Skip to main content
SpringerLink
Log in

The comparative transcriptome analysis of two green super rice genotypes with varying tolerance to salt stress

  • Original Article
  • Published:
Molecular Biology Reports Aims and scope Submit manuscript

Abstract

Background

Salinity is one of the main abiotic factors that restrict plant growth, physiology, and crop productivity is salt stress. About 33% of the total irrigated land suffers from severe salinity because of intensive underground water extraction and irrigation with brackish water. Thus, it is important to understand the genetic mechanism and identify the novel genes involved in salt tolerance for the development of climate-resilient rice cultivars.

Methods and results

In this study, two rice genotypes with varying tolerance to salt stress were used to investigate the differential expressed genes and molecular pathways to adapt under saline soil by comparative RNA sequencing at 42 days of the seedling stage. Salt-susceptible (S3) and -tolerant (S13) genotypes revealed 3982 and 3463 differentially expressed genes in S3 and S13 genotypes. The up-regulated genes in both genotypes were substantially enriched in different metabolic processes and binding activities. Biosynthesis of secondary metabolites, phenylpropanoid biosynthesis, and plant signal transduction mechanisms were highly enriched. Salt-susceptible and -tolerant genotypes shared the same salt adaptability mechanism with no significant quantitative differences at the transcriptome level. Moreover, bHLH, ERF, NAC, WRKY, and MYB transcription factors were substantially up-regulated under salt stress. 391 out of 1806 identified novel genes involved in signal transduction mechanisms. Expression profiling of six novel genes further validated the findings from RNA-seq data.

Conclusion

These findings suggest that the differentially expressed genes and molecular mechanisms involved in salt stress adaptation are conserved in both salt-susceptible and salt-tolerant rice genotypes. Further molecular characterization of novel genes will help to understand the genetic mechanism underlying salt tolerance in rice.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6

Similar content being viewed by others

Data availability

The RNA-seq dataset generated and analyzed in the present study is submitted in NCBI GEO under the accession GSE210952.

References

  1. Shrivastava P, Kumar R (2015) Soil salinity: a serious environmental issue and plant growth promoting bacteria as one of the tools for its alleviation. Saudi J Biol Sci 22:123–131

    Article  CAS  PubMed  Google Scholar 

  2. Munns R (2005) Genes and salt tolerance: bringing them together. New Phytol 167:645–663

    Article  CAS  PubMed  Google Scholar 

  3. Umali DL (1993) Irrigation-induced salinity: a growing problem for development and the environment. World Bank Publications, Washington, DC

    Book  Google Scholar 

  4. Ahmad H et al (2022) Impact of pre-anthesis drought stress on physiology, yield-related traits, and Drought-responsive genes in green super rice. Front Genet 13:832542

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  5. Ali J, Anumalla M, Murugaiyan V, Li Z (2021) Green super rice (GSR) traits: breeding and genetics for multiple biotic and abiotic stress tolerance in rice. In: Ali J, Wani SH (eds) Rice Improvement: physiological, molecular breeding and genetic perspectives. Springer International Publishing, pp 59–97. https://doi.org/10.1007/978-3-030-66530-2_3

    Chapter  Google Scholar 

  6. Amanat MA et al (2022) Evaluation of green super rice lines for agronomic and physiological traits under salinity stress. Plants 11:1461

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  7. Zaid IU et al (2022) Estimation of genetic variances and stability components of yield-related traits of green super rice at multi-environmental conditions in Pakistan. Agronomy 12:1157

    Article  Google Scholar 

  8. Zhang Q (2007) Strategies for developing green super rice. Proc Natl Acad Sci 104:16402–16409

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  9. Yu S, Ali J, Zhang C, Li Z, Zhang Q (2020) Genomic breeding of green super rice varieties and their deployment in Asia and Africa. Theor Appl Genet 133:1427–1442

    Article  PubMed  PubMed Central  Google Scholar 

  10. Reddy INBL, Kim B-K, Yoon I-S, Kim K-H, Kwon T-R (2017) Salt tolerance in rice: focus on mechanisms and approaches. Rice Sci 24:123–144

    Article  Google Scholar 

  11. Zhao S et al (2021) Regulation of plant responses to salt stress. Int J Mol Sci 22:4609

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  12. Javid MG, Sorooshzadeh A, Moradi F, Modarres SSAM, Allahdadi I (2011) The role of phytohormones in alleviating salt stress in crop plants. Aust J Crop Sci 5:726–734

