Skip to main content
Log in

Characterization of a novel cotton MYB gene, GhMYB108-like responsive to abiotic stresses

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

Abstract

Transcriptional factors are the major regulators of plant signaling pathways in response to environmental stresses i.e., drought, salinity and cold. Hereby, the GhMYB108-like was characterized to determine whether it regulate these stresses. The GhMYB108-like cDNA consisted of 1107 base pairs (bp) with 807 open reading frame encoded a protein of 268 amino acids. Its isoelectric point and molecular weight are 5.51 and 30.3 kDa respectively. Phylogenetic analysis and online databases revealed that GhMYB108-like proteins are closely related with the Arabidopsis thaliana MYB2. Important cis-elements were detected in the promotor region of GhMYB108-like responding to stresses and phytohormones. The 3D structure of GhMYB108-like protein has been predicted. In addition, various physico-chemical properties of GhMYB108-like have been determined. Subcellular localization confirmed that GhMYB108-like are nuclear localized protein. Quantitative expression analysis showed that polyethylene glycol and salt treatments significantly induced the expression of GhMYB108-like. Overall, our findings suggest that GhMYB108-like is an important gene that would plays important regulatory role in response to drought and salt stresses.

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

Access this article

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

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3

Similar content being viewed by others

References

  1. Ullah A, Heng S, Munis MFH, Fahad S, Yang X (2015) Phytoremediation of heavy metals assisted by plant growth promoting (PGP) bacteria: a review. Environ Exp Bot 117:28–40

    Article  CAS  Google Scholar 

  2. Yu LH, Wu SJ, Peng YS et al (2016) Arabidopsis EDT1/HDG11 improves drought and salt tolerance in cotton and poplar and increases cotton yield in the field. Plant Biotechnol J 14:72–84

    Article  CAS  PubMed  Google Scholar 

  3. Ullah A, Nisar M, Ali H, Hazrat A et al (2019) Drought tolerance improvement in plants: an endophytic bacterial approach. Appl Microbiol Biotechnol 103:7385–7397

    Article  CAS  PubMed  Google Scholar 

  4. Ullah A, Akbar A, Luo Q, Khan AH, Manghwar H, Shaban M, Yang X (2019) Microbiome diversity in cotton rhizosphere under normal and drought conditions. Microb Ecol 77:429–439

    Article  CAS  PubMed  Google Scholar 

  5. Comas LH, Becker SR, Cruz VMV, Byrne PF, Dierig DA (2013) Root traits contributing to plant productivity under drought. Front Plant Sci 4:442

    Article  PubMed  PubMed Central  Google Scholar 

  6. Kumar M, Choi JY, Kumari N, Pareek A, Kim SR (2015) Molecular breeding in Brassica for salt tolerance: importance of microsatellite (SSR) markers for molecular breeding in Brassica. Front Plant Sci 6:688

    PubMed  PubMed Central  Google Scholar 

  7. Zhang F, Li S, Yang S, Wang L, Guo W (2015) Overexpression of a cotton annexin gene, GhAnn1, enhances drought and salt stress tolerance in transgenic cotton. Plant Mol Biol 87:47–67

    Article  CAS  PubMed  Google Scholar 

  8. Ullah A, Sun H, Yang X, Zhang X (2017) Drought coping strategies in cotton: increased crop per drop. Plant Biotechnol J 15:281–284

    Article  Google Scholar 

  9. Dawn news (2016) http://www.dawn.com/news/1240448

  10. Zhang H, Li Y, Zhu JK (2018) Developing naturally stress-resistant crops for a sustainable agriculture. Nat Plants 4:989–996

    Article  PubMed  Google Scholar 

  11. Shaban M, Ahmed MM, Sun H, Ullah A, Zhu L (2018) Genome-wide identification of lipoxygenase gene family in cotton and functional characterization in response to abiotic stresses. BMC Genom 19:599

