Functional Characterization of Glutathione Peroxidase Genes Reveals Their Contribution to the Rapid Range Expansion of Amaranthus palmeri Under Stress Conditions

Abstract

Amaranthus palmeri is an aggressive, highly invasive weed that thrives across a wide range of adverse environments worldwide; nevertheless, the mechanisms underlying its rapid expansion remain largely unstudied. Glutathione peroxidase (GPX) is a crucial enzyme within the antioxidant defense system, belonging to the phylogenetic conserved family of oxidoreductases present in all living organisms. Despite its significance, the role of GPX in A. palmeri has not been reported. This study identified eight GPX genes (ApGPXs) in A. palmeri through comprehensive bioinformatics and gene expression analyses. The research examined the characteristics, evolutionary relationships, chromosomal mapping, gene structure, subcellular localization, conserved motifs, and cis-acting elements of these genes, as well as their evolutionary conserved functions in relation to Arabidopsis thaliana GPXs and RT-qPCR analysis under various stress conditions. The ApGPXs were distributed across scaffolds (2, 4, and 12) of the A. palmeri genome. Phylogenetic analysis grouped GPX genes into four subgroups, and conserved motifs were found within certain phylogenetic subgroups. We identified Actin8 as the most stable internal reference gene for A. palmeri under diverse stress conditions. Gene expression analysis revealed that ApGPXs participate in both early and late regulatory responses to oxidative stress induced by NaCl, high temperature, osmotic pressure, and glufosinate ammonium. The Arabidopsis GPX mutant (AT4G31870) exhibited a stronger flg22-induced oxidative burst than the wild type, and qPCR confirmed that AtGPXs contribute significantly to glufosinate ammonium stress responses. Evolutionary analysis found high sequence similarity between ApGPX4 and AT1G63460, as well as ApGPX3 and AT4G11600. Also, ApGPX3 and AT4G11600 shared similar expression patterns under glufosinate ammonium stress. This research presents the first gene family study in A. palmeri and provides foundational insights for future studies in this economically critical species. Our findings establish a framework for mitigating A. palmeri’s impact on crop production and exploring ApGPXs in developing herbicide- and stress-tolerant cultivars.

1. Introduction

Plants experience a wide range of environmental stresses that trigger signal-transduction pathways, leading to molecular, metabolic, and physiological responses that help organisms adapt and survive. Environmental stresses are unavoidable disturbances in the natural environment, which affect the plant by means of various modes. Stress causes the generation of excessive reactive oxygen species (ROS), which has a negative impact on the growth, development, and productivity of plants [1,2]. ROS are the highly reactive chemical species that are produced as a natural by-product of plant cellular metabolism. When ROS concentration exceeds its normal range, it causes cell damage by degrading lipids, proteins, and nucleic acids, ultimately leading to cell death [3]. Despite their destructive effect, ROS are also considered important secondary messengers in cell signaling and also help to maintain redox homeostasis. Among the ROS, hydrogen peroxide (H₂O₂) is the most relevant due to its reactivity, ability to diffuse, and longer half-life compared to other ROS, such as superoxide radicals (O₂⁻), hydroxyl radicals (OH), and singlet oxygen (½O₂) [4]. ROS must be tightly regulated by the antioxidant and redox systems, which are composed of proteins capable of transferring electrons from input elements to downstream target proteins. These transmitters are a large family of oxidoreductase proteins in plants, including thioredoxins (TRXs), TRX-like proteins, and glutaredoxins (GRXs) [1,4].

Glutathione peroxidase (GPX) is a key enzyme in the antioxidant system, classified within a family of phylogenetically related oxidoreductases that are present across all living organisms. GPXs facilitate the reduction of H₂O₂ or organic hydroperoxides into water or corresponding alcohols, while simultaneously oxidizing reduced glutathione (GSH, γ-Glu-Cys-Gly) or thioredoxin (TRX). Plant GPXs share the highest similarity with the animal GPX4 isoenzyme; however, the active sites of plant enzymes contain cysteine instead of selenocysteine and typically favor the TRX regeneration system over GSH [5]. The GPX gene family was first discovered in blue-green algae [6,7]. Although the functions of plant GPXs are still not well understood, they exhibit variability in cellular localization. This localization is vital for their protective roles against biotic stress, as it influences their effectiveness [8,9]. In chloroplasts, during pathogen attacks, the production of ROS can rise dramatically, and GPX plays a role in alleviating this stress by safeguarding photosynthetic components and potentially decreasing programmed cell death (PCD) [8]. In peroxisomes, where various antioxidant enzymes are located, GPXs also help regulate H₂O₂ levels during biotic stress [10]. In the nucleus, GPXs protect DNA from oxidative harm and contribute to the regulation of gene expression in response to stress [11].

Studies on the GPX family in relation to plant stress and growth regulation have been conducted in various plant species. Overexpression of two potential GPX genes from Triticum aestivum in A. thaliana resulted in changes to the transcript levels of genes associated with salt stress responses (SOS1 and RbohD) and abscisic acid (ABA) regulation (ABI1 and ABI2) [12]. The Arabidopsis protein AtGPXL3 interacts with the 2C-type protein phosphatases ABI1 and ABI2, functioning as an oxidative signaling transducer in ABA and drought stress responses by promoting stomatal closure through the activation of plasma membrane Ca²⁺ and K⁺ channels. Additionally, AtGPXL3 interacts with transcription factors such as dehydration-responsive element-binding proteins (DREB2A and DREB2B) via the CEO1 interacting protein, which regulates genes related to plant responses to dehydration and heat stress [13]. When rice OsGPX3 was silenced, there was a noticeable reduction in chlorophyll content, photosystem II activity, CO₂ assimilation rate, stomatal conductance, and intercellular CO₂ partial pressure, along with an increase in H₂O₂ levels in roots. Furthermore, OsGPX3 may play a role in epigenetic regulation through DNA methylation [14]. Four maize ZmGPXs exhibited splice variants, and their varying expression in stress-tolerant versus sensitive genotypes under drought and waterlogging conditions suggests that splicing mechanisms targeting ZmGPX RNAs are involved in effective stress responses [15]. GPXs have been noted for their key function in providing resistance to phytopathogens [16]. They are essential for maintaining redox homeostasis in plants during both normal and stressful conditions [17]. Increased expression change of AtGPXL2, AtGPXL3, and AtGPXL8 have been observed during the seed germination process in Arabidopsis [18]. In rice, depletion of GSH and inhibition of GPX activity led to high ROS accumulation in zygotic/embryonic nuclei, adversely affecting early embryonic development [19].

