Skip to main content
Download PDF

Genome-wide identification of polyamine metabolism and ethylene synthesis genes in Chenopodium quinoa Willd. and their responses to low-temperature stress

BMC Genomics volume 25, Article number: 370 (2024) Cite this article

Abstract

Background

Quinoa (Chenopodium quinoa Willd.) is valued for its nutritional richness. However, pre-harvest sprouting poses a significant threat to yield and grain quality. This study aims to enhance our understanding of pre-harvest sprouting mitigation strategies, specifically through delayed sowing and avoiding rainy seasons during quinoa maturation. The overarching goal is to identify cold-resistant varieties and unravel the molecular mechanisms behind the low-temperature response of quinoa. We employed bioinformatics and genomics tools for a comprehensive genome-wide analysis of polyamines (PAs) and ethylene synthesis gene families in quinoa under low-temperature stress.

Results

This involved the identification of 37 PA biosynthesis and 30 PA catabolism genes, alongside 227 ethylene synthesis. Structural and phylogenetic analyses showcased conserved patterns, and subcellular localization predictions indicated diverse cellular distributions. The results indicate that the PA metabolism of quinoa is closely linked to ethylene synthesis, with multiple genes showing an upregulation in response to cold stress. However, differential expression within gene families suggests a nuanced regulatory network.

Conclusions

Overall, this study contributes valuable insights for the functional characterization of the PA metabolism and ethylene synthesis of quinoa, which emphasize their roles in plant low-temperature tolerance and providing a foundation for future research in this domain.

Peer Review reports

Background

Quinoa (Chenopodium quinoa Willd.) is an annual dicotyledonous herb of the family Amaranthaceae, cultivated for over 5,000 years [1]. Quinoa seeds are rich in protein and known as the “mother of grain.” By-products produced during seed production and processing, such as straw and bran, can be used as animal feed. Moreover, the leaves contain high levels of nutrients, such as protein, potassium, manganese, and copper, and can be consumed as a vegetable [2, 3].

In recent years, quinoa has become increasingly popular among the public, and the planting area has become increasingly extensive; however, the pre-harvest sprouting (PHS) has seriously affected the yield and quality of quinoa seeds [4, 5]. Appropriate delay in sowing for quinoa maturity to avoid the rainy season is a novel idea in reducing the quinoa PHS. However, certain high-altitude areas such as Shangri-La and other places in August begin to decline in temperature. Further, the nighttime temperatures can be reduced to < 0 ℃. Cultivating cold-resistant quinoa varieties is necessary to ensure that plants grow and develop normally under cold conditions. Additionally, many regions do not plant crops in winter, and quinoa, which is more resistant to cold, can utilize many winter fields. Harvesting nutrient biomass to feed livestock can also increase the income of farmers, even if it is not intended for seed harvesting. Therefore, studying the molecular mechanism of the low-temperature response in quinoa can provide genetic resources for cold-resistant breeding and theoretical guidance for popularizing quinoa cultivation.

Under low-temperature stress, plants experience disturbances in physiological processes including osmotic balance, photosynthetic carbon fixation, and lipid metabolism. When faced with adversity, plants activate defense mechanisms and generate responses to adapt to their environment. Polyamines (PAs), which are closely related to plant resistance, growth, and development, their levels increase in plants during abiotic stress such as salinity, extreme temperature, paraquat or heavy metals, particularly important for adaptation and resistance to cold stress, serving as crucial metabolites for responding to external stimuli [6, 7], and are a class of low-molecular-weight, aliphatic, nitrogen-containing bases with strong bioactivities that are widely present in prokaryotic and eukaryotic organisms, mainly including putrescine (Put), spermidine (Spd), spermine (Spm), thermospermine (Tspm) [8]. Under physiological pH conditions(7.0 ∼ 7.4.), PA carries a positive charge in plants and interacts with large biomolecules such as nucleic acids, proteins (enzymes), and phospholipids through hydrogen and macromolecular bonds, participating in various life processes, including the regulation of gene translation, expression, cell proliferation, and cell signal transduction, which are closely related to plant growth and development [9, 10]. They can also regulate the activity of certain ion channels, directly or indirectly participating in reactive oxygen species (ROS) metabolism in plants, act as signaling molecules in plant stress responses, and initiate the expression of resistance genes, such as those participating in responses to abiotic stresses including drought, cold, and salinity, which play an important regulatory role in plant resistance [11,12,13]. Two main pathways are known for PA synthesis in plant cells, the arginine decarboxylase pathway and the ornithine decarboxylase pathway, both use l-arginine as a substrate [14], as shown in Fig. 1 [15].

Fig. 1
figure 1

PA metabolism and ethylene synthesis pathway

Full size image

Arginine is converted to agmatine by the action of arginine decarboxylase (ADC, EC 4.1.1.19), which is then converted to N-carbamoylputrescine by the action of agmatine iminohydrolase (AIH, EC 3.5.3.12), followed by the catalysis of N-carbamoylputrescine amidohydrolase (CPA, EC 3.5.1.53) to form Put [15]. The second pathway involves the hydrolysis of arginine to remove urea, generating ornithine, which is then converted into Put via ornithine decarboxylase (ODC, EC 4.1.1.17) catalysis [16]. As a precursor for synthesizing other PAs, Put combines with an aminopropyl group catalyzed by spermidine synthase (SPDS, EC 2.5.1.16) to produce Spd. Spd is catalyzed by spermine synthase (SPMS, EC 2.5.1.22), thermospermine synthase (ACL5, EC 2.5.1.79), and an aminopropyl group to form Spm and Tspm, respectively.

As important plant growth regulators, the dynamic equilibrium of PAs related to their synthesis and catabolism. The catabolism of PAs is mainly catalyzed by copper-containing amine oxidases (CuAO, EC 1.4.3.6) and flavin-containing polyamine oxidases (PAO, EC1.5.3.17) [17]. Put is the central product of the PA biosynthesis pathway, and CuAO has a high affinity for Put, which is oxidatively deaminated to form H2O2, ammonia, and 4-aminobutanal catalyzed by this enzyme [17, 18]. PAO can be divided into two categories. The first group catalyzes Spd and Spm to produce 1,3-diaminopropane, H2O2 and N-(3-aminopropyl)-4-aminobutanal or 4-aminobutanal, which are involved in terminal catabolic (TC) pathways. The second type participates in the back conversion (BC) pathway, which converts Spm back to Spd, and Spd back to Put [18].

The function of PAs are largely realized through their synthesis and catabolism, and the in vivo balance of PAs is crucial [19]. Under adversity stress, some content or morphological changes in PA levels occur in plants, and to a certain extent, the strengthening of plant resistance to adversity is synchronized with the accumulation of PAs. In addition, the metabolites produced by PA decomposition play an important role in plant growth and development, stress tolerance, and defense. For example, H2O2 can be used as a signaling molecule to induce plant resistance, enhance the ability of the plant reactive oxygen species scavenging system, regulate the balance of reactive oxygen species metabolism, maintain the stable membrane structure of the cell, and is also a good mechanism to respond to adverse stress [20].

