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Assessment of DNA methylation pattern under drought stress using methylation-sensitive randomly amplified polymorphism analysis in rice

Published online by Cambridge University Press:  24 August 2020

Harihar Sapna Open the ORCID record for Harihar Sapna [Opens in a new window] ,
Narasimha Ashwini ,
Sampangiramareddy Ramesh Open the ORCID record for Sampangiramareddy Ramesh [Opens in a new window]  and
Karaba N. Nataraja
Harihar Sapna
Affiliation:
Department of Crop Physiology, University of Agricultural Sciences, Gandhi Krishi Vigyan Kendra, Bengaluru560065, India
Narasimha Ashwini
Affiliation:
Department of Crop Physiology, University of Agricultural Sciences, Gandhi Krishi Vigyan Kendra, Bengaluru560065, India
Sampangiramareddy Ramesh
Affiliation:
Department of Genetics and Plant Breeding, University of Agricultural Sciences, Gandhi Krishi Vigyan Kendra, Bengaluru560065, India
Karaba N. Nataraja*
Affiliation:
Department of Crop Physiology, University of Agricultural Sciences, Gandhi Krishi Vigyan Kendra, Bengaluru560065, India
*
*Corresponding author. E-mail: [email protected]
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Abstract

DNA methylation is known to regulate gene expression when plants are exposed to abiotic stress such as drought. Therefore, insight into DNA methylation pattern would be useful for a better understanding of the expression profile of genes associated with drought adaptation. In the present study, we attempted to analyse the DNA methylation pattern at the whole-genome level and the expression of a few drought-responsive genes in rice under different regimes of soil water status, i.e. puddled, 100 and 60% field capacities (FC). The methylation-sensitive randomly amplified polymorphic DNA analysis was employed to identify DNA methylation pattern. We observed an increase in DNA methylation at 60% FC, and reduced methylation under 100% FC compared to puddled condition. The genes such as protein phosphatases (PP2C) and phenylalanine ammonia-lyase (PAL) having CpG islands in their promoter region had lower expression level under 100 and 60% FC compared to puddled conditions. Heat shock protein 70 (HSP70) and RNA helicase 25 (RH25), with no CpG islands in their promoter region, exhibited enhanced expression compared to puddled plants. In rice, increased DNA methylation seems to be an important mechanism associated with drought responses, which probably regulates the methylation-sensitive gene expression. The drought-induced changes in DNA methylation would contribute for epigenetic mechanism. The study provided evidence to argue that drought-induced increased methylation might be one of the major mechanisms associated with acclimation responses in field crops like rice.

Keywords

CpG islandDNA methylationdrought stressgene expressionMS-RAPDrice
Type
Research Article
Information
Plant Genetic Resources , Volume 18 , Issue 4 , August 2020 , pp. 222 - 230
Copyright
Copyright © NIAB 2020

