in an attempt to control glyphosate-resistant weeds, yet these populations seem primed to develop resistance to group 4 herbicides already via previous exposure to group 4 herbicides used in grass crops. Odds Ratio-Previous Herbicide-Resistance Dose-response data were further analyzed using logistic regression to access the influence previous management history had on the occurrence of resistant accessions. Odds ratio analyses were performed using the ED50’s generated from the dose-response assays performed in objective 1 (Table 3.1), previous herbicide-resistance screening performed at Plant and Pest Diagnostics at MSU (MSU-PPD, 2024), county the accession was collected, and crop rotation information from the location the accession was collected using the USDA-NASS Cropland Data Layer CroplandCROS web application (USDA, 2022) (Table 3.3). In total, 174 pairwise comparisons were performed for the analysis (Supplementary Table S1). 65 Amongst all combinations, nine were statistically significant (p-value <0.20, Table 3.4) (Andrade 2019). Out of the significant pairwise comparisons, 33% involved comparisons of herbicide-resistance phenotypes identified in objective 1 to different SOA previously screened (MSU-PPD, 2024). First, if an E. canadensis accession has reduced sensitivity to 2,4-D the odds the accession is glyphosate-resistant increases by 20% (OR = 0.20, p = 0.19, Table 3.4). Second, if an E. canadensis accession is resistant to cloransulam the odds the accession is glyphosate- resistant increases by 15% (OR = 0.15, p = 0.08, Table 3.4). Finally, if an E. canadensis accession has reduced sensitivity to 2,4-D the odds the accession has reduced sensitivity to dicamba increases by 8% (OR = 0.08, p = 0.03, Table 3.4). Overall, our results suggest that resistance to one herbicide is associated to resistance to another in E. canadensis, a finding that is supported by previous literature. In general, when one herbicide fails to control a weed, the primary alternative is to use a different herbicide chemical family or SOA to control those individuals, which can often lead to multiple herbicide-resistance in which accessions are resistant to herbicides with different herbicide chemical families or SOA (Beckie & Tardif, 2012). Specifically, the co-occurrence of ALS and glyphosate resistance in E. canadensis has been reported by Byker et al. (2013). Furthermore, cross-resistance has occurred in wild mustard (Sinapis arvensis L.) to three auxin mimicking herbicides from different chemical families (2,4-D, dicamba, and/or quinclorac) (Heap & Morrison, 2002). Another case reported multiple resistance in E. sumatrensis Retz. to paraquat, glyphosate, and chlorimuron (Albrecht et al. 2020). The results found in this study highlight the propensity of E. canadensis to evolve multiple resistance, especially in accessions that were already resistant to one SOA. Odds Ratio-Location The second most influential variable was location, where combinations between the counties the accessions were collected were analyzed to resistance. Specifically, glyphosate- resistant accessions were 2,400% (OR = 24.00, p = 0.04, Table 3.4) more likely to occur in Ingham County, or 1,200% (OR = 12.00, p = 0.13, Table 3.4) more likely to occur in Isabella County when glyphosate resistance was already present in the neighboring county, Montcalm (Table 3.4, Figure 2). This is not surprising as these counties have similar crop rotations: corn, soybean, and winter wheat and thus share herbicide SOAs used in those rotations (USDA, 2022). Interestingly, Isabella and Montcalm counties share a boarder, and because E. canadensis seed dispersal is wind- 66 mediated, the spread of resistance is potentially favored by the short distance between these counties. Odds Ratio-Crop Rotation Frequency The