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Identification and characterization of drought-induced long noncoding RNAs (DRILs) in rice


Long noncoding RNAs (lncRNAs) act as transcriptional regulators in plants and animals. To date, they have been reported to regulate various biological processes, such as phosphate homeostasis, grain yield, and fertility in rice (Oryza sativa L.). However, the lncRNAs involved in abiotic stress responses remain poorly identified in rice. In this study, we analyzed the expression profiles of lncRNAs using public rice transcriptome datasets derived from abiotic stress-treated samples. We found that the expression of thousands of rice lncRNAs was significantly altered in the shoot and root tissues under different abiotic stresses (drought, high salinity, low temperature, and abscisic acid). We selected six novel drought-induced lncRNAs (DRILs, specifically DRIL1 to DRIL6) for further study. Real-time polymerase chain reaction analysis revealed the differential expression patterns of these DRILs under various stress conditions. The expression of abiotic stress-responsive genes was upregulated in the protoplasts by transiently overexpressed DRIL1 and DRIL4. Therefore, DRILs may be involved in the transcriptional regulation of abiotic stress-responsive genes in rice.


Innovative sequencing technologies have revealed numerous unidentified transcripts in plants. To date, thousands of noncoding RNAs (ncRNAs) in plants have been annotated, and described ncRNA loci have increased continually in the plant genome [1]. ncRNAs do not code for proteins but have key regulatory roles in various biological processes [2]. Recent studies have demonstrated the broad range of long noncoding RNA (lncRNA) functions, including chromatin remodeling and transcriptional regulation at specific genomic loci [3]. The lncRNAs are ncRNAs that are longer than 200 nucleotides and have low protein-coding potential (< 100 amino acids); they modulate the expression of neighboring genes by cis-action and the expression of distant genes by trans-action [4, 5].

The functions of lncRNAs in rice (Oryza sativa L.) have been experimentally characterized in a few studies, which demonstrated that lncRNAs are involved in critical biological processes in rice [6]. Among them, LRK Antisense Intergenic RNA (LAIR) is a natural antisense transcript (NAT) transcribed from the antisense strand of the adjacent Leucine-rich Repeat Receptor Kinase (LRK) gene cluster in rice. LAIR overexpression increases grain yield and upregulates the expression of LRK genes [7]. Additionally, cis-NATPHO1;2 regulates phosphate homeostasis and plant fitness by promoting Phosphate 1;2 (PHO1;2) translation [8]. Overexpression of NATPHO1;2 leads to an increase in PHO1;2 protein levels under conditions of sufficient phosphate. Other rice NATs such as Twisted Leaf and Early Flowering-Completely Dominant regulate leaf development and flowering, respectively [9, 10]. Moreover, intergenic lncRNAs, including Long-Day–Specific Male-Fertility–Associated RNA, An Leaf Expressed and Xoo-induced lncRNA 1, and Mis-shapen Endosperm, are involved in photoperiod-sensitive male sterility, disease resistance, and endosperm development, respectively [11,12,13]. However, the lncRNAs related to abiotic stress responses have not yet been elucidated in rice.

Drought, high salinity, and low temperature are common abiotic stressors that adversely affect crop development and productivity. Plants have evolved molecular systems that coordinate gene expression to protect them from abiotic stress and boost their chances of survival in locations with abiotic stressors [15]. Intensive research has focused on protein-coding genes to understand the mechanisms of these stress responses and has provided a valuable platform for stress-tolerant crop development.

Here, we sought to identify abiotic stress-responsive lncRNAs via transcriptome analysis [16]. We then selected a group of unknown noncoding transcripts that were responsive to abiotic stresses and designated six of them as drought-induced long noncoding RNAs (DRILs) whose induced expressions were further validated under long-term drought stress. We aimed to investigate whether DRILs regulate the expression of stress-responsive genes and demonstrate that lncRNAs play essential roles in abiotic stress responses in rice.

