Next Article in Journal
Variation in Assemblages of Freshwater Mussels Downstream of Dams and Dam Removals in the Lake Michigan Basin, Michigan, USA
Next Article in Special Issue
High Differentiation among Populations of Green Foxtail, Setaria viridis, in Taiwan and Adjacent Islands Revealed by Microsatellite Markers
Previous Article in Journal
Landscape and Species Traits Co-Drive Roadkills of Bats in a Subtropical Island
Previous Article in Special Issue
Do Weeds Hinder the Establishment of Native Plants on a Reclaimed North American Boreal Mine Site?
 
 
Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
Journals
Diversity
Volume 13
Issue 3
10.3390/d13030118
diversity-logo
Submit to this Journal Review for this Journal Propose a Special Issue
► Article Menu

Article Menu

share Share announcement Help format_quote Cite question_answer Discuss in SciProfiles thumb_up
...
Endorse textsms
...
Comment
first_page
settings
Order Article Reprints
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Article

Detection of Target-Site Herbicide Resistance in the Common Ragweed: Nucleotide Polymorphism Genotyping by Targeted Amplicon Sequencing

by
Barbara Kutasy
1,
Zoltán Farkas
2,
Balázs Kolics
1,
Kincső Decsi
1,
Géza Hegedűs
3,
Judit Kovács
4,
János Taller
1,
Zoltán Tóth
2,
Nikoletta Kálmán
5,
Gabriella Kazinczi
6 and
Eszter Virág
1,*
1
Department of Plant Science and Biotechnology, Georgikon Campus, Szent István University, 7 Festetics Str., 8360 Keszthely, Hungary
2
Department of Crop Production and Land Use, Georgikon Campus, Szent István University, 7 Festetics Str., 8360 Keszthely, Hungary
3
Department of Economic Methodology, Georgikon Campus, Szent István University, 16 Deák Ferenc Str., 8360 Keszthely, Hungary
4
Gregor Mendel Institute of Molecular Plant Biology, Austrian Academy of Sciences, Vienna Biocenter, Dr. Bohr-Gasse 3, 1030 Vienna, Austria
5
Department of Biochemistry and Medical Chemistry, University of Pécs Medical School, 12 Szigeti Str., 7624 Pécs, Hungary
6
Institute of Plant Science, Kaposvár Campus, Szent István University, 40 Guba S. Str., 7400 Kaposvár, Hungary
*
Author to whom correspondence should be addressed.
Diversity 2021, 13(3), 118; https://doi.org/10.3390/d13030118
Submission received: 29 January 2021 / Revised: 3 March 2021 / Accepted: 6 March 2021 / Published: 10 March 2021
(This article belongs to the Special Issue Weed Ecology and Diversity)
Browse Figures
Versions Notes

Abstract

:
Background: The spread of herbicide-resistance Ambrosia artemisiifolia threatens not only the production of agricultural crops, but also the composition of weed communities. The reduction of their spread would positively affect the biodiversity and beneficial weed communities in the arable habitats. Detection of resistant populations would help to reduce herbicide exposure which may contribute to the development of sustainable agroecosystems. Methods: This study focuses on the application of target-site resistance (TSR) diagnostic of A. artemisiifolia caused by different herbicides. We used targeted amplicon sequencing (TAS) on Illumina Miseq platform to detect amino acid changes in herbicide target enzymes of resistant and wild-type plants. Results: 16 mutation points of four enzymes targeted by four herbicide groups, such as Photosystem II (PSII), Acetohydroxyacid synthase (AHAS), 5-enolpyruvylshikimate 3-phosphate synthase (EPSPS) and protoporphyrinogen IX oxidase (PPO) inhibitors have been identified in common ragweed populations, so far. All the 16 mutation points were analyzed and identified. Out of these, two mutations were detected in resistant biotypes. Conclusions: The applied next-generation sequencing-targeted amplicon sequencing (NGS-TAS) method on A. artemisiifolia resistant and wild-type populations enable TSR detection of large sample numbers in a single reaction. The NGS-TAS provides information about the evolved herbicide resistance that supports the integrated weed control through the reduction of herbicide exposure which may preserve ecological properties in agroecosystems.