third most impactful variable was crop rotation frequency. When corn is planted between 20 to 50% of the years evaluated (medium frequency), the odds of E. canadensis having reduced dicamba sensitivity increases by 600% (OR = 6.00, p = 0.15, Table 3.4). When soybean is planted in <20% of the years evaluated (low frequency), the odds of E. canadensis having reduced 2,4-D sensitivity increases by 560% (OR = 5.60, p = 0.17, Table 3.4). When soybean is planted in >50% of the years (high frequency), the odds of E. canadensis having reduced 2,4-D sensitivity increases by 18% (OR = 0.18, p = 0.17, Table 3.4). Finally, when winter wheat is planted in <20% of years, the odds of E. canadensis having reduced dicamba sensitivity increases by 15% (OR = 0.15 p = 0.17, Table 3.4). Crop rotation dictates what herbicide SOAs are used within a particular crop and across the rotation. With the introduction of auxinic resistant soybean varieties, there is potential that this SOA will be used more frequently or even continuously in the crop rotation, especially for soybean-corn rotations (Figure 2A and B). Furthermore, using the same herbicide SOA increases the selection pressure and speed at which E. canadensis evolves resistant to those SOA (Evans et al., 2016). Specifically, the propensity of E. canadensis to evolve dicamba resistance increased in our study when corn was present at medium frequency in the rotation. Furthermore, our finding that having soybean represented at low frequency in the crop rotation leads to an increase in 2,4- D resistance is supported by the high frequency of grass crops (i.e. corn and pasture) as the main components of these low soybean rotations (Table 3.3, Figure 2). Overall, these results suggest that having a medium to high frequency of grass crops, which are naturally tolerant to auxinic herbicides, in the rotation will predispose E. canadensis to have reduced sensitivity to auxinic herbicides when they are used more frequently in the future as adoption of auxinic resistant soybean increases. This is potentially already occurring as our data found that there was a marginal increase in 2,4-D resistance in high frequency soybean rotations (Table 3.4). The epidemiological approach utilized in this study begins to elucidate the main agronomic predictors of herbicide-resistance in E. canadensis in Michigan. These predictors reiterate the importance of diverse management strategies and crop rotations to prevent future resistance evolution. Alarmingly, we are already able to find E. canadensis accessions that have reduced 67 sensitivity to 2,4-D and dicamba, therefore it is possible that the introduction of Enlist™ and Xtend® technologies may only offer short-term relief and control of glyphosate-resistant weeds (Evans et al., 2016; LeClere et al., 2018; Todd et al., 2020) if used without other non-chemical management strategies. Not coincidentally, counties in the same agroclimatic zone are prone to have similar food production systems and therefore comparable overall management strategies and resistance issues (Evans et al., 2016). Perhaps expectedly, similarity in food production and management strategies favors the evolution and spread of herbicide-resistance in E. canadensis, highlighting lack of diversity is a major factor in resistance evolution. Furthermore, in a wind dispersed species such as E. canadensis, once herbicide-resistance is established in a certain county, the proximity between counties potentially leads to the spread of herbicide-resistant accessions in neighboring counties. The epidemiological approach performed in this study focused on evaluating a medium sized data set of categorical variables that are controllable by farmers. However, other drivers may be influencing the shift towards herbicide resistance of E. canadensis in Michigan, which will require more research to explore and integrate to form robust predictions. Overall, growers have the ability to proactively manage herbicide-resistance evolution progression of E. canadensis in Michigan by adopting integrated weed management (IWM) techniques to slow successive selection events that occur in low diversity management systems. 