ArticlePlant physiology2012
Exploring tomato gene functions based on coexpression modules using graph clustering and differential coexpression approaches.
Article in Plant physiology, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 33 papers, 1 of them a synthesis that pooled it.
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Who cites it
33 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Integration of meta-analysis, machine learning and systems biology approach for investigating the transcriptomic response to drought stress in Populus species.Scientific reports · 2023Pooled it
- Decoding Nano-Bio Interactions: Gene Regulatory Networks in Advanced Drug Loading.Methods in molecular biology (Clifton, N.J.) · 2027Article
- Organ-level gene-regulatory networks inferred from transcriptomic data reveal context-specific regulation and highlight novel regulators of ripening and ABA-mediated responses in tomato.Plant communications · 2025Article
- Development of phytochemical genomics: From decoding metabolome to functional genomics and biotechnology of plant metabolism.Proceedings of the Japan Academy. Series B, Physical and biological sciences · 2025Review
- Soybean gene co-expression network analysis identifies two co-regulated gene modules associated with nodule formation and development.Molecular plant pathology · 2023Article
- NetREx: Network-based Rice Expression Analysis Server for abiotic stress conditions.Database : the journal of biological databases and curation · 2022Article
- Gene Co-Expression Network Tools and Databases for Crop Improvement.Plants (Basel, Switzerland) · 2022Review
- The metabolic changes that effect fruit quality during tomato fruit ripening.Molecular horticulture · 2022Review
- Review
- Comparative co-expression network analysis extracts thePlant biotechnology (Tokyo, Japan) · 2019Article
- Whirly (Why) transcription factors in tomato (Solanum lycopersicum L.): genome-wide identification and transcriptional profiling under drought and salt stresses.Molecular biology reports · 2019Article
- Co-regulation analysis of co-expressed modules under cold and pathogen stress conditions in tomato.Molecular biology reports · 2018Article
- Comparative transcriptomics with self-organizing map reveals cryptic photosynthetic differences between two accessions of North American Lake cress.Scientific reports · 2018Article
- A Systems Analysis With "Simplified Source-Sink Model" Reveals Metabolic Reprogramming in a Pair of Source-to-Sink Organs During Early Fruit Development in Tomato by LED Light Treatments.Frontiers in plant science · 2018Article
- CytoCluster: A Cytoscape Plugin for Cluster Analysis and Visualization of Biological Networks.International journal of molecular sciences · 2017Article
- Topological features of a gene co-expression network predict patterns of natural diversity in environmental response.Proceedings. Biological sciences · 2017Article
- Comparative transcriptome analyses of flower development in four species of Achimenes (Gesneriaceae).BMC genomics · 2017Article
- Differential Coexpression Analysis Reveals Extensive Rewiring of Arabidopsis Gene Coexpression in Response to Pseudomonas syringae Infection.Scientific reports · 2016Article
- Integrated bioinformatics to decipher the ascorbic acid metabolic network in tomato.Plant molecular biology · 2016Article
- An RNA-Seq-based reference transcriptome for Citrus.Plant biotechnology journal · 2016Article
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7 authors.
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Abstract
Gene-to-gene coexpression analysis provides fundamental information and is a promising approach for predicting unknown gene functions in plants. We investigated various associations in the gene expression of tomato (Solanum lycopersicum) to predict unknown gene functions in an unbiased manner. We obtained more than 300 microarrays from publicly available databases and our own hybridizations, and here, we present tomato coexpression networks and coexpression modules. The topological characteristics of the networks were highly heterogenous. We extracted 465 total coexpression modules from the data set by graph clustering, which allows users to divide a graph effectively into a set of clusters. Of these, 88% were assigned systematically by Gene Ontology terms. Our approaches revealed functional modules in the tomato transcriptome data; the predominant functions of coexpression modules were biologically relevant. We also investigated differential coexpression among data sets consisting of leaf, fruit, and root samples to gain further insights into the tomato transcriptome. We now demonstrate that (1) duplicated genes, as well as metabolic genes, exhibit a small but significant number of differential coexpressions, and (2) a reversal of gene coexpression occurred in two metabolic pathways involved in lycopene and flavonoid biosynthesis. Independent experimental verification of the findings for six selected genes was done using quantitative real-time polymerase chain reaction. Our findings suggest that differential coexpression may assist in the investigation of key regulatory steps in metabolic pathways. The approaches and results reported here will be useful to prioritize candidate genes for further functional genomics studies of tomato metabolism.
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