Springer Nature is making SARS-CoV-2 and COVID-19 research free. View research | View latest news | Sign up for updates

Biological Network Analyses of WRKY Transcription Factor Family in Soybean (Glycine max) under Low Phosphorus Treatment


WRKY transcription factor (TF) is plant specific genes and play essential roles involved in biotic and abiotic stress tolerance. Gene co-expression network (GCN) analysis is effective tool for the interpretation of transcriptomic data. In this study, a co-expression network of 152 WRKY genes using publicly available microarray data (GSE78242) was constructed under low phosphate (Pi) treatment in soybean (Glycine max). A total of 149 nodes and 641 edges were obtained from CGN and seven seed genes were identified. Particularly, Glyma.19G094100 and Glyma.16G054400 seed genes (orthologue to Arabidopsis WRKY75) were found to have a direct connection to P deficiency. Promotor analyses of seed genes revealed the variations in the number of cis-regulatory elements (CREs) ranging from 80 to 137 with a total of 835 CREs. The methylation profile of Glyma.04G218700 (orthologue to Arabidopsis WRKY51) was found higher than other seed genes. As a result, our findings can be used as a scientific basis to cope with P deficiency in soybean as well as abiotic stress tolerance. In addition, these findings of this study may prove the crop improvement studies in future, especially genetically engineered soybean plants.

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


  1. Albert R, Barabasi AL. 2002. Statistical mechanics of complex networks. Rev. Modern Phys. 74: 47–97

  2. Bader GD, Hogue, CW. 2003. An automated method for finding molecular complexes in large protein interaction networks. BMC Bioinformatics, 4, 2. doi: 10.1186/1471-2105-4-2

  3. Bakshi M, Oelmüller R. 2014. WRKY transcription factors: Jack of many trades in plants. Plant Signal Behav. 9: e27700

  4. Bartels A, Han Q, Nair P, Stacey L, Gaynier H, Mosley M, Huang QQ, Pearson JK, Hsieh TF, An YC, Xiao W. 2018. Dynamic DNA methylation in plant growth and development. Int. J. Mol. Sci. 19:2144

  5. Chen H, Lai Z, Shi J, Xiao Y, Chen Z, Xu X. 2010. Roles of Arabidopsis WRKY 18, WRKY40 and WRKY60 transcription factors in plant responses to abscisic acid and abiotic stress. BMC Plant Biol. 10:281

  6. Chen J, Nolan TM, Ye H, Zhang M, Tong H, Xin P, Chu J, Chu C, Li Z, Yin Y. 2017. Arabidopsis WRKY46, WRKY54, and WRKY70 transcription factors are involved in brassinosteroid-regulated plant growth and drought responses. Plant Cell 29: 1425–1439

  7. Chen L, Song Y, Li S, Zhang L, Zou C, Yu D. 2012. The role of WRKY transcription factors in plant abiotic stresses. Biochim. Biophys. Acta Gene Regul. Mech. 1819: 120–128

  8. Chou KC, Shen HB. 2007. Recent progress in protein subcellular location prediction. Anal. Biochem. 370: 1–16

  9. Chow CN, Zheng HQ, Wu NY, Chien CH, Huang HD, Lee TY, Chiang-Hsieh YF, Hou PF, Yang TYI, Chang WC. 2015. PlantPAN 2.0: an update of plant promoter analysis navigator for reconstructing transcriptional regulatory networks in plants. Nucleic Acids Res. 44: D1154–60

  10. D’Haeseleer P. 2005. How does gene expression clustering work? Nat. Biotechnol. 23: 1499–501

  11. Eulgem T, Rushton PJ, Robatzek S, Somssich IE. 2000. The WRKY superfamily of plant transcription factors. Trends Plant Sci. 5: 199–206

  12. Finn RD, Coggill P, Eberhardt RY, Eddy SR, Mistry J, Mitchell AL, Potter SC, Punta M, Qureshi M, Sangrador-Vegas A, Salazor GA, et al. 2016. The Pfam protein families database: towards a more sustainable future. Nucleic Acids Res. 44: D279–D285

  13. Finnegan EJ, Peacock WJ, Dennis ES. 2000. DNA methylation, a key regulator of plant development and other processes. Curr. Opin. Genet. Dev. 10: 217–223

  14. Gao QM, Venugopal S., Navarre D, Kachroo A. 2011. Low oleic acid-derived repression of jasmonic acid-inducible defense responses requires the WRKY50 and WRKY51 proteins. Plant, 464–476

  15. Gasteiger E, Hoogland C, Gattiker A, Duvaud S, Wilkins MR, Appel RD, Bairoch A. 2005. Protein identification and analysis tools on the ExPASy server, In: JM Walker, ed., The Proteomics Protocols Handbook, Humana Press pp. 571–607

  16. Goodstein DM, Shu S, Howson R, Neupane R, Hayes RD, Fazo J, et al. 2012. Phytozome: a comparative platform for green plant genomics. Nucleic Acids Res. 40: D1178–D1186

  17. Hall TA. 1999. BioEdit: a user-friendly biological sequence alignment editor and analysis program for Windows 95/98/NT. Nucleic Acids Symp. Ser. 41: 95–98

  18. Lamesch P, Berardini TZ, Li D, Swarbreck D, Wilks C, Sasidharan R, Muller R, Dreher K, Alexander DL, Garcia-Hernandez M, et al. 2012. The Arabidopsis Information Resource (TAIR): improved gene annotation and new tools. Nucleic Acids Res. 40: D1202–10