In the PA metabolic pathway, the aminopropyl group required for the synthesis of Spd, Spm, and Tspm is formed by S-adenosylmethionine decarboxylase (SAMDC, EC 4.1.1.50) catalyzed decomposition of S-adenosylmethionine (SAM) [19]. SAM is a ubiquitous methyl donor that is converted to 1-aminocyclopropane-1-carboxylic acid (ACC) under the catalysis of 1-aminocyclopropane-1-carboxylate synthase (ACS, EC 4.4.1.14), and then oxidized and decomposed by 1-aminocyclopropane-1-carboxylic acid oxidase (ACO, EC 1.14.17.4) to produce ethylene [21].

Some overlap between PA and ethylene biosynthetic pathways was observed, which may have been antagonistic. Locke et al. [22] found that using an ethylene synthesis inhibitor during barley seed germination significantly reduced the release of ethylene from barley leaves, thus promoting the synthesis of endogenous PAs in the leaves. Lasanajak et al. [23] demonstrated that during fruit ripening, an antagonistic relationship was observed between producing high-level PA and ethylene by radioactive labeling. This opposite relationship is regulated by SAMDC expression. Ethylene was positively correlated with senescence, whereas PAs had the opposite effect [24]. However, in transgenic tomato fruits overexpressing Yeast SAMDC and SPDS, high Spd and Spm levels were accompanied by an accumulation of ACS and increased ethylene content [25]. Similar changes were observed in the transgenic leaves of Arabidopsis thaliana overexpressing SPMS [26], making it challenging to establish the precise correlation between polyamines and ethylene. However, both compounds are products of plant defense response mechanisms under adverse conditions and play crucial roles in various stress responses.

Exploring PA and ethylene responses to low-temperature stress in quinoa can help to understand the mechanisms of quinoa cold resistance and enrich the theory of plant cold resistance. When studying low-temperature stress, 4 °C is a commonly used stress condition, which simulates the environment of low temperatures in early spring or late fall seasons, a temperature that can trigger a low-temperature response in the plant without causing immediate cellular frostbite, and enables researchers to observe the performance of the plant under mild to moderately intense low-temperature stresses to assess its cold tolerance [27,28,29]. Previously, we collected 39 quinoa resources from various regions in Yunnan Province, China, and through screening experiments, we obtained two materials with disparate cold resistance, i.e., low-temperature-tolerant red quinoa RQ8 and low-temperature-sensitive white quinoa WQ13, and determined that 48 h of stress at 4 °C was sufficient to cause quinoa to produce an obvious stress response, including physiological and molecular-level changes without causing excessive damage, which allowed us to better evaluate quinoa’s cold-tolerant and recovery abilities. Therefore, in this study, with the help of bioinformatics, we screened, identified and analyzed the PA metabolism gene family and ethylene synthesis gene family of quinoa in the quinoa genome, and analyzed the expression patterns of PA metabolism and ethylene synthesis genes in response to low-temperature stress by combining the transcriptomic and proteomic data of two quinoa materials with different cold tolerance under 48 h of 4 °C stress, in order to explore the roles of both in response to the process of cold stress.

Materials and methods

Identification of PA metabolism and ethylene synthesis genes in quinoa

Hidden Markov Model (HMM) files of conserved structural domains of PA biosynthesis, PA catabolism, and ethylene synthesis genes were obtained from Pfam. Quinoa genome-wide data were obtained from the National Center of Biotechnology Information database (NCBI, https://www.ncbi.nlm.nih.gov). Quinoa genome-wide protein sequences were scanned using hmmsearch and filtered by setting the e-value to < 1e-5. The filtered quinoa protein sequences were used to construct a new species-specific HMM and searched. Protein sequences of relevant gene family members were downloaded from the Arabidopsis (https://www.arabidopsis.org/) and rice genome databases(http://rice.uga.edu/analyses_search_blast.shtml) [17, 30,31,32,33,34], and E values < 1e-10 were set to perform blastp homology comparisons with quinoa. The Pfam search and BLASTP results were integrated, and proteins containing the target structural domains were identified as gene family members using NCBI-CDD (http://www.ncbi.nlm.nih.gov/Structure/cdd/wrpsb.cgi).

The number of amino acids, theoretical isoelectric point (pI), molecular weight (Mw), instability index(Ii), aliphatic index (Ai), and grand average of hydropathy (GRAVY) of gene families were analyzed using TB tools. Subcellular localization was predicted using the online software subCELlular LOcalization predictor ( http://cello.life.nctu.edu.tw/).

Construction of phylogenetic tree of quinoa PA metabolism and ethylene synthesis genes

Protein sequences were compared by clustering using MEGA 11.0. The bootstrap value was set to 1,000, and the maximum likelihood method was used to construct a phylogenetic tree of the gene families of quinoa, Arabidopsis, and rice.

Analysis of gene motif, promoter cis-acting elements, and gene structure

Protein-conserved motifs were analyzed using the MEME online tool (https://meme-suite.org/meme/tools/meme); 2,000 bp of upstream sequences of the genes were extracted using TBtools 2.031 software and submitted to PlantCare (http://bioinformatics.psb.ugent.be/webtools/plantcare/html/) to analyze the promoter cis-acting elements. The gene structures were predicted using TBtools software and the intron-exon maps of the genes were obtained, and all the above results were visualized with TBtools software.

2.4 Analysis of expression patterns of quinoa PA metabolism and ethylene synthesis gene family members under cold stress.

Red quinoa (RQ8) seeds resistant to low temperatures and white quinoa (WQ13) seeds susceptible to low temperatures were sown in pots (caliber: 100 cm; height: 85 cm; bottom diameter: 70 cm) filled with 0.8 kg nutrient-rich soil (Table S1 for nutritional components) and gently compacted. These pots were placed in an incubator, at 25 ℃/20 ℃ (14 h light/10 h dark) temperature regime, 70% relative humidity and photosynthetic photon flux density (PPFD) of 190 µmol·(m2·s)-1. When the quinoa grew to 6 true leaves, some of the plants were removed from the incubator and put into a low-temperature incubator with the same light and humidity conditions, and the temperature was adjusted to 4 ℃. 48 h later, quinoa leaves under normal and low-temperature conditions were collected for transcriptome and proteome sequencing analysis, respectively. Transcriptome and proteomic sequencing analyses were conducted, and relevant graphs were drawn using the R language. RQ8 and WQ13 in the control group were abbreviated as ZR and ZW. Red quinoa and white quinoa in the treatment group were abbreviated as LZR and LZW, respectively.

Transcriptome methods: RNA was extracted from different materials, and cDNA was synthesized using RNA as a template with a mixture of 6-base random primers and reverse transcriptase to generate the first strand cDNA. The second strand cDNA synthesis was then carried out using the first strand cDNA as a template. After library construction, Next-Generation Sequencing was performed on the library using the Illumina HiSeq sequencing platform with paired-end (PE) sequencing. The raw data was filtered to obtain high-quality clean data, which was then aligned to the reference genome of quinoa (GCF_001683475.1_ASM168347v1_genomic.fna). Gene expression levels were calculated based on the alignment results. Further differential expression analysis, enrichment analysis, and clustering analysis were conducted on the samples. Reads that aligned were assembled to reconstruct the transcript sequences.

Proteomics methods: Proteins were extracted from different materials, quantified using the BCA method, digested using FASP, and the resulting peptides were dried and reconstituted with 0.1% TFA for peptide concentration determination for LC-MS analysis. Each sample was then subjected to chromatographic separation using the Easy nLC 1200 chromatography system (Thermo Scientific). Mass spectrometry database search was conducted using MSFragger 3.4 software with the Uniprot protein database (Uniprot Chenopodium quinoa (Quinoa)[63459]-34188-202201030.fasta) for protein sequence alignment and identification.

