Integrated mRNA and small RNA sequencing reveals microRNA regulatory network associated with internode elongation in sugarcane (Saccharum officinarum L.)
Internode elongation is one of the most important traits in sugarcane because of its relation to crop productivity. Understanding the microRNA (miRNA) and mRNA expression profiles related to sugarcane internode elongation would help develop molecular improvement strategies but they are not yet well-investigated. To identify genes and miRNAs involved in internode elongation, the cDNA and small RNA libraries from the pre-elongation stage (EI), early elongation stage (EII) and rapid elongation stage (EIII) were sequenced and their expression were studied.
Based on the sequencing results, 499,495,518 reads and 80,745 unigenes were identified from stem internodes of sugarcane. The comparisons of EI vs. EII, EI vs. EIII, and EII vs. EIII identified 493, 5035 and 3041 differentially expressed genes, respectively. Further analysis revealed that the differentially expressed genes were enriched in the GO terms oxidoreductase activity and tetrapyrrole binding. KEGG pathway annotation showed significant enrichment in “zeatin biosynthesis”, “nitrogen metabolism” and “plant hormone signal transduction”, which might be participating in internode elongation. miRNA identification showed 241 known miRNAs and 245 novel candidate miRNAs. By pairwise comparison, 11, 42 and 26 differentially expressed miRNAs were identified from EI and EII, EI and EIII, and EII and EIII comparisons, respectively. The target prediction revealed that the genes involved in “zeatin biosynthesis”, “nitrogen metabolism” and “plant hormone signal transduction” pathways are targets of the miRNAs. We found that the known miRNAs miR2592-y, miR1520-x, miR390-x, miR5658-x, miR6169-x and miR8154-x were likely regulators of genes with internode elongation in sugarcane.
The results of this study provided a global view of mRNA and miRNA regulation during sugarcane internode elongation. A genetic network of miRNA-mRNA was identified with miRNA-mediated gene expression as a mechanism in sugarcane internode elongation. Such evidence will be valuable for further investigations of the molecular regulatory mechanisms underpinning sugarcane growth and development.
KeywordsTranscriptome Next-generation sequencing Zeatin biosynthesis Nitrogen metabolism Plant hormone signal transduction
Cytokinin dehydrogenase 5 precursor
Cytokinin hydroxylase-like isoform X1
Early elongation stage
Rapid elongation stage
False discovery rate
Ferredoxin-dependent glutamate synthase
Lateral suppressor-like protein
Kyoto encyclopedia of genes and genomegenomes
Eukaryotic orthologous group
RNA sequencing or the transcriptome sequencing
Reads Per kb per Million reads
Ribosomal ribonucleic acid
Small nucleolar RNA
Small nuclear ribonucleic acid
Transcripts per million
Internode elongation is a major feature that affects plant growth, errectness, biomass and ultimately yield . Thus, the genetics and the regulatory mechanisms of internode elongation in crop plants have been extensively investigated. Genetic and environmental factors such as gene expression [2, 3, 4], genomic variation [5, 6], hormonal regulation [7, 8], nutrients [9, 10], light , water  and temperature  control internode elongation. Of these regulatory factors, hormonal manipulation is an effective and efficient approach to promote crop growth to promote productivity [14, 15, 16].
Complex hormonal mechanisms are associated with internode elongation. For example, auxin , gibberellin  and brassinosteroids  induce internode elongation. In contrast, abscisic acid , ethylene  and jasmonic acid  suppress internode elongation in plants. Further, different species and growing condition add additional complexity to growth and developmental regulation. Understanding sugarcane crop-specific mechanisms of hormonal regulation stem growth would help improve crop productivity. Alternatively, endogenous hormones can be manipulated by genome editing [22, 23] and RNA interference technologies [24, 25]. microRNAs (miRNAs), being an effective RNA interference mechanisms, show the prospect of regulating hormone production and action [26, 27, 28]. TIR1 and AFB, part of auxin signaling, are targets of miR393, and the suppressive effects of miR393 on auxin are indicated in Arabidopsis . GAMYB, a gene in gibberellin signal pathway, is regulated by miR159 . Also, hormones regulate miRNA expression in plants. For instance, with deep sequencing of abscisic acid-treated tomato (Solanum lycopersicum), 269 differentially expressed miRNAs were identified .
