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Article

The Potassium-Dependent Transcriptome Analysis of Maize Provides Novel Insights into the Rescue Role of Auxin in Responses to Potassium Deficiency

by
Dongying Zhou
1,
Kai Wang
1,
He Zhang
1,
Qi Du
1,2,
Yingyan Liu
1,
Jing Wang
1,
Xiaoguang Wang
1,
Haiqiu Yu
1 and
Xinhua Zhao
1,*
1
College of Agronomy, Shenyang Agricultural University, Shenyang 110866, China
2
Coastal Agriculture Institute, Hebei Academy of Agricultural and Forestry Sciences, Tangshan 063299, China
*
Author to whom correspondence should be addressed.
Agronomy 2022, 12(6), 1318; https://doi.org/10.3390/agronomy12061318
Submission received: 19 May 2022 / Revised: 24 May 2022 / Accepted: 27 May 2022 / Published: 30 May 2022
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Abstract

:
Potassium (K+) deficiency is a key factor limiting maize growth and yield. Auxin plays an important role in maize adaptation to K+ deficiency, but its physiological and molecular mechanisms are largely unclear. In this study, the exogenous application of 0.01 μmol·L–1 α-Naphthalene acetic acid (NAA) could effectively alleviate the growth inhibition of maize roots caused by K+ deficiency, especially in the low-K-sensitive maize inbred line D937. The transcriptome results showed that 3924 and 5458 genes were differentially expressed by exogenous NAA in D937 (sensitive to K+ deficiency) and 90-21-3 (tolerant to K+ deficiency) under K+ deficiency, respectively. The exogenous application of NAA to D937 results in maintenance of the indole acetic acid (IAA) levels by inducing an upregulation in the expression of YUCCA-encoding genes and decreases abscisic acid (ABA) content by inducing the differential expression of genes encoding NCED (downregulated), ABA2 (downregulated), and PP2C (upregulated), thereby reducing growth damage caused by K+ deficiency. In 90-21-3, exogenous NAA can decrease ABA content and increase IAA/ABA by inducing the differential expression of CYP707- and ABF-related genes, inhibiting the excess accumulation of reactive oxygen species by inducing the differential expression of genes encoding antioxidant enzymes, and maintain cellular K+ homeostasis by regulating the expression of genes encoding K+ channels and transporters, thus enhancing plant tolerance to K+ deficiency. This study lays the foundation for understanding the molecular mechanisms underlying maize adaptation to K+ deficiency.

1. Introduction

Potassium (K+) is an essential element for growth and development in plants that plays a crucial role in multiple physiological processes [1,2,3,4,5]. However, the availability of K+ in arable soil rapidly decreases in long-term intensive cropping systems due to leaching loss, continuous cropping, and soil erosion [6,7]. In the determination of available K+ content in surface soil samples from nine important agricultural regions in China, the content of high-availability K+ and maximum available K+ were found to be relatively insufficient in most eastern regions [8]. Maize (Zea mays L.) is one of the most important cereal crops for global food and fodder security, but K+ deficiency in most arable soils hinders its global productivity [9,10]. There is evidence that stomatal conductance, photosynthesis-related enzyme activities, and net photosynthetic rate are significantly reduced in maize under K+ deficiency conditions [11]. Moreover, root development can also be impeded by K+ deficiency, resulting in shorter roots with a lower surface area and volume and, thereby, resulting in reduced nutrient absorption, lower material conversion efficiency, and a significantly reduced yield of plants [1,12,13]. Although the most effective way to alleviate K+ deficiency in arable soil is fertilization, the supply of K+ fertilizers sourced from K+-bearing minerals, the most scarce in China, is finite [14,15]. Therefore, breeding K+ deficiency-tolerant varieties and developing innovative cultivation techniques for efficient K+ utilization have been proposed as strategies toward solving the problem of K+ deficiency to facilitate sustainable maize production.
To adapt to K+ deficiency, plants have evolved sophisticated signaling networks, including activating root growth within the pathway of nutrient availability to coordinate sensing, absorbing, transporting, and utilization of K+ at deficient levels [5,16,17]. Plant roots exhibit strong plasticity under K+ deficiency; for example, the number, length, angle, and diameter of primary roots, lateral roots, and root hairs can be altered to optimize K+ capture [18]. Under longer periods of K+ starvation, the development of primary and lateral roots is restricted, and shoot biomass is decreased [19,20,21]. Different plant species or genotypes of the same species show obviously varied K+ absorption and utilization efficiencies [22]. Substantial evidence shows that the K+ deficiency can also stimulate root hair elongation in many crops [22,23]. Two extreme strategies for morphological adaption to K+ starvation have been implemented by different genotypes in Arabidopsis, one of which is to maintain main root growth at the expense of lateral root elongation, and the other is to arrest main root elongation in favor of lateral root branching [24]. Under K+ deficiency, tolerant varieties could expand their coverage area by extending root length and reducing root diameter, consequently promoting K+ uptake, as observed in sweet potato [25]. The K+-efficient phenotype is characterized by a larger surface area of contact between roots and soil, leading to an enlarged diffusion gradient to roots by increasing absorption at the root–soil interface [26]. Therefore, one of the main potential approaches for genetic improvement of K+ efficiency in crops is to optimize their root architecture, which comprises primary roots, lateral roots, and root hairs.
Auxin, the central hormone for root growth and development, can regulate the plasticity and flexibility of root development according to environmental induction [27,28,29,30]. The indole acetic acid (IAA) content in Arabidopsis roots becomes significantly decreased under low-K stress [31], which may be caused by the downregulated expression of genes involved in auxin biosynthesis in roots and shoots [19]. Recent studies have shown that low-K stress can prevent primary root growth due to inhibition of the vesicular trafficking of auxin efflux carrier PIN1 protein and the decreased auxin concentration in Arabidopsis root tips [32]. In addition, the transcription factor MYB77 could positively regulate HAK5 expression and enhance K+ uptake to induce the elongation of Arabidopsis root hairs under low-K stress [33,34]. The exogenous application of NAA can increase the levels of auxin produced in root tips and promote the formation and elongation of tobacco lateral roots under low-K stress [35].
Our previous studies indicated that the increase in IAA in the roots of a low-K-tolerant maize inbred line (90-21-3) stimulated lateral root development, and the activities of antioxidant enzymes were also significantly increased, which led to elimination of reactive oxygen species (ROS) and thus the maintenance of physiological functions under low-K stress [13]. However, the molecular and physiological mechanisms of auxin-regulated adaptation to K+ deficiency in maize remain unclear. Therefore, in this study, our objectives were to study the effects on maize roots resulting from the application of exogenous NAA at the seedling stage under low-K stress and to specifically (i) observe the morphological and physiological variations in roots, (ii) explore the transcriptomic changes in roots, and (iii) elucidate the mechanisms by which exogenous NAA regulates antioxidant capacity at the root hormone level. These results should further our understanding of the molecular mechanisms underlying the potential responses to K+ deficiency in maize.

