Next Article in Journal
Macrophyte-Based Assessment of Upland Rivers: Bioindicators and Biomonitors
Next Article in Special Issue
Heat-Stress-Induced Changes in Physio-Biochemical Parameters of Mustard Cultivars and Their Role in Heat Stress Tolerance at the Seedling Stage
Previous Article in Journal
Nootropic Herbs, Shrubs, and Trees as Potential Cognitive Enhancers
Previous Article in Special Issue
High-Nitrate-Supply-Induced Transcriptional Upregulation of Ascorbic Acid Biosynthetic and Recycling Pathways in Cucumber
 
 
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Article

Lipidome Profiling of Phosphorus Deficiency-Tolerant Rice Cultivars Reveals Remodeling of Membrane Lipids as a Mechanism of Low P Tolerance

1
Faculty of Agriculture, Yamagata University, Tsuruoka 997-8555, Japan
2
Yamagata Integrated Agricultural Research Center, Tsuruoka 997-7601, Japan
3
RIKEN Center for Sustainable Resource Science, Yokohama 230-0045, Japan
4
Research Faculty of Agriculture, Hokkaido University, Sapporo 060-8589, Japan
5
Graduate School of Integrated Sciences for Life, Hiroshima University, Higashi-Hiroshima 739-8521, Japan
*
Author to whom correspondence should be addressed.
Plants 2023, 12(6), 1365; https://doi.org/10.3390/plants12061365
Submission received: 9 December 2022 / Revised: 15 March 2023 / Accepted: 16 March 2023 / Published: 18 March 2023
(This article belongs to the Special Issue New Insights into Plant Resistance to Stress)

Abstract

:
Plants have evolved various mechanisms for low P tolerance, one of which is changing their membrane lipid composition by remodeling phospholipids with non-phospholipids. The objective of this study was to investigate the remodeling of membrane lipids among rice cultivars under P deficiency. Rice (Oryza sativa L.) cultivars (Akamai, Kiyonishiki, Akitakomachi, Norin No. 1, Hiyadateine, Koshihikari, and Netaro) were grown in 0 (−P) and 8 (+P) mg P L−1 solution cultures. Shoots and roots were collected 5 and 10 days after transplanting (DAT) in solution culture and subjected to lipidome profiling using liquid chromatography-mass spectrometry. Phosphatidylcholine (PC)34, PC36, phosphatidylethanolamine (PE)34, PE36, phosphatidylglycerol (PG)34, phosphatidylinositol (PI)34 were the major phospholipids and digalactosyldiacylglycerol (DGDG)34, DGDG36, 1,2-diacyl-3-O-alpha-glucuronosylglycerol (GlcADG)34, GlcADG36, monogalactosyldiacylglycerol (MGDG)34, MGDG36, sulfoquinovosyldiacylglycerol (SQDG)34 and SQDG36 were the major non-phospholipids. Phospholipids were lower in the plants that were grown under −P conditions than that in the plants that were grown under +P for all cultivars at 5 and 10 DAT. The levels of non-phospholipids were higher in −P plants than that in +P plants of all cultivars at 5 and 10 DAT. Decomposition of phospholipids in roots at 5 DAT correlated with low P tolerance. These results suggest that rice cultivars remodel membrane lipids under P deficiency, and the ability of remodeling partly contributes to low P tolerance.

1. Introduction

Phosphorus (P) is an essential nutrient for plant growth and is frequently the major limiting nutrient in soils due to its low availability. P deficiency elicits morphological and physiological changes in the root system and decreases the growth of the plant [1]. Farmers address the issue of P deficiency in soil P by the application of P fertilizer, which is produced from phosphate rock. P is a non-renewable source, and “peak-phosphorus” is expected to happen as early as around 2030 [2]. Phosphorus availability also regulates soil microbial effects on plant performance [3]. Plants have evolved several mechanisms for low P tolerance to cope with low P availability in soil, including (1) higher P acquisition efficiency (PAE) and (2) higher P utilization efficiency (PUE, Wang et al. [4]); however, improvements in PAE and PUE of crop plants are needed to secure food production.
The main mechanisms related to PAE are the expression of high-affinity P transporters, alterations of root system architecture, secretion of phosphatase and organic acids, and association with soil microbes such as mycorrhizal fungi. The main mechanisms relating to PUE include lower P concentration, optimal P distribution, internal P remobilization, lipid remodeling, and alternative P metabolic pathways.
Arabidopsis thaliana copes with P deficiency by replacing phospholipids with nonphosphorous galactolipids [5]. Oats that are grown under P-deficient conditions decrease phospholipid production and increase digalactosyldiacylglycerol (DGDG) production [6]. P-deficient plants use their phospholipids as a major source of internal P supply by replacing phospholipids in their membranes with the non-phosphorus galactolipids [7].
Lipidome profiling is the identification and quantification of all lipids in a biological material. Liquid chromatography-mass spectrometry is a useful analytical method for the separation and detection of a wide variety of plant lipids [8]. Lipid remodeling is one of the mechanisms underlying PUE in plants. The ability of lipid remodeling can differ among plant genotypes with different low P tolerances. Reuse of P from P-containing metabolites is an adaptive strategy for plants. Rice is an important crop and staple food for more than half of the world’s population and globally grown on 161 million hectares, with an average annual production of 678.7 million tons [9]. Low P availability in soil is one of the main constraints in rice production [10]. Morphological changes and physiological changes contribute to the P deficiency tolerance of rice [11,12]. However, the relationship between the remodeling ability and the low P tolerance in rice is unknown. The objectives of this study were to identify metabolic alterations in phospholipids and non-phospholipids of rice cultivars under P deficiency with lipidome profiling and to clarify the differences in the lipid replacement ability of among the rice cultivars.

2. Results

2.1. Growth of 42 Rice Cultivars in Soil Culture

Shoot dry weight of 34 cultivars out of the 42 cultivars was lower in the −P than in the +P (Table S1). Shoot dry weights of eight cultivars showed no difference between −P and +P. The shoot P concentration of 38 cultivars was lower at −P than at +P. The shoot P content of 40 cultivars was lower at −P than at +P. Low P tolerance was different among cultivars and ranged from 33% in Netaro to 76% in Akamai (Figure S1). Akamai, Hiyadateine, and Kiyonishiki were selected as the low P-tolerant cultivars due to the highest value of low P tolerance in the present study. Netaro, Koshihikari, and Norin No.1 were selected as the low P-sensitive cultivars due to the lowest value of low P tolerance in the present study and Akitakomachi were selected as the non-tolerant and non-sensitive cultivars due to the medium value of low P tolerance.

