Abstract
In natural environments, fluctuating light (FL) conditions significantly influence plant growth by modulating the balance between photosynthesis and water loss through stomata, quantified as the intrinsic water use efficiency under fluctuating light (iWUEFL). This effect is particularly pronounced under drought stress (FL-DS). To elucidate the genetic basis of stomatal responses to FL-DS, we analyzed iWUEFL variations across 206 rice accessions and identified OsPIL13, a phytochrome-interacting factor, as a key gene associated with iWUEFL through genome-wide association studies. Functional validation revealed that overexpressing OsPIL13 in rice (WYG7) and its homolog in soybean (DN50) enhanced iWUEFL by 13% and 15%, respectively, under FL-DS, demonstrating its conserved role across species. Conversely, knockout of OsPIL13 or mutation of a causal SNP in its promoter reduced iWUEFL by at least 10%. Mechanistically, OsPIL13 regulates stomatal responses by repressing OsSAL1, a chloroplast retrograde signal regulator, and activating OsNHX1, a vacuolar sodium/proton antiporter. These findings highlight the potential of PIL13 in improving crop resilience to FL-DS, particularly in maize-soybean intercropping systems.
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Introduction
Water scarcity, mostly exacerbated by climate change, rapid industrialization, and urbanization, poses a critical challenge to agricultural sustainability, particularly in regions with extensive rice cultivation1. It is predicted that by 2025, ~15–20 million hectares of irrigated rice in Asia are expected to face water scarcity2. Consequently, it becomes challenging for farmers to produce more rice per unit of land, given the limited water available, to meet the increasing food demand of the growing population. The persistent need to enhance rice production per unit of land amid limited water resources underscores the urgency of developing new rice cultivars with improved water use efficiency (WUE)3.
Intrinsic WUE (iWUE) is a critical parameter in quantifying carbon uptake and water loss at leaf-to-continental scales4, reflecting the trade-off between photosynthetic carbon gain and water loss through stomatal conductance. It is defined as the ratio of photosynthetic rates (A) to stomatal conductance (gs). There are substantial genetic variations in iWUE among different species5, even within the same species, such as rice6, wheat, poplar, and cottonwood7,8,9. Earlier, iWUE has been considered a screening target for drought stress (DS) breeding in various studies7,8,10. However, their utility remains debated, as their correlation with drought tolerance is weak or inconsistent, mainly due to lack of consideration of environmental changes8. Therefore, identifying the new trait representing drought tolerance level under changing environments is essential to guide molecular selection for DS breeding11,12.
Fluctuating light (FL) is a significant environmental factor that influences iWUE through stomatal regulation, especially for the bottom leaves within a canopy9. Predominantly, FL usually occurs concomitantly with DS. The latter (DS) significantly delayed the induction kinetics of stomatal and mesophyll conductances after transitioning from low to high light conditions13. Thus, this delayed photosynthetic induction under FL further aggravated sensitive performance under DS. This evidence suggests that some common mechanisms regulate plant responses to both environmental events (FL and DS). However, the FL and DS combined stress (FL-DS) regulatory mechanism remains unclear, which needs to be deeply investigated and well interpreted.
GWAS has become a valuable tool for gene mining; however, research on the gene regulation of ecophysiological traits under combined stress using GWAS is limited14. In the current study, we aimed to explore iWUE traits with high genetic variation and heritability that could be used as a selection target for molecular-assisted breeding. In this regard, we investigated the natural variation of iWUE dynamics during FL-DS in both field and growth chamber using a Minicore rice population. The population comprises 206 accessions, known for its suitable population size and genetic diversity15 for exploring genes associated with photosynthetic and nitrogen (N) utilization traits16,17.
Through large-scale phenotyping, we found that iWUEFL possessed high SNP heritability and a strong correlation with FL-DS tolerance. Based on GWAS, we observed a strong association between the allelic variation of a phytochrome-interacting factor (OsPIL13) and iWUEFL, which mainly attributes the variation to a v3 SNP at the OsPIL13 promoter. A functional analysis suggests that overexpressing OsPIL13 increases iWUEFL by 13% during FL-DS. Importantly, the promotive effects of PIL13 in iWUEFL were also true in soybean, suggesting a conserved function of PIL13 in both species. Transcriptome analysis revealed that two genes (OsSAL1 and OsNHX1) carrying G-box binding motifs exhibited the most significantly contrasting expressions. The binding ability and transcriptional regulation by OsPIL13 upon the OsSAL1 and OsNHX1 were further confirmed by a yeast one-hybrid (Y1H) assay and chromatin immunoprecipitation (ChIP)-qPCR. This investigation sheds light on the genetic mechanisms underlying OsPIL13-regulated iWUE dynamics through coordination with OsSAL1 and OsNHX1 during FL-DS in rice. By unraveling OsPIL13 elite variation and the intricate interactions, our study provides valuable insights to guide molecular selection breeding strategies aimed at improving rice grain production and water conservation, which could also work in other species, including soybean in maize-soybean intercropping practices.
Results
iWUEFL as a crucial indicator for tolerance to FL-DS
To explore which iWUE parameters possess high heritability and correlate with tolerance to FL-DS, we investigated the natural variation of four iWUE-related traits, including iWUEIr, iWUEDr, iWUELL, and iWUEFL during FL using 206 rice accessions in a Minicore population18. The four iWUE-related traits exhibited natural variation and a normal distribution in the Minicore population (Fig. 1A; Supplementary Figs. 1A–E, 2A–E; Supplementary Data 1). Among them, a parameter representing a balance index between photosynthesis and water loss via stomata during FL (iWUEFL), exhibited the highest positive correlation with the biomass ratio in FL-DS compared to the CK condition (R = 0.72) (Supplementary Fig. 3A–E; Supplementary Data 2). In particular, ten rice accessions (five with extremely high iWUEFL and five with extremely low iWUEFL) maintained a similar iWUEFL ranking between the field and GC conditions (Fig. 1B). Consistently, accessions with low iWUEFL values exhibited severe growth impairment under FL-DS. Those accessions with high iWUEFL values displayed relatively greater FL-DS tolerance, as reflected by the biomass ratio in FL-DS compared to the CK condition (Fig. 1C, D). Importantly, iWUEFL showed a robust positive correlation between field and GC conditions (Supplementary Fig. 3F), suggesting high natural variation and low environmental plasticity of iWUEFL.
A A diagram displaying the definition of each iWUE-related trait during the FL condition. B Comparison of iWUEFL in ten rice accessions with enormously differed iWUEFL from the Minicore population grown under field and GC exposed to FL-DS. GC growth chamber. n = 4 (individual plants). C Imaging of ten rice accessions grown in a GC exposed to a 20d FL-DS. The vertical bar represents 10 cm. D Biomass ratio in ten rice accessions grown in GC with FL-DS relative to CK. Data are mean ±s.d. (n = 5 individual plants). E SNP heritability in five iWUE parameters in rice Minicore population grown under field and GC conditions. F, G Manhattan plots for iWUEFL of rice accessions grown under field and GC conditions. The overlapping genomic region surrounding the peaked SNP associated with iWUEFL between field and GC conditions was highlighted by the vertical dashed box.
The heritability (h2SNP) calculations for each iWUE parameter aimed to evaluate genetic control19. The results indicated h2SNP values > 0.26 (P < 0.05) across all iWUE parameters, with iWUEFL exhibiting the highest h2SNP value of 0.51 compared to the other three parameters under both field and GC conditions (Fig. 1E). This evidence suggests that iWUEFL has high heritability and could be considered an important parameter for reflecting FL-DS tolerance (Supplementary Note1).
Screening candidate genes responsible for the iWUEFL trait
Further explorations of candidate genes governing the iWUEFL parameter, as well as the other three iWUE parameters (iWUEIr, iWUEDr, and iWUELL), were conducted using GWAS with a low-coverage genotype dataset (Fig. 1F, G; Supplementary Fig. 4A–D; Supplementary Note 2). Several known QTLs were identified in the genomic window of overlapped SNPs that were associated with these iWUE parameters, including PsbP20, RM552121, OsCML422,23, Psb2824, and qDada1225 (Supplementary Fig. 4A–D). The Manhattan plots revealed a lead SNP (3m32427027, p value = 4.67 ×10−06) that was strongly associated with iWUEFL in the field, while a lead SNP (3m32401540, p value = 8.12 ×10−07) was strongly related to iWUEFL in GC (Fig. 2A, B). The two lead SNPs accounted for approximately 20% of the phenotypic variation (Fig. 1F, G). Notably, the two lead SNPs were located within the same linkage disequilibrium (LD) block window (32.42–32.45 Mb), where six candidate genes were identified (Fig. 2C).