1. Introduction

Extensive weed management in agricultural fields is a major threat to agroecosystem biodiversity as weed communities play a key role in maintaining heterogeneity. The total number of weed species in agricultural fields has increased since the 1950s. Although this has resulted in a more diverse composition of agricultural weeds, it has negatively affected landscape structure and land-use intensity. As a result, crop intensification methods, such as herbicide treatment, have become critical to control weed communities to improve agricultural crop production [1]. It is important not to endanger beneficial weed species while using weed control. To define the correct management of invasive species, local environmental drivers have to be identified due to their severe effects on individual performance [2].
Common ragweed (Ambrosia artemisiifolia L.: Asteraceae, A. artemisiifolia) is a highly adaptive, invasive weed and has a negative impact on biodiversity [3,4]. Its population can be found not only in agricultural habitats where herbicides are normally used but also in field margins and paths, abandoned fields, and forest edges that could be affected by herbicide or intensified mowing [5,6]. Common ragweed has spread from North America to habitats in temperate climates such as Eurasia, Asia and Australia [7,8], and has become distributed in all countries of Southern and Eastern Europe [9,10,11,12]. In North America large common ragweed populations have extensively arisen along roadsides and arable fields as well, which was recently observed mainly in Eastern Canada [13].
Many weed scientists deliberate on the knowledge and practice gap of the perspectives and approaches in weed ecology and management [14,15,16]. Due to the complexity of the problem, it requires transdisciplinary. Transdisciplinary approaches contribute to the most promising technological improvements managing weed control and agroecosystem diversity and reduce the potential unwanted environmental impacts of weed management. The negative correlation between weed diversity and crop yield loss has been reported [17]. As a consequence of the diverse weed management and crop production systems, the more adaptable weedy plants may replace the invasive species and the given ecosystems benefit [15]. Therefore, a well-thought herbicide use strategy should be effective and reasonable. The weed thresholds are required to promote the usage of optimal herbicides to protect crop yields and arable habitats [18].
To improve weed management and avoid ecological damages, monitoring the different herbicide-resistance in a population seems to be a great solution to find the optimal chemical crop protection. In this study, we focus on the subject of the common ragweed chemical control. Our primary goal is to achieve the controlled eradication of ragweed or at least to maintain its low moderate level while minimizing the ecological damage caused by the applied herbicide.
Common ragweed has evolved different herbicide resistance modes, making it particularly problematic to control [19]. Herbicide resistance can be categorized into two categories based on mode of action: target-site resistance (TSR) and non-target-site resistance (NTSR) [20,21,22]. Here, we focus on TSR resistance, which can be caused by mutation or polymorphism that results in either increased abundance of the target protein or a structural change in the target protein that reduces affinity to the herbicide [23,24]. Structural changes are generally due one or several amino acid substitutions [25,26,27,28,29]. The accumulation of multiple amino acid substitutions in a target protein has been known as multiple target-site resistance (MTSR) which triggers an increased resistance level of individual plants [22,30,31]. MTSR has been detected in different weeds conferring resistance to Photosystem II (PSII) and Acetohydroxyacid synthase (AHAS) inhibitors [32,33,34]. Resistant genotypes proliferate in areas where herbicides are used for weed control. In order to effectively combat herbicide-resistant common ragweed, effective methods to measure the prevalence of TSR and MTSR within target populations are needed.
Four herbicide mode-of-action groups are commonly used to control A. artemisiifolia. These are: (i) triazines and ureas (Photosystem II (PSII) inhibitors), (ii) sulfonylureas, imidazolinones, sulfonylaminocarbonyl-triazolinones, pyrimidinylthiobenzoates and triazolopyrimidines (AHAS inhibitors), (iii) glyphosate (5-enolpyruvylshikimate 3-phosphate synthase (EPSPS) inhibitors) and (iv) diphenylethers, N-phenylphthalimides, aryl triazolinones, phenylpyrazoles, pyrimidinediones (protoporphyrinogen IX oxidase (PPO) inhibitors).
PS II inhibitors bind to the D1 protein of the photosystem II (EC: 1.10.3.9) complex, blocking electron transport and stopping CO2 fixation. The D1 protein is encoded by the chloroplast psbA gene. The first documented herbicide resistant population of A. artemisiifolia was discovered in 1976 and was resistant to the PSII-inhibitor atrazine (a triazines) [35]. Resistance was conferred by a point mutation in the psbA gene resulting in a serine-to-glycine substitution, which alters D1 protein conformation, causing reduced herbicide target interaction [36,37]. To detect the causal mutation (Ser264Gly) in common ragweed, a bidirectional allele-specific PCR (Bi-PASA) method was developed [38]. Resistant biotypes and populations have also been reported against linuron (belonging to ureas) in eastern Canada [39,40]. TSR, conferred by the psbA mutation Val219Ile, was detected after linuron treatment using TaqMan single nucleotide polymorphism (SNP) genotyping and Sanger sequencing [41]. Moreover, three additional mutations at the site of action (Ala251Val, Phe255Ile, and Asn266Thr) have been confirmed in populations of other species, each with a unique cross resistance pattern [42].
AHAS inhibitors are among the most used common ragweed inhibitors worldwide. AHAS (EC 4.1.3.18 also known as acetolactate synthase, ALS) catalyses the first common step in the pathway for synthesis of the branched-chain amino acids leucine, isoleucine, and valine in plants [43]. AHAS inhibitors have low mammalian toxicity, are broad spectrum and highly effective in low doses. However, resistance to AHAS inhibitors tends to arise rapidly in weed populations. Multiple studies have reported that AHAS inhibitor-resistant weed species are more numerous than weed species resistant to other herbicide groups [44,45]. Many AHAS inhibitor-resistant common ragweed populations have been reported. Cross resistance in these populations is common, with resistant individuals displaying resistance to additional herbicides, including cloransulam-methyl (triazolopyrimidines), chlorimuron (sulfonylureas), and imazaquin (imidazolinones) [46]. Resistance in common ragweed against AHAS inhibitors is conferred by the substitution Trp574Leu [47]. Although eight different AHAS amino acid substitutions confer resistance to AHAS inhibitors in other species, only Trp574Leu has been reported in common ragweed [20,48].
Several polymorphisms in the epsps gene of many plant species confer resistance to glyphosate. Resistance is conferred by mutations at Pro106 and Thr102, and recently an example of MTSR was reported in Amaranthus hybridus that contained the triple-substitution Thr102Ile, Ala103Val and Pro106Ser [49,50,51,52]. Glyphosate resistance in A. artemisiifolia was first reported in Missouri and Arkansas in 2004 but the mechanism of the resistance has not yet been determined [53].
PPO inhibitors have been used widely to control weeds in different crop cultures since the 1960s. PPO (EC 1.3.3.4) is a key enzyme in the tetrapyrrole biosynthetic pathway that produces heme and chlorophyll in plastids and mitochondria [54]. Two different nuclear-encoded PPO isozymes are in plants: plastidal PPO1 encoded by the gene ppx1 and mitochondrial PPO2 encoded by the ppx2 gene [55]. The weed reported to evolve resistance to PPO inhibitors was Amaranthus tuberculatus, which contained a glycine deletion at position 210 (ΔG210) in PPX2 (GenBank accession: DQ386114) [56]. In A. artemisiifolia, an Arg98Leu substitution in the ppx2 gene contributes to PPO resistance [57].
Multi-resistant A. artemisiifolia populations can be found worldwide, containing multiple resistance-conferring mutations in genes encoding PSII, AHAS, EPSPS, and PPO [46]. The investigation of specific mutations conferring herbicide resistance in populations is essential for the selection of effective herbicides for weed control. Targeted amplicon sequencing (TAS) is an effective approach that takes advantage of NGS (next generation sequencing) to detect specific mutations. To sequence large numbers of targeted gene regions, NGS is using indexed primers to label samples that are expansively used for population genetics and for genome-wide genotyping in plants with ultralow SNP densities [58].
This study presents an NGS-TAS method for TSR identification in A. artemisiifolia. In order to discover multiple polymorphisms in psbA, ahas, epsps, and ppx2 that confer resistance, we analysed sensitive biotypes, as well as imazethapyr-resistant (imidazolinones, AHAS inhibitor) and linuron-resistant (ureas, PSII inhibitor) biotypes. This method may contribute to the sustainable maintenance of biological integrity in agroecosystems by screening herbicide resistant common ragweed populations.

2. Materials and Methods

2.1. Plant Materials and DNA Extraction

Leaves of 20 susceptible A. artemisiifolia plants were collected from an agricultural field in West-Transdanubian region of Hungary (46°44′54.7″ N 17°14′07.7″ E). Seeds of linuron resistant biotypes were collected in a field border of Ste-Clotilde Legault Quebec, Canada (45°07′14″ N 73°38′19″ W) and seeds of imazethapyr resistant biotypes were collected in a soybean field of Mirabel Quebec, Canada (45°39′16.94″ N 74°05′45.31″ W). Seedlots were sampled from sites where ragweed was tested and identified as imazethapyr and linuron resistant. Resistance seeds were germinated in petri dishes at 30 °C/20 °C 16 h photoperiod and were planted in pots and were growing in greenhouse. Leaves of 20-20 planted individuals were further collected. Samples were frozen in liquid nitrogen immediately after collection and stored at −80 °C until DNA and RNA analysis.
Total DNA from leaf tissues was isolated according to the protocol Doyle, J. J. and Doyle, J. L. [59]. The DNA quantity and purity were assessed on NanoDrop2000 (Thermo Scientific, Waltham, MA, USA). For the experiments, DNA of resistant and sensitive biotypes were used according to the following classification: (i) bulked sample of 20 sensitive genotypes deriving from Hungarian sampling site; (ii) bulked sample of 20 imazethapyr (imidazolinones) resistant genotypes collected from Mirabel sampling site (AMI) and (iii) bulked sample of 20 linuron (ureas) resistant genotypes collected from Ste-Clotilde Legault sampling site (AMU). All individuals, both susceptible and resistant genotypes, were analyzed by Sanger method.

2.2. Identification of A. artemisiifolia Herbicide Target Enzyme mRNAs

In order to identify in silico coding sequences (cds) of herbicide target enzymes of each herbicide group, we used the transcript dataset of A. artemisiifolia, deposited in the National Centre for Biotechnology Information’s (NCBI) Transcriptome Shotgun Assembly (TSA) dataset under the accession GEZL01000001 [60]. Reference genes were selected based on taxonomic relationship from closely related species and were downloaded from the UniProt database: A. artemisiifolia, psbA (B5MF75); Xanthium sp., ahas (Q41716); Cichorium intybus, ppx1 (Q9SPL6); Amaranthus palmeri, ppx2 (A0A291B3V5); Erigeron canadensis, epsps (G4U4J5) [61]. The identity of reference genes and identified genes was 96–99% [62]. The investigated sequences were deposited in the NCBI GenBank database (Accession numbers see below).

2.3. Intron Analysis, Amplification and Cloning of A. artemisiifolia Herbicide Target Enzyme Genes

Multiple primer pairs were designed in order to cover all possible mutation points along the whole psbA and ahas gene sequences by using Primer3Plus [63] (Figures S1 and S2).
In the case of intron containing epsps gene, the exon-intron bounds were predicted based on complete gene sequences of closely related species by using ClustalW aligning the sequences of Conyza canadensis (AY545667.1) and Amaranthus palmeri (FJ861242.1 and FJ861243.1) [64] (Figure S3).
In order to validate polymorphisms that characterize herbicide resistance, the imazethapyr, linuron resistant, and sensitive bulked samples were amplified. The PCR amplifications was performed by using Dream Taq DNA polymerase (Thermo Fisher Scientific, Waltham, MA, USA) The PCR products were separated on 1.5% agarose gel (Promega, Madison, WI, USA) and were purified using NucleoSpin Gel and PCR Clean-up system (Macharey-Nagel GmbH & Co, Düren, Germany). The pGEM-T Easy Vector System kit (A1360 Promega, Madison, WI, USA) and JM109 Competent Cells were used to clone PCR products [65]. Sanger sequencing of the cloned fragments was performed with ABI 3130xl Genetic Analyzer (Applied Biosystems, Carlsbad, CA, USA). Sequenced fragments of herbicide target genes were aligned to predicted gene sequences certifying amino acid substitutions in the mutation points.