2.2. Shoot P Concentration and Shoot Dry Weight of Rice

The shoot P concentrations of all cultivars were lower in the −P plants than in the +P plants at 5 DAT and 10 DAT (Table 1). The shoot P concentration of each P treatment decreased from 5 DAT to 10 DAT, and the degree of decrease was higher in the −P treatment than in the +P treatment. The shoot P concentration of cultivars, except Kiyonishiki, was 1 mg P g−1 or less. The shoot dry weights of Akamai, Norin No. 1, and Koshihikari were lower in the −P plants than in the +P plants (Table 1). The shoot dry weight of cultivars except Kiyonishiki were lower in the −P plants than in the +P plants.

2.3. Lipid Profiles in Shoots of Seven Rice Cultivars

A total of 120 lipid species were identified in the shoots of seven rice cultivars at 5 and 10 DAT (Table S2). Phosphatidylcholine (PC)34, PC36, phosphatidylethanolamine (PE)34, PE36, phosphatidylglycerol (PG)34, and phosphatidylinositol (PI)34 were the major phospholipids and digalactosyldiacylglycerol (DGDG)34, DGDG36, 1,2-diacyl-3-O-alpha-glucuronosylglycerol (GlcADG)34, GlcADG36, monogalactosyldiacylglycerol (MGDG)34, MGDG36, sulfoquinovosyldiacylglycerol (SQDG)34, and SQDG36 were the major non-phospholipids. The levels of phosphatidylcholine (PC)34, PC36, phosphatidylethanolamine (PE)36, and phosphatidylinositol (PI)34 at 5 and 10 DAT and of phosphatidylglycerol (PG)34 at 10 DAT were lower in the −P plants than in the +P plants for the shoots of Koshihikari (Table 2, Figure 1 and Figure 2). The levels of PE36 and PI34 at 5 and 10 DAT and of PC34, PC36, PE34, and PG34 at 5 DAT were lower in the −P plants than in the +P plants for the shoot of Norin No.1. The levels of PC34, PC36, PE34, PE36, and PI34 at 5 and 10 DAT and of PG34 at 10 DAT were lower in the −P plants than in the +P plants for the shoots of Akamai. The levels of PI34 at 5 and 10 DAT and of PC34, PC36, PE34 and PE36 at 10 DAT were lower in the −P plants than in the +P plants of shoot of Hiyadateine. Levels of PC36, PE34, PE36, and PI34 at 5 and 10 DAT and of PC34 and PG34 at 10 DAT were lower in the −P plants than in the +P plants of shoot of Netaro. The levels of PC34, PC36, PE34, PE36, PG34, and PI34 were lower in the −P plants than in the +P plants of shoot of Akitakomachi. The levels of PC36 and PI34 at 5 and 10 DAT and of PC34 and PG34 at 10 DAT were lower in the −P plants than in the +P plants of shoot of Kiyonishiki.
The levels of digalactosyldiacylglycerol (DGDG)34, 1,2-diacyl-3-O-alpha-glucuronosylglycerol (GlcADG)34, GlcADG36, monogalactosyldiacylglycerol (MGDG)34, and sulfoquinovosyldiacylglycerol (SQDG)34 at 5 and 10 DAT and of DGDG36 and MGDG36 at 10 DAT were higher in the −P plants than in the +P plants for the shoots of Koshihikari (Table 2). The levels of DGDG34, GlcADG34, GlcADG36, and MGDG34 at 5 and 10 DAT and of DGDG36 and SQDG36 at 5 DAT and of SQDG34 at 10 DAT were higher in the −P plants than in +P plants for the shoots of Norin No.1. The levels of DGDG34, DGDG36, GlcADG34, GlcADG36, MGDG34, and SQDG34 at 5 and 10 DAT were higher in the −P plants than in the +P plants for the shoot of Akamai. The levels of DGDG34, DGDG36, GlcADG34, GlcADG36, SQDG34, and SQDG36 at 5 and 10 DAT and of MGDG34 and MGDG36 at 10 DAT were higher in the −P plants than in the +P plants for the shoots of Hiyadateine. The levels of DGDG34, DGDG36, GlcADG34, GlcADG36, MGDG34, MGDG36, and SQDG34 at 5 and10 DAT were higher in the −P plants than in the +P plants for the shoots of Netaro. The levels of DGDG34, DGDG36, GlcADG34, GlcADG36, MGDG34, MGDG36, and SQDG34 at 5 and 10 DAT were higher in the −P plants than in the +P plants for the shoots of Akitakomachi. The levels of DGDG34, DGDG36, GlcADG34, GlcADG36, and SQDG34 at 5 and 10 DAT and of MGDG34 and MGDG36 at 5 DAT were higher in the −P plants than in +P plants for the shoots of Kiyonishiki.

2.4. Lipid Profiles in Roots of Seven Rice Cultivars

A total of 120 lipid species were identified in the roots of seven rice cultivars at 5 and 10 DAT (Table S3). The levels of PC34, PE34, and PI34 at 5 and 10 DAT and of PG34 at 5 DAT were lower in the −P plants than in +P plants for the roots of Koshihikari (Table 3, Figure 3 and Figure 4). The levels of PC34, PE34, PE36, PG34, and PI34 at 5 and 10 DAT were lower in the −P plants than in the +P plants for the roots of Norin No.1. The levels of PC34, PC36, PE34, PE36, and PI34 at 5 and 10 DAT and of PG34 at 5 DAT were lower in the −P plant than in the +P plants for the roots of Akamai. Levels of PC36 at 5 and 10 DAT and of PC34, PE34, and PG34 at 5 DAT were lower in the −P plants than in the +P plants for the roots of Hiyadateine. The levels of PE34 and PI34 at 5 and 10 DAT and of PC34 and PE34 at 5 DAT and PG34 at 10 DAT were lower in the −P plants than in +P plants for the roots of Netaro. The levels of PC34, PE34, PE36, PG34, and PI34 at 5 and 10 DAT were lower in the −P plants than in the +P plants for the roots of Akitakomachi. The levels of PC34, PC36, PE34, PE36, PG34, and PI34 at 10 DAT were lower in the −P plants than in the +P plants for the roots of Kiyonishiki.
The levels of DGDG34, DGDG36, GlcADG34, GlcADG36, MGDG34, SQDG34, and SQDG36 at 5 and 10 DAT and of MGDG36 at 10 DAT were higher in the −P plants than in the +P plants for the roots of Koshihikari (Table 3). The levels of DGDG34, DGDG36, GlcADG34, GlcADG36, MGDG34, and SQDG36 at 5 and 10 DAT and of SQDG34 at 5 DAT and of MGDG36 at 10 DAT were higher in the −P plants than in the +P plants for the roots of Norin No.1. The levels of DGDG34, DGDG36, GlcADG34, GlcADG36, MGDG34, SQDG34, and SQDG36 at 5 and 10 DAT and of MGDG36 at 10 DAT were higher in the −P plants than in the +P plants for the roots of Akamai. The levels of DGDG34, DGDG36, GlcADG34, MGDG34, MGDG36, and SQDG34 at 5 and 10 DAT and of SQDG36 at 5 DAT and of GlcADG36 at 10 DAT were higher in the −P plants than in the +P plants for the roots of Hiyadateine. The levels of DGDG34, DGDG36, GlcADG34, GlcADG36, MGDG34, SQDG34, and SQDG36 at 5 and 10 DAT were higher in the −P plants than in the +P plants for the roots of Netaro. The levels of DGDG34, DGDG36, GlcADG34, GlcADG36, MGDG34, and SQDG36 at 5 and 10 DAT and of SQDG34 at 5 DAT were higher in the −P plants than in the +P plants for the roots of Akitakomachi. The levels of DGDG34, DGDG36, GlcADG34, GlcADG36, MGDG34, SQDG34, and SQDG36 at 5 and 10 DAT were higher in the −P plants than in the +P plants for the roots of Kiyonishiki.