  19. Li J, Brader G, Kariola T, Tapio Palva E. 2006. WRKY70 modulates the selection of signaling pathways in plant defense. Plant J. 46: 477–491

  20. Li R, Liang F, Li M, Zou D, Sun S, Zhao Y, Zhao W, Bao Y, Xiao J, Zhang Z. 2018. MethBank 3.0: a database of DNA methylomes across a variety of species. Nucleic Acids Res. 46: D288–D295

  21. Nilsson L, Müller R, Nielsen TH. 2010. Dissecting the plant transcriptome and the regulatory responses to phosphate deprivation. Physiol. Plant 139: 129–143

  22. Pandey SP, Roccaro M, Schön M, Logemann E, Somssich IE. 2010. Transcriptional reprogramming regulated by WRKY 18 and WRKY40 facilitates powdery mildew infection of Arabidopsis. Plant J. 64: 912–923

  23. Raghothama KG. 1999. Phosphate acquisition. Annu. Rev. Plant Biol. 50: 665–693

  24. Rhee SY, Mutwil M. 2014. Towards revealing the functions of all genes in plants. Trends Plant Sci. 19: 212–221

  25. Rushton PJ, Somssich IE, Ringler P, Shen QJ. 2010. WRKY transcription factors. Trends Plant Sci. 15: 247–258

  26. Saitou N, Nei M. 1987. The neighbor-joining method: A new method for reconstructing phylogenetic trees. Mol. Biol. Evol. 4: 406–425

  27. Shannon P, Markiel A, Ozier O, Baliga NS, Wang JT, Ramage D, Amin N, Schwikowski B, Ideker T. 2003. Cytoscape: a software environment for integrated models of biomolecular interaction networks. Genome Res. 13: 2498–2504

  28. Takuno S, Ran JH, Gaut BS. 2016. Evolutionary patterns of genic DNA methylation vary across land plants. Nat. Plants 2: 15222

  29. Tesfaye M, Liu J, Allan DL, Vance CP. 2007. Genomic and genetic control of phosphate stress in legumes. Plant Physiol. 144: 594–603

  30. Toronen P, Medlar A, Holm L. 2018. PANNZER2: A rapid functional annotation webserver. Nucl. Acids Res. 46: W84–W88

  31. van Dam S, Võsa U, van der Graaf A, Franke L, de Magalhaes JP. 2018. Gene co-expression analysis for functional classification and gene-disease predictions. Brief Bioinform. 19: 575–592

  32. Vance CP, Uhde-Stone C, Allan DL. 2003. Phosphorus acquisition and use: critical adaptations by plants for securing a nonrenewable resource. New Phytol. 157: 423–447

  33. Wang Q, Wang J, Yang Y, Du W, Zhang D, Yu D, Cheng H. 2016. A genome-wide expression profile analysis reveals active genes and pathways coping with phosphate starvation in soybean. BMC Genomics 17: 192

  34. Wasaki J, Yonetani R, Kuroda S, Shinano T, Yazaki J, Fujii F, Shimbo K, Yamamoto K, Sakata K, et al. 2003. Transcriptomic analysis of metabolic changes by phosphorus stress in rice plant roots. Plant Cell Environ. 26: 1515–1523

  35. Wu LF, Hughes TR, Davierwala AP, Robinson MD, Stoughton R, Altschuler SJ. 2002. Large-scale prediction of Saccharomyces cerevisiae gene function using overlapping transcriptional clusters. Nature Genet. 31: 255

  36. Yadav BS, Mani A. 2019. Analysis of bHLH coding genes of Cicer arietinum during heavy metal stress using biological network. Physiol. Mol. Biol. Plants 25: 113,

  37. Yang Y, Zhou Y, Chi Y, Fan B, Chen Z. 2017. Characterization of soybean WRKY gene family and identification of soybean WRKY genes that promote resistance to soybean Cyst nematode. Sci. Rep. 7: 17804

  38. Youens-Clark K, Buckler E, Casstevens T, Chen C, Declerck G, Derwent P, Dharmawardhana P, Jaiswal P, Kersey P, Karthikeyan AS, et al. 2011. Gramene database in 2010: updates and extensions. Nucleic Acids Res. 39: D1085–94

  39. Yu CS, Chen YC, Lu CH, Hwang JK. 2006. Prediction of protein subcellular localization. Proteins 64: 643–651

  40. Zeng H, Wang G, Zhang Y, Hu X, Pi E, Zhu Y, Wang H, Du L. 2016. Genome-wide identification of phosphate-deficiency-responsive genes in soybean roots by high-throughput sequencing. Plant Soil 398: 207–227

  41. Zuo YC, Li QZ. 2011. Identification of TATA and TATA-less promoters in plant genomes by integrating diversity measure, GC-Skew and DNA geometric flexibility. Genomics 97: 112–20

Download references

Author information

Correspondence to Ertugrul Filiz.

Additional information

Compliance with ethical standards Conflict of interest

The authors declare that they have no conflict of interests.

Rights and permissions

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

Kurt, F., Filiz, E. Biological Network Analyses of WRKY Transcription Factor Family in Soybean (Glycine max) under Low Phosphorus Treatment. J. Crop Sci. Biotechnol. 23, 127–136 (2020).

Download citation

Key words

  • Bioinformatics
  • co-expression
  • Glycine max
  • phosphorus
  • WRKY