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Article

Transcriptome Analysis of Maize Ear Leaves Treated with Long-Term Straw Return plus Nitrogen Fertilizer under the Wheat–Maize Rotation System

by
Jun Li
1,*,
Jintao Liu
2,
Kaili Zhu
1 and
Shutang Liu
3,*
1
College of Agronomy, Qingdao Agricultural University, Qingdao 266109, China
2
School of Engineering, Universidad de Almería, ES04120 Almería, Spain
3
College of Resources and Environment, Qingdao Agricultural University, Qingdao 266109, China
*
Authors to whom correspondence should be addressed.
Plants 2023, 12(22), 3868; https://doi.org/10.3390/plants12223868
Submission received: 3 October 2023 / Revised: 6 November 2023 / Accepted: 14 November 2023 / Published: 16 November 2023
(This article belongs to the Special Issue Soil Fertility, Plant Nutrition and Nutrient Management)
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Abstract

:
Straw return (SR) plus nitrogen (N) fertilizer has become a practical field management mode to improve soil fertility and crop yield in North China. This study aims to explore the relationship among organic waste, mineral nutrient utilization, and crop yield under SRN mode. The fertilizer treatments included unfertilized (CK), SR (straws from wheat and corn), N fertilizer (N), and SR plus N fertilizer (SRN). SRN treatment not only significantly increased the grain yield, net photosynthetic rate, and transpiration rate but also enhanced the contents of chlorophyll, soluble sugar, and soluble protein and increased the activities of antioxidant enzymes but reduced intercellular CO2 concentration and malondialdehyde (MDA) content when compared to other treatments. There were 2572, 1258, and 3395 differentially expressed genes (DEGs) identified from the paired comparisons of SRvsCK, NvsCK, and SRNvsCK, respectively. The transcript levels of many promising genes involved in the transport and assimilation of potassium, phosphate, and nitrogen, as well as the metabolisms of sugar, lipid, and protein, were down-regulated by straw returning under N treatment. SRN treatment maintained the maximum maize grain yield by regulating a series of genes’ expressions to reduce nutrient shortage stress and to enhance the photosynthesis of ear leaves at the maize grain filling stage. This study would deepen the understanding of complex molecular mechanisms among organic waste, mineral nutrient utilization, crop yield, and quality.

1. Introduction

Massive amounts of chemical nitrogen (N) fertilizers have been applied to agricultural soil for the past forty years. Chemical N plays an important role in enhancing agricultural food production [1]; however, low N utilization efficiency (NUE), nitrate leaching, and severe environmental issues such as the emission of nitrous oxide and ammonia into the atmosphere occurred due to excessive application of chemical N fertilizer [2]. Therefore, it is necessary to search for alternative ways to reduce the overuse of synthetic fertilizers.
The winter wheat-summer maize rotation system is the main cropping mode in North China, producing 518 million tons of straw annually [3,4]. In the past, more than 30% of crop residues were frequently regarded as organic wastes, which were simply burned in fields after harvest and resulted in serious air pollution [5,6]. Nowadays, its beneficial utilization has received much attention because the rotted straw can provide crops with suitable nutrients and various salinities [7]. Straw return (SR) to the field can not only increase soil organic carbon (SOC), maintain soil fertility, and promote crop yield [8,9] but also improve the defense response of plants to diseases [10].
SR plus N fertilizer (SRN) practice has a significant influence on soil fertility and crop yield. In a seven-year-old field experiment, Chen et al. [11] reported that continuous SRN treatment improved maize yield by 154% and meanwhile dramatically increased soil nutrients, including total soil N, available P, available K, enzyme activities (such as invertase, urease, and cellulose) and organic carbon. Yang et al. [8] also demonstrated that SR significantly reduced soil N leaching at 30–90 cm soil depth, increased the NUE, and thus improved the yields of rice and wheat.
Maize (Zea mays L.) is one of the important food, feed, and industrial crops in the world. Although the positive impacts of SRN on soil fertility and crop yield were well documented, little is known regarding the molecular relationship among organic waste, mineral nutrient utilization, and crop yield under SRN mode in long-term field conditions. Till now, no transcriptome analysis of maize responsive to SRN treatment under Wheat–Maize rotation system has been reported in field conditions so far. Considering that ear leaves contribute a substantial proportion of photosynthetic products to maize kernels [12], we conducted transcriptome analysis of ear leaves under different fertilizer treatments using RNA-Seq techniques. The study would provide insights into the molecular mechanism of the enhancements of mineral nutrient utilization and crop yield via SR and its combination with N fertilizer. Also, the study revealed the candidate genes involved in mineral nutrient transport and assimilation and the metabolisms of sugar, lipid, and protein.

2. Results

2.1. Grain Yield and Photosynthetic Parameters under Various Fertilizer Treatments

Compared to the control, the grain yields under SR, N, and SRN treatments in two consecutive years were enhanced by 29%, 71%, 156.8%, and 11.3%, 58.5%, and 131%, respectively, in two consecutive years (Table 1). Long-term SRN treatment exhibited the highest maize grain yield among all treatments. Similarly, SRN treatment also showed higher chlorophyll content, net photosynthetic rate, transpiration rate, and total conductance to water, as well as lower intercellular CO2 concentration and total conductance to CO2 when compared to other treatments (Figure S1). Compared to the control, the chlorophyll content, net photosynthetic rate, transpiration rate, and total conductance to water under SRN treatment were significantly enhanced by 106%, 52%, 58%, and 45%, respectively, whereas the intercellular CO2 concentration and total conductance to CO2 were decreased by 7.5% and 14%, respectively.