    CAS  Google Scholar 

  13. Zelm EV, Zhang Y, Testerink C (2020) Salt tolerance mechanisms of plants. Annu Rev Plant Biol 71:403–433

    Article  PubMed  Google Scholar 

  14. Anwar K, Lakra N, Singla-Pareek SL, Pareek A (2016) Investigating abiotic stress response machinery in plants: the metabolomic approach. In: Dagar JC, Sharma PC, Sharma DK, Singh A (eds) Innovative saline agriculture. Springer, Berlin

    Google Scholar 

  15. Banerjee A, Ghosh P, Roychoudhury A (2019) Salt acclimation differentially regulates the metabolites commonly involved in stress tolerance and aroma synthesis in indica rice cultivars. Plant Growth Regul 88:87–97

    Article  CAS  Google Scholar 

  16. Wang X et al (2020) Advances in transcriptomics in the response to stress in plants. Glob Med Genet 7:30–34

    Article  PubMed  PubMed Central  Google Scholar 

  17. Li Y-F et al (2018) Comparative transcriptome and translatome analysis in contrasting rice genotypes reveals differential mRNA translation in salt-tolerant Pokkali under salt stress. BMC Genomics 19:935

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  18. Kong W et al (2019) Meta-analysis of salt stress transcriptome responses in different rice genotypes at the Seedling Stage. Plants 8:64

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  19. Wang J et al (2018) Comparative transcriptome analysis reveals molecular response to salinity stress of salt-tolerant and sensitive genotypes of indica rice at seedling stage. Sci Rep 8:2085

    Article  PubMed  PubMed Central  Google Scholar 

  20. Zhou Y et al (2016) Transcriptome analysis of salt stress responsiveness in the seedlings of Dongxiang wild rice (Oryza rufipogon Griff). PLoS One 11:e0146242

    Article  PubMed  PubMed Central  Google Scholar 

  21. Ye X, Tie W, Xu J, Ding Z, Hu W (2022) Comparative transcriptional analysis of two contrasting rice genotypes in response to salt stress. Agronomy 12:1163

    Article  CAS  Google Scholar 

  22. Chandran AKN et al (2019) Transcriptome analysis of rice-seedling roots under soil–salt stress using RNA-Seq method. Plant Biotechnol Rep 13:567–578

    Article  Google Scholar 

  23. Cartagena JA, Yao Y, Mitsuya S, Tsuge T (2021) Comparative transcriptome analysis of root types in salt tolerant and sensitive rice varieties in response to salinity stress. Physiol Plant 173:1629–1642

    Article  CAS  PubMed  Google Scholar 

  24. Kong W, Sun T, Zhang C, Deng X, Li Y (2021) Comparative transcriptome analysis reveals the mechanisms underlying differences in salt tolerance between Indica and Japonica rice at seedling stage. Front Plant Sci 12:725436

    Article  PubMed  PubMed Central  Google Scholar 

  25. Mirdar Mansuri R et al (2019) Dissecting molecular mechanisms underlying salt tolerance in rice: a comparative transcriptional profiling of the contrasting genotypes. Rice 12:13

    Article  PubMed  PubMed Central  Google Scholar 

  26. Andrews S (2010) FastQC: a quality control tool for high throughput sequence data. http://www.bioinformatics.babraham.ac.uk/projects/fastqc

  27. Bolger AM, Lohse M, Usadel B (2014) Trimmomatic: a flexible trimmer for Illumina sequence data. Bioinformatics 30:2114–2120

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  28. Kim D, Paggi JM, Park C, Bennett C, Salzberg SL (2019) Graph-based genome alignment and genotyping with HISAT2 and HISAT-genotype. Nat Biotechnol 37:907–915

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  29. Liao Y, Smyth GK, Shi W (2014) featureCounts: an efficient general purpose program for assigning sequence reads to genomic features. Bioinforma Oxf Engl 30:923–930

    Article  CAS  Google Scholar 

  30. Love MI, Huber W, Anders S (2014) Moderated estimation of Fold change and dispersion for RNA-seq data with DESeq2. Genome Biol 15:550

    Article  PubMed  PubMed Central  Google Scholar 

  31. Pertea M et al (2015) StringTie enables improved reconstruction of a transcriptome from RNA-seq reads. Nat Biotechnol 33:290–295