Zoom-in Manhattan plots of iWUEFL for field (A) and GC (B) conditions. The SNPs in the OsPIL13 gene above the threshold of significant association were highlighted in red scatters. C List of six candidate genes that are located within the linkage disequilibrium (LD) block and their genomic positions. D Response of candidate genes, within the LD block surrounding the lead SNP, to FL-DS in two groups possessing contrasting iWUEFL values. Plants were exposed to HL for 30 min, followed by 20 min LL, for qPCR experiments. Each group has 10 rice accessions in the Minicore population. Data are mean ± s.d. (n = 3 independent replicates). Student’s t-test was used to determine the significance level of the LL response of each gene between the two iWUEFL subgroups. E OsPIL13 gene expression levels followed by HL to LL transition treatment within 10 min between A4003 and T4178. Data are mean ± s.d. (n = 3 independent replicates). F Protein expression of OsPIL13 following HL to LL transition within 10 min in leaves of WYG7. G Heatmap representing the relative gene expression of 13 orthologous genes of PIL13 in the rice genome in leaves of WYG7 exposed to either HL or LL conditions. The values for each cell are derived from three biological replicates.
To screen the candidate genes that are responsible for iWUEFL, we investigated the relative gene expression levels of these six candidate genes under 30 min of HL followed by 20 min of LL conditions (HL-LL transition treatment) using 20 rice accessions, with 10 belonging to the subgroup with an extremely high iWUEFL (high iWUEFL subgroup) and 10 belonging to the subset with an extremely low iWUEFL (low iWUEFL subgroup), and all plants were exposed to FL-DS (Supplementary Table 2). Interestingly, among the six candidate genes, only OsPIL13 gene expression showed significant differences in response to LL between the high iWUEFL and low iWUEFL groups (p < 0.01) (Fig. 2D). Consistently, the expression level of OsPIL13 in A4003, a japonica rice line from the Minicore panel with the highest iWUEFL, was dramatically enhanced up to 5 fold higher than in T4178, an indica rice type from Minicore panel with the lowest iWUEFL in Minicore population subjected to HL-LL transition treatment (Figs. 1B and 2E; Supplementary Table 2). The OsPIL13 protein contents were gradually increased following HL-LL transition treatment (Fig. 2F). These results reveal that OsPIL13 is a potential candidate gene responsible for variation in iWUEFL in the rice population.
Spatiotemporal gene expression pattern of OsPIL13
According to the Rice Genome Annotation Database, the OsPIL13 gene is annotated as a phytochrome-interacting factor (http://rice.uga.edu/). OsPIL13 is predicted to exhibit nuclear localization by RSLPred (http://www.imtech.res.in/ raghava/rslpred/), which was confirmed by the transient transformation in tobacco leaves (Supplementary Fig. 5A). Phylogenetic tree analysis revealed that OsPIL13 displays weak sequence similarities with other 13 phytochrome-interacting factor genes in the rice genome (Supplementary Fig. 5B). Remarkably, among these phytochrome-interacting factor genes, the OsPIL13 gene shows the most significant increase in its expression level following HL to LL transition treatment (Fig. 2G). The OsPIL13 gene was predominantly expressed in leaves, followed by stem and root (Supplementary Fig. 5C). The expression level of OsPIL13 was increased gradually from 5 to 60 DAG and declined at 80 DAG (Supplementary Fig. 5D). In comparison, the expression levels over five time-points within 80 DAG of OsPIL13 in A4003, with the highest iWUEFL in the Minicore population, was all higher than that in T4178, with the lowest iWUEFL in the Minicore population (Supplementary Fig. 5D). Interestingly, the expression of OsPIL13 gene was also stimulated by ABA treatment and exhibited a circadian rhythm pattern with low expression from 8:00 to 16:00, while it maintains a high expression from 20:00 to 04:00 as reported earlier in its homolog in Arabidopsis26 (Supplementary Fig. 6A, B).
OsPIL13 highly expressed under low light, particularly in the HapII subgroup
To fully resolve the DNA sequence variation in OsPIL13 that might have been missed by low-coverage genome sequencing27, we re-sequenced OsPIL13 in the Minicore population and identified 46 SNPs and 6 InDels in OsPIL13 (Supplementary Data 3; Supplementary Note 3). Through GWAS screening of these 52 variants, nine SNPs were detected that were strongly associated with the variation of iWUEFL under both field and GC conditions (P value < 1.87 × 10−6) (Supplementary Fig. 7; Supplementary Tables 3, 4). These nine SNPs of OsPIL13 are integrated in a single LD block, and among them, six SNPs were positioned in the promoter and three within the intron regions of the OsPIL13 gene (Fig. 3A; Supplementary Table 4). This evidence suggests that variation in iWUEFL could be associated with the expression levels of OsPIL13 rather than protein structure variation.
A Structure and haplotype analysis of OsPIL13. Distribution of iWUEFL in the field (B) and in GC (C) in two haplotypes of the OsPIL13 gene. The dotted lines represent the 0.25 and 0.75 quantiles, with median values indicated by bold lines. Differences between haplotypes were statistically analyzed using Student’s t test. The number of plants carrying Hap I and Hap II is shown in brackets. D Subpopulation distribution in two haplotypes of the OsPIL13 gene. E Response of OsPIL13 promoter activity to light during the switch from HL to LL within 10 min. Hap II and Hap I represent the two versions present in the OsPIL13 promoter. Protoplast was exposed to HL for 30 min, followed by 20 min of LL. F Stimulated expression of OsPIL13 by LL with different variations in the OsPIL13 promoter. Values were calculated using the ratio of luciferase activities at 5 min of LL exposure against 0 min LL for each SNP version. The symbol “v(x)ml” represents six mutation versions introduced from Hap II into Hap I of the OsPIL13 promoter. For panels (E, F), data are mean ± s.d. (n = 3 independent replicates). For panel (E), the symbols “*”, “**” and “***” were used to represent the significant differences for each time point at P < 0.05, P < 0.01, and P < 0.001, respectively, based on Student’s t test. For panel (F), different letters indicate significant differences based on one-way ANOVA followed by Tukey’s HSD tests (P < 0.05).
The nine SNPs were divided into two haplotypes, named Haplotype I (Hap I) and Haplotype II (Hap II), which comprise 42 and 164 accessions, respectively (Fig. 3A; Supplementary Table 4). Among these accessions, plants with Hap II exhibited significantly higher iWUEFL values than those in Hap I in both field and GC conditions (Fig. 3B, C). Consistently, of the ten rice accessions that were screened based on their contrasting iWUEFL values, the five with low iWUEFL values all belong to Hap I, while those with high iWUEFL values belong entirely to Hap II (Fig. 1B; Supplementary Table 2). Additionally, almost 90% of rice accessions in Hap I were of the indica-type (including IND and AUS). In contrast, nearly half of the rice accessions of Hap II were japonica type (including TEJ, TRJ, and ARO) (Fig. 3D), suggesting that the japonica subgroup preferentially carries the elite OsPIL13 haplotype (Hap II).
Furthermore, OsPIL13 promoter activity was more strongly stimulated in the Hap II promoter (amplified from A4003) than in the Hap I promoter (amplified from T4178) during the HL to LL transition within 10 min in rice protoplasts (p < 0.01) (Fig. 3E). Moreover, we assessed the effects of six SNPs at OsPIL13 promoter region during HL-LL transition through luciferase-based promoter activity approach. This was achieved by introducing different SNPs from Hap II into the Hap I promoter. The findings indicate that the third SNP (v3), positioned at −1075 bp from the start codon of the OsPIL13 gene, exhibited the lowest sensitivity to HL-LL transition treatment (Fig. 3F).
OsPIL13 gene function validation in vivo using transgenic techniques
To validate the function of the OsPIL13 gene, we created an OsPIL13 mutant (ospil13) at its third exon using CRISPR/CAS9, resulting in the loss of function of OsPIL13 in WYG7. ospil13 shows greater sensitivity to FL-DS with abolished OsPIL13 protein compared to WYG7 (Supplementary Fig. 8A, B). This led to a 26%, 20%, and 11% reduction in iWUEFL, tiller number, and yield in ospil13 compared to WYG7, respectively, after an exposure to 20 d FL-DS treatment (Supplementary Fig. 8C–E).