2.2. Physiological Changes of Ear Leaves Responsive to Various Fertilizer Treatments

As shown in Figure 1a,b, the contents of soluble sugar and soluble protein were quite lower for maize plants under CK than under fertilizer treatments but reached the maximum under SRN treatment. For instance, the contents of soluble sugar and soluble protein under SRN treatment were 7.3 times and 2.4 times the control, respectively. Besides, maize plants under CK treatment exhibited higher MDA content and lower CAT and POD activities than those under the other three fertilizer treatments, and the plants under SRN showed the lowest MDA content and the highest CAT and POD activities among three treatments (Figure 1c–e). MDA contents under SR, N, and SRN treatments were respectively decreased by 46%, 42%, and 65%, respectively, while CAT and POD enzyme activities were respectively enhanced by 314%, 222%, 571%, 42%, 35%, and 76% when compared to the control.

2.3. Transcriptome Sequencing

After removing the low-quality reads and adaptor sequences, we obtained a total of 974,889,944 clean reads. All clean reads contained 142.0922 Gb with a GC content of above 49%, a Q20 level of above 97.21%, and a Q30 level of above 92.96% (Table S1). For reads mapping, approximately 75% (132,812,884/176,794,952) of the reads were mapped to the maize B73 genome, and about ~65% of the mapped reads (86,264,550/132,812,884) were uniquely mapped (Table S2).

2.4. Identification of DEGs Responsive to Various Fertilizer Treatments

The clean reads from each of the three fertilizer treatments were all compared to those from the control, that is, SR versus CK (SRvsCK), N versus CK (NvsCK), SRN versus CK (SRNvsCK), and pairwise comparison was performed. The genes meeting p-value < 0.05 and ∣log2FC∣ ≥ 1.0 were chosen as DEGs for further analysis (Figure S2). Finally, we identified 2572 DEGs (1386 up-regulated and 1186 down-regulated) from SRvsCK, 1258 DEGs (704 up-regulated and 554 down-regulated) from NvsCK, and 3395 DEGs (1817 up-regulated and 1578 down-regulated) from SRNvsCK (Figure 2a). There were 223 common DEGs for the three groups of paired comparisons (Figure 2b). The correlation coefficient between RNA-Seq data and qRT-PCR data was 0.93, indicating that the transcriptome sequencing results are meaningful (Figure 2c).

2.5. GO and KEGG Analysis of the DEGs Responsive to Fertilizer Treatments

GO enrichment analysis of the DEGs demonstrated that the detected GO terms (p-value < 0.05) were involved in three categories: biological process (BP), cellular component (CC), and molecular functions (MF) (Figure S3). Many GO terms like “cell communication” and “response to abiotic stimulus” in biological processes, “chloroplast part” and “mitochondrion” in cellular components, “zinc ion binding” and “protein serine/threonine kinase activity” in molecular functions from SRNvsCK and SRvsCK were exactly the same. In biological processes, some special GO terms were found in one comparison group, like “lipid biosynthetic process” from SRNvsCK, “cellular amino acid metabolic process”, and “organic acid biosynthetic process” from NvsCK and “carbohydrate biosynthetic process” and “response to nutrient levels” from SRvsCK. The numbers of KEGG pathways (p-value < 0.05) detected from SRvsCK, NvsCK, and SRNvsCK are 15, 12, and 15, respectively (Table S3). A few of these KEGG pathways, like “starch and sucrose metabolism” and “nitrogen metabolism”, are commonly in three groups of paired comparisons, but the others are especially found in one or two comparison groups. For example, “carotenoid biosynthesis” and “sphingolipid metabolism” were from SRvsCK, “biosynthesis of amino acids” was from NvsCK, and “MAPK signaling pathway”, “plant hormone signal transduction”, and “fatty acid elongation” were special from SRNvsCK.