3. Discussion

3.1. P Deficiency Increases Phospholipids Decomposition

The degradation of phospholipids for lipid remodeling under P deprivation has been reported in Avena sativa [6], Arabidopsis thaliana [13], Emiliania huxleyi [14], microalgae [15], Phaseolus vulgaris [16], and Proteaceae [17,18]. These experiments were carried out using one cultivar or genotype. We clarified that the low P-tolerant rice cultivar Akamai catabolizes more phosphatidylcholine, phosphatidylethanolamine, and phosphatidylgylcerol in older leaves than the low P-sensitive cultivar Koshihikari and synthesized digalactosyldiacylglycerol and monogalactosyldiacylglycerol in younger leaves [19]. However, it is not known whether this difference also occurs among different low P-tolerant cultivars. A total of seven cultivars decreased phospholipids, PI, PG, PE, and PC in the shoots and roots under P deficiency at 5 and 10 DAT (Figure 1, Figure 2, Figure 3 and Figure 4). The degree of decrease in most phospholipids in roots at 5 and 10 DAT was higher than that in the shoots at 5 and 10 DAT. Degradation of PE and PC in mature leaves of Hakea prostrata under P deficiency was higher than that in young leaves and the phosphocholine/phosphoethanolamine phosphatase gene expression in mature leaves was higher than that in young leaves [18]. Phosphatidylcholine-hydrolyzing phospholipase C of A. thaliana showed transcriptional activation upon P limitation [13]. Higher degradation of PE and PC degradation in rice roots may be related to the activities of these enzymes. The degree of decrease in the PI, PG, PE, and PC content in the shoots and roots at 10 DAT was higher than that at 5 DAT. The difference in the shoot P concentration between −P and +P was higher at 10 DAT than that at 5 DAT. Severe P deficiency at 10 DAT exacerbates the degradation of PI, PG, PE, and PC.

3.2. P Deficiency Increases Non-Phospholipid Synthesis

Accumulation of non-phospholipids for lipid remodeling under P deprivation has been observed in Avena sativa [6], Emiliania huxleyi [14], microalgae [15], Phaseolus vulgaris [16], and Proteaceae [17,18]. These experiments were also conducted with one cultivar or genotype. We clarified that the low P-tolerant rice cultivar Akamai synthesizes more non-phospholipids than the low P-sensitive cultivar Koshihikari [19]. It is also not known whether this difference occurs among different low P-tolerant cultivars. A total of seven cultivars increased non-phospholipids, GlcADG, SQDG, MGDG, and DGDG in shoots and roots under P deficiency at 5 and 10 DAT. The degrees of increase in most non-phospholipids in roots at 5 and 10 DAT was higher than those in shoots at 5 and 10 DAT. P-depleted conditions increased mol% of DGDG and SQDG in Seamum indicum and up-regulated MGDG synthase gene (SeMGD1 and SeMGD2) [20]. Upregulation of the SQDG synthase transcripts level in tomatoes and soybeans was observed [21]. The synthesis of non-phospholipid DGDG [22] and GlcADG [8] in Arabidopsis was also reported. MGDG, DGDG, and SQDG synthases may be related to the accumulation of non-phospholipids in rice. The degrees of increase in most non-phospholipids in shoots and roots at 10 DAT was higher than those at 5 DAT. Accumulation of DGDG in 4-week old shoots and roots of A. sativa was higher than that in 2-week old plants [6]. The difference in the shoot P concentration between −P and +P was higher at 10 DAT than at 5 DAT. Severe P deficiency at 10 DAT exacerbates the synthesis of GlcADG, SQDG, MGDG, and DGDG.

3.3. Relationship between Lipid Remodeling and Low P Tolerance

The degree of phospholipid decomposition in roots at 5 DAT was negatively correlated with the low P tolerance of seven rice cultivars (Figure 5, Table S4). Low P-tolerant cultivars decomposed more phospholipids than low P-sensitive cultivars. The degrees of decrease in PI, PG, PE, and PC were higher in the roots of Akamai at 5 DAT and degrees of decrease in PI, PE, and PC were higher in the shoots and roots of Akamai at 5 and 10 DAT. The ability to degrade phospholipids in Akamai may contribute to the low P tolerance of this cultivar. Orthophosphate that is produced by decomposition can be used for the synthesis of P-containing compounds such as sugar phosphate, ATP, and nucleic acids. The degrees of increase in GlcADG, SQDG, MGDG, and DGDG were similar among the seven cultivars. The degree of increase in MGDG was higher in the roots of Akamai at 10 DAT. There was no correlation between low P tolerance and the degree of phospholipid decomposition in shoots. Maintenance of membrane lipids in the roots by the remodeling is more important than that in the shoots at this growth stage when root membranes support nutrient uptake. There was no correlation between low P tolerance and degree of non-phospholipid synthesis. Verma et al. (2021) found that there was no correlation between galactolipid synthesis and physiological P use efficiency of rice genotypes [23]. Contribution of non-phospholipid synthesis to the P use efficiency may be different among the seven rice cultivars that were used in this study.

4. Materials and Methods

4.1. Screening of P-Tolerant and P-Sensitive Rice Cultivars Grown in Soil Culture

We grew 42 Japonica rice (Oryza sativa L.) cultivars in soil applied with 4.8 g P kg−1, (+P) or without (−P) phosphate fertilizer in a growth chamber (16 h light, 365 µmol m−2,s−1, at 27 °C; 8 h dark at 27 °C) for 27 days after transplanting (DAT). Subsequently, the shoot P concentration and shoot dry weight analyses were carried out on the samples that were collected 5 and 10 DAT. The low P tolerance value of cultivars was calculated by the ratio of shoot dry weight at −P/shoot dry weight at +P.