To further examine the v3 SNP effects on iWUEFL, we created a knocking-down line of OsPIL13 through CRISPR/CAS9, leading to the deletion of v3 SNP at the promoter, named PIL13v3m (Fig. 4A). The result reveals that, like ospil13 mutant, the performance of PIL13v3m was impaired under FL-DS, compared to WYG7, together with 55% and at least 13% reduction in OsPIL13 gene expression and iWUEFL, respectively (Fig. 4C, D). This led to a 16% increase in half-time of stomatal closure (τcl) and to 20%, 25%, 15%, and 12% reduction in A, SPAD values (chlorophyll content), tiller number, and yield, respectively, in PIL13v3m compared to WYG7 under FL-DS (Supplementary Fig. 9A–G).
A A nucleotide “G” at v3 SNP was deleted by CRISPR/CAS9 in the background of the WYG7 rice line (PIL13v3m). B Image of WYG7 and PIL13v3m at the grain filling stage. The white vertical bar represents a scale of 10 cm. C Gene expression levels of OsPIL13 in WYG7 and PIL13v3m rice line. D iWUEFL in WYG7 and PIL13v3m rice line following different days of FL-DS treatment. E Gene expression levels of OsPIL13 in WYG7 and OsPIL13 overexpression (OE) lines. F Western blot showing OsPIL13 expression in three OE lines. G Image of WYG7 and three OsPIL13-OE lines at their grain filling stage. The white vertical bar represents a scale of 10 cm. H iWUEFL in WYG7, and three OsPIL13-OE rice lines following different days of FL-DS. I, J Stomatal aperture dynamics during FL. For panel (I), the shapes of stomatal apertures were marked in red circles. Bar, 10 μm. For panels (C, D), the symbols “*,” “**,” and “***” were used to represent the significant differences between FL-DS and CK at P < 0.05, 0.01, and 0.001, respectively, based on Student’s t test. ns non-significant. Each bar data represents the mean of n replicates ±s.d.: n = 3 (independent replicates) for panel (C) and n = 7 (individual plants) for panel (D). For panels (E, H), different letters represent significant differences among three OsPIL13-OE lines and WYG7 based on one-way ANOVA followed by Tukey’s HSD tests (P < 0.05). Each bar data represents the mean of n replicates ±s.d.: n = 3 (independent replicates) for panel (E) and n = 7 (individual plants) for panel (H).
In addition, to validate the Hap II effects of OsPIL13, we generated three overexpression (OE) lines of OsPIL13 driven by its promoter from Hap II, leading to up to 3 times increase in OsPIL13 gene expression together with around 2 times increase in OsPIL13 protein levels across OE lines (Fig. 4E, F). Plants of three OsPIL13 OE lines show greater tolerance to FL-DS (Fig. 4G). Within 20d FL-DS treatment during the grain-filling stage, these OE lines exhibited at least a 13% increase in iWUEFL compared to WYG7 (Fig. 4H). This leads to a 30% reduction in τcl and to increases of 20%, 7%, 20%, and 13% in A, SPAD records, tiller number, and yield, respectively, in three OE lines compared to WYG7 under FL-DS (Supplementary Fig. 10A–G).
Consistently, the stomatal aperture in PIL13v3m shows slower closure than WYG7 during HL-LL transition treatment, which collaborates with the higher τcl compared to WYG7 (Fig. 4I, J; Supplementary Fig. 9A), and vice versa for OsPIL13 OE lines (Fig. 4I, J; Supplementary Fig. 10A), suggesting that stomatal movement during FL-DS is strongly related to the changes in iWUEFL regulated by OsPIL13.
Under CK condition, iWUEFL values show a 7% decrease (P < 0.05) in PIL13v3m and a 6% increase (P < 0.05) across three OE lines, compared to WYG7 (Supplementary Fig. 11A–C). However, no significant differences were observed in tiller numbers and yield per plant when PIL13v3m and WYG7 or the three OsPIL13-OE lines were compared to WYG7 (Supplementary Fig. 11D–G). These results further emphasize that OsPIL13 regulates iWUEFL, predominantly under FL-DS conditions.
Greater regulation of OsPIL13 on iWUEFL under FL-DS than under either FL or DS
Stomatal induction differs under combined FL-DS events compared to their single case13. To compare the effects of FL-DS with single cases (FL or DS) on iWUEFL, we treated plants using an OE line (OE1) with WYG7 in either the FL or DS condition. Results suggest that expression level of OsPIL13 was higher in FL-DS than under either FL or DS condition (Supplementary Fig. 12A). Thus, a higher expression level of OsPIL13 was observed under FL than under DS, leading to a 13% and 8% increase in iWUEFL in OE line compared to WYG7 under FL and DS, respectively (Supplementary Fig. 12A–C). We also observed a 15% and 10% decrease in τcl in OE line compared to WYG7 under FL and DS, respectively (Supplementary Fig. 12D). A higher enhancement in both tiller number and yield in OE line compared to WYG7 was observed under FL than under DS (Supplementary Fig. 12E, F). This evidence further corroborates that FL-DS significantly affects iWUEFL more than either FL or DS event.
Screening downstream regulatory genes of OsPIL13
To further elucidate the molecular mechanism of OsPIL13 underlying the iWUEFL, we resorted to transcriptome analysis. The obtained results showed that the mean clean reads for both WYG7 and PIL13v3m are 21,467,615, which maps to 92.5% of the raw reads, and the mean Q30 values are 0.94, based on the quality control of the transcriptome analysis (Supplementary Table 5; Supplementary Data 2). We identified 1,806 upregulated DEGs and 1,917 downregulated DEGs (Fig. 5B). In particular, we found that the OsSAL1 gene was highly upregulated, and the OsNHX1 gene was dramaticallly downregulated in the top 1% list of DEGs (Fig. 5B). Consistently, the increased expression of OsSAL1 and the reduced expression of OsNHX1 were measured in PIL13v3m compared to WYG7 (Fig. 5B, C), the two genes show reversed expression patterns, as observed in PIL13v3m, in the two OE lines of OsPIL13, compared to WYG7 exposed to FL-DS (Fig. 5B, C).
A Volcano plot representing differentially expressed genes (DEGs) between WYG7 and PIL13v3m under FL-DS based on transcriptome analysis. The samples were collected from WYG7 and PIL13v3m rice lines after an exposure to 20d FL-DS treatment. B, C OsSAL1, and OsNHX1 gene expression levels in WYG7, PIL13v3m, and two OsPIL13 OE rice lines under FL-DS. D, E ChIP-qPCR experiments for OsPIL13 regulating OsSAL1 gene expression in OsPIL13-OE1 rice line subjected to either 20d of FL-DS or CK using eGFP beads for affinity. F, G Luciferase activity determination for OsPIL13 transcriptionally represses the expression of OsSAL1. For panels (B, C) and (F, G), different letters represent the significant differences based on one-way ANOVA followed by Tukey’s HSD tests (P < 0.05), while for panels (D, E), the symbol “**” was used to represent the significant differences between FL-DS and CK at a P < 0.01 based on Student’s t test. ns non-significant. n = 3 (independent replicates) for panels (A–C, E, F).
ChIP-qPCR results show a dramatic fold enrichment in the promoters of both OsSAL1 and OsNHX1 binding with OsPIL13 in the OsPIL13-OE1 rice line exposed to 20d of FL-DS, compared to CK (Fig. 5D, E), which implies that OsPIL13 harbors strong affinity with OsSAL1 and OsNHX1 especially under FL-DS condition, as observed in Y1H assays (Supplementary Figs. 13, 14). Consistently, luciferase activity assay strongly suggested that OsPIL13 transcriptionally inhibits and activates the expression of the OsSAL1 and OsNHX1, respectively (Fig. 5F, G).
OsPIL13 regulates stomatal adjustment through OsSAL1 and OsNHX1
Both OsSAL1 and OsNHX1 were significantly involved in stomatal adjustment through different biological pathways. The SAL1-PAP retrograde pathway is known for interacting with ABA signaling, crucial in regulating stomatal closure and drought resistance28, while OsNHX1 represents a proton sodium exchanger responsible for stomatal dynamics during DS16. To further investigate the regulation of iWUFL by OsPIL13 through the expression of OsSAL1 and OsNHX1, we established OE rice lines for both OsSAL1 and OsNHX1 (OsSAL1-OE and OsNHX1-OE) individually driven by their native promoters, an OsSAL1 mutant (ossal1), and co-expression rice lines of OsPIL13-OsSAL1 and OsPIL13-OsNHX1.