Development of sequencing technology has facilitated transcriptome studies that provide unprecedented detail about the molecular biological processes in plants [32, 33]. Transcriptome sequencing approaches promise increased understanding of the expression patterns and molecular regulatory mechanisms in gene expression . By transcriptome sequencing, the genes associated with culm elongation in bamboo (Dendrocalamus sinicus) were identified . In another study, transcriptome sequencing showed the changes in gene expression via induction of ethephon in maize (Zea mays) plants . These studies provide basic information about the functional genes involved in internode elongation. In cotton (Gossypium hirsutum), 64 differentially expressed miRNAs were identified during the fiber elongation process . The miRNA profiles during tissue differentiation and growth revealed by small RNA sequencing may provide new insight for epigenetic regulation, which might determine a starting point toward important questions regarding plant growth.
Sugarcane (Saccharum officinarum L.) is an economically important crop that is widely planted in tropical and subtropical regions . Sugarcane is used for producing ethanol and raw sugar; thus, this valuable crop is grown around the world . Understanding the genetic control of sugarcane growth, particularly the biological process of internode elongation, would accelerate the industrial development of sugarcane cultivation. Investigation of miRNA-mRNA networks in sugarcane could reinforce further crop gains. Although several studies demonstrate changes in gene expression or miRNAs during internode elongation [40, 41], the present study focused on the integrated analysis of miRNA and mRNA interactions, which should produce an image of the mRNA-miRNA networks that occur between transcriptional and posttranscriptional regulation in this biological process.
To better understand the molecular changes and regulation of gene expression by miRNA, we sequenced mRNA and small RNA libraries from internode tissues at different stages including the pre-elongation stage, early elongation stage and rapid elongation stage. The libraries from these tissues were sequenced by an Illumina Hiseq 4000 platform. By comparing the differential expression, the candidate genes and miRNAs involved in internode elongation were identified. Furthermore, the mRNA and miRNA interaction network was built by target prediction using a bioinformatic approach. These integrated mRNA and small RNA sequencing results provide pioneering evidence for a view of candidate internode elongation-associated miRNAs in sugarcane and may be useful for development of potential functional markers to develop molecular breeding.
mRNA expression profiles in different stages from internodes
Summary of the RNA-Seq Data
Before Filter Read Number
After Filter Read Number
Differentially expressed genes in different stages of internode development
Summary of Transcriptome Assembly Statistics
Max. length (bp)
Min. length (bp)
Average length (bp)
Total assembled bases (bp)
Functional annotation of the differentially expressed genes
From the KEGG enrichment results, it was found that 16 KEGG pathways were enriched. From the EI vs. EII comparison, 9 enriched pathways were identified, including “zeatin biosynthesis” and “nitrogen metabolism”, which involved tissue growth. The EI vs. EIII comparison contained 11 enriched pathways, including “plant hormone signal transduction” and “nitrogen metabolism” associated with growth. For EII vs. EIII, 7 enriched pathways were found, including “nitrogen metabolism” (Fig. 3b, Additional file 3).
Sequencing of small RNAs in internodes
Summary of Small RNA Data and miRNA Annotation
Known miRNA number
Novel miRNA number
Identification of known and novel miRNAs
The known miRNAs were conducted by blastn to hit the miRBase. A total of 241 known miRNAs were detected in the internode tissues from sugarcane. From all the sequenced libraries, 118 known miRNAs were overlapped in all the groups. miR168-x, miR319-y, miR168-y, miR396-x and miR166-y were the most abundant known miRNAs. The novel miRNAs were predicted by the mireap v0.2 package. A total of 245 novel candidate miRNAs were found in the internodes from sugarcane (Table 3, Additional file 4). Novel-miR0183-5p, novel-miR0209-5p and novel-miR0183-3p were the most abundant novel miRNAs.
Differentially expressed miRNAs and their targets
Targets of the differentially expressed miRNAs were detected. For 8 of the total differentially expressed miRNAs in the EI and EII comparison, the target unigenes were identified (78 in total), whereas no targets were identified for the other 3 miRNAs. In the EI and EIII comparison, 204 targets for 31 miRNAs were identified (Additional file 6).