2.6. DEGs Involved in Mineral Nutrient Transport and Assimilation

According to the criteria of p-value < 0.05 and ∣log2FC∣ ≥ 1.0, the numbers of DEGs involved in potassium (K) transport were 10 (2 up-regulated and 8 down-regulated), 1 (1 up-regulated), 11 (2 up-regulated and 9 down-regulated) from SRvsCK, NvsCK and SRNvsCK, respectively, the DEGs involved in phosphorus (P) transport were 3 (1 up-regulated and 2 down-regulated), 3 (3 up-regulated), 2 (1 up-regulated and 1 down-regulated) from SRvsCK, NvsCK and SRNvsCK, respectively, and the DEGs involved in nitrogen (N) transport and assimilation were 3 (3 up-regulated), 7 (7 up-regulated), and 2 (2 up-regulated) from SRvsCK, NvsCK and SRNvsCK, respectively (Figure 3a–c). For these DEGs with ∣log2FC∣ ≥ 2.0, there were four DEGS involved in K transport, one involved in P transport, and seven involved in N transport and assimilation (Table 2). GRMZM2G477457 encoding HAK3 and GRMZM2G425999 encoding HAK4 were found to be significantly down-regulated, while GRMZM2G122584 encoding potassium/sodium hyperpolarization-activated cyclic nucleotide-gated channel 1 was significantly up-regulated in SR and SRN treatments when compared with the control. However, no changes were observed in the N treatment. GRMZM2G154090 encoding Pht2 was the sole gene that was significantly up-regulated under SR, N, and SRN treatments when compared with the control. Among seven DEGs involved in N transport and assimilation, two were involved in N transport, three were involved in N reduction, and the remaining two were involved in nitrite reduction. GRMZM2G455124 encoding NRT2.3 and NR encoding nitrate reductase were significantly up-regulated in SR, N, and SRN treatments when compared with the control. Additionally, another four genes are also found to be up-regulated in N treatment but not in SR and SRN treatments.

2.7. DEGs Involved in Sugar Metabolism, Fatty Acid Metabolism and Amino Acids Biosynthesis

Based on the threshold of p-value < 0.05 and ∣log2FC∣ ≥ 1.0, we found many DEGs related to sugar metabolism, fatty acid metabolism, and biosynthesis of amino acids. The numbers of DEGs involved in sugar metabolism were 19 (5 up-regulated and 14 down-regulated), 17 (11 up-regulated and 6 down-regulated), and 28 (11 up-regulated and 17 down-regulated) from SRvsCK, NvsCK, and SRNvsCK, respectively, DEGs involved in fatty acid metabolism were 7 (2 up-regulated and 5 down-regulated), 4 (2 up-regulated and 2 down-regulated), and 13 (3 up-regulated 10 down-regulated) from SRvsCK, NvsCK, and SRNvsCK, respectively, and those involved in the biosynthesis of amino acids were 13 (7 up-regulated and 6 down-regulated), 21 (18 up-regulated and 3 down-regulated), and 23 (18 up-regulated and 5 down-regulated), from SRvsCK, NvsCK and SRNvsCK, respectively (Figure 4a–c). Among the DEGs above, 25 met the threshold of ∣log2FC∣ ≥ 2.0. Fourteen of the 25 DEGs were related to sugar metabolism, three were related to fatty acid metabolism, and eight were related to the biosynthesis of amino acids (Table 3). The fourteen DEGs relevant to sugar metabolism were involved in four groups: starch metabolism, cellulose metabolism, trehalose metabolism, and sugar transport. Compared to the control, AGPL2 encoding glucose-1-phosphate adenylyltransferase large subunit 2 was significantly up-regulated in response to three fertilizer treatments. Contrary to AGPL2, GRMZM2G008263 encoding granule-bound starch synthase II, a precursor, GRMZM2G086845 encoding fructokinase 1, and GRMZM6G738249 encoding trehalose-phosphate phosphatase J were significantly down-regulated in SR and SRN treatments, but their expression level did not change in N treatment. Compared to the control, GRMZM2G157675 encoding SWEET was the sole gene that was significantly down-regulated in N treatment. Except for GRMZM2G157675, two genes encoding beta-glucosidase 1 (GRMZM2G016890 and GBA1), GRMZM2G066162 encoding endoglucanase 12-like and GRMZM2G063824 encoding carbohydrate transporter/sugar porter were significantly up-regulated in N treatment, but their expression level kept the same as in SR and SRN treatments. There were three DEGs (GRMZM2G178014, GRMZM2G022558, and GRMZM2G160417) involved in fatty acid metabolism. GRMZM2G160417 has not been characterized so far. The other two genes were regulated oppositely in SR and SRN treatments: GRMZM2G178014 encoding alpha/beta-Hydrolases superfamily protein was up-regulated while GRMZM2G022558 encoding fatty acid elongase 1 was down-regulated. The expression trends of GRMZM2G178014 and GRMZM2G022558 were not observed in N treatment. Among the eight DEGs involved in amino acid biosynthesis, GRMZM2G028535, GRMZM2G061777, and Rpi2 were significantly up-regulated in all the fertilizer treatments. Except for down-regulated GRMZM2G153536, the other three genes (GRMZM2G053669, GRMZM2G078472, and GRMZM2G013430) detected in N treatment were significantly up-regulated, but their expression level did not change in SR and SRN treatments. On the contrary, GRMZM2G124963 encoding alanine aminotransferase 10 exhibited significant up-regulation in SR and SRN treatments but no difference in N treatment.