4.2. Lipidome Profiling for Seven Rice Cultivars Grown in Solution Culture

Rice cultivars Akamai, Kiyonishiki, Akitakomachi, NorinNo.1, Hiyadateine, Koshihikari, and Netaro were used. The seeds were put on sterilized perlite and covered with sterilized perlite, applied with deionized water, and kept in a growth chamber (Biotron LH-350S, NK System, Tokyo) at 27 °C (16 h light 150 µMm−2 s−1/8 h dark) for seven days. Subsequently, 10 seven-day-old seedlings were transplanted to a paper cup (90 × 140 mm) filled with 545 mL of nutrient solution. The nutrient solution contained the following essential nutrients (mg L−1) as described by Wagatsuma et al. (1988): 40 N (NH4NO3), 20 N (NaNO3), 60 K (K2SO4), 80 Ca (CaCl2), 40 Mg (MgSO4), 2 Fe (FeSO4), 1 Mn (MnSO4), 0.01 Cu (CuSO4), 0.005 Mo ((NH4) 6Mo7O24), 0.4 B (H3BO3), and 0.2 Zn (ZnCl2). P concentrations of the nutrient solutions were adjusted to 0 (−P) and 8 (+P) mg P L−1 with NaH2PO4. The pH of the solutions was adjusted daily to 5.0, using 0.1 M NaOH and 0.1 M H2SO4. Air was continuously supplied to the solutions with vinyl chloride tubes that were connected to an air pump and were replaced every two days. Each P treatment had five replications. Rice plants were grown in a growth chamber at 27 °C (16 h light 150 µMm−2s−1/8 h dark) for five and ten days.
The shoots and roots were harvested 5 DAT and 10 DAT. The whole plants were washed with tap water and deionized water. Subsamples of the shoots and the roots were separated, and fresh weights were measured. The subsamples were frozen right away at –20 °C and dried at 70 °C for three days, respectively. The frozen shoots and roots were used for lipid concentration measurement. The dried shoots were used to determine the dry weight and P concentration. The dry weights of the shoot subsamples were then measured. Ground shoot subsamples were digested using a HNO3-HClO4-H2SO4 (5:2:1) solution. The P concentration in the digested solution was determined calorimetrically using the vanadomolybdate-yellow assay.

4.3. Lipidomic Analysis

Crude lipid extracts were prepared and analyzed on a Wasters UPLC Xevo G2 Qtof MS in the positive ion mode as previously reported [21,24].

4.4. Statistical Analyses

The data were statistically analyzed using analysis of variance using the statistical software KaleidaGraph 5.0 (Synergy Software, Reading, PA, USA). Comparison of means performed using the least significant difference method at the 5% probability level where the F-value was significant.

5. Conclusions

The seven rice cultivars decomposed phospholipids PI, PG, PE, and PC and synthesized non-phospholipids GlcADG, SQDG, MGDG, and DGDG in shoots and roots under P deficiency. Degrees of decomposition of PI, PG, PE, and PC in the shoots and roots and synthesis of GlcADG, SQDG, MGDG, and DGDG in shoots and roots were different among seven rice cultivars. The degree of phospholipid decomposition in the roots was negatively correlated with the low P tolerance of seven rice cultivars. The ability of phospholipid decomposition contributes to the P use efficiency as the component of low P tolerance mechanisms of rice.

Supplementary Materials

The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/plants12061365/s1, Figure S1: Low phosphorus tolerance of rice cultivars; Table S1: Shoot dry weight, P concentration, and P content of 42 rice cultivars grown in −P and +P levels. * indicates significant (p < 0.05) difference between −P and +P level; Table S2: Lipid species that were detected in the shoots of seven cultivars under −P and +P treatment 5 and 10 days after transplanting (DAT); Table S3: Lipid species that were detected in the roots of seven cultivars under −P and +P treatment 5 and 10 days after transplanting (DAT); Table S4: Correlation coefficient between log (−P/+P) of lipid species and low P tolerance values of seven cultivars.

Author Contributions

K.T., S.H., J.W. and T.W. conceived the study. K.T., S.H., M.C., Y.O., A.O., H.M., Y.Y., T.M. and J.W. designed and performed the experiments. K.T., S.H., J.W. and T.W. prepared the manuscript. K.T., S.H., W.C., M.C., Y.O., K.S., A.O., H.M., J.W. and T.W. edited the manuscript. All authors have read and agreed to the published version of the manuscript.

Funding

This research was funded by a Grant-in-Aid for Scientific Research (Nos. 23580086 and 23380041) from the Japan Society for the Promotion of Science (JSPS), the research project “Development of mitigation and adaptation techniques to global warming in the sectors of agriculture, forestry, and fisheries” by the Ministry of Agriculture, Forestry and Fisheries (MAFF), and the Japan Advanced Plant Science Network.

Data Availability Statement

All data supporting the findings of this study are available within the paper and within its supplementary data published online.

Acknowledgments

We thank Kouji Takano (RIKEN CSRS) for the technical assistance for recording the lipidome data.

Conflicts of Interest

The authors declare that they have no conflict of interest in related to this work.