Differentially expressed mRNA and miRNA pairs related to internode elongation
Stem is the primary valuable tissue for sugarcane, which grows within the internode elongation process. To understand the miRNA-mRNA network during this important process, an integrated mRNA and small RNA sequencing study was done using a next-generation sequencing approach for different internode elongation stages in sugarcane in the present study. This pioneer study provided a molecular basis underlying the elongated internodes in posttranscription regulation.
To investigate the gene profiles in a wide range during sugarcane internode elongation, next-generation sequencing technology was used to analyze the transcriptome changes in the stems from the pre-elongation stage, early elongation stage and rapid elongation stage. The de novo assembly generated 80,745 unigenes. The number of differentially expressed genes in the EI vs. EII, EI vs. EIII and EII vs. EIII comparisons were 493, 5035 and 3041, respectively. Compared with the differentially expressed genes, a significantly higher ratio of unigenes showed similar expression among all the groups, strongly suggesting that the differentially expressed genes were involved in sugarcane internode elongation.
The enriched GO terms identified from the differentially expressed genes were within our expectations. Oxidoreductase activity and tetrapyrrole binding were highly enriched in EI compared with those in the other two groups, indicating the function of these genes in sugarcane internode elongation. Contributing to oxidoreductase activity, flavonoid 3-monooxygenase was significantly higher in the EI pre-elongation stage than in the other groups. Flavonoid 3-monooxygenase is responsible for catalyzing flavonoid to 3′-hydroxyflavonoid. Flavonoids affect plant resistance , and flavonoid accumulation may inhibit lignin synthesis . Tetrapyrrole plays various roles in biological processes in plants, including plant growth . For the tetrapyrrole binding term, higher expression of ent-kaurenoic acid oxidase 1 was identified at EII and EIII than EI. This enzyme catalyzes the gibberellin biosynthesis pathway and regulates lignin synthesis .
To understand the key pathways in sugarcane internode elongation, the enriched KEGG pathways with differentially expressed genes were identified, and “zeatin biosynthesis”, “nitrogen metabolism” and “plant hormone signal transduction” pathways were enriched with differentially expressed genes. The differentially expressed genes in “zeatin biosynthesis” pathways included CKX3, CKX5, CKX9, CKX10 and CKO2 at EII and EIII compared with EI. It was noted that with the exception of CKX5 at EII, all the other CKX and CKO were significantly down-regulated at EII and EIII stages. CKX/CKO is responsible for degradation of cytokinin [46, 47]. Low expression of the genes in these pathways might be related to high growth activities at EII and EIII stages during internode elongation via cytokinin accumulation . Glutamate dehydrogenase and nitrate reductase were the two enzyme families in “nitrogen metabolism” pathways that might be involved in internode elongation. Transgenic studies in plants found that glutamate dehydrogenase is important for plant growth and productivity . Nitrate as a nutrient for plant growth is regulated by nitrate reductase, indicating changes in nutrient requirements during sugarcane internode elongation . The changing of “plant hormone signal transduction” during internode elongation was also expected. Auxin-related genes including auxin-responsive proteins were decreased at EII and EIII compared with those at EI. Auxin-responsive proteins affect auxin expression by acting on its promoter [51, 52], leading to regulation of sugar accumulation, ethylene biosynthesis and promoting cell elongation.
The observations that several differentially expressed genes were related to internode elongation in the present study indicated that the sugarcane internode elongation was induced by the changes in gene expression in key pathways, suggesting a complex network of the relationships between hormone secretion and internode elongation in sugarcane.
Previous studies demonstrated that plant miRNAs regulate gene expression at posttranscriptional levels related to plant development, including germination, root development, flowering and internode elongation. Here, small RNA sequencing was performed in the stems from the pre-elongation stage, early elongation stage and rapid elongation stage in the present study. A total of 241 known miRNAs and 245 novel candidate miRNAs were identified in these small RNA libraries. Most of these miRNAs were expressed widely among the three different stages. miR168-x, miR319-y, miR168-y, miR396-x and miR166-y were the most abundant known miRNAs, which were consistent with previous miRNA studies in sugarcane [53, 54, 55].