Results and discussion

Transcriptome-wide re-analysis of abiotic stress-related lncRNAs

We re-analyzed public RNA-sequencing data to identify lncRNAs that responded to diverse abiotic stresses. Overall, 3,425 lncRNAs were induced or repressed under abiotic stress. Among them, 1,794 lncRNAs were commonly up-regulated and 1,631 were down-regulated in shoot and root samples (Fig. 1a). The heat map analysis in Fig. 1b shows the expression patterns of lncRNAs under different abiotic stress conditions. We considered the six most upregulated lncRNAs under four different abiotic stress conditions as DRILs (Table 1). Five of the lncRNAs (DRIL1 to DRIL5) are intergenic, and DRIL6 is a NAT. Schematic diagrams of the genomic locations of the DRILs are shown in Additional file 1: Figure S1; the DRILs had various transcript lengths. Predicted gene structures of the DRILs were diagramed using the Integrative Genomics Viewer browser (Additional file 1: Figure S2). We evaluated the protein-coding potential of the DRILs using the Coding Potential Calculator 2 to predict the coding potential of each transcript [17]. Five DRIL transcripts showed a very low coding potential score (0–0.2), similar to that of ELENA1, an lncRNA that has demonstrated no protein-coding potential [18]. DRIL6 showed a high coding potential score, comparable to that of the known protein-coding gene OsNAC14 (Additional file 1: Figure S3) [19]. Although there are no reports of NATs with protein-coding capacity, examining DRIL6 using mutated putative ORF is necessary to prove that it is an authentic lncRNA.

Fig. 1
figure 1

Genome-wide screening of abiotic stress-related lncRNAs. A Venn diagrams show the number of commonly expressed lncRNAs in shoot and root samples treated with drought, cold, abscisic acid (ABA), and salt. B Heat map analysis shows the differential expression of lncRNAs after drought, cold (4 °C), ABA (100 µM), and high salt (150 mM NaCl) treatments

Table 1 Six most up-regulated lncRNAs under abiotic stress conditions

DRILs are abiotic stress-inducible lncRNAs

The expression patterns of DRILs under abiotic stress were investigated using quantitative real-time polymerase chain reaction (qRT-PCR) analysis. Total RNA was extracted from the leaves and roots of 15-day-old rice seedlings (O. sativa L. cv. Kitaake) after exposure to drought, high salinity, abscisic acid (ABA), and low temperature. Each DRIL responded differentially to abiotic streses. DRIL1 expression was significantly upregulated in shoots by ABA, whereas it was highly induced in the roots by salt. DRIL5 expression was induced by drought, ABA, and salt stress in shoots, whereas it was strongly induced in roots, especially under cold conditions. The expression of DRIL2, DRIL3, and DRIL4 was induced under all stress conditions. To distinguish DRIL6 expression from the sense gene, the expression of DRIL6 and sense genes was verified using strand-specific qRT-PCR analysis. The results showed that DRIL6 expression was induced under drought conditions. Thus, the expression of DRILs was induced by various abiotic stressors (Fig. 2). Next, we examined the expression patterns of the DRILs under long-term drought conditions. After drought treatment, the time-course transcript levels of DRILs in the leaves were investigated using qRT-PCR analysis. Dehydration stress-inducible protein 1 (OsDip1, Os02g0669100) was used as a marker gene for the drought response. Our results showed that the expression of all DRILs gradually increased during long-term drought treatment, suggesting that all six DRILs were involved in drought stress responses in rice (Fig. 3).

