Characterization of graphene
The ultraviolet-visible absorption spectrogram (Fig. 1A) shows a strong absorption peak at 270 nm, which is a typical peak of graphene. Raman spectroscopy is a nondestructive and sensitive method of analysis of graphene and grapheme derivatives [34, 35]. Raman spectroscopy (Fig. 1B) shows that G peak appears near 1576 cm− 1, which is generated by the stretching and far-moving of sp2 hybridized atoms in carbon rings or long chains, representing the ordered sp2 bond structure. Peak D appeared near 1348 cm− 1, which was related to sp3 hybrid structure, representing defects and amorphous structure at the edge of graphene. A wide 2D peak appeared near 2707 cm− 1, indicating that the number of graphene layers prepared was within 10 layers. High-resolution scanning electron microscopy (Fig. 1C) and transmission electron microscopy (Fig. 1D) showed that the graphene presented a transparent sheet structure with slightly wrinkled and undulate surface. The number of graphene layers prepared was 3–5 layers as observed under transmission electron microscopy.
Exogenous Graphene Promoted The Growth And Development Of Maize
Six concentration gradients (0, 20, 25, 33, 50 and 100 mg/L) of graphene were used to treat maize seedling roots and irrigated through the roots. At the seedling stage, the phenotypes of maize plants were observed (Fig. 2). As shown in the Fig. 2, the graphene concentration of 50.00 mg/L could promote the growth of maize plants. Subsequently, we measured multiple physiological indexes to analyze the effect of graphene on the growth or development of maize plants.
Exogenous graphene enhancedZea maysroot development
Root architecture of maize seedlings under six concentration gradients of graphene (0, 20, 25, 33, 50 and 100 mg/L) was investigated. The root growth and development of maize seedlings under graphene treatments were promoted, especially for the 50 mg/L graphene concentration (Fig. 3A). Root architecture, including total root length, total project area, total surface area, root volume, the number of root tips and root forks were measured (Fig. 3B-G). Compared to the control group, 25, 50 and 100 mg/L graphene increased the total root length (Fig. 3B), root volume (Fig. 3E), the number of root tips (Fig. 3F) and root forks (Fig. 3G) of maize seedlings. Total project area (Fig. 3C) and total surface area (Fig. 3D) were not affected by any of graphene treatment. 33 mg/L graphene promoted the number of root tips (Fig. 3F), but inhibited the development of total length (Fig. 3B). Among them, The maize seedlings treated with 50 mg/L graphene displayed significant higher values than CK (Fig. 3). Based on the above assay results, the 50 mg/L graphene concentration was used for the subsequent experiments and analyses.
Transcriptome Sequencing
To gain insights into how graphene might induce a promoting effect leading to enhanced root development, a comparative transcriptome analysis was performed. We collected root tissue samples from maize seedlings treated with 50 mg/L graphene (X100) and used untreated seedlings as the corresponding controls (CK). All samples were used for transcriptome sequencing with three biological replicates (Additional file 1: Table S1). In total, 170.02 million raw reads were obtained for the CK libraries (CK-1, CK-2 and CK-3), and 166.69 million raw reads were obtained for the X100 libraries (X100-1, X100-2 and X100-3). After removing adapter and low-quality sequences along with contaminated reads, 24.15 Gb and 23.92 Gb high-quality clean bases remained from the CK and X100 libraries, respectively (Table S1). Using the Z. mays genome of B73 [36], the number of total clean reads was 43.67–60.13 million for the CK libraries (79.65–87.30% mapped rate, and 77.66–85.09% unique mapped rate) and 49.56–59.40 million for the X100 libraries (77.83–84.46% mapped rate, and 75.66–82.18% unique mapped rate) (Additional file 2: Table S2).
Genes that are differentially expressed in the root samples ofZea mays in response to graphene treatment
We firstly calculated the Pearson correlation coefficient (PCC) of all the genes, and generated a heatmap plot showing changes in gene expression (as shown in Fig. 4A). The correlation coefficients of the three biological replicates were greater than 0.90, indicating that the RNA-seq data were reliable for further analysis. Based on principal component analysis of six samples, the transcriptional response observed in Zea mays roots exposed to 50.00 mg/L graphene was due to the graphene treatment, and varieties with graphene treatment exhibited two levels of gene expression (as shown in Fig. 4B).
