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Detalle de: Organ-level gene regulatory network models enable the identification of central transcription factors in Solanum lycopersicum

Title Organ-level gene regulatory network models enable the identification of central transcription factors in Solanum lycopersicum
Abstract

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 sequences in open chromatin sites. Our networks confirmed key TFs, including TOMATO AGAMOUS LIKE 1 and RIPENING INHIBITOR in fruit ripening, as well as ABF3 and ABF5 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 ( Sl GBF3) in ABA-related and drought pathways. To further validate the GRNs, we used DNA Affinity Purification Sequencing (DAP-seq) for Sl GBF3, 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 . Highlight We developed organ-level gene regulatory networks for tomato using 10,000+ RNA-seq libraries, validated predictions and identified new regulators of fruit ripening and ABA response. These networks are available at https://plantaeviz.tomsbiolab.com/tomviz .

Apa Reference Fernández, J.D., Navarro-Payá, D., Santiago, A., Canan, J., Contreras-Riquelme, S., Cerda, A., Moyano, T.C., Melet, L., Johnson, N.R., Canales, J., Álvarez, J.M., Matus, J.T. & Vidal, E.A. (2025). Organ-level gene regulatory network models enable the identification of central transcription factors in Solanum lycopersicum. 10.1101/2025.03.26.645553
Doi 10.1101/2025.03.26.645553
Publication Date 31 Mar 2025
Publication Type Preprint
Researcher David Navarro Payá
Ontology Transcriptomics, RNA Sequencing (RNA-seq), Expression Profiling, Gene regulatory networks, Regulatory biology, Chromatin accessibility, Drug Discovery and design, Climate change adaptation
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