Glyphosate Resistance in Horseweed

This assignment delves into the growing issue of glyphosate resistance in horseweed (Conyza canadensis). It examines various biological and ecological factors contributing to this resistance, including target-site mutations and non-target-site mechanisms. The focus is on understanding how horseweed develops resistance, its impact on weed control practices, and potential solutions for managing resistant populations. The assignment likely requires students to analyze scientific literature and research articles related to glyphosate resistance in horseweed.

The genetic basis of glyphosate resistance in the Central Valley
agricultural weed hairy fleabane (Erigeron bonariensis L.)

ABSTRACT
Herbicide resistance is the heritable ability of weeds to survive and reproduce in the presence of
herbicide doses that are lethal to the wild type of the species. One mechanism of such resistance
is non-target site reduced translocation of the herbicide, in which vacuolar sequestration prevents
the chemical from spreading around the plant. Resistance of Erigeron canadensis to glyphosate
is thought to involve this mechanism and it is believed that EPSPS and the ABC transporter
genes M10 and M11 may be responsible for this resistance. This study therefore aims at
determining through quantitative PCR and RNA-Seq if these genes provide the mechanism for
glyphosate resistance in Erigeron bonariensis, a close relative of Erigeron canadensis, or if there
are other genes responsible for the resistance observed in this species. RNA will be extracted
from the leaves of glyphosate treated and untreated individuals, collected from 10 sites in the
Central Valley and two control populations of Erigeron bonariensis, for quantitative real time
PCR and RNA-Seq analysis. Total RNA for RNA-Seq analysis will be used in cDNA library
synthesis and sequenced via Illumina HiSeq. Sequenced reads will be assembled de novo using
the software Trinity, assigned to respective genes with the pipeline HTSeq, tested for differential
expression by DESeq and functionally annotated using the NCBI nonredundant protein (Nr)
database.

INTRODUCTION
Moss (2002) defines herbicide resistance as the heritable ability of weeds to survive and
reproduce in the presence of herbicide doses that are lethal to the wild type of the species.
Herbicide resistance was first observed by an ornamental nursery owner in 1968 (Jasieniuk at al.
1996). The first recorded case of herbicide resistance was in Senecio vulgaris; seeds from the
resistant biotypes were found to resist the chemicals simazine and atrazine (Pieterse 2010). In
1974, herbicide resistance became a problem for corn growers (Gressel et al. 1982). Since then,
more than 187 species of weeds have developed resistance against various herbicides worldwide
(Pieterse 2010). The first case of herbicide resistance in California was reported in 1981 by
scientists at UC-Riverside (Holt at al. 1981) and recently, more species have also evolved
resistance to various other herbicide chemicals employed by farmers in California (Malone 2014.
Glyphosate herbicide (marketed by Monsanto as RoundUp®) contains N-
phosphonomethyl glycine and it acts against plants by hindering aromatic amino acid synthesis
(Bridges 2003). Upon application, the plant takes up glyphosate and it is remitted with other
products of photosynthesis to all parts of the plant. In susceptible plants, glyphosate hinders the
role of the plastidine enzyme 5-enolpiruvilshikimate-3-phosphate synthase (EPSPS) important in
the prechorismate step of the shikimate pathway: normally, this enzyme works by condensing
shikimate-3-phosphate and phosphoenolpyruvate into 5-enolpiruvilshikimate-3-phosphate
(EPSP) with inorganic phosphate, initiating the anabolism of aromatic amino acids (Ferreira
2008). Being unable to synthesize the amino acids phenylalanine, tryptophan, and tyrosine
eventually kills the plant (Herman and Weaver 1999). Glyphosate has become the world’s most
commonly used herbicide since its market introduction in 1974 (Baylis 2000). Several factors
have made it the most utilized herbicide globally: it has numerous ideal characteristics, including

