ArticlePlant communications2025
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.
Article in Plant communications, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
What it found
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Who cites it
6 citing papers in PubMed.
- From knowledge graph to topological data analysis: a novel framework to analyze gene regulatory networks for tomato-multi-pathogen interactions.The New phytologist · 2026Article
- Deciphering Cell-Type-Specific Transcriptional Regulation in Tomato Leaves Through Ensemble Machine Learning and Single-Cell Transcriptomics.Plants (Basel, Switzerland) · 2026Article
- Decoding plant physiology through systems biology: Integrative multi-omics and computational perspectives for next-generation crop design.Plant communications · 2026Review
- Integrated Gene Regulatory Network Analysis Reveals Coordinated Transcriptional Reprogramming in thePlants (Basel, Switzerland) · 2026Article
- Rewiring of auxin and MAPK signaling is associated with contrasting shoestring and fern-like manifestations in ToBRFV-A134T-infected tomato.Frontiers in plant science · 2026Article
- Post-transcriptional regulation of light-stress responses and predictive modeling in vegetableFrontiers in plant science · 2026Review
Corrections and comments
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Authors and funding
14 authors.
Funding
Abstract
Tomato (Solanum lycopersicum) is a globally important crop, yet the gene-regulatory networks (GRNs) that control its gene expression remain poorly understood. In this study, we constructed GRNs for roots, leaves, flowers, fruits, and seeds by inferring transcription factor (TF)-target interactions from over 10 000 RNA-sequencing libraries using the GENIE3 algorithm. We refined these networks using gene co-expression data and computational predictions of TF binding sites. Our networks confirmed key regulators in important processes, including TOMATO AGAMOUS LIKE 1 and RIPENING INHIBITOR in fruit ripening, and SlABF2, SlABF3, and SlABF5 in abscisic acid (ABA) response in leaves. In addition, we identified novel candidate regulators, including AUXIN RESPONSE FACTOR 2A and ETHYLENE RESPONSE FACTOR E2 in fruit ripening and G-BOX BINDING FACTOR 3 (SlGBF3) in ABA-related and drought pathways. To further validate the GRNs, we performed DNA affinity purification sequencing for SlGBF3 and confirmed the accuracy of our GRN predictions. This study provides a valuable resource for dissecting transcriptional regulation in tomato, with potential applications in crop improvement. The GRNs are publicly accessible through a user-friendly web platform at https://plantaeviz.tomsbiolab.com/tomviz.
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Registered trials
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