    Article  Google Scholar 

  12. Ullah A, Sun H, Yang X, Zhang X (2017) A novel cotton WRKY-gene, GhWRKY6-like, improves salt tolerance by activating the ABA signalling pathway and scavenging of reactive oxygen species. Physiol Plant 162:439–454

    Article  PubMed  Google Scholar 

  13. Ambawat S, Sharma P, Yadav NR, Yadav RC (2013) MYB transcription factor genes as regulators for plant responses: an overview. Physiol Mol Biol Plants 19:307–321

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  14. Chen T, Li W, Hu X, Guo J, Liu A, Zhang B (2015) A cotton MYB transcription factor, GbMYB5, is positively involved in plant adaptive response to drought stress. Plant Cell Physiol 56:917–929

    Article  CAS  PubMed  Google Scholar 

  15. Baldoni E, Genga A, Cominelli E (2015) Plant MYB transcription factors: their role in drought response mechanisms. Int J Mol Sci 16:15811–15851

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  16. Xiong H, Li J, Liu P, Duan J, Zhao Y, Guo X, Li Y, Zhang H, Ali J, Li Z (2014) Overexpression of OsMYB48-1, a novel MYB-Related transcription factor, enhances drought and salinity tolerance in rice. PLoS ONE 9:e92913

    Article  PubMed  PubMed Central  Google Scholar 

  17. Gao F, Zhou J, Deng RY, Zhao HX, Li CL, Chen H, Suzuki T, Park S, Wu Q (2017) Overexpression of a tartary buckwheat R2R3-MYB transcription factor gene, FtMYB9, enhances tolerance to drought and salt stresses in transgenic Arabidopsis. J Plant Physiol 214:81–90

    Article  CAS  PubMed  Google Scholar 

  18. Li K, Xing C, Yao Z, Huang X (2017) PbrMYB21, a novel MYB protein of Pyrus betulaefolia, functions in drought tolerance and modulates polyamine levels by regulating arginine decarboxylase gene. Plant Biotechnol J 15:1186–1203

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  19. Jin F, Hu L, Yuan D, Xu J, Gao W, He L, Yang X, Zhang X (2014) Comparative transcriptome analysis between somatic embryos (SEs) and zygotic embryos in cotton: evidence for stress response functions in SE development. Plant Biotechnol J 12:161–173

    Article  CAS  PubMed  Google Scholar 

  20. Kokkirala VR, Yonggang P, Abbagani S, Zhu Z, Umate P (2010) Subcellular localization of proteins of Oryza sativa L. in the model tobacco and tomato plants. Plant Signal Behav 5:1336–1341

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  21. Gasteiger E, Hoogland C, Gattiker A, Duvaud SE, Wilkins MR, Appel RD, Bairoch A (2005) Protein identification and analysis tools on the ExPASy server. In: The proteomics protocols handbook. Humana Press, Totowa

    Chapter  Google Scholar 

  22. Arnold L, Bordoli J, Kopp T, Schwede (2006) The SWISS-MODEL workspace: a web-based environment for protein structure homology modelling. Bioinformatics 22:195–201

    Article  CAS  PubMed  Google Scholar 

  23. Laskowski RA, Rullmann JA, MacArthur MW, Kaptein R, Thornton JM (1996) AQUA and PROCHECK-NMR: programs for checking the quality of protein structures solved by NMR. J Biomol NMR 8:477–486

    Article  CAS  PubMed  Google Scholar 

  24. Wiederstein M, Sippl MJ (2007) ProSA-web: interactive web service for the recognition of errors in three-dimensional structures of proteins. Nucleic Acids Res 35:407–410

    Article  Google Scholar 

  25. Benkert P, Kunzli M, Schwede T (2009) QMEAN server for protein model quality estimation. Nucleic Acids Res 37:510–514

    Article  Google Scholar 

  26. Colovos C, Yeates TO (1993) Verification of protein structures: patterns of nonbonded atomic interactions. Protein Sci 2:1511–1519