2.4. PCR Amplification for NGS-TAS Experiments

The KAPA HiFi HotStart PCR Kit (Kapa Biosystems, Wilmington, NC, USA) was used for amplification of target fragments. In NGS-TAS experiments of investigated regions of psbA, ahas, epsps, and ppx2 genes, primers were designed by using Primer3Plus (Figure S7).
The PCR amplifications were performed and the PCR products were separated on 1.5% agarose gel (Promega, Madison, USA). PCR products were controlled with Agilent 2100 Bioanalyzer (Agilent Technologies, Waldbronn, Germany) using Agilent DNA 1000 Kit and were purified using NucleoSpin Gel and PCR Clean-up system (Macharey-Nagel GmbH &Co, Düren, Germany).

2.5. NGS-TAS Experiments

For NGS-TAS experiments, resistant samples were used and grouped with the following nomenclature.
Sample AMI was named based on the imidazolinone (imazethapyr) resistant bulked DNA of A. artemisiifolia and sample AMU was named based on the urea (linuron) resistant bulked DNA of A. artemisiifolia. Numbers 1–3 were three biological repeats of the same bulked DNA (AMI1-3, AMU1-3). The concentrations of PCR products were measured by NanoDrop2000 (Thermo Scientific, Waltham, USA) and fragments for each sample were diluted relative to the PCR product with the lowest concentration. AMI1control and AMU1control contained the not diluted samples of the first biological repeats. In the AMI and AMU groups bulked DNA of 20 individuals were used.
In order to obtain long fragments that cover all the mutation points in each gene, fragments were sequenced on MiSeq 550 platform obtaining 300 bp paired-end reads detailed as follows: locus-specific PCR products were purified using 1.0 volume KAPA PureBeads (F. Hoffmann-La Roche, Basel, Switzerland) according to the manufacturer’s protocol. The concentration of eluted DNA was measured using a Qubit 3.0 Fluorometer with Qubit dsDNA HS Assay Kit (Thermo Fisher Scientific, Waltham, USA). Index PCR reactions (20 µL each) were set up by using 20 ng of purified template in 6 µL, 2 µL Nextera XT Index kit v2 Primers (N7xx & S5xx) (Illumina, Inc. San Diego, CA, USA), and 10 µL of 2xKAPA Hifi Hot Start Ready Mix (F. Hoffmann-La Roche, Switzerland). The used primer and IlluminaNextera adapter sequences are detailed in Figure S7. PCR cycling parameters for index PCRs were as follows: initial denaturation at 95 °C for 3 min; 8 cycles at 95 °C for 30 s, 55 °C for 30 s, 72 °C for 30 s; final extension at 72 °C for 5 min. PCR products were purified using 1.0 volume KAPA PureBeads and eluted in 20 µL of 10 mM Tris-HCl pH 8. The product libraries were quantified and qualified by using High Sensitivity D1000 ScreenTape on TapeStation 2200 instrument (Agilent Technologies, Santa Clara, CA, USA) (Figure S11). Equimolar concentrations of libraries were pooled, diluted to 4 nM, and combined with other sample pools to gain the desired sequencing depth. Sequencing was carried out using Illumina MiSeq platform and 600-cycle Reagent Kit v3 (Illumina, Inc. San Diego, CA, USA). Samples were demultiplexed and adapter-trimmed by using MiSeq Control Software.

2.6. Bioinformatics Analysis

Pear software [66] was used to merge paired-end reads with minimum overlap size 10 bp, without discard uncalled bases, and with 30 parallel threads in processing (arguments –v 10 –u 1 –j 30). All the samples contained the reads amplified by the 7 primer pairs covering all the mutation points. Accordingly, the reads belonging to each fragment were counted in each sample (Figure S12). Usearch software [67] was applied to collect identical sequences for resistance polymorphism. Usearch was used in three steps: (i) Quality filter with fastq_filter command with fastq_maxee 1.0 and fastq_minlen 160 parameters; (ii) Singleton filter with fastq_uniques command; (iii) Grouping with cluster_otus parameter with minsize 10. Groups were shown the similarity threshold 99% representing the different amplicon products with nucleotide polymorphism for the investigated gene.

3. Results

In order to perform NGS-TAS analysis, it would be necessary to know cds and gene sequences of herbicide target enzymes. However, no whole genome sequence data of A. artemisiifolia yet exists. To design correct NGS-TAS primer pairs, it is essential to know at least the sequences at the intron-exon boundaries close to the mutation points. Accordingly, gene sequences and point mutations of the herbicide target enzymes were determined in sensitive genotypes by using in silico NGS transcriptome analysis (NGS-TA), SS Sanger sequencing, and NGS-TAS (Figure 1).

3.1. Identification of A. artemisiifolia Herbicide Target Enzyme cds and Genes

In silico analysis of investigated herbicide target enzyme cds was performed with BLAST+. The accession numbers of predicted GOIs are MT425203 (psbA), MK096760 (ahas), MK096765 (epsps), and MK096762 (ppx2). Open reading frame (ORF) sequences were predicted using NCBI ORF finder [68]. The predicted sequence of the psbA gene consisted of one exon with a total length of 1062bp, as previously described (Table 1) [37]. The psbA gene was amplified with 2 primer pairs covering the resistance mutation points as described before (Figure S1, GenBank accession MT879746).
The structure of the ahas gene contained one exon with a total length of 1965bp. The whole ahas gene was amplified with five primer pairs covering the resistance mutation points as described before (Figures S2 and S4, GenBank accession MT415954) [20,47].
The structure of the epsps gene contained 8 exons and 7 introns with a total length of 3539bp. A similar structure was described in Amaranthus palmeri (JX564536.1) [64]. The epsps gene was amplified with eight primer pairs covering the resistance mutation points as described before (Figures S3 and S4, GenBank accessions MT415955 (exon1-intron1), MT409110 (intron1-exon8)) [32].
The first published weed species to evolve resistance to PPO-inhibiting herbicides was Amaranthus tuberculatus [56]. The ppx2 gene (GenBank accession DQ386118) from the resistant biotype of A. tuberculatus contained a glycine deletion at position 210 (ΔG210) that was shown to confer resistance. This deletion in A. artemisiifolia has not been published, yet, although the substitution Arg98Leu was discovered to contribute to PPO-inhibitor resistance A. artemisiifolia [57]. So far, no complete gene sequence exists of the whole ppx2 gene in plants covering all of the introns and exons. Therefore, identifying the complete sequence of ppx2 gene is not possible only using Sanger sequencing. By using the NGS-TAS, a 324 bp fragment of ppx2 gene was amplified with one primer pair covering the resistance mutation point Arg98 [55]. Electropherogram of Sanger sequenced PCR product revealed two product lengths. The differences between the two fragments were 13 bp localised in one intron (Figures S4 and S5, GenBank accession MT879747, MT879748).
In order to obtain accurate information about the investigated enzymes, in silico predicted cds of Illumina data and the Sanger sequenced data of the appropriate PCR products were compared. The two technologies showed slight variability (1–2% differences) in amino acid sequences across ahas and epsps, however these discrepancies were not at mutation points. There was no difference in sequencing results of the psbA gene between the two methods (Figure S6).