3. Discussion

Straw return to soil has been a common agricultural practice in China [13]. In the present study, maize plants growing in unfertilized plots exhibited significantly reduced chlorophyll, soluble sugar, and soluble protein contents and lowered antioxidant enzyme activities but highly enhanced MDA content. It indicated that these plants were subjected to severe osmotic and oxidative stresses due to nutrient deficiency. However, this adverse growth status is largely alleviated by the addition of SR, N fertilizer, and SRN, of which SRN had the best effect. Maize plants under SRN treatment exhibited higher antioxidant activities and higher contents of chlorophylls and osmotic materials but lower MDA contents, and thus, the photosynthetic capacity and yields were improved. This further explains the reason why SRN is a common practice to improve soil fertility and crop yield in North China Plain. Additionally, this result agrees with our GO and KEGG analyses that are rich in “response to abiotic stimulus”, “starch and sucrose metabolism”, “nitrogen metabolism”, and so on. Su et al. [7] reported that rotten crop straw could provide various nutrients except for nitrogen for crops. It is conceivable that SR or SRN would induce the differential expression of more genes than sole N application. Our transcriptome analysis verified that the number of DEGs from the NvsCK comparison is much less than those from SRvsCK or SRNvsCK comparison group.
N, P, and K are essential nutrients for plant growth and crop yield. Their utilization efficiency in crops is largely dependent on their capacities of absorption and translocation in crops [14]. Here, only four genes related to K transport were found to be highly regulated by different fertilizer treatments, and three of them were significantly down-regulated. This is consistent with the previous study reported by Shen et al. [15], in which the transcript levels of most K transporters and channels were reduced to be responsive to low K treatment. In maize, there are 27 genes encoding high-affinity K transporter (HAK) [16]. Here, we found that HAK3 and HAK4 were significantly down-regulated in SR and SRN treatments but not in N treatment. GRMZM2G122584 encoding potassium/sodium hyperpolarization-activated cyclic nucleotide-gated channel 1 was the sole gene that was found to be highly up-regulated in SR and SRN treatments but not in N treatment. This suggests that the supplement of straw returning induces more gene expression than sole N treatment. Further study is needed to clarify their roles in K homeostasis in response to low K stress.
H2PO4−, a major phosphate (Pi) source, is taken up via Pi transporters in the plasma membrane of root cells. So far, five Pi transporter families have been identified [17]. Here, Pht2 encoding a Pht2 protein was found to be significantly up-regulated in all treatments, but the magnitude in SR and SRN treatments was much lower than that in the N treatment. This suggests that Pht2 might play crucial roles in the Pi uptake and translocation, while the function was repressed to some extent by the supplement of SR.
Low N utilization efficiency (NUE) has become a major constraint in crop production worldwide [18]. NUE is largely determined by nitrate uptake and nitrate reduction [19]. The former is mediated by nitrate transporters (NRT), and the latter, nitrate, is firstly degraded into nitrite and then to ammonium, catalyzed by nitrate (NR) and nitrite reductase (NIR), respectively. There are two types of nitrate transporters: one is low-affinity NRT1s, and the other is high-affinity NRT2s [18]. In sorghum, the low-N tolerant genotype showed higher transcript levels of NRT2s than the low-N sensitive genotype [20]. Here, eight genes, including three genes encoding nitrate transporters, three genes encoding nitrate reductase enzymes, and two genes encoding nitrite reductase enzymes, were significantly up-regulated in response to various fertilizer treatments. Consistent with the previous results [20], GRMZM2G455124 and GRMZM5G878558 showed significant up-regulation expression levels in all treatments, indicating that they played important roles in nitrate uptake and assimilation to deal with nutrient deficiency stresses. In the present study, the number and magnitude of DEGs in NvsCK comparison were much higher than those in SRvsCK and SRNvsCK comparisons, indicating that the addition of straw inhibited the expression levels of some N-related genes. In addition, the down-regulation of DEG genes related to K transporters and the up-regulation of DEG genes related to N transporters and P transporters responsive to nutrient shortage confirmed the important role of N and P in promoting the synthesis of key cellular molecules such as nucleic acid, protein, and ATP and maintaining the basic life activities of cells [21,22].
At the maize grain-filling stage, the ear-leaf plays a major role in providing photosynthetic assimilates for grain yield. It is conceivable that the transcriptional levels of a large number of sugar metabolism-related genes varied in response to various fertilizer treatments. Our transcriptome data showed that a total of 46 DEGs were significantly regulated, which is in agreement with vigorous photosynthesis in leaves. The lower ratio of up- or down-regulated DEGs in SR and SRN treatments when compared to N treatment suggested that the addition of straw into the field inhibited the expression levels of some sugar metabolism-related genes.