2. Materials and Methods

2.1. Plant Materials and Experimental Design

Two maize (Zea mays L.) inbred lines with low-K-sensitive (D937) and low-K-tolerance (90-21-3) were selected, belonging to Ludahonggu and Reid cultivars, respectively [12]. Soil potassium deficiency at the seedling stage caused obvious yellowing symptoms of D937 leaves, but with no visible symptoms in 90-21-3. In K+ deficient soil, plant biomass and grain yield of 90-21-3 at the mature stage were significantly higher than those of D937. The study on plants complied with relevant institutional, national, and international guidelines and legislation.
Experiments were conducted in a solar greenhouse at the experimental base of Shenyang Agricultural University, Shenyang (41.8°N, 123.4°E). Unbroken maize seeds of normal size and plumpness were selected and surface-sterilized with 10% NaClO solution for 10 min. A filter paper roll system was used to grow the maize seeds to the 2-leaf stage [36]. After removing the endosperm, seedlings were carefully selected and transferred into 3 L hydroponic containers with 5 plants per container. The basic nutrient solution was 0.5× modified Hoagland nutrient solution (BNS). The major elements of BNS are as follows: 2.0 mmol·L–1 Ca(NO3)2, 2.0 mmol·L–1 NaNO3, 1.0 mmol·L–1 MgSO4, 0.5 mmol·L–1 NH4H2PO4, and 100 mmol·L–1 FeNa-EDTA. The micronutrient composition of BNS is as follows: 23 μmol·L–1 H3BO3, 6.3 μmol·L–1 MnSO4, 0.16 μmol·L–1 CuSO4, 0.383 μmol·L–1 ZnSO4, and 0.809 μmol·L–1 (NH4)6Mo7O24. Maize seedlings at the 2-leaf stage were independently subjected to the three following treatments, with three replicates per treatment: LK (BNS + 0.2 mmol·L–1 KCl), and LK + NAA (BNS + 0.2 mmol·L–1 KCl + 0.01 μmol·L–1 NAA) [37]. The nutrient solution was continuously aerated and changed every 3 days throughout the experiment, while reductions in volume were supplemented daily with distilled H2O, and the pH was checked daily and maintained at 6.00 ± 0.05.

2.2. Root Morphological and Seedling Dry Matter Accumulation

After 3, 6, 9, 12, and 15 days of different nutrient solution treatments, plants were collected to conduct root morphological analysis and determine their dry weight.
Total root length (TRL), root average diameter (RAD), and number of root tips (RT) were measured using the WinRhizo scanner-based image analysis system (Regent Instruments, Montreal, QC, Canada). The primary root length (PRL) was measured using a ruler [38]. The lateral root length (LRL) was calculated as the difference between the TRL and PRL.
For dry matter determination, three seedlings were chosen randomly for one replicate, and three replicates were used for each treatment. Seedlings were divided into shoots and roots, exposed to 105  °C for 60 min, and then dried at 75 °C to constant weight. The dry tissue samples were weighed to obtain the dry weight. The root–shoot ratio (R/S) was determined by dividing the total root dry weight (RDW) by the shoot dry weight (SDW) per seedling.

2.3. Hormone Determination

After 6 days of LK and LK + NAA treatment, 1.0 g of D937 and 90-21-3 root samples were quickly placed in liquid nitrogen following collection and then ground into homogenate. Then, the IAA and ABA content were detected using MetWare (http://www.metware.cn/, accessed on 28 October 2020) based on the AB Sciex QTRAP4500 LC-MS/MS platform (Applied Biosystems, Foster City, CA, USA). Each treatment contained three replicates [39].

2.4. Determination of ROS and MDA

The hydrogen peroxide (H2O2) content of superoxide anion radical scavenging activities in the root were measured using a Hydrogen Peroxide Assay Kit and an Inhibition and Produce Superoxide Anion Assay Kit (colorimetric method), respectively (Nanjing Jiancheng Bioengineering Institute, Nanjing, China). Antisuperoxide anion (anti-O2•–) activity is negatively correlated with the accumulation of O2•– [40].
Malondialdehyde (MDA) content was determined using the method of Li et al. [41]. Then, 0.1 g fresh root samples were ground and transferred to a 10 mL glass tube; 5 mL of 5% (w/v) trichloroacetic acid (TCA) was added to the tube and centrifuged at 3000 rpm for 10 min at 4 °C. Then, 2 mL of supernatant was mixed with 0.67% thiobarbituric acid solution and heated in a 100 °C water bath for 30 min. Subsequently, the mixture was centrifuged at 3000 rpm for 10 min at 4 °C, and the supernatant was collected. Absorbance was measured at 600, 450, and 532 nm using a spectrophotometer.