Palmer amaranth (A. palmeri S. Watson) is a highly competitive, dioecious annual herb indigenous to the southern United States and Mexico. It has rapidly expanded beyond its original range after being introduced to Europe and the broader Mediterranean region, and it is regarded as one of the most economically damaging weed species affecting cropping systems in the United States. A. palmeri is drought-tolerant and resilient, showcasing high adaptability due to its notable genetic and phenotypic plasticity and efficient resource utilization [20,21,22]. It is particularly notorious for rapidly developing resistance to herbicides across multiple sites of action, with resistance reported in various countries [23]. Under continuous water stress, A. palmeri can survive and produce over 14,000 seeds per plant [24]. Seeds produced under water-limited conditions tend to be heavier, less dormant, and germinate more quickly [25]. A. palmeri is viewed as a significant threat to conventional tillage systems in summer plant regions [26]. This highlights the necessity to identify stress-regulatory genes within the A. palmeri genome involved in various stress responses. To address this gap, in this study, we conducted the first genome-wide study of A. palmeri, focusing on the GPX gene family under abiotic stress conditions.

Previous research has conducted genome-wide analyses of GPX genes in various species, linking them to different stress and developmental regulatory conditions [15,27,28]. However, the role of GPX genes in A. palmeri concerning stress and herbicide regulation remains unexplored. In the present study, bioinformatics methods will be employed to identify ApGPX genes and analyze their physiochemical properties. Expression analyses will assess the regulatory roles of ApGPXs under NaCl, glufosinate ammonium, high temperature, and PEG6000-induced osmotic stress. The results of this study will provide a foundation for future research on ApGPX genes and their potential application in managing A. palmeri in agricultural settings, as well as in developing stress-resistant crop varieties through molecular breeding of economically important crops, including rice, wheat, and maize.

2. Materials and Methods

2.1. Identification and Physicochemical Properties of ApGPX Proteins

Two approaches were utilized to identify the ApGPX proteins. First, the genomic and annotation data for A. palmeri were obtained from the Comparative Genomics research (CoGe) database (https://genomevolution.org/coge/ accessed on 16 October 2024). The HMM profile for the GPX domain (PF00255) was sourced from the Pfam database (http://pfam.xfam.org/ accessed on 16 October 2024). The simple HMM search feature in TBtools v2.310 [29] was employed to search for GPXs using the protein sequences of A. palmeri along with the retrieved Pfam HMM file.

Second, protein sequences of GPX from A. Arabidopsis (AtGPXs) [11], Brassica napus (BnGPXs) [30], wheat (TaGPXs) [31], and cucumber (CsGPXs) [32] were collected from the NCBI (https://www.ncbi.nlm.nih.gov/ accessed on 18 October 2024) and Ensembl Plants (https://plants.ensembl.org/ accessed on 18 October 2024) databases. A BLASTp (https://blast.ncbi.nlm.nih.gov/Blast.cgi?PROGRAM=blastp&PAGE_TYPE=BlastSearch&LINK_LOC=blasthome accessed on 18 October 2024) search was conducted between the AtGPX, BnGPX, TaGPX, and CsGPX sequences and the protein sequences of the A. palmeri genome using the Blast Several Sequences to a Big Database tool in TBtools, with an E-value threshold of 1 × 10⁻⁵. The candidate ApGPX proteins identified through these two methods were merged and screened using the NCBI conserved domain (CDDv3.21-62456 PSSMs) and SMART (http://smart.embl.de/ accessed on 19 October 2024) databases, using default settings to eliminate redundant, unmatched, and incomplete protein sequences. The identified ApGPX genes were subsequently renamed from ApGPX1 to ApGPX8.

2.2. Characteristic Analysis of ApGPX Protein

The ExPASy-ProtParam (https://www.expasy.org/resources/protparam accessed on 25 October 2024) software was used to analyze the physicochemical characteristics of the ApGPX genes, such as molecular weight (MW), isoelectric point (pI), instability index, grand average of hydropathicity (GRAVY), and amino acid count (aa). The 3D modeling of the ApGPX proteins was performed using the SWISS-MODEL (https://swissmodel.expasy.org/ accessed on 25 October 2024) program. The SOPMA online software (https://npsa.lyon.inserm.fr/cgi-bin/npsa_automat.pl?page=/NPSA/npsa_sopma.html accessed on 25 October 2024) was used to predict the protein secondary structure.

2.3. Phylogenetic Analysis of the GPX Gene Family

The GPX protein sequences for Amaranthus hypochondriacus (AhGPXs), Amaranthus tuberculatus (AtuGPXs), Amaranthus hybridus (AhyGPXs), Amaranthus cruentus (AcGPXs), A. thaliana (AtGPXs), Panicum virgatum (PvGPXs), Portulaca amilis (FUGPXs), and Solanum lycopersicum (SlGPXs) were obtained from the Phytozome v13 and Amaranth Genomic Resource (AGRDB) [33] databases using a BLASTp search with an E-value of 1 × 10⁻⁵. A phylogenetic analysis was performed on the protein sequences of 8 ApGPXs, 7 AhGPXs, 7 AtuGPXs, 4 AhyGPXs, 5 AcGPXs, 8 AtGPXs, 6 FUGPXs, 7 SlGPXs, and 10 PvGPXs utilizing MEGA 11 software. This analysis employed the ClustalW program with default settings, and the Neighbor-Joining (NJ) method was used to construct the phylogenetic tree. A bootstrap analysis with 1000 replicates was conducted using the Jones-Taylor-Thornton (JTT) model, uniform rates, and pairwise deletion [34]. The iTOL program was applied to edit and enhance the visualization of the GPX protein phylogenetic tree [35].