Starch is the main storage carbohydrate in higher plants. ADPG pyrophosphorylase (AGP) is the rate-limiting enzyme that catalyzes the generation of precursor molecules for starch biosynthesis-ADPG [23]. Here, AGPL2 encoding AGP large subunits were found to be significantly up-regulated in all treatments, indicating that it played a positive role in the conversion of photosynthetic products into starch upon different fertilizer treatments. However, another gene (GRMZM2G008263) involved in starch biosynthesis was significantly down-regulated in SR and SRN treatments but not detected in N treatment, suggesting that the addition of straw inhibited its expression. Many starch-degrading enzymes, including starch phosphorylase, α- and β-amylases, are engaged in starch breakdown. Here, we found that GRMZM2G025833 encoding β-amylase was significantly down-regulated in SRN treatment but not detected in N and SR treatments, suggesting that SRN treatment was beneficial to starch accumulation in maize leaves. This explains the reason in part why maize plants under SRN treatment exhibited higher kernel yields.
As the main component of plant cell walls, cellulose is one of the most widely distributed and abundant polysaccharides in nature. Dong et al. [24] reported that late sowing increased the lodging resistance of wheat plants by up-regulating the contents of lignin and cellulose, which is intriguing. Here, three genes (GRMZM2G016890, GBA1, and GRMZM2G066162) involved in cellulose metabolism were found to be significantly up-regulated in N treatment but not detected in SR and SRN treatments. Also, other genes, such as GRMZM2G086845, GRMZM6G738249, etc., were significantly down-regulated in SR and SRN treatments but not detected in N treatment. Trehalose is a kind of non-reducing disaccharide that functions as a stress protectant in many organisms, such as primitive plants. Trehalose synthesis is catalyzed by TPS and TPP via Tre6P [25]. Here, GRMZM6G738249 encoding trehalose-phosphate phosphatase J and GRMZM2G140078 encoding trehalose-6-phosphate phosphatase two were found to be significantly down-regulated in SR and SRN treatments, but no differential expression was detected in N treatment, indicating that trehalose biosynthesis is highly regulated by the addition of straw and (or) N fertilizer thus to cope with stresses caused by nutrient limitation. Sugar transport from leaves to sink tissues is crucial for yield formation. SWEET (Sugar Will Eventually be Exported Transporter) has been considered to be involved in the apoplastic loading of sugar [26]. Yang et al. [27] reported that CoSWEET12 from Camellia oleifera was involved in the regulation of sugar transport. In this work, two sugar transporter genes (GRMZM2G157675 and GRMZM2G063824) showed quite opposite expression patterns in N treatment, but their expression level did not change in SR and SRN treatment. It indicated that sugar transport in maize leaf was highly regulated and responsive to different fertilizer treatments at the maize grain-filling stage.
Fatty acids (FA) participate in the construction of cell membrane systems, stress resistance, nutritional quality improvement, and so on. Here, we found that the relevant DEG number in the N treatment was quite less than those in SR and SRN treatments. This is in agreement with the result of a previous study, which showed that some nutrients other than N promote FA biosynthesis and accumulation [28]. In FA biosynthesis, FA elongase (FAE) catalyzed the germination of long-chain fatty acids. Shi et al. [29] reported that FAE1 mutation led to changes in the composition of fatty acid in Brassica napus. Here, GRMZM2G022558, involved in the production of long-chain FA, exhibited significantly down-regulated expression levels in SR and SRN treatments, but no differential expression was observed in N treatment. Fang et al. [30] reported that GRMZM2G022558 participated in the biosynthesis of long-chain fatty acid by regulating the ratio of C18:0/C20:0 in a direct way. Conversely, GRMZM2G178014 related to the elongation of FA carbon chain were significantly up-regulated in SR and SRN treatments.
In plants, amino acids are important nitrogen storage compounds [31]. Our transcriptome analysis demonstrated that a total of 39 genes involved in the biosynthesis of amino acids expressed differentially, suggesting that amino acid biosynthesis was much more active at the maize grain-filling stage. The DEG number, especially the up-regulated DEGs, was quite less in SR treatment than in other treatments, indicating that straw nutrients were not sufficient for crop growing and N fertilizer application is necessary. Proline can serve as an osmoprotectant to cope with stresses caused by drought, salt, etc. [32]. In the present study, two genes (GRMZM2G028535 and GRMZM2G061777) involved in proline biosynthesis were significantly up-regulated in fertilizer treatments, and meanwhile, the GO and KEGG analysis revealed that many regulated genes were related to plant defense response in all treatments. Asparagine plays a major role in nitrogen recycling and transport in many organs, such as developing seeds and vegetative and senescence organs [33]. Two genes (GRMZM2G053669 and GRMZM2G078472) involved in aspartate biosynthesis were found to be significantly up-regulated only in N treatment but not in the other two fertilizer treatments, suggesting that straw addition adversely affected these genes’ expression. Histidine has been considered to play a role in enhancing heavy metal tolerance in plants and bacteria [34,35]. Here, Rpi2 involved in histidine biosynthesis is significantly up-regulated in all treatments, indicating that it might have participated in plant defense to cope with nutrient deficiency.