2.5. Antioxidant Enzyme Activity Assay

Fresh root samples were weighed and 0.5 g ground into fine powder after freezing in liquid nitrogen. Then, 5 mL of 0.2 mol·L–1 potassium phosphate buffer (pH 7.8 containing 0.1 mmol·L–1 EDTA) was added and centrifuged at 4 °C and 10,000 rpm for 20 min. The supernatant was taken as the crude enzyme extract.
For the determination of peroxidase (POD) activity, the improved guaiacol oxidation method of Maechlay and Chance was used [42]. Briefly, 100 mL of 0.1 mol·L–1 phosphate buffer (pH 6.0) was placed in the beaker with the addition of 56 μL of guaiacol, and the mixture was heated with magnetic stirring until complete dissolution. After cooling, 38 μL of 30% hydrogen peroxide solution was added and mixed as the reaction solution. During the determination, 20 μL enzyme solution was added to 3 mL of reaction solution in a colorimetric dish. The change in the absorbance of the mixture was read at 470 nm and recorded every 30 s for 180 s.

2.6. RNA-seq Analysis

Total RNA was extracted from roots treated with LK and LK + NAA [43]. RNA samples from three biological repeats were pooled together for qPCR analysis, and at least three technical replicates were analyzed for each pooled sample. RNA purity was assessed by agarose gel electrophoresis. RNA concentration was measured using the Qubit® RNA assay kit in Qubit® 2.0 fluorescence spectrometer (Life Technologies, Carlsbad, CA, USA). An RNA Nano 6000 Assay Kit on an Agilent Bioanalyzer 2100 system (Agilent Technologies, Santa Clara, CA, USA) was used to evaluate RNA integrity (RIN). Then, the RNA was used to prepare a cDNA library using the NEBNext® UltraTM RNA Library Prep Kit, and sequencing was conducted using the standard Illumina protocol in Wuhan MetWare Biotechnology Co., Ltd. (http://www.metware.cn/, accessed on 10 December 2020).
Raw data obtained by sequencing were filtered, mainly to remove sequences with adaptors plus sequences of low sequencing quality, for which it was impossible to determine the base information. The remaining clean reads were then mapped to the reference Zea mays genome sequence Zm-B73-REFERENCE-NAM-5.0 (http://ensembl.gramene.org/Zea_mays, accessed on 18 December 2020). Feature Counts v1.6.2 was used to perform the gene alignment, and the fragments per kilobase of transcript per million fragments mapped (FPKM) of each gene were calculated based on gene length. DESeq2 v1.22.1 was used to analyze the differential expression between the two groups, and the p-value was corrected using the Benjamini and Hochberg method. The corrected p-value and |log2Foldchange| were used as the threshold for significant differential expression. Enrichment analysis was performed based on a hypergeometric test. For the Kyoto Encyclopedia of Genes and Genomes (KEGG; https://www.genome.jp/kegg, accessed on 25 December 2020), the hypergeometric distribution test was performed with the unit of the pathway; for Gene Ontology (GO, http://www.geneontology.org/, accessed on 26 December 2020), it was performed based on the GO term.

2.7. qPCR

To verify the reliability of the transcriptome data, we measured the expression of 12 genes using real-time quantitative PCR (qPCR). Maize ubiquitin 5 (ZmUBQ5) was used as the internal reference gene. Gene-specific primers were designed using Primer 5 software (Table S1). First-strand cDNA was synthesized from 1 µg of total RNA using a FastQuant RT Kit (Tiangen Biotech, Beijing, China). qPCR was performed on QuantStudio 7 Flex (Applied Biosystems, Waltham, MA, USA) using KAPA SYBR® FAST qPCR Kits (KAPA Biosystems, Wilmington, MA, USA) Master Mix. The program used for qPCR was as follows: 95 °C for 10 min and 40 cycles of 95 °C for 15 s and 60 °C for 1 min. Melting curve analysis was used to verify the specificity of the reactions. The relative expression of genes was calculated using the delta-delta Ct method (∆∆Ct) [44]. qPCR was performed at least three times under the same conditions for each sample.

2.8. Statistical Analysis

All the sequence data in this study are available in the Sequence Read Archive (SRA) database (SRA accession number of RNA-seq data: PRJNA810588). Data were analyzed using Microsoft Excel and plotted using origin2021b software. Statistical analyses were performed using SPSS 17.0 software (SPSS, Inc. Chicago, IL, USA). Venn diagrams, bubble plots, heatmaps, and circle diagrams were prepared using OmicShare tools (www.omicshare.com/tools, accessed on 18 January 2022). The Student’s t-test was used to assess differences; p  <  0.05 was considered significant.

3. Results

3.1. Changes in Root Morphology

The lateral root length (LRL) of D937 and 90-21-3 began to change significantly compared with the LK treatment after 6 days of exogenous NAA treatment (p < 0.05). Among them, LRL of 90-21-3 significantly decreased by 13.87% compared with LK at 15 days under LK+NAA treatment (p < 0.05) (Figure 1a,b). Moreover, D937 and 90-21-3 appeared to inhibit primary root length (PRL) elongation and promote root tips (RT) germination to alleviate damage in response to LK treatment on roots after exogenous NAA application (Figure 1c,d,g,h). Under LK+NAA treatment, the RT of D937 and 90-21-3 increased by 12.14% and 13.49% compared with LK at 15 days, respectively. Under LK+NAA treatment, the root average diameter (RVD) and RT of D937 and 90-21-3 were significantly increased compared with the LK treatment after 6 days (Figure 1e–h).

