Skip to main content
NCBI home page
BMC Plant Biology logoLink to BMC Plant Biology
. 2025 Oct 1;25:1266. doi: 10.1186/s12870-025-07273-4

OsFLN2 gene knockout reduces leaf water status and photosynthetic performance of rice plants under water deficit

Danyel Fernandes Contiliani 1,2,#, Simone Ferreira da Silva 1,#, Rafael Vasconcelos Ribeiro 3, Vitor Nolasco Moraes 1, Laísa Medeiros Rocha 1,2, Greice Lubini 1, Paula Macedo Nóbile 1, Tiago Campos Pereira 2,4, Silvana Creste 1,2,✉
PMCID: PMC12487551  PMID: 41034703

Abstract

Abiotic stresses significantly impact plant growth and productivity. To overcome these challenges, plants employ photosynthetic acclimation mechanisms, enabling them to sustain photosynthetic efficiency under adverse conditions. The OsFLN2 gene has been identified as a key player in chloroplast development and response to heat and salinity stress. However, the physiological effects of OsFLN2 gene knockout and its impact on drought tolerance remain elusive. In this study, we explored the function of OsFLN2 in rice plants under water deficit conditions using a non-transgenic CRISPR knockout mutant. Our findings demonstrate that Osfln2 mutant plants exhibit higher sensitivity to water deficit, characterized by reduced photosynthetic activity and reduced transcriptional responsiveness of plastid genes, such as RbcL and PsaA. As a result, these plants display compromised carboxylation efficiency and reduced leaf water use efficiency at the maximum water deficit. Concluding, our results demonstrate the role of OsFLN2 on physiological acclimation of rice plants under water-limiting conditions.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12870-025-07273-4.

Keywords: Drought, fructokinase-like protein 2, Osmotic regulation, Photosynthesis, Rice

Introduction

Chloroplasts are the energy factories of the cell, converting light into chemical energy, thus sustaining life on Earth. Despite its relatively small genome size (typically up to 160 kb), chloroplasts display a few hundred genes crucial for plant viability [10]. Many of these genes are committed to assembling the photosynthetic apparatus, such as photosystem II and I proteins [40]. Hence, transcriptional disturbances in plastid genes often result in developmental defects and, in severe cases, plant death. For instance, in ever-changing environments, some chloroplast proteins require repair, de novo synthesis, or even depletion under a specific developmental stage or external stimulus. Thus, a robust chloroplast transcriptional system must function properly to ensure both photosynthetic and plant plasticity. As a sensor of the external environment, the plastid genome has a complicated transcriptional system that enables the fine regulation of gene expression. Plastid genes are transcribed by two distinct types of RNA polymerases: nucleus-encoded RNA polymerase (NEP) and plastid-encoded RNA polymerase (PEP) [4, 20], with the latter being responsible for more than 80% of the transcripts in mature chloroplasts [42]. Polymerase-associated proteins (PAPs) form a complex with PEP, which safeguards the transcriptional machinery [34], especially against redox imbalances in the chloroplasts [28].

One of these PAPs is FRUCTOKINASE-LIKE 2 (FLN2), a member of the pfkB-carbohydrate kinase family, which is encoded in the nucleus and interacts alongside FLN1 with other PAPs – mainly PAP10/THIOREDOXIN Z, conferring redox regulation of the transcriptional activity [29]. In rice plants, while OsFLN1 loss-of-function is associated with severe albino phenotype and seedling lethality [13], OsFLN2 knockout resulted in heat- and salt-sensitive, pale-green seedlings with a substantial delay in chloroplast biogenesis [6, 30]. These Osfln2 mutant plants also exhibited downregulation of some plastid genes, such as PsaA and RbcL, indicating the importance of OsFLN2 in PEP-mediated transcriptional regulation under normal and stressful conditions [30]. However, the direct impact of OsFLN2 knockout on photochemical efficiency and leaf gas exchange remains to be explored, particularly under abiotic stresses.

Drought and heat stresses, two major threats exacerbated by climate change, often coincide, significantly reducing crop yields globally. The OsFLN2 gene was recently reported as necessary for rice plants to withstand heat [30] and salinity [6] stresses. Based on the similarities with these abiotic stresses, such gene would also improve plant acclimation to drought [7]. Nevertheless, the relevance of this gene in water-scarce conditions needs to be investigated. The impact of the OsFLN2 knockout on photosynthetic processes has so far only been assessed at the transcriptional level, thus warranting further investigations at the physiological level in rice plants. In this regard, this study aimed to analyze the role of the OsFLN2 gene in rice plants under drought conditions and the physiological disturbances caused by the defective PEP-mediated transcriptional regulation in Osfln2 knockout plants. The results of this study provide a better understanding of the OsFLN2 role in photosynthetic acclimation to environmental challenges.

Results

Knockout of OsFLN2 affects plastid gene expression in rice plants

The FRUCTOKINASE-LIKE 2 (OsFLN2) genomic sequence was targeted by a CRISPR-Cas9 system using an experimentally validated sgRNA (Fig. 1a) reported elsewhere [6, 30]. In the T0 generation, regenerated plants were screened for indels in the target site using a T7 endonuclease I (T7E1) assay, revealing potential gene-edited plants (Figure S1). To avoid any effect of the T-DNA integration in the genome, these plants were subjected to T-DNA segregation to obtain the third generation of edited (E3) transgene-free plants, which Sanger sequencing showed a homozygous insertion for the Osfln2 line #16 (Fig. 1b), resulting in a frameshift with a premature stop codon, thus indicating loss of function.

