μChIP-Seq for Genome-Wide Mapping of In Vivo TF-DNA Interactions in Arabidopsis Root Protoplasts

Organ-specific characteristics govern the relationship between histone code dynamics and transcriptional reprogramming during nitrogen response in tomato

Environmental stimuli trigger rapid transcriptional reprogramming of gene networks. These responses occur in the context of the local chromatin landscape, but the contribution of organ-specific dynamic chromatin modifications in responses to external signals remains largely unexplored. We treated tomato seedlings with a supply of nitrate and measured the genome-wide changes of four histone marks, the permissive marks H3K27ac, H3K4me3, and H3K36me3 and repressive mark H3K27me3, in shoots and roots separately, as well as H3K9me2 in shoots. Dynamic and organ-specific histone acetylation and methylation were observed at functionally relevant gene loci. Integration of transcriptomic and epigenomic datasets generated from the same organ revealed largely syngenetic relations between changes in transcript levels and histone modifications, with the exception of H3K27me3 in shoots, where an increased level of this repressive mark is observed at genes activated by nitrate. Application of a machine learning approach revealed organ-specific rules regarding the importance of individual histone marks, as H3K36me3 is the most successful mark in predicting gene regulation events in shoots, while H3K4me3 is the strongest individual predictor in roots. Our integrated study substantiates a view that during plant environmental responses, the relationships between histone code dynamics and gene regulation are highly dependent on organ-specific contexts.

The TARGET System: Rapid Identification of Direct Targets of Transcription Factors by Gene Regulation in Plant Cells

The TARGET system allows for the rapid identification of direct regulated gene targets of transcription factors (TFs). It employs the transient transformation of plant protoplasts with inducible nuclear entry of the TF and subsequent transcriptomic and/or ChIP-seq analysis. The ability to separate direct TF-target gene regulatory interactions from indirect downstream responses and the significantly shorter amount of time required to perform the assay, compared to the generation of transgenics, make this plant cell-based approach a valuable tool for a higher throughput approach to identify the genome-wide targets of multiple TFs, to build validated transcriptional networks in plants. Here, we describe the use of the TARGET system in Arabidopsis seedling root protoplasts to map the gene regulatory network downstream of transcription factors-of-interest.

Evolutionary rewiring of the wheat transcriptional regulatory network by lineage-specific transposable elements

More than 80% of the wheat genome consists of transposable elements (TEs), which act as major drivers of wheat genome evolution. However, their contributions to the regulatory evolution of wheat adaptations remain largely unclear. Here, we created genome-binding maps for 53 transcription factors (TFs) underlying environmental responses by leveraging DAP-seq in Triticum urartu, together with epigenomic profiles. Most TF binding sites (TFBSs) located distally from genes are embedded in TEs, whose functional relevance is supported by purifying selection and active epigenomic features. About 24% of the non-TE TFBSs share significantly high sequence similarity with TE-embedded TFBSs. These non-TE TFBSs have almost no homologous sequences in non-Triticeae species and are potentially derived from Triticeae-specific TEs. The expansion of TE-derived TFBS linked to wheat-specific gene responses, suggesting TEs are an important driving force for regulatory innovations. Altogether, TEs have been significantly and continuously shaping regulatory networks related to wheat genome evolution and adaptation.

Joint single-cell multiomic analysis in Wnt3a induced asymmetric stem cell division

Wnt signaling usually functions through a spatial gradient. Localized Wnt3a signaling can induce the asymmetric division of mouse embryonic stem cells, where proximal daughter cells maintain self-renewal and distal daughter cells acquire hallmarks of differentiation. Here, we develop an approach, same cell epigenome and transcriptome sequencing, to jointly profile the epigenome and transcriptome in the same single cell. Utilizing this method, we profiled H3K27me3 and H3K4me3 levels along with gene expression in mouse embryonic stem cells with localized Wnt3a signaling, revealing the cell type-specific maps of the epigenome and transcriptome in divided daughter cells. H3K27me3, but not H3K4me3, is correlated with gene expression changes during asymmetric cell division. Furthermore, cell clusters identified by H3K27me3 recapitulate the corresponding clusters defined by gene expression. Our study provides a convenient method to jointly profile the epigenome and transcriptome in the same cell and reveals mechanistic insights into the gene regulatory programs that maintain and reset stem cell fate during differentiation.

A localized Wnt3a signal has been shown to induce asymmetric division of mouse embryonic stem cells. Here the authors develop SET-seq, an approach to jointly profile epigenome and transcriptome in the same single cell and use it to provide mechanistic insights into the gene regulatory programs for maintaining and resetting stem cell fate during differentiation.