3.2. Dry Biomass Accumulation in Seedlings

Under LK+NAA treatment, the shoot dry weight (SDW) did not significantly change relative to the LK in D937 and 90-21-3 (Figure 2a,b). After the addition of exogenous NAA, the root dry weight (RDW) of 90-21-3 significantly decreased compared with the LK treatment from 6 days onwards (Figure 2c,d). Moreover, the root–shoot ratio (R/S) of D937 began to change significantly compared with LK treatment after 6 days of exogenous NAA treatment, with the R/S of D937 higher by 17.59% compared with LK at 15 days (p < 0.05) (Figure 2e,f).

3.3. Transcriptome Sequencing Results and Sequence Assembly

After 6 days, exogenous NAA treatment could effectively alleviate the effects of low-K stress on the root morphology of D937 and 90-21-3. Therefore, we conducted transcriptome comparative analysis and physiological index determination of roots at this stage. RNA sequencing (RNA-seq) was performed for genome-wide gene expression profiling to compare the two maize inbred lines under LK and LK + NAA treatment. The results of the sequencing overview from the data of 45.988 million to 64.437 million original reads from 12 samples were generated by the sequencing platform. More than 95% of the raw reads were clean reads. After Q30 quality control, 92.93% of the data remained, and the GC content was stable at 52.80–54.84%. Next, all clean reads were aligned to the maize B73 inbred line reference genome, and more than 78% of them could be uniquely mapped to the genome (Table S2). These results indicate the high quality of transcriptome assembly.
To analyze the difference in gene expression in D937 and 90-21-3, a bar graph was constructed for the total differentially expressed genes (DEGs) dataset (Figure 3a). A total of 3924 DEGs (2091 up- and 1833 downregulated) were obtained in D937 under LK+NAA treatment, and 5458 DEGs (2985 up- and 2473 downregulated) were obtained in 90-21-3. A total of 1821 DEGs were co-expressed in D937 and 90-21-3 under LK + NAA compared with LK, of which only 8 were downregulated and 32 were upregulated (Figure 3b). The roots of D937 and 90-21-3 may exhibit different response patterns to exogenous NAA under low-potassium stress.

3.4. Enrichment Analysis of Differentially Expressed Genes

We mapped the DEGs of D937 and 90-21-3 under LK+NAA treatment to reference canonical pathways in the KEGG database and obtained 130 and 132 pathways, respectively (Table S3). The ranking of pathways was based on p values identified by KEGG pathway analysis. We determined the top 25 KEGG pathways that were enriched in D937 and 90-21-3 (Figure 4a,b). A total of 20 and 13 significantly enriched KEGG pathways were identified in the D937 and 90-21-3, respectively (p < 0.05). In D937-LK+NAA vs. D937-LK, the most heavily enriched KEGG pathways include phenylpropanoid biosynthesis, indole alkaloid biosynthesis, nitrogen metabolism, and plant hormone signal transduction pathways. In 90-21-3-LK+NAA vs. 90-21-3-LK, KEGG enrichment analysis indicated that biosynthesis of secondary metabolism pathways was predominant, and subsequent analysis revealed that phenylpropanoid biosynthesis, plant hormone signal transduction, and indole alkaloid biosynthesis pathways were particularly enriched. KEGG enrichment analysis showed that phenylpropanoid biosynthesis, indole alkaloid biosynthesis, nitrogen metabolism, and plant hormone signal transduction pathways were enriched in both groups.
In D937-LK+NAA vs. D937-LK and 90-21-3-LK+NAA vs. 90-21-3-LK, DEGs were classified based on biological processes (BP), cellular components (CC), and molecular function (MF) according to the GO database (Table S4). To identify the functional enrichment categories of the DEGs further, we used p < 0.05 to filter the significantly enriched GO categories. In D937-LK+NAA vs. D937-LK, DEGs were significantly enriched for 308 GO terms, of which 212, 12, and 92 were enriched in terms BP, CC, and MF, respectively. We determined the top 25 GO terms enriched in D937-LK+NAA vs. D937-LK. and 90-21-3-LK+NAA vs. 90-21-3-LK (Figure 4c,d). Phenylpropanoid metabolic process (GO: 0009698), extrinsic component of plasma membrane (GO: 0019897), and tetrapyrrole binding (GO: 0046906) were the most abundant GO terms within the BP, CC, and MF categories of D937-LK+NAA vs. D937-LK, respectively. GO analysis identified 333 GO terms significantly enriched with the DEGs in T1 vs. T0: 212 BP, 40 CC, and 81 MF terms. Concerning BP, CC, and MF in 90-21-3-LK+NAA vs. 90-21-3-LK, the most abundant GO terms were hydrogen peroxide metabolic process (GO: 0042743), ribosome (GO: 0005840), and structural constituent of ribosome (GO: 0003735), respectively. The GO term enrichment analysis showed that the DEGs between D937-LK+NAA vs. D937-LK and 90-21-3-LK+NAA vs. 90-21-3-LK were significantly enriched in peroxidase activity (GO:0004601), oxidoreductase activity (GO:0016684), antibiotic catabolic process (GO:0017001), heme binding (GO:0020037), tetrapyrrole binding (GO:0046906), and cofactor catabolic process (GO:0051187).

3.5. DEGs Related to K+ Acquisition and Transport

In the current study, 7 and 8 DEGs in D937 and 90-21-3 were related to K+ uptake and translocation were identified, respectively, under LK+NAA treatment (p-adjust < 0.05 and |log2FC| > 1, Table 1). Among them, the genes encoding potassium transporter (4 downregulated), potassium channel (1 upregulated, 1 downregulated), and metal ion binding protein (1 upregulated) were differentially expressed in D937 under LK+NAA treatment, and genes encoding potassium transporter (5 upregulated), potassium channel (2 upregulated, 1 downregulated) in 90-21-3.