References

  1. Abel, S.; Ticconi, C.A.; Delatorre, C.A. Phosphate sensing in higher plants. Physiol. Plant. 2002, 115, 1–8. [Google Scholar] [CrossRef]
  2. Cordell, D.; Drangert, J.O.; White, S. The story of phosphorus: Global food security and food for thought. Glob. Environ. Chang. Hum. Policy Dimens. 2009, 19, 292–305. [Google Scholar] [CrossRef]
  3. Padalia, K.; Bargali, S.S.; Bargali, K.; Manral, V. Soil microbial biomass phosphorus under different land use systems of Central Himalaya. Trop. Ecol. 2022, 63, 30–48. [Google Scholar] [CrossRef]
  4. Wang, X.R.; Shen, J.B.; Liao, H. Acquisition or utilization, which is more critical for enhancing phosphorus efficiency in modern crops? Plant Sci. 2010, 179, 302–306. [Google Scholar] [CrossRef]
  5. Hartel, H.; Dormann, P.; Benning, C. DGD1-independent biosynthesis of extraplastidic galactolipids after phosphate deprivation in Arabidopsis. Proc. Natl. Acad. Sci USA 2000, 97, 10649–10654. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  6. Andersson, M.X.; Stridh, M.H.; Larsson, K.E.; Lijenberg, C.; Sandelius, A.S. Phosphate-deficient oat replaces a major portion of the plasma membrane phospholipids with the galactolipid digalactosyldiacylglycerol. FEBS Lett. 2003, 537, 128–132. [Google Scholar] [CrossRef] [Green Version]
  7. Nakamura, Y. Phosphate starvation and membrane lipid remodeling in seed plants. Prog. Lipid Res. 2013, 52, 43–50. [Google Scholar] [CrossRef]
  8. Okazaki, Y.; Kamide, Y.; Hirai, M.Y.; Saito, K. Plant lipidomics based on hydrophilic interaction chromatography coupled to ion trap time-of-flight mass spectrometry. Metabolomics 2013, 9, S121–S131. [Google Scholar] [CrossRef] [Green Version]
  9. Vibhuti; Shahi, C.; Bargali, K.; Bargali, S.S. Seed germination and seedling growth parameters of rice (Oryza sativa) varieties as affected by salt and water stress. Indian J. Agric. Sci. 2015, 85, 102–108. [Google Scholar]
  10. Fageria, N.K.; Santos, A.B.; Heinemann, A.B. Lowland Rice Genotypes Evaluation for Phosphorus Use Efficiency in Tropical Lowland. J. Plant Nutr. 2011, 34, 1087–1095. [Google Scholar] [CrossRef]
  11. Kumar, S.; Pallavi; Chugh, C.; Seem, K.; Kumar, S.; Vinod, K.K.; Mohapatra, T. Characterization of contrasting rice (Oryza sativa L.) genotypes reveals the Pi-efficient schema for phosphate starvation tolerance. BMC Plant Biol. 2021, 21, 282. [Google Scholar] [CrossRef]
  12. Kumar, S.; Agrawal, A.; Seem, K.; Kumar, S.; Vinod, K.K.; Mohapatra, T. Transcriptome analysis of a near-isogenic line and its recurrent parent reveals the role of Pup1 QTL in phosphorus deficiency tolerance of rice at tillering stage. Plant Mol. Biol. 2022, 109, 29–50. [Google Scholar] [CrossRef] [PubMed]
  13. Nakamura, Y.; Awai, K.; Masuda, T.; Yoshioka, Y.; Takamiya, K.; Ohta, H. A novel phosphatidylcholine-hydrolyzing phospholipase C induced by phosphate starvation in Arabidopsis. J. Biol. Chem. 2005, 280, 7469–7476. [Google Scholar] [CrossRef] [Green Version]
  14. Shemi, A.; Schatz, D.; Fredricks, H.F.; Van Mooy, B.A.S.; Porat, Z.; Vardi, A. Phosphorus starvation induces membrane remodeling and recycling in Emiliania huxleyi. New Phytol. 2016, 211, 886–898. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  15. Canavate, J.P.; Armada, I.; Hachero-Cruzado, I. Interspecific variability in phosphorus-induced lipid remodelling among marine eukaryotic phytoplankton. New Phytol. 2017, 213, 700–713. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  16. Russo, M.A.; Quartacci, M.F.; Izzo, R.; Belligno, A.; Navari-Izzo, F. Long- and short-term phosphate deprivation in bean roots: Plasma membrane lipid alterations and transient stimulation of phospholipases. Phytochemistry 2007, 68, 1564–1571. [Google Scholar] [CrossRef]
  17. Lambers, H.; Cawthray, G.R.; Giavalisco, P.; Kuo, J.; Laliberte, E.; Pearse, S.J.; Scheible, W.R.; Stitt, M.; Teste, F.; Turner, B.L. Proteaceae from severely phosphorus-impoverished soils extensively replace phospholipids with galactolipids and sulfolipids during leaf development to achieve a high photosynthetic phosphorus-use-efficiency. New Phytol. 2012, 196, 1098–1108. [Google Scholar] [CrossRef]
  18. Kuppusamy, T.; Giavalisco, P.; Arvidsson, S.; Sulpice, R.; Stitt, M.; Finnegan, P.M.; Scheible, W.R.; Lambers, H.; Jost, R. Lipid Biosynthesis and Protein Concentration Respond Uniquely to Phosphate Supply during Leaf Development in Highly Phosphorus-Efficient Hakea prostrata. Plant Physiol. 2014, 166, 1891–1911. [Google Scholar] [CrossRef] [Green Version]
  19. Tawaraya, K.; Honda, S.; Cheng, W.; Chuba, M.; Okazaki, Y.; Saito, K.; Oikawa, A.; Maruyama, H.; Wasaki, J.; Wagatsuma, T. Ancient rice cultivar extensively replaces phospholipids with non-phosphorus glycolipid under phosphorus deficiency. Physiol. Plant. 2018, 163, 297–305. [Google Scholar] [CrossRef] [Green Version]
  20. Shimojima, M.; Watanabe, T.; Madoka, Y.; Koizumi, R.; Yamamoto, M.P.; Masuda, K.; Yamada, K.; Masuda, S.; Ohta, H. Differential regulation of two types of monogalactosyldiacylglycerol synthase in membrane lipid remodeling under phosphate-limited conditions in sesame plants. Front. Plant Sci. 2013, 4, 469. [Google Scholar] [CrossRef] [Green Version]
  21. Okazaki, Y.; Nishizawa, T.; Takano, K.; Ohnishi, M.; Mimura, T.; Saito, K. Induced accumulation of glucuronosyldiacylglycerol in tomato and soybean under phosphorus deprivation. Physiol. Plantarum 2015, 155, 33–42. [Google Scholar] [CrossRef] [PubMed]
  22. Tjellstrom, H.; Andersson, M.X.; Larsson, K.E.; Sandelius, A.S. Membrane phospholipids as a phosphate reserve: The dynamic nature of phospholipid-to-digalactosyl diacylglycerol exchange in higher plants. Plant Cell Environ. 2008, 31, 1388–1398. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  23. Verma, L.; Kohli, P.S.; Maurya, K.; Abhijith, K.; Thakur, J.K.; Giri, J. Specific galactolipids species correlate with rice genotypic variability for phosphate utilization efficiency. Plant Physiol. Bioch. 2021, 168, 105–115. [Google Scholar] [CrossRef] [PubMed]