Fig. 1.

Fig. 1

Open in a new tab

Knockout of OsFLN2 in rice plants and plastid gene expression. a, Schematic illustration of OsFLN2 gene and the guide RNA targeting the second exon. b, Sanger sequencing of OsFLN2 target site in WT (up) and Osfln2 #16 KO plants (down). The red asterisk indicates the homozygous insertion in Osfln2 plants. c, 15-day-old WT and Osfln2 rice plants, highlighting the albino phenotype of the KO plant (right). d, e, f, g, Differential gene expression analyses on PsaA, PsaB, RcbL, and TrxZ genes comparing Osfln2 against WT rice plants under irrigated and drought treatments. P values were obtained using the two-tailed Student’s t-test. *P < 0.05, **P < 0.01

Fifteen days after sowing, the line Osfln2 #16 exhibited an albino phenotype in contrast to the wild-type (WT) rice plants (Fig. 1c); however, both genotypes displayed normal phenotypes and similar chlorophyll levels (Figure S2) at the adult stage. The water deficit regime was applied on 57-day-old plants, and their chloroplast transcription responses were determined at the maximum water deficit (after eight days under water deficit). Four plastid genes, PsaA, PsaB, RcbL, and TrxZ, had their expressions analyzed under irrigated and water deficit (Fig. 1d-g). By comparing the gene expression of Osfln2 against WT plants, PsaA was significantly repressed even under irrigated conditions (Fig. 1d). Under water deficit, PsaA (Fig. 1d) and RcbL (Fig. 1f) were also significantly downregulated. Despite the repression trends on PsaB and TrxZ gene expressions, there were no statistical differences.

Osfln2 plants show improved leaf water retention under water deficit

Substrate moisture was gradually reduced after water withholding, reaching approximately 20% of the maximum water retention capacity (MWC) after 8 days (maximum water deficit) (Figure S3). At this stage, drought-stressed plants showed a significant reduction in leaf water potential (Fig. 2a, b) and relative water content (Fig. 2c, d) compared with irrigated plants, regardless of the genotypes. However, these parameters were fully restored on the fourth day after substrate rehydration. Although no differences in Ψ were observed between the genotypes, Osfln2 plants had higher relative water content (RWC) than WT plants at the maximum water deficit, indicating a less severe water loss.

Fig. 2.

Fig. 2

Open in a new tab

Drought treatment on rice plants. Leaf water potential (Ψ) and RWC of wild-type (a,c) and Osfln2 plants (b,d) under irrigated (CTRL) and water deficit (WD) conditions. Measurements were carried out at the onset of drought regime (T0), eight days after irrigation suspension (maximum water deficit, T1) and four days after rehydration (T2, gray area). Capital letters compare water treatments, whereas the lowercase ones compare genotypes (n = 5), BF10 > 3

Osfln2 plants display reduced carboxylation and water use efficiency under water deficit

The leaf gas exchange parameters were evaluated on these plants every two days (Fig. 3). As an expected response to low water availability, both genotypes showed reductions in photosynthesis (Fig. 3a, b), stomatal conductance (Fig. 3c, d), and transpiration (Fig. 3e, f). In Osfln2 plants, these changes became evident four days after water withholding, whereas no changes were observed in WT plants until the sixth day. At the maximum water deficit, photosynthesis was significantly lower in Osfln2 plants (−50%) than in WT plants (Fig. 3a, b). As stomatal closed, the intercellular CO2 concentration was reduced in both genotypes (Fig. 3g, h). However, the intercellular CO2 concentration in Osfln2 plants was much higher than one in WT plants at the maximum water deficit. We did not find any change on how photosynthesis is dependent on stomatal conductance (gs) or on photochemical (ΦPSII) and biochemical (k) reactions (Figure S4).

Fig. 3.

Fig. 3

Open in a new tab

Assessment of leaf gas exchange parameters. a, b, Leaf CO2 assimilation (An), c, d, stomatal conductance (gs), e, f, transpiration (E), g, h, intercellular CO2 concentration (Ci) in fully expanded young leaves of WT and Osfln2 rice plants subjected to irrigated (CTRL) and water deficit (WD) regimes. The gray area represents the period after the rehydration of drought-treated plants. Each dot indicates the average value (n = 5) ± standard deviation. The asterisk indicates the statistical difference between water treatments and letters compare genotypes under the same treatment, BF10 > 3

Considering the disturbances on carbon assimilation in Osfln2 plants, the carboxylation and water use efficiencies were determined (Fig. 4). Although the instantaneous carboxylation efficiency was significantly reduced under water deficit in both genotypes, it was lower in Osfln2 plants at the sixth and eighth days (−62%) as compared to the WT plants. Accordingly, the water use efficiency of Osfln2 plants was significantly lower (−43%) than one of WT plants under the maximum water deficit.

Fig. 4.