Our findings revealed that OsSAL1-OE exhibited a significant impairment in growth under FL-DS conditions, simultaneous to a substantial increase in OsSAL1 protein levels relative to WYG7. In contrast, the ossal1 mutant displayed better growth performance compared to WYG7 under FL-DS conditions (Fig. 6A, B). Although less pronounced than in ossal1, the growth of OsPIL13-OsSAL1 was considerably better than that for both WYG7 and the OsSAL1-OE line, suggesting that OsPIL13 compensates for the OsSAL1 inhibitory effects under FL-DS conditions (Fig. 6A, B). Corresponding to their performance under FL-DS, iWUEFL contributes to a 13% reduction in OsSAL1-OE and 15% increase in ossal1. In addition, OsPIL13-OsSAL1 has similar enhanced effects with ossal1 (Fig. 6C). As a downstream metabolic substrate of OsSAL1, PAP contents were conversely corresponding to the expression of OsSAL1 in OsSAL1-OE, and ospil13 under FL-DS (Fig. 6D). This corresponds to the rapidity of stomatal closure during HL-LL transition treatment among OsSAL1-OE, ossal1, and OsPIL13-OsSAL1 (Fig. 6E; Supplementary Fig. 15A, B). In addition, tiller number and yield show corresponding changes as iWUEFL was performed in these rice lines (Fig. 6C; Supplementary Fig. 15C, D). These findings confirm the regulation of stomatal adjustment by OsPIL13 through the OsSAL1-PAP retrograde pathway.
A Images of WYG7, OE lines of OsSAL1 (OsSAL1-OE), ossal1 mutant, and co-overexpression of both OsSAL1 and OsPIL13 (OsPIL13-OsSAL1) exposed to 20d FL-DS at the graining stage. The vertical bar represents a scale of 10 cm. B Western blot showing OsSAL1 expression levels in WYG7, OsSAL1-OE, ossal1, and OsPIL13-OsSAL1. C, D iWUEFL, and PAP contents in WYG7, OsSAL1-OE, ossal1, and OsPIL13-OsSAL1. Each bar represents the mean of n replicates (n = 10, individual plants) for panel (C) and (n = 4, individual plants) for panel (D). E Stomatal aperture dynamics in WYG7, OsSAL1-OE, ossal1, and OsPIL13-SAL1 during FL treatment. The shapes of the stomatal apertures were marked in red circles. Bar, 10 μm. F Images of WYG7, OsNHX1-OE, and OsPIL13-OsNHX1 exposed to 20d FL-DS at the graining stage and images of WYG7 and OsPIL13-OsNHX1 exposed to 20d DS in the field. The vertical bar represents a scale of 10 cm. G Western blot showing OsNHX1 protein expression levels in WYG7, OsNHX1-OE, and OsPIL13-OsNHX1 under FL-DS. H–J iWUEFL, and yield per plant in WYG7, OsNHX1-OE, and OsPIL13-OsNHX1 under FL-DS. Each bar of data represents the mean of n replicates (n = 10, individual plants) for panels (H–J). I Stomatal aperture dynamics in WYG7, OsNHX1-OE, and OsPIL13-OsNHX1 under FL-DS. The shapes of the stomatal apertures were marked in red circles. Bar, 10 μm. K Summary model representing the regulation of OsPIL13 with two haplotypes on iWUEFL under FL-DS through collaborating with OsSAL1 and OsNHX1. For panels (C, D, H–J), different letters represent significant differences among groups based on one-way ANOVA followed by Tukey’s HSD test (P < 0.05).
Next, we analyzed OsPIL13, which is expected to regulate an alternative pathway of stomatal adjustment through OsNHX1. Thus, both OsNHX1-OE and OsPIL13-OsNHX1 rice lines exhibited better performance than WYG7 under FL-DS (Fig. 6F), concomitant with a gradual increase in OsNHX1 protein levels in OsNHX1-OE and OsPIL13-OsNHX1 rice lines (Fig. 6G). Compared to WYG7, iWUEFL values were increased by 11% and 19% in OsNHX1-OE and OsPIL13-OsNHX1, respectively (Fig. 6H), while decreased by 10% in osnhx1 under FL-DS (Supplementary Fig. 16A, B). Both stomatal aperture and gs dynamics data during the HL-LL transition show faster stomatal closure in OsNHX1-OE and OsPIL13-OsNHX1 (Fig. 6I; Supplementary Fig. 16C, D). PAP contents were not significantly altered in OsNHX1-OE, while it was increased dramatically in OsPIL13-OsNHX1 rice line (Supplementary Fig. 16E), confirming that cellular PAP consumption was due to OsSAL1 but not to OsNHX1. In addition, the changes of both tiller number and yield mirror the results of iWUEFL in these OsNHX1 overexpression lines (OsNHX1-OE and OsPIL13-OsNHX1) under FL-DS (Fig. 6J; Supplementary Fig. 16F).
Further exploration was performed to validate the regulation of OsSAL1 and OsNHX1 by OsPIL13 through in vivo transcriptional dynamics of these genes in response to FL-DS. As expected, results suggest that OsNHX1 displays a similar expression pattern as OsPIL13 does (Supplementary Fig. 17A). OsSAL1 shows a reversed expression pattern with OsPIL13 during FL-DS (Supplementary Fig. 17A), and the expression of OsPIL13 exhibits more rapid response than those of the two other downstream genes (OsSAL1 and OsNHX1). In addition, the expression levels of OsNHX1 and OsSAL1 were not changed in the mutants of their counterpart, while it is valid for the expression of the OsPIL13 gene in either osnhx1 or ossal1 mutants under FL-DS (Supplementary Fig. 17B–E).
Under CK condition, OsSAL1-OE, OsPIL13-OE1, and OsPIL13-OsSAL1 did not show significant differences in their performance, as well as tiller number and yield, compared to WYG7, despite iWUEFL and PAP contents being significantly higher in osal1 and OsPIL13-OsSAL1 compared to OsSAL1-OE (Supplementary Fig. 18A–E). In addition, the performances of the OsNHX1-OE and OsPIL13-OsNHX1 rice lines, as displayed by tiller number and yield, were not significantly altered in either OsNHX1 or OsPIL13-OsNHX1, compared to WYG7, although iWUEFL was increased dramatically in OsNHX1 and OsPIL13-OsNHX1, the promotive effects were less pronounced than those under FL-DS condition (Fig. 6H; Supplementary Fig. 19A–D). These findings suggest that the effectiveness of OsSAL1 and OsNHX1 regulation by OsPIL13 on iWUEFL was more pronounced under FL-DS than under CK condition.
We summarized that the FL-DS event triggered a marked increase in OsPIL13 gene expression, which in turn induces an increase in OsNHX1 expression, leading to accelerated stomatal closure and, consequently, enhanced water conservation, especially in OsPIL13 Hap II rice types (Fig. 6K). Simultaneously, OsPIL13 transcriptionally represses OsSAL1 expression, leading to the accumulation of PAP and rapid stomatal closure. These dual pathways regulated by OsPIL13, eventually promote iWUEFL during FL and enhance tolerance to FL-DS (Fig. 6K).
Local light regime shapes the haplotypic distribution of OsPIL13
Geographical and environmental gradients shape phenotypic trait variation and genetic structure in plants29. To understand the relationship between extreme FL-DS environments and OsPIL13 haplotypic distribution, we analyzed the originated climate information for each rice accession in the Minicore population. We found that local light irradiance features, including annual total solar irradiance, direct total solar irradiance, and mean yearly visibility, were significantly lower in rice accessions with Hap I compared to Hap II. In contrast, mean precipitation was considerably higher in Hap I rice accessions than in Hap II ones, although there are no significant changes in the mean annual temperature (Supplementary Fig. 20A–E).
As mentioned above, japonica rice types preferentially exist in the Hap II group of OsPIL13 (Fig. 3D). Compared to indica, it has been reported to have a higher WUE and is mainly grown in the temperate region30,31. Consistently, we found regional occurrences and distributions of the two OsPIL13 haplotypes: Hap II is found primarily in North America, Southeast Asia, and Western Europe, with a dominant regional presence in China, Japan, and United States, whereas Hap I is preferentially present in the regions that typically experience extreme DS events from Africa, South America, Southeast Asia, and the Indian subcontinent, including Mali, Egypt, Iran, Argentina, Indonesia, India, and Pakistan. These observations indicate that the haplotypic distribution of OsPIL13 is widely related to local light regimes and DS, where rice accessions were selected, and iWUEFL experiences environmental pressure for FL-DS adaptation.
Conserved function of OsPIL13 in iWUEFL in soybean
To explore the broader biological significance across diverse species, we performed multiple sequence alignment of OsPIL13 with its homologs from representative species and observed that the protein sequences of PIL13 were very conserved in its bHLH domain26 (Fig. 7A). Following FL-DS, we found that 15% increase in iWUEFL in two overexpression lines of GmPIL13 (GmPIL13-OEs), with at least 6 times increase in gene expression than its WT (DN50) (Fig. 7B, C). Accordingly, τcl shows a 15% reduction together with a 12% enhancement in biomass in two GmPIL13-OE than DN50 (Fig. 7E, F). Conversely, knocking-out GmPIL13 leads to 8% reduction in iWUEFL, a 10% increase in τcl, and a 10% reduction in biomass than DN50 under FL-DS (Fig. 7D–F).