4. Materials and Methods

4.1. Experiment Site, Crop Material and Design

The field experiment was carried out at a long-term fertilization experimental site located at Laiyang City, Shandong Province, China (36°10′ N, 120°31′ E). The experimental site was established in 2009 with the aim of evaluating the effect of long-term straw returning on soil quality and crop production. The initial nutrients of experimental soils included 5.0 g kg−1 organic matter, 0.6 g kg−1 total N, 16.3 mg kg−1 available P, and 72.0 mg kg−1 available K. The area has a temperate continental monsoon climate, with an annual average temperature of 11.2 °C and precipitation of 779 mm.
A maize cultivar, Luyu 16, and a wheat cultivar, Yanyou 361, were used as crop materials, and maize plants were further studied. The two crops grew in a winter wheat-summer maize rotation system. Winter wheat was directly seeded in October and harvested in June of the next year, and summer maize was directly seeded in June and harvested in October. Four fertilizer treatments were set, that is, CK (no fertilizer), SR (straws from wheat and maize), N (N fertilizer), and SRN (SR plus N fertilizer) (Table S4). In this experiment, the four treatments and three replicates were assigned in a randomized block design, each plot being 33 m2.

4.2. Measurement of Photosynthetic Parameters and Maize Yield

The investigated photosynthetic parameters included net photosynthetic rate, transpiration rate, total conductance to water, intercellular CO2 concentration, and total conductance to CO2, which were measured using a portable photosynthetic system (LI6400, Li-Cor Inc., Lincoln, NE, USA). Maize ear leaves grew in light, were consistent in appearance, and were selected for parameter determination. The work was done on sunny days from 9:00 to 11:30. Five plants of each treatment were measured, and the average value was taken. Maize yield was estimated according to two rows of 30 individuals of each plot, and the grain yield was standardized to 14% moisture.

4.3. Sampling and Assay of Physiological Indexes

At the maize grain filling stage, the upper parts of ear leaves were collected from three plants of each plot, immediately frozen in liquid nitrogen, and then stored at −80 °C. The samples were used for Illumina sequencing and assay of physiological indexes. Total chlorophyll and soluble sugar contents were measured as described by Yamashita et al. [36] and Wu et al. [37], respectively. Soluble protein content and malondialdehyde (MDA) content were determined with the Bradford assay and thiobarbituric acid method [38], respectively. Activity assays of peroxidase (POD) and catalase (CAT) were performed as described by Hui et al. [39].

4.4. RNA Extraction, cDNA Library Construction, Illumina Sequencing, Read Processing, Assembling and Gene Functional Annotation

RNA Extraction, cDNA library construction, and Illumina sequencing were conducted by WHbioacme Co., Ltd. (Wuhan, China). The procedures for RNA extraction, cDNA library construction, Illumina sequencing, read processing, assembling, and gene functional annotation were the same as described in Liu et al. [14].

4.5. Real-Time Quantitative RT-PCR

To validate the reliability of RNA-Seq results, 15 genes were randomly selected, and specific primer pairs were designed (Table S5). The RNA samples for qRT-PCR analysis were the same as used in the RNA-seq experiments. cDNA was synthesized from 1 μg of total RNA using the Primer Script RT Reagent Kit (Takara, Beijing, China). The total reaction volume for each qRT-PCR was 20 μL. The procedure was 95 °C for 12 min, 40 cycles of 95 °C for 5 s, and finally 60 °C for 32 s. The ZmActin1gene was used as a reference, and the relative expression level was calculated using the 2−ΔΔCt method [40].

4.6. Statistical Analysis

Unless indicated, all experiments were performed in three independent biological replicates. All data were analyzed by the Excel 2013 software and SPSS.18.0 software (SPSS Inc., Chicago, IL, USA). Statistically, the difference at p-value < 0.05 was considered as significant.

5. Conclusions

This study provided the transcriptome information of maize ear leaves under long-term SRN tilling mode. As summarized in Figure 5, maize reached its maximum grain yield under SRN, which was due to a series of genes involved in the transport and assimilation of N, P, and K, as well as the mechanisms of sugar, lipid, and biosynthesis of amino acid were regulated in SRN tilling mode and then reduced plants’ nutrient deficiency stresses and increased the photosynthesis of ear leaves at maize grain filling stage. The identification of these promising genes will deepen our global understanding of complex molecular mechanisms among organic waste, mineral nutrient utilization, and crop yield.

Supplementary Materials

The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/plants12223868/s1, Supplementary Table S1: Summary of the RNA-seq clean data; Supplementary Table S2: Summary of mapping results; Supplementary Table S3: KEGG enrichment pathways of the DEGs in three pairwise comparisons with p-value < 0.05; Supplementary Table S4: Fertilization rates in the experiment field per year (kg ha−1); Supplementary Table S5: Primers used for qRT-PCR validation; Supplementary Figure S1: Changes of photosynthetic parameters responsive to various fertilizer treatments; Supplementary Figure S2: Volcano plots of DEGs in SRvsCK, NvsCK and SRNvsCK comparisons; Supplementary Figure S3: GO bar plots of DEGs in SRvsCK, NvsCK and SRNvsCK comparisons. CC, cell component; BP, biological process; MF, molecular function.

Author Contributions

Conceptualization, J.L. (Jun Li) and S.L.; data curation, K.Z. and J.L. (Jintao Liu); formal analysis, J.L. (Jintao Liu); funding acquisition, J.L. (Jun Li) and S.L.; investigation, K.Z. and J.L. (Jintao Liu); methodology, K.Z. and J.L. (Jintao Liu); project administration, J.L. (Jun Li) and S.L.; software, K.Z.; supervision, S.L.; validation, K.Z.; visualization, K.Z. and J.L. (Jintao Liu); writing—original draft, J.L. (Jun Li); writing—review and editing, J.L. (Jun Li), J.L. (Jintao Liu), K.Z. and S.L. All authors have read and agreed to the published version of the manuscript.

Funding

This work was partially supported by grants from Qingdao Agricultural University (QNYYAL1901, XJG2017054) and the National Key Research and Development Program of China (2017YFD0301002).