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  32. Drost H-G, Paszkowski J (2017) Biomartr: genomic data retrieval with R. Bioinformatics 33:1216–1217

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  33. Carlson, M. & Pagès, H (2021) AnnotationForge: tools for building SQLite-based annotation data packages

  34. Wu T et al (2021) clusterProfiler 4.0: a universal enrichment tool for interpreting omics data. The Innovation 2:100141

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  35. Yanagisawa S (1998) Transcription factors in plants: physiological functions and regulation of expression. J Plant Res 111:363–371

    Article  CAS  Google Scholar 

  36. Dobin A et al (2013) STAR: ultrafast universal RNA-seq aligner. Bioinformatics 29:15–21

    Article  CAS  PubMed  Google Scholar 

  37. McKenna A et al (2010) The genome analysis Toolkit: a MapReduce framework for analyzing next-generation DNA sequencing data. Genome Res 20:1297–1303

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  38. Cingolani P et al (2012) A program for annotating and predicting the effects of single nucleotide polymorphisms, SnpEff. Fly (Austin) 6:80–92

    Article  CAS  PubMed  Google Scholar 

  39. Lu Y et al (2020) Coordination between growth-regulating factor1 and GRF-interacting factor1 plays a key role in regulating leaf growth in rice. BMC Plant Biol 20:200

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  40. Wang S-L et al (2022) Control of grain weight and size in rice (Oryza sativa L.) by OsPUB3 encoding a U-Box E3 ubiquitin ligase. Rice 15:58

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  41. Li W et al (2011) Comparative characterization, expression pattern and function analysis of the 12-oxo-phytodienoic acid reductase gene family in rice. Plant Cell Rep 30:981–995

    Article  CAS  PubMed  Google Scholar 

  42. Xiang Y, Huang Y, Xiong L (2007) Characterization of stress-responsive CIPK genes in rice for stress tolerance improvement. Plant Physiol 144:1416–1428

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  43. Lan T et al (2019) OsSPL10, a SBP-Box Gene, plays a dual role in salt tolerance and trichome formation in rice (Oryza sativa L). G3 GenesGenomesGenetics 9:4107–4114

    Article  CAS  Google Scholar 

  44. Bhatla SC, Lal MA (2018) Plant physiology development and metabolism. Springer, Berlin

    Book  Google Scholar 

  45. Passardi F, Cosio C, Penel C, Dunand C (2005) Peroxidases have more functions than a Swiss army knife. Plant Cell Rep 24:255–265

    Article  CAS  PubMed  Google Scholar 

  46. Zhao C, Zhang H, Song C, Zhu J-K, Shabala S (2020) Mechanisms of plant responses and adaptation to soil salinity. The Innovation 1:100017

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  47. Formentin E et al (2018) Transcriptome and cell physiological analyses in different rice cultivars provide new insights into adaptive and salinity stress responses. Front Plant Sci. https://doi.org/10.3389/fpls.2018.00204

    Article  PubMed  PubMed Central  Google Scholar 

  48. Xie Z et al (2020) Characterizing the metabolites related to rice salt tolerance with introgression lines exhibiting contrasting performances in response to saline conditions. Plant Growth Regul 92:157–167

    Article  CAS  Google Scholar 

  49. Šamec D, Karalija E, Šola I, Vujčić Bok V, Salopek-Sondi B (2021) The role of polyphenols in abiotic stress response: the influence of molecular structure. Plants 10:118

    Article  PubMed  PubMed Central  Google Scholar 

  50. Shomali A et al (2022) Diverse physiological roles of flavonoids in plant environmental stress responses and tolerance. Plants 11:3158

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  51. Sharma A et al (2019) Response of phenylpropanoid pathway and the role of polyphenols in plants under abiotic stress. Molecules 24:2452

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  52. Miller G, Suzuki N, Ciftci-Yilmaz S, Mittler R (2010) Reactive oxygen species homeostasis and signalling during drought and salinity stresses. Plant Cell Environ 33:453–467

    Article  CAS  PubMed  Google Scholar 

  53. Mata-Pérez C et al (2015) Transcriptomic profiling of linolenic acid-responsive genes in ROS signaling from RNA-seq data in Arabidopsis. Front Plant Sci. https://doi.org/10.3389/fpls.2015.00122

    Article  PubMed  PubMed Central  Google Scholar 

  54. Guo J et al (2021) Current understanding of bHLH transcription factors in plant abiotic stress tolerance. Int J Mol Sci 22:4921