  24. Okazaki, Y.; Saito, K. Plant Lipidomics Using UPLC-QTOF-MS. In Plant Metabolomics: Methods and Protocols, Methods in Molecular Biology; Antonio, C., Ed.; Springer-Nature: Berlin/Heidelberg, Germany, 2018; Volume 1778, pp. 157–169. [Google Scholar]
Figure 1. Log (−P/+P) of each lipid species in the shoots of seven rice cultivars 5 days after transplanting. For each lipid species, different letters indicate significant (p < 0.05) differences among the seven cultivars.
Figure 1. Log (−P/+P) of each lipid species in the shoots of seven rice cultivars 5 days after transplanting. For each lipid species, different letters indicate significant (p < 0.05) differences among the seven cultivars.
Plants 12 01365 g001
Figure 2. Log (−P/+P) of each lipid species in the shoots of seven rice cultivars 10 days after transplanting. For each lipid species, different letters indicate significant (p < 0.05) differences among the seven cultivars.
Figure 2. Log (−P/+P) of each lipid species in the shoots of seven rice cultivars 10 days after transplanting. For each lipid species, different letters indicate significant (p < 0.05) differences among the seven cultivars.
Plants 12 01365 g002
Figure 3. Log (−P/+P) of each lipid species in the roots of seven rice cultivars 5 days after transplanting. For each lipid species, different letters indicate significant (p < 0.05) differences among the seven cultivars.
Figure 3. Log (−P/+P) of each lipid species in the roots of seven rice cultivars 5 days after transplanting. For each lipid species, different letters indicate significant (p < 0.05) differences among the seven cultivars.
Plants 12 01365 g003
Figure 4. Log (−P/+P) of each lipid species in the roots of seven rice cultivars 10 days after transplanting. For each lipid species, different letters indicate significant (p < 0.05) differences among the seven cultivars.
Figure 4. Log (−P/+P) of each lipid species in the roots of seven rice cultivars 10 days after transplanting. For each lipid species, different letters indicate significant (p < 0.05) differences among the seven cultivars.
Plants 12 01365 g004
Figure 5. Relationship between low phosphorus tolerance and log (−P/+P) of PC34 (A), PC36 (B), PE34 (C), PE36 (D), PG34 (E), and PI34 (F) in roots at 5 days after transplanting.
Figure 5. Relationship between low phosphorus tolerance and log (−P/+P) of PC34 (A), PC36 (B), PE34 (C), PE36 (D), PG34 (E), and PI34 (F) in roots at 5 days after transplanting.
Plants 12 01365 g005
Table 1. Shoot P concentration and shoot dry weight of rice cultivars that were grown in −P and +P. For each cultivar, different lowercase letters indicate significant (p < 0.05) differences between −P and +P treatment.
Table 1. Shoot P concentration and shoot dry weight of rice cultivars that were grown in −P and +P. For each cultivar, different lowercase letters indicate significant (p < 0.05) differences between −P and +P treatment.
CultivarsTreatmentShoot P ConcentrationShoot Dry Weight
  (mg P g−1)(mg plant−1)
  5 DAT10 DAT5 DAT10 DAT 
Akamai−P2.54 ± 0.10 a0.98 ± 0.04 a136.0 ± 3.0 a363.0 ± 11.0 a
 +P9.90 ± 0.11 b7.14 ± 0.37 b149.0 ± 4.0 b706.0 ± 1.0 b
Kiyonishiki−P3.63 ± 0.44 a2.19 ± 0.16 a7.7 ± 1.0 a21.5 ± 1.0 a
 +P9.75 ± 0.66 b9.07 ± 0.31 b8.4 ± 0.0 a22.4 ± 2.0 a
Akitakomachi−P2.97 ± 0.11 a0.97 ± 0.03 a7.1 ± 1.0 a17.3 ± 0.0 a
 +P10.22 ± 0.27 b6.96 ± 0.36 b7.6 ± 0.0 a30.4 ± 5.0 b
Norin No.1−P2.53 ± 0.05 a0.86 ± 0.01 a95.0 ± 3.0 a180.0 ± 3.0 a
 +P9.27 ± 0.69 b6.64 ± 0.56 b108.0 ± 3.0 b342.0 ± 26.0 b
Hiyadateine−P3.19 ± 0.20 a1.05 ± 0.02 a8.9 ± 0.0 a22.0 ± 1.0 a
 +P11.07 ± 0.34 b8.05 ± 0.12 b9.6 ± 1.0 a34.5 ± 1.0 b
Koshihikari−P2.72 ± 0.07 a1.01 ± 0.12 a72.0 ± 6.0 a147.0 ± 21.0 a
 +P8.67 ± 0.44 b6.26 ± 0.43 b74.0 ± 3.0 b263.0 ± 37.0 b
Netaro−P3.49 ± 0.15 a1.47 ± 0.03 a7.4 ± 0.0 a17.2 ± 1.0 a
 +P10.40 ± 0.21 b6.90 ± 0.20 b8.4 ± 0.0 a29.4 ± 1.0 b
Table 2. Non-phospholipid species and phospholipid species that were detected in the shoots of seven cultivars under −P and +P treatment 5 and 10 days after transplanting (DAT). For each cultivar, different letters indicate significant (p < 0.05) differences between −P and +P treatment.
Table 2. Non-phospholipid species and phospholipid species that were detected in the shoots of seven cultivars under −P and +P treatment 5 and 10 days after transplanting (DAT). For each cultivar, different letters indicate significant (p < 0.05) differences between −P and +P treatment.
Lipid SpeciesKoshihikari Norin No.1 Akamai Hiyadateine Netaro Akitakomachi Kiyonishiki
 5 DAT   10 DAT   5 DAT   10 DAT   5 DAT   10 DAT   5 DAT   10 DAT   5 DAT   10 DAT   5 DAT   10 DAT   5 DAT   10 DAT   
 −P +P −P +P −P +P −P +P −P +P −P +P −P +P     −P +P −P +P −P +P −P +P −P +P −P +P 
DGDG_345.3616 a3.1267 b10.9152 a4.4578 b7.8770 a3.2909 b11.4592 a4.9968 b8.0599 a3.1104 b9.8775 a3.9650 b4.7858 a2.3152 b8.3167 a2.5239 b7.9142 a5.0111 b9.7454 a4.8061 b9.1287 a4.6217 b11.0602 a4.6388 b8.4620 a5.0525 b13.2061 a7.5372 b
DGDG_367.6882 a6.9466 a14.3118 a9.8575 b11.5013 a8.3420 b15.2931 a11.9604 a12.4606 a8.2258 b14.1992 a9.7847 b8.8747 a6.3478 b12.2270 a6.8134 b13.5905 a12.1261 b14.7189 a12.2135 b13.9443 a11.4374 b15.1426 a10.9655 b13.1541 a11.3376 b11.9844 a8.6851 b
GlcADG_3430.4106 a0.1195 b0.6119 a0.1458 b0.5564 a0.1271 b0.6772 a0.1357 b0.5613 a0.1433 b0.8470 a0.1890 b0.4532 a0.1655 b1.1200 a0.1967 b0.6546 a0.1830 b1.0884 a0.2266 b0.8383 a0.2113 b1.3073 a0.2438 b0.4814 a0.2651 b0.9776 a0.2250 b
GlcADG_360.3994 a0.0996 b0.4446 a0.0875 b0.3504 a0.1004 b0.4431 a0.0833 b0.3832 a0.1239 b0.8106 a0.1058 b0.2251 a0.0682 b0.5165 a0.0735 b0.1581 a0.0352 b0.3907 a0.0363 b0.2387 a0.0318 b0.5218 a0.0600 b0.1269 a0.0619 b0.4416 a0.1094 b
MGDG_340.7984 a0.3207 b1.8279 a0.5317 b0.9193 a0.3167 b2.6777 a1.0501 b0.8749 a0.4065 b0.8236 a0.3392 b0.5259 a0.5583 a1.5062 a0.5691 b3.6475 a1.9410 b4.2732 a1.8870 b4.1173 a1.8295 b3.7471 a1.4233 b2.3695 a1.3675 b0.5551 a0.4065 a
MGDG_364.8094 a5.3192 a17.1815 a10.2331 b9.9968 a7.4017 a20.7257 a16.2440 a12.0847 a5.8848 a11.0500 a10.5372 a7.5537 a6.7931 a14.7230 a8.1712 b26.4800 a23.3615 b26.5992 a22.9215 b26.6611 a22.3083 b25.4037 a19.6906 b23.9469 a20.8229 b9.2537 a6.6118 a