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Field recommended labeled rates are 1.26, 0.56, and 1.07 kg ae ha-1 for glyphosate, dicamba, and 2,4-D, respectively. 73 Figure 3.2. Location and resistance phenotype of E. canadensis accessions that were collected throughout Michigan. Crop rotation data was collected from USDA-NASS Cropland Data Layer using the CroplandCROS web application from an eight year period (2015-2022, USDA, 2022) soybean (A), corn (B), winter wheat (C), potatoes (D), and pasture (E). 74 Table 3.1. Mean herbicide dose (ED50 in kg ae ha-1 ± [SE])a required for 50% biomass reduction in 20 Erigeron canadensis L. accessions collected from eight counties in Michigan. Accession location Glyphosate Dicamba 2,4-D ---------------------------- ED50 kg ae ha-1------------------------ Cass Delta Ingham Ingham Ingham Ingham Ingham Isabella Isabella Isabella Macomb Midland Montcalm Montcalm Montcalm Montcalm Montcalm Montcalm Montcalm Saginaw 1.85 (1.34) <0.32 <0.32 <0.32 <0.32 4.75 (3.27) <0.32 <0.32 1.15 (0.75) 6.53 (2.98) >40.32 3.59 (2.69) 0.38 (0.33) 2.79 (1.47) 3.76 (2.89) 2.92 (0.53) 0.02 (0.00) 0.04 (0.04) 0.01 (0.49) >0.56 0.07 (0.13) 0.03 (0.01) <0.01 0.05 (0.03) >0.56 <0.01 0.05 (0.06) 0.13 (0.08) 0.03 (0.01) 0.33 (0.13) >0.56 0.04 (0.04) 9.46 (20.28) <0.01 14.25 (20.75) 0.49 (1.01) >40.32 >0.56 28.82 (19.19) 0.06 (0.03) >1.07 0.02 (0.62) 0.11 (0.55) >1.07 0.78 (0.13) 1.03 (0.48) <0.02 >1.07 0.29 (0.24) 0.26 (0.04) >1.07 0.33 (0.17) 0.22 (0.20) >1.07 >1.07 0.02 (0.01) 0.81 (0.52) 0.48 (0.11) >1.07 <0.02 aED50 calculated using dry plant biomass harvested 21 days after treatment using the DRC package in R. Field recommended labeled rates are 1.26, 0.56, and 1.07 kg ae ha-1 for glyphosate, dicamba, and 2,4-D, respectively. 75 Table 3.2. List of statistical models used to generate mean herbicide dose (ED50 in kg ae ha-1 ± [SE]) required for 50% biomass reduction in 20 Erigeron canadensis L. accession collected from eight counties in Michigan.a Model Model Fit Accession Glyphosate Dicamba 2,4-D Glyphosate Dicamba 2,4-D ---------------Function-------------- ---------------P-value-------------- location Cass Delta Ingham Ingham Ingham Ingham Ingham Isabella Isabella Isabella Macomb LL.3 LL2.3 LL.4 W1.3 LL.3 LL.4 LL.4 LL.4 LL.3 LL.3 LL.3 LL.4 LL.3 LL.4 LL2.3 LL2.3 LL.3 LL.3 W1.4 W2.3u LL2.3 LL.4 LL.3 LL.4 LL.3 Midland LL2.3 Montcalm Montcalm Montcalm LL.4 LL.4 LL.3 Montcalm LL2.3 Montcalm Montcalm LL.4 LL.4 Montcalm LL2.4 Saginaw LL.3 LL.4 LL2.3 LL2.4 LL.4 LL.3 LL.4 LL.3 LL.3 LL.3 LL.4 LL2.3u LL.3 LL.3 LL.3 LL2.3 LL2.3 LL.4 LL2.4 LL2.3 LL.3 LL.4 LL.4 LL.3 LL.4 LL.3u LL2.4 0.99 0.15 0.98 0.03 0.06 0.93 0.73 0.26 0.79 0.64 0.99 0.11 0.60 0.04 0.14 0.79 0.88 0.45 0.84 0.94 0.42 0.31 0.29 0.08 0.89 0.17 0.26 0.32 0.06 0.65 0.98 0.14 0.23 0.91 0.73 0.99 0.75 0.64 0.79 0.42 0.007 0.48 0.96 0.38 0.61 0.09 0.71 0.99 0.84 0.83 0.11 0.03 0.95 0.14 0.54 0.99 0.84 0.55 0.33 0.29 aModels were chosen using the modelFit function in R (Knezevic et al., 2007). LL3, log logistic three-parameter model; LL3u, log logistic three-parameter model with upper limit of 1; LL2.3, log logistic type 2 three-parameter model; LL2.3u, log logistic type 2 three-parameter model with upper limit of 1; LL.4, log logistic four-parameter model; LL2.4, log logistic type 2 four- 76 Table 3.2. (cont’d) parameter model; W1.3, Weibull three-parameter model; W1.4, Weibull four-parameter model; W2.3u, Weibull type 2 three-parameter model with upper limit of 1; W2.4, Weibull type 2 four- parameter model. 