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.
Keywords: Solanum lycopersicum; drought; gene-regulatory network; ripening; transcriptional regulation.
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