Data Availability Statement

The datasets generated during and/or analyzed during the current study are available from the corresponding author upon reasonable request.

Conflicts of Interest

The authors declare no conflict of interest.

Abbreviations

N, nitrogen; P, phosphate; K, potassium; SR, straw return; MDA, malondialdehyde; CAT, catalase; POD, peroxidase; GO, Gene Ontology; KEGG, Kyoto Encyclopedia of Genes and Genomes; DEGs, differentially expressed genes; FC, fold change; FA, fatty acid.

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Plants 12 03868 g001
Figure 1. Metabolites and antioxidant enzyme activities analyses responsive to various fertilizer treatments. (a) soluble sugar content; (b) soluble protein content; (c) malondialdehyde content (MDA); (d) catalase (CAT); (e) peroxidase (POD). Data shown are means ± SE, n = 3. Different letters indicate statistically significant differences between treatments at p-value < 0.05.
Figure 1. Metabolites and antioxidant enzyme activities analyses responsive to various fertilizer treatments. (a) soluble sugar content; (b) soluble protein content; (c) malondialdehyde content (MDA); (d) catalase (CAT); (e) peroxidase (POD). Data shown are means ± SE, n = 3. Different letters indicate statistically significant differences between treatments at p-value < 0.05.
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Figure 2. Number of differentially expressed genes (DEGs) from SRvsCK, NvsCK, and SRNvsCK comparisons. (a) Distribution of up-regulated and down-regulated DEGs in each comparison; (b) Venn diagram analysis; and (c) validation of RNA-Seq results.
Figure 2. Number of differentially expressed genes (DEGs) from SRvsCK, NvsCK, and SRNvsCK comparisons. (a) Distribution of up-regulated and down-regulated DEGs in each comparison; (b) Venn diagram analysis; and (c) validation of RNA-Seq results.
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Figure 3. Number of up-regulated and down-regulated DEGs in potassium transport (a), phosphate transport (b), nitrogen transport, and assimilation (c) detected from SRvsCK, NvsCK, and SRNvsCK comparisons (|Log2FC| ≥ 1.0, p-value < 0.05).
Figure 3. Number of up-regulated and down-regulated DEGs in potassium transport (a), phosphate transport (b), nitrogen transport, and assimilation (c) detected from SRvsCK, NvsCK, and SRNvsCK comparisons (|Log2FC| ≥ 1.0, p-value < 0.05).
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Figure 4. Number of up-regulated and down-regulated DEGs in sugar metabolism (a), biosynthesis of an amino acid (b), and fatty acid metabolism (c) among SRvsCK, NvsCK, and SRNvsCK comparisons (|Log2FC| ≥ 1.0, p-value < 0.05).
Figure 4. Number of up-regulated and down-regulated DEGs in sugar metabolism (a), biosynthesis of an amino acid (b), and fatty acid metabolism (c) among SRvsCK, NvsCK, and SRNvsCK comparisons (|Log2FC| ≥ 1.0, p-value < 0.05).
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Figure 5. Schematic representation of the molecular mechanism of organic waste, mineral nutrient utilization, and crop yield under SRN tilling mode. Red or blue fonts refer to the up- or down-regulated DEGs in SRN treatment, respectively, over the N treatment. Solid or dashed arrows indicate the direct or indirect effects exerted by SRN treatment, respectively. SR, N, POD, CAT, MDA, SS, CC, NPr, and TR are the abbreviations of straw return, nitrogen, peroxidase, catalase, malondialdehyde, soluble sugar, chlorophyll content, net photosynthetic rate, transpiration rate, respectively.
Figure 5. Schematic representation of the molecular mechanism of organic waste, mineral nutrient utilization, and crop yield under SRN tilling mode. Red or blue fonts refer to the up- or down-regulated DEGs in SRN treatment, respectively, over the N treatment. Solid or dashed arrows indicate the direct or indirect effects exerted by SRN treatment, respectively. SR, N, POD, CAT, MDA, SS, CC, NPr, and TR are the abbreviations of straw return, nitrogen, peroxidase, catalase, malondialdehyde, soluble sugar, chlorophyll content, net photosynthetic rate, transpiration rate, respectively.
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Table 1. The years 2019 and 2020 grain yield of maize under long-term fertilizer treatments (kg ha−1). Data represent mean ± SE, n = 3. Different letters indicate statistically signifcant diferences between treatments at p-value < 0.05.