Subsequently, the miRNAs involved in control of the gene expression that was related to internode elongation was analyzed. As found in transcriptome analysis, several genes in “zeatin biosynthesis”, “nitrogen metabolism” and “plant hormone signal transduction” pathways participated in sugarcane internode elongation. A total of 43 miRNA-mRNA pairs were found included. Only 6 miRNAs were decreased while other 37 miRNAs increased in EII and EIII stages. Thus, the overall expression trend of miRNAs in these pathways were downregulated and their targeted mRNA were upregulated during elongation process. Among them, CKX5 precursor and CYP735A1 were targeted by two novel miRNAs. This evidence showed that numbers of the candidate miRNA-mRNA remained unidentified to date. Further studies are required to demonstrate the substantive regulatory roles of the novel miRNAs. miR2592 is proposed to participate in the adventitious shoot organogenesis in Acacia crassicarpa . In the present study, it was found that miR2592-y was up regulated at EIII and EII stages, whereas its targets were GDH1 isoform X2 and TPA, and GDH1 was down-regulated. In the “plant hormone signal transduction” pathway, 11 miRNA-mRNA pairs were found related to auxin. In these pairs, 5 known miRNAs and 4 novel miRNAs were included. The 5 known miRNAs were miR1520-x, miR390-x, miR5658-x, miR6169-x and miR8154-x. miR1520 is unstable in sugarcane buds under cold stress  and only increased at EII stage, which would be expected to lead to an increase in repressing IAA4-like gene expression. The miR390 and its target as auxin response factor were previously reported , and therefore, the up-regulation at EII and EIII stages to affect the internode elongation was understandable. miR5658 targeted lateral suppressor-like protein (HaLS-L) and participated in growth and development, as reported previously in carrot . Overexpression of miR8154 in Taxus cell lines indicates that miR8154 regulates Taxol, phenylpropanoid, and flavonoid biosynthesis pathways . In this study, high expression of miR8154 at EI stage suggested that the activities of miR8154 were increasing at pre-elongation stage of internode in sugarcane.
In summary, mRNA and small RNA profiles were first revealed in sugarcane internode elongation, and comprehensive analysis was performed to identify the regulatory network during this biological process. The results suggested that potential miRNA-mRNA pairs involved in “zeatin biosynthesis”, “nitrogen metabolism” and “plant hormone signal transduction” pathways controlled stem growth and development. This evidence provides valuable information for further functional characterization of the miRNAs and their targets in sugarcane internode elongation.
Plant cultivation and tissue collection
The sugarcane variety GT42, which was bred through sexual hybridization , was used as the material in the present study. The sugarcane was grown in an intelligent greenhouse at the Sugarcane Research Institute of Guangxi Academy of Agricultural Sciences, Nanning, China. The bud body from the upper middle stem was selected on March 15, 2016. The seedcane was cut into single-bud setts, and cultivated in a sand table. When the seedlings grew to a height of 8–10 cm, those with consistent size were transplanted to an intelligent greenhouse. After two more month’s growth, when 9–10 true leaves emerged, the plants entered the pre-elongation stage (EI), and the tissue of the stem internode covered by the second true leaf was collected. When 12–13 true leaves emerged, the plants entered the early elongation stage, and the tissue from the stem internode covered by the second true leaf was collected (EII). The rapid elongation stage was determined when 15–16 true leaves emerged, and the stem internode tissue covered by the second true leaf was collected (EIII). Three biological replicates (individuals) were included in the present study for each stage. These tissues were stored at − 80 °C after liquid nitrogen treatment.
Construction of RNA and small RNA sequencing libraries
According to the supplier’s instructions, total RNA was extracted with RNA Trizol (Invitrogen, Carlsbad, CA, USA). The RNA integrity and quantity were detected by an Agilent 2100 bioanalyzer (Agilent, Santa Clara, CA, USA). Nine mRNA-seq libraries were constructed. First, the mRNAs were enriched by oligo (dT) beads and fragmented into short fragments by fragmentation buffer; second, the first-strand cDNA was reversely transcribed by random primers followed by synthesis of the second-strand cDNA using DNA polymerase I and RNase H; finally, the cDNA fragments were purified with a Qiaquick PCR extraction kit (Qiagen, Hilden, Germany) and ligated with Illumina sequencing adapters (Illumina, San Diego, CA, USA). The mRNA-seq libraries were prepared using pair-end methods (read length was 150 bp) and sequenced using a HiSeq™ 4000 (Illumina, San Diego, CA, USA).