2.4. Subcellular Localization Analysis of ApGPX Genes

The subcellular localization of ApGPXs was predicted using the online software WoLFPSORT (https://wolfpsort.hgc.jp/ accessed on 1 November 2024). To confirm the predicted localization of ApGPXs, the full-length coding sequence (CDS) of ApGPX3 was amplified with primers ApGPX3-GFP-F/R (Supplementary Table S1) and fused to the C-terminus of the green fluorescent protein (GFP) gene in the pCAMBIA1302-GFP overexpression vector. The resulting recombinant plasmid, ApGPX3-GFP, was transformed into Agrobacterium tumefaciens strain GV3101 using the freeze–thaw method. The transformed GV3101 was cultured in solid LB medium at 28 °C for 48 h. A single positive colony was then inoculated into fresh medium and shaken overnight. The bacterial cells were centrifuged and resuspended in infiltration buffer. For transient expression, the Agrobacterium suspension was injected into the abaxial side of 4-week-old Nicotiana benthamiana leaves using a needleless syringe. The empty pCAMBIA1302-GFP vector served as a positive control for GFP localization. After infiltration, the plants were kept in the dark for 24 h and then grown under normal light conditions for 48 h before imaging. GFP fluorescence was observed using a laser scanning confocal microscope.

2.5. Conserved Motifs, Gene Structure, Chromosome Mapping, and Duplication Analyses

The MEME Suite online program (https://meme-suite.org accessed on 5 November 2024) was utilized to investigate a conserved structural domain within the ApGPX genes, applying default settings and specifying the number of motifs to be 10 [36]. The gene structures of the ApGPXs were analyzed using the BioSequence Structure Illustrator feature in TBtools, with the A. palmeri genome annotation GFF3 file as the reference. The locations of ApGPX genes on the scaffolds of A. palmeri were mapped using the genome annotation GFF3 file and the Gene Location Visualizer tool in TBtools software. To identify duplicated pairs of ApGPX, sequence alignments were conducted with ClustalW, followed by analysis with the duplication tool in MEGA11. For these duplicated genes, the non-synonymous/synonymous substitution ratio (Ka/Ks) was calculated using TBtools’ Simple Ka/Ks Calculator. The timing of duplication events was estimated using the formula T = Ks/2λ × 10⁻⁶ million years ago (Mya), with λ set at 6.5 × 10⁻⁹ substitutions/site/year [37].

2.6. Cis-Acting Elements Analysis

The promoter region located upstream of the ApGPX genes, extending 2 kb, was predicted using the PlantCARE database [38]. TBtools was used to visualize the ApGPX genes cis-acting regulatory elements.

2.7. Prediction of miRNA-ApGPXs and Protein–Protein Interaction (PPI) Network

Putative miRNAs of A. palmeri were obtained from the online AGRDB (nbpgr.ernet.in:8080/AmaranthGRD/downloads.aspx accessed on 18 November 2024) database. These miRNAs, along with the CDSs of ApGPXs, were analyzed utilizing the psRNATarget online platform (https://www.zhaolab.org/psRNATarget/ accessed on 18 November 2024) with default settings to predict potential interactions between miRNAs and ApGPXs [39]. The protein sequences of ApGPXs were submitted to the STRING v12.0 database (http://string-db.org accessed on 18 November 2024), using the A. thaliana genome as a reference. After performing a BLAST analysis, orthologous proteins from STRING with Arabidopsis that exhibited higher sequence identity and an E-value of 1 × 10⁻⁵ were identified and used to construct the ApGPXs protein–protein interaction (PPI) network [40]. The predicted interactions between miRNA-ApGPXs and the PPI network were visualized using Cytoscape v3.10.2 [41].

2.8. Plant Material and Treatment Conditions

The seeds of A. palmeri were utilized in this study. The seeds were surface-sterilized using a 1% hypochlorite solution, thoroughly washed with distilled water, and germinated on Petri dishes with filter paper in a growth room maintained at an average humidity of 60%. The conditions included a day/night temperature cycle of 25 °C and a light/dark cycle of 16 h light and 8 h dark. For the NaCl (200 μM) and osmotic stress (20% PEG6000) treatments, three biological replicate seedlings were transferred to a hydroponics tray with a half-strength diluted Hoagland nutrient solution (pH 6.0). For the glufosinate ammonium (100 μM) and high temperature (40 °C) treatments, three biological replicate seedlings were transplanted into soil-filled plastic pots. Treatments were performed at the five-leaf stage, and leaf samples were collected in three technical replicates at various time points: 0 h, 24 h, and 48 h for NaCl; 0 h, 12 h, 24 h, 36 h, 48 h, and 72 h for glufosinate ammonium; and 0 h, 12 h, 24 h, 48 h, and 72 h for PEG6000 and high-temperature treatments. Samples were immediately frozen in liquid nitrogen and stored at −80 °C.

2.9. Selection and Analysis of Internal Reference Genes

To identify appropriate internal reference genes (RGs) for ApGPXs qPCR analysis, the CDSs of A. thaliana internal RGs (18sRNA, Actin2, Actin7, Actin8, Tub2, Tub4, Tub6, Tub8, GAPA2, GAPC2, and UBQ) were retrieved from the NCBI database and subjected to a BLAST search against A. palmeri sequences to identify the most similar genes as potential internal references, with an E-value threshold of 1 × 10⁻⁵. Primers for the selected candidate’s internal RGs were designed using Primer3Plus v3.3.0 (https://www.primer3plus.com/ accessed on 1 December 2024) (Supplementary Table S1). The expression stability of the internal RGs in A. palmeri seedlings treated with NaCl, glufosinate ammonium, high temperature, and osmotic stress was assessed using NormFinder [42], BestKeeper [43], RefFinder [44], the delta Ct method [45], and GeNorm [46]. Raw Cq values were utilized for the BestKeeper, RefFinder, and delta Ct analyses, while for GeNorm and NormFinder, the raw Cq values were converted into relative quantities [47].

