Iron is an essential nutrient element for plants, and it participates in plant photosynthesis, respiration, nitrogen metabolism and other important biological processes. As one of the essential mineral elements in the process of chlorophyll synthesis, most of the iron element in plants is present in the chloroplast, and only a small part is present in other organs (Dunford, 1987). In addition, iron is found in many key enzymes such as peroxidase, catalase and cytochrome oxidase. However, if iron accumulates too much in cells, it will lead to a large amount of oxygen free radicals (ROS), which will lead to toxic effects on plants (Becana et al., 1998). Excessive oxygen free radicals in cells can cause oxidative damage of proteins, lipids, nucleic acids and other biological macromolecules, leading to membrane system damage and even cell death (Blokhina et al., 2003). Therefore, maintaining iron homeostasis is of great significance to the normal growth and development of plants. Plants have formed a set of mechanisms during the evolution process to maintain iron homeostasis in the body when the soil iron concentration is low (Sperotto et al., 2012).

Under long-term flooding conditions, iron poisoning is particularly prone to occur during rice cultivation. Iron often exists in the form of low-solubility high-valent iron (Fe³⁺) in well-ventilated soils. Flooded environments can cause hypoxia and reduce Fe3+ to more soluble divalent iron (Fe²⁺) (Becker and Asch, 2005). Wetland rice represents most of the rice production in the world. Iron toxicity leads to varying degrees of reduction in rice production. The extent of the reduction depends on the genotype of cultivated rice, the intensity of iron toxicity stress, and soil fertility conditions (Sahrawat, 2004). In the long-term evolution of rice, a variety of mechanisms to tolerate iron toxic stress have been formed. The enzymes produced by the aerated tissue of the roots oxidize Fe²⁺ to Fe³⁺, and the formation of patchy deposits on the roots (Wu et al., 2014). In addition, the transporters in rice vacuoles can transport Fe²⁺ iron ions in the cytoplasm to the vacuoles. There are two related transporters in rice－OsVIT1 and OsVIT2, which play an important role in the transport of iron ions in rice vacuoles(Zhang et al., 2012). Studies have shown that tolerance to iron toxicity stress in rice is a quantitative trait, and many QTLs related to iron toxicity tolerance have been identified (Dufey et al., 2015; Matthus et al., 2015; Zhang et al., 2017). The iron toxicity tolerance based on the stem may be related to the two glutathione S-transferases located on chromosome 1 of rice, and they are induced to express under iron toxicity stress (Matthus et al., 2015). The iron toxicity tolerance mechanism of rice roots may be related to a QTL co-localized with OsIRT1, which encodes an Fe²⁺ transporter and involves in iron transport in rice (Ishimaru et al., 2006).
 

This study used bioinformatics methods (Liu et al., 2019) to mine the expression profile data of the iron-tolerant rice variety Epagri 108 and screen out differentially expressed genes under iron toxicity stress and normal control treatments, and then analysis the function of these genes.

1 Results and analysis
1.1 Screening of differentially expressed genes under iron toxicity stress vs control treatment

After using oligo, affy, and limma toolkits to compare the sample data of different treatments, a total of 407 differentially expressed genes were identified (FC>2 or FC<0.5, p<0.05). Compared with the normal control group, it was found that 330 genes were up-regulated and 77 genes were down regulated under the iron-toxin stress treatment (Figure 1).

1.2 Gene ontology analysis of differentially expressed genes under different conditions

Cluster analysis was conducted using GO analysis in the PlantGSEA database. Gene ontology analysis for differentially expressed genes was performed according to the enrichment of molecular function and biological process. After the comparing analysis of iron toxicity stress and control treatment, the enrichment results of differentially expressed genes are shown in Figure 2 and Figure 3. Through go analysis, it is helpful to better understand the gene expression of rice with iron toxicity tolerance genotypes in the process of iron toxicity stress. In this study, we found that the differentially expressed genes could be classified into 13 categories and 15 groups according to their molecular functions and biological process. The results showed that the molecular function of differentially expressed genes is mainly related to ion binding activity, oxidoreductase activity, and hydrolase activity, etc. The biological processes involved include mainly electron transport process, nitrogen metabolic process, and carbohydrate metabolic process, etc. This lays a foundation for further study of the molecular mechanism of iron tolerance in Rice.

1.3 Changes in metabolic pathways of EPAGRI 108 under iron stress

The changes in rice metabolic pathways were analyzed using the ClusterProfile toolkit. As shown in Table 1, there are significant changes in multiple metabolic pathways between rice EPAGRI 108 under iron stress and control condition. This result suggests that these metabolic pathways may be involved in iron tolerance in Rice.

