Dataset Information

Transcription Factor Activity Mapping of a Tissue-Specific in vivo Gene Regulatory Network.

ABSTRACT: A wealth of physical interaction data between transcription factors (TFs) and DNA has been generated, but these interactions often do not have apparent regulatory consequences. Thus, equating physical interaction data with gene regulatory networks (GRNs) is problematic. Here, we comprehensively assay TF activity, rather than binding, to construct a network of gene regulatory interactions in the C. elegans intestine. By manually observing the in vivo tissue-specific knockdown of 921 TFs on a panel of 19 fluorescent transcriptional reporters, we identified a GRN of 411 interactions between 19 promoters and 177 TFs. This GRN shows only modest overlap with physical interactions, indicating that many regulatory interactions are indirect. We applied nested effects modeling to uncover information flow between TFs in the intestine that converges on a small set of physical TF-promoter interactions. We found numerous cell nonautonomous regulatory interactions, illustrating tissue-to-tissue communication. Altogether, our study illuminates the complexity of gene regulation in the context of a living animal.

SUBMITTER: MacNeil LT

PROVIDER: S-EPMC4584425 | biostudies-literature | 2015 Aug

REPOSITORIES: biostudies-literature

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Publications

Transcription Factor Activity Mapping of a Tissue-Specific in vivo Gene Regulatory Network.

MacNeil Lesley T LT Pons Carles C Arda H Efsun HE Giese Gabrielle E GE Myers Chad L CL Walhout Albertha J M AJ

Cell systems 20150801 2

A wealth of physical interaction data between transcription factors (TFs) and DNA has been generated, but these interactions often do not have apparent regulatory consequences. Thus, equating physical interaction data with gene regulatory networks (GRNs) is problematic. Here, we comprehensively assay TF activity, rather than binding, to construct a network of gene regulatory interactions in the C. elegans intestine. By manually observing the in vivo tissue-specific knockdown of 921 ...[more]

PMID: 26430702

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Project description:BackgroundGene regulatory networks (GRNs) are models of molecule-gene interactions instrumental in the coordination of gene expression. Transcription factor (TF)-GRNs are an important subset of GRNs that characterize gene expression as the effect of TFs acting on their target genes. Although such networks can qualitatively summarize TF-gene interactions, it is highly desirable to quantitatively determine the strengths of the interactions in a TF-GRN as well as the magnitudes of TF activities. To our knowledge, such analysis is rare in plant biology. A computational methodology developed for this purpose is network component analysis (NCA), which has been used for studying large-scale microbial TF-GRNs to obtain nontrivial, mechanistic insights. In this work, we employed NCA to quantitatively analyze a plant TF-GRN important in floral development using available regulatory information from AGRIS, by processing previously reported gene expression data from four shoot apical meristem cell types.ResultsThe NCA model satisfactorily accounted for gene expression measurements in a TF-GRN of seven TFs (LFY, AG, SEPALLATA3 [SEP3], AP2, AGL15, HY5 and AP3/PI) and 55 genes. NCA found strong interactions between certain TF-gene pairs including LFY???MYB17, AG???CRC, AP2???RD20, AGL15???RAV2 and HY5???HLH1, and the direction of the interaction (activation or repression) for some AGL15 targets for which this information was not previously available. The activity trends of four TFs?-?LFY, AG, HY5 and AP3/PI as deduced by NCA correlated well with the changes in expression levels of the genes encoding these TFs across all four cell types; such a correlation was not observed for SEP3, AP2 and AGL15.ConclusionsFor the first time, we have reported the use of NCA to quantitatively analyze a plant TF-GRN important in floral development for obtaining nontrivial information about connectivity strengths between TFs and their target genes as well as TF activity. However, since NCA relies on documented connectivity information about the underlying TF-GRN, it is currently limited in its application to larger plant networks because of the lack of documented connectivities. In the future, the identification of interactions between plant TFs and their target genes on a genome scale would allow the use of NCA to provide quantitative regulatory information about plant TF-GRNs, leading to improved insights on cellular regulatory programs.

Dataset Information

Transcription Factor Activity Mapping of a Tissue-Specific in vivo Gene Regulatory Network.

Publications

Transcription Factor Activity Mapping of a Tissue-Specific <i>in vivo</i> Gene Regulatory Network.

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