, Volume 249, Issue 5, pp 1487–1501 | Cite as

Gene co-expression network analysis identifies trait-related modules in Arabidopsis thaliana

  • Wei LiuEmail author
  • Liping Lin
  • Zhiyuan Zhang
  • Siqi Liu
  • Kuan Gao
  • Yanbin Lv
  • Huan Tao
  • Huaqin HeEmail author
Original Article


Main conclusion

A comprehensive network of the Arabidopsis transcriptome was analyzed and may serve as a valuable resource for candidate gene function investigations. A web tool to explore module information was also provided.

Arabidopsis thaliana is a widely studied model plant whose transcriptome has been substantially profiled in various tissues, development stages and other conditions. These data can be reused for research on gene function through a systematic analysis of gene co-expression relationships. We collected microarray data from National Center for Biotechnology Information Gene Expression Omnibus, identified modules of co-expressed genes and annotated module functions. These modules were associated with experiments/traits, which provided potential signature modules for phenotypes. Novel heat shock proteins were implicated according to guilt by association. A higher-order module networks analysis suggested that the Arabidopsis network can be further organized into 15 meta-modules and that a chloroplast meta-module has a distinct gene expression pattern from the other 14 meta-modules. A comparison with the rice transcriptome revealed preserved modules and KEGG pathways. All the module gene information was available from an online tool at Our findings provide a new source for future gene discovery in Arabidopsis.


Rice Conservation Hub gene Transcriptome 



Gene co-expression network


Weighted gene co-expression network analysis


National Centre for Biotechnology Information


Gene Expression Omnibus


Relative standard deviation


Gene ontology


Kyoto Encyclopedia of Genes and Genomes



There are so many insightful literatures about gene co-expression analysis. The authors apologize that not all related studies were cited due to lack of space.


This work was supported in part by the National Natural Science Foundation of China (Grant numbers 31270454 and 81502091) and Open Project of Key laboratory of Loquat Germplasm Innovation and Utilization, Putian University, Fujian Province (Grant number 2017003).

Compliance with ethical standards

Conflicts of interest

The authors have no conflicts of interest to declare.

Supplementary material

425_2019_3102_MOESM1_ESM.xlsx (595 kb)
Supplementary material 1 (xlsx 595 kb)