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References

Ahmad, F, Farman, K, Waseem, M, Rana, RM, Nawaz, MA, Rehman, HM, Abbas, T, Baloch, FS, Akrem, A, Huang, J and Zhang, H (2019) Genome-wide identification, classification, expression profiling and DNA methylation (5mC) analysis of stress-responsive ZFP Transcription factors in rice (Oryza sativa L.). Gene 718: 144018–144028.10.1016/j.gene.2019.144018CrossRefGoogle Scholar
Ali, F, Bano, A and Fazal, A (2017) Recent methods of drought stress tolerance in plants. Plant Growth Regulation 82: 363–375.10.1007/s10725-017-0267-2CrossRefGoogle Scholar
Azzouz-Olden, F, Hunt, AG and Dinkins, R (2020) Transcriptome analysis of drought-tolerant sorghum genotype SC56 in response to water stress reveals an oxidative stress defense strategy. Molecular Biology Reports 47: 3291–3303. doi: 10.1007.CrossRefGoogle ScholarPubMed
Barrs, HD and Weatherley, PE (1962) A re-examination of the relative turgidity technique for estimating water deficits in leaves. Australian Journal of Biological Sciences 15: 413–428.10.1071/BI9620413CrossRefGoogle Scholar
Bird, AP (1987) Cpg islands as gene markers in the vertebrate nucleus. Trends in Genetics 3: 342–347.10.1016/0168-9525(87)90294-0CrossRefGoogle Scholar
Borrell, A, Garside, A and Fukai, S (1997) Improving efficiency of water use for irrigated rice in a semi-arid tropical environment. Field Crops Research 52: 231–248.10.1016/S0378-4290(97)00033-6CrossRefGoogle Scholar
Boudet, AM (2007) Evolution and current status of research in phenolic compounds. Phytochemistry 68: 2722–2735.10.1016/j.phytochem.2007.06.012CrossRefGoogle ScholarPubMed
Bouman, BAM, Lampayan, RM and Tuong, TP (2007) Water Management in Irrigated Rice: Coping with Water Scarcity. Los Banos, Philippines: International Rice Research Institute, pp. 1–54.Google Scholar
Castaneda, AR, Bouman, BAM, Peng, S and Visperas, RM (2002) The potential of aerobic rice to reduce water use in water-scarce irrigated lowlands in the tropics. Proceedings of the International Work-shop on Water-wise Rice Production, pp. 165–176.Google Scholar
Chan, CS, Zainudin, H, Saad, A and Azmi, M (2012) Productive water use in aerobic rice cultivation. Journal of Tropical Agriculture and Food Science 49: 117–126.Google Scholar
Correia, B, Valledor, L, Hancock, RD, Jesus, C, Amaral, J, Meijón, M and Pinto, G (2016) Depicting how Eucalyptus globulus survives drought: involvement of redox and DNA methylation events. Functional Plant Biology 43: 838–850.10.1071/FP16064CrossRefGoogle ScholarPubMed
Deaton, AM and Bird, A (2011) Cpg islands and the regulation of transcription. Genes and Development 25: 1010–1022.10.1101/gad.2037511CrossRefGoogle ScholarPubMed
Demirkiran, A, Marakli, S, Temel, A and Gozukirmizi, N (2013) Genetic and epigenetic effects of salinity on in vitro growth of barley. Genetics and Molecular Biology 36: 566–570.10.1590/S1415-47572013000400016CrossRefGoogle ScholarPubMed
Dharmappa, PM, Doddaraju, P and Malagondanahalli, MV (2019) Introgression of root and water use efficiency traits enhances water productivity: an evidence for physiological breeding in rice (Oryza sativa L.). Rice 12: 1–14.10.1186/s12284-019-0268-zCrossRefGoogle Scholar
Doyle, JJ and Doyle, JL (1987) A rapid DNA isolation procedure for small quantities of fresh leaf tissue. Phytochemical Bulletin 19: 11–15.Google Scholar
Dzialo, M, Szopa, J, Czuj, T and Zuk, M (2017) Oligodeoxynucleotides can transiently up and downregulate CHS gene expression in flax by changing DNA methylation in a sequence-specific manner. Frontiers in Plant Science 8: 755–768.10.3389/fpls.2017.00755CrossRefGoogle Scholar
Eprintsev, AT, Fedorin, DN, Karabutova, LA and Igamberdiev, AU (2016) Expression of genes encoding subunits A and B of succinate dehydrogenase in germinating maize seeds is regulated by methylation of their promoters. Journal of Plant Physiology 205: 33–40.10.1016/j.jplph.2016.08.008CrossRefGoogle Scholar
Erturk, FA, Agar, G, Arslan, E, Nardemir, G and Sahin, Z (2014) Determination of genomic instability and DNA methylation effects of Cr on maize (Zea mays L.) using RAPD and CRED-RA analysis. Acta Physiologiae Plantarum 36: 1529–1537.10.1007/s11738-014-1529-5CrossRefGoogle Scholar
Finnegan, EJ, Genger, RK, Peacock, WJ and Dennis, ES (1998) DNA Methylation in plants. Annual Review of Plant Biology 49: 223–247.10.1146/annurev.arplant.49.1.223CrossRefGoogle ScholarPubMed