Fig. 4

Open in a new tab

Carboxylation and water use by Osfln2 rice plants. a, b, Carboxylation efficiency (k) and c, d, water use efficiency (WUE) in fully expanded young leaves of WT and Osfln2 rice plants subjected to irrigated (CTRL) and water deficit (WD) regimes. The gray area represents the period after the rehydration of drought-treated plants. Each dot indicates the average value (n = 5) ± standard deviation. The asterisk indicates the statistical difference between water treatments and letters compare genotypes under the same treatment, BF10 > 3

To assess the light-dependent reactions under drought stress in these plants, the electron transport rate, and the effective and potential quantum efficiencies of photosystem II were analyzed (Fig. 5). The water deficit significantly reduced the electron transport rate and the effective quantum efficiency of photosystem II in both genotypes after six days of water withholding, with full recovery observed four days after substrate rehydration. However, Osfln2 plants exhibited substantial decreases in both parameters as compared to WT plants. Although water deficit did not reduce Fv/Fm at the predawn (Fig. 5f, g), Osfln2 plants showed significantly lower Fv/Fm than WT plants at the maximum water deficit (T1) and after rehydration (T2), regardless of water treatment.

Fig. 5.

Fig. 5

Open in a new tab

Photochemical parameters on Osfln2 rice plants. a,b, Electron transport rate (ETR), c, d, effective quantum efficiency of PSII (ΦPSII) in fully expanded young leaves of WT and Osfln2 rice plants subjected to irrigated (CTRL) and water deficit (WD) regimes. Each dot indicates the average value (n = 5) ± standard deviation. The gray area represents the period after the rehydration of drought-treated plants. The asterisk indicates the statistical difference between water treatments and letters compare genotypes under the same treatment, BF10 > 3. e,f, Maximum quantum efficiency of PSII (Fv/Fm) in fully expanded young leaves of WT and Osfln2 rice plants subjected to irrigated (CTRL) and water deficit (WD) regimes. T0: onset of experiments; T1: eight days after water withholding (maximum water deficit), and T2 (gray area): four days after substrate rehydration. Capital letters compare water treatments and lowercase letters compare genotypes (n = 5), BF10 > 3

Finally, we investigated the photochemical (qP) and non-photochemical quenching (NPQ) to understand the ability of Osfln2 plants to utilize light energy for the production of ATP and NADPH and the dissipation of energy as heat, respectively (Fig. 6). Although these plants showed significantly lower qP values (Fig. 6a) compared to WT plants under maximum water deficit, no differences in NPQ were observed in the same condition (Fig. 6b). The excess excitation energy at PSII (EXC) was significantly higher in Osfln2 rice plants under water deficit.

Fig. 6.

Fig. 6

Open in a new tab

Fluorescence quenching analyses on Osfln2 rice plants. a, Photochemical quenching (qP), indicating the proportion of open PSII reaction centers available for electron transport, b, Non-photochemical quenching (NPQ), reflecting the dissipation of excess energy as heat, and c, the excess of excitation energy at PSII (EXC), the level of energetic pressure due to excess light absorption. The measurements were taken between 8h00 and 10h00. Capital letters compare water treatments and lowercase letters compare genotypes (n = 5), BF10 > 3

Discussion

The OsFLN2 gene regulates chloroplast development by interacting with the PEP complex, thus contributing to the transcription of PEP-dependent plastid genes [13]. Since the chloroplast is a critical sensor of the environment, plants with OsFLN2 loss-of-function cannot cope adequately with abiotic stresses, such as heat [30] and salinity [6]. Here, we subjected Osfln2 knockout rice plants to water deficit and investigated the impacts on their photosynthetic performance. Similarly to Qiu et al. [30], our transgene-free, gene-edited Osfln2 rice plants displayed albino phenotype at early stages and transcriptional repression of plastid genes even under irrigated conditions. Although ectopic overexpression of OsFLN2 (driven by the drought-inducible OsHAK1 promoter) has ensured drought tolerance in rice [7], the physiological effects of OsFLN2 loss-of-function under water-scarce conditions were unknown until now. Here, we demonstrate a higher photosynthetic sensitivity of Osfln2 rice plants to water deficit, alongside reduced water use efficiency under low water availability. These results reinforce the key role of OsFLN2 gene in maintaining the transcriptional dynamics of plastid genes, especially under abiotic stress.

In a water scarcity scenario, plant roots sense changes in water availability and emit chemical (e.g., ABA) and hydraulic signals to the shoots, an essential reaction for proper metabolic adjustment to water stress [41]. The osmotic balance of drought-stressed plants is typically regulated by the influx and efflux of compatible solutes, including ions, amino acids and soluble sugars, critical osmoregulatory substances [17]. Interestingly, despite anticipating stomatal closure at the early stages of water stress, Osfln2 rice plants showed significantly lower RWC than WT plants at the maximum water deficit. Although the Ψ behaved similarly between genotypes, Osfln2 plants presented leaves with the highest water content. This result suggests higher efficiency in controlling water loss, which may be associated with anticipating stomatal closure and the activation of osmotic adjustment mechanisms. Interestingly, despite exhibiting higher relative water content in the leaves than WT plants under water deficit, Osfln2 rice plants displayed a more pronounced decline in leaf CO2 assimilation (An) at the maximum water deficit, suggesting a higher sensitivity of the photosynthetic apparatus in this genotype. Although subtle in magnitude, the differences observed between genotypes were statistically significant and may hold physiological relevance, especially under drought conditions. It is well-established that small changes in photosynthetic parameters, such as CO₂ assimilation or stomatal conductance, can result in meaningful impacts on plant performance under water-limited environments [5, 11].