2.10. RNA Extraction and Real-Time Quantitative PCR Analysis

Total RNA was extracted from the fully expanded treatment leaves collected at 0 h, 12 h, 24 h, 36 h, 48 h, and 72 h as described in Section 2.8 using TRIzol reagent (Invitrogen, Gaithersburg, MD, USA), following the manufacturer’s guidelines. The purity and concentration of the RNA were evaluated using agarose gel electrophoresis and a NanoDrop 2000 spectrophotometer (Thermo Scientific, Waltham, MA, USA). cDNA synthesis was carried out with HiScript IV RT SuperMix for qPCR (+gDNA wiper) (Vazyme Biotech, Nanjing, China), according to the manufacturer’s instructions. Gene-specific primers were designed using the Primer3Plus software. qPCR was performed in a 20 µL reaction using ChamQ SYBR qPCR Master Mix (Vazyme, Nanjing, China) on a Bio-Rad C1000 Touch Thermal Cycler (Hercules, CA, USA). The thermal cycling protocol included stage 1 at 95 °C for 30 s; stage 2 at 95 °C for 10 s and 60 °C for 30 s for a total of 40 cycles; and stage 3 at 94 °C for 2 min, followed by 65 °C for 0.5 s, and 94 °C for 20 s. Each sample was analyzed in triplicate, and gene expression changes were calculated using the 2^−ΔΔCT method [48]. Actin8 was used as the internal RG (Supplementary Table S1). A two-way ANOVA was conducted to evaluate the statistical differences in ApGPX gene expression among the treatment groups using GraphPad Prism v10.2.0 software, with a p-value of ≤0.05 deemed statistically significant [49].

2.11. Oxidative Burst Assay

Leaf disks from 4-week-old AtGPX7 mutants (AT4G31870) and wild-type (Col-0) plants were submerged in distilled water (30 mL, replaced every 30 min), wrapped in foil, and kept in the dark for 2 h with three biological replicates. The disks were then moved to a white 96-well plate containing 200 µL of water and incubated overnight in darkness. The water was replaced with 200 µL of a 1.25× luminol/HRP working solution, followed by the addition of 50 µL of bacterial flagellin (flg22) to achieve a final concentration of 100 nM. Chemiluminescence was immediately measured using a microplate reader (λ = 425 nm). Control wells contained luminol/HRP without flg22. Col-0 seedlings underwent surface sterilization using 0.15% HgCl₂ for 30 s, followed by 75% ethanol for 10 min, and were then rinsed three times with sterilized distilled water. The sterilized seeds were germinated in Murashige and Skoog (MS) media at 25 °C and 60% humidity under a 16 h light/8 h dark cycle. After germination, three biological replicates of the seedlings were transplanted into soil and grown for 4 weeks. Plants were treated with 20 µM glufosinate-ammonium, and three technical replicates of the rosettes were collected at 0, 12, 24, and 36 h. The samples were quickly frozen and stored at −80 °C for later analysis. Total RNA extraction, quality assessment, cDNA synthesis, and qPCR were conducted as detailed in Section 2.10.

3. Results

3.1. Identification and Characteristic Features of ApGPX Genes

A total of nine ApGPX protein sequences were initially identified through the two BLAST methods. After screening with the NCBI CDD and SMART databases, eight ApGPX genes were confirmed to contain characteristic thioredoxin-like domains. These eight ApGPXs were selected for further analysis of their physicochemical properties. The deduced protein sequences varied in length from 129 to 571 aa, with an average length of 283.12 aa (Supplementary Table S2). The theoretical isoelectric points ranged from 4.76 to 9.35, averaging 6.81. Their molecular weights varied between 14.17 and 64.55 kDa, with an average of 31.77 kDa. All ApGPX proteins exhibited instability index values from 23.52 to 38.16. The aliphatic index ranged from 78.53 to 84.86, with a mean of 81.23, while the GRAVY scores varied from −0.44 to −0.06, averaging −0.29, indicating that these proteins are generally hydrophilic.

The secondary structure analysis of the ApGPX proteins shows that ApGPXs have four structural forms: alpha helix, beta turn, random coil, and extended strand. Among these, alpha helix (21.31–40.46) and random coil (36.08–58.61) were the main secondary structures; the beta turn (4.92–8.28) and extended strand (14.23–21.76) protein secondary structures were smaller (Supplementary Table S3). Three-dimensional analysis of the ApGPXs shows that ApGPX5 and ApGPX6 are less structured, which confirms their higher random coil secondary structure (Figure 1). ApGPX7 and ApGPX8, which have higher alpha helices, were shown to have complex 3D structures.

3.2. Evolutionary Relationships of GPX Proteins

To explore the evolutionary relationships within the GPX gene family, a comprehensive phylogenetic analysis was performed using 62 GPX proteins. This set included 8 ApGPXs, 7 AhGPXs, 7 AtuGPXs, 4 AhyGPXs, 5 AcGPXs, 8 AtGPXs, 6 FUGPXs, 7 SlGPXs, and 10 PvGPXs. The phylogenetic clustering classified the 62 proteins into four distinct subgroups, with ApGPXs evenly distributed across these groups, featuring two genes in each. Specifically, subgroup I contained 20 GPXs, subgroup II had 12, and there were 15 in both subgroups III and IV. GPX proteins from ApGPXs, AhGPXs, AtuGPXs, AhyGPXs, AcGPXs, AtGPXs, FUGPXs, SlGPXs, and PvGPXs were found in all four subgroups (Figure 2). We found that AT4G11600, ApGPX3, and ApGPX2 were grouped in subgroup I; AT4G31870, AT2G25080, ApGPX5, and ApGPX6 in subgroup II; AT2G31570, AT2G43350, AT1G63460, ApGPX1, and ApGPX4 in subgroup III; whereas AT3G63080, AT2G48150, ApGPX7, and ApGPX8 were found in subgroup IV. Also, ApGPX4 and ApGPX5 were clustered together on a terminal branch with Atube003984.1 and Atube024717.1, respectively. These results indicate a conserved evolutionary relationship within the GPX gene family across species.