  1. Agarwal S, Deane CM, Porter MA, Jones NS (2010) Revisiting date and party hubs: novel approaches to role assignment in protein interaction networks. PLoS Comput Biol 6(6):e1000817. CrossRefPubMedPubMedCentralGoogle Scholar
  2. Amrine KC, Blanco-Ulate B, Cantu D (2015) Discovery of core biotic stress responsive genes in Arabidopsis by weighted gene co-expression network analysis. PLoS ONE 10(3):e0118731. CrossRefPubMedPubMedCentralGoogle Scholar
  3. Aoki K, Ogata Y, Shibata D (2007) Approaches for extracting practical information from gene co-expression networks in plant biology. Plant Cell Physiol 48(3):381–390. CrossRefPubMedGoogle Scholar
  4. Aoki Y, Okamura Y, Tadaka S, Kinoshita K, Obayashi T (2016) ATTED-II in 2016: a plant coexpression database towards lineage-specific coexpression. Plant Cell Physiol 57(1):e5. CrossRefGoogle Scholar
  5. Banti V, Mafessoni F, Loreti E, Alpi A, Perata P (2010) The heat-inducible transcription factor HsfA2 enhances anoxia tolerance in Arabidopsis. Plant Physiol 152(3):1471–1483. CrossRefPubMedPubMedCentralGoogle Scholar
  6. Batada NN, Hurst LD, Tyers M (2006) Evolutionary and physiological importance of hub proteins. PLoS Comput Biol 2(7):e88. CrossRefPubMedPubMedCentralGoogle Scholar
  7. Bolstad BM, Irizarry RA, Astrand M, Speed TP (2003) A comparison of normalization methods for high density oligonucleotide array data based on variance and bias. Bioinformatics 19(2):185–193CrossRefGoogle Scholar
  8. Boruc J, Van den Daele H, Hollunder J, Rombauts S, Mylle E, Hilson P, Inze D, De Veylder L, Russinova E (2010) Functional modules in the Arabidopsis core cell cycle binary protein–protein interaction network. Plant Cell 22(4):1264–1280. CrossRefPubMedPubMedCentralGoogle Scholar
  9. Chang X, Xu T, Li Y, Wang K (2013) Dynamic modular architecture of protein-protein interaction networks beyond the dichotomy of ‘date’ and ‘party’ hubs. Sci Rep 3:1691. CrossRefPubMedPubMedCentralGoogle Scholar
  10. Chang W, Cheng J, Allaire JJ, Xie Y, McPherson J (2015) Shiny: web application framework for R. R package version 011 1(4):106Google Scholar
  11. Chiu RS, Pan S, Zhao R, Gazzarrini S (2016) ABA-dependent inhibition of the ubiquitin proteasome system during germination at high temperature in Arabidopsis. Plant J 88(5):749–761. CrossRefPubMedGoogle Scholar
  12. De Preter K, Barriot R, Speleman F, Vandesompele J, Moreau Y (2008) Positional gene enrichment analysis of gene sets for high-resolution identification of overrepresented chromosomal regions. Nucleic Acids Res 36(7):e43. CrossRefPubMedPubMedCentralGoogle Scholar
  13. De Vleesschauwer D, Xu J, Hofte M (2014) Making sense of hormone-mediated defense networking: from rice to Arabidopsis. Front Plant Sci 5:611. CrossRefPubMedPubMedCentralGoogle Scholar
  14. Dietz KJ, Jacquot JP, Harris G (2010) Hubs and bottlenecks in plant molecular signalling networks. New Phytol 188(4):919–938. CrossRefGoogle Scholar
  15. Esfandiari E, Jin Z, Abdeen A, Griffiths JS, Western TL, Haughn GW (2013) Identification and analysis of an outer-seed-coat-specific promoter from Arabidopsis thaliana. Plant Mol Biol 81(1–2):93–104. CrossRefPubMedGoogle Scholar
  16. Feltus FA, Ficklin SP, Gibson SM, Smith MC (2013) Maximizing capture of gene co-expression relationships through pre-clustering of input expression samples: an Arabidopsis case study. BMC Syst Biol 7:44. CrossRefPubMedPubMedCentralGoogle Scholar
  17. Ficklin SP, Feltus FA (2011) Gene coexpression network alignment and conservation of gene modules between two grass species: maize and rice. Plant Physiol 156(3):1244–1256. CrossRefPubMedPubMedCentralGoogle Scholar
  18. Ficklin SP, Dunwoodie LJ, Poehlman WL, Watson C, Roche KE, Feltus FA (2017) Discovering condition-specific gene co-expression patterns using gaussian mixture models: a cancer case study. Sci Rep 7(1):8617. CrossRefPubMedPubMedCentralGoogle Scholar
  19. Gendron JM, Pruneda-Paz JL, Doherty CJ, Gross AM, Kang SE, Kay SA (2012) Arabidopsis circadian clock protein, TOC1, is a DNA-binding transcription factor. Proc Natl Acad Sci USA 109(8):3167–3172. CrossRefPubMedGoogle Scholar
  20. Giorgi FM, Bolger AM, Lohse M, Usadel B (2010) Algorithm-driven artifacts in median polish summarization of microarray data. BMC Bioinform 11:553. CrossRefGoogle Scholar
  21. Giorgi FM, Del Fabbro C, Licausi F (2013) Comparative study of RNA-seq- and microarray-derived coexpression networks in Arabidopsis thaliana. Bioinformatics 29(6):717–724. CrossRefPubMedGoogle Scholar