its potency against an extensive variety of species (monocots and dicots), less harmful activity
against animals than other herbicides (glyphosate targets the enzyme EPSPS that is not found in
animals), fast inactivation in the soil, and low cost (Duke and Powles 2008). Also, it has been
commonly used in recent years as a part of reduced tillage frameworks that have numerous
environmental-based benefits and economic importance; these systems depend greatly on
herbicides to control weeds (Owen 2008; Powles 2008; Shaner 2000). With the adoption of
genetically modified glyphosate resistant crops in 1996, the already high levels of glyphosate
application increased even more (Powles & Preston 2006). The combined effects of glyphosate
over-usage in glyphosate-resistant crops and zero tillage adoption created a significantly
increased risk of evolution of glyphosate resistance (Neve at al. 2003). Herbicide resistance is
stimulated by the re-current use of herbicides with the same active chemical ingredients
(LeBaron 1991), and so inevitably, glyphosate resistance has evolved in many weeds (Powles et
al. 1998). Because of its ability to control numerous weeds and other features which are key to
farmers, such as low cost and reduced soil erosion, glyphosate remains the best option, and
therefore farmers are unwilling to return to the tillage system or older, more toxic herbicides
(Beckie 2012).
Two mechanisms that have been demonstrated to contribute to glyphosate resistance in
weed species are target-site and non-target site resistance. Target site-based resistance is a
condition where resistance evolves due to a gene mutation conferring a change to a target site
enzyme so that the herbicide fails to effectively inhibit the normal enzyme function (Powles and
Preston 2006). The mutation may involve a specific nucleotide substitution in the coding region
producing a different amino acid that results in structural, hydrophobicity or charge change in
site of the enzyme that the herbicide targets, making it less sensitive to inhibition by the

herbicide. A few weeds such as goosegrass, have evolved weak target site mutagenesis (Lee and
Ngim, 2000; Dinelli et al. 2006) of the enzyme EPSPS, via a substitution mutation that replaced
the amino acid proline with serine at position 106 (Pro106-Ser). Ng et al. (2004 & 2005) also
showed that substitution of proline by threonine (Pro106-Thr) confers resistance glyphosate
resistance to the weed goosegrass (Eleusine indica (L.) Gaertn.). The mutated EPSPS enzyme
has a low affinity for glyphosate but almost normal affinity for phosphoenol pyruvate (the
enzyme’s usual substrate); therefore the shikimate pathway can proceed normally, synthesizing
aromatic amino acids (Gaines et al. 2010).
Non-target site reduced translocation of glyphosate (Wakelin et al. 2004) prevents
glyphosate from reaching all sites of the plant. According to Claus & Brehrens’ (1976) study,
rapid and widespread glyphosate translocation is necessary to achieve high herbicide efficacy.
There is therefore a possibility that changes in its translocation may enable resistance in plants
that were initially susceptible to it. The study that unraveled this phenomenon was carried out in
rigid ryegrass (Lolium rigidum Gaud.; Lorrraine-Colwill et al. 2002), and indicated that
resistance in at least one biotype of this species was not due to EPSPS enzyme target
mutagenesis or degradation. In the same study, it was shown that there was no significant
difference between glyphosate resistance and susceptible species in EPSPS sensitivity or
expression level or in glyphosate absorption, but the pattern of its translocation was significantly
different. The researchers observed that glyphosate accumulated at the lower part of the plant
and to some extent in the roots in susceptible plants, while in resistant plants, it accumulated in
the tip of the leaves with a negligible amount translocated to the roots (Lorrraine-Colwill et al.
2002). Welkelin et al. (2004) found the same pattern of reduced glyphosate translocation when
working with four glyphosate resistant ryegrass populations in Australia.

Researchers investigating mechanisms of glyphosate resistance in other Lolium
populations have not found large differences in glyphosate translocation. Perez et al. (2004)
found no significant difference in glyphosate absorption and translocation between susceptible
and resistant Chilean Lolium plants. In an investigation in glyphosate resistance in Californian
Lolium, Simarmata et al. (2003) found significantly higher glyphosate concentration in treated
leaves of glyphosate resistant plants 2-3 days after treatment. Interestingly, these authors
observed no other significant differences in glyphosate absorption or translocation between
resistant and susceptible plants. These varying results suggest that there might be different
mechanisms responsible for glyphosate resistance in different Lolium populations. In general,
most studies observed no differences in glyphosate absorption, but its translocation to the roots
was greatly reduced (Feng et al. 2004; Koger and Reddy 2005) in resistant species. Failure of
glyphosate translocation from leaves to the roots seems to be important mechanisms that lead to
resistance in certain Lolium biotypes and biotypes of other weeds, including those in the genus
Erigeron (Conyza) (Preston 2002).
Erigeron species consist of annual or short-lived perennial plants native to the Americas
that have in the recent past become cosmopolitan and invasive weeds of many crops and arable
lands (Prieur-Richard et al. 2000). The genus is in the sunflower family (Asteraceae) and the
weed species were formerly placed in the genus Conyza before taxonomic revision ( Baldwin,
2012). Erigeron spp. are prolific seed producers: a single plant is capable of producing
thousands of viable seeds (Weaver 2001) that can be widely dispersed by wind (Shields et al.
2006), establishing themselves in areas previously uninfected.
Erigeron spp. have become very common and problematic weedy plants in agronomic
crops around the world (Weaver 2001). This is probably because they are capable of adapting to