Table 1. The years 2019 and 2020 grain yield of maize under long-term fertilizer treatments (kg ha−1). Data represent mean ± SE, n = 3. Different letters indicate statistically signifcant diferences between treatments at p-value < 0.05.
YearCKSRNSRN
20193087 ± 24.5 d3991 ± 141.1 c5276 ± 50.7 b7926 ± 118.4 a
20203542 ± 65.6 d3942 ± 169.7 c5615 ± 67.9 b8180 ± 167.6 a
Table 2. Summary of the DEGs involved in the transport and assimilation of potassium, phosphate, and nitrogen in SRvsCK, NvsCK, and SRNvsCK comparisons (|Log2FC| ≥ 2.0, p-value < 0.05).
Table 2. Summary of the DEGs involved in the transport and assimilation of potassium, phosphate, and nitrogen in SRvsCK, NvsCK, and SRNvsCK comparisons (|Log2FC| ≥ 2.0, p-value < 0.05).
Gene NameGene ID|Log2FC| ≥ 2Annotation
SRvsCKNvsCKSRNvsCK
Potassium transport
GRMZM2G477457103635197−2.29 −2.23HAK3
GRMZM2G425999103653279−2.00 −2.36HAK4
GRMZM5G838773103636639−2.12 Potassium channel KAT3
GRMZM2G1225841036513602.36 2.82Potassium/sodium hyperpolarization-activated cyclic nucleotide-gated channel 1
Phosphate transport
GRMZM2G1540907327161.062.541.03Pht2
Nitrogen transport and assimilation
GRMZM2G4551241036362181.832.881.61High-affinity nitrate transporter 2.3
GRMZM2G161459103637664 2.05 NRT1/PTR family 6.3
NR1003832104.428.134.31Nitrate reductase
NR1542278 2.96 Nitrate reductase-like
NR31099399752.83 Nitrate reductase 3
NIR542264 2.7 Nitrite reductase 2
GRMZM2G102959103627781 3.89 Ferredoxin—nitrite reductase
Table 3. Summary of the DEGs involved in sugar, amino acid, and fatty acid metabolism in SRvsCK, NvsCK, and SRNvsCK comparisons (|Log2FC| ≥ 2.0, p-value < 0.05).
Table 3. Summary of the DEGs involved in sugar, amino acid, and fatty acid metabolism in SRvsCK, NvsCK, and SRNvsCK comparisons (|Log2FC| ≥ 2.0, p-value < 0.05).
Gene NameGene ID|Log2FC| ≥ 2Annotation
SRvsCKNvsCKSRNvsCK
Sugar metabolism
AGPL21036351822.932.42.74Glucose-1-phosphate adenylyltransferase large subunit 2
GRMZM2G008263100125638−2.08 −1.47Granule-bound starch synthase II, a precursor
GRMZM2G025833100281141 −3.13Beta-amylase
GRMZM2G086845542107−1.68 −2.29Fructokinase 1
GRMZM2G008247732807 −2.58Beta-D-glucosidase precursor
GRMZM2G016890542414 2.68 Beta glucosidase 1
GBA1103634742 2.85 Beta-glucosidase 1
GRMZM2G076946100174972 −4.84Dhurrinase-like B-glucosidase
GRMZM2G120962103650330 −2.514-hydroxy-7-methoxy-3-oxo-3,4-dihydro-2H-1,4-benzoxazin-2-yl glucoside beta-D-glucosidase 1
GRMZM2G066162103641803 3.41 Endoglucanase 12-like
GRMZM6G738249100273093−1.43 −2.53Trehalose-phosphate phosphatase J
GRMZM2G140078107546758 −2Trehalose-6-phosphate phosphatase 2
GRMZM2G157675100282631 −2.08 SWEET
GRMZM2G063824100285023 4.9 Carbohydrate transporter/sugar porter
Fatty acid metabolism
GRMZM2G1780141001914311.21 2.37Alpha/beta-Hydrolases superfamily protein
GRMZM2G022558542018−3.7 −4.54Fatty acid elongase 1
GRMZM2G160417100382638 −2.07Uncharacterized
Biosynthesis of amino acid
GRMZM2G0285351002807191.933.162.82Delta 1-pyrroline-5-carboxylate synthetase 1
GRMZM2G0617771036304301.891.52.08Delta-1-pyrroline-5-carboxylate synthase-like
GRMZM2G153536100281255 −2.57 Branched-chain-amino-acid aminotransferase
GRMZM2G1249631002791492.14 2.34alanine aminotransferase 10
GRMZM2G053669100192350 4.99 Asparagine synthetase 3
GRMZM2G078472100192351 5.52 Asparagine synthetase 4
Rpi21036262474.363.274.72Ribose-5-phosphate isomerase 2
GRMZM2G013430541959 2.22 Serine acetyltransferase 2
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Li, J.; Liu, J.; Zhu, K.; Liu, S. Transcriptome Analysis of Maize Ear Leaves Treated with Long-Term Straw Return plus Nitrogen Fertilizer under the Wheat–Maize Rotation System. Plants 2023, 12, 3868. https://doi.org/10.3390/plants12223868

AMA Style

Li J, Liu J, Zhu K, Liu S. Transcriptome Analysis of Maize Ear Leaves Treated with Long-Term Straw Return plus Nitrogen Fertilizer under the Wheat–Maize Rotation System. Plants. 2023; 12(22):3868. https://doi.org/10.3390/plants12223868

Chicago/Turabian Style

Li, Jun, Jintao Liu, Kaili Zhu, and Shutang Liu. 2023. "Transcriptome Analysis of Maize Ear Leaves Treated with Long-Term Straw Return plus Nitrogen Fertilizer under the Wheat–Maize Rotation System" Plants 12, no. 22: 3868. https://doi.org/10.3390/plants12223868

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