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  55. Abe H et al (2003) Arabidopsis AtMYC2 (bHLH) and AtMYB2 (MYB) function as transcriptional activators in abscisic acid signaling. Plant Cell 15:63–78

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  56. Falcone Ferreyra ML, Rius S, Casati P (2012) Flavonoids: biosynthesis, biological functions, and biotechnological applications. Front. Plant Sci 3:222

    CAS  Google Scholar 

  57. Qian Y et al (2021) Regulatory mechanisms of bHLH transcription factors in plant adaptive responses to various abiotic stresses. Front Plant Sci. https://doi.org/10.3389/fpls.2021.677611

    Article  PubMed  PubMed Central  Google Scholar 

  58. Zhu J-K (2002) Salt and drought stress signal transduction in plants. Annu Rev Plant Biol 53:247–273

    Article  CAS  PubMed  PubMed Central  Google Scholar 

Download references

Acknowledgements

The authors extend their appreciation to the Researchers Supporting Project number (RSP-2024R369), King Saud University, Riyadh, Saudi Arabia. We are also thankful to the Bioinformatics and Functional Genomics Labs at the National Institute for Genomics and Advanced Biotechnology (NIGAB), Pakistan, for providing the research facilities.

Funding

No specific funds have been received for this study.

Author information

Authors and Affiliations

  1. National Institute for Genomics and Advanced Biotechnology (NIGAB), NARC, Park Road, Islamabad, 45500, Pakistan

    Nageen Zahra, Muhammad Uzair, Imdad Ullah Zaid, Safeena Inam, Muhammad Kashif Naeem, Umer Farooq, Nazia Rehman & Muhammad Ramzan Khan

  2. Department of Biochemistry, College of Science, King Saud University, P.O. Box 2455, 11451, Riyadh, Saudi Arabia

    Kotb A. Attia

  3. Department of Plant Breeding and Genetics, The University of Haripur, Haripur, 22620, Pakistan

    Sajid Fiaz

  4. Department of Rice, Field Crops Research Institute, ARC, Sakha, Kafrelshiekh, 33717, Egypt

    Rizk M. Abdallah

  5. Pakistan Agriculture Research Council, Islamabad, Pakistan

    Ghulam Muhammad Ali

  6. Institute of Crop Science, Chinese Academy of Agricultural Sciences, Beijing, China

    Jianlong Xu & Zhikang Li

Authors
  1. Nageen Zahra
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Muhammad Uzair
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Imdad Ullah Zaid
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Kotb A. Attia
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Safeena Inam
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Sajid Fiaz
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. Rizk M. Abdallah
    View author publications

    You can also search for this author in PubMed Google Scholar

  8. Muhammad Kashif Naeem
    View author publications

    You can also search for this author in PubMed Google Scholar

  9. Umer Farooq
    View author publications

    You can also search for this author in PubMed Google Scholar

  10. Nazia Rehman
    View author publications

    You can also search for this author in PubMed Google Scholar

  11. Ghulam Muhammad Ali
    View author publications

    You can also search for this author in PubMed Google Scholar

  12. Jianlong Xu
    View author publications

    You can also search for this author in PubMed Google Scholar

  13. Zhikang Li
    View author publications

    You can also search for this author in PubMed Google Scholar

  14. Muhammad Ramzan Khan
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

Conceptualization, NZ, and MRK; methodology, software, and validation, IUZ, UF, MKN, SI, NR, and MU; formal analysis and investigation, NZ, and MU; writing—original draft preparation, review, and editing, NZ, MU, GMA, SF, RMA, JX, ZL, and MRK; visualization, MU; supervision and funding acquisition, MRK. All authors have read and agreed to the published version of the manuscript.

Corresponding authors

Correspondence to Sajid Fiaz or Muhammad Ramzan Khan.

Ethics declarations

Competing interest

The authors declare no competing interests.

Ethical approval

Not applicable.

Consent to participate

Not applicable.

Consent to publish

Not applicable.

Additional information

Publisher’s Note

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

Supplementary Information

Rights and permissions

Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Zahra, N., Uzair, M., Zaid, I.U. et al. The comparative transcriptome analysis of two green super rice genotypes with varying tolerance to salt stress. Mol Biol Rep 51, 22 (2024). https://doi.org/10.1007/s11033-023-08998-x

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1007/s11033-023-08998-x

Keywords

Search

Navigation