Tomato (Solanum lycopersicum) is a globally important crop, yet the gene regulatory networks (GRNs) controlling 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-seq libraries using the GENIE3 algorithm. We refined these networks with 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, as well as SlABF2, SlABF3 and SlABF5 in abscisic acid response in leaves. Additionally, 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 used DNA Affinity Purification Sequencing for SlGBF3, confirming the accuracy of our GRNs. 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.
Fernández et al. (Mon,) studied this question.