Abstact
Plant sumoylation research has seen significant advances in recent years, particularly since high-throughput proteomic strategies have enabled the discovery of more than one thousand SUMO targets. In the present chapter, we update the previously reported SUMO (small ubiquitin-related modifier) gene network (SGN) to its v4 iteration. SGN is a curated assembly of Arabidopsis thaliana genes that have been functionally associated with sumoylation, from SUMO pathway components to targets and interactors. The enclosed tutorial helps interpret and manage these datasets and details bioinformatic tools that can be used for in silico-based hypothesis generation. The latter include tools for sumoylation site prediction, comparative genomics, and gene network analysis.
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References
Castro PH, Tavares RM, Bejarano ER et al (2012) SUMO, a heavyweight player in plant abiotic stress responses. Cell Mol Life Sci 69(19):3269–3283
Srivastava M, Sadanandom A, Srivastava AK (2021) Towards understanding the multifaceted role of SUMOylation in plant growth and development. Physiol Plant 171(1):77–85
Sharma M, Fuertes D, Perez-Gil J et al (2021) SUMOylation in phytopathogen interactions: balancing invasion and resistance. Front Cell Dev Biol 9:703795
Castro PH, Santos MA, Magalhaes AP et al (2016) Bioinformatics tools for exploring the SUMO Gene Network. Methods Mol Biol 1450:285–301
Provart NJ, Brady SM, Parry G et al (2021) Anno genominis XX: 20 years of Arabidopsis genomics. Plant Cell 33(4):832–845
Zheng Y, Schumaker KS, Guo Y (2012) Sumoylation of transcription factor MYB30 by the small ubiquitin-like modifier E3 ligase SIZ1 mediates abscisic acid response in Arabidopsis thaliana. Proc Natl Acad Sci U S A 109(31):12822–12827
Miura K, Jin JB, Lee J et al (2007) SIZ1-mediated sumoylation of ICE1 controls CBF3/DREB1A expression and freezing tolerance in Arabidopsis. Plant Cell 19(4):1403–1414
Gareau JR, Lima CD (2010) The SUMO pathway: emerging mechanisms that shape specificity, conjugation and recognition. Nat Rev Mol Cell Biol 11(12):861–871
Elrouby N, Bonequi MV, Porri A et al (2013) Identification of Arabidopsis SUMO-interacting proteins that regulate chromatin activity and developmental transitions. Proc Natl Acad Sci U S A 110(49):19956–19961
Miller MJ, Barrett-Wilt GA, Hua Z et al (2010) Proteomic analyses identify a diverse array of nuclear processes affected by small ubiquitin-like modifier conjugation in Arabidopsis. Proc Natl Acad Sci U S A 107(38):16512–16517
Miller MJ, Scalf M, Rytz TC et al (2013) Quantitative proteomics reveals factors regulating RNA biology as dynamic targets of stress-induced SUMOylation in Arabidopsis. Mol Cell Proteomics 12(2):449–463
Elrouby N, Coupland G (2010) Proteome-wide screens for small ubiquitin-like modifier (SUMO) substrates identify Arabidopsis proteins implicated in diverse biological processes. Proc Natl Acad Sci U S A 107(40):17415–17420
Van Bel M, Silvestri F, Weitz EM et al (2021) PLAZA 5.0: extending the scope and power of comparative and functional genomics in plants. Nucleic Acids Res 50:gkab1024
Toufighi K, Brady SM, Austin R et al (2005) The botany array resource: e-Northerns, expression angling, and promoter analyses. Plant J 43(1):153–163
Franz M, Rodriguez H, Lopes C et al (2018) GeneMANIA update 2018. Nucleic Acids Res 46(W1):W60–W64
Rhee SY, Beavis W, Berardini TZ et al (2003) The Arabidopsis Information Resource (TAIR): a model organism database providing a centralized, curated gateway to Arabidopsis biology, research materials and community. Nucleic Acids Res 31(1):224–228
Goodstein DM, Shu S, Howson R et al (2012) Phytozome: a comparative platform for green plant genomics. Nucleic Acids Res 40(D1):D1178–D1186
Beauclair G, Bridier-Nahmias A, Zagury JF et al (2015) JASSA: a comprehensive tool for prediction of SUMOylation sites and SIMs. Bioinformatics 31(21):3483–3491
Zhao Q, Xie Y, Zheng Y et al (2014) GPS-SUMO: a tool for the prediction of sumoylation sites and SUMO-interaction motifs. Nucleic Acids Res 42(W1):W325–W330
Smoot ME, Ono K, Ruscheinski J et al (2011) Cytoscape 2.8: new features for data integration and network visualization. Bioinformatics 27(3):431–432
Maere S, Heymans K, Kuiper M (2005) BiNGO: a Cytoscape plug-in to assess overrepresentation of gene ontology categories in biological networks. Bioinformatics 21(16):3448–3449
Bindea G, Mlecnik B, Hackl H et al (2009) ClueGO: a Cytoscape plug-in to decipher functionally grouped gene ontology and pathway annotation networks. Bioinformatics 25(8):1091–1093
Acknowledgments
H.A. was supported by national funds through FCT, Fundação para a Ciência e a Tecnologia, I.P., within the scope of the Stimulus of Scientific Employment-Individual Support [CEECIND/00399/2017/CP1423/CT0004]. P.H.C. was supported by FCT/MCTES, FEDER, and COMPETE-POCI – Programa Operacional Competividade e Internacionalização [PTDC/BAA-AGR/31122/2017, POCI-01-0145-FEDER- 031122].
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Castro, P.H., Santos, M.Â., Magalhães, A.P., Tavares, R.M., Azevedo, H. (2023). Bioinformatic Tools for Exploring the SUMO Gene Network: An Update. In: Lois, L.M., Trujillo, M. (eds) Plant Proteostasis. Methods in Molecular Biology, vol 2581. Humana, New York, NY. https://doi.org/10.1007/978-1-0716-2784-6_26
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DOI: https://doi.org/10.1007/978-1-0716-2784-6_26
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