3.6. DEGs Related to Phytohormone Synthesis and Signaling

Through KEGG enrichment analysis, we found that hormone-related pathways played an important role in the process of NAA regulating maize root adaptation to low-K stress. Therefore, we further analyzed the ABA and IAA metabolism-related pathways. In this study, 39 DEGs (23 for D937-LK+NAA vs. D937-LK and 24 for 90-21-3-LK+NAA vs. 90-21-3-LK, 8 common genes) were screened for auxin metabolism (Table S5). Among them, the genes encoding YUCCA (1 upregulated), VAS1 (1 upregulated, 1 downregulated), TDC (3 downregulated), AAO1 (1 downregulated), AMI (2 downregulated), AUX/IAA (1 upregulated, 3 downregulated). TDC (1 downregulated), and SUAR (5 upregulated, 4 downregulated) were differentially expressed in D937-LK+NAA vs. D937-LK, and genes encoding VAS1 (1 upregulated), TDC (1 upregulated), ALDH (3 upregulated), AAO1 (1 upregulated), YUCCA (2 downregulated), AUX1 (3 downregulated), AUX/IAA (1 upregulated, 1 downregulated), ARF (1 upregulated, 1 downregulated), GH3 (1 upregulated, 1 downregulated), and SAUR (7 upregulated) were differentially expressed in 90-21-3-LK+NAA vs. 90-21-3-LK (Figure 5a,b). Furthermore, 20 DEGs (8 for D937-LK+NAA vs. D937-LK and 15 for 90-21-3-LK+NAA vs. 90-21-3-LK, 3 common genes) were screened for abscisic acid metabolism. Among them, genes encoding ABA1 (1 upregulated, 1 downregulated), NCED (1 downregulated), ABA2 (1 downregulated), CYP707A (1 upregulated, 1 downregulated), PP2C (1 upregulated), and SRK2 (1 upregulated) were differentially expressed in S1 vs. S0, and the genes encoding ABA1 (2 upregulated), NCED (1 upregulated), ABA2 (3 upregulated), CYP707A (2 upregulated), PYR/PYL (2 upregulated), SRK2 (1 upregulated) and ABF (3 downregulated, 1 upregulated) were differentially expressed in 90-21-3-LK+NAA vs. 90-21-3-LK (Figure 5c,d).
After NAA was added, the IAA and ABA content in the roots of D937 and 90-21-3 decreased, and the ABA content significantly decreased by 28.22% and 73.79% compared with LK treatment, respectively (p < 0.05). This promoted an increase in IAA/ABA ratio of D937 and 90-21-3 under LK+NAA treatment, which indicates that the levels of growth hormone were higher than those of inhibitory hormones, and the effect was more pronounced in 90-21-3 (Figure 6a–c).

3.7. Oxidative Stress

According to the GO enrichment analysis of the DEGs, 119 DEGs (54 for D937-LK+NAA vs. D937-LK and 92 for 90-21-3-LK+NAA vs. 90-21-3-LK, 27 common genes) were involved in peroxidase activity in both maize lines (Table S6). Among them, a large number of DEGs were found to be involved in the expression of peroxidase genes (PODs) in both maize lines, and most of them were upregulated in 90-21-3-LK+NAA vs. 90-21-3-LK in addition to the gene encoding L-ascorbate peroxidase (SAPX, upregulated) in both D937-LK+NAA vs. D937-LK and 90-21-3-LK+NAA vs. 90-21-3-LK. Further examination revealed genes encoding glutathione peroxidase (GPxs, upregulated) and catalase (cat2, upregulated) in 90-21-3-LK+NAA vs. 90-21-3-LK (Figure 7a). We determined the antioxidant indices of roots treated with LK and LK + NAA for 6 days. The results showed that the activities of anti-O2•– and POD were higher in the roots of maize seedlings under LK+NAA treatment (Figure 7b,c). Additionally, POD activity was significantly increased in 90-21-3 under LK+NAA treatment (p < 0.05). Under LK+NAA treatment, the H2O2 and MDA content of the D937 and 90-21-3 seedlings roots were decreased compared with the LK treatment (Figure 7d,e).

3.8. Validation of Gene Expression by qPCR

To confirm the reliability of the expression profile data obtained by RNA-seq analysis, we randomly selected 12 candidate DEGs for qPCR analyses. Details of the selected genes and the specific primers used are shown in Table S1. The qPCR results of all 12 genes (3 for phytohormones and 9 for oxidative stress) were perfectly consistent with the RNA-seq data (Table S1), suggesting the high reliability and accuracy of RNA-seq.

4. Discussion

4.1. Regulatory Effect of Exogenous NAA on Low-K Tolerance of Maize

The root system directly impacts mineral nutrient acquisition and responds to nutrient abundance and deficiency. In low-potassium-tolerant plants, a short period of K+ deficiency stress can promote plant growth, which is referred to as the stress-induced morphological response (SIMR). Lateral roots, one of the most important root types for plants to absorb soil nutrients and water, show high developmental plasticity under stress [45]. In the present study, low-K-tolerant maize inbred line 90-21-3 showed significantly higher lateral root length, root dry weight, and root–shoot ratio, but the low-K-sensitive maize inbred line D937 showed significantly lower root length and dry matter accumulation under low-K stress. This is consistent with previous research on the root systems of pear trees [46] and barley seedlings [47]. Therefore, lateral roots may respond differently to nutrient stress among different crop varieties. Auxin (indole acetic acid, IAA) plays an important role in plant growth and development, such as in the processes of plant cell elongation and division, root hair formation, and the growth of the main and lateral roots [35,48]. This study demonstrated that exogenous application of NAA was able to promote the accumulation of substances and the increase in the length of D937 roots under low-K stress. This is consistent with the results from previous studies [49]. In addition, the Alarcon study on maize lateral roots found that exogenous NAA could prolong the germination area of maize lateral roots [50] and significantly increase the number of root tips, which is consistent with the results of this study.