3.2. NGS-TAS Experiments of AMI and AMU Biological Repeats

In NGS-TAS experiments specific regions of psbA, ahas, epsps, and ppx2 genes were amplified by different primers (Figure 2, Figures S9 and S10). Sample AMI was named based on the imidazolinone (imazethapyr) resistant bulked DNA of A. artemisiifolia and sample AMU was named based on the urea (linuron) resistant bulked DNA of A. artemisiifolia. Both AMI and AMU contained three replicates.
Each sample contained the PCR products of psbA, ahas, epsps, and ppx2 genes. The control of AMI1-3 group was labeled as AMI1control and contained PCR products of AMI1. Similarly, AMU1control served as a control for AMU1-3 group and contained PCR products of AMU1. Both in AMI and AMU samples, the concentrations of the PCR products of the four genes were measured in each replicate, respectively. Afterwards, the lowest concentration was used as a base for further dilution of the other PCR products to avoid error in sequencing analysis (Table 2, Figure S8). In NGS-TAS analyses the samples were sequenced in four lanes. Based on the ratio of concentration/contig number of the samples, we found that all concentrations of AMI and AMU samples were optimal for the diagnostic procedure.

3.3. Bioinformatics Analysis of AMI and AMU Groups

Samples with different concentrations showed different distributions in contig number (Table 2). As a result of amplicon sequencing the number of Illumina MiSeq 300 bp reads were 276,462 (forward), 296,722 (reverse) in case of AMI and 316,465 (forward), 369,748 (reverse) in case of AMU samples. After quality filtering dropped reads were 0.7% on average of AMI samples and 4.7% on average of AMU samples. PEAR software was used to assemble cleaned reads of which unpaired ones were filtered out with the average ratio 5.45 and 9.05% of AMI and AMU samples, respectively. Numbers of filtered and assembled reads were 255,357–287,197. In order to separate the investigated gene fragments we clustered the contigs (assembled reads) into groups based on appropriate primer motifs by using Usearch software. During clustering singletons were dropped (unique groups with one sequence). Average ratios of the survived contigs were 69.8% and 69.7%. The group number was 18 and 12 in AMI and AMU samples (Figure S12).
Fragments in each sample contain different numbers of contigs. Primer sorted groups contain min 8066 max 52,289 contigs (Table 2). Undiluted AMI1control and AMU1 control samples showed an equable read distribution in each fragment, therefore dilution of samples in the same concentration is recommended. Confirmation of a fragment with such a large number of reads provides an opportunity for large-sample analysis.

3.4. Detection of Mutation Points in Resistant Biotypes

To be able to identify the mutations causing resistance in A. artemisiifolia, bulked and amplified DNA sequences of imazethapyr and linuron resistant samples were further analysed by NGS-TAS that covered 16 known resistance mutations sites in A. artemisiifolia. In the AMI group, sequence alignment analysis showed that a single nucleotide in the ahas gene was changed from TGG to TTG and resulted in a Trp574Leu substitution conferring herbicide resistance [47] (Figure 3). Other amino acid substitutions in the D1 protein, EPSPS and PPX2 enzymes at known resistance-conferring mutations sites were not found. Based on these data, the investigated population was susceptible to PSII, EPSP synthase and PPO inhibitors (Figure 3). In the AMU group, sequence alignment analysis showed that a single triplet was changed (GTA to ATA) in the psbA gene and resulted in a resistance-conferring Val219Ile substitution [41] (Figure 3). Other amino acid substitutions in AHAS, EPSPS, and PPX2 enzymes at known resistance-conferring mutations sites were not found. Based on this data the investigated biotype was susceptible to AHAS, EPSP synthase, and PPO inhibitors in terms of TSR (Figure 3).

4. Discussion

Chemical weed control is one of the most common ways to fight against weeds in agricultural areas, giving a high selection pressure for resistant biotypes. After herbicide treatment, the rapid diagnosis of resistance mutations present in surviving individuals using would inform and improve the effectiveness of the next herbicide treatment. In order to maintain sustainability in crop fields and beneficial weed communities that are required for natural ecosystems, the monitoring of resistant common ragweed populations between treatments is important. In this study, we present a molecular biology-based approach (NGS-TAS) to detect herbicide resistant common ragweed populations in arable habitats [69,70].
It is important that only a few herbicides with new mechanism of action (MOA) have been released since the 1980s. The increasing number of herbicide resistant weeds and the lack of discovery of new MOAs make it difficult or even impossible to use existing herbicides effectively. Some studies predict that these problems will endanger the sustainability of weed control [16,71]. Therefore, it is essential to inform farmers about integrated and resistant weed management strategies that are less harmful to the environment [16].
Determining TSR would largely improve the weed management strategy of arable lands. Field sampling of populations and testing them by NGS-TAS method would guide farmers to select the proper herbicides thereby decreasing the impact of agricultural chemical inputs on the populations of crop fields. Thereby, unnecessary and ineffective chemical usage could be avoided [16].
In this study, we describe an effective diagnostic process using NGS-TAS to get information about evolved TSR in A. artemisiifolia populations. In NGS-TAS, TSR is determined using SNP genotyping following genome-wide genotyping. We demonstrate that NGS-TAS analysis is a method that can monitor TSR against four different enzymes targeted by different herbicides in A. artemisiifolia simultaneously. In order to analyse SNPs as part of the resistance mechanism of A. artemisiifolia, coding sequences and complete genes of D1 protein, AHAS and EPSPS were identified. However, the sequence of PPX2 only partially was identified at the region of interest as its length and genomic data is unknown. Mutations and polymorphisms in these four proteins that had previously been reported to confer resistance were specifically investigated. The developed NGS-TAS markers can identify 16 amino acid substitutions of the investigated common ragweed genes among which 4 (psbA: Val219, Ser264, ahas: Trp 574 and ppx2:Arg98) were proven. As a result, the investigated samples characterized by imidazolinone (imazethapyr) and urea (linuron) TSR were proved to carry mutation points at Trp574Leu and Val219Ile in the ahas and psbA genes, respectively. Although no MTSR existed in the studied resistant samples (AMI, AMU), the NGS-TAS method can be used to detect multiple herbicide resistance, which needs to be confirmed by specific MTSR samples.
NGS technology can examine a large number of samples simultaneously using fragment or sample-specific indexed primers. Therefore, amplicon primers were provided that are suitable for discriminating mutation points. In this study, we demonstrated the trial of a pooled sample evolved mutations points of herbicide target genes supporting resistance of A. artemisiifolia populations and biotypes.

5. Conclusions

Invasive weed species appeared to be the bane of biodiversity, ecosystem services, and food security. Integrated weed management practices provide several comprehensive solutions for weed control to reduce weed coverage in agricultural fields. Unfortunately, many weed management approaches used nowadays are highly unsustainable. Moreover, many studies report on the rapid evolution of herbicide-resistant weed populations. This complex evolution of herbicide-resistant weeds makes it difficult to use sustainable herbicide technology [20]. Therefore, applying weed management tools for invasive plants are often ineffective at producing long-term benefits [72]. In order to map evolved resistance in populations, different herbicide resistance mechanisms have to be investigated, such as TSR.
To summarize, NGS-TAS method is a powerful approach that was used for the detection of amino acid polymorphism and mutations that induce TSR. Therefore, it can improve effective weed control taking into account biological integrity and sustainability in agroecosystems by selecting the optimal and effective herbicide usage in cropping systems.

Supplementary Materials

The following are available online at https://www.mdpi.com/1424-2818/13/3/118/s1, Figures S1–S12: Primers, gel pictures and electropherograms of Sanger sequencing. Primers, gel pictures, electropherograms and concentrations of amplicon sequencing. Bioinformatics analysis.