We were particularly interested in identifying transcripts that were differentially expressed in the root sample in response to graphene treatment, as such transcripts may represent genes related to root development under graphene treatment. The expression value of each gene was calculated using FPKM (Fragments Per Kilobase of transcript per Million fragments mapped) algorithm. A two-fold change and a p-value of less than 0.05 were set as the cutoffs to define genes with significant differential expression (Fig. 4C). We identified 962 differentially expressed genes, among which 792 were graphene-induced and 170 were graphene-repressed (Fig. 4D).
Gene Enrichment Analysis For Differentially Expressed Genes
To investigate possible biological functions that determine the different responses of the maize plants to 50.00 mg/L graphene treatment, we used GOseq [37] to perform GO category enrichment analysis for differentially expressed genes. Figure 5 lists the results of the gene ontology (GO) analysis for differentially expressed genes after graphene treatment. GO terms associated with important biological processes, such as the cellular, metabolic, developmental, and immune system processes, biological regulation, response to stimulus and detoxification were enriched in maize exposed to graphene treatment. GO terms associated with important cellular component, such as cell, membrane and organelle parts were enriched. GO terms associated with important molecular function, such as catalytic activity, transporter activity, nucleic acid binding transcription factor activity, antioxidant activity and transcription factor activity were enriched.
DEGs were subjected to COG database [38] to classify the gene function and homology. Additional file 3: Figure S1 lists the results of the COG analysis for differentially expressed genes. Most DEGs were distributed on the orthologous groups of 1) secondary metabolites biosynthesis, transport and catabolism, 2) carbohydrate transport and metabolism, 3) amino acid transport and metabolism, 4) lipid transport and metabolism and 5) defense mechanisms.
DEGs were subjected to KEGG pathway analysis to identify the functional categorization. Additional file 4: Figure S2 lists the results of the KEGG analysis for differentially expressed genes. Most DEGs were categorized on the functional pathways of 1) metabolisms, including phenylpropanoid biosynthesis, glutathione metabolism, flavonoid biosynthesis, carbon metabolism, amino sugar and nucleotide sugar metabolism, cysteine and methionine metabolism, terpenoid backbone biosynthesis, biosynthesis of amino acids, as well as starch and sucrose metabolism etc; 2) cellular process of peroxisome; 3) environmental information processing, including plant hormone signal transduction, ABC transporters, phosphatidylinositol signaling system, circadian rhythm in plant and plant-pathogen interaction. DEGs with up-regulation were assigned to 73 KEGG pathways, including phenylpropanoid biosynthesis, glutathione metabolism, flavonoid biosynthesis, and nitrogen metabolism (Fig. 6A). DEGs with down-regulation were significantly enriched in 14 KEGG pathways, including amino sugar and nucleotide sugar metabolism, starch and sucrose metabolism pathways as well as plant hormone signal transduction (Fig. 6B) etc,. The results revealed that graphene could affect the expression of maize root genes, showing majority of up-regulation genes. The enrichment analysis illustrated that graphene treatment had extensive and distinct effects on the life processes in maize.
Transcription Factors Enriched In Maize Plants Exposed To Graphene
We found that the GO term “transcription factor activity, protein binding” was significantly enriched in maize roots subjected to graphene treatment (Fig. 5). Transcription factors are DNA-binding proteins that play a key role in gene transcription and expression that mediated many processes. Many transcription factors in the roots of maize responded to the graphene treatment, and the responses differed by up or down regulated expressions (Table 1). 44 maize transcription factor genes classified into 7 different families according to PlantTFDB [39], were differentially expressed under the graphene treatment, including ERF, WRKY, bHLH, MYB and MYB-like, NAC, AP2 as well as MADS-box. Among them, 32 transcription factor genes were up-regulated and 12 were down-regulated. The transcription factor genes activated in Z. mays roots in response to the graphene treatment mostly belonged to the MYB and MYB-like, WRKY, NAC and bHLH families, suggesting that these transcription factor genes might response to the graphene specifically in Z. mays root.
Many studies have proved that plant root development could be regulated by ERF [40], WRKY [41, 42], bHLH [43–45], MYB and MYB-like [46–49], NAC [50, 51], AP2 [52, 53] as well as MADS-box [54, 55] TF genes. After exposure to graphene treatment of Z. mays roots, there were three up and one down-regulated ethylene-responsive (ERF) transcription factor genes (Fig. 7A), eight up and one down-regulated WRKY TF genes (Fig. 7B), five up and one down-regulated bHLH TF genes (Fig. 7C), ten up and two down-regulated MYB and MYB-like TF genes (Fig. 7D), three up and four down-regulated NAC TF genes (Fig. 7E), three up and one down-regulated AP2 TF genes (Fig. 7F) as well as two down-regulated MADS-box TF genes (Fig. 7G). As proved above, the total root length, root volume, the number of root tips and root forks (Fig. 3) of maize seedlings were increased after 50 mg/L graphene treatment. These improved root phenotypes might be affected by these differentially expressed transcription factor genes. Therefore, these TFs were considered the candidate graphene-responsive genes, and might be the internal causes in promoting the development of roots in Z. mays.