PC_340.5774 b0.9145 a0.4843 b1.3865 a0.7501 a0.8520 a0.7709 b2.0325 b0.8634 b1.2749 a0.3161 b1.2872 a0.4471 a0.4321 a0.1639 b0.5655 a6.0609 a6.4913 a3.5015 b7.9569 a5.4276 b8.3458 a1.0718 b4.1896 a4.0372 a2.9329 a1.0390 b0.9798 a
PC_360.2180 b0.3976 a0.2160 b0.5257 a0.3044 a0.3845 a0.4035 b0.8042 b0.3718 b0.7397 a0.1287 b0.5664 a0.1030 a0.1137 a0.0387 b0.1105 a1.5022 b2.2044 a0.9587 b2.4878 a1.5039 b2.9702 a0.2502 b1.2075 a1.3627 b1.0164 a0.2420 b0.3029 a
PE_340.1676 b0.4464 a0.1009 b0.5477 a0.2082 a0.3027 a0.1196 b0.6479 b0.2310 b0.4773 a0.0513 b0.4949 a0.1750 a0.2363 a0.0422 b0.2685 a1.2859 b1.7725 a0.6035 b1.8971 a1.0610 b2.1695 a0.2222 b1.4252 a1.1224 a1.0473 a0.3200 a0.4323 a
PE_360.1618 b0.3482 a0.1173 b0.3881 a0.1738 b0.3363 a0.0894 b0.3332 b0.1863 b0.3011 a0.0500 b0.2688 a0.4523 a0.5594 a0.1598 b0.6344 a0.8896 b1.2646 a0.4723 b1.3025 a0.7694 b1.4488 a0.2905 b1.0533 a0.7349 a0.7830 a0.2323 a0.4056 a
PG_340.2863 a0.3472 a0.2789 b0.4676 a0.3386 a0.4541 a0.2954 b0.7915 b0.4993 a0.6133 a0.3333 b0.6305 a0.3214 a0.2901 a0.2099 a0.2861 a1.0031 a1.2126 a0.5228 b1.2552 a0.8392 b1.4246 a0.3211 b0.8327 a0.6302 a0.4654 a0.2533 b0.3851 a
PI_340.1212 b0.2589 a0.0463 b0.2542 a0.1292 b0.2146 a0.0486 b0.2339 b0.1647 b0.3251 a0.0129 b0.2476 a0.1363 b0.2388 a0.0154 b0.1490 a0.2511 b0.3604 a0.1053 b0.2893 a0.2096 b0.3550 a0.0545 b0.2827 a0.2796 b0.3707 a0.1006 b0.2026 a
SQDG_342.1202 a1.2953 b2.4285 a1.4403 b2.1416 a1.4351 a2.1120 a1.4000 b2.2988 a1.6146 b2.4740 a1.3576 b1.8724 a1.1112 b2.1319 a1.2299 b1.4969 a0.9251 b1.7847 a0.9928 b1.7025 a0.8827 b2.4321 a1.0891 b1.0839 a0.8188 b1.7256 a1.1263 b
SQDG_361.4513 a1.0888 a1.7041 a1.4038 a1.5798 a1.5102 b1.5247 a1.7620 a2.1438 a1.8306 a1.7439 a1.5504 a2.1151 a1.4527 b2.0272 a1.5021 b2.3732 a2.1987 a2.2388 a2.4521 a2.2513 a2.0198 a2.2181 a2.0028 a2.2257 a1.7331 a2.0217 a1.9173 a
Table 3. Non-phospholipid and phospholipid species that were detected in the roots of seven cultivars under −P and +P treatments 5 and 10 days after transplanting (DAT). For each cultivar, different letters indicate significant (p < 0.05) differences between the −P and +P treatments.
Table 3. Non-phospholipid and phospholipid species that were detected in the roots of seven cultivars under −P and +P treatments 5 and 10 days after transplanting (DAT). For each cultivar, different letters indicate significant (p < 0.05) differences between the −P and +P treatments.
Lipid SpeciesKoshihikari Norin No.1 Akamai Hiyadateine Netaro Akitakomachi Kiyonishiki −P
 5 DAT   10 DAT  5 DAT  10 DAT  5 DAT  10 DAT  5 DAT   10 DAT  5 DAT  10 DAT  5 DAT   10 DAT  5 DAT   10 DAT  
 −P +P −P +P −P +P −P +P −P +P −P +P −P +P     −P +P −P +P −P +P −P +P −P +P −P +P 
DGDG_342.5461 a0.6081 b3.7276 a1.1494 b3.2980 a0.6880 b4.0855 a0.9496 b3.5617 a0.9287 b5.0312 a0.8796 b1.1670 a0.3672 b2.2844 a0.6136 b2.5635 a0.7854 b3.3035 a0.7487 b2.8166 a0.6945 b3.1561 a0.8893 b3.7333 a1.9439 b4.2200 a1.2870 b
DGDG_360.7269 a0.2053 b1.3244 a0.3358 b0.9371 a0.2777 b1.5299 a0.3806 b1.1818 a0.3322 b2.1628 a0.3855 b0.2329 a0.1072 b0.7394 a0.1702 b0.8680 a0.3745 b1.1587 a0.4197 b0.9629 a0.3560 b1.2586 a0.4309 b1.6001 a0.8916 b1.4470 a0.4171 b
GlcADG_3430.4106 a0.1195 b0.6119 a0.1458 b0.5564 a0.1271 b0.6772 a0.1357 b0.5613 a0.1433 b0.8470 a0.1890 b0.3456 a0.1315 b0.6106 a0.1574 b0.6532 a0.2023 b0.8150 a0.2485 b0.7569 a0.1769 b0.8133 a0.2466 b0.6255 a0.3071 b0.8517 a0.2211 b
GlcADG_360.0880 a0.0204 b0.1414 a0.0272 b0.1276 a0.0216 b0.1705 a0.0268 b0.1356 a0.0276 b0.2285 a0.0386 b0.0138 a0.0076 a0.0779 a0.0111 b0.1812 a0.0250 b0.1381 a0.0303 b0.1911 a0.0181 b0.1408 a0.0249 b0.3054 a0.0667 b0.3161 a0.0360 b
MGDG_340.5489 a0.1553 b0.6651 a0.4015 b0.5732 a0.2018 b0.6701 a0.2122 b0.6598 a0.2746 b0.9403 a0.1350 b0.3639 a0.1799 b0.7719 a0.3747 b0.8789 a0.4104 b0.9220 a0.2726 b0.9975 a0.2981 b0.9070 a0.3996 b0.9165 a0.4754 b0.4695 a0.1738 b
MGDG_360.3212 a0.2969 a0.5822 a0.3555 b0.3458 a0.3945 a0.6109 a0.3572 b0.4239 a0.4713 a0.9095 a0.2774 b0.0823 a0.1240 b0.3586 a0.2272 b0.5590 a0.6593 a0.7228 a0.6979 a0.6187 a0.5673 a0.6641 a0.5624 a1.1418 a1.4052 a0.4763 a0.3417 a
PC_340.2117 b0.4913 a0.1854 b0.6143 a0.2462 b0.3686 a0.2788 b1.2806 a0.1719 b0.6580 a0.1315 b1.1979 a0.1368 b0.2985 a0.1323 a0.3055 a2.5237 b3.3479 a2.6537 a3.4487 a1.9142 b2.7873 a0.7333 b1.1837 a1.1934 a1.6091 a0.2022 b0.5490 a
PC_360.1303 a0.2518 a0.1168 a0.1324 a0.1715 a0.1984 a0.1954 a0.2847 a0.0889 b0.3044 a0.0651 b0.2963 a0.0545 b0.1299 a0.0249 b0.0227 a0.5878 a0.7231 a0.6793 a0.5593 a0.4723 a0.5195 a0.1789 a0.2214 a0.7883 a0.8056 a0.0728 b0.2472 a
PE_340.1163 b0.3740 a0.0791 b0.2730 a0.1263 b0.2325 a0.1197 b0.6153 a0.0985 b0.4898 a0.0434 b0.4934 a0.1027 b0.3089 a0.0683 a0.2074 a1.3741 b2.2589 a1.0417 b2.4083 a1.2522 b2.1380 a0.4045 b1.0958 a0.8298 a1.1042 a0.1353 b0.4246 a
PE_360.0144 a0.0313 a0.0081 a0.0167 a0.0105 b0.0257 a0.0099 b0.0499 a0.0085 b0.0632 a0.0055 b0.0570 a0.0027 b0.0159 a0.0025 b0.0021 a0.1191 b0.2708 a0.1006 a0.1557 a0.0958 b0.1888 a0.0194 b0.0528 a0.2093 a0.2604 a0.0042 b0.0662 a
PG_340.0012 b0.0031 a0.0011 a0.0047 a0.0014 b0.0029 a0.0010 b0.0091 a0.0015 b0.0094 a0.0016 a0.0096 a0.0018 a0.0068 a0.0014 b0.0145 a0.0486 a0.0764 a0.0287 b0.1277 a0.0402 b0.0848 a0.0088 b0.0350 a0.0313 a0.0418 a0.0024 b0.0103 a
PI_340.0080 b0.0250 a0.0056 b0.0359 a0.0141 b0.0286 a0.0093 b0.0550 a0.0094 b0.0487 a0.0019 b0.0824 a0.0032 b0.0120 a0.0024 a0.0069 a0.0755 b0.1454 a0.0375 b0.1668 a0.0622 b0.1268 a0.0150 b0.1060 a0.0980 a0.1744 a0.0065 b0.0319 a
SQDG_340.0345 a0.0156 b0.0577 a0.1157 b0.0434 a0.0115 b0.0584 a0.0685 a0.0483 a0.0147 b0.0741 a0.0218 b0.0225 a0.0165 a0.0450 a0.0765 a0.0651 a0.0175 b0.0927 a0.0407 b0.0681 a0.0106 b0.0833 a0.0597 a0.0708 a0.0202 b0.0791 a0.0133 b
SQDG_360.0102 a0.0031 b0.0139 a0.0041 b0.0121 a0.0044 b0.0162 a0.0061 b0.0134 a0.0067 b0.0181 a0.0053 b0.0032 a0.0014 b0.0064 a0.0024 a0.0171 a0.0068 b0.0210 a0.0055 b0.0151 a0.0058 b0.0149 a0.0062 b0.0283 a0.0095 b0.0243 a0.0054 b
Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content.