A, Phylogenetic tree analysis on the amino acids of OsPIL13 homologs among different species. The domain architecture of OsPIL13 was annotated according to Gao et al. (2022)17. B, Performance of a CRISPR edited line (gmpil13) and two overexpression lines of GmPIL13 in soybean (Glyma.08G303900) with the background of Dongnong 50 (DN50) under FL-DS for 20 d. 15 d old soybean seedlings in growth chamber with same growth condition as performed in rice were used for FL-DS treatments. The FL-DS treatments were conducted following same protocol as performed in rice in growth chamber. CRISPR editing brings a “G” insertion at 41-bp downstream of ATG leading to premature translation termination at 25th amino acids of GmPIL13. The vertical bar represents a scale of 10 cm. C, Gene expression levels of GmPIL13 in two overexpression lines of GmPIL13. Relative expression levels were determined using GmPIL13 against Tublin (reference gene). The primer was listed in Supplementary Table 1. D-F, iWUEFL, τcl and biomass in gmpil13 and two overexpression lines of GmPIL13 exposed to FL-DS. Each bar data represents the mean of n replicates (n = 3 individual plants for panel C and n = 5 individual plants for panels D-F) ±s.d. Different letters represent the significance level for each trait among DN50, gmpil13 and two overexpression lines of GmPIL13 based on Tukey’s HSD test (P < 0.05).
In terms of CK condition, we observed a less enhancement in both growth performance in the two overexpression lines of GmPIL13 compared it to that under FL-DS condition (Fig. 7B; Supplementary Fig. 21A). The GmPIL13 gene expression levels were stimulated by less than 1.5 times in two OE lines of GmPIL13 (Supplementary Fig. 21B). Overexpressing GmPIL13 leads to around 10% increase in iWUEFL, 5% decrease in τcl and 7% increase in biomass accumulation under CK condition (Supplementary Fig. 21C–E). In contrast, knocking-out GmPIL13 shows around 10% increase in iWUEFL, 10% reduction in τcl, and 4% increase in biomass under CK condition (Supplementary Fig. 21C–E).
Discussion
FL triggers an undesirable iWUE and further aggravates sensitive performance under DS through altering stomatal movements13,32. However, the molecular mechanism underlying the genes responsible for this response remains largely unknown. In this study, we identified an iWUE-related trait, iWUEFL, strongly correlated with biomass ratio under FL-DS over CK condition, rather than biomass under either FL-DS or CK condition. We observed that a v3 SNP carrying the “G” allele from Hap II at the OsPIL13 promoter conferred the tolerance to FL-DS through enhancing iWUEFL. We demonstrated that OsPIL13 directly regulated the expression of OsSAL1 and OsNHX1 and, hence, promoted the iWUEFL during FL-DS. The new mechanism could help molecular breeding for rice to cope with such combined stress conditions.
First, performing an appropriate phenotyping approach and selecting a suitable natural population are two keys for identifying genes responsible for photosynthetic traits with high heritability used for GWAS. In this study, our phenotyping results show a robust correlation of iWUEFL between field and GC experiments (Fig. 1B; Supplementary Fig. 3F), which confirms the effectiveness of the approach of transplanting plants from the field to GC as reported earlier in rice33. Previous studies have reported many genes that regulate photosynthetic efficiency, such as NRP134, EmBP135, and PsbS36. However, very few studies have documented the photosynthetic regulatory genes using GWAS. Thus, applying GWAS on the rice Minicore population collaborating with the phenotyping screening, we discovered 20 SNPs shared across various iWUE parameters. Notably, the candidate gene RM5521 on chromosome 2 (Chr 2)21 appeared within the LD block (15.56–16.13 Mb) associated with iWUEIr and iWUE (Supplementary Fig. 4A, C). Furthermore, our investigation identified OsCML4 (29.16–30.57 Mb) on chromosome 3 (Chr 3)22,23 within the candidate genes governing iWUE, iWUELL, and iWUEFL (Supplementary Fig. 4A, D). These genes were previously reported to be related to the photosynthetic traits, suggesting a successful case of using the Minicore population for GWAS on the iWUE-related traits in our study. Therefore, the rice Minicore population was always used for GWAS on photosynthetic characteristics, as it has a proper population size and huge genetic diversity15,20,37.
We then employed GWAS using the Minicore population to identify the gene responsible for a novel trait, iWUEFL, with high SNP heritability and positive correlation to FL-DS performance. In this regard, we identified a strong association between allelic variations of OsPIL13 with iWUEFL and validated the promoted effects of OsPIL13 on iWUEFL by PIL13v3m, an OsPIL13 mutant, and three OsPIL13-OE lines under FL-DS (Fig. 4; Supplementary Figs. 8–11). OsPIL13, belonging to the phytochrome-interacting factors (PIFs) gene family, is also named OsPIL138,39. The PIFs were renowned for playing diverse roles, including internode elongation, stomatal movements, and photomorphogenic and ABA responses in plants39,40,41,42,43,44. PIFs typically accumulate in darkness, promoting skotomorphogenesis, while exposure to light triggers their rapid phosphorylation and subsequent degradation via the activity of phyB and phyA in Arabidopsis45,46. We confirmed that OsPIL13 in rice gradually accumulated following exposure to LL within 10 min, together with its gene expression levels (Fig. 2E, F). Notably, the enhanced expression of OsPIL13 induced by LL was more pronounced than that of its 12 orthologue genes in the rice genome (Fig. 2G). This evidence suggests a scenario akin to PIF1, where activated phyB interacts with OsPIL13, thus prompting its phosphorylation and degradation under light irradiation47.
Disconnection between A and gs during FL is a significant factor in the changes of iWUE, especially under FL-DS32. It has been reported that sluggish stomatal closure during the HL-LL transition could cause water loss37. In our study, we observed faster stomatal closure speed as displayed by lower values of τcl and faster decline in stomatal aperture in OsPIL13-OE lines, relative to WYG7 (Fig. 4H, J; Supplementary Fig. 10A), and vice versa for PIL13v3m (Fig. 4D, I, J; Supplementary Fig. 9A). This evidence reveals that stomatal movement and aperture regulate iWUEFL response by OsPIL13, which supports the fact that stomatal movements could be regulated by some other PIFs in rice41 and Arabidopsis42.
Previous molecular studies have elucidated the direct regulatory role of PIFs in downstream gene expression by binding to a G-box motif (CACGTG) present in their promoters, including ABI5 and CDF226,48. Based on transcriptome analysis, we identified two extreme DEGs, OsNHX1 and OsSAL1, with downregulated and upregulated levels, respectively, in the PIL13v3m (Fig. 5A–C). Our study further revealed that OsPIL13 directly binds to the G-box motif of both OsSAL1 and OsNHX1, coordinating distinct transcriptional regulation (Fig. 5D, E).
The expression of SAL1 is stimulated by light, as reported in Arabidopsis49, which is in line with our observation that OsSAL1 expression is inhibited by OsPIL13, a light repressor in rice (Figs. 2E, F and 5F). In addition, SAL1 interacts with some light signaling regulators, such as phyB49 and HY5, in Arabidopsis50. SAL1 is proposed to antagonize the light response of the hypocotyl downstream of a convergence point between phyB and other photoreceptors in Arabidopsis49. This reflects the possibility that OsPIL13 regulates the expression of OsSAL1 with downstream regulation by phyB51.
Importantly, SAL1-PAP is a typical retrograde signal produced in chloroplasts under DS, triggering the expression of nuclear-encoded stress response genes and facilitating stomatal closure28,52. SAL1-PAP pathway also integrates chloroplast retrograde, light, and hormonal signaling in Arabidopsis53. Consistent with this, we observed a dramatic degradation in PAP in OsSAL1-OE through metabolism analysis. In contrast, the PAP degradation was mitigated in an OsPIL13-OsSAL1 co-overexpression line (Fig. 6D), suggesting that OsPIL13 participates in the SAL1-PAP mediated chloroplast retrograde signaling pathway and promotes stomatal closure during FL-DS.