Plant Hormone Signaling Pathways
Plant hormones, including auxin, cytokinin (CK), gibberellin (GA), abscisic acid (ABA), ethylene, brassinosteroid (BR), jasmonate (JA), salicylic acid (SA), and strigolactone (SL) play critical roles in the plant’s processes of growth, development and adapting to the external changing environments [56–59]. We identified differentially expressed genes related to nine hormone signal transduction pathways. An overview of gene expression patterns under graphene treatment in maize roots is shown in Fig. 8. Four auxin-responsive genes, such as gene-LOC100281448 (IAA9), gene-LOC103642166 (auxin response factor 11) and gene-PIN5c (auxin efflux carrier PIN5c) were differentially expressed in maize under graphene conditions, indicating the existence of crosstalk between graphene and auxin signaling. Therefore, auxin modulates the plant’s response to graphene by altering the expression of genes involved in root growth regulation.
The cytokinin (CK) signaling pathway plays an important role in the plant’s growth regulation. Four genes associated with the cytokinin signaling pathway showed significantly differentially expression under graphene treatment (Fig. 8). The expression of gene-cko1 (cytokinin oxidase1), gene-LOC100280143 (cytokinin-N-glucosyltransferase 1) and gene-LOC100282611 (cytokinin-O-glucosyltransferase 2) was increased. We found that five genes associated with the GA pathway were also up-regulated expressed, including gene-LOC100283080 (Gibberellin 20 oxidase 2), gene-LOC100283652 (gibberellin receptor GID1L2) and gene-gar1 (gibberellin responsive 1). JA and SA play important roles in plant defense response. The expression of six JA-related genes, such as gene-LOC100283794 (Jasmonate-induced protein), gene-LOC103629478 (jasmonate O-methyltransferase) and gene-LOC100273620 (Jasmonate-regulated gene 21), and one SA-related gene (salicylic acid-binding protein 2) were up-regulated in the roots of maize subjected to graphene. Two gene involved in brassinosteroid (BR) and strigolactone (SL) signal transduction respectively were induced in response to graphene, suggesting the roles of graphene-responsive hormones are emerging to function. Together, these results demonstrated that hormones might form a complex regulatory network related to the graphene response in roots.
Nitrogen And Potassium Metabolism
We also identified eight nitrogen and potassium metabolism genes that were differentially expressed (Fig. 9). All the five nitrogen metabolism genes were up-regulated (Fig. 9A) and three of them (gene-GLN6, gene-nrt2 and gene-nrt2.2) were validated by qRT-PCR analysis (Fig. 9B). These genes were annotated into the glutamine synthetase root isozyme 1 and nitrate transporter, which were involved in the nitrogen transmembrane transport and root development. In view of this, we measured the N content in the soil around the maize seedling roots, and the N content in 50.00 mg/L graphene was significantly increased, up to 1.64 times (Fig. 9C).
In addition, the expressions of three potassium metabolism genes (gene-HAK20, gene-HAK21 and gene-kup1) were up-regulated by RNA-seq (Fig. 9D) and qRT-PCR data (Fig. 9E). These genes were involved in the potassium ion transmembrane transport and uptake. We also measured the K content in the soil around the maize seedling roots, and the K content in 50.00 mg/L graphene was increased by 1.33 times (Fig. 9F). The results indicated that the soil fertility, such as the content of N and K, could be elevated after irrigating the graphene, which further promote the growth and development of maize seedling roots.
Qrt-pcr Identification Of Degs In Response To Graphene
Furthermore, to validate the RNA-seq results, 20 DEGs were screened for qRT-PCR validation, including 14 transcription factor genes, three nitrogen metabolism and three potassium metabolism genes. We analyzed the expression of these genes using quantitative real-time PCR (qRT-PCR) analysis and compared the results with the RNA-seq data (Table 2). These transcripts had similar expression patterns in the qRT-PCR and RNA-seq experiments and the correlation coefficient between the two sets of data was 0.7783 (Table 2).