  22. He F, Maslov S (2016) Pan- and core- network analysis of co-expression genes in a model plant. Sci Rep 6:38956. CrossRefPubMedPubMedCentralGoogle Scholar
  23. He F, Yoo S, Wang D, Kumari S, Gerstein M, Ware D, Maslov S (2016) Large-scale atlas of microarray data reveals the distinct expression landscape of different tissues in Arabidopsis. Plant J 86(6):472–480. CrossRefPubMedGoogle Scholar
  24. Huang DW, Sherman BT, Lempicki RA (2009) Bioinformatics enrichment tools: paths toward the comprehensive functional analysis of large gene lists. Nucleic Acids Res 37(1):1–13. CrossRefGoogle Scholar
  25. Huber W, Carey VJ, Gentleman R, Anders S, Carlson M, Carvalho BS, Bravo HC, Davis S, Gatto L, Girke T, Gottardo R, Hahne F, Hansen KD, Irizarry RA, Lawrence M, Love MI, MacDonald J, Obenchain V, Oles AK, Pages H, Reyes A, Shannon P, Smyth GK, Tenenbaum D, Waldron L, Morgan M (2015) Orchestrating high-throughput genomic analysis with Bioconductor. Nat Methods 12(2):115–121. CrossRefPubMedPubMedCentralGoogle Scholar
  26. Khan D, Millar JL, Girard IJ, Chan A, Kirkbride RC, Pelletier JM, Kost S, Becker MG, Yeung EC, Stasolla C, Goldberg RB, Harada JJ, Belmonte MF (2015) Transcriptome atlas of the Arabidopsis funiculus—a study of maternal seed subregions. Plant J 82(1):41–53. CrossRefPubMedGoogle Scholar
  27. Kliebenstein D (2004) Secondary metabolites and plant/environment interactions: a view through Arabidopsis thaliana tinged glasses. Plant Cell Environ 27(6):675–684CrossRefGoogle Scholar
  28. Lamb J, Crawford ED, Peck D, Modell JW, Blat IC, Wrobel MJ, Lerner J, Brunet JP, Subramanian A, Ross KN, Reich M, Hieronymus H, Wei G, Armstrong SA, Haggarty SJ, Clemons PA, Wei R, Carr SA, Lander ES, Golub TR (2006) The Connectivity Map: using gene-expression signatures to connect small molecules, genes, and disease. Science 313(5795):1929–1935. CrossRefPubMedGoogle Scholar
  29. Langfelder P, Horvath S (2008) WGCNA: an R package for weighted correlation network analysis. BMC Bioinform 9:559. CrossRefGoogle Scholar
  30. Langfelder P, Luo R, Oldham MC, Horvath S (2011) Is my network module preserved and reproducible? PLoS Comput Biol 7(1):e1001057. CrossRefPubMedPubMedCentralGoogle Scholar
  31. Lee T, Yang S, Kim E, Ko Y, Hwang S, Shin J, Shim JE, Shim H, Kim H, Kim C, Lee I (2015) AraNet v2: an improved database of co-functional gene networks for the study of Arabidopsis thaliana and 27 other nonmodel plant species. Nucleic Acids Res 43:996–1002. (database issue) CrossRefGoogle Scholar
  32. Li Y, Pearl SA, Jackson SA (2015) Gene networks in plant biology: approaches in reconstruction and analysis. Trends Plant Sci 20(10):664–675. CrossRefPubMedGoogle Scholar
  33. Lloyd JP, Seddon AE, Moghe GD, Simenc MC, Shiu SH (2015) Characteristics of plant essential genes allow for within- and between-species prediction of lethal mutant phenotypes. Plant Cell 27(8):2133–2147. CrossRefPubMedPubMedCentralGoogle Scholar
  34. Ma B, Chen S, Zhang J (2010) Ethylene signaling in rice. Chin Sci Bull 55(21):2204–2210CrossRefGoogle Scholar
  35. Mao L, Van Hemert JL, Dash S, Dickerson JA (2009) Arabidopsis gene co-expression network and its functional modules. BMC Bioinform 10:346. CrossRefGoogle Scholar
  36. Movahedi S, Van Bel M, Heyndrickx KS, Vandepoele K (2012) Comparative co-expression analysis in plant biology. Plant Cell Environ 35(10):1787–1798. CrossRefPubMedGoogle Scholar
  37. Mueller AJ, Canty-Laird EG, Clegg PD, Tew SR (2017) Cross-species gene modules emerge from a systems biology approach to osteoarthritis. NPJ Syst Biol Appl 3:13. CrossRefPubMedPubMedCentralGoogle Scholar
  38. Mutwil M, Usadel B, Schutte M, Loraine A, Ebenhoh O, Persson S (2010) Assembly of an interactive correlation network for the Arabidopsis genome using a novel heuristic clustering algorithm. Plant Physiol 152(1):29–43. CrossRefPubMedPubMedCentralGoogle Scholar
  39. Mutwil M, Klie S, Tohge T, Giorgi FM, Wilkins O, Campbell MM, Fernie AR, Usadel B, Nikoloski Z, Persson S (2011) PlaNet: combined sequence and expression comparisons across plant networks derived from seven species. Plant Cell 23(3):895–910. CrossRefPubMedPubMedCentralGoogle Scholar
  40. Nishiyama S, Onoue N, Kono A, Sato A, Yonemori K, Tao R (2018) Characterization of a gene regulatory network underlying astringency loss in persimmon fruit. Planta 247(3):733–743. CrossRefPubMedGoogle Scholar
  41. Oldham MC, Konopka G, Iwamoto K, Langfelder P, Kato T, Horvath S, Geschwind DH (2008) Functional organization of the transcriptome in human brain. Nat Neurosci 11(11):1271–1282CrossRefGoogle Scholar