Results

Identification, physicochemical properties, and phylogeny analysis of PA metabolism and ethylene synthesis gene families

An HMM matrix search was performed on quinoa genome protein sequence files, and subsequently, a BLASTP comparison was performed with Arabidopsis and rice PA metabolism proteins and ethylene synthesis proteins. After integration, 37 genes, including two CqADCs, two CqODCs, two CqAIHs, two CqSPDSs, two CqSPMSs, three CqACL5s, seven CqSAMDCs, and 17 CqCPAs were identified from the quinoa PA biosynthesis pathway. Six CqCuAOs and 24 CqPAOs in PA catabolism, 35 CqACSs, and 192 CqACOs in the ethylene synthesis pathway were identified (Table S2).

The lengths of the proteins involved in the PA synthesis pathway ranged from 80 (CqCPA16) to 747 (CqADC1) amino acids. Their Mw were 9382.99 (CqCPA16) to 80138.71 Da (CqADC1), whereas pI ranged from 4.69 (CqSAMDC7) to 9.37 (CqCPA14). Their Ii was between 25.25 (CqCPA6) to 48.13 (CqSPMS2), of which 21 proteins were unstable (Ii>40). Their Ai ranged from 74.78 (CqCPA4) to 95.14 (CqODC2), while the GRAVY ranged from − 0.429 (CqAIH2) to 0.057 (CqSAMDC6), with 81.58% hydrophilic proteins. Subcellular localization prediction showed that CqCPA14 and CqSAMDC2 were localized in the nucleus; CqCPA17, CqSAMDC3, CqSAMDC4, CqSAMDC6 and CqSAMDC7 were localized in the plasma membrane; CqADC2, CqCPA1, CqCPA2, CqCPA8 ∼ CqCPA13, CqCPA15, CqCPA16, CqSAMDC1, CqSAMDC5 in chloroplasts. All the other genes were localized in the cytoplasm.

The lengths of the PA catabolic proteins ranged from 281 (CqCuAO3) to 1,939 (CqPAO16) amino acids. Their Mw were 32,151.04 (CqCuAO3) to 210,966.23 Da (CqPAO16), while the pI ranged from 5.08 (CqPAO22) to 9.38 (CqPAO9). The Ii ranged from 30.88 (CqPAO18) to 46.76 (CqPAO1), of which 9 proteins belonged to unstable proteins. Their Ai were 75.87 (CqPAO5) to 98.72 (CqPAO18), whereas GRAVY ranged from − 0.469 (CqPAO16) to 0.009 (CqPAO18), except CqPAO18; all other proteins were hydrophilic. The predicted subcellular localization results showed that CqPAO16 and CqPAO24 were localized in the nucleus; CqCuAO1, CqCuAO4, CqCuAO5, CqPAO9, CqPAO21 in the plasma membrane; CqPAO1, CqPAO3, CqPAO7, CqPAO10, CqPAO17, CqPAO22 in the chloroplasts and cytoplasm.

The lengths of the ethylene anabolic proteins ranged from 234 (CqACO109) to 884 (CqACO166) amino acids. Their Mw were 27104.85 (CqACO109) to 100879.54 Da (CqACO166), while pI ranged from 4.82 (CqACO117) to 8.77 (CqACO79). Their Ii ranged from 17.51 (CqACO56) to 59.05 (CqACO187), while Ai were 67.33 (CqACO188) to 107.49 (CqACO117). The GRAVY were at -0.615 (CqACO96) to 0.052 (CqACS14), where CqACS4, CqACS35, CqACS4, CqACS35, CqACO117, CqACS14 were hydrophobic proteins. The predicted subcellular localization results showed that ethylene anabolic genes were mainly localized in the cytoplasm, nucleus, chloroplasts, and plasma membrane.

Phylogenetic trees of the PA metabolism and ethylene biosynthesis gene families in quinoa, Arabidopsis, and rice were constructed (Fig. 2). Fewer members of CqADC, CqODC, CqSPDS, CqSPMS, CqAIH, and CqACL5 families were observed in the PA synthesis pathway. CqADC, CqSPDS, and CqSPMS, as well as CqACL5/2 and CqACL5/3, were more closely related to Arabidopsis, whereas CqAIH and CqACL5/1 were more closely related to rice. CqODC was only compared with OsODC in rice because no ODC family was observed in Arabidopsis. CqSAMDC1 and CqSAMDC5 were similar to those in Arabidopsis. More members of the CqCPA family were found, and most were closely related to rice.

Fig. 2
figure 2

Phylogenetic trees of quinoa, Arabidopsis, and rice (a) PA synthesis gene family, (b) PA catabolism gene family, (c) ACS gene family in the ethylene synthesis pathway, (d) ACO gene family in the ethylene synthesis pathway

Full size image

Analysis of conserved motif, cis-acting element of promoter and gene structure

Members of the same family have similar conserved motifs (Fig. 3). The conserved motifs CqADC, CqODC, CqSPDS, CqSPMS, and CqAIH in the PA synthesis pathway were identical to those of members of the same family. All CqACL5 family members contain motifs 1 ∼ 6, and CqACL5/2, as well as CqACL5/3, contain motifs 7 and 8. In the CqSAMDC family, motifs 1 ∼ 3, 5, and 6 are highly conserved and present in each member. In the CqCPA family, motif 2 is the most conserved motif and is present in all members. Except for CqCPA16, all members of the CqCPA family contain motif 3. In the catabolism of PA (Figs. S1), motif 1, motif 5 and motif 6 were the most conservative. Excluding CqCuAO2 and CqCuAO3, all other members of the CqCuAO family had the same motif and were arranged similarly. In the CqPAO family, motif 3 and motif 4 were the most conserved, followed by motif 7 and motif 9. In the ethylene synthesis pathway (Figs. S2 and S3), all members of the CqACS family had motif 1, motif 5, and motif 6, and all members had Motif 8 except for CqACS21. In the CqACO family, motif 4 was the most conserved, except for CqACO124 and CqACO161, all other members had motif 3 and motif 6.

The exon-intron structural diversity of gene families is important for studying the evolution and function of gene family members. The results of gene structure analysis (Figs. S4 ∼ S7) showed that the structural features of quinoa PA anabolic genes showed a clear family distribution pattern. The members of the same family, possessed identical structural features, CqADC, CqODC, CqSPDS, CqSPMS, and CqACL5 with 10, 10, 10, 10, 8, 1 exon, and 8, 10, 9, 7, 0 intron, all of them had 5’ and 3’ UTR, respectively. CqSAMDC1, CqSAMDC2, CqSAMDC5, and CqSAMDC7 had the same structure, including 1exon and 2 introns, whereas CqSAMDC3 and CqSAMDC6 did not. The number of exons in the CqCPA family ranged from 3 to 10, and the number of introns ranged from 2 to 9. CqCPA16 had a simpler structure containing 3 exons, 2 introns, and 3’ UTR, while CqCPA4 and CqCPA6 were structurally complex containing 10 exons, 9 introns, and 5 ’and 3’ UTR. In the catabolic pathway of PA, CqCuAO2, and CqCuAO6 are similar in structure, with 5 exons and 4 introns. Excluding CqCuAO1 and CqCuAO5 which only had a 3’ UTR, the other family members had 5’ and 3’ UTRs. In the CqPAO family, CqPAO1, CqPAO19 and CqPAO22 have 1 exon and no introns. In the ethylene synthesis pathway, the number of exons in the CqACS family ranged from 3 to 15, with introns from 2 to 14, CqACS23 and CqACS24 without UTR, and CqACS 14 had only a 3’ UTR. The number of exons in the CqACO family ranged from 2 to 12, of which 88 had 3 exons and 54 had 4 exons. CqACO5, CqACO6, CqACO55, and CqACO57 had the most complex structure, containing 12 exons, 11 introns, and 5’ and 3’ UTR.