Fig. 2
figure 2

Relative expression patterns of the DRILs in response to abiotic stresses. Fifteen-day-old rice seedlings were exposed to drought (air-drying), salt (400 mM NaCl), ABA (100 µM abscisic acid), and cold (4 °C). Leaves from the rice plants were harvested at the indicated times after treatment. The left graph shows expression in the shoot, and the right graph shows expression in the root. OsUBIQUITIN1 (OsUbi1) was used as an internal control for normalization. Data represent the mean value and standard deviation (n = 3). Significant differences from the mock 0 h control are indicated by asterisks (unpaired Student’s t-test, *P ≤ 0.05, **P ≤ 0.01, ***P ≤ 0.001)

Fig. 3
figure 3

Expression patterns of the DRILs during long-term drought conditions. One-month-old rice seedlings were exposed to drought conditions for 3 d. Relative expression of DRILs was determined via qRT-PCR analysis. OsUbi1 was used as an internal control for normalization. Data represent the mean value and standard deviation (n = 3). Significant differences from the control are indicated by asterisks (unpaired Student’s t-test, *P ≤ 0.05, **P ≤ 0.01, ***P ≤ 0.001)

DRILs positively regulate the expression of stress-responsive genes

To understand the transcription network that is regulated by DRILs, we performed transient expression analysis using a rice protoplast system. DRILs were overexpressed via the GOS2 constitutive promoter (Fig. 4a). We performed qRT-PCR analysis using the total RNA extracted from the rice protoplasts. The results showed that the expression of stress marker genes, such as OsWRKY71 (Os02g0181300), WIH2 (Os08g0205800), OsABA45 (Os12g0478200), and RBBI2-3 (Os01g0124650), was increased by DRIL1 overexpression (Fig. 4b). Additionally, cells that overexpressed DRIL4 showed enhanced expression of stress marker genes, such as WIH2, RGLG2 (Os12g0288400), OsGDH2 (Os04g0543900), and OsTPP1 (Os02g0661100), compared to the control (empty vector) (Fig. 4d). These stress marker genes were noted by previously reported RNA gel blot analysis results [20] and were confirmed by qRT-PCR analysis (Additional file 1: Figure S4). OsGDH2, RBBI2-3, and RGLG2 were expressed under drought, ABA, salt, and cold stress conditions. OsWRKY71 and WIH2 expression was induced by drought, ABA, and salt stress. GEM expression was induced under drought and low temperature, and OsTPP1 was induced only by cold stress. We then selected a downstream gene that responded to multiple abiotic stresses as a marker gene for various patterns. To confirm whether DRIL1 and DRIL4 have cis-target genes, the expression of two neighboring genes was examined. Our results showed that there was no change in the expression levels of these neighboring genes, suggesting that DRIL1 and DRIL4 are trans-acting lncRNAs (Fig. 4c, e). Subsequently, we investigated the spatiotemporal expression of DRIL1 and DRIL4 corresponding to each developmental stage. lncRNAs exhibit tissue and cell type specificity similarly to protein-coding genes [21]. Hence, DRIL1 showed specific expression in root tissue; however, DRIL4 did not significantly differ, regardless of the tissue and the developmental stages (Additional file 1: Figure S5). To assess whether DRIL6 expression changed that of the sense gene OsDof2, we analyzed their relative expression levels using strand-specific qRT-PCR. Our results indicated that there was a mutual activation between DRIL6 and OsDof2 (Fig. 4f) because DRIL6 was the antisense transcript of the OsDof2 transcription factor. A previous study showed that OsDof2 has a circadian rhythm and is regulated by phytochrome signaling, which is associated with grain size in rice [22]. It has been reported that lncRNAs, as pivotal regulators, are involved in every step of gene expression. In general, lncRNAs act in cis or trans, regulating neighboring or distal target genes. For instance, lncRNAs alter gene transcription by changing chromatin modifications and guiding or sequestering transcriptional activators or repressors. Also, lncRNAs control post-transcriptional processing, such as splicing, editing, and stability of messenger RNAs. Besides, lncRNAs affect translation, localization, and stability of proteins [2, 3, 5, 6]. In this study, we demonstrated that DRIL1, DRIL4, and DRIL6 activate the expression of stress marker genes and cis-target gene, respectively. Therefore, we assume that these three DRILs might activate their target genes through the regulatory mechanisms mentioned above. Although the precise mechanism and function of DRILs are still unknown, we expect that DRILs could affect abiotic stress responses in plants. Further research should focus on functional characterization of DRILs to understand the molecular mechanisms of lncRNAs in these stress responses.

