A matter of time - How transient transcription factor interactions create dynamic gene regulatory networks

Differential impact of sex on regulation of skeletal muscle mitochondrial function and protein homeostasis by hypoxia-inducible factor-1α in normoxia

Hypoxia-inducible factor (HIF)-1α is continuously synthesized and degraded in normoxia. During hypoxia, HIF1α stabilization restricts cellular/mitochondrial oxygen utilization. Cellular stressors can stabilize HIF1α even during normoxia. However, less is known about HIF1α function(s) and sex-specific effects during normoxia in the basal state. Since skeletal muscle is the largest protein store in mammals and protein homeostasis has high energy demands, we determined HIF1α function at baseline during normoxia in skeletal muscle. Untargeted multiomics data analyses were followed by experimental validation in differentiated murine myotubes with loss/gain of function and skeletal muscle from mice without/with post-natal muscle-specific Hif1a deletion (Hif1amsd). Mitochondrial oxygen consumption studies using substrate, uncoupler, inhibitor, titration protocols; targeted metabolite quantification by gas chromatography-mass spectrometry; and post-mitotic senescence markers using biochemical assays were performed. Multiomics analyses showed enrichment in mitochondrial and cell cycle regulatory pathways in Hif1a deleted cells/tissue. Experimentally, mitochondrial oxidative functions and ATP content were higher with less mitochondrial free radical generation with Hif1a deletion. Deletion of Hif1a also resulted in higher concentrations of TCA cycle intermediates and HIF2α proteins in myotubes. Overall responses to Hif1amsd were similar in male and female mice, but changes in complex II function, maximum respiration, Sirt3 and HIF1β protein expression and muscle fibre diameter were sex-dependent. Adaptive responses to hypoxia are mediated by stabilization of constantly synthesized HIF1α. Despