Enhanced maps of transcription factor binding sites improve regulatory networks learned from accessible chromatin data

Determining where transcription factors (TFs) bind in genomes provides insight into which transcriptional programs are active across organs, tissue types, and environmental conditions. Recent advances in high-throughput profiling of regulatory DNA have yielded large amounts of information about chromatin accessibility. Interpreting the functional significance of these data sets requires knowledge of which regulators are likely to bind these regions. This can be achieved by using information about TF-binding preferences, or motifs, to identify TF-binding events that are likely to be functional. Although different approaches exist to map motifs to DNA sequences, a systematic evaluation of these tools in plants is missing. Here, we compare four motif-mapping tools widely used in the Arabidopsis (Arabidopsis thaliana) research community and evaluate their performance using chromatin immunoprecipitation data sets for 40 TFs. Downstream gene regulatory network (GRN) reconstruction was found to be sensitive to the motif mapper used. We further show that the low recall of Find Individual Motif Occurrences, one of the most frequently used motif-mapping tools, can be overcome by using an Ensemble approach, which combines results from different mapping tools. Several examples are provided demonstrating how the Ensemble approach extends our view on transcriptional control for TFs active in different biological processes. Finally, a protocol is presented to effectively derive more complete cell type-specific GRNs through the integrative analysis of open chromatin regions, known binding site information, and expression data sets. This approach will pave the way to increase our understanding of GRNs in different cellular conditions

TF2Network : predicting transcription factor regulators and gene regulatory networks in Arabidopsis using publicly available binding site information

A gene regulatory network (GRN) is a collection of regulatory interactions between transcription factors (TFs) and their target genes. GRNs control different biological processes and have been instrumental to understand the organization and complexity of gene regulation. Although various experimental methods have been used to map GRNs in Arabidop-sis thaliana, their limited throughput combined with the large number of TFs makes that for many genes our knowledge about regulating TFs is incomplete. We introduce TF2Network, a tool that exploits the vast amount of TF binding site information and enables the delineation of GRNs by detecting potential regulators for a set of co-expressed or functionally related genes. Validation using two experimental benchmarks reveals that TF2Network predicts the correct regulator in 75-92% of the test sets. Furthermore, our tool is robust to noise in the input gene sets, has a low false discovery rate, and shows a better performance to recover correct regulators compared to other plant tools. TF2Network is accessible through a web interface where GRNs are interactively visualized and annotated with various types of experimental functional information. TF2Network was used to perform systematic functional and regulatory gene annotations, identifying new TFs involved in circadian rhythm and stress response

Functional characterization of the Arabidopsis transcription factor bZIP29 reveals its role in leaf and root development

Plant bZIP group I transcription factors have been reported mainly for their role during vascular development and osmosensory responses. Interestingly, bZIP29 has been identified in a cell cycle interactome, indicating additional functions of bZIP29 in plant development. Here, bZIP29 was functionally characterized to study its role during plant development. It is not present in vascular tissue but is specifically expressed in proliferative tissues. Genome-wide mapping of bZIP29 target genes confirmed its role in stress and osmosensory responses, but also identified specific binding to several core cell cycle genes and to genes involved in cell wall organization. bZIP29 protein complex analyses validated interaction with other bZIP group I members and provided insight into regulatory mechanisms acting on bZIP dimers. In agreement with bZIP29 expression in proliferative tissues and with its binding to promoters of cell cycle regulators, dominant-negative repression of bZIP29 altered the cell number in leaves and in the root meristem. A transcriptome analysis on the root meristem, however, indicated that bZIP29 might regulate cell number through control of cell wall organization. Finally, ectopic dominant-negative repression of bZIP29 and redundant factors led to a seedling-lethal phenotype, pointing to essential roles for bZIP group I factors early in plant development

GSyellow, a multifaceted tag for functional protein analysis in monocot and dicot plants

The ability to tag proteins has boosted the emergence of generic molecular methods for protein functional analysis. Fluorescent protein tags are used to visualize protein localization, and affinity tags enable the mapping of molecular interactions by, for example, tandem affinity purification or chromatin immunoprecipitation. To apply these widely used molecular techniques on a single transgenic plant line, we developed a multifunctional tandem affinity purification tag, named GS(yellow), which combines the streptavidin-binding peptide tag with citrine yellow fluorescent protein. We demonstrated the versatility of the GS(yellow) tag in the dicot Arabidopsis (Arabidopsis thaliana) using a set of benchmark proteins. For proof of concept in monocots, we assessed the localization and dynamic interaction profile of the leaf growth regulator ANGUSTIFOLIA3 (AN3), fused to the GS(yellow) tag, along the growth zone of the maize (Zea mays) leaf. To further explore the function of ZmAN3, we mapped its DNA-binding landscape in the growth zone of the maize leaf through chromatin immunoprecipitation sequencing. Comparison with AN3 target genes mapped in the developing maize tassel or in Arabidopsis cell cultures revealed strong conservation of AN3 target genes between different maize tissues and across monocots and dicots, respectively. In conclusion, the GS(yellow) tag offers a powerful molecular tool for distinct types of protein functional analyses in dicots and monocots. As this approach involves transforming a single construct, it is likely to accelerate both basic and translational plant research

Inference of plant gene regulatory networks using data-driven methods : a practical overview

Transcriptional regulation is a complex and dynamic process that plays a vital role in plant growth and development. A key component in the regulation of genes is transcription factors (TFs), which coordinate the transcriptional control of gene activity. A gene regulatory network (GRN) is a collection of regulatory interactions between TFs and their target genes. The accurate delineation of GRNs offers a significant contribution to our understanding about how plant cells are organized and function, and how individual genes are regulated in various conditions, organs or cell types. During the past decade, important progress has been made in the identification of GRNs using experimental and computational approaches. However, a detailed overview of available platforms supporting the analysis of GRNs in plants is missing. Here, we review current databases, platforms and tools that perform data-driven analyses of gene regulation in Arabidopsis. The platforms are categorized into two sections, 1) promoter motif analysis tools that use motif mapping approaches to find TF motifs in the regulatory sequences of genes of interest and 2) network analysis tools that identify potential regulators for a set of input genes using a range of data types in order to generate GRNs. We discuss the diverse datasets integrated and highlight the strengths and caveats of different platforms. Finally, we shed light on the limitations of the above approaches and discuss future perspectives, including the need for integrative approaches to unravel complex GRNs in plants