3.3. Subcellular Localization of ApGPX3

Predictions of subcellular localization using WoLFPSORT revealed a diverse distribution of ApGPX genes across various organelles. Specifically, ApGPX5 and ApGPX6 were predicted to localize to both chloroplasts and mitochondria. In contrast, ApGPX7 and ApGPX8 were expected to localize within the cytoplasm, chloroplast, and nucleus. Additionally, ApGPXs (1, 2, 3, and 4) were predicted to be distributed across the cytoplasm, chloroplast, and nucleus (Supplementary Table S2). To further confirm the subcellular localization predictions, we examined the transient expression of ApGPX3. We analyzed the localization of the 35S promoter-driven ApGPX3-GFP fusion protein in N. benthamiana, using the empty 35S:GFP vector as a control. Laser scanning confocal microscopy showed that the GFP fluorescence was present throughout the entire cell. Notably, the fluorescence of the ApGPX3-GFP fusion protein was specifically localized in the nucleus and the extracellular region (Figure 3). These findings support the predictions from the WoLFPSORT software, suggesting that ApGPX3 may be involved in regulating gene expression and cellular processes.

3.4. Conserved Motifs, Structure, Chromosome Mapping, and Duplication Analyses of ApGPX Genes

Conserved motif analysis revealed 10 putative motifs ranging from 6 to 50 aa, each appearing once per sequence (Figure 4A). The ApGPX proteins exhibited between 3 and 10 conserved motifs, with all proteins consistently containing motifs 1, 2, and 3. Notably, ApGPX proteins in phylogenetic subgroups II and IV contain all 10 motifs, while those in subgroup I have 6 to 7 motifs, and subgroup III proteins have 3 to 7 motifs. Well-characterized GSHP (PF00255) conserved domains, such as LAFPCNQF, WNFEKF, and VLLIVNVASKC, were found within motifs 1, 2, and 4, respectively. Several highly conserved residues, including Trp (W), Gln (Q), Cys (C), and Asn (N), suggest their possible roles in enzyme activity. Gene structure analysis indicated significant variation in the number of exons and introns among the ApGPXs, with no untranslated regions (UTRs) detected. Each ApGPX gene consisted of 4 to 7 exons and 3 to 6 introns, which typically had large structural lengths (Figure 4B). The absence of UTRs suggests a streamlined gene structure that may enhance expression efficiency.

To examine their chromosomal distribution, the eight ApGPXs were mapped onto the A. palmeri genome scaffolds using the corresponding GFF file. The genes were located on three scaffolds (Figure 5A). Scaffold 2 had the highest genes, ApGPXs (3, 4, 7, and 8). Scaffold 12 contained ApGPXs (2, 5, and 6), while Scaffold 4 had a single gene, ApGPX1. Genes on Scaffold 2 were linked to subgroups I, III, and IV, whereas those on Scaffold 12 were associated with subgroups I and II. The solitary gene on Scaffold 4 was classified in subgroup III. Gene duplication analysis identified 3 pairs of duplicated genes, which include one tandem duplication (ApGPX6/ApGPX5) (Figure 5B, Supplementary Table S4). To evaluate the evolutionary pressures on these genes, we calculated the Ka/Ks ratios for each pair. All ratios were significantly below 1.0, suggesting that strong purifying selection has influenced the evolution of ApGPXs. The estimated divergence times for the duplicated pairs, based on Ks values, ranged from 0.446 to 45.098 Mya (Supplementary Table S4). These results highlight the role of gene duplication in the expansion of the ApGPX family, indicating potential ancient origins and a conserved function in stress-response pathways in A. palmeri.

3.5. Cis-Acting Regulatory Elements of ApGPX Genes

Analysis of the 2 kb upstream promoter regions of the ApGPX genes uncovered various cis-acting regulatory elements related to plant stress responses and development. These elements were classified into three major categories: those associated with biotic and abiotic stresses (ABRE, as-1, DRE, STRE, W box, drought-inducibility, low temperature response, and anaerobic induction), light responsiveness (light response elements and circadian control), and phytohormonal regulation (ABA, auxin, ERE, gibberellin, MeJA, and salicylic acid response elements) (Figure 6). Light-responsive elements were present in all ApGPX promoters, with seven distinct elements involved in light reaction processes. Additionally, several cis-elements linked to phytohormone signaling and stress adaptation were identified, including those responsive to gibberellin, salicylic acid, ABA, and methyl jasmonate (MeJA). The promoters also contained elements related to drought and low-temperature responses, circadian rhythm regulation, defense mechanisms, and anaerobic induction.

3.6. Protein-Protein and miRNA-ApGPXs Target Interaction Network

To explore the integrated role of ApGPXs in the stress responses of A. palmeri, protein–protein interaction (PPI) analysis was conducted using the Arabidopsis reference genome via the STRING database. The resulting PPI network comprised eight Arabidopsis proteins, including one likely thiol-disulfide oxidoreductase (T13D8.29) (Figure 7A). Gene Ontology (GO) enrichment analysis of the network revealed that the associated biological processes were predominantly focused on responses to oxidative stress. The proteins were mainly localized within the cytosol, while the molecular functions showed significant enrichment for antioxidant activity and glutathione peroxidase activity. To gain further insights into the regulatory mechanisms of ApGPXs, interactions with miRNAs were analyzed. A total of 30 miRNAs were predicted to target six ApGPX genes (Figure 7B; Supplementary Table S5). Each ApGPX gene was targeted by 3 to 17 miRNAs, with ApGPX8 and ApGPX7 each interacting with 17 miRNAs. Additionally, ApGPX1 was targeted by 9 miRNAs, ApGPX3 by 7 miRNAs, and ApGPX4 by 3 miRNAs. These results suggest that miRNAs may significantly impact the post-transcriptional regulation of ApGPX gene expression.