Small RNAs from total RNAs were isolated with 3.5% agarose gel electrophoresis by isolating the 18–30 nt fragments. After ligation with 3′ adapters, the small RNAs were extracted by denaturing urea polyacrylamide gel electrophoresis by isolating the 36–44 nt desired band. Then, 5′ adapters were ligated with the isolated small RNAs following reverse transcription PCR, and the products were isolated again using 3.5% agarose gel electrophoresis at 62–75 bp. The small RNA libraries were sequenced using a HiSeq™ 2000 (Illumina, San Diego, CA, USA).
Raw data processing and de novo assembly of mRNA-seq reads
Raw reads were stored as fastq and filtered to obtain high-quality clean reads. Briefly, the adapters from raw reads were first removed; then, the reads containing > 10% unknown nucleotides (N) were excluded; and finally, low-quality reads that had 50% low quality (q-value lower than 10) bases were removed. The remaining reads were clean reads.
De novo assembly was conducted using the Trinity program (Version: v2.1.1). The inchworm assembled reads using a K-mer-based approach to generate contigs. Chryalis built a de Bruijn graph for clusters of contigs. Finally, based on de Bruijn graphs, Butterfly analyzed the read pairings from the contigs to generate transcripts and unigenes.
Identification of differentially expressed genes
Gene expression was calculated based on Reads Per kb per Million reads (RPKM) . The RPKM formula was the following: RPKM = (1 × 106 × C)/(N × L/1000), where C represents the number of reads mapped to the target unigenes, N represents the number of reads mapped to all the unigenes, and L is the length of the target unigenes. The calculation was performed by the RSEM package. The adjustment of the P-value for multiple testing by FDR correction was performed for identification of differentially expressed genes with FDR cutoff< 0.05. The differentially expressed genes were identified using the standard as |log2Ratio| ≥ 1 and q < 0.05.
The unigenes from De novo assembly were annotated by four public databases, including the NCBI non-redundant protein database (www.ncbi.nlm.nih.gov), Swiss-Prot protein database (www.expasy.ch/sprot), KOG database (www.ncbi.nlm.nih.gov/KOG) and Kyoto Encyclopedia of Genes and Genomes database (www.genome.jp/kegg), using the Blastx package from NCBI (www.ncbi.nlm.nih.gov/BLAST/). The cutoff e-value was 1e-5, and the best-aligned sequence was determined as the annotation for unigenes. Gene Ontology (GO) was used to reflect the gene function of the large unigene set. The GO annotation of the unigenes was performed using Blast2GO software based on the annotation results from the NCBI non-redundant protein database.
Processing of small RNA sequencing data
The clean small RNA reads were obtained from raw reads after removing the adapters and low-quality reads (the reads with more than one base with a Q-value lower than 20). Only small RNAs ranging from 18 to 35 nt in length were included in the further analysis. The clean small RNA reads were matched to the GenBank database (www.ncbi.nlm.nih.gov/genbank/, Version 209.0) and Rfam database (rfam.xfam.org/, Version 11) to identify and remove rRNA, scRNA, snRNA and tRNA by blastn (the cutoff e-value was 1e-5).
Identification of known miRNAs and novel miRNAs
Known miRNAs were identified by hitting the candidate miRNAs miRBase (www.mirbase.org/, Version 21) using blastn (the cutoff e-value was 1e-5). The annotated miRNAs were determined as known miRNAs. Novel miRNAs were predicted by mireap v0.2 (https://sourceforge.net/projects/mireap/). The parameters of mireap were -A 18, −B 25, −a 20, −b 23, −u 20, −e 18, −d 300, −p 16, −v 4, −s 4, and -f 20.