Constitutive high-level accumulation of PAP through knocking out SAL1 confers drought tolerance to plants, but slows down and even alters plant growth and development in Arabidopsis53 and wheat54,55. Notably, compared to less successful DS tolerance through these attempts, we attributed this to a more prominent condition, FL-DS combined stress, than single cases (Supplementary Fig. 12). We hypothesized that under FL-DS, dynamic regulation of OsPIL13 on OsSAL1 expression was essential for maintaining high iWUEFL with optimized carbon gains against stomatal conductances. PAPs, as a signal regulator for stomatal closure28, are beneficial for iWUE regulation, especially under FL-DS combined stress, as reported in the current study. Our results support the idea that appropriate stomatal closure might be a key feature to improving plant growth under FL-DS.
In addition, our investigation highlights another gene involved in stomatal closure speed, OsNHX1, observed during FL16. Importantly, OsNHX1 is recognized as a proton-sodium exchanger and has been shown to enhance drought and salt tolerance in Arabidopsis56. It could also impact stomatal kinetics during changing environments, such as osmotic stress, daily shifts, and FL, by regulating guard cell turgor and vacuolar K+ accumulation in Arabidopsis57,58. In our study, OsPIL13 could transcriptionally activate OsNHX1 gene expression (Fig. 5G). The co-overexpression rice line of OsPIL13 and OsNHX1 markedly favored plant growth under DS by hastening stomatal response speed during FL (Fig. 6F–I; Supplementary Fig. 16C, D). This observation suggests that the OsPIL13-OsNHX1 module contributes to the accumulation of K+ ions within plant cell vacuoles, thereby augmenting their osmotic potential. This process drives the water uptake, generating the requisite turgor pressure essential for cell expansion and growth under DS58.
Plants always exhibit enormous diversity in some water-conserving traits during FL14,59; these plant water-conserving traits are well adapted to their local light circumstances16,60. We compared the distribution of OsPIL13 haplotypes with local light regimes from where rice accessions were originally collected, where most japonica rice accessions preferentially exist in Hap II, representing the elite haplotype with high iWUEFL. These rice accessions were majorly derived from the regions characterized by low solar irradiance and annual visibility (Figs. 3D and Supplementary Fig. 20A–E), suggesting that the elite haplotype of the OsPIL13 gene in the japonica rice group might have undergone artificial selection targeted for high iWUEFL through stomatal closure under low light regime, rather than indica rice group. However, the negative effect of rapid stomatal closure, which increases the risk of stomatal closure limitation, is lethal and non-negligible during FL61. Notably, the selection pressure might be higher in northern areas of America, Japan, and China (Fig. 7F). Hence, the rapid stomatal responsiveness during FL might result from indirect breeding selection for better growth and yield potential under DS, similar to other species, such as sugar beet62.
Conclusion
Our results demonstrate that iWUEFL is closely related to FL-DS tolerance, with high SNP heritability. Based on GWAS, we identified the OsPIL13 gene strongly associated with the variation in iWUEFL in both field and GC conditions. Overexpressing either OsPIL13 or its homolog in soybean, GmPIL13, led to at least a 10% increase in iWUEFL. We confirmed a v3 SNP at the OsPIL13 promoter region as a candidate causal allele for regulating iWUEFL. OsPIL13 transcriptionally represses OsSAL1 and activates OsNHX1 expression by directly binding to the G-box motifs at promoters of these two genes, and hence promotes iWUEFL during FL-DS. We found that japonica rice accessions preferentially harbor the elite haplotype group of OsPIL13 (Hap II), which is always distributed in geographic regions with low light regimes. These findings provide new insights into the molecular mechanism by which OsPIL13 regulates iWUEFL, collaborating with the SAL1-PAP signaling and the NHX1 ion exchanger. Our study underscores the importance of engineering the OsPIL13 causal allele for molecular breeding aimed at improving yield under FL-DS in rice, which also offers valuable guidance for the molecular breeding of FL-DS tolerance in other species, including soybean.
Materials and methods
Materials
The Minicore rice population, comprising 206 accessions from 97 countries, was utilized in this study. The population was categorized into six subpopulations: indica (IND, 35.4%), aus (AUS, 18.7%), tropical japonica (TRJ, 18.2%), temperate japonica (TEJ, 15.2%), aromatic (ARO, 3.0%), and admixtures (Admix, 9.6%)15,63. In a superclass, japonica includes TEJ, TRJ, and ARO, while indica includes IND and AUS. The population represents a significant genetic variation and an appropriate population size, making it an ideal germplasm for identifying photosynthetic traits16.
Fluctuating light and drought stress combined treatments
To investigate the natural variation of iWUE kinetics induced by FL in combination with DS (FL-DS) in a rice population, two independent experiments were conducted under both field and growth chamber (GC) conditions. For the field experiment, the population was cultivated in a paddy field in Yazhou, Hainan, China (110.0375°E, 18.5060°N) on November 18th, 2020, using a randomized complete block design with four replications. The soil composition in field plots was maintained at around 20% sandy soil containing small particles of weathered rock, and 80% paddy soil, thus minimizing the effects of plant movement on root damage for iWUE measurements64. To minimize boundary effects, a planting scheme of 49 plants for each rice accession was implemented (7 × 7), with 15 cm spacing between plants within each row and 20 cm between rows. Standard local agronomic practices were followed for field management. To investigate the iWUE kinetics effects of FL-DS in the Minicore population, plants were carefully transferred to pots in a growth chamber (GC) at around 40 days after germination (DAG), then exposed to either FL-DS or well-watered conditions under HL as a control (CK) for 20d. Four rice seedlings of each accession were grown per pot, and two pots were used per accession, which signifies that at least four replicates were used for statistical analysis. DS treatments were applied by irrigating every 5d. Soil humidity was maintained at 25–40% and monitored using a soil moisture meter (Hansatech Instruments Ltd, UK). A FL treatment cycle of 40 min comprises of 10 min of HL (1500 μmol m−2s−1), 25 min of low light (LL, 100 μmol m−2s−1), and 5 min of HL as reported previously6. The frequency of FL was controlled by a light frequency controller (FL053C, Zhongkang Omics Corp. Ltd., China). The FL treatments were conducted each day from 6:30 am to 6:30 pm. The CK was performed to estimate the biomass ratio values of rice accessions in the Minicore population to determine the tolerance to FL-DS.
For GC experiments, rice seeds were sown for ∼10 d in a soil seed bed, then transplanted into 12 L plastic pots containing commercial peat soil (Pindstrup Substrate no. 4, Pindstrup Horticulture Ltd, Shanghai, China) and kept in outdoor conditions to ensure normal growth. Four rice seedlings of each accession were grown in each pot, with two pots used per accession. FL-DS combined treatment was applied from 40 to 60 DAG with 33/27 °C day/night temperature, a 12 h photoperiod, and 60-70% air humidity. The same FL-DS treatment protocol was followed, and the field transfer to GC approach was followed to ensure the consistency between field and GC conditions.
Kinetics of iWUE measurements during FL
To ensure stomatal adaptation, a 2 h HL treatment (1500 μmol m−2s−1 photosynthetic photon flux density, PPFD) was applied before measuring iWUE kinetics6. For iWUE kinetics measurements, four replicates were conducted simultaneously using a high-efficiency all-weather photosynthetic measurement system (HAPS)33, coupled with four portable photosynthesis systems, LICOR 6400 (Li-COR, Inc.). To minimize potential errors introduced by growth stage differences, photosynthetic parameters were measured sequentially from accession 1 to 206 for the first and third replicates, and from accession 206 to 1 for the second and fourth replicates6. Measurements were taken during FL treatment between 9:30 to 16:30. The FL measurement in the leaf cuvette followed the same light transition cycle as the GC setup, controlled by an automatic program in LICOR 6400. Several gas exchange parameters measured under high HL (1500 μmol m−2s−1 PPFD) include net A, gs, and iWUE. Fully expanded leaves were used, with CO2 concentration maintained at 400 μmol mol−1 and flow rate at 500 μmol mol s−1. Leaf cuvette humidity was maintained at ~70%.
Calculation of iWUE parameters
The iWUE dynamics during light transitions occur in distinct phases6. As the light shifts from high to low intensity (from time-point i to j), iWUE decreases sharply. From time-point j to k, the iWUE linearly increases due to the gs reduction. From time-point k to p, a slight iWUE drop occurs due to gs recovery. Upon HL resumption (from time-point p to f), iWUE increases rapidly. To quantify these transitions, five iWUE-related parameters are calculated using specific equations:
Where ΔT represents the time interval from each point during FL, iWUEIr signifies the slope of iWUE during the linear increase phase of FL (from j to k). Meanwhile, iWUEDr represents the slope of iWUE during the third stage of decreasing light (from k to p). iWUELL denotes the steady-state iWUE calculated from five peaked values during the low-light phase6. iWUEFL refers to the averaged iWUE during a FL cycle. We defined iWUEFL as a balance index between photosynthesis and water loss via stomata. MATLAB v.R2010a (Mathworks Inc., Natick, MA, USA) was used to fit stomatal closure kinetics to estimate τcl with a first-order exponential decay curve65.