3.7. Selection of Stable Internal Reference Gene

To determine the most stable internal reference genes (RGs) for A. palmeri, cDNA from both treatment and control samples underwent qPCR analysis. All primer pairs produced a single peak in the melting curve, confirming the specificity of the amplicons. PCR efficiency and correlation coefficients for each primer pair were calculated using the standard curve method. Data analysis was conducted according to the guidelines established by Bustin et al. [50]. Raw quantification cycle (Cq) values, which ranged from 20.98 to 32.35, were utilized to evaluate gene expression levels (Figure 8A). The expression stability of the selected internal RGs was assessed using five statistical algorithms: NormFinder, BestKeeper, RefFinder, the comparative delta Ct method, and GeNorm. Each algorithm produced a stability ranking from the most stable to the least stable gene. Although some discrepancies were noted among the methods, several results aligned. Notably, NormFinder, RefFinder, and the delta Ct method identified Actin8 as the most stable gene, followed by Actin7 (Supplementary Table S6). BestKeeper ranked Actin7 highest, with Actin8 coming in second. GeNorm analysis indicated that Actin8 and Actin7 had equal expression stability (SV = 0.391), making them the top candidates, closely followed by UBQ. Across all five methods, 18SRNA was consistently identified as the least stable reference gene (Figure 8B). Based on these comprehensive results, Actin8 was chosen as the most stable internal reference gene for A. palmeri and was subsequently used for normalization in the qPCR analysis of ApGPX gene expression.

3.8. Transcriptional Responses of the ApGPXs Under Different Treatments

To examine the roles of ApGPXs under various treatments, we performed qPCR analysis to assess the expression change of six ApGPX genes. Under salt treatment, the expression change of ApGPX4 and ApGPX6 decreased from 12 to 48 h but increased again at 72 h (Figure 9A). The expression of ApGPX3 and ApGPX8 was elevated during the first 12 h but declined in the subsequent treatment periods. In contrast, ApGPX5 showed a notable increase in expression from 36 to 72 h, while ApGPX2 had significantly lower expression compared to the control. With glufosinate ammonium treatment, the expression change of ApGPX (4, 5, and 6) remained low throughout the treatment period. Conversely, ApGPX (2, 3, and 8) were upregulated during the stress periods, each displaying distinct expression patterns (Figure 9B). Under high-temperature stress, the expression change of the ApGPXs were generally increased throughout the treatment duration, except for ApGPX2, which showed reduced expression after 3 h but significantly rose again at the 4 h mark (Figure 9C). During osmotic stress, the expression patterns of the ApGPXs were upregulated throughout the treatment, with the exception of ApGPX2, which significantly decreased after 72 h compared to the control (Figure 9D). The expression of the ApGPXs increased and peaked after 48 h, while ApGPX2 reached its peak after 24 h of treatment.

3.9. Oxidative Burst Assay, Expression Change, and Homology Analysis of AtGPXs

To further investigate the regulatory roles of ApGPXs, we examined the flg22-triggered oxidative burst in AtGPX7 mutant and wild-type (col-0) plants. The results indicated that ROS generation in response to flg22 was higher in the AtGPX7 mutant seedlings compared to col-0 (Figure 10A). This suggests that AT4G31870 acts as a negative regulator of ROS production during flg22-induced immune responses in Arabidopsis. Additionally, qPCR analysis was conducted to evaluate the regulatory effects of the eight Arabidopsis GPXs during herbicide stress. The data showed that the expression change of AT4G31870, AT2G31570, AT1G63460, and AT4G11600 were upregulated throughout the treatment periods (Figure 10B), indicating their significant role in mitigating glufosinate-induced ROS. Conversely, the expression of AT3G63080, AT2G25080, AT2G43350, and AT2G31570 decreased initially but increased after 36 h, suggesting that these genes may contribute to secondary defense or recovery processes.

Sequence homology analysis between ApGPX and AtGPX genes was conducted using Circoletto v25.03.23 software [51] and the MEGA 11 program. The analysis revealed that ApGPX4 and ApGPX3 share ≤99.9% sequence similarity with AT1G63460 and AT4G11600, respectively (Figure 10C). Additionally, ApGPX3 showed ≤75% similarity with AT2G31570, AT3G63080, and AT2G48150, while ApGPX6 shared ≤75% similarity with AT4G31870, AT2G43350, and AT2G25080. Phylogenetic analysis grouped ApGPXs and AtGPXs into three subgroups, with AT4G11600/ApGPX3, AT2G43350/ApGPX1, and AT1G63460/ApGPX4 clustered together on a terminal branch (Figure 10D). These findings indicate that ApGPXs have a high degree of homology with AtGPXs and may act as negative regulators of ROS production, facilitating effective immune responses and playing important roles in cellular protection and recovery during oxidative stress conditions in A. palmeri.

4. Discussion

The GPX family plays a significant role in maintaining redox homeostasis in plants during both normal and stressful conditions, including cold, drought, heat, and salinity [17]. However, their functions in the stress responses of A. palmeri have not been extensively studied. Understanding ApGPX functions is essential to explore the molecular mechanisms of A. palmeri’s stress tolerance, which may explain its invasiveness and herbicide resistance, and guide the development of targeted weed management and stress-resilient crop strategies. In this study, we identified eight ApGPX proteins and explored their regulatory roles in response to NaCl, glufosinate ammonium, high temperatures, and osmotic stress. The findings suggest that ApGPXs are involved in regulating various stress conditions in A. palmeri.