periodically plant-free, undisturbed soil where they establish in the absence of tillage (Buhler
1992). The opportunistic nature of Erigeron in undisturbed areas makes them well suited for
becoming established in agricultural fields and the areas surrounding them and especially in no-
tillage or where tillage is minimal (Bruce and Kells 1990). Considering the fact that over the last
two decades the amount of crop hectares in conservation tillage has greatly increased (Young
2006), weeds such as Erigeron spp. are becoming a problem of great concern.
The two main species of Erigeron in California are hairy fleabane (Erigeron bonariensis
L.) and horseweed (Erigeron canadensis L.), both summer annuals. Unlike horseweed, which is
weedy across the U.S., fleabane is an agricultural problem specific to California (Shrestha 2008).
The optimal temperature for germination of fleabane ranges between 650F and 750F and the
seeds usually germinate under moderate water conditions (Karlsson and Milberg, 2007). Based
on these characteristics, conditions are ideal for fleabane germination in mid- to late fall and
winter in California’s Central Valley. Hairy fleabane has adapted to irrigated vineyard and
orchard systems as well as dry non-crop areas (Shrestha et al. 2014). Information concerning the
economic impact of fleabane on crop production is available (Pandolfo, et al, 2016).
Erigeron bonariensis have been shown to exhibit extensive glyphosate resistance in the
southern Central Valley of California (Okada et al. 2013), but the actual resistance mechanism is
still obscure, especially the dynamics that transpire at the genetic level that bring about the plant
detoxification. A number of studies have been performed on fleabane’s close relative, E.
canadensis, in an attempt to establish the presence or absence of target site mutations at codon
106 of the EPSPS gene, as well the synchronization mechanism of EPSPS enzyme
overexpression levels together with ABC transporter genes (Tani et al. 2015). However, the
presence and number of these genes and their specific roles in glyphosate resistance in fleabane

have not been established. The ABC transporter genes’ expression relationship with glyphosate
transport in the resistant biotypes needs to be examined in California fleabane, given the
importance of these genes in fleabane’s close relative horseweed (Tani et al. 2015), and the fact
that reduced translocation is the suspected mechanism of glyphosate resistance in fleabane from
other parts of the world (Ferreira et al. 2008). It is also imperative to examine if target mutations
in the EPSPS gene, or possibly an increase in gene copy number (e.g. Gaines et al. 2010), are
involved in fleabane glyphosate resistance. In addition to looking for the known target site
mutation in EPSPS (Pro106 in Lolium rigidum), it is important to find out if there are other
mutations that confer target site resistance via changes in the EPSPS enzyme itself.
P450 genes have been demonstrated to play an important role in mediating non-target
herbicide resistance. This was elucidated by affirming the relationship between P450 enzyme
activity and herbicide resistance in weeds, which suggested that this class of genes also
contributes to the difficulty with which the weeds are eliminated (Yuan et al. 2007). P450 genes
code for enzymes that can be involved in detoxification of herbicides in phase I metabolic
processes. Their expression products bring about reactions such as hydroxylations,
decarboxylations, and deaminations, among others, processes that all aim at neutralizing the
effects of a toxin in the plant body (Morant et al. 2003). The p450 enzymes have been shown to
be synchronized with phase II detoxifying enzymes to ensure that herbicide effects are
neutralized in the plant body (Menendez et al. 1996). This means the herbicide induces the
expression of the p450 genes which will ultimately act against it and metabolize it. Even though
no specific P450 genes have yet been identified from herbicide resistant weeds, P450 genes are
candidates for study in glyphosate-resistant fleabane to determine via RNA-Seq whether they are
upregulated in resistant plants before or after glyphosate treatment, and if so, whether they work

in conjunction with other relevant genes that all have a common objective of neutralizing the
toxins.
Weeds are very competitive and therefore bring about huge crop yield losses by
competing with crop plants for water, nutrients, and sunlight. Because herbicides are the most
commonly used method to control weeds, these plants devise a mechanism of survival through
resistance to the toxic effects of the herbicide. This herbicide selection pressure has been
encountered for a long time now in many weed species, meaning a lot of losses due to the
evolution of resistance are already felt by farmers (Green et al. 2008). Acquisition of knowledge
about the genetic basis of herbicide resistance is key in weed management and has the potential
to bolster agricultural productivity. Elucidating the role of the target site mutations and non-
target mutations in resistance to various chemicals is important in genetic engineering of crop
plant resistance, especially by plant transformation techniques. Due to advancements in
molecular biology techniques, it is now possible to determine genes that are upregulated in
response to herbicide exposure in particular weed species, to begin to decipher the mechanisms
behind NTSR. The aim of this study is to elaborate on the specific role of previously-identified
genes in herbicide resistance in fleabane specifically, as well to unearth further target and non-
target mutations that may yet be undiscovered, using these molecular biology tools. This study is
meant to reaffirm that there is glyphosate-resistant fleabane in the Central Valley, and will shed
light on whether it has evolved once or multiple times, based on the underlying genetic changes
discovered in our population-level survey of the Valley. This information is critical to the
cultivators to ensure that effective and sustainable weed management and control strategies are
put in place.