Garg, R, Chevala, NV, Shankar, R and Jain, M (2015) Divergent DNA methylation patterns associated with gene expression in rice cultivars with contrasting drought and salinity stress response. Scientific Reports 5: 14922–14937.10.1038/srep14922CrossRefGoogle ScholarPubMed
Girsang, SS, Quilty, JR, Correa, TQ Jr, Sanchez, PB and Buresh, RJ (2019) Rice yield and relationships to soil properties for production using overhead sprinkler irrigation without soil submergence. Geoderma 352: 277–288.10.1016/j.geoderma.2019.06.009CrossRefGoogle Scholar
Godwin, J and Farrona, S (2020) Plant epigenetic stress memory induced by drought: a physiological and molecular perspective. Methods in Molecular Biology 2093: 243–259.10.1007/978-1-0716-0179-2_17CrossRefGoogle ScholarPubMed
Graham-Acquaah, S, Siebenmorgen, TJ, Reba, ML, Massey, JH, Mauromoustakos, A, Adviento-Borbe, A, January, R, Burgos, R and Baltz-Gray, J (2019) Impact of alternative irrigation practices on rice quality. Cereal Chemistry 96: 815–823.10.1002/cche.10182CrossRefGoogle Scholar
Hiscox, JD and Israelstam, GF (1979) A method for the extraction of chlorophyll from leaf tissue without maceration. Canadian Journal of Botany 57: 1332–1334.10.1139/b79-163CrossRefGoogle Scholar
Karaba, A, Dixit, S, Greco, R, Aharoni, A, Trijatmiko, KR, Marsch-Martinez, N and Pereira, A (2007) Improvement of water use efficiency in rice by expression of HARDY, an Arabidopsis drought and salt tolerance gene. Proceedings of the National Academy of Sciences, USA 104: 15270–15275.10.1073/pnas.0707294104CrossRefGoogle Scholar
Karaca, M, Aydin, A and Ince, AG (2019) Cytosine methylation polymorphisms in cotton using TD-MS-RAPD-PCR. Modern Phytomorphology 13: 13–19.Google Scholar
Kinoshita, T and Seki, M (2014) Epigenetic memory for stress response and adaptation in plants. Plant and Cell Physiology 55: 1859–1863.10.1093/pcp/pcu125CrossRefGoogle ScholarPubMed
Lenka, SK, Katiyar, A, Chinnusamy, V and Bansal, KC (2011) Comparative analysis of drought-responsive transcriptome in Indica rice genotypes with contrasting drought tolerance. Plant Biotechnology Journal 9: 315–327.10.1111/j.1467-7652.2010.00560.xCrossRefGoogle ScholarPubMed
Li, C, Nong, Q, Solanki, MK, Liang, Q, Xie, J, Liu, X, Li, Y, Wang, W, Yang, L and Li, Y (2016) Differential expression profiles and pathways of genes in sugarcane leaf at elongation stage in response to drought stress. Scientific Reports 6: 25698–25708.10.1038/srep25698CrossRefGoogle Scholar
Livak, KJ and Schmittgen, TD (2001) Analysis of relative gene expression data using real-time quantitative PCR and the 2(-Delta Delta C(T)) method. Methods (San Diego, Calif.) 25: 402–408.10.1006/meth.2001.1262CrossRefGoogle Scholar
Luan, A, Chen, C, Xie, T, He, J and He, Y (2020) Methylation analysis of CpG islands in pineapple SERK1 promoter. Genes 11: 425–434.10.3390/genes11040425CrossRefGoogle ScholarPubMed
Meyer, P (2015) Epigenetic variation and environmental change. Journal of Experimental Botany 66: 3541–3548.10.1093/jxb/eru502CrossRefGoogle ScholarPubMed
Mozgova, I, Mikulski, P, Pecinka, A and Farrona, S (2019) Epigenetic mechanisms of abiotic stress response and memory in plants. In: Alvarez-Venegas, R, De-la-Peña, C and Casas-Mollano, JA (eds.) Epigenetics in Plants of Agronomic Importance: Fundamentals and Applications. Cham: Springer, pp. 1–64.Google Scholar
Munshi, A, Ahuja, YR and Bahadur, B (2015) Epigenetic mechanisms in plants: an overview. In: Bahadur, B, Venkat Rajam, M, Sahijram, L, Krishnamurthy, K (eds.) Plant Biology and Biotechnology. New Delhi: Springer, pp. 265–278.10.1007/978-81-322-2283-5_12CrossRefGoogle Scholar
Nataraja, KN and Jacob, J (1999) Clonal differences in photosynthesis in Hevea brasiliensis Müll. Arg. Photosynthetica 36: 89–98.10.1023/A:1007070820925CrossRefGoogle Scholar
Parvathi, MS and Nataraja, KN (2017) Simultaneous expression of abiotic stress-responsive genes: an approach to improve multiple stress tolerance in crops. In: Senthil-Kumar, M (ed.) Plant Tolerance to Individual and Concurrent Stresses. New Delhi: Springer, pp. 151–163.10.1007/978-81-322-3706-8_10CrossRefGoogle Scholar
Priya, M, Dhanker, OP, Siddique, KH, Hanumantha Rao, B, Nair, RM, Pandey, S, Singh, S, Varshney, RK, Prasad, PV and Nayyar, H (2019) Drought and heat stress-related proteins: an update about their functional relevance in imparting stress tolerance in agricultural crops. Theoretical and Applied Genetics 132: 1607–1638.10.1007/s00122-019-03331-2CrossRefGoogle ScholarPubMed