4.2. Regulation of Exogenous NAA on K+ Channels and Transporter Genes under Low-K Stress

Under low-K stress, plants can maintain cellular K+ homeostasis through strategies such as altering root development and root architecture, improving K+ uptake and transport, and redistributing K+ between the cytoplasm and cell membrane. Among them, K+ absorption and transport are mediated by several types of channels and transporters. Generally, K+ channels mediate low-affinity K+ uptakes, and K+ transporters assume high-affinity K+ uptakes. There are three main types of K+ channels: (i) shaker-like K+ channels; (ii) tandem-pore K+ channels; (iii) inwardly rectifying K+ channels. Notably, K+ Shaker channels are involved in many physiological processes that require sustained large-scale K+ fluxes [30,51]. In the present study, the results showed that the addition of NAA in D937 roots upregulated the expression of Zm00001d012717 (potassium channel KAT1). Moreover, exogenous NAA induced upregulation of Zm00001d011473 (inward rectifying potassium channel, ZMK1) and inhibited the expression of Zm00001d037289 (outward rectifying potassium channel, ZORK) in 90-21-3. Among them, KAT1 and ZMK1 transcription are induced specifically by active auxin [5,52]. In plants, potassium transporters are encoded by four multigene families: (i) HAK/KUP/KT family; (ii) HKT family; (iii) KEA family; and (iv) CHX family. There are various K+/H+ symporters in the KT/HAK/KUP family participate in high-affinity K+ uptake in roots. Furthermore, some of these transporters are involved in physiological processes, including cell elongation, root hair elongation, and auxin transport [30]. The current study found that exogenous NAA could increase the transcript level of HAKs in 90-21-3 roots, whereas inhibited the transcription of HAKs in D937. This intriguing result could be due to the inhibition of 90-21-3 lateral root elongation within exogenous NAA under low-K stress.

4.3. Regulation of Exogenous NAA on Hormone Synthesis and the Signal Transduction Pathway under Low-K Stress

Exogenous auxin can alter the activity levels and gene expression patterns of the synthesis and signal transduction pathways of plant hormones under nutrient stress [53]. Transcriptome analysis under K+ deficiency was previously used to identify 33 hormone-related genes in rice roots, most of which were related to auxin [54]. Furthermore, it was found that ROS accumulation is significantly increased, and the expression of K+ uptake and transport-related genes is upregulated, but that of eight auxin-related genes is downregulated under K+ deficiency in N. cadamba [55]. Three tryptophan-dependent pathways are responsible for producing IAA: (i) the indole-3-pyruvic acid (IPA) pathway, (ii) the indole-3-acetaldoxime (IAOx) pathway, and (iii) the indole-3-acetamide (IAM) pathway. Among these, the IPA pathway is the main pathway of IAA synthesis [56]. In the present study, results showed that the addition of NAA in 90-21-3 roots not only upregulated the expression of VAS1 (LOC100285201), a negative regulator of IAA synthesis but also downregulated the expression of genes related to YUCCA (LOC103646858 and LOC1002876), a positive regulator of IAA synthesis. This may be related to the passive transport of NAA into root cells through the lipid membrane, thus replacing endogenous auxin [57]. In the auxin signal transduction pathway, the SAUR gene family is the most abundant auxin primary response gene. This study showed that exogenous NAA could induce the expression of a large number of SAUR-related genes under low-potassium stress, and all were upregulated in 90-21-3. Studies on Arabidopsis thaliana have shown that exogenous auxin treatment can significantly upregulate SAUR76 and SAUR41 expression, thereby increasing root length [58]. However, the overexpression of OsSAUR39 in rice inhibited root elongation and lateral root development [59]. Therefore, further studies are needed to determine precisely how SAUR proteins regulate root growth and development.
ABA, as a stress hormone, plays a regulatory role in biological and abiotic stress. In Arabidopsis mutants, ABA and IAA regulate root development via interactions. For example, PYL9 can enhance the expression of MYB77 in the ABA signaling pathway, thereby promoting the interaction between MYB77 and ARF to regulate the formation of lateral roots [60]. NCED and ABA2 are positive regulators of ABA biosynthesis, and the expression of NCED gene family members is particularly closely related to changes in endogenous ABA levels. The 80-hydroxylation of ABA by the CYP707A subfamily of cytochrome P450 monooxygenases is the main pathway of ABA degradation [61]. Through comparative transcriptional analysis, we found that exogenous NAA could inhibit the expression of NCED (LOC100383768), ABA2 (Zm00001d007705), and CYP707A (LOC100383693, LOC103647484) in 90-21-3, which may be related to the significantly decreased ABA content in the roots of both inbred maize lines. In addition, exogenous NAA induced upregulation of PP2C (Zm00001d011132) in D937, which is a negative regulator of ABA signal transduction, and inhibited the expression of ABF (LOC100191211, LOC100037791, and LOC103643147) in 90-21-3, which is a positive regulator of ABA signal transduction. The findings presented above show that ABA played an important role in maize tolerance to low-K, but their functions should be further studied.

4.4. Exogenous NAA and Regulation of the Antioxidant System under Low-K Stress

ROS, as signal molecules, play an important role in the process of plant roots sensing and transmitting signals of low potassium [30]. Low-K stress promotes root growth by activating ROS in Arabidopsis thaliana [62]. The excessive accumulation of ROS in plant cells affects cell physiological activities, signal transduction, and membrane stability, eventually leading to programmed cell death [63]. Oxidative stress can induce a large number of antioxidant enzymes, thereby inhibiting reactive oxygen species-induced programmed cell death. However, as a negative regulator, auxin can inhibit the expression of the peroxidase gene by binding to auxin response elements in the promoter [64]. In this study, under exogenous NAA treatment, the higher IAA level in the D937 roots may be caused by the downregulation of PODs in the D937 roots. The low IAA level in 90-21-3 roots may be upregulated by PODs and GPxs, which promotes the antioxidant capacity of the roots. A study on A. thaliana found that the production of peroxidase and glutathione peroxidase could regulate lateral root growth by oxidizing IAA [65]. Thus, we speculate that exogenous NAA can regulate low-K stress through crosstalk with the ROS signaling pathway or other pathways, but the underlying mechanism should be further studied.