77 Table 3.3. Categorical variables associated with Erigeron canadensis L. accessions used in odds ratio analysis. Accession locationa Previous Phenotypeb herbicide- Corn Soybean resistancec Winter wheat Potato Pasture ----Frequency of crop in rotation (2015-2022)d---- Cass Delta Ingham Ingham Ingham Ingham Ingham Isabella Isabella Isabella GR, DRS, ES None GS, DS, ES Cloransulam GS, DS, ES GS, DRS, ERS GS, DRS, ES GR, DRS, ES GS, DS, ES GS, DRS, ES None None None None None None High High Low High Medium High High Medium High Low High Low Medium Medium Medium High Low Low Low Low Low Low Low Low High Low Low Low Low Low Low Low Low Low Low High Low Medium Low GS, DS, ERS Cloransulam Medium High Medium Low GR, DS, ES Cloransulam Medium Macomb GR, DRS, ES Cloransulam Midland GR, DS, ES Cloransulam Montcalm GS, DS, ES Cloransulam Low High High Montcalm GR, DRS, ERS Cloransulam Medium High Low Low Low Low Low Low Medium Low High High Low Low Low Low Montcalm GR, DRS, ERS Cloransulam Medium High Medium Low Montcalm GR, DS, ES Cloransulam Medium Montcalm GR, DRS, ES Cloransulam Low Montcalm GR, DS, ERS Cloransulam Medium High High High Low Low Low Low Low Low Low Low Low High Low Low Low Low Low Low Low Montcalm GR, DRS, ERS Cloransulam Medium Low Low Low High Saginaw GR, DS, ES Cloransulam High Medium Low Low Low aCounty accession collection from in Michigan bPhenotyped through does-response assays in objective 1 of this study; G, glyphosate; D, dicamba; E, 2,4-D; R, resistant; RS, reduced sensitivity; S, susceptible. 78 Table 3.3. (cont’d) cThe Plant and Pest Diagnostics at Michigan State University previously evaluated these accessions for herbicide response (screened with one and four times the recommend field use rate) to glyphosate, 2,4-D, dicamba, and cloransulam (MSU-PPD, 2024). dCrop rotation data was collected from USDA-NASS Cropland Data Layer using the CroplandCROS web application (USDA, 2022). Once crop rotation information was extracted the frequency of a particular crop grown in that rotation was calculated for each rotation and categorized as: high (greater than 50% of the years contained that crop), medium (20-50% of the years contained that crop), and low (less than 20% of the years contained that crop). 79 Table 3.4. Results of odds ratio analysis of significant pairwise comparisons amongst categorical variables (p ≤ 0.2). General categorical variable Previous herbicide-resistancea Location (counties in MI)c Crop rotation frequencyd Comparison Odds ratio P-value 2,4-D RSb Cloransulam R 2,4-D RS Glyphosate R Montcalm VS VS VS VS Glyphosate R Glyphosate R Dicamba RS 0.20 0.15 0.08 Glyphosate R 24.00 Ingham 0.19 0.08 0.03 0.04 Glyphosate R VS Glyphosate R 12.00 0.13 Montcalm Corn M Soybean L Soybean H Winter wheat L VS VS VS VS Isabella Dicamba RS 2,4-D RS 2,4-D RS Dicamba RS 6.00 5.6 0.18 0.15 0.15 0.17 0.17 0.17 aPlant and Pest Diagnostics at Michigan State University previously evaluated these accessions for herbicide response (screened with one and four times the recommend field use rate) to glyphosate, 2,4-D, dicamba, and cloransulam (MSU-PPD, 2024). bPhenotyped through does-response assays in objective 1 of this study; R, resistant; RS, reduced sensitivity. cCounty accession collection from in Michigan dCrop rotation data was collected from USDA-NASS Cropland Data Layer using the CroplandCROS web application (USDA, 2022). Once crop rotation information was extracted the frequency of a particular crop grown in that rotation was calculated for each rotation and categorized as: high (H = greater than 50% of the years contained that crop), medium (M = 20-50% of the years contained that crop), and low (L = less than 20% of the years contained that crop) 80