SPECIFIC AIMS
Broad Objective: To discover the genetic basis (or bases) of glyphosate (RoundUp®) resistance
in the Central Valley agricultural weed fleabane (Erigeron bonariensis L.).
Specific Objectives:
1. To determine differential gene expression in known populations of glyphosate-resistant
vs. sensitive fleabane before and after different glyphosate application rates.
2. To establish if the candidate genes EPSPS and ABC transporter genes M10 and M11, as
well as to-be-determined candidate genes from RNA-Seq, have a role in glyphosate
herbicide resistance in fleabane populations.
3. To determine whether different glyphosate-resistant populations of fleabane from the
Central Valley have different genetic bases for resistance.
Hypothesis: Glyphosate resistance in fleabane is due to non-target site resistance, facilitated by
transcriptional upregulation of ABC transporter genes.
Specific Hypotheses:
1. Glyphosate application will result in more significant upregulation of ABC transporter
genes in glyphosate-resistant fleabane, than in glyphosate-sensitive fleabane.
2. EPSPS has no direct role in glyphosate resistance in fleabane (i.e., target site resistance is
not present), but M10 and M11 (and possibly other ABC transporter genes) play a role in
non-target site herbicide resistance in fleabane.
3. Different glyphosate-resistant Central Valley fleabane populations have different
expression levels for M10 and M11 (and possibly other ABC transporter genes), due to
different origins of resistance.

EXPERIMENTAL DESIGN
Sample preparation
Ten different populations of Erigeron bonariensis (each population containing 18 plants) will be
selected for germination. HFS and HFR populations will be used as control plants as HFS are
susceptible and the HFR are glyphosate in nature. The setting up of the greenhouse for the
rearing of the samples began with the minimal headspace (few if any of the plants would grow
into a hanging plant) and utmost lighting in great consideration. Square footage was also to be
minimal as the samples requires not as much clearance. The freestanding design will be favored
due to the maximum lighting provided by the design unlike the attached design which would
limit the lighting to only the sides. The freestanding design will also allow a wider berth of the
growing season would the need arise. Plastic sheeting will be utilized as the glazing material due
to its cheap price and also because the greenhouse is but for a single experiment but if more
experiments crop up, then polycarbonate glazing will be a favorable alternative. The structure is
to be grounded further from sunlight obstruction objects and oriented for optimal sunlight in
which additional 4ft T5 glow lights can be utilized to compensate any light deficiency. The
sample population seeds will be evenly distributed in portable pots/trays with spraying
glyphosate rates at 1.15 kg·ha−1 (Singh and Sharma, 2007). Research design, growth conditions
and exposure to glyphosate will be as described in Okada et al. (2013; 2014). Prior to exposure
to glyphosate, several leaves will be collected from all the populations and stored in a -800C
freezer for RNA extraction. Twenty-four hours after exposure to glyphosate, leaves will be
collected from all the individuals and stored in the -800C freezer for RNA analysis. The leaves
are to be selected randomly ensuring inclusiveness of all strata (pots/trays) picking equal number
of sample subjects per stratum randomly. Each plastic tray/pot will have 72holes in 3-rows

having six subjects per row of a particular species and each species being replicated in three
trays/pots (Signh and Sharma, 2007).
RNA extraction
Leaves will be harvested, stored at -80°C, and ground in liquid nitrogen. Total RNA will be
isolated from the leaves using the Qiagen Plant RNeasy Mini Kit, using the protocol included
with the kit, and stored at -20°C C until downstream gene-expression analysis. Potential genomic
DNA will be removed using DNase (FisherSci) and RNA will be measured using Qubit® dsDNA
HS Assay Kits. Denaturing gel electrophoresis will be done to assess RNA quality.
1st Round of real-time quantitative PCRs
This will target EPSPS, ABC M10, ABC M11, and actin as a control. These genes were
upregulated in glyphosate-resistant E. canadensis (Nol et al. 2012; Tani et al. 2015), which is
closely related to E. bonariensis.
First-strand cDNA will be reverse-transcribed from 2 μg of total RNA. Samples will be
denatured at 650C for 5 min followed by quick chill on ice. The reaction mixture (12 μL in
volume) will contain 500 ng oligo (dT) 18 mer and 1 μL of 10 mM dNTPs. After the addition of
4 μL of 5x PrimeScriptTM buffer (TaKaRa), 1 μL (40 units) of human placental ribonuclease
inhibitor (HT Biotechnology Ltd., Cambridge, UK), 1 lL (200 units) of PrimeScriptTM RT
(TaKaRa) and water to a 20-lL final volume, the reaction mixture will then be incubated at 420C
for 50 min, followed by heat inactivation at 700C for 15 min. Target cDNAs will be PCR
amplified using gene-specific primers shown in Table 1 (Bhstis, ed).
Quantitative RT-PCR will be performed using Thermo Scientific ABsolute SYBR®
Green Master Mix on an Eppendorf® Mastercycler® RealPlex thermocycler (Applied