2 Discussions

Iron is one of the trace elements necessary for plant nutrition, but if excessive ferrous salts accumulate in some acidic soils, it will cause toxic effects on plants. Plant iron toxic stress was first discovered in rice research, widely distributed in tropical and subtropical regions (Sahrawat, 2000). In order to maintain the iron steady state in the body and avoid the accumulation of excessive iron in the leaves, plants will accumulate iron in the roots and reduce the transfer of iron to the above-ground parts (Silveira et al., 2007). Another mechanism for plants to tolerate iron toxic stress is the oxidation of iron on the root surface (Becker and Asch, 2005), Rice can expel the iron in the root cells to the root surface, and transport oxygen from the stem to the root, so that the iron is oxidized on the root surface to form trivalent iron precipitate (Wu et al., 2014).

Rice is one of the most important ration crops in the world, and it is of great significance to study the mechanism of its tolerance to iron toxin stress. There are wide differences in the tolerance to iron toxicity between different rice resources. Under the condition of excessive iron treatment, EPAGRI 108 plants accumulate a large amount of iron in the roots, and its ability to deal with high concentrations of iron in the root cells plays an important role in protecting the plants against iron toxic stress (Stein et al., 2014).

In this article, bioinformatics method was used to mine the expression profiles chip data of rice variety EPAGRI 108 under the conditions of iron-toxic stress. After analysis, a total of 407 differentially expressed genes were identified between the two treats of materials. Compared with the control group, 330 genes are up-regulated and 77 genes are down-regulated under the iron-toxin stress treatment. In this study, we classified the differentially expressed genes according to their molecular functions and biological process. Studies have shown that a variety of enzymes play an important role in the process of plant tolerance to iron toxin stress, such as iron transporter, oxidoreductase, etc (Becker and Asch, 2005; Ishimaru et al., 2006; Zhang et al., 2012). Through analyzing the changes in the metabolic pathways of the iron toxicity stress treatment and the control group, it was found that a large number of iron binding and transport active proteins and redox active proteins were activated and expressed. In the process of responding to abiotic stress, plants often produce organic substances such as carbohydrates, amino acids and their derivatives in their bodies to maintain normal cell metabolism. In this study, multiple carbohydrate and amino acid metabolism pathways was changed under iron toxicity stress. All these results lay the foundation for further research on the molecular mechanisms related to rice response to iron toxic stress.

3 Materials and Methods
3.1 Source of material

The gene expression profiling chip data was obtained from the GEO database of NCBI, which submitted by Fett (2019). The experiment used the Affymetrix Rice Genome Array chip platform. The samples of rice EPAGRI 108 treated with iron toxicity stress and control were selected.

3.2 Data processing and screening of differentially expressed genes

Data processing was performed using oligo、affy and limma toolkits under the Bioconductor project(Gentleman et al., 2004). The expression data set was subjected to background correction and standardization using Robust Multichip Averaging method. The two groups of samples were compared using the limma package to screened the differentially expressed genes (Smyth, 2004).

3.3 Gene ontology and metabolic pathways analysis of differentially expressed genes

After identifying the differentially expressed genes between the two groups, GO enrichment analysis and metabolic pathway analysis were performed by using PlantGSEA toolkit (Yi et al., 2013). PlantGSEA is an online plant bioinformatics analysis toolkit developed by China Agricultural University. It can be used for enrichment analysis of plant gene sets to analysis Gene Ontology and signal pathways.

Authors’ contributions

Liu Weihua and Zhu Zhenhua are the executors of the experimental design and experimental research of this study. Kou Shuyan and Wu Zhigang complete the data analysis and the writing of the first draft of the paper. Cui Yongzhen participates in experimental design and analysis of experimental results. Yuan Pingrong is the creator and person in charge of the project. All authors read and approved the final manuscript.

Acknowledgements

This research was funded by the Yunnan Provincial Technological Innovation Talent Training Program(2015HB107) and Yunnan Yunling Industrial Technology Leading Talent Training Project.

References

Becana M., Moran J.F., and Iturbe-Ormaetxe I., 1998, Iron-dependent oxygen free radical generation in plants subjected to environmental stress: toxicity and antioxidant protection, Plant Soil, 201: 137-147
https://doi.org/10.1023/A:1004375732137

Becker M., and Asch F., 2005, Iron toxicity in rice-conditions and management concepts, Journal of Plant Nutrition and Soil Science, 168(4): 558-573
https://doi.org/10.1002/jpln.200520504

Blokhina O., Virolainen E., and Fagerstedt K.V., 2003, Antioxidants, oxidative damage and oxygen deprivation stress: a review, Ann. Bot., 91(2): 179-194
https://doi.org/10.1093/aob/mcf118
PMid:12509339 PMCid:PMC4244988

Dufey I., Mathieu A.S., Draye X., Lutts S., and Bertin P., 2015, Construction of an integrated map through comparative studies allows the identification of candidate regions for resistance to ferrous iron toxicity in rice, Euphytica, 203(1): 59-69
https://doi.org/10.1007/s10681-014-1255-5