Fig. 3
figure 3

Conserved motifs of quinoa PA synthesis pathway genes (a) CqADC family, (b) CqODC family, (c) CqSPDS family, (d) CqACL5 family, (e) CqSPMS family, (f) CqODC family, (g) SAMDC family, (h) CqAIH family

Full size image

Quality testing of sequencing data

More than 94% clean reads were obtained for all 12 samples, and after purification, the Q20 base ratio was greater than 98%, and the Q30 base ratio was > 94% (Tables S3, S4). PCA can cluster similar samples together, and the closer the distance, the higher the similarity between samples. The correlation of gene expression level between samples is an important index to test the reliability of the experiment and determine whether the sample selection is reasonable. These correlations between samples were expressed by the Pearson correlation coefficient (Fig. S8); the repeatability and similarity of the LZW, LZR, ZW, and ZR samples were better, and the quality of the sequencing data was higher, which could be used for subsequent analysis.

Upset venn diagram analysis of PA metabolism and ethylene synthesis genes

The distribution of family genes in the samples was demonstrated using an Upset Venn diagram (Fig. 4). A total of 149 genes were detected in the transcriptomes of the PA metabolism and ethylene synthesis families, among which 88 genes were present in all four samples, 21 genes were only present in ZR and ZW, and 13 genes were only present in LZR and LZW. The genes unique to ZR, LZR, ZW, and LZW were 6, 1, 5 and 5, respectively.

Fig. 4
figure 4

Upset analysis of PA metabolism and ethylene synthesis genes

Full size image

Expression of PA metabolism and ethylene synthesis genes under low temperature stress

Different gene families showed differential expression under cold stress, indicating specificity in the expression of these genes (Fig. 5). In the PA synthesis pathway, the CqSPDS and CqADC family genes showed a consistent up-regulation trend in expression after low-temperature stress. In contrast, the opposite trend was found for CqACL5 and CqCPA. CqODC was highly expressed in LZW. CqCPA was highly expressed under non-stress conditions, whereas CqCPA1 showed increased expression under stress. The CqAIH family is comprised of two genes with completely different expression patterns. CqAIH1 was highly expressed before stress exposure, whereas the opposite was true for CqAIH2. A similar situation was observed for the CqSPMS and CqSAMDC families. CqSAMDC2, CqSAMDC3, and CqSAMDC6 were highly expressed before stress, whereas the opposite was true for CqSAMDC1 and CqSAMDC5. Among the PA catabolic gene families, CqCuAO5 and CqCuAO6 were highly expressed before stress, whereas other genes were highly expressed after stress. After low-temperature stress, the expression levels of CqPAO7, CqPAO10, CqPAO18 ∼ CqPAO20 and CqPAO24 were upregulated, whereas those of CqPAO1, CqPAO3, CqPAO4, CqPAO8, CqPAO9, CqPAO14, CqPAO17 and CqPAO21 ∼ CqPAO23 were decreased. In the ethylene synthesis pathway, most gene members of the CqACS family showed higher expression after stress. 37 genes of the CqACO family had upregulated expression and 51 genes showed decreased expression after low-temperature stress, whereas the other members showed no obvious expression pattern.

Fig. 5
figure 5

Expression changes of PA metabolism and ethylene synthesis genes under low temperature stress

Full size image

Expression analyses of differential genes in PA metabolism and ethylene synthesis under low temperature stress

In the LZR_vs_ZR and LZW_vs_ZW comparison groups, the number of upregulated genes was high, and the expression of CqACO30, CqACO37, CqACO83, CqACO113, CqACO119, CqACO169, CqACS1, CqSAMDC1, and CqCuAO3 was significantly upregulated, with a fold difference of more than 10-fold ( FPKM), in which the expression levels of CqACO83 and CqACO119 varied more than 100-fold (FPKM), indicating a strong response to low temperature (Fig. 6); CqACO20, CqACO44, and CqACO137 were significantly downregulated in both groups by more than 20-fold (FPKM). The number of differentially expressed genes in different materials at the same temperature was lower. CqACO98 was significantly downregulated in LZR_vs_LZW and ZR_vs_ZW, and CqACS6 and CqACO187 were significantly upregulated. The expression of gene family members in the three metabolic pathways fluctuated greatly between LZR_vs_ZR and LZW_vs_ZW.

Taking LZR_vs_ZR as an example, the differentially expressed family genes were subjected to GO enrichment analysis, and GO classification was performed according to their molecular function, biological processes, and cellular components (Fig. S9). The molecular functions of the differentially expressed genes were mainly enriched in 6 areas namely 2 − oxoglutarate − dependent dioxygenase activity, dioxygenase activity, L-ascorbic acid binding, monosaccharide binding, pyridoxal phosphate binding, and vitamin binding. Biological processes were mainly enriched in amine biosynthesis, amine metabolism, biogenic amine biosynthesis, biogenic amine metabolism, polyamine biosynthesis, and polyamine degradation. The cellular components were mainly enriched in microbodies and peroxisomes.

KEGG analysis (Fig. S10, Table  S5) showed that differentially expressed genes in LZR_vs_ZR were involved in 11 pathways, including cysteine and methionine metabolism; arginine and proline metabolism; isoquinoline alkaloid biosynthesis; flavonoid biosynthesis; phenylalanine metabolism; tropane, piperidine, and pyridine alkaloid biosynthesis; tyrosine metabolism; diterpenoid biosynthesis; ubiquinone and other terpenoid-quinone biosynthesis; phenylalanine, tyrosine, and tryptophan biosynthesis; and beta-alanine. Among them, more genes were enriched in cysteine and methionine metabolism, namely CqACO156, CqACS1, CqACS34, CqACS4, CqSAMDC1, CqSAMDC5, and CqSPMS2, all of which were upregulated.

Fig. 6
figure 6

Expression of differential genes in PA metabolism and ethylene synthesis, (a) differential expression in LZR_vs_ZR, (b) differential expression in LZW_vs_ZW, (c) differential expression in LZR_vs_LZW, (d) differential expression in ZR_vs_ZW

Full size image

Gene set enrichment analyses of genes in PA metabolism and ethylene synthesis

Gene set enrichment analysis (GSEA) was utilized to explore further the overall expression of the 12 gene families (Fig. 7). The families were upregulated in LZR_vs_ZR, LZW_vs_ZW, and ZR_vs_ZW, and CqSPMS2, CqCuAO4, CqPAO7, CqPAO18, and CqACS21 accounted for important positions among the upregulated genes. In LZR_vs_LZW, the proportions of upregulated and downregulated genes were approximately the same.