Author Contributions

Conceptualization, B.K. (Barbara Kutasy), B.K. (Balázs Kolics); methodology, B.K. (Barbara Kutasy), Z.F., K.D., B.K. (Balázs Kolics), N.K.; software, G.H.; validation, B.K. (Barbara Kutasy), E.V. and G.H. formal analysis, B.K. (Barbara Kutasy); investigation, B.K. (Barbara Kutasy), E.V.; resources B.K. (Barbara Kutasy); data curation, E.V.; writing—original draft preparation, B.K. (Barbara Kutasy), E.V.; writing—review and editing, E.V., J.K., G.K.; visualization B.K. (Barbara Kutasy), E.V. and J.K.; supervision, E.V.; project administration, B.K. (Barbara Kutasy), E.V.; funding acquisition, G.K., J.T. and Z.T. All authors have read and agreed to the published version of the manuscript.

Funding

The work was supported by the EFOP-3.6.3-VEKOP-16-2017-00008 and the GINOP-2.3.4-15-2016-00005 projects. The project is co-financed by the European Union and the European Regional Development Fund. This work/research was supported by the Hungarian Government and the European Union, with the co-funding of the European Regional Development Fund in the frame of Széchenyi 2020 Programme GINOP-2.3.2-15-2016-00054 project.

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

Not applicable.

Acknowledgments

We express our thanks to Diane Lyse Benoit, Agriculture and Agri-Food Canada, Horticulture Research and Development Centre, Quebec, to release available the resistant Ambrosia artemisiifolia seeds (biological samples) to our experiments. The work was supported by the EFOP-3.6.3-VEKOP-16-2017-00008 and the GINOP-2.3.4-15-2016-00005 projects. We are indebted in the financial supporting to TKP2020-IKA-12 project. The project is co-financed by the European Union and the European Regional Development Fund. This work/research was supported by the Hungarian Government and the European Union, with the co-funding of the European Regional Development Fund in the frame of Széchenyi 2020 Programme GINOP-2.3.2-15-2016-00054 project. We are grateful to the editor and to two anonymous reviewers for valuable comments that have helped to improve the manuscript.

Conflicts of Interest

The authors declare no conflict of interest. The funders had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript, or in the decision to publish the results.