The stomatal closure, as an adaptive response of plants to cope with drought stress, also leads to a reduction in CO2 assimilation [27]. In fact, this diffusional limitation reduced photosynthetic rates in WT and Osfln2 rice plants under the water deficit. While the intercellular CO2 concentration (Ci) is expected to decrease in early stages of water deficit (e.g., after 6 days under water withholding), a substantial increase of Ci was found in Osfln2 plants but not in WT at the maximum water deficit. This finding suggests that photosynthesis was limited by carboxylation reactions rather than by CO2 availability at the ribulose-1,5-bisphosphate carboxylase/oxygenase (RuBisCO) sites. In fact, RuBisCO promotes the fixation of CO2 during photosynthesis, converting it into organic compounds essential for sugar production and yield [19]. Its large and small subunits, encoded by RbcL and RbcS genes, respectively, play complementary roles in carboxylation activity [2, 26]. Although PEP-dependent transcription of RbcL gene was significantly repressed in drought-stressed Osfln2 plants, it is unlikely to associate gene expression with RbcL protein levels at the stage sampled – as RuBisCO synthesis in rice is virtually completed before leaf maturation [23]. However, considering that Osfln2 knockout plants may present deturbed PEP-dependent gene expression from the early stages of development, it is expected that the low availability of RuBisCO may contribute to the lower k values observed under stress conditions [35, 36]. In light of the importance of RbcL in maintaining photosynthetic rates under water-limiting conditions [1, 16, 18, 31] – a typical trait of drought-tolerant plants [9, 22, 24, 33] – the impaired regulation of this gene at early developmental stages may be associated with the sensitivity of Osfln2 plants to abiotic stresses.

The impact of drought on net carbon assimilation leads to an imbalance between the capture and use of energy by photosynthesis and also to damage to the photosynthetic machinery, with decreases in ΦPSII and then ETR [38]. At the maximum water deficit, Osfln2 rice plants exhibited significantly lower qP, ΦPSII, ETR, and Fv/Fm and higher EXC than WT plants, indicating lower photochemical efficiency and excessive energy pressure at PSII. Several proteins assemble photosystems I and II, cytochrome b6-f complex and ATP synthase in the thylakoid membranes, which act synergistically with other molecular mediators on photophosphorylation. The transcription of their encoding genes is mostly PEP-dependent [40] and, hence, is expected to be downregulated in FLN2 loss-of-function lines [14, 15, 30]. In fact, the protein levels of PsbD (D1, core of PSII) and PetA (cytf, a component of the cytochrome b6-f complex) were found to be low in Arabidopsis fln2-4 mutant lines [15]. This may be directly associated with a decrease in the conversion of light energy into ATP and NADPH in Osfln2 rice plants under water deficit. Furthermore, the PsaA gene expression was significantly repressed in rice Osfln2 mutants, as it is regulated by PEP. Its expression was even more suppressed (4-fold log2 fold-change) than the WT line under water deficit. As a coding core component of the PSI, PsaA functioning is considered critical for photoacclimation towards harsh environments (Leelavathi et al., 2011). Collectively, these findings point to correlations between the Osfln2 loss of function and its impacts on photosynthesis under water deficit.

Conclusions

The OsFLN2 gene, as a genetic element involved in PEP-dependent transcription pathways of plastid genes [29], is crucial for chloroplast development in plants. Here, we revealed that Osfln2 knockout rice plants are more sensitive to water deficit, showing transcriptional repression of genes associated with RuBisCO and photochemical activity. This compromised transcriptional responsiveness to low water availability is translated into compromised carboxylation and water use efficiencies and reduced ability to convert light energy into chemical one in chloroplasts. Finally, our findings reinforce the molecular relevance of the OsFLN2 gene on photosynthetic responses to limiting conditions, drought in our case.

Materials and methods

Rice genome editing

The OsFLN2 coding sequence (LOC_Os03g40550) was obtained from the Rice Genome Annotation Project (RGAP) and submitted to CRISPOR [8] for sgRNA design. Among the suggested sgRNAs, an experimentally validated sequence 5’-TCAAGTGATGATGAGAGTGA-3’ [6, 30] was selected and cloned into a commercial CRISPR/Cas9 vector (pCRISPRPL, Sigma-Aldrich). The sgRNA-containing pCRISPRPL plasmid was transformed into Agrobacterium tumefaciens (EHA105) for rice stable transformation.

Japonica rice (Oryza sativa ssp. japonica cv. Nipponbare) plants were grown in 5 L pots containing a mixture (1:1, v/v) of soil and substrate (Carolina Soil, Santa Cruz do Sul, Brazil) under greenhouse conditions (21°11′S, 47°48′W). Mature seeds were obtained and used for Agrobacterium-mediated transformation of embryogenic calli, as described elsewhere [37]. Transformed plants were selected and regenerated on a medium containing 30 mg L−1 hygromycin. Then, regenerated plants were transferred to 5 L pots and grown as previously described.

Mutation analyses and screening of transgene-free plants

Genomic DNA from hygromycin-resistant T0 plants was extracted using GenEluteTM Plant Genomic DNA Miniprep kit (Sigma-Aldrich, USA), and the OsFLN2 target site was amplified using specific primers (Table S1) and Q5® High-Fidelity DNA Polymerase (New England Biolabs, USA). As a preliminary screening, 250 ng of purified PCR products were denatured, reannealed, and digested with T7 Endonuclease I enzyme (New England Biolabs, USA), according to the manufacturers’ recommendations. The digested products were analyzed via 1.5% agarose gel electrophoresis. Events that showed digested DNA bands in the T7E1 assay were genotyped using Sanger sequencing of PCR products. The overlapping chromatogram peaks of Sanger sequencing were decomposed using TIDE (Brinkman et al., 2014), thus providing the percentage of indels for each event. Gene-edited rice plants were self-crossed up to the E3 generation, and the T-DNA was amplified using specific primers (Table S1). Plants without T-DNA were genotyped and selected for downstream analyses.