Fig. 7
figure 7

GSEA of genes in PA metabolism and ethylene synthesis

Full size image

Protein-protein interaction analyses of PA metabolism and ethylene synthesis genes

Protein–protein interaction (PPI) network construction of quinoa PA metabolism and ethylene synthesis family proteins were performed using the STRING website (https://string-db.org/) (Fig. 8). The gene had a certain interaction relationship with each other, and 10 genes with high connectivity were screened: CqODC1, CqAIH1, CqCPA3, CqSPMS2, CqSPDS2, and CqACL5/1 in PA anabolism; CqCuAO3 and CqPAO19 in PA catabolism; and CqACS23 and CqACS26 in the ethylene synthesis pathway. Among them, CqODC1 had the highest network connectivity at the center, indicating that this gene is closely related to genes involved in PA metabolism and ethylene synthesis.

Fig. 8
figure 8

PPI of PA metabolism and ethylene synthesis families

Full size image

Mantel-test analyses of PA metabolism and ethylene synthesis families

Mantel test analysis was used to explore further the relationship between PA metabolism and ethylene synthesis gene families (Fig. 9). Different correlations were observed between PA catabolism and ethylene synthesis gene families. The CqACO, CqACS, CqCuAO, and CqPAO families showed low significance (P < 0.05) for CqSPMS1, CqSAMDC7, CqODC2, CqCPA2, CqCPA16 and CqACL5/1 of the PA synthesis genes. However, a strong correlation was found between CqACS and CqACL5/1 and between CqCuAO and CqCPA16 (0.2 ≤ r < 0.4). The significance of CqACO with CqSPDS1 and CqCPA4 was low (P < 0.05). CqACS showed low significance (P ≥ 0.05) with CqSPMS2, CqCPA8, CqCPA1, CqCPA3, CqCPA11, and CqAIH2; however, it had a strong correlation with CqCPA3 (0.2 ≤ r < 0.4). CqCuAO showed low significance (P < 0.05) for CqODC1, CqCPA4, and CqCPA11. In addition, the correlation (r ≥ 0.2) and significance (P < 0.05) between the genes involved in PA catabolism and ethylene synthesis and the genes involved in PA synthesis were high, indicating a close relationship and mutual influence between these three metabolic pathways.

Fig. 9
figure 9

Mantel-test of PA metabolism and ethylene synthesis genes

Full size image

Discussion

PAs and ethylene play important roles in plant growth, development, and responses to adverse stress. In this study, we identified the quinoa PA synthesis and catabolic metabolism and ethylene synthesis gene families at the gene level, analyzed the basic family characteristics, and investigated the expression patterns of the gene families of the three metabolic pathways under low-temperature stress.

Members of the same gene family have similar motif and exon-intron structures, and different groups of genes exhibit different structures that have remained conserved through evolution and may play a role in protecting gene integrity. A gene structure with a small number of introns increases the efficiency of gene expression and enables a faster response to external damage, and also implies that the gene is more stable during evolution. In the metabolic pathways of PAs, there were 25 genes that contained less than or equal to 5 introns. Among them, CqSAMDC3, CqSAMDC4, CqSAMDC6, CqPAO1, CqPAO19 ∼ CqPAO22, and the CqADC gene family did not contain any introns. In the ethylene synthesis pathway, 90% of the genes in the CqACO family had less than or equal to 5 introns, which may indicate a faster activation efficiency of these genes. The SPDS, SPMS, and ACL5 families are more special, with highly similar protein sequences, so phylogenetic and motif analyses are often employed to determine their homologous sequences. Most plants contain 2 SPDS and 1 or 2 SPMS, with the SPDS having 9 exons and the SPMS having 10 or 11 exons [35]. Quinoa contained two CqSPDS and two CqSPMS genes, each with 9 and 10 exons respectively, following the gene structure pattern. In addition, the arrangement and size of exons were conserved between the two gene families, indicating that these two classes of enzymes were involved in similar biochemical reactions. The genomic structure of plant ACL5 genes is also conserved, with independent origin [35]. ACL5 and SPMS both show substrate specificity for Spermidine and respectively synthesize asymmetric Thermospermine and symmetric Spermine. The Quinoa CqACL5 family had 3 members, each with 10 exons, consistent with the number and arrangement of exons in other plants of this family, indicating stability during evolution.

A phylogenetic analysis of the PA metabolism and ethylene synthesis genes in quinoa showed that various proteins cluster with homologous proteins in Arabidopsis thaliana, indicating close evolutionary relationships and potentially similar functional roles. The promoter elements of each gene family were diverse, mainly involving stress response, hormone response, developmental response, and light response elements. The more abundant the promoter elements, the faster and broader the coordination in regulating the expression of related genes in time and space, making them more effective in defending against external threats. These genes may play important roles in quinoa growth and development and may be involved in plant defense mechanisms.

Two general pathways are known to synthesize Put in plants: the ADC pathway and the ODC pathway. ADC appears to encode a larger protein than ODC [8]. Most plants have the ODC pathway, but some Brassicaceae plants such as Arabidopsis thaliana lack this pathway, and the corresponding enzyme activity is defective. Therefore, the ADC gene may serve as a compensatory mechanism for the absence of ODC in these plants [36]. Changes in gene expression before and after low-temperature stress indicated that the expression trend of CqODC1 was consistent with CqADC, with increased expression levels after temperature stress, suggesting a positive response of these genes to low temperature. Studies have shown that the ADC pathway is mainly induced by stress such as low temperature and drought, while the ODC pathway is involved in plant growth, organ differentiation, and reproductive stages [37]. For example, overexpression of AtADC1 in Arabidopsis enhanced cold tolerance, while mutant plants lacking AtADC were more sensitive to low temperatures [8]. ODC activity significantly increased between the flowering period and fertilization period in tobacco, while using the ODC inhibitor Difluoromethylornithine (DFMO) could temporarily halt fruit growth [8].

The expression patterns of CqAIH2, CqCPA1, CqSPDS and CqSPMS2, CqSAMDC1 were consistently upregulated after low-temperature stress, but the opposite was true for other genes in the same family, such as CqAIH1, CqCPA5, CqACL17, and CqSAMDC6, probably because when plants are in a low-temperature environment, they will resist external stimuli by increase the PAs content in the body to resist external stimuli, the expression of some genes in the PAs synthesis family, although down-regulated, can be compensated by the high expression and accumulation of other members of the same family, and therefore do not deter the synthesis of PAs [31]. The expression of CqSAMDC4 was extremely low before and after the low-temperature stress, which may be the result of the expression of the gene was affected by the material varieties, the intensity of the stress, or the tissue site. The expression of CqACL5 family members were all reduced, probably because CqACL5 competed with CqSPMS for the same substrate Spermidine, and quinoa preferentially utilized CqSPMS to accumulate Spermine to cope with the external injury during low-temperature stress.