References

  1. Baessler, C.; Klotz, S. Effects of changes in agricultural land-use on landscape structure and arable weed vegetation over the last 50 years. Agric. Ecosyst. Environ. 2006, 115, 43–50. [Google Scholar] [CrossRef]
  2. Lommen, S.T.E.; Hallmann, C.A.; Jongejans, E.; Chauvel, B.; Leitsch-Vitalos, M.; Aleksanyan, A.; Tóth, P.; Preda, C.; Šćepanović, M.; Onen, H.; et al. Explaining variability in the production of seed and allergenic pollen by invasive Ambrosia artemisiifolia across Europe. Biol. Invasions 2018, 20, 1475–1491. [Google Scholar] [CrossRef] [Green Version]
  3. Pinke, G.; Király, G.; Barina, Z.; Mesterházy, Á.; Balogh, L.; Csiky, J.; Schmotzer, A.; Molnár, A.V.; Pál, R.W. Assessment of endangered synanthropic plants of Hungary with special attention to arable weeds. Plant Biosyst. Int. J. Deal. All Asp. Plant Biol. 2011, 145, 426–435. [Google Scholar] [CrossRef]
  4. Alberternst, B.; Nawrath, S.; Starfinger, U. Biodiversity impacts of common ragweed. Julius-Kühn-Archiv 2016. [Google Scholar] [CrossRef]
  5. Essl, F.; Biró, K.; Brandes, D.; Broennimann, O.; Bullock, J.M.; Chapman, D.S.; Chauvel, B.; Dullinger, S.; Fumanal, B.; Guisan, A.; et al. Biological Flora of the British Isles: Ambrosia artemisiifolia. J. Ecol. 2015, 103, 1069–1098. [Google Scholar] [CrossRef] [Green Version]
  6. Fumanal, B.; Girod, C.; Fried, G.; Bretagnolle, F.; Chauvel, B. Can the large ecological amplitude of Ambrosia artemisiifolia explain its invasive success in France? Weed Res. 2008, 48, 349–359. [Google Scholar] [CrossRef]
  7. Bassett, I.J.; Crompton, C.W. The biology of Canadian weeds.: 11. Ambrosia artemisiifolia L. and A. psilostachya DC. Can. J. Plant Sci. 1975, 55, 463–476. [Google Scholar] [CrossRef]
  8. Zhu, J.; Wang, J.; DiTommaso, A.; Zhang, C.; Zheng, G.; Liang, W.; Islam, F.; Yang, C.; Chen, X.; Zhou, W. Weed research status, challenges, and opportunities in China. Crop. Prot. 2020, 134, 104449. [Google Scholar] [CrossRef]
  9. Kiss, L.; Beres, I. Anthropogenic factors behind the recent population expansion of common ragweed (Ambrosia artemisiifolia L.) in Eastern Europe: Is there a correlation with political transitions? J. Biogeogr. 2006, 33, 2156–2157. [Google Scholar] [CrossRef]
  10. Csontos, P.; Vitalos, M.; Barina, Z.; Kiss, L. Early distribution and spread of Ambrosia artemisiifolia in Central and Eastern Europe. Bot. Helv. 2010, 120, 75–78. [Google Scholar] [CrossRef]
  11. Chauvel, B.; Dessaint, F.; Cardinal-Legrand, C.; Bretagnolle, F. The historical spread of Ambrosia artemisiifolia L. in France from herbarium records. J. Biogeogr. 2006, 33, 665–673. [Google Scholar] [CrossRef]
  12. Hamaoui-Laguel, L.; Vautard, R.; Liu, L.; Solmon, F.; Viovy, N.; Khvorostyanov, D.; Essl, F.; Chuine, I.; Colette, A.; Semenov, M.A.; et al. Effects of climate change and seed dispersal on airborne ragweed pollen loads in Europe. Nat. Clim. Chang. 2015, 5, 766–771. [Google Scholar] [CrossRef]
  13. Simard, M.-J.; Benoit, D.L. Distribution and abundance of an allergenic weed, common ragweed (Ambrosia artemisiifolia L.), in rural settings of southern Quebec, Canada. Can. J. Plant Sci. 2010, 90, 549–557. [Google Scholar] [CrossRef] [Green Version]
  14. Müller-Schärer, H.; Sun, Y.; Chauvel, B.; Karrer, G.; Kazinczi, G.; Kudsk, P.; Oude, A.L.; Schaffner, U.; Skjoth, C.; Smith, M.; et al. Cross-fertilizing weed science and plant invasion science to improve efficient management: A European challenge. Basic Appl. Ecol. 2018, 33, 1–13. [Google Scholar] [CrossRef] [Green Version]
  15. Neve, P.; Barney, J.N.; Buckley, Y.; Cousens, R.D.; Graham, S.; Jordan, N.R.; Lawton-Rauh, A.; Liebman, M.; Mesgaran, M.B.; Schut, M.; et al. Reviewing research priorities in weed ecology, evolution and management: A horizon scan. Weed Res. 2018, 58, 250–258. [Google Scholar] [CrossRef] [Green Version]
  16. Westwood, J.H.; Charudattan, R.; Duke, S.O.; Fennimore, S.A.; Marrone, P.; Slaughter, D.C.; Swanton, C.; Zollinger, R. Weed Management in 2050: Perspectives on the Future of Weed Science. Weed Sci. 2018, 66, 275–285. [Google Scholar] [CrossRef] [Green Version]
  17. Moss, S.R.; Storkey, J.; Cussans, J.W.; Perryman, S.A.M.; Hewitt, M.V. Symposium the Broadbalk long-term experiment at Rothamsted: What has it told us about weeds? Weed Sci. 2004, 52, 864–873. [Google Scholar] [CrossRef]
  18. Coble, H.D. Future Directions and Needs for Weed Science Research. Weed Technol. 1994, 8, 410–412. [Google Scholar] [CrossRef]
  19. Kazinczi, G.; Novák, R.; Pathy, Z.; Béres, I. Common ragweed (Ambrosia artemisiifolia L.): A review with special regards to the results in Hungary. III. Resistant biotypes, control methods and authority arrangements. Herbologia 2008, 9, 119–144. [Google Scholar]
  20. Powles, S.B.; Yu, Q. Evolution in Action: Plants Resistant to Herbicides. Annu. Rev. Plant Biol. 2010, 61, 317–347. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  21. Harker, K.N.; O’Donovan, J.T. Recent Weed Control, Weed Management, and Integrated Weed Management. Weed Technol. 2013, 27, 1–11. [Google Scholar] [CrossRef]
  22. Délye, C.; Jasieniuk, M.; Le Corre, V. Deciphering the evolution of herbicide resistance in weeds. Trends Genet. 2013, 29, 649–658. [Google Scholar] [CrossRef]
  23. Vila-Aiub, M.M.; Neve, P.; Powles, S.B. Fitness costs associated with evolved herbicide resistance alleles in plants. New Phytol. 2009, 184, 751–767. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  24. Powles, S.B.; Preston, C. Evolved Glyphosate Resistance in Plants: Biochemical and Genetic Basis of Resistance. Weed Technol. 2006, 20, 282–289. [Google Scholar] [CrossRef]
  25. Bernasconi, P.; Woodworth, A.R.; Rosen, B.A.; Subramanian, M.V.; Siehl, D.L. A Naturally Occurring Point Mutation Confers Broad Range Tolerance to Herbicides That Target Acetolactate Synthase. J. Biol. Chem. 1995, 270, 17381–17385. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  26. Han, H.; Yu, Q.; Purba, E.; Li, M.; Walsh, M.; Friesen, S.; Powles, S.B. A novel amino acid substitution Ala-122-Tyr in ALS confers high-level and broad resistance across ALS-inhibiting herbicides. Pest Manag. Sci. 2012, 68, 1164–1170. [Google Scholar] [CrossRef] [PubMed]
  27. Li, J.; Li, M.; Gao, X.; Fang, F. A novel amino acid substitution Trp574Arg in acetolactate synthase (ALS) confers broad resistance to ALS-inhibiting herbicides in crabgrass (Digitaria sanguinalis). Pest Manag. Sci. 2017, 73, 2538–2543. [Google Scholar] [CrossRef]
  28. McNaughton, K.E.; Letarte, J.; Lee, E.A.; Tardif, F.J. Mutations inALSconfer herbicide resistance in redroot pigweed (Amaranthus retroflexus) and Powell amaranth (Amaranthus powellii). Weed Sci. 2005, 53, 17–22. [Google Scholar] [CrossRef]
  29. Riar, D.S.; Norsworthy, J.K.; Srivastava, V.; Nandula, V.; Bond, J.A.; Scott, R.C. Physiological and Molecular Basis of Acetolactate Synthase-Inhibiting Herbicide Resistance in Barnyardgrass (Echinochloa crus-galli). J. Agric. Food Chem. 2013, 61, 278–289. [Google Scholar] [CrossRef] [PubMed]
  30. Warwick, S.I.; Xu, R.; Sauder, C.; Beckie, H.J. Acetolactate Synthase Target-Site Mutations and Single Nucleotide Polymorphism Genotyping in ALS-Resistant Kochia (Kochia scoparia). Weed Sci. 2008, 56, 797–806. [Google Scholar] [CrossRef]
  31. Yu, Q.; Jalaludin, A.; Han, H.; Chen, M.; Sammons, R.D.; Powles, S.B. Evolution of a Double Amino Acid Substitution in the 5-Enolpyruvylshikimate-3-Phosphate Synthase in Eleusine indica Conferring High-Level Glyphosate Resistance. Plant Physiol. 2015, 167, 1440–1447. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  32. Brosnan, J.T.; Vargas, J.J.; Breeden, G.K.; Grier, L.; Aponte, R.A.; Tresch, S.; Laforest, M. A new amino acid substitution (Ala-205-Phe) in acetolactate synthase (ALS) confers broad spectrum resistance to ALS-inhibiting herbicides. Planta 2016, 243, 149–159. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  33. Diebold, R.S.; McNaughton, K.E.; Lee, E.A.; Tardif, F.J. Multiple resistance to imazethapyr and atrazine in Powell amaranth (Amaranthus powellii). Weed Sci. 2003, 51, 312–318. [Google Scholar] [CrossRef]
  34. Liu, M.; Hulting, A.G.; A Mallory-Smith, C. Characterization of multiple-herbicide-resistant Italian ryegrass (Lolium perenne spp. multiflorum). Pest Manag. Sci. 2014, 70, 1145–1150. [Google Scholar] [CrossRef]
  35. Stephenson, G.R.; Dykstra, M.D.; McLaren, R.D.; Hamill, A.S. Agronomic Practices Influencing Triazine-Resistant Weed Distribution in Ontario. Weed Technol. 1990, 4, 199–207. [Google Scholar] [CrossRef]
  36. Alfonso, M.; Pueyo, J.J.; Gaddour, K.; Etienne, A.L.; Kirilovsky, D.; Picorel, R. Induced New Mutation of D1 Serine-268 in Soybean Photosynthetic Cell Cultures Produced Atrazine Resistance, Increased Stability of S2QB- and S3QB-States, and Increased Sensitivity to Light Stress. Plant Physiol. 1996, 112, 1499–1508. [Google Scholar] [CrossRef] [Green Version]
  37. Cseh, A.; Cernák, I.; Taller, J. Molecular characterization of atrazine resistance in common ragweed (Ambrosia artemisiifolia L.). J. Appl. Genet. 2009, 50, 321–327. [Google Scholar] [CrossRef] [PubMed]
  38. Mátyás, K.K.; Taller, J.; Cseh, A.; Poczai, P.; Cernák, I. Development of a simple PCR-based assay for the identification of triazine resistance in the noxious plant common ragweed (Ambrosia artemisiifolia) and its applicability in higher plants. Biotechnol. Lett. 2011, 33, 2509–2515. [Google Scholar] [CrossRef] [PubMed]
  39. Saint-Louis, S.; DiTommaso, A.; Watson, A.K. A Common Ragweed (Ambrosia artemisiifolia) Biotype in Southwestern Québec Resistant to Linuron. Weed Technol. 2005, 19, 737–743. [Google Scholar] [CrossRef]
  40. Beckie, H.J.; Hall, L.; Tardif, F.; Blackshaw, R. Herbicide resistance in Canada—Where are we today. In Integrated Weed Management: Explore the Potential; Expert Committee on Weeds: Sainte-Anne-de-Bellevue, QC, Canada, 2001; pp. 1–36. [Google Scholar]
  41. Simard, M.-J.; Laforest, M.; Soufiane, B.; Benoit, D.L.; Tardif, F. Linuron resistant common ragweed (Ambrosia artemisiifolia) populations in Québec carrot fields: Presence and distribution of Target site and non-target site resistant biotypes. Can. J. Plant Sci. 2017, 98, 345–352. [Google Scholar] [CrossRef]
  42. Beckie, H.J.; Tardif, F.J. Herbicide cross resistance in weeds. Crop. Prot. 2012, 35, 15–28. [Google Scholar] [CrossRef]
  43. Duggleby, R.G.; Pang, S.S. Acetohydroxyacid synthase. J. Biochem. Mol. Biol. 2000, 33, 1–36. [Google Scholar]
  44. Tranel, P.J.; Wright, T.R. Resistance of weeds to ALS-inhibiting herbicides: What have we learned? Weed Sci. 2002, 50, 700–712. [Google Scholar] [CrossRef]
  45. Yu, Q.; Powles, S.B. Resistance to AHAS inhibitor herbicides: Current understanding. Pest Manag. Sci. 2014, 70, 1340–1350. [Google Scholar] [CrossRef] [PubMed]
  46. Heap, I. The International Survey of Herbicide Resistant Weeds. 2021. Available online: www.weedscience.org (accessed on 10 February 2021).
  47. Patzoldt, W.L.; Tranel, P.J.; Alexander, A.L.; Schmitzer, P.R. A common ragweed population resistant to cloransulam-methyl. Weed Sci. 2001, 49, 485–490. [Google Scholar] [CrossRef]
  48. Massa, D.; Krenz, B.; Gerhards, R. Target-site resistance to ALS-inhibiting herbicides in Apera spica-venti populations is conferred by documented and previously unknown mutations. Weed Res. 2011, 51, 294–303. [Google Scholar] [CrossRef]