GPX genes have been identified and characterized in numerous plant species, including Zea mays, Sorghum bicolor, Cucumis sativus, T. aestivum, Oryza sativa, A. thaliana, S. lycopersicum, Citrus sinensis, Panax ginseng, and Hordeum vulgare [3]. It has been reported that plant GPXs differ in their cellular localization, which can include chloroplasts, mitochondria, cytoplasm, extracellular spaces, and nuclei; however, their functions remain poorly understood [8]. In O. sativa, five OsGPXs have been localized in chloroplasts, cytosol, and mitochondria [52]. In A. thaliana, a total of eight AtGPXs have been identified in various cellular locations, such as the plasma membrane, cytosol, chloroplasts, mitochondria, Golgi body, and the nucleus [53]. In our study, we identified 8 ApGPX genes, localized in chloroplasts, mitochondria, cytoplasm, and nucleus. These results imply that ApGPXs may play a role in managing oxidative stress, regulating cellular signaling, and detoxifying ROS. We further validated the predicted localization of ApGPX3 through transient expression in N. benthamiana, confirming its presence in the nucleus. This suggests that ApGPX3 likely protects DNA from oxidative damage, influences cell signaling pathways, and modulates cellular responses to oxidative stress in A. palmeri during stress conditions.

Plant GPXs are typically found in a monomeric form, and the alignment of various GPXs has revealed conserved amino acid motifs, such as ILAFPCNQF, GK(V/A)LLIVNVAS(R/Q/K)CG(L/F)(T/A), (LY(E/P/Q)KY(K/R)(T/D/E), KWNF(S/E/T)KFLVDK(E/N)G), P(L/V/I)Y(K/Q)FLK, and C(T/N)RF(K/OAE(Y/F)P(I/V)F(D/R/Q)KV(D/R)VNG [54,55]. In line with these findings, our analysis identified that the ApGPXs contain several known conserved motifs: ILAFPCNQF (motif 1), KWNFEKFLVDKNG (motif 2), PIYKFLK (motif 3), and VLLIVNVASKC (motif 4), indicating that these motifs are crucial for glutathione peroxidase activity. Previous research has shown that GPXs generally have four to six exons, with the number of introns varying from four to ten, exhibiting significant variability across species [15,18,28,32,56]. In our study, structural analysis revealed that ApGPXs have 4 to 7 exons and 3 to 6 introns, with no UTR present among the genes. This variability in exon and intron suggests evolutionary adaptability and functional diversity of GPX genes in different plant species. The lack of UTR in ApGPXs indicates a streamlined gene structure that may enhance expression efficiency [57].

To gain meaningful evolutionary insights, a phylogenetic analysis was conducted between ApGPX proteins and those from AhGPXs, AtuGPXs, AhyGPXs, AcGPXs, AtGPXs, FUGPXs, SlGPXs, and PvGPXs. This approach ensured the inclusion of lineage-specific conservation, ecological diversity, and well-annotated GPX proteins. The analysis revealed that ApGPX genes clustered into distinct clades, indicating conserved functional divergence. Most ApGPXs grouped closely with other Amaranthus homologs, indicating strong evolutionary conservation within the genus. Notably, ApGPX7 and ApGPX8 aligned with more distantly related species, suggesting potential neofunctionalization or adaptation to unique stress conditions. These findings imply that while certain ApGPX genes maintain ancestral roles, others may have acquired novel functions to potentially enhance A. palmeri resistance to environmental conditions.

Post-transcriptional regulation involves mechanisms that control the translation, stability, and localization of mRNAs. The functional information encoded in the sequence and structure of 3′UTRs is recognized and acted upon by various cellular regulatory factors (trans-acting factors). These factors include a range of non-coding RNAs, such as miRNAs and RNA-binding proteins, which interact with the sequences and structural elements encoded in 3′UTRs [58]. Diener et al. [59] noted that miRNA responsive elements (MREs) are typically found within the 3′UTRs of targeted mRNAs but can also occur in 5′UTRs or CDS [60]. Liu et al. [57] identified 71 bHLHs and 5 MYCs in Nymphaea colorata, observing that 29 of these genes were targeted by 28 miRNAs. Most genes with UTRs were targeted by 1 to 4 miRNAs; however, NcbHLH52, which lacks a UTR, was targeted by 7 miRNAs. Consistent with our findings, we identified 30 miRNAs that target 5 ApGPXs, with each gene being targeted by 3 to 17 miRNAs. This suggests potential alternative miRNA-binding mechanisms that may affect post-transcriptional gene regulation and stress-responsive modulation, independent of traditional UTR-mediated interactions, implying a possible non-canonical miRNA targeting within the CDS or intronic regions to facilitate efficient detoxification of ROS [61].

Normalizing results using one or more suitable internal reference genes (RGs) is a straightforward and widely accepted method for minimizing errors in qPCR assays. So far, only a limited number of internal RGs have been identified in A. palmeri under various stress conditions [62]. Notably, no internal RGs have been identified in response to NaCl, glufosinate ammonium, high temperatures, and osmotic stress. Therefore, it is important to identify suitable RGs for target gene expression analysis under different experimental conditions when developing a qPCR assay for gene family analysis in A. palmeri under stress. Previous studies have indicated that NormFinder and GeNorm are among the most reliable tools for assessing the stability of internal RGs [63]. Research involving rice [64], wheat [47,65], tomato [66], and cotton [67] utilized these algorithms to identify internal RGs. In this study, we employed NormFinder, BestKeeper, RefFinder, the Delta Ct method, and GeNorm algorithms to evaluate 11 potential internal RGs in A. palmeri for qPCR analysis under various stress conditions. Each tool produced slightly different results, yet the algorithms generally agreed on the most stable RGs. Specifically, NormFinder, RefFinder, and the Delta Ct method identified Actin8 as the most stable internal RG, followed by Actin7, while BestKeeper ranked Actin7 first, followed by Actin8. GeNorm indicated that Actin8 and Actin7 had equal stability. Based on these results, we selected Actin8 as the most stable internal RG for A. palmeri, and it was used to normalize the qPCR data under various stress conditions.