The expression of some genes of the CqCuAO and CqPAO families was upregulated after low-temperature stress, suggesting that these genes were induced by low temperature. However, CuAOs and PAOs are mainly responsible for catalyzing PAs and generating a higher amount of H2O2 [18], so will it reduce the content of PAs, and weaken the plant’s ability to withstand low temperature? In addition reactive oxygen species accumulation is a well-recognized pangenetic marker of abiotic or biotic stress, and it is a matter of existential debate whether H2O2, formed by PA catabolism, is always pathological or plays a role in cellular signaling [38]. Studies have shown that excess PAs can induce programmed cell death in many different cellular systems [39]. Although the cytotoxicity of polyamines is often attributed to their oxidation, it is well known that high levels of polyamines produce direct toxic effects [39]. Although ROS are deleterious at high concentrations, there is evidence that they are powerful signaling molecules in the adaptive response to stress stimuli [40,41,42]. In plants, H2O2 produced by polyamine catabolism is considered to be an important second messenger in the signal transduction network involved in the downstream activation of ion channels and regulation of gene expression, drives peroxidase-mediated oxidative cross-linking of structural cell wall components, contributing to cell wall strengthening during development and under stress conditions, such as wound healing, and low temperature stress [38]. Arabidopsis AtCuAOα2 and AtCuAOα3 were involved in xylem differentiation of leaves or roots, and also induced stress-related hormone expression and activated plant defense mechanisms [43]. Overexpression of Capsicum annuum CaPAO2 and CaPAO4 in transgenic Arabidopsis significantly increased freezing tolerance, while up-regulating endogenous low temperature responsive genes [44]. Therefore, the increased expression of genes in the CqCuAO and CqPAO families may not decrease quinoa’s ability to withstand low-temperature damage but may play a positive role in the plant’s response to low-temperature stress.

Ethylene, known as the plant stress hormone, is a gaseous small molecule (C2H4) that is involved in numerous developmental processes in plants, such as seed germination, cell elongation, tissue differentiation, senescence and abscission of leaves and flowers, and fruit ripening [45, 46]. Moreover, it is also involved in various plant responses to biotic and abiotic stresses [47, 48]. ACS and ACO are the two key enzymes involved in ethylene synthesis. The CqACO family has a large number of members, and after low-temperature stress, the family members were categorized into three main groups. The first category was the low-temperature expression type, such as CqACO165, CqACO106, CqACO118, and CqACO190, whose expression was dramatically upregulated. The second was the low-temperature suppression type, which included CqACO110, CqACO191, and CqACO119. The third was species-specific types, such as CqACO9, CqACO25, CqACO131, and CqACO132 only appeared in red quinoa, and CqACO98 was only expressed in white quinoa. The expression of these genes may be related to the variety, but may also be affected by the time of stress or the site of stress. The diversity of CqACO gene expression revealed that this family may have highly coordinated and broad functional roles.

The aminopropyl necessary for the synthesis of PAs is catalyzed by SAMDC to decompose SAM. SAM is the precursor for PAs and ethylene synthesis. After low temperature stress, the expression level of the CqSAMDC gene was upregulated. Theoretically, the PAs content will continue to increase, while the ethylene content is competitively inhibited. In many cases, the PA biosynthesis pathway often competes with ethylene biosynthesis for its common precursor SAM, and PAs interact with ethylene at the level of biosynthesis and physiological effects. However, some studies have failed to observe such competition during flower senescence, cold stress response, or fruit ripening [49]. In this study, PA and ethylene were interlinked and extremely closely related after low-temperature stress, as shown by various analytical methods. However, no obvious antagonistic effect was observed, probably because quinoa synthesized a large amount of PA, the increase in PA also stimulated an increase in the activity of enzymes related to PA catabolic metabolic pathways, which accelerated the decomposition of PAs and produced more reactive oxygen radicals, such as H2O2. The excessive amount of reactive oxygen radicals accelerated the ACS-catalyzed conversion of ACC to ethylene, increasing ethylene release. In addition, PAs and ethylene compete for the SAM pool during metabolic synthesis, the antagonistic effects of PA and ethylene may only occur when the SAM library capacity is limited, and these two may not show obvious inhibitory effects when the SAM library capacity is sufficient. PA and ethylene are affected by various factors such as stress factors, stress time, tissue site, and developmental period of the plant. The relationship between them cannot be accurately determined from gene family analysis and the expression of PA metabolism genes and ethylene synthesis genes alone. Therefore, we will continue to study the involvement of marker proteins, inhibitors, or the expression of antisense genes to determine the PA and ethylene concentrations to elucidate the relationship between them further.

The structure and expression patterns of members of the same family may be similar, but there are also special members with functional differentiation, for example, the expression of CqSAMDC1 and CqSAMDC5 increased significantly after low temperature stress, and correlation analysis showed that they were significantly correlated with PA metabolism and ethylene synthesis pathways, suggesting that they played important roles in the process of resisting cold damage. However, the opposite was true for CqSAMDC2 and CqSAMDC3 expression. Therefore making it difficult to evaluate the role of the entire family in plant resistance and growth and development through a single gene [50]. A family is considered as a whole, and by analyzing the differential gene expression and GSEA analysis of the overall trend of gene families in different materials, it is found that after low temperature stress, the expression changes of members of the PAs metabolic and ethylene synthesis gene families were not completely consistent. However, different families of genes showed an overall upregulation trend, indicating that these two metabolisms may participate in the temperature stress process by increasing the expression levels of genes in the metabolic pathways, thus playing a role in resisting stimuli. Members of different families showed different expression levels after low temperature stress, but the overall trend was consistent, which may be the regulation of PAs metabolism and ethylene synthesis genes in quinoa, the molecular basis of both metabolisms to resist low temperature attack.

Different families have different numbers and functions of genes, and there is a complex network of relationships between different genes. Interaction network analysis of the proteins of the PAs metabolism and ethylene synthesis family members showed that CqODC1, CqSPMS2, and CqACS23 had a large central connectivity in the proteins, which suggested that they had a great influence on the PAs metabolism and ethylene synthesis family, and thus were involved in the quinoa low-temperature response process. In addition, members of the same family had obvious strong and weak variations in correlation with other families, such as the different correlations between CqODC1 and CqODC2 with CqPAO, and the inhomogeneity of intergenic expression, which may be related to the complexity, extensiveness, and reinforcement of the function of the PAs family.

Conclusions

This study conducted a comprehensive genome analysis of the PAs metabolic and ethylene synthesis gene families in quinoa, identifying 37 PAs synthesis genes, 30 PAs catabolism genes, and 227 ethylene synthesis genes, showing a clear family distribution pattern of gene structural characteristics that remained conservative during evolution. By analyzing the transcriptome and proteome data of two quinoa varieties at different temperatures, the expression patterns and protein expression characteristics of the PAs metabolic and ethylene synthesis genes in quinoa were explored. The expression patterns of members of the same family were relatively similar, but differential expression may occur, possibly influenced by factors such as varietal specificity, tissue specificity, and stressor specificity, indicating that this gene family may have multiple stress response mechanisms. Overall, the expression of PAs metabolic genes and ethylene synthesis genes was induced by low temperatures and showed an upregulation trend, playing an important role in the low-temperature response process. The PAs metabolism gene family was closely linked to the ethylene synthesis gene family, and no obvious antagonistic effect was observed. The roles and interactions between the two in plant cold resistance require further exploration and research.

Data availability

The raw data of transcriptome sequencing can be found in the National Center for Biotechnology Information (NCBI) database with the accession number PRJNA1080447. The proteomic mass spectrometry data were obtained from iProX, accession number IPX0008218001.

References

  1. Angeli V, Miguel Silva P, Crispim Massuela D, Khan MW, Hamar A, Khajehei F, et al. Quinoa (Chenopodium quinoa Willd.): an overview of the potentials of the Golden Grain and socio-economic and environmental aspects of its cultivation and marketization. Foods. 2020;9:216.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  2. Pathan S, Siddiqui RA. Nutritional composition and bioactive components in quinoa (Chenopodium quinoa Willd.) Greens: a review. Nutrients. 2022;14:558.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  3. Katarzyna Adamczewska-Sowińska. Józef Sowiński, Anna Jama-Rodzeńska. The effect of sowing date and harvest time on leafy greens of quinoa (Chenopodium quinoa Willd.) Yield and selected nutritional parameters. Agriculture. 2021;11.