Prediction of the targets of miRNAs
The software patmatch (ftp://ftp.arabidopsis.org/home/tair/Software/Patmatch/, Version1.2) with default parameters was used to predict the targets of miRNAs. Then, based on the patmatch prediction, the gene-miRNA pairs with Spearman’s correlation coefficient for ranked data lower than − 0.5 were further confirmed the targets of miRNAs. The target gene functions of miRNAs were clarified by GO and KEGG annotation. GO enrichment was calculated by FDR correction, with FDR lower than 0.05 as significantly enriched. The KEGG pathways were performed with FDR correction, with FDR lower than 0.05 as a threshold.
Identification of differentially expressed miRNAs
The expression of miRNAs was assessed by transcripts per million (TPM), and TPM = miRNA counts/(Total miRNA counts× 106). The fold-changes were calculated using the formula fold-changes = log2(group1/group2). The miRNAs with fold change greater than 2 and P-value less than 0.05 were identified as differentially expressed miRNAs.
Quantitative PCR (qPCR)
Sugarcane tissues were collected as described previously. The total RNA from the different stages EI, EII and EIII was extracted with RNA Trizol (Invitrogen, Carlsbad, CA, USA). Ten of the differentially expressed genes from “zeatin biosynthesis”, “nitrogen metabolism” and “plant hormone signal transduction” pathways were selected for confirmation by qRT-PCR. The primers for qPCR were designed by Primer Express v3.0 (Applied Biosystems, Waltham, MA, USA) (Additional file 8). β-actin was used as the internal control. After RNA extraction, the first-strand cDNA synthesis was obtained using total RNA and a PrimeScript RT Reagent Kit with gDNA Eraser (TaKaRa, Dalian, China) following the manufacturer’s instructions. The cDNA was diluted to 1:20 and used as template for qPCR, which was performed using SYBR®Premix Ex Taq™ II (TliRNaseH Plus) (TakaRa, Dalian, China) according to the manufacturer’s instructions. The PCR was started with initial denaturation at 95 °C for 30 s, followed by 40 amplification cycles at 95 °C for 10 s and 60 °C for 30 s using an ABI 7500 Fast Real Time PCR System (Applied Biosystems, Waltham, MA, USA). The threshold cycle (CT) values were used to calculate relative expression by the 2-ΔΔCT method , which was performed using 7500 software version 2.0.4 (Applied Biosystems, Waltham, MA, USA). For qPCR of miRNA, the reverse transcriptase reaction was performed using a microRNA RT kit (TakaRa, Dalian, China). The cycles were the same as with mRNA analysis. All the reactions were performed with three biological repeats. The data were presented as the mean ± SD. The significant differences among the groups were assessed using one-factor analysis of variance (one-way ANOVA) followed by a Bonferroni post hoc test. P-value< 0.05 was considered statistically significant.
The authors are grateful to Dr. Prakash Lakshmanan (E-Mail: firstname.lastname@example.org) for his critical revision of this manuscript. We thank Pu Li from Guangxi Pfomic Info Technology Co., Ltd. for the technical support of bioinformatics analysis.
LQ, RC, and YF performed the experiments. XH and HL collected materials. FX, JL1 and RZ analyzed the data. LQ, JL2, HZ, JW and YL wrote the paper. All authors participated in the discussion and read and approved the final manuscript.
National Natural Science Foundation of China (31701363 and 31360312), Guangxi Natural Science Foundation Project (2018GXNSFAA138149, 2017GXNSFBA198050, 2016GXNSFBA380034, 2015GXNSFDA139011 and 2015GXNSFBA139095), Guangxi Key Laboratory Construction Project (15–140-13 and 16–380-18), Guangxi Science and Technology Project (Guike AA17202042–13), Guangxi Bangui Scholars and Special Experts Special Funds (2013), Guangxi Academy of Agricultural Sciences Fund Project (2015YM13 2018YM02 and 2018YT01), and National Modern Agricultural History Technology System, Guangxi Sugarcane Innovation Team Project (nycytxgxcxtd-03-01). The funding bodies had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
Ethics approval and consent to participate
No special permits were required to collect tissues from sugarcane.
Consent for publication
The authors declare that they have no competing interests.
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