Biosystems). The reaction mixture (20 μL) will contain gene-specific oligonucleotides at a final
concentration of 0.2 μM each and 1.25 μL of the cDNA as template. PCR cycling will start with
the initial polymerase activation at 950C for 3 min, followed by 40 cycles of 950C for 15 s, 550C
for 15 s and 720C for 20 s. The primer specificity and the formation of primer dimers will be
monitored by dissociation curve analysis. The expression levels of the E. bonariensis actin gene
will be used as an internal standard to normalize small differences in cDNA template amounts.
Relative transcript levels of the genes of interest will be calculated as a ratio to the actin gene
transcripts. PCR efficiency for each amplicon will be calculated by employing the linear
regression method on the log (fluorescence) per cycle number data, using the LinRegPCR
software (Ramakers et al., 2003). All realtime qPCR will be performed on three biological
replications.
Clean total RNA that is treated with RNase from controls, HFS and HFR treated with glyphosate
will then be send to UCLA for library preparation and Illumina HiSeq sequencing.
Table 1 Primers used for real-time qRT-PCR
Target gene Forward prime Reverse primer
EPSPS 5’-TTACTTCTTAGCTGGTGCTG-3’ 5’-GGCATTTTGTTCATGTTCACATC-3’
M10 5’-TTGGCTCAACTTCGTGGTATTGGG-3’ 5’-CCAAGAAATTCCAAGCGGAACCCT-3’
M11 5’-ATGCTGTCTTCTTTTACCTTTGC-3’ 5’-CGACTTCCCACTACCAGTTCTTC-3’
Actin 5’-GTGGTTCAACTATGTTTCCCTG-3’ 5’-CTTAGAAGCATTTCCTGTGG-3’
Bioinformatic data analysis

Illumina HiSeq reads will be assembled de novo using Trinity (Haas et al. 2013). The quality of
assembled reads will be assessed and assigned to their respective genes by HTSeq (Anders et al.
2015). Test for differentially expressed genes will be performed using DESeq (Anders & Huber
2010) between HFS and HFR. All assembled upregulated or downregulated genes were
matched against the National center for Biotechnology (NCBI), nonredundant protein (Nr)
database for functional annotation.
2nd round of quantitative PCR
This will be informed by the RNA-Seq results in the previous experiment. New E. bonariensis-
specific candidate genes will be used in the primer design primers for up- and down-regulated
genes from RNA-Seq results in a quantitative PCR with the same design as the 1st round
quantitative PCR.
The RNA-sequencing design.
RNA-seq study will harbor the desired potential to curb the questions under study. This is to be
achieved via proper experimental design, sequencing depth coupled with the right replicates
number and sufficient experimental sequencing to minimize bias (Conesa et al., 2016). Conesa et
al. records that the RNA extraction protocol experimental design is vital for mRNA under
interest (2016). Some strand specific protocols for instance the chiefly utilized dUTP method,
apply initial protocol extension via utilization of UTP nucleotides on the first subsequent cDNA
synthesis stage (Parkhomchuk D et al., 2009). Prioritization between single-end (SE) and paired-
end (PE) reads and optimal sequencing depth will depend on the analysis set goals for the
experiment (Conesa et al., 2016). Conesa et al. goes ahead to note the vitality of more transcripts
for detection, the more precise is their respective segment quantification due to the deepened

sequencing level (2016). The replicates number is equally an important design factor. RNA
sequence procedures technical variability quantity coupled with the system’s biological
variability are to be included in a RNA sequence experiment (Conesa et al., 2016). The same is
to be incorporated in the desired statistical power.
Analysis of RNA sequence data.
We are aware of the numerous RNA-seq data real analysis diversifications similarly as the
existence of technological applications. Below is a flowchart describing the procedures involved
in the process.
Image courtesy of Conesa et al. (2016)

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