Gene expression analysis

Total RNA was extracted from fully expanded young leaves (flag leaf) of 64-day-old rice plants by the phenol chloroform method. Thereafter, 1 µg of RNA was treated with DNAse I (Invitrogen, USA) and the cDNA synthesis was performed with the GoScript Reverse Transcriptase Kit (Promega, USA). For gene expression, 3 µL of diluted (1:10) cDNA was utilized in each qPCR reaction with the GoTaq qPCR Master Mix (Promega, USA). The analysis was performed on a Step One Plus Real-Time qPCR Systems (Thermo Fisher Scientific, USA), and all procedures were performed according to the manufacturers’ instructions. The gene expression was normalized by the GAPDH housekeeping gene expression and relative expression (log2 fold-change) was determined by comparing Osfln2 against WT samples using the 2−ΔΔCT method [21]. Primers sequences are listed in Table S1.

Plant material and growth condition

Thirty-five days after sowing (DAS), gene-edited (Osfln2) and wild-type (WT) rice seedlings were transferred to polyvinyl chloride pots (5 L) containing a mixture (1:1, v/v) of soil and substrate (Carolina Soil, Santa Cruz do Sul, Brazil). The soil was fertilized with 3 g of (NH₄)₂SO₄, 1 g of KCl, and 0.75 g of monoammonium phosphate. Each pot contained one Osfln2 and one WT rice seedling, ensuring their exposure to the same water availability [39]. The plants were cultivated in a greenhouse, with air temperature and relative humidity monitored using a data logger (HOBO® MX2300, Onset Computer Corporation, USA) at Centro de Cana, Ribeirão Preto SP, Brazil (21.1704˚S, 47.8103˚W). All the plants were fertigated with Sarruge nutrient solution [32] before the start of the experimental period.

Water deficit

Fifty-seven DAS, five plants of each genotype were initially evaluated (T0), and another 40 plants were grouped into two groups. One group remained irrigated (control, CTRL), with plants Maintained under substrate moisture at around 80% of the maximum water storage capacity (MWC) throughout the experimental period. The other group was submitted to water deficit (WD) by water withholding for eight days, when the second evaluation occurred (T1, maximum WD). Following this, the substrate of the WD plants was rehydrated for four days before the final evaluation (T2, rehydration). The soil water content (Figure S5) was measured every two days using a soil moisture sensor probe (ProCheck, Decagon Devices Inc, USA).

Physiological analyses

Leaf relative water content (RWC) was measured using six leaf discs (0.6 cm2) in two replicates for each plant. The RWC was calculated as: RWC=[fresh weight – dry weight]/[turgid weight – dry weight]*100 [12]. Leaf water potential (Ψ) was evaluated using a pressure chamber (model 3005, Soil Moisture Equipment Corp., USA). These evaluations were taken on fully expanded young leaves of tillers adjacent to the main tiller (secondary tiller) at T0, T1, and T2 between 4h00 and 6h00 (predawn).

Leaf gas exchange and chlorophyll fluorescence were measured using an infrared gas analyzer (Li-6400, Li-Cor, USA) equipped with a modulated fluorometer (6400-40 LCF, Li-Cor, USA). These evaluations were taken on two fully expanded young leaves from the main tillers. Leaf CO2 assimilation (An), stomatal conductance (gs), transpiration (E), intercellular CO2 concentration (Ci), the effective quantum efficiency of photosystem II (ΦPSII) and the electron transport rate (ETR) were measured under photosynthetically active radiation (PAR) of 1000 µmol m−2 s−1 and air CO2 concentration of 400 µmol mol−1. The measurements in dark-adapted leaves were taken at pre-dawn and the potential quantum efficiency of PSII was quantified. Then, measurements of leaf gas exchange and chlorophyll fluorescence in light-adapted leaves were taken between 8h00 and 10h00 AM in the same leaves evaluated at pre-dawn and under greenhouse conditions. In light-adapted state, we measured the steady-state (F’), the maximum (Fm’) and the variable (DF) chlorophyll fluorescence signals. Based on all chlorophyll fluorescence signals measured in both dark- and light-adapted states, the effective quantum efficiency of PSII (FPSII=DF/Fm’), the photochemical [qP=(Fm’-F’)/(Fm’-Fo’)] and non-photochemical [NPQ=(Fm-Fm’)/Fm’] quenching, the apparent electron transport rate [ETR = FPSII*0.5*α*PAR, in which α is light absorption and PAR is the photosynthetically active radiation] and also the excess of excitation energy at PSII [EXC=(Fv/Fm)-(FPSII)/(Fv/Fm)] [3]. The measurements were performed every two days during the experimental period. Leaf water use efficiency and instantaneous carboxylation efficiency were estimated as WUE (An/E) and k (An/Ci), respectively. Statistical analyses.

Leaf water potential and leaf gas exchange data were analyzed using Bayesian statistics and the JASP software (https://jasp-stats.org), with water regimes and genotypes as sources of variation. When significant effects of the water regimes or genotypes were detected, mean values (n = 5) were compared using Bayes Factor (BF10). Bayes Factors as evidence for the alternative hypothesis (H1) followed [25], with positive support to H1 when BF10 > 3.