5. Conclusions

In summary, exogenous NAA treatment could significantly alleviate the inhibitory effect of low K+ on the root morphology of D937 and 90-21-3. Through the analysis of transcriptional groups and physiological indices, we found that, after the exogenous application of NAA, D937 could maintain the IAA level in roots by regulating the genes encoding YUCCA and POD and induce the differential expression of genes encoding NCED, ABA2, and PP2C to reduce the ABA content, which promoted the germination and elongation of lateral roots under low-K stress and improved the area covered by roots. In 90-21-3, the expression of genes encoding CYP707 and ABF decreased the ABA content, increased IAA/ABA, and decreased the accumulation of ROS in roots by inducing the expression of genes encoding antioxidant enzymes, and maintained cellular K+ homeostasis by regulating the expression of genes encoding K+ uptake and transport, thus improving the ability to tolerate low K. Under low-K stress, differences were apparent in the root regulation mechanisms of D937 and 90-21-3 in response to exogenous NAA. This paper could contribute to a better understanding of the internal physiological mechanism of maize roots responding to low-K stress and will provide a solid basis for chemical regulation of root development and accelerate the breeding of superior cultivars.

Supplementary Materials

The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/agronomy12061318/s1, Table S1: Genes and the corresponding primers for the quantitative real-time PCR analysis, Table S2: Statistics of RNA-seq data and reads mapping, Table S3: KEGG pathways enrichment analysis of DEGs in D937-LK+NAA vs. D937-LK and 90-21-3-LK+NAA vs. 90-21-3-LK, Table S4: GO enrichment analysis of DEGs in D937-LK+NAA vs. D937-LK and 90-21-3-LK+NAA vs. 90-21-3-LK, Table S5: Differential expression of auxin and abscisic acid metabolism-related genes in D937-LK+NAA vs. D937-LK and 90-21-3-LK+NAA vs. 90-21-3-LK, Table S6: Differential expression of oxidative stress-related genes in D937-LK+NAA vs. D937-LK and 90-21-3-LK+NAA vs. 90-21-3-LK.

Author Contributions

Conceptualization, D.Z. and X.Z.; methodology, Q.D. and X.W.; software, Q.D. and J.W.; validation, Q.D. and K.W.; formal analysis, D.Z.; investigation, D.Z., Y.L. and K.W.; resources, Q.D., J.W. and X.W.; data curation, D.Z. and H.Z.; writing—original draft preparation, D.Z.; writing—review and editing, D.Z., H.Z. and X.Z.; visualization, D.Z.; supervision, X.Z. and H.Y.; project administration, X.Z.; funding acquisition, X.Z. and H.Y. All authors have read and agreed to the published version of the manuscript.

Funding

This research was supported by the National Natural Science Foundation of China (31771725).

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

Not applicable.

Conflicts of Interest

The authors declare no competing interest.

