Abstract
Many methods are now available to identify or predict the target genes of transcription factors (TFs) in plants. These include experimental approaches such as in vivo or in vitro TF-target gene-binding assays and various methods for identifying regulated targets in mutants, transgenics, or isolated plant cells. In addition, computational approaches are used to infer TF-target gene interactions from the regulatory elements or gene expression changes across treatments. While each of these approaches has now been applied to a large number of TFs from many species, each method has its own limitations which necessitates that multiple data types are integrated to build the most accurate representation of the gene regulatory networks operating in plants. To make the analyses of TF-target interaction datasets available to the broader research community, we have developed the ConnecTF web platform (https://connectf.org/). In this chapter, we describe how ConnecTF can be used to integrate validated and predicted TF-target gene interactions in order to dissect the regulatory role of TFs in developmental and stress response pathways. Using as our examples KN1 and RA1, two well-characterized maize TFs involved in developing floral tissue, we demonstrate how ConnecTF can be used to (1) compare the target genes between TFs, (2) identify direct vs. indirect targets by combining TF-binding and TF-regulation datasets, (3) chart and visualize network paths between TFs and their downstream targets, and (4) prune inferred user networks for high-confidence predicted interactions using validated TF-target gene data. Finally, we provide instructions for setting up a private version of ConnecTF that enables research groups to store and analyze their own TF-target gene interaction datasets.
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Acknowledgments
This work is funded by NIH-NIGMS R01 GM121753 to G.M.C., NSF Plant Genome grant NSF-PGRP: IOS-1840761 to G.M.C., and the Zegar Family Foundation A16-0051 to G.M.C. Any opinions, findings, and conclusions or recommendations expressed in this publication are those of the author(s) and do not necessarily reflect the views of the US Department of Agriculture. Mention of trade names or commercial products in this publication is solely for the purpose of providing specific information and does not imply recommendation or endorsement by the US Department of Agriculture. USDA is an equal opportunity provider and employer.
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Huang, J., Katari, M.S., Juang, CL., Coruzzi, G.M., Brooks, M.D. (2023). Building High-Confidence Gene Regulatory Networks by Integrating Validated TF–Target Gene Interactions Using ConnecTF. In: Kaufmann, K., Vandepoele, K. (eds) Plant Gene Regulatory Networks. Methods in Molecular Biology, vol 2698. Humana, New York, NY. https://doi.org/10.1007/978-1-0716-3354-0_13
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DOI: https://doi.org/10.1007/978-1-0716-3354-0_13
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