Genome-wide association study
A genome-wide association study (GWAS) was performed using the genotype dataset obtained from low-coverage genome sequencing27. GEMMA software v.0.98.5, employing a mixed linear model, was used for the analysis66. A relatedness matrix and the first four principal components derived from the principal component analysis (PCA) were incorporated to account for population structure. To prevent inflation in the genome-wide association tests, a genome-wide significance level was set using 200 permutations of phenotypes to determine cut-off27. Manhattan and QQ plots for GWAS were generated using the R package qqman67. LocusZoom plots were generated using an R script sourced from GitHub (https://github.com/statgen/ locuszoom-standalone).
Haplotype analysis
Linkage disequilibrium (LD) analysis was conducted using Haploview v.4.2 to explore the genetic relatedness of candidate genes near the lead SNP. LD blocks were defined by criteria: the upper 95% confidence bounds of the r2 value surpassing 0.98 and lower bounds exceeding 0.7068. Genes within these LD blocks were considered as potential candidate genes associated with iWUE-related traits.
Estimation of trait heritability
Trait heritability (h2SNP) indicates the proportion of phenotypic variance explained by SNPs69. The h2SNP for iWUE-related parameters was estimated using GCTA v.1.11.2 beta via the Restricted Maximum Likelihood method. The P-value of SNP heritability was assessed using the Log Likelihood Test (LRT) per the GCTA software manual.
GO and KEGG analysis
An online tool AgriGO v2 (https://systemsbiology.cau.edu.cn/agriGOv2/)70 was utilized for gene ontologies (GO) annotation of candidate genes corresponding to SNPs overlapping among various iWUE parameters, referencing the UniProtKB GOA file (ftp.ebi.ac.uk/pub/databases/GO/goa). The KOBAS software (KEGG Orthology Based Annotation System, v2.0) was utilized to identify reprogrammed biochemical pathways71.
Generation of transgenic plants
To investigate the function of OsPIL13 (LOC_Os03g56950) based on GWAS, two mutants of OsPIL13 were generated: 1) to validate the biological function of v3 SNP, a locus specific mutant line of OsPIL13 (named PIL13v3m) was generated with a one-nucleotide knockout targeting a v3 SNP. 2) a knock-out mutant of OsPIL13 (ospil13) at its third exon through two nucleotides “AA” insertion, leading to an early stop codon formation at 270th amino acid. Additionally, a mutant of its regulatory gene OsSAL1 (inositol polyphosphate 1-phosphatase, LOC_Os07g37220) was generated with two nucleotides (“CT”) knockout at 17-bp after the start codon, leading to early translation termination at 55th amino acids, named ossal1. These mutant creations were accomplished using CRISPR/Cas9 technology implemented by the Biogle Company (Hangzhou, China). The single guide RNA (sgRNA) was inserted into a BGK032-DSG vector containing Cas9. This vector was introduced into an Agrobacterium tumefaciens (thereafter, A. tumefaciens) strain EHA105 and then transformed into wild-type Wuyungeng 7 (WYG7, termed WT), a modern rice cultivar belonging to Hap II. A mutant of OsNHX1 (osnhx1) was also used in the current study16. Homozygous lines from this process were sequenced based on gene-specific primers (Supplementary Table 1).
For the construction of the overexpression vector for OsPIL13, OsSAL1, and OsNHX1 (vacuolar sodium/proton antiporter, LOC_Os07g47100), their cDNA (primer sequences listed in Supplementary Table 1) was amplified from WYG7. Restriction sites (BamHI and SacI) were added, and the amplified fragments were transferred into the pCAMBIA 1301 plasmid backbone. This plasmid backbone included a GFP tag (Youbio, China, VT1842) and the hygromycin B phosphotransferase (HPT) gene driven by its native promoter from HapII (pOsPIL13HapII::OsPIL13-GFP) to generate OsPIL13-OE rice lines. The three vectors were then individually transformed into rice72 to generate overexpression lines of different genes (OE). Additionally, their native promoters were used to construct OsSAL1 and OsNHX1 overexpression lines. Co-overexpression lines of two genes, including OsPIL13-OsSAL1 and OsPIL13-OsNHX1, were obtained by crossing the OE lines of OsPIL13 with other OE lines of either OsNHX1 or OsSAL1.
Positive OE lines of three genes were detected using primers listed in Supplementary Table 1. Three homozygous OE lines with the highest expression of the OsPIL13 gene and one homozygous OE line for OsNHX1 and OsSAL1 from the T3 generation were selected for FL-DS treatment experiments. Primers for detecting the HPT expression level are provided in Supplementary Table 1.
Soybean typically experiences the FL-DS condition during maize-soybean intercropping. To investigate the biological function of OsPIL13 homolog (GmPIL13, Glyma.08G303900) in soybean, we also generated a mutant (knock-out) line and two overexpression lines of GmPIL13. The knockout construct of GmPIL13 was designed using CRISPR-Cas9 technology73. Knockout mutant was generated with a 20-bp target sequence at the first exon of GmPIL13 for a Cas9 cleavage site. Primers used for detecting mutation sites are illustrated in Supplementary Table 1. The CRISPR-Cas9 plasmid was transformed into the soybean cultivar Dongnong 50 (DN50), and the generated transgenic plants were selected using the Bar resistance marker. For the overexpression method, the ORF (open reading frame) of GmPIL13 was obtained from DN50, amplified by overlapping PCR to obtain one fragment, and then introduced into the pTF101-Gene vector (containing the bar gene for glufosinate resistance)74. The construct driven by its native promoter (pGmPIL13:GmPIL13-GFP) was then transformed into A. tumefaciens strain EHA105, and thus the transgenic lines were generated by A. tumefaciens-mediated transformation using the floral dip method with DN50 accomplished by Weimi Biotech. Company (Hainan, China), and then 1/500 10% (w/v) Basta (Ingbio, Lot: CB26213210) selection.
Stomatal aperture determinations
The stomatal aperture determination was assessed on 20d after FL-DS, where leaves were sampled during different time-points (0, 10, 20, 30, and 60 min) during FL. The top fully expanded leaves from each plant were collected and stored in formalin-acetic-alcohol (FAA) fixative solution for subsequent analysis. Stomatal observation protocols were employed25. Using a TM-1000 desktop scanning electron microscope, stomatal characteristics, including stomatal width (Wstomata) and stomatal length (Lstomata) representing the characteristic dimensions (width and length), of stomatal pores on the adaxial leaf surface, were observed and recorded.
Determination of OsPIL13 subcellular localization
To assess OsPIL13 subcellular localization, we implemented a transient transformation in tobacco leaves. A GFP fusion vector, pOsPIL13HapII::OsPIL13-GFP, was constructed using the pCAMBIA1300 backbone. The known nuclear-localized bZIP transcription factor EmBP1 was used as a positive control to validate nuclear localization35. The transformation of the construct into tobacco leaves was achieved through the agro-infiltration method75. Briefly, the GFP-protein fusion construct was transfected into A. tumefaciens strain C58C1 (WeiDi Biotech, China, AC1110). Subsequently, it was transiently expressed in the leaf epidermal cells of 5-week-old tobacco (Nicotiana benthamiana) plants through Agrobacterium-mediated leaf infiltration76. A visual observation was performed using confocal laser scanning microscopy (Zeiss LSM 700, Germany) equipped with a Fluor 10X/0.50M27 objective lens and an SP640 filter. The green fluorescence of the GFP fusion protein was excited at 488 nm, and signals were collected at 660–736 nm for chlorophyll autofluorescence and 495–515 nm for GFP.
RNA extraction and qRT-PCR analysis
The top fully expanded leaves from each plant at 40 DAG, either unexposed (CK) or exposed to 20d FL-DS, were collected for qRT-PCR analysis. Total mRNA extraction was performed using TRIzol Reagent (Invitrogen), followed by the removal of genomic DNA using DNase I treatment (Takara). The extracted RNA was reverse transcribed into cDNA using the SuperScript VILO cDNA Synthesis Kit (Invitrogen Life Technologies). We employed SYBR Green PCR Master Mix (Applied Biosystems, USA, 4309155) for qRT-PCR analysis on a Real-Time PCR System (ABI StepOnePlus, Applied Biosystems, USA). Primers for qRT-PCR were designed using Primer Prime Plus 5 Software v. 3.0 (Applied Biosystems, USA), and the Actin1 gene (LOC_Os03g50885) served as an internal reference. The relative expression of the gene against Actin1 was quantified using the 2−ΔΔCT method (ΔΔCT = CT, gene of interest−CT)77. This analysis was performed based on three biological replicates. The primers were employed to determine gene expression levels responsive to iWUEFL (Supplementary Table 1).