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  27. Liithy R, Bowie JU, Eisenber DM (1992) Assessment of protein models with three-dimensional profiles. Nature 356:83–85

    Article  Google Scholar 

  28. Ul Qamar MT, Khan MS (2017) A novel structural and functional insight into chloroplast-encoded central subunit of dark-operated protochlorophyllide oxidoreductase (DPOR) of plants. Pak J Agric Sci 54:395–406

    Google Scholar 

  29. Xu Z, Li J, Guo X, Jin S, Zhang X (2016) Metabolic engineering of cottonseed oil biosynthesis pathway via RNA interference. Sci Rep 6:33342

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  30. Schmittgen TD, Livak KJ (2008) Analyzing real-time PCR data by the comparative CT method. Nat Protoc 3:1101–1108

    Article  CAS  PubMed  Google Scholar 

  31. Hooft RW, Sander C, Vriend G (1997) Objectively judging the quality of a protein structure from a Ramachandran plot. Comput Appl Biosci 13:425–430

    CAS  PubMed  Google Scholar 

  32. Agarwal PK, Shukla PS, Gupta K, Jha B (2013) Bioengineering for salinity tolerance in plants: state of the art. Mol Biotechnol 54:102–123

    Article  CAS  PubMed  Google Scholar 

  33. Gray SB, Brady SM (2016) Plant developmental responses to climate change. Dev Biol 419:64–77

    Article  CAS  PubMed  Google Scholar 

  34. Yamaguchi-Shinozaki K, Urao T, Shinozaki K (1995) Regulation of genes that are induced by drought stress in Arabidopsis thaliana. J Plant Res 108:127–136

    Article  CAS  Google Scholar 

  35. Wittkopp PJ, Kalay G (2012) Cis-regulatory elements: molecular mechanisms and evolutionary processes underlying divergence. Nat Rev Genet 13:59–69

    Article  CAS  Google Scholar 

  36. Ullah A, Manghwar H, Shaban M, Khan AH, Akbar A, Ali U, Ali E, Fahad S (2018) Phytohormones enhanced drought tolerance in plants: a coping strategy. Env Sci Pollut Res 25:33103–33118

    Article  CAS  Google Scholar 

  37. Zhou L, Wang NN, Gong SY, Lu R, Li Y, Li XB (2015) Overexpression of a cotton (Gossypium hirsutum) WRKY gene, GhWRKY34, in Arabidopsis enhances salt-tolerance of the transgenic plants. Plant Physiol Biochem 96:311–320

    Article  CAS  PubMed  Google Scholar 

  38. Xie C, Zhang R, Qu Y, Miao Z, Zhang Y, Shen X, Wang T, Dong J (2012) Overexpression of MtCAS31 enhances drought tolerance in transgenic Arabidopsis by reducing stomatal density. New Phytol 195:124–135

    Article  CAS  PubMed  Google Scholar 

  39. Ching T, Himmelstein DS, Beaulieu-Jones BK, Kalinin AA, Do BT, Way GP, Xie W (2018) Opportunities and obstacles for deep learning in biology and medicine. J R Soc Interface 15:20170387

    Article  PubMed  PubMed Central  Google Scholar 

Download references

Acknowledgements

I am grateful to Chinese Scholarship Council who financially supported me during my PhD study. This study was funded by the National Key Project of Research and the Development Plan (2016YFD0101006). There is no conflict of interest between the authors.

Author information

Authors and Affiliations

Authors

Corresponding authors

Correspondence to Abid Ullah or Xiyan Yang.

Additional information

Publisher's Note

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

Electronic supplementary material

Below is the link to the electronic supplementary material.

Supplementary material 1 (DOCX 713 kb)

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Ullah, A., Ul Qamar, M.T., Nisar, M. et al. Characterization of a novel cotton MYB gene, GhMYB108-like responsive to abiotic stresses. Mol Biol Rep 47, 1573–1581 (2020). https://doi.org/10.1007/s11033-020-05244-6

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11033-020-05244-6

Keywords

Navigation