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Figure 1. Effects of LK and LK + NAA treatments on root morphology of D937 and 90-21-3 maize seedlings. (a–h) Bar graph, mean ± SE of lateral root length (LRL, (a,b)), primary root length-PRL, (c,d)), root average diameter (RAD, (e,f)), and the number of root tips (RT, (g,h)). For all bar charts, * p  <  0.05 indicate a significant difference between different treatments under the same variety.
Figure 1. Effects of LK and LK + NAA treatments on root morphology of D937 and 90-21-3 maize seedlings. (a–h) Bar graph, mean ± SE of lateral root length (LRL, (a,b)), primary root length-PRL, (c,d)), root average diameter (RAD, (e,f)), and the number of root tips (RT, (g,h)). For all bar charts, * p  <  0.05 indicate a significant difference between different treatments under the same variety.
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Figure 2. Effects of LK and LK + NAA treatment on dry matter accumulation of D937 and 90-21-3 maize seedlings. Bar graph, mean ± SE of D937 and 90-21-3 shoot dry weight (SDW, (a,b)), root dry weight (RDW, (c,d)), and root–shoot ratio (R/S, (e,f)), respectively. For all bar charts, * p  <  0.05 indicate a significant difference between different treatments under the same variety.
Figure 2. Effects of LK and LK + NAA treatment on dry matter accumulation of D937 and 90-21-3 maize seedlings. Bar graph, mean ± SE of D937 and 90-21-3 shoot dry weight (SDW, (a,b)), root dry weight (RDW, (c,d)), and root–shoot ratio (R/S, (e,f)), respectively. For all bar charts, * p  <  0.05 indicate a significant difference between different treatments under the same variety.
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Figure 3. The number of differentially expressed genes (DEGs). (a) Number of DEGs in D937 under LK + NAA compared with LK. (FPKM > 50). (b) Venn diagram of DEGs commonly or specifically in D937 and 90-21-3.
Figure 3. The number of differentially expressed genes (DEGs). (a) Number of DEGs in D937 under LK + NAA compared with LK. (FPKM > 50). (b) Venn diagram of DEGs commonly or specifically in D937 and 90-21-3.
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Figure 4. KEGG pathway and GO enrichment analysis of DEGs. (a,b) Bubble plot of the top 25 significantly enriched KEGG pathways of D937-LK+NAA vs. D937-LK and 90-21-3-LK+NAA vs. 90-21-3-LK. (c,d) Circle diagram of the top 25 significantly enriched GO terms of D937-LK+NAA vs. D937-LK and 90-21-3-LK+NAA vs. 90-21-3-LK; Moving inside, the 1st circle illustrates the GO term, colored according to different functional categories. The 2nd circle illustrates the number of DEGs matched in the term, and the color depth denotes the degree of correlation. The 3rd circle displays upregulated (purple) and downregulated (blue) DEGs. The 4th (innermost) circles represent the Rich Factor values for different GO terms, with each cell of the background helpline representing 0.1.
Figure 4. KEGG pathway and GO enrichment analysis of DEGs. (a,b) Bubble plot of the top 25 significantly enriched KEGG pathways of D937-LK+NAA vs. D937-LK and 90-21-3-LK+NAA vs. 90-21-3-LK. (c,d) Circle diagram of the top 25 significantly enriched GO terms of D937-LK+NAA vs. D937-LK and 90-21-3-LK+NAA vs. 90-21-3-LK; Moving inside, the 1st circle illustrates the GO term, colored according to different functional categories. The 2nd circle illustrates the number of DEGs matched in the term, and the color depth denotes the degree of correlation. The 3rd circle displays upregulated (purple) and downregulated (blue) DEGs. The 4th (innermost) circles represent the Rich Factor values for different GO terms, with each cell of the background helpline representing 0.1.
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Figure 5. Expression of auxin and abscisic acid-related genes induced by exogenous NAA. (a,c) Simplified biosynthesis and signal transduction pathway of auxin and abscisic acid, respectively. (b,d) DEGs of transcription factors and protein kinases, false discovery rate (FDR) < 0.05, |log2FC| > 1.
Figure 5. Expression of auxin and abscisic acid-related genes induced by exogenous NAA. (a,c) Simplified biosynthesis and signal transduction pathway of auxin and abscisic acid, respectively. (b,d) DEGs of transcription factors and protein kinases, false discovery rate (FDR) < 0.05, |log2FC| > 1.
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Figure 6. Auxin and abscisic acid content. (a–c) Bar graph represented as mean ± SE of IAA content, ABA content, and IAA/ABA, respectively. For all bar charts, * p  <  0.05 and ** p  <  0.01 indicate a significant difference between different treatments under the same variety.
Figure 6. Auxin and abscisic acid content. (a–c) Bar graph represented as mean ± SE of IAA content, ABA content, and IAA/ABA, respectively. For all bar charts, * p  <  0.05 and ** p  <  0.01 indicate a significant difference between different treatments under the same variety.
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Figure 7. Oxidative stress-related genes and matter change. (a) Heat maps representing genes involved in oxidative stress. (b–e) Bar graph represented as mean ± SE of anti-O2•– activity (antisuperoxide anion activity), POD activity (peroxidase activity), H2O2 content (hydrogen peroxide content), and MDA content (malondialdehyde content), respectively. For all bar charts, * p  <  0.05 and ** p  <  0.01 indicate a significant difference between different treatments under the same variety.
Figure 7. Oxidative stress-related genes and matter change. (a) Heat maps representing genes involved in oxidative stress. (b–e) Bar graph represented as mean ± SE of anti-O2•– activity (antisuperoxide anion activity), POD activity (peroxidase activity), H2O2 content (hydrogen peroxide content), and MDA content (malondialdehyde content), respectively. For all bar charts, * p  <  0.05 and ** p  <  0.01 indicate a significant difference between different treatments under the same variety.
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Table
Table 1. List of differentially expressed genes related to K+ acquisition and transport.
Table 1. List of differentially expressed genes related to K+ acquisition and transport.
Gene IDD93790-21-3Annotation
(log2 LK+NAA/LK)(log2 LK+NAA/LK)
Zm00001d003859−4.047-potassium transporter 19-like, HAK20 [Zea mays]
Zm00001d019631−1.2211.302high-affinity potassium transporter, HAK18 [Zea mays]
Zm00001d020325−1.2361.529high-affinity potassium transporter isoform X1, HAK23
[Zea mays]
Zm00001d022485−1.9572.922potassium transporter 7-like, HAK7 [Zea mays]
Zm00001d025303-1.092potassium transporter 1-like, HAK19 [Zea mays]
Zm00001d033068-3.563high-affinity potassium transporter [Zea mays]
Zm00001d0127171.681-Potassium channel KAT1
[Zea mays]
Zm00001d037289-−1.475outward rectifying potassium channel 1, ZORK [Zea mays]
Zm00001d010209-1.81potassium channel protein ZMK2 [Zea mays]
Zm00001d011473−4.1393.424potassium channel 5, ZMK1 [Zea mays]
Zm00001d0117312.318-metal ion binding protein
[Zea mays]
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Zhou, D.; Wang, K.; Zhang, H.; Du, Q.; Liu, Y.; Wang, J.; Wang, X.; Yu, H.; Zhao, X. The Potassium-Dependent Transcriptome Analysis of Maize Provides Novel Insights into the Rescue Role of Auxin in Responses to Potassium Deficiency. Agronomy 2022, 12, 1318. https://doi.org/10.3390/agronomy12061318

AMA Style

Zhou D, Wang K, Zhang H, Du Q, Liu Y, Wang J, Wang X, Yu H, Zhao X. The Potassium-Dependent Transcriptome Analysis of Maize Provides Novel Insights into the Rescue Role of Auxin in Responses to Potassium Deficiency. Agronomy. 2022; 12(6):1318. https://doi.org/10.3390/agronomy12061318

Chicago/Turabian Style

Zhou, Dongying, Kai Wang, He Zhang, Qi Du, Yingyan Liu, Jing Wang, Xiaoguang Wang, Haiqiu Yu, and Xinhua Zhao. 2022. "The Potassium-Dependent Transcriptome Analysis of Maize Provides Novel Insights into the Rescue Role of Auxin in Responses to Potassium Deficiency" Agronomy 12, no. 6: 1318. https://doi.org/10.3390/agronomy12061318

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