Time-Based Systems Biology Approaches to Capture and Model Dynamic Gene Regulatory Networks

All aspects of transcription and its regulation involve dynamic events. However, capturing these dynamic events in gene regulatory networks (GRNs) offers both a promise and a challenge. The promise is that capturing and modeling the dynamic changes in GRNs will allow us to understand how organisms adapt to a changing environment. The ability to mount a rapid transcriptional response to environmental changes is especially important in nonmotile organisms such as plants. The challenge is to capture these dynamic, genome-wide events and model them in GRNs. In this review, we cover recent progress in capturing dynamic interactions of transcription factors with their targets-at both the local and genome-wide levels-and how they are used to learn how GRNs operate as a function of time. We also discuss recent advances that employ time-based machine learning approaches to forecast gene expression at future time points, a key goal of systems biology.

Dynamic histone acetylation in floral volatile synthesis and emission in petunia flowers

Biosynthesis of secondary metabolites relies on primary metabolic pathways to provide precursors, energy, and cofactors, thus requiring coordinated regulation of primary and secondary metabolic networks. However, to date, it remains largely unknown how this coordination is achieved. Using Petunia hybrida flowers, which emit high levels of phenylpropanoid/benzenoid volatile organic compounds (VOCs), we uncovered genome-wide dynamic deposition of histone H3 lysine 9 acetylation (H3K9ac) during anthesis as an underlying mechanism to coordinate primary and secondary metabolic networks. The observed epigenome reprogramming is accompanied by transcriptional activation at gene loci involved in primary metabolic pathways that provide precursor phenylalanine, as well as secondary metabolic pathways to produce volatile compounds. We also observed transcriptional repression among genes involved in alternative phenylpropanoid branches that compete for metabolic precursors. We show that GNAT family histone acetyltransferase(s) (HATs) are required for the expression of genes involved in VOC biosynthesis and emission, by using chemical inhibitors of HATs, and by knocking down a specific HAT gene, ELP3, through transient RNAi. Together, our study supports that regulatory mechanisms at chromatin level may play an essential role in activating primary and secondary metabolic pathways to regulate VOC synthesis in petunia flowers.

Nutrient dose-responsive transcriptome changes driven by Michaelis-Menten kinetics underlie plant growth rates

An increase in nutrient dose leads to proportional increases in crop biomass and agricultural yield. However, the molecular underpinnings of this nutrient dose-response are largely unknown. To investigate, we assayed changes in the Arabidopsis root transcriptome to different doses of nitrogen (N)-a key plant nutrient-as a function of time. By these means, we found that rate changes of genome-wide transcript levels in response to N-dose could be explained by a simple kinetic principle: the Michaelis-Menten (MM) model. Fitting the MM model allowed us to estimate the maximum rate of transcript change (V _max), as well as the N-dose at which one-half of V _max was achieved (K _m) for 1,153 N-dose-responsive genes. Since transcription factors (TFs) can act in part as the catalytic agents that determine the rates of transcript change, we investigated their role in regulating N-dose-responsive MM-modeled genes. We found that altering the abundance of TGA1, an early N-responsive TF, perturbed the maximum rates of N-dose transcriptomic responses (V _max), K _m, as well as the rate of N-dose-responsive plant growth. We experimentally validated that MM-modeled N-dose-responsive genes included both direct and indirect TGA1 targets, using a root cell TF assay to detect TF binding and/or TF regulation genome-wide. Taken together, our results support a molecular mechanism of transcriptional control that allows an increase in N-dose to lead to a proportional change in the rate of genome-wide expression and plant growth.

Transient genome-wide interactions of the master transcription factor NLP7 initiate a rapid nitrogen-response cascade

Dynamic reprogramming of gene regulatory networks (GRNs) enables organisms to rapidly respond to environmental perturbation. However, the underlying transient interactions between transcription factors (TFs) and genome-wide targets typically elude biochemical detection. Here, we capture both stable and transient TF-target interactions genome-wide within minutes after controlled TF nuclear import using time-series chromatin immunoprecipitation (ChIP-seq) and/or DNA adenine methyltransferase identification (DamID-seq). The transient TF-target interactions captured uncover the early mode-of-action of NIN-LIKE PROTEIN 7 (NLP7), a master regulator of the nitrogen signaling pathway in plants. These transient NLP7 targets captured in root cells using temporal TF perturbation account for 50% of NLP7-regulated genes not detectably bound by NLP7 in planta. Rapid and transient NLP7 binding activates early nitrogen response TFs, which we validate to amplify the NLP7-initiated transcriptional cascade. Our approaches to capture transient TF-target interactions genome-wide can be applied to validate dynamic GRN models for any pathway or organism of interest.

Conventional methods cannot reveal transient transcription factors (TFs) and targets interactions. Here, Alvarez et al. capture both stable and transient TF-target interactions by time-series ChIP-seq and/or DamID-seq in a cell-based TF perturbation system and show NLP7 as a master TF to initiate a rapid nitrogen-response cascade.