Dunford H.B., 1987, Free radicals in iron-containing systems, Free Radic. Biol. Med., 3(6): 405-421
https://doi.org/10.1016/0891-5849(87)90019-0

Gentleman R.C., Carey V.J., Bates D.M., Bolstad B., Dettling M., Dudoit S., Ellis B., Gautier L., Ge Y., Gentry J., Hornik K., Hothorn T., Huber W., Iacus S., Irizarry R., Leisch F., Li C., Maechler M., Rossini A.J., Sawitzki G., Smith C., Smyth G., Tierney L., Yang J.Y., and Zhang J., 2004, Bioconductor: open software development for computational biology and bioinformatics, Genome Biol., 5(10): R80
https://doi.org/10.1186/gb-2004-5-10-r80
PMid:15461798 PMCid:PMC545600

Ishimaru Y., Suzuki M., Tsukamoto T., Suzuki K., Nakazono M., Kobayashi T., Wada Y., Watanabe S., Matsuhashi S., and Takahashi M., 2006, Rice plants take up iron as an Fe³⁺-phytosiderophore and as Fe²⁺, Plant J., 45: 335
https://doi.org/10.1111/j.1365-313X.2005.02624.x
PMid:16412081

Matthus E., Wu L.B., Ueda Y., Holler S., Becker M., and Frei M., 2015, Loci genes and mechanisms associated with tolerance to ferrous iron toxicity in rice (Oryza sativa L.), Theor. Appl. Genet., 128(10): 2085-2098
https://doi.org/10.1007/s00122-015-2569-y
PMid:26152574

Sahrawat K.L, 2000, Elemental composition of the rice plant as affected by iron toxicity under field conditions, Commun. Soil Sci. Plant, 31(7-8): 2819-2827
https://doi.org/10.1080/00103620009370630

Sahrawat L.K., 2004, Iron toxicity in wetland rice and the role of other nutrients, J. Plant Nutrition, 27(8): 1471-1504
https://doi.org/10.1081/PLN-200025869

Silveira V.C.D., Oliveira A.P.D., Sperotto R.A., Espindola L.S., Amaral L., Dias J.F., Cunha J.O.B.D., and Fett J.P., 2007, Influence of iron on mineral status of two rice (Oryza sativa L.) cultivars, Braz. J. Plant Physiol., 19(2): 127-139
https://doi.org/10.1590/S1677-04202007000200005

Smyth G.K., 2004, Linear models and empirical bayes methods for assessing differential expression in microarray experiments, Stat. Appl. Genet. Mol. Biol., DOI: 10.2202/1544-6115. 1027
https://doi.org/10.2202/1544-6115.1027
PMid:16646809

Sperotto R.A., Ricachenevsky F.K., Waldow Vde A., and Fett J.P., 2012, Iron biofortification in rice: it's a long way to the top, Plant Sci., 190: 24-39
https://doi.org/10.1016/j.plantsci.2012.03.004
PMid:22608517

Stein R.J., Lopes S.I.G., and Fett J.P., 2014, Iron toxicity in field-cultivated rice: contrasting tolerance mechanisms in distinct cultivars, Theor. Exp. Plant Physiol., 26(2): 135-146
https://doi.org/10.1007/s40626-014-0013-3

Wu L.B., Shhadi M.Y., Gregorio G., Matthus E., Becker M., and Frei M., 2014, Genetic and physiological analysis of tolerance to acute iron toxicity in rice, Rice, 7(1): 8
https://doi.org/10.1186/s12284-014-0008-3
PMid:24920973 PMCid:PMC4052628

Yi X., Du Z., and Su Z., 2013, PlantGSEA: a gene set enrichment analysis toolkit for plant community, Nucleic Acids Res., 41(W): 98-103
https://doi.org/10.1093/nar/gkt281
PMid:23632162 PMCid:PMC3692080

Zhang J., Chen K., Pang Y., Naveed S.A., Zhao X., Wang X., Wang Y., Dingkuhn M., Pasuquin J., Li Z., and Xu J., 2017, QTL mapping and candidate gene analysis of ferrous iron and zinc toxicity tolerance at seedling stage in rice by genome-wide association study, BMC Genomics, 18: 828
https://doi.org/10.1186/s12864-017-4221-5
PMid:29078746 PMCid:PMC5658907

Zhang Y., Xu Y.H., Yi H.Y., and Gong J.M., 2012, Vacuolar membrane transporters OsVIT1 and OsVIT2 modulate iron translocation between flag leaves and seeds in rice, Plant Journal for Cell and Molecular Biology, 72: 400-410
https://doi.org/10.1111/j.1365-313X.2012.05088.x
PMid:22731699