Rajkumar, MS, Shankar, R, Garg, R and Jain, M (2020) Bisulphite sequencing reveals dynamic DNA methylation under desiccation and salinity stresses in rice cultivars. Genomics pii 112: S0888–754330983–8. doi:10.1016.CrossRefGoogle ScholarPubMed
Sajeevan, RS, Shivanna, MB and Nataraja, KN (2014) An efficient protocol for total RNA isolation from healthy and stressed tissues of mulberry (Morus sp.) and other species. American Journal of Plant Sciences 5: 2057–2065.10.4236/ajps.2014.513221CrossRefGoogle Scholar
Sapna, H and Nataraja, KN (2016) Prediction of DNA methylation marks and related gene expression pattern in contrasting rice genotypes under drought stress. Mysore Journal of Agricultural Sciences 50: 316–319.Google Scholar
Schübeler, D (2015) Function and information content of DNA methylation. Nature 517: 321–326.10.1038/nature14192CrossRefGoogle ScholarPubMed
Sharma, E, Jain, M and Khurana, JP (2019) Differential quantitative regulation of specific gene groups and pathways under drought stress in rice. Genomics 111: 1699–1712.10.1016/j.ygeno.2018.11.024CrossRefGoogle ScholarPubMed
Su, Z, Xia, J and Zhao, Z (2011) Functional complementation between transcriptional methylation regulation and post-transcriptional microRNA regulation in the human genome. BMC Genomics 12: 5–15.10.1186/1471-2164-12-S5-S15CrossRefGoogle ScholarPubMed
Surdonja, K, Eggert, K, Hajirezaei, MR, Harshavardhan, V, Seiler, C, Von Wirén, N, Sreenivasulu, N and Kuhlmann, M (2017) Increase of DNA methylation at the HvCKX2.1 Promoter by terminal drought stress in Barley. Epigenomes 1: 9–22.10.3390/epigenomes1020009CrossRefGoogle Scholar
Tirado-Magallanes, R, Rebbani, K, Lim, R, Pradhan, S and Benoukraf, T (2017) Whole genome DNA methylation: beyond genes silencing. Oncotarget 8: 5629–5637.10.18632/oncotarget.13562CrossRefGoogle ScholarPubMed
Van-Dooren, TJ, Silveira, AB, Gilbault, E, Jiménez-Gómez, JM, Martin, A, Bach, L, Tisné, S, Quadrana, L, Loudet, O and Colot, V (2020) Mild drought in the vegetative stage induces phenotypic, gene expression and DNA methylation plasticity in Arabidopsis but no transgenerational effects. Journal of Experimental Botany 132: 1–15.Google Scholar
Varotto, S, Tani, E, Abraham, E, Krugman, T, Kapazoglou, A, Melzer, R, Radanović, A and Miladinović, D (2020) Epigenetics: possible applications in climate-smart crop breeding. Journal of Experimental Botany pii: eraa188. doi: 10.1093.CrossRefGoogle ScholarPubMed
Wang, WS, Pan, YJ, Zhao, XQ, Dwivedi, D, Zhu, LH, Ali, J, Fu, BY and Li, ZK (2011) Drought-induced site-specific DNA methylation and its association with drought tolerance in rice (Oryza sativa L.). Journal of Experimental Botany 62: 1951–1960.10.1093/jxb/erq391CrossRefGoogle Scholar
Wang, W, Qin, Q, Sun, F, Wang, Y, Xu, D, Li, Z and Fu, B (2016) Genome-wide differences in DNA methylation changes in two contrasting rice genotypes in response to drought conditions. Frontiers in Plant Science 7: 1675–1687.10.3389/fpls.2016.01675CrossRefGoogle ScholarPubMed
Yang, Q, Liu, K, Niu, X, Wang, Q, Wan, Y, Yang, F, Li, G, Wang, Y and Wang, R (2018) Genome-wide identification of PP2C genes and their expression profiling in response to drought and cold stresses in Medicago truncatula. Scientific Reports 8: 12841–12854.10.1038/s41598-018-29627-9CrossRefGoogle ScholarPubMed
Zemach, A, Kim, MY, Silva, P, Rodrigues, JA, Dotson, B, Brooks, MD and Zilberman, D (2010) Local DNA hypomethylation activates genes in rice endosperm. Proceedings of the National Academy of Sciences, USA 107: 18729–18734.10.1073/pnas.1009695107CrossRefGoogle ScholarPubMed
Zheng, X, Chen, L, Li, M, Lou, Q, Xia, H, Wang, P, Li, T, Liu, H and Luo, L (2013) Transgenerational variations in DNA methylation induced by drought stress in two rice varieties with distinguished difference to drought resistance. PLoS ONE 8: e80253.10.1371/journal.pone.0080253CrossRefGoogle ScholarPubMed
Zilberman, D, Gehring, M, Tran, RK, Ballinger, T and Henikoff, S (2007) Genome-wide analysis of Arabidopsis thaliana DNA methylation uncovers an inter-dependence between methylation and transcription. Nature Genetics 39: 61–69.10.1038/ng1929CrossRefGoogle Scholar
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