Fig. 4
figure 4figure 4

Overexpression of the DRILs in rice protoplasts. A Schematic diagram of the transient overexpression constructs of the DRILs. In the constructs, the DRILs are under the GOS2 promoter and PinII terminator. The binary vector was generated through the gateway system. B DRIL1 overexpression and the expression levels of stress marker genes. OsUbi1 was used as an internal control for normalization. C The expression of the putative cis-target genes of DRIL1. Numeric values in Tables indicate fold changes derived from RNA-sequencing with long-term drought stress-treated samples. d, drought; C, control. D DRIL4 overexpression and the expression levels of stress marker genes. E The expression of the putative cis-target genes of DRIL4. Numeric values in Tables indicate fold changes derived from RNA-sequencing with long-term drought stress-treated samples. d, drought; C, control. F Overexpression of DRIL6 and OsDof2. The green bars represent OsDof2 overexpression, and the yellow bars represent DRIL6 overexpression (unpaired Student’s t-test, *P ≤ 0.05, **P ≤ 0.01)

Materials and methods

Plant growth conditions and stress treatments

The O. sativa L. japonica rice cultivar Kitaake was used in this study; its genetic sequence was obtained from the Phytozome v. 13 genomics resource data. For germination, dehusked rice seeds were surface-sterilized by soaking in a 70% ethanol solution for 1 min, followed by washing with a 50% sodium hypochlorite solution for 30–40 min. The seeds were then washed ten times with sterile distilled water and sown on Murashige and Skoog media. After three days, the rice was transferred to seedling culture containers (Phytohealth, 120 × 80 mm; SPL, Korea), which were used to grow the seedlings. All rice materials were grown in a growth chamber at 28 °C under a 12 h light/12 h dark photoperiod. For the stress treatment, 14-day-old seedlings were adapted to water for one day and treated for each stress condition.

RNA extraction and quantitative real-time PCR

Total RNA was extracted from wild-type plants using a total RNA purification kit (Hybrid-R, Geneall, Korea), following the manufacturer’s instructions. For cDNA synthesis, 1 µg of total RNA was reverse-transcribed using an improved reverse transcriptase (SuperiorScript II Reverse Transcriptase, Enzynomics, Korea) for 5 min at 37 °C and 60 min at 50 °C. Subsequently, the reaction was terminated by incubating for 10 min at 70 °C. qRT-PCR was performed (using the 2X Real-Time PCR Smart Mix, SRH72-M10h, SolGent, Korea). The reaction was performed at 95 °C for 15 min, followed by 40 cycles of 95 °C for 20 s, 60 °C for 20 s, and 70 °C for 30 s, using an qRT-PCR machine (AriaMx, Agilent, USA). OsUbi1 (Os06g0681400) was used as an internal control for normalization. Three replicates were analyzed for quantitative experiments. The primer sequences used for qRT-PCR are listed in Additional file 2: Table S1.

Strand-specific reverse transcription

An adapter-mediated qRT-PCR assay was used to distinguish strand-specific expression, as stated previously [23]. We used synthesized cDNAs with a antisense DRIL6- or Dof2- specific reverse primer and including a tag sequence (Additional file 2: Table S1). Subsequently, qRT-PCR was performed with the tag-specific primer and DRIL6- or Dof2-specific forward primer.