  49. Ng, C.H.; Wickneswari, R.; Salmijah, S.; Teng, Y.T.; Ismail, B.S. Gene polymorphisms in glyphosate-resistant and -susceptible biotypes of Eleusine indica from Malaysia. Weed Res. 2003, 43, 108–115. [Google Scholar] [CrossRef]
  50. Lee, L.J.; Ngim, J. A first report of glyphosate-resistant goosegrass (Eleusine indica (L) Gaertn) in Malaysia. Pest Manag. Sci. Former. Pestic. Sci. 2000, 56, 336–339. [Google Scholar] [CrossRef]
  51. Baerson, S.R.; Rodriguez, D.J.; Tran, M.; Feng, Y.; Biest, N.A.; Dill, G.M. Glyphosate-Resistant Goosegrass. Identification of a Mutation in the Target Enzyme 5-Enolpyruvylshikimate-3-Phosphate Synthase. Plant Physiol. 2002, 129, 1265–1275. [Google Scholar] [CrossRef] [Green Version]
  52. Perotti, V.E.; Larran, A.S.; E Palmieri, V.; Martinatto, A.K.; E Alvarez, C.; Tuesca, D.; Permingeat, H.R. A novel triple amino acid substitution in the EPSPS found in a high-level glyphosate-resistant Amaranthus hybridus population from Argentina. Pest Manag. Sci. 2019, 75, 1242–1251. [Google Scholar] [CrossRef]
  53. Brewer, C.E.; Oliver, L.R. Confirmation and Resistance Mechanisms in Glyphosate-Resistant Common Ragweed (Ambrosia artemisiifolia) in Arkansas. Weed Sci. 2009, 57, 567–573. [Google Scholar] [CrossRef]
  54. Smith, A.G.; Marsh, O.; Elder, G.H. Investigation of the subcellular location of the tetrapyrrole-biosynthesis enzyme coproporphyrinogen oxidase in higher plants. Biochem. J. 1993, 292, 503–508. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  55. Lermontova, I.; Kruse, E.; Mock, H.-P.; Grimm, B. Cloning and characterization of a plastidal and a mitochondrial isoform of tobacco protoporphyrinogen IX oxidase. Proc. Natl. Acad. Sci. USA 1997, 94, 8895–8900. [Google Scholar] [CrossRef] [Green Version]
  56. Patzoldt, W.L.; Hager, A.G.; McCormick, J.S.; Tranel, P.J. A codon deletion confers resistance to herbicides inhibiting protoporphyrinogen oxidase. Proc. Natl. Acad. Sci. USA 2006, 103, 12329–12334. [Google Scholar] [CrossRef] [Green Version]
  57. Rousonelos, S.L.; Lee, R.M.; Moreira, M.S.; Vangessel, M.J.; Tranel, P.J. Characterization of a Common Ragweed (Ambrosia artemisiifolia) Population Resistant to ALS- and PPO-Inhibiting Herbicides. Weed Sci. 2012, 60, 335–344. [Google Scholar] [CrossRef]
  58. Shirasawa, K.; Kuwata, C.; Watanabe, M.; Fukami, M.; Hirakawa, H.; Isobe, S. Target Amplicon Sequencing for Genotyping Genome-Wide Single Nucleotide Polymorphisms Identified by Whole-Genome Resequencing in Peanut. Plant Genome 2016, 9, 1–8. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  59. Doyle, J.J.; Doyle, J.L. A rapid DNA isolation procedure for small quantities of fresh leaf tissue. Phytochem. Bull. 1987, 19, 11–15. [Google Scholar]
  60. Virág, E.; Hegedűs, G.; Barta, E.; Nagy, E.; Mátyás, K.; Kolics, B.; Taller, J. Illumina Sequencing of Common (Short) Ragweed (Ambrosia artemisiifolia L.) Reproductive Organs and Leaves. Front. Plant Sci. 2016, 7, 1506. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  61. Altschul, S.F.; Gish, W.; Miller, W.; Myers, E.W.; Lipman, D.J. Basic local alignment search tool. J. Mol. Biol. 1990, 215, 403–410. [Google Scholar] [CrossRef]
  62. Thompson, J.D.; Higgins, D.G.; Gibson, T.J. CLUSTAL W: Improving the sensitivity of progressive multiple sequence alignment through sequence weighting, position-specific gap penalties and weight matrix choice. Nucleic Acids Res. 1994, 22, 4673–4680. [Google Scholar] [CrossRef] [Green Version]
  63. Untergasser, A.; Nijveen, H.; Rao, X.; Bisseling, T.; Geurts, R.; Leunissen, J.A.M. Primer3Plus, an enhanced web interface to Primer3. Nucleic Acids Res. 2007, 35, W71–W74. [Google Scholar] [CrossRef] [Green Version]
  64. Gaines, T.A.; Wright, A.A.; Molin, W.T.; Lorentz, L.; Riggins, C.W.; Tranel, P.J.; Beffa, R.; Westra, P.; Powles, S.B. Identification of Genetic Elements Associated with EPSPS Gene Amplification. PLoS ONE 2013, 8, e65819. [Google Scholar] [CrossRef] [Green Version]
  65. Marcus, L.; Hartnett, J.; Storts, D.R. The pGEM®-T and pGEM®-T Easy Vector Systems. Promega Notes Mag. 1996, 58, 36. [Google Scholar]
  66. Zhang, J.; Kobert, K.; Flouri, T.; Stamatakis, A. PEAR: A fast and accurate Illumina Paired-End reAd mergeR. Bioinformatics 2014, 30, 614–620. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  67. Edgar, R.C. Search and clustering orders of magnitude faster than BLAST. Bioinformatics 2010, 26, 2460–2461. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  68. Rombel, I.T.; Sykes, K.F.; Rayner, S.; Johnston, S.A. ORF-FINDER: A vector for high-throughput gene identification. Gene 2002, 282, 33–41. [Google Scholar] [CrossRef]
  69. Kniss, A.R. Genetically Engineered Herbicide-Resistant Crops and Herbicide-Resistant Weed Evolution in the United States. Weed Sci. 2017, 66, 260–273. [Google Scholar] [CrossRef] [Green Version]
  70. Gaines, T.A.; Zhang, W.; Wang, D.; Bukun, B.; Chisholm, S.T.; Shaner, D.L.; Nissen, S.J.; Patzoldt, W.L.; Tranel, P.J.; Culpepper, A.S.; et al. Gene amplification confers glyphosate resistance in Amaranthus palmeri. Proc. Natl. Acad. Sci. USA 2009, 107, 1029–1034. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  71. Bajwa, A.A.; Mahajan, G.; Chauhan, B.S. Nonconventional Weed Management Strategies for Modern Agriculture. Weed Sci. 2015, 63, 723–747. [Google Scholar] [CrossRef]
  72. Pearson, D.E.; Ortega, Y.K.; Runyon, J.B.; Butler, J.L. Secondary invasion: The bane of weed management. Biol. Conserv. 2016, 197, 8–17. [Google Scholar] [CrossRef] [Green Version]
Diversity 13 00118 g001 550
Figure 1. Flow chart of target-site resistance (TSR) diagnostic method using the following steps: (i) Next generation sequencing (NGS) Transcriptome analysis (NGS-TA). Open reading frames of target enzymes were identified based on transcriptome database; (ii) Sanger sequencing method (SS). Specific primers were designed covering the mutation points, fragments were amplified by PCR, PCR products were cloned and sequenced; (iii) Next-generation sequencing-Targeted amplicon sequencing (NGS-TAS) method. PCR products were sequenced on Illumina MiSeq550 platform resulting 300 bp paired-end reads that were sorted based on primer motifs, assembled, and grouped.
Figure 1. Flow chart of target-site resistance (TSR) diagnostic method using the following steps: (i) Next generation sequencing (NGS) Transcriptome analysis (NGS-TA). Open reading frames of target enzymes were identified based on transcriptome database; (ii) Sanger sequencing method (SS). Specific primers were designed covering the mutation points, fragments were amplified by PCR, PCR products were cloned and sequenced; (iii) Next-generation sequencing-Targeted amplicon sequencing (NGS-TAS) method. PCR products were sequenced on Illumina MiSeq550 platform resulting 300 bp paired-end reads that were sorted based on primer motifs, assembled, and grouped.
Diversity 13 00118 g001
Diversity 13 00118 g002 550
Figure 2. The schematic representation of (a), psbA; (b), ahas; (c), epsps, and (d), ppx2 genes in A. artemisiifolia indicating regions amplified by different primers. Vertical grey lines indicate amino acid positions that contain substitutions in herbicide resistant plants. The number after the amino acid refers to the amino acid position. Green boxes indicate exons and grey lines between boxes indicate introns. Colour lines show positions of primer pairs.
Figure 2. The schematic representation of (a), psbA; (b), ahas; (c), epsps, and (d), ppx2 genes in A. artemisiifolia indicating regions amplified by different primers. Vertical grey lines indicate amino acid positions that contain substitutions in herbicide resistant plants. The number after the amino acid refers to the amino acid position. Green boxes indicate exons and grey lines between boxes indicate introns. Colour lines show positions of primer pairs.
Diversity 13 00118 g002
Diversity 13 00118 g003 550
Figure 3. Amino acid mutations in investigated gene products. Imidazolinone and urea resistant bulked samples were analyzed by NGS-TAS that covered 16 known resistance-conferring mutations sites in A. artemisiifolia. Marking: green, possible mutation sites; red, mutant amino acids. DNA sequencing revealed that an inferred leucine for tryptophan substitution at amino acid position 574 in AHAS enzyme was responsible for the imazethapyr herbicide resistance. Amino acid substitution at the position 219 (valine/isoleucine) in psbA gene product, D1 protein, was responsible for the linuron resistance. Amino acid substitutions in EPSPS and PPX2 enzymes at known resistance-conferring mutations sites were not found.
Figure 3. Amino acid mutations in investigated gene products. Imidazolinone and urea resistant bulked samples were analyzed by NGS-TAS that covered 16 known resistance-conferring mutations sites in A. artemisiifolia. Marking: green, possible mutation sites; red, mutant amino acids. DNA sequencing revealed that an inferred leucine for tryptophan substitution at amino acid position 574 in AHAS enzyme was responsible for the imazethapyr herbicide resistance. Amino acid substitution at the position 219 (valine/isoleucine) in psbA gene product, D1 protein, was responsible for the linuron resistance. Amino acid substitutions in EPSPS and PPX2 enzymes at known resistance-conferring mutations sites were not found.
Diversity 13 00118 g003
Table
Table 1. Detailed information of gene structures and coding sequences (cds) of psbA, ahas, epsps, and ppx2 genes.
Table 1. Detailed information of gene structures and coding sequences (cds) of psbA, ahas, epsps, and ppx2 genes.
Gene NamecdsComplete Gene
Length (bp)Lenght (aa)Similarity (%)Reference ID
NCBI GeneBank		Contig ID
NCBI GeneBank
GEZL01000001		NCBI AccessionGC Content
(%)		Length (bp)Intron NumberIntron Position
from…to		NCBI AccessionGC Content
(%)
psbA106235399%A. artemisiifolia
AB427162.1		TR92155|c0_g1_i1MT42520341.71062--MT87974641
ahas196565495%Xanthium sp. AAA74913.1TR49503|c0_g3_i1
TR49503|c0_g8_i1		MK09676048.11965--MT41595448.3
epsps153951296%Helianthus annuus XP_022017499.1TR44247|c0_g1_i1MK0967654535397316…1311
1557…1832
1987…2114
2330…2410
2529…2656
2868…3006
3069…3400		MT415955
MT409110		34
37.5
ppx2147649195%Helianthus annuus
XP_021982414.1		TR33881|c0_g1_i1MK09676242.8Partial
325		156–276MT879747 MT87974834.3
33.1
Table
Table 2. Concentrations of PCR product (cc: ng/µL) and numbers of contig in each group in imidazolinone (imazethapyr) resistant bulked samples (AMI) and urea (linuron) resistant bulked samples (AMU).
Table 2. Concentrations of PCR product (cc: ng/µL) and numbers of contig in each group in imidazolinone (imazethapyr) resistant bulked samples (AMI) and urea (linuron) resistant bulked samples (AMU).
FragmentsLength of
Fragment
with Adapter
(bp)		AMIAMU
1 Sample2 Sample3 Sample1 Control Sample1 Sample2 Sample3 Sample1 Control Sample
ccNumber
of
Contig		ccNumber
of
Contig		ccNumber
of
Contig		ccNumber
of
Contig		ccNumber
of
Contig		ccNumber
of
Contig		ccNumber
of
Contig		ccNumber
of
Reads
psbA37750.326,98932.834,59440.830,56072.132,59224.328,10619.128,52319.930,49248.340,178
ahas 128810,00925,81711,80260.39129806621,40112,70924.311,426
ahas 227345,61332,64145,88750.334,15843,41147,52550,63543.452,289
ahas 331918,48815,10623,63974.320,21025,58021,73819,6123723,140
ahas 445312,56313,66811,95588.617,56713,13315,54915,85437.112,032
epsps31021,54334,05329,77951.916,59918,10310,83917,47631.715,737
ppx239011,580928026,65958.810,54615,20510,108934637.515,583
Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Share and Cite