Supplementary Information

12870_2025_7273_MOESM1_ESM.docx (3.2MB, docx)

Additional file 1. Figure S1. T7 Endonuclease I (T7E1) assay in rice T0 lines. Table S1. Primers used in this study. Figure S2. Relative content of chlorophyll. Figure S3. Wild-type and Osucl23knock-out rice lines. On the left, the pot contains both genotypes under control conditions (irrigated). On the right, the pot shows the genotypes under conditions of maximum water deficit (64 days old), showing the wilted leaves. Figure S4. Correlation between the leaf CO2 assimilation (An) and stomatal conductance (gs, a), effective quantum efficiency of PSII (ΦPSII, b) and carboxylation efficiency (k, c). Figure S5. Environmental variables measured in this study. Variation in air temperature (a), relative air humidity (b), and water retention in the substrate of irrigated plants (CTRL) and plants under water deficit (WD). The gray area represents the period after the rehydration of drought-treated plants. The asterisk indicates the statistical difference between water treatments, BF10 >3.

Acknowledgements

This work was supported by the São Paulo Research Foundation (FAPESP, Brazil), Fundação de Apoio à Pesquisa Agrícola (FUNDAG), and the Coordination for the Improvement of Higher Education Personnel (CAPES, Brazil) – Finance Code 001. The authors also acknowledge the fellowships granted by FAPESP (D.F.C. – Grants 2020/07045-3, 2021/13478-2, 2022/11738-0; L.M.R. – Grant 2023/04788-3), CAPES (D.F.C., and L.M.R.) and the National Council for Scientific and Technological Development (CNPq, Brazil; R.V.R – Grant 304295/2022-1).

Authors’ contributions

D.F.C., S.F.S., T.C.P., and S.C. conceived and designed the experiments. D.F.C., S.F.S., V.N.M., L.M.R., G.L., and P.M.N. conducted experiments. D.F.C., S.F.S., and V.N.M. performed data analyses. R.V.R. provided expertise in physiological analyses and contributed with data interpretation. D.F.C., S.F.S., and R.V.R. wrote the manuscript. All authors read and approved the final manuscript.

Funding

This work was supported by the São Paulo Research Foundation (FAPESP, Brazil), Fundação de Apoio à Pesquisa Agrícola (FUNDAG), and the Coordination for the Improvement of Higher Education Personnel (CAPES, Brazil) – Finance Code 001. The authors also acknowledge the fellowships granted by FAPESP (D.F.C. – Grants 2020/07045-3, 2021/13478-2, 2022/11738-0; L.M.R. – Grant 2023/04788-3), CAPES (D.F.C., and L.M.R.) and the National Council for Scientific and Technological Development (CNPq, Brazil; R.V.R – Grant 304295/2022-1).

Data availability

The datasets generated and/or analysed during the current study are available in the Genome Sequence Archive (GSA) repository, PRJCA039006.

Declarations

Ethics approval and consent to participate

Not applicable.

Consent for publication

All authors read and approved the final manuscript.

Competing interests

The authors declare no competing interests.

Footnotes

Publisher’s note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Danyel Fernandes Contiliani and Simone Ferreira da Silva contributed equally to this work and shared the first authorship.

References

  • 1.Amoah JN, Seo YW. Effect of progressive drought stress on physio-biochemical responses and gene expression patterns in wheat. 3 Biotech. 2021;11: 440. 10.1007/s13205-021-02991-6. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 2.Andersson I. Catalysis and regulation in Rubisco. J Exp Bot. 2008;59:1555–68. [DOI] [PubMed] [Google Scholar]
  • 3.Bilger W, Schreiber U, Bock M. Determination of the quantum efficiency of photosystem II and of non-photochemical quenching of chlorophyll fluorescence in the field. Oecologia. 1995;102:425–32. 10.1007/BF00341354. [DOI] [PubMed] [Google Scholar]
  • 4.Börner T, Aleynikova AY, Zubo YO, Kusnetsov VV. Chloroplast RNA polymerases: role in chloroplast biogenesis. Biochimica et Biophysica Acta (BBA). 2015;1847:761–9. 10.1016/j.bbabio.2015.02.004. [DOI] [PubMed] [Google Scholar]
  • 5.Chaves MM, Flexas J, Pinheiro C. Photosynthesis under drought and salt stress: regulation mechanisms from whole plant to cell. Ann Bot. 2009;103:551–60. 10.1093/aob/mcn125. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 6.Chen G, Hu J, Dong L, Zeng D, Guo L, Zhang G, et al. The tolerance of salinity in rice requires the presence of a functional copy of FLN2. Biomolecules. 2019;10: 17. 10.3390/biom10010017. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 7.Chen G, Lian W, Geng A, Wang Y, Liu M, Zhang Y, et al. pOsHAK1:OsSUT1 promotes sugar transport and enhances drought tolerance in rice. Int J Mol Sci. 2024;25: 2158. 10.3390/ijms25042158. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 8.Concordet J-P, Haeussler M. CRISPOR: intuitive guide selection for CRISPR/Cas9 genome editing experiments and screens. Nucleic Acids Res. 2018;46:W242-5. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 9.Contiliani DF, de Oliveira Nebó JFC, Ribeiro RV, Andrade LM, Peixoto Júnior RF, Lembke CG, et al. Leaf transcriptome profiling of contrasting sugarcane genotypes for drought tolerance under field conditions. Sci Rep. 2022;12: 9153. 10.1038/s41598-022-13158-5. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 10.de Vries J, Archibald JM. Plastid genomes. Curr Biol. 2018;28:R336–7. [DOI] [PubMed] [Google Scholar]
  • 11.Flexas J, Medrano H. Drought-inhibition of photosynthesis in C3 plants: stomatal and non‐stomatal limitations revisited. Ann Bot. 2002;89:183–9. 10.1093/aob/mcf027. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 12.González L, González-Vilar M. Determination of relative water content. in Handbook of plant ecophysiology techniques. Springer; 2001. pp. 207–12.
  • 13.He L, Zhang S, Qiu Z, Zhao J, Nie W, Lin H, et al. Fructokinase-like protein 1 interacts with TRXz to regulate chloroplast development in rice. J Integr Plant Biol. 2018;60:94–111. 10.1111/jipb.12631. [DOI] [PubMed] [Google Scholar]
  • 14.Huang C, Yu Q-B, Lv R-H, Yin Q-Q, Chen G-Y, Xu L, et al. The reduced plastid-encoded polymerase-dependent plastid gene expression leads to the delayed greening of the Arabidopsis fln2 mutant. PLoS One. 2013;8: e73092. 10.1371/journal.pone.0073092. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 15.Huang C, Yu Q-B, Yuan X-B, Li Z-R, Wang J, Ye L-S, et al. Rubisco accumulation is important for the greening of the fln2-4 mutant in Arabidopsis. Plant Sci. 2015;236:185–94. 10.1016/j.plantsci.2015.04.005. [DOI] [PubMed] [Google Scholar]
  • 16.Johnson SM, Lim F-L, Finkler A, Fromm H, Slabas AR, Knight MR. Transcriptomic analysis of Sorghum bicolor responding to combined heat and drought stress. BMC Genomics. 2014;15: 456. 10.1186/1471-2164-15-456. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 17.Khan MS, Ahmad D, Khan MA. Utilization of genes encoding osmoprotectants in transgenic plants for enhanced abiotic stress tolerance. Electron J Biotechnol. 2015;18:257–66. 10.1016/j.ejbt.2015.04.002. [Google Scholar]
  • 18.Khandaker MM, Jamaludin R, Majrashi A, Rashid ZM, Karim SMR, Al-Yasi HM, et al. Enhancing Rubisco gene expression and metabolites accumulation for better plant growth in Ficus deltoidea under drought stress using hydrogen peroxide. Front Plant Sci. 2022;13: 965765. 10.3389/fpls.2022.965765. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 19.Kovtun Y, Daie J. End-product control of carbon metabolism in culture-grown sugar beet plants (molecular and physiological evidence on accelerated leaf development and enhanced gene expression). Plant Physiol. 1995;108:1647–56. 10.1104/pp.108.4.1647. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 20.Liere K, Weihe A, Börner T. The transcription machineries of plant mitochondria and chloroplasts: composition, function, and regulation. J Plant Physiol. 2011;168:1345–60. 10.1016/j.jplph.2011.01.005. [DOI] [PubMed] [Google Scholar]
  • 21.Livak KJ, Schmittgen TD. Analysis of relative gene expression data using real-time quantitative PCR and the 2(-Delta delta C(T)) method. Methods San Diego Calif. 2001;25:402–8. 10.1006/meth.2001.1262. [DOI] [PubMed] [Google Scholar]
  • 22.Ma X, Xia H, Liu Y, Wei H, Zheng X, Song C, et al. Transcriptomic and metabolomic studies disclose key metabolism pathways contributing to well-maintained photosynthesis under the drought and the consequent drought-tolerance in rice. Front Plant Sci. 2016;7. 10.3389/fpls.2016.01886. [DOI] [PMC free article] [PubMed]
  • 23.Mae T, Makino A, Ohira K. Changes in the amounts of ribulose bisphosphate carboxylase synthesized and degraded during the life span of rice leaf (Oryza sativa L). Plant Cell Physiol. 1983;24:1079–86. [Google Scholar]
  • 24.Martins J, Neves M, Canhoto J. Drought-stress-induced changes in chloroplast gene expression in two contrasting strawberry tree (Arbutus unedo L.) genotypes. Plants. 2023;12: 4133. 10.3390/plants12244133. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 25.Miranda MT, Silva D, Silveira SF, Pereira NM, Machado L, E. C., and, Ribeiro RV. Root osmotic adjustment and stomatal control of leaf gas exchange are dependent on citrus rootstocks under water deficit. J Plant Growth Regul. 2021;40:11–9. [Google Scholar]