Share and Cite

MDPI and ACS Style

Honda, S.; Yamazaki, Y.; Mukada, T.; Cheng, W.; Chuba, M.; Okazaki, Y.; Saito, K.; Oikawa, A.; Maruyama, H.; Wasaki, J.; et al. Lipidome Profiling of Phosphorus Deficiency-Tolerant Rice Cultivars Reveals Remodeling of Membrane Lipids as a Mechanism of Low P Tolerance. Plants 2023, 12, 1365. https://doi.org/10.3390/plants12061365

AMA Style

Honda S, Yamazaki Y, Mukada T, Cheng W, Chuba M, Okazaki Y, Saito K, Oikawa A, Maruyama H, Wasaki J, et al. Lipidome Profiling of Phosphorus Deficiency-Tolerant Rice Cultivars Reveals Remodeling of Membrane Lipids as a Mechanism of Low P Tolerance. Plants. 2023; 12(6):1365. https://doi.org/10.3390/plants12061365

Chicago/Turabian Style

Honda, Soichiro, Yumiko Yamazaki, Takumi Mukada, Weiguo Cheng, Masaru Chuba, Yozo Okazaki, Kazuki Saito, Akira Oikawa, Hayato Maruyama, Jun Wasaki, and et al. 2023. "Lipidome Profiling of Phosphorus Deficiency-Tolerant Rice Cultivars Reveals Remodeling of Membrane Lipids as a Mechanism of Low P Tolerance" Plants 12, no. 6: 1365. https://doi.org/10.3390/plants12061365

APA Style

Honda, S., Yamazaki, Y., Mukada, T., Cheng, W., Chuba, M., Okazaki, Y., Saito, K., Oikawa, A., Maruyama, H., Wasaki, J., Wagatsuma, T., & Tawaraya, K. (2023). Lipidome Profiling of Phosphorus Deficiency-Tolerant Rice Cultivars Reveals Remodeling of Membrane Lipids as a Mechanism of Low P Tolerance. Plants, 12(6), 1365. https://doi.org/10.3390/plants12061365

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

Article Metrics

Back to TopTop