MDPI and ACS Style

Kutasy, B.; Farkas, Z.; Kolics, B.; Decsi, K.; Hegedűs, G.; Kovács, J.; Taller, J.; Tóth, Z.; Kálmán, N.; Kazinczi, G.; et al. Detection of Target-Site Herbicide Resistance in the Common Ragweed: Nucleotide Polymorphism Genotyping by Targeted Amplicon Sequencing. Diversity 2021, 13, 118. https://doi.org/10.3390/d13030118

AMA Style

Kutasy B, Farkas Z, Kolics B, Decsi K, Hegedűs G, Kovács J, Taller J, Tóth Z, Kálmán N, Kazinczi G, et al. Detection of Target-Site Herbicide Resistance in the Common Ragweed: Nucleotide Polymorphism Genotyping by Targeted Amplicon Sequencing. Diversity. 2021; 13(3):118. https://doi.org/10.3390/d13030118

Chicago/Turabian Style

Kutasy, Barbara, Zoltán Farkas, Balázs Kolics, Kincső Decsi, Géza Hegedűs, Judit Kovács, János Taller, Zoltán Tóth, Nikoletta Kálmán, Gabriella Kazinczi, and et al. 2021. "Detection of Target-Site Herbicide Resistance in the Common Ragweed: Nucleotide Polymorphism Genotyping by Targeted Amplicon Sequencing" Diversity 13, no. 3: 118. https://doi.org/10.3390/d13030118

APA Style

Kutasy, B., Farkas, Z., Kolics, B., Decsi, K., Hegedűs, G., Kovács, J., Taller, J., Tóth, Z., Kálmán, N., Kazinczi, G., & Virág, E. (2021). Detection of Target-Site Herbicide Resistance in the Common Ragweed: Nucleotide Polymorphism Genotyping by Targeted Amplicon Sequencing. Diversity, 13(3), 118. https://doi.org/10.3390/d13030118

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

Article Metrics

Back to TopTop