  42. Penga J, Wang T, Huc J, Wang Y, Chen J (2016) Constructing networks of organelle functional modules in Arabidopsis. Curr Genom 17(5):427–438. CrossRefGoogle Scholar
  43. Pepper SD, Saunders EK, Edwards LE, Wilson CL, Miller CJ (2007) The utility of MAS5 expression summary and detection call algorithms. BMC Bioinform 8:273. CrossRefGoogle Scholar
  44. Pickett FB, Champagne MM, Meeks-Wagner DR (1996) Temperature-sensitive mutations that arrest Arabidopsis shoot development. Development 122(12):3799–3807PubMedGoogle Scholar
  45. Prasch CM, Sonnewald U (2013) Simultaneous application of heat, drought, and virus to Arabidopsis plants reveals significant shifts in signaling networks. Plant Physiol 162(4):1849–1866. CrossRefPubMedPubMedCentralGoogle Scholar
  46. Rajjou L, Belghazi M, Huguet R, Robin C, Moreau A, Job C, Job D (2006) Proteomic investigation of the effect of salicylic acid on Arabidopsis seed germination and establishment of early defense mechanisms. Plant Physiol 141(3):910–923. CrossRefPubMedPubMedCentralGoogle Scholar
  47. Rasmussen S, Barah P, Suarez-Rodriguez MC, Bressendorff S, Friis P, Costantino P, Bones AM, Nielsen HB, Mundy J (2013) Transcriptome responses to combinations of stresses in Arabidopsis. Plant Physiol 161(4):1783–1794. CrossRefPubMedPubMedCentralGoogle Scholar
  48. R Development Core Team (2013) R: a language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. Accessed 1 May 2018
  49. Ruprecht C, Proost S, Hernandez-Coronado M, Ortiz-Ramirez C, Lang D, Rensing SA, Becker JD, Vandepoele K, Mutwil M (2017) Phylogenomic analysis of gene co-expression networks reveals the evolution of functional modules. Plant J 90(3):447–465. CrossRefPubMedGoogle Scholar
  50. Schmid M, Davison TS, Henz SR, Pape UJ, Demar M, Vingron M, Scholkopf B, Weigel D, Lohmann JU (2005) A gene expression map of Arabidopsis thaliana development. Nat Genet 37(5):501–506. CrossRefGoogle Scholar
  51. Shaik R, Ramakrishna W (2013) Genes and co-expression modules common to drought and bacterial stress responses in Arabidopsis and rice. PLoS ONE 8(10):e77261. CrossRefPubMedPubMedCentralGoogle Scholar
  52. Usadel B, Obayashi T, Mutwil M, Giorgi FM, Bassel GW, Tanimoto M, Chow A, Steinhauser D, Persson S, Provart NJ (2009) Co-expression tools for plant biology: opportunities for hypothesis generation and caveats. Plant Cell Environ 32(12):1633–1651. CrossRefPubMedGoogle Scholar
  53. van Veen H, Vashisht D, Akman M, Girke T, Mustroph A, Reinen E, Hartman S, Kooiker M, van Tienderen P, Schranz ME, Bailey-Serres J, Voesenek LA, Sasidharan R (2016) Transcriptomes of eight Arabidopsis thaliana accessions reveal core conserved, genotype- and organ-specific responses to flooding stress. Plant Physiol 172(2):668–689. CrossRefPubMedPubMedCentralGoogle Scholar
  54. Vlot AC, Liu PP, Cameron RK, Park SW, Yang Y, Kumar D, Zhou F, Padukkavidana T, Gustafsson C, Pichersky E, Klessig DF (2008) Identification of likely orthologs of tobacco salicylic acid-binding protein 2 and their role in systemic acquired resistance in Arabidopsis thaliana. Plant J 56(3):445–456. CrossRefPubMedGoogle Scholar
  55. Wang F, Rong W, Wen J, Zhang W (2012a) Quantitative dissection of lipid degradation in rice seeds during accelerated aging. Plant Growth Regul 66(1):49–58CrossRefGoogle Scholar
  56. Wang S, Yin Y, Ma Q, Tang X, Hao D, Xu Y (2012b) Genome-scale identification of cell-wall related genes in Arabidopsis based on co-expression network analysis. BMC Plant Biol 12:138. CrossRefPubMedPubMedCentralGoogle Scholar
  57. Yang Y, Xu R, Ma CJ, Vlot AC, Klessig DF, Pichersky E (2008) Inactive methyl indole-3-acetic acid ester can be hydrolyzed and activated by several esterases belonging to the AtMES esterase family of Arabidopsis. Plant Physiol 147(3):1034–1045. CrossRefPubMedPubMedCentralGoogle Scholar
  58. Yim WC, Yu Y, Song K, Jang CS, Lee BM (2013) PLANEX: the plant co-expression database. BMC Plant Biol 13:83. CrossRefPubMedPubMedCentralGoogle Scholar
  59. Zhang B, Horvath S (2005) A general framework for weighted gene co-expression network analysis. Stat Appl Genet Mol Biol 4:Article17.
  60. Zheng X, Liu T, Yang Z, Wang J (2011) Large cliques in Arabidopsis gene coexpression network and motif discovery. J Plant Physiol 168(6):611–618. CrossRefPubMedGoogle Scholar

Copyright information

© Springer-Verlag GmbH Germany, part of Springer Nature 2019

Authors and Affiliations

  1. 1.School of Life SciencesFujian Agriculture and Forestry UniversityFuzhouPeople’s Republic of China

Personalised recommendations