  4. Shen ZJ, Xu SX, Huang QY, Li ZY, Xu YD, Lin CS, et al. TMT proteomics analysis of a pseudocereal crop, quinoa (Chenopodium quinoa Willd.), during seed maturation. Front Plant Sci. 2022;13:975073.

    Article  PubMed  PubMed Central  Google Scholar 

  5. McGinty EM, Murphy KM, Hauvermale AL. Seed dormancy and preharvest sprouting in Quinoa (Chenopodium quinoa Willd). Plants (Basel). 2021;10:458.

    Article  CAS  PubMed  Google Scholar 

  6. Jiménez-Bremont JF, Chávez-Martínez AI, Ortega-Amaro MA, Guerrero-González ML, Jasso-Robles FI, Maruri-López I, et al. Translational and post-translational regulation of polyamine metabolic enzymes in plants. J Biotechnol. 2022;344:1–10.

    Article  PubMed  Google Scholar 

  7. Romero FM, Maiale SJ, Rossi FR, Marina M, Ruíz OA, Gárriz A. Polyamine metabolism responses to biotic and abiotic stress. Methods Mol Biol. 2018;1694:37–49.

    Article  CAS  PubMed  Google Scholar 

  8. Liu T, Huang B, Chen L, Xian Z, Song S, Chen R, et al. Genome-wide identification, phylogenetic analysis, and expression profiling of polyamine synthesis gene family members in tomato. Gene. 2018;661:1–10.

    Article  CAS  PubMed  Google Scholar 

  9. Childs AC, Mehta DJ, Gerner EW. Polyamine-dependent gene expression. Cell Mol Life Sci. 2003;60:1394–406.

    Article  CAS  PubMed  Google Scholar 

  10. Alet AI, Sánchez DH, Cuevas JC, Marina M, Carrasco P, Altabella T, et al. New insights into the role of spermine in Arabidopsis thaliana under long-term salt stress. Plant Sci. 2012;182:94–100.

    Article  CAS  PubMed  Google Scholar 

  11. Hasan MM, Skalicky M, Jahan MS, Hossain MN, Anwar Z, Nie Z-F, et al. Spermine: its emerging role in regulating drought stress responses in plants. Cells. 2021;10:261.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  12. Alcázar R, Cuevas JC, Planas J, Zarza X, Bortolotti C, Carrasco P, et al. Integration of polyamines in the cold acclimation response. Plant Sci. 2011;180:31–8.

    Article  PubMed  Google Scholar 

  13. Nahar K, Hasanuzzaman M, Rahman A, Alam MM, Mahmud J-A, Suzuki T, et al. Polyamines confer salt tolerance in Mung Bean (Vigna radiata L.) by reducing sodium uptake, improving nutrient homeostasis, antioxidant defense, and methylglyoxal detoxification systems. Front Plant Sci. 2016;7:1104.

    Article  PubMed  PubMed Central  Google Scholar 

  14. Sagor GHM, Inoue M, Kusano T, Berberich T. Expression profile of seven polyamine oxidase genes in rice (Oryza sativa) in response to abiotic stresses, phytohormones and polyamines. Physiol Mol Biology Plants. 2021;27:1353–9.

    Article  CAS  Google Scholar 

  15. Shi H, Chan Z. Improvement of plant abiotic stress tolerance through modulation of the polyamine pathway. J Integr Plant Biol. 2014;56:114–21.

    Article  CAS  PubMed  Google Scholar 

  16. Eller MH, Warner AL, Knap HT. Genomic organization and expression analyses of putrescine pathway genes in soybean. Plant Physiol Biochem. 2006;44:49–57.

    Article  CAS  PubMed  Google Scholar 

  17. Yariuchi Y, Okamoto T, Noutoshi Y, Takahashi T. Responses of polyamine-metabolic genes to polyamines and plant stress hormones in arabidopsis seedlings. Cells. 2021;10:3283.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  18. Gholizadeh F, Mirzaghaderi G. Genome-wide analysis of the polyamine oxidase gene family in wheat (Triticum aestivum L.) reveals involvement in temperature stress response. PLoS ONE. 2020;15:e0236226.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  19. Kusano T, Berberich T, Tateda C, Takahashi Y. Polyamines: essential factors for growth and survival. Planta. 2008;228:367–81.

    Article  CAS  PubMed  Google Scholar 

  20. Wang W, Paschalidis K, Feng J-C, Song J, Liu J-H. Polyamine catabolism in plants: a universal process with diverse functions. Front Plant Sci. 2019;10:561.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  21. Pattyn J, Vaughan-Hirsch J, Van de Poel B. The regulation of ethylene biosynthesis: a complex multilevel control circuitry. New Phytol. 2021;229:770–82.

    Article  CAS  PubMed  Google Scholar 

  22. Locke JM, Bryce JH, Morris PC. Contrasting effects of ethylene perception and biosynthesis inhibitors on germination and seedling growth of barley (Hordeum vulgare L). J Exp Bot. 2000;51:1843–9.

    Article  CAS  PubMed  Google Scholar 

  23. Lasanajak Y, Minocha R, Minocha SC, Goyal R, Fatima T, Handa AK, et al. Enhanced flux of substrates into polyamine biosynthesis but not ethylene in tomato fruit engineered with yeast S-adenosylmethionine decarboxylase gene. Amino Acids. 2014;46:729–42.

    Article  CAS  PubMed  Google Scholar 

  24. Sobieszczuk-Nowicka E. Polyamine catabolism adds fuel to leaf senescence. Amino Acids. 2017;49:49–56.

    Article  CAS  PubMed  Google Scholar 

  25. Nambeesan S, Datsenka T, Ferruzzi MG, Malladi A, Mattoo AK, Handa AK. Overexpression of yeast spermidine synthase impacts ripening, senescence and decay symptoms in tomato. Plant J. 2010;63:836–47.

    Article  CAS  PubMed  Google Scholar 

  26. Gonzalez ME, Marco F, Minguet EG, Carrasco-Sorli P, Blázquez MA, Carbonell J, et al. Perturbation of spermine synthase gene expression and transcript profiling provide new insights on the role of the tetraamine spermine in Arabidopsis defense against Pseudomonas viridiflava. Plant Physiol. 2011;156:2266–77.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  27. Lantzouni O, Alkofer A, Falter-Braun P, Schwechheimer C. Growth-regulating factors interact with dellas and regulate growth in cold stress. Plant Cell. 2020;32:1018–34.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  28. Cheng J, Huang H, Liu W, Zhou Y, Han W, Wang X, et al. Unraveling the effects of cold stratification and temperature on the seed germination of invasive spartina alterniflora across latitude. Front Plant Sci. 2022;13:911804.

    Article  PubMed  PubMed Central  Google Scholar 

  29. Duncan S, Holm S, Questa J, Irwin J, Grant A, Dean C. Seasonal shift in timing of vernalization as an adaptation to extreme winter. Elife. 2015;4:e06620.

    Article  PubMed  PubMed Central  Google Scholar 

  30. Tanwar UK, Stolarska E, Paluch-Lubawa E, Mattoo AK, Arasimowicz-Jelonek M, Sobieszczuk-Nowicka E. Unraveling the genetics of polyamine metabolism in barley for senescence-related crop improvement. Int J Biol Macromol. 2022;221:585–603.

