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Biology subjects

Contreras-Riquelme, S.

Publications and source records attributed to Contreras-Riquelme, S..

2 recordsLinked to original sources

Organ-level Gene Regulatory Network models enable the identification of central transcription factors in Solanum lycopersicum

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 (SlGBF3) in ABA-related and drought pathways. To further validate the GRNs, we used DNA Affinity Purification Sequencing (DAP-seq) 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. HighlightWe 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.

systems biology↗

Automated generation of context-specific Gene Regulatory Networks with a weighted approach in D. melanogaster

MotivationThe regulation of gene expression is a key factor in the development and maintenance of life in all organisms. This process is carried out mainly through the action of transcription factors (TFs), although other actors such as ncRNAs are involved. In this work, we propose a new method to construct Gene Regulatory Networks (GRNs) depicting regulatory events in a certain context for Drosophila melanogaster. Our approach is based on known relationships between epigenetics and the activity of transcription factors. ResultsWe developed method, Tool for Weighted Epigenomic Networks in D. melanogaster (Fly T-WEoN), which generates GRNs starting from a reference network that contains all known gene regulations in the fly. Regulations that are unlikely taking place are removed by applying a series of knowledge-based filters. Each of these filters is implemented as an independent module that considers a type of experimental evidence, including DNA methylation, chromatin accessibility, histone modifications, and gene expression. Fly T-WEoN is based on heuristic rules that reflect current knowledge on gene regulation in D. melanogaster obtained from literature. Experimental data files can be generated with several standard procedures and used solely when and if available.Fly T-WEoN is available as a Cytoscape application that permits integration with other tools, and facilitates downstream network analysis. In this work, we first demonstrate the reliability of our method to then provide a relevant application case of our tool: early development of D. melanogaster. AvailabilityFly T-WEoN, together with its step-by-step guide is available at https://weon.readthedocs.io Contactalberto.martin@umayor.cl

bioinformatics↗