Protoplast isolation and transient gene expression

A polyethylene glycol (PEG)–mediated protoplast transformation method was used to transiently express DRILs and verify the relationship between DRILs and stress marker genes [24, 25]. Leaf sheaths of 100 rice seedlings were cut into 0.5 mm pieces using a sharp blade on glass. The pieces were transferred into 0.6 M mannitol solution and incubated for 20 min at room temperature in the dark. After removing the mannitol solution, the pieces were soaked in enzyme solution consisting of 1.5% Cellulase R-10 (Yakult, Japan), 0.75% Macerozyme R-10 (Yakult, Japan), 0.5 M mannitol, 10 mM MES (pH 5.7), 0.1% BSA, 10 mM CaCl2, and 5 mM β-mercaptoethanol for cell wall degradation. Vacuum infiltration was repeated thrice for 15 min to apply the enzyme solution. Digestion was performed in a dark chamber with gentle shaking for 4 h. The solution was filtered twice through 70 µm and 40 µm nylon meshes (Falcon, USA) and centrifuged at 150 × g for 3 min. The protoplast pellet was resuspended in W5 solution, which contained 154 mM NaCl, 125 mM CaCl2, 5 mM KCl, and 2 mM MES (pH 5.7). The protoplast concentration was measured under a microscope using a hemocytometer and was adjusted to 7 × 107 protoplasts/mL. To transfect DNA into cells, 50 µL of the protoplast solution (2 × 106 cells) was mixed with 15 µL of plasmid (1 µg) and 130 µL of PEG solution, which contained 0.2 M mannitol, 100 mM CaCl2, and 40% w/v PEG4000. The mixture was incubated for 15 min in the dark; subsequently, 1 mL of W5 solution was added. The mixture was then centrifuged at 300 × g for 2 min to collect protoplasts, which were resuspended in an incubation solution containing 0.5 M mannitol, 20 mM KCl, and 4 mM MES (pH 5.7) for 12 h. Protoplasts were harvested by centrifugation at 300 × g for 2 min and used for RNA extraction and qRT-PCR.

Availability of data and materials

The datasets used and/or analysed during the current study are available from the corresponding author on reasonable request.



Abscisic acid


Drought-induced long noncoding RNAs


Long noncoding RNAs


Natural antisense transcript


Noncoding RNAs


Polyethylene glycol


Quantitative real-time polymerase chain reaction


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We would like to thank Mr. Jae-Yun Lim for the bioinformatics analysis.


This work was supported by the Creative-Pioneering Researchers Program of Seoul National University, National Research Foundation of Korea (NRF) grant (2019R1F1A1046305), and New Breeding Technologies Development Program (PJ016542) through the Rural Development Administration (RDA), Republic of Korea.

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NO and CJ designed the study. NO performed the experiments. PJ assisted with bioinformatics analysis. JL, JKS, JHK, and HSC interpreted and discussed the data. NO, JSS, and CJ wrote the manuscript and prepared the figures. All authors read and approved the final manuscript.

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Correspondence to Choonkyun Jung.

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Supplementary Information

Additional file 1: Figure S1.

Schematic diagram of the genomic locations of the DRILs. Figure S2. Visualizations of the RNA-sequencing reads in the Integrative Genomics Viewer browser. These show an increasing pattern as time elapsed. Figure S3. Coding potential scores of the DRILs. This was analyzed by using the Coding Potential Calculator 2 to predict the coding potential of each transcript. ELENA1 was used as the control for lncRNA, and OsNAC14 was used as the control for protein-coding RNAs. Figure S4. Relative expression patterns of stress marker genes in response to abiotic stressors. Fifteen-day-old seedlings (Oryza sativa L. japonica cv. Kitaake) were exposed to drought (air-drying), salt (400 mM NaCl), ABA (100 µM abscisic acid), and cold (4 °C). OsUbi1 was used as an internal control for normalization. Data represent the mean value and standard deviation (n=3). Significant differences from the mock 0 h control are indicated by asterisks (unpaired Student’s t-test, *P ≤ 0.05, **P ≤ 0.01, ***P ≤0.001). Figure S5. DRIL1 and DRIL4 expression at each developmental stage. qRT-PCR analysis of DRIL expression in rice tissues at different developmental stages.

Additional file 2: Table S1.

List of primer sequences.

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Oh, N., Seo, J.S., Chung, P.J. et al. Identification and characterization of drought-induced long noncoding RNAs (DRILs) in rice. Appl Biol Chem 65, 79 (2022).

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  • Long noncoding RNA
  • Abiotic stress response
  • Drought
  • Abscisic acid
  • High salinity
  • Low temperature
  • Rice
  • Protoplasts