    Article  CAS  PubMed  Google Scholar 

  31. Do PT, Degenkolbe T, Erban A, Heyer AG, Kopka J, Köhl KI, et al. Dissecting rice polyamine metabolism under controlled long-term drought stress. PLoS ONE. 2013;8:e60325.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  32. Yamagami T, Tsuchisaka A, Yamada K, Haddon WF, Harden LA, Theologis A. Biochemical diversity among the 1-amino-cyclopropane-1-carboxylate synthase isozymes encoded by the Arabidopsis gene family. J Biol Chem. 2003;278:49102–12.

    Article  CAS  PubMed  Google Scholar 

  33. Iwai T, Miyasaka A, Seo S, Ohashi Y. Contribution of ethylene biosynthesis for resistance to blast fungus infection in young rice plants. Plant Physiol. 2006;142:1202–15.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  34. Houben M, Van de Poel B. 1-Aminocyclopropane-1-Carboxylic acid oxidase (ACO): the enzyme that makes the plant hormone Ethylene. Front Plant Sci. 2019;10:695.

    Article  PubMed  PubMed Central  Google Scholar 

  35. Shao L, Majumdar R, Minocha SC. Profiling the aminopropyltransferases in plants: their structure, expression and manipulation. Amino Acids. 2012;42:813–30.

    Article  CAS  PubMed  Google Scholar 

  36. Hanfrey C, Sommer S, Mayer MJ, Burtin D, Michael AJ. Arabidopsis polyamine biosynthesis: absence of ornithine decarboxylase and the mechanism of arginine decarboxylase activity. Plant J. 2001;27:551–60.

    Article  CAS  PubMed  Google Scholar 

  37. Fuell C, Elliott KA, Hanfrey CC, Franceschetti M, Michael AJ. Polyamine biosynthetic diversity in plants and algae. Plant Physiol Biochem. 2010;48:513–20.

    Article  CAS  PubMed  Google Scholar 

  38. Tavladoraki P, Cona A, Federico R, Tempera G, Viceconte N, Saccoccio S, et al. Polyamine catabolism: target for antiproliferative therapies in animals and stress tolerance strategies in plants. Amino Acids. 2012;42:411–26.

    Article  CAS  PubMed  Google Scholar 

  39. Walters D. Resistance to plant pathogens: possible roles for free polyamines and polyamine catabolism. New Phytol. 2003;159:109–15.

    Article  CAS  PubMed  Google Scholar 

  40. Wu J, Shu S, Li C, Sun J, Guo S. Spermidine-mediated hydrogen peroxide signaling enhances the antioxidant capacity of salt-stressed cucumber roots. Plant Physiol Biochem. 2018;128:152–62.

    Article  CAS  PubMed  Google Scholar 

  41. Jasso-Robles FI, Gonzalez ME, Pieckenstain FL, Ramírez-García JM, Guerrero-González M, de la Jiménez-Bremont L. Decrease of Arabidopsis PAO activity entails increased RBOH activity, ROS content and altered responses to Pseudomonas. Plant Sci. 2020;292:110372.

    Article  CAS  PubMed  Google Scholar 

  42. Benkő P, Gémes K, Fehér A. Polyamine oxidase-generated reactive oxygen species in plant development and adaptation: the polyamine Oxidase-NADPH oxidase nexus. Antioxid (Basel). 2022;11:2488.

    Article  Google Scholar 

  43. Fraudentali I, Rodrigues-Pousada RA, Angelini R, Ghuge SA, Cona A. Plant copper amine oxidases: key players in hormone signaling leading to stress-induced phenotypic plasticity. Int J Mol Sci. 2021;22:5136.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  44. Zhang J, Liang L, Xiao J, Xie Y, Zhu L, Xue X, et al. Genome-wide identification of polyamine oxidase (PAO) family genes: roles of CaPAO2 and CaPAO4 in the cold tolerance of pepper (Capsicum annuum L). Int J Mol Sci. 2022;23:9999.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  45. Takahashi H, Iwasa T, Shinkawa T, Kawahara A, Kurusu T, Inoue Y. Isolation and characterization of the ACC synthase genes from lettuce (Lactuca sativa L.), and the involvement in low pH-induced root hair initiation. Plant Cell Physiol. 2003;44:62–9.

    Article  CAS  PubMed  Google Scholar 

  46. Dubois M, Van den Broeck L, Inzé D. The pivotal role of Ethylene in Plant Growth. Trends Plant Sci. 2018;23:311–23.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  47. Müller M, Munné-Bosch S. Ethylene Response factors: a key regulatory hub in hormone and stress signaling. Plant Physiol. 2015;169:32–41.

    Article  PubMed  PubMed Central  Google Scholar 

  48. Shekhawat K, Fröhlich K, García-Ramírez GX, Trapp MA, Hirt H. Ethylene: a master regulator of plant-microbe interactions under abiotic stresses. Cells. 2022;12:31.

    Article  PubMed  PubMed Central  Google Scholar 

  49. Huang X-L, Li X-J, Li Y, Huang L-Z. The effect of AOA on ethylene and polyamine metabolism during early phases of somatic embryogenesis in Medicago sativa. Physiol Plant. 2001;113:424–9.

    Article  CAS  PubMed  Google Scholar 

  50. Zhang X, Li X, Zhao R, Zhou Y, Jiao Y. Evolutionary strategies drive a balance of the interacting gene products for the CBL and CIPK gene families. New Phytol. 2020;226:1506–16.

    Article  CAS  PubMed  Google Scholar 

Download references

Acknowledgements

Not applicable.

Funding

This study was financially supported by the National Natural Science Foundation of China (31960417).

Author information

Authors and Affiliations

  1. Faculty of Animal Science and Technology, Yunnan Agricultural University, 650201, Kunming, China

    Xiaoxue Zhao

  2. College of Horticulture and Landscape, Yunnan Agricultural University, 650201, Kunming, China

    Shiyu Wang

  3. College of Agronomy and Biotechnology, Yunnan Agricultural University, 650201, Kunming, China

    Fenggen Guo & Pan Xia

Authors
  1. Xiaoxue Zhao
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Shiyu Wang
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Fenggen Guo
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Pan Xia
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

X.Z. and S.W. conceived the idea and designed the research. X.Z performed the bioinformatics analysis and wrote the manuscript. P.X. contributed to the visualized data. F.G. reviewed the manuscript of the paper and approved the final manuscript. All authors have read and agreed to the published version of the manuscript.

Corresponding author

Correspondence to Fenggen Guo.

Ethics declarations

Ethics approval and consent to participate

Not applicable.

Consent for publication

Not applicable.

Conflict of interest

The authors declare that they have no competing financial interests or personal relationships that may have influenced the work reported in this study.

Competing interests

The authors declare no competing interests.

Additional information

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Electronic supplementary material

Below is the link to the electronic supplementary material.

Supplementary Material 1

Rights and permissions

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Zhao, X., Wang, S., Guo, F. et al. Genome-wide identification of polyamine metabolism and ethylene synthesis genes in Chenopodium quinoa Willd. and their responses to low-temperature stress. BMC Genomics 25, 370 (2024). https://doi.org/10.1186/s12864-024-10265-7

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1186/s12864-024-10265-7

Keywords

BMC Genomics

ISSN: 1471-2164

Contact us