Numerous studies have indicated that GPXs are essential antioxidant enzymes that protect plant cellular mechanisms from environmental stresses. For instance, Gao et al. [68] reported that TsGPX genes exhibited tissue-specific expression under salt stress, with three TsGPXs significantly upregulated in leaves and six in root tissue. OsGPXs were shown to be activated under high salinity conditions [52]. Zhang et al. [69] found that the expression of five GPX isoforms increased in drought-stressed mulberry, and their overexpression enhanced both the antioxidant system and ROS-scavenging capacity, leading to improved drought tolerance in transgenic plants. A. palmeri has developed specific strategies to address various types of abiotic stress encountered during its growth [70]. These traits enhance its invasive potential, competitive ability, and capacity to develop resistance to multiple herbicide families [23,71]. A glufosinate-resistant accession has been utilized to explore the mechanisms behind glufosinate resistance in A. palmeri [72]. In the current study, we examined the expression change of ApGPXs under treatments of salt, glufosinate ammonium, high temperature, and PEG6000-induced osmotic stress. The biphasic response of ApGPX6 and ApGPX4 under salt treatment suggests an initial tolerance to ROS followed by a re-establishment of redox homeostasis during recovery. The early activation of ApGPX8 and ApGPX3 indicates immediate roles in ROS scavenging, while their subsequent decline may suggest a reallocation of energy. The sustained upregulation of ApGPX5 points to its potential role in managing prolonged oxidative stress. Under glufosinate ammonium treatment, the persistent upregulation of ApGPX2, ApGPX3, and ApGPX8 indicates their significant role in activating detoxification processes to regulate ROS and reduce cellular damage. Conversely, the downregulation of ApGPX4, ApGPX5, and ApGPX6 suggests greater susceptibility to glufosinate effects. During high-temperature and osmotic stress, the upregulation of ApGPXs highlights their key functions in alleviating oxidative damage caused by heat and cellular dehydration in A. palmeri. These findings imply that ApGPXs are likely involved in regulating the abiotic stress responses of A. palmeri.

Plant defense against pathogens is activated by the recognition of microbe-associated molecular patterns (MAMPs). The response to flg22, perceived by the pattern recognition receptor flagellin-sensing2, is the well-studied MAMP response. Yi et al. [73] discovered that the oxidative burst triggered by flg22 was more pronounced in SA or jasmonic acid (JA) mutants compared to wild-type plants. Recombinant proteins AtGPX2, AtGPX5, and AtGPX6 provide protection against stresses induced by copper, salt, and ROS [74]. Islam et al. [52] conducted a study on GPXs in rice and Arabidopsis under various stress conditions, including salt and oxidative stress, revealing that AtGPXs and OsGPXs may have evolved with distinct defensive roles against different stresses. In the present study, the flg22-triggered oxidative burst was greater in the AtGPX7 mutant compared to the wild type, suggesting that ApGPXs potentially serve as negative regulators of pattern-triggered immunity by mitigating excessive ROS production in Arabidopsis [75]. Gaber et al. [11] found that AT2G31570, AT3G63080, AT4G31870, and AT1G63460 were upregulated, while AT2G25080, AT2G43350, AT2G48150, and AT4G11600 were downregulated in Arabidopsis seedlings treated with paraquat. In the present study, qPCR analysis of AtGPXs under glufosinate ammonium shows that AT4G31870, AT1G63460, AT4G11600, and AT2G48150 were consistently upregulated throughout the treatment periods. These findings reinforce the role of AtGPXs in detoxifying oxidative damage induced by herbicides. Homology mapping revealed near-identical sequence identity between ApGPX4/AT1G63460 and ApGPX3/AT4G11600, indicating strong functional conservation among species. Expression analysis of ApGPXs under glufosinate ammonium showed consistent upregulation of ApGPX3 throughout the treatment periods, similar to the behavior of AT4G11600 under the same conditions. These results suggest that ApGPXs are key players in regulating oxidative defenses and likely reflect the redox modulation mediated by AtGPXs.

This study presents the first genomic characterization of the GPX gene family in A. palmeri. The expression profiles and structural features of the ApGPX genes provide strong insights into their potential role in A. palmeri’s remarkable invasiveness. The observed robust upregulation of ApGPXs under glufosinate ammonium, high temperature, and osmotic stress; their potential for rapid miRNA-mediated regulation due to the lack of UTRs; and their strategic localization across key cellular compartments collectively suggest a highly efficient system for managing oxidative stress. We hypothesize that this enhanced antioxidant capacity constitutes a significant adaptive trait, enabling A. palmeri to thrive under the diverse abiotic stresses during range expansion. This molecular adaptability likely influences its survival and competitive dominance and facilitates its rapid spread. Further studies are required to validate the proposed functional link between ApGPX activity and A. palmeri ecological success.

5. Conclusions

In this study, we identified and analyzed eight ApGPX genes that lack UTRs and were distributed across scaffolds 2, 4, and 12 of the A. palmeri genome. Phylogenetic analysis revealed that GPXs can be classified into four distinct subgroups, with conserved motif analysis indicating functional diversification within these groups. We evaluated the stability of 11 potential internal RGs for normalizing qPCR expression data and found that Actin8 is the most stable A. palmeri internal RG. Gene expression results suggest that ApGPXs play a vital role in maintaining cellular redox balance and protecting A. palmeri from oxidative damage under stress conditions such as salt, osmotic pressure, high temperatures, and glufosinate ammonium. AtGPX7 mutant was found to exhibit a stronger flg22-induced oxidative burst compared to the wild type, and qPCR analysis found that AtGPXs are involved in response to glufosinate ammonium. Evolutionary analysis and gene expression results discovered a closer similarity between AT4G11600 and ApGPX3 in managing oxidative damage induced by glufosinate ammonium. Further research is necessary to fully characterize ApGPXs and explore the conserved evolutionary functions between AtGPXs and ApGPXs under these stress conditions to discover the regulatory mechanisms behind ApGPXs’ stress responses. This study offers new insights into gene family analysis in A. palmeri and lays the groundwork for future investigations into the role of ApGPXs in stress regulation and development, which could significantly aid in managing the impact of A. palmeri on agricultural production and provide essential stress response genes for breeding economically important crops.