  • 26.Palmqvist K, Campbell D, Ekblad A, Johansson H. Photosynthetic capacity in relation to nitrogen content and its partitioning in lichens with different photobionts. Plant Cell Environ. 1998;21:361–72. [Google Scholar]
  • 27.Perdomo JA, Capó-Bauçà S, Carmo-Silva E, Galmés J. Rubisco and Rubisco activase play an important role in the biochemical limitations of photosynthesis in rice, wheat, and maize under high temperature and water deficit. Front Plant Sci. 2017; 8. 10.3389/fpls.2017.00490. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 28.Pfannschmidt T, Liere K. Redox regulation and modification of proteins controlling chloroplast gene expression. Antioxid Redox Signal. 2005;7:607–18. 10.1089/ars.2005.7.607. [DOI] [PubMed] [Google Scholar]
  • 29.Pfannschmidt T, Blanvillain R, Merendino L, Courtois F, Chevalier F, Liebers M, et al. Plastid RNA polymerases: orchestration of enzymes with different evolutionary origins controls chloroplast biogenesis during the plant life cycle. J Exp Bot. 2015;66:6957–73. [DOI] [PubMed] [Google Scholar]
  • 30.Qiu Z, Kang S, He L, Zhao J, Zhang S, Hu J, et al. The newly identified heat-stress sensitive albino 1 gene affects chloroplast development in rice. Plant Sci. 2018;267:168–79. 10.1016/j.plantsci.2017.11.015. [DOI] [PubMed] [Google Scholar]
  • 31.Raja V, Qadir SU, Alyemeni MN, Ahmad P. Impact of drought and heat stress individually and in combination on physio-biochemical parameters, antioxidant responses, and gene expression in solanum lycopersicum. 3 Biotech. 2020;10(208). 10.1007/s13205-020-02206-4. [DOI] [PMC free article] [PubMed]
  • 32.Sarruge JR. Soluções nutritivas. Summa Phytopathol. 1975;1:231–3. [Google Scholar]
  • 33.Shi W, Cheng J, Wen X, Wang J, Shi G, Yao J, et al. Transcriptomic studies reveal a key metabolic pathway contributing to a well-maintained photosynthetic system under drought stress in foxtail millet (Setaria Italica L). PeerJ. 2018;6: e4752. 10.7717/peerj.4752. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 34.Steiner S, Schröter Y, Pfalz J, Pfannschmidt T. Identification of essential subunits in the plastid-encoded RNA polymerase complex reveals building blocks for proper plastid development. Plant Physiol. 2011;157:1043–55. 10.1104/pp.111.184515. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 35.Suzuki Y, Makino A. Availability of Rubisco small subunit up-regulates the transcript levels of large subunit for stoichiometric assembly of its holoenzyme in rice. Plant Physiol. 2012;160:533–40. 10.1104/pp.112.201459. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 36.Suzuki Y, Miyamoto T, Yoshizawa R, Mae T, Makino A. Rubisco content and photosynthesis of leaves at different positions in transgenic rice with an overexpression of RBCS. Plant Cell Environ. 2009;32:417–27. 10.1111/j.1365-3040.2009.01937.x. [DOI] [PubMed] [Google Scholar]
  • 37.Toki S, Hara N, Ono K, Onodera H, Tagiri A, Oka S, et al. Early infection of scutellum tissue with Agrobacterium allows high-speed transformation of rice. Plant J. 2006;47:969–76. [DOI] [PubMed] [Google Scholar]
  • 38.Urban L, Aarrouf J, Bidel, L. P. R. Assessing the effects of water deficit on photosynthesis using parameters derived from measurements of leaf gas exchange and of chlorophyll a fluorescence. Front Plant Sci. 2017;8. 10.3389/fpls.2017.02068. [DOI] [PMC free article] [PubMed]
  • 39.Verslues PE, Agarwal M, Katiyar-Agarwal S, Zhu J, Zhu J. Methods and concepts in quantifying resistance to drought, salt and freezing, abiotic stresses that affect plant water status. Plant J. 2006;45:523–39. [DOI] [PubMed] [Google Scholar]
  • 40.Zhang Y, Zhang A, Li X, Lu C. The role of chloroplast gene expression in plant responses to environmental stress. Int J Mol Sci. 2020;21: 6082. 10.3390/ijms21176082. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 41.Zhang H, Zhu J, Gong Z, Zhu J-K. Abiotic stress responses in plants. Nat Rev Genet. 2022;23:104–19. 10.1038/s41576-021-00413-0. [DOI] [PubMed] [Google Scholar]
  • 42.Zhelyazkova P, Sharma CM, Förstner KU, Liere K, Vogel J, Börner T. The primary transcriptome of barley chloroplasts: numerous noncoding RNAs and the dominating role of the plastid-encoded RNA polymerase. Plant Cell. 2012;24:123–36. [DOI] [PMC free article] [PubMed] [Google Scholar]

Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

12870_2025_7273_MOESM1_ESM.docx (3.2MB, docx)

Additional file 1. Figure S1. T7 Endonuclease I (T7E1) assay in rice T0 lines. Table S1. Primers used in this study. Figure S2. Relative content of chlorophyll. Figure S3. Wild-type and Osucl23knock-out rice lines. On the left, the pot contains both genotypes under control conditions (irrigated). On the right, the pot shows the genotypes under conditions of maximum water deficit (64 days old), showing the wilted leaves. Figure S4. Correlation between the leaf CO2 assimilation (An) and stomatal conductance (gs, a), effective quantum efficiency of PSII (ΦPSII, b) and carboxylation efficiency (k, c). Figure S5. Environmental variables measured in this study. Variation in air temperature (a), relative air humidity (b), and water retention in the substrate of irrigated plants (CTRL) and plants under water deficit (WD). The gray area represents the period after the rehydration of drought-treated plants. The asterisk indicates the statistical difference between water treatments, BF10 >3.

Data Availability Statement

The datasets generated and/or analysed during the current study are available in the Genome Sequence Archive (GSA) repository, PRJCA039006.

Articles from BMC Plant Biology are provided here courtesy of BMC

RESOURCES