Transcriptome analysis
For transcriptome analysis of WYG7 and PIL13v3m leaves, RNA degradation and contamination were monitored using 1% agarose gel electrophoresis, and purity was assessed using a Nano-Photometer spectrophotometer (IMPLEN, CA, USA). The RNA Nano 6000 Assay Kit on the Agilent Bioanalyzer 2100 system (Agilent Technologies, CA, USA) was employed to evaluate RNA integrity. Subsequently, 1.5 μg of RNA per sample was used for RNA sample preparations. The NEBNext Ultra RNA Library Prep Kit for Illumina (NEB, USA) was utilized to generate sequencing libraries78. Following cluster formation, the prepared libraries were sequenced on an Illumina HiSeq 4000 platform, producing 150 bp paired-end reads.
The quality assessment of RNA-seq data was performed using FastQC software. Following generation of genome index, clean RNA-seq reads were aligned using STAR79, with the ‘—quantMode GeneCounts’ option utilized to quantify the number of reads per gene. Subsequently, gene and isoform quantification were carried out using Cufflinks v.2.2.1. Therefore, differentially expressed genes (DEGs) analysis between WYG7 and PIL13v3m under FL-DS conditions was performed using the fragment per kilobase of transcript per million mapped reads (FPKM) method to assess transcript abundance. Then, DEGs were identified employing the R package ‘DESeq2’80, with read counts obtained from STAR79 considered in the analysis. Only genes exhibiting an adjusted P-value < 0.05 were considered as DEGs. To minimize transcriptional noise, each isoform/gene was included for analysis if its FPKM values were >0.01, based on a threshold established through gene coverage saturation analysis66.
ChIP-qPCR assays
All leaves of rice seedlings (OsPIL13 OE1 transgenic plants and WYG7) grown under FL-DS conditions for 20d were used for the chromatin immunoprecipitation (ChIP) assays81. Approximately 2.5 g of leaf blades from three seedlings were harvested for each replicate to extract chromatin. In this regard, three biological replicates were conducted. After sonication, the supernatant was incubated with GFP-Trap magnetic agarose beads (Chromotek, Martinsried, Germany) at 4 °C for 1.5 h. An eGFP coding sequence was amplified from the 35S-eGFP construct to generate eGFP-pBI101.3 as a negative control. Enrichment efficiency was assessed as a percentage of IP DNA relative to input DNA. Primers used for ChIP-qPCR are also given in Supplementary Table 1.
Luciferase activity assay in rice protoplasts
To analyze the response of the OsPIL13 promoter to FL, ~2.0-kb DNA fragments upstream of the OsPIL13 coding region were amplified from T4178 and A4003 and inserted into the pGreenII 0800-LUC vector, generating pHapI-LUC and pHapII-LUC, respectively. Subsequently, six variants were generated by mutating pHapII-LUC using the Q5 site-directed mutagenesis kit (NEB, E0552S). The primer sets used for PCR amplification and mutation are detailed in Supplementary Table 1. One-month-old rice seedlings of WYG7 grown under a high light regime (~1500 μmol m−2s−1 PPFD) underwent a 24 h dark exposure before leaf sample collection for protoplast extraction. The generated vectors were individually transformed into protoplasts, then divided into two groups and exposed to either dark or high light conditions for 1 h to establish distinct light environments. All samples were incubated in cell lysis buffer (10 mM Tris-HCl, pH 8, 2 mM MgCl2) for 4–6 h at 28 °C. The activities of firefly luciferase (LUC) and Renilla luciferase (REN) were assessed using the Dual-Luciferase Reporter Assay System kit (Promega, E1960). The ratio of LUC/REN was calculated as relative activity, and the dark/HL ratio was used to characterize light response. Each vector underwent three replicates to evaluate its light responsiveness.
Yeast-one hybrid assays
Yeast one-hybrid (Y1H) assays were conducted to investigate OsPIL13 binding to the G-box motif (CACGTG) within OsNHX1 and OsSAL1 promoters (Clontech, CA, USA). The coding region of OsPIL13 was amplified and cloned into the GAL4 activation domain (GAL4 AD) of pGADT7-Rec2 (Clontech, CA, USA), forming the prey vector. Simultaneously, ~1.5-kbp segments upstream of the ATG start codon for OsSAL1 and OsNHX1, containing the G-box CACGTG-motifs, were amplified and cloned into the pAbAi vector (Clontech, CA, USA) to generate the Pro-OsSAL1-AbAi and Pro-OsNHX1-AbAi bait vectors. Additionally, mutated motifs were generated via PCR and ligated into pAbAi. These prey and bait vectors were co-transformed into the Y1H Gold yeast strain. The positively transformed yeast cell concentrations, harboring various bait-prey vector combinations, were adjusted to OD600 ≈ 1.0 and then serially diluted 1/10, 1/100, and 1/1000 in sterile ddH2O. The serial dilution of transformed yeast cells was cultured on SD/−Leu medium plates with an optimal concentration of aureobasidin A (AbA) to examine protein-DNA interactions. An empty vector containing recombinant GFP was co-transformed as a negative control.
PAP content determinations
Total adenosines were extracted using 0.1 M HCl, followed by derivatization with chloroacetaldehyde. Quantification was conducted fluorometrically after HPLC fractionation82. Quantifying 3′-phosphoadenosine 5′-phosphate (PAP) involved integrating the HPLC peak area and converting these to pmol units using standard curves calibrated with 1, 5, and 10 pmol standards.
Western blot analysis
Western blot experiments were conducted to compare the protein levels of OsPIL13 and OsSAL1 in their OE lines. Approximately 5 µg of total protein from crude leaf extracts was used, and the protein concentration was determined using the Bicinchoninic Acid (BCA) protein concentration assay kit (Beyotime, P0010). The extracts were loaded and separated on a 12% SDS–PAGE gel. Subsequently, the gel was either stained with Coomassie Brilliant Blue (CBB) or transferred to a nitrocellulose membrane for Western blot analysis83. Signals were detected using a Pierce ECL Plus Kit (Thermo Scientific, USA) and visualized with a luminescent image analyzer (Tanon-5200, Tanon). Antibodies against OsPIL13 (cat#AS163955), OsNHX1 (cat#AS09484), OsSAL1 (cat#AS07256) from Agrisera (USA) and anti-GFP (A-11122, Invitrogen) were used at a dilution of 1:10,000.
Statistics and reproducibility
Data from all biological triplicate experiments are presented with error bars as mean ± SD. Two-tailed unpaired Student’s t test was used to compare the two cohorts of data. One-way ANOVA or two-way ANOVA was performed to compare multiple cohorts of data. P-value of less than 0.05 was considered statistically significant. All statistical analyses were performed using GraphPad Prism 10.
Data availability
The GEO number of RNA sequencing raw data is GSE284707. The detailed processed data of RNA sequencing were deposited in Supplementary Data 2. Supplementary Fig. 22 lists all Western blot experiments in the manuscript in uncropped and unedited forms. All source data are included in the “Supplementary Data 1, 2” file linked to this manuscript. The data used to substantiate the findings of this study are retrievable from the author at a reasonable request.
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Acknowledgements
We are grateful to Prof. Chengcai Chu at South China Agricultural University for sharing rice population materials, and Dr. Yue Lu at Yangzhou University for helping to perform statistical analysis. We also thank Honest Biotech. Co., Ltd., Shanghai, China, for performing RNA sequencing and bioinformatic analysis. This work was supported by the National Natural Science Foundation of China (32170245; 32260447), Tianjin Science and Technology Plan Project “Research on High-efficiency Breeding Technology of New Rice Varieties with High Light Efficiency in Coastal Saline-alkali Land” (22YFZCSN00110) and Sanya Yazhou Bay Science and Technology City (SCKJ-JYRC-2022-04).
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M.Q. and G.C. planned and designed the research. Z.I., Y.L., Z.X., C.L., S.F., J.E., K.H., N.L., X.M. and Z.L. performed experiments. C.L., Z.I., Y.L., J.E., and Z.L. analyzed data. M.Q. and G.C. wrote the manuscript.
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Luo, C., Xu, Z., Iqbal, Z. et al. The phytochrome-interacting factor PIL13 enhances water use efficiency under fluctuating light and drought resilience in rice and soybean. Commun Biol 8, 1286 (2025). https://doi.org/10.1038/s42003-025-08605-8
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DOI: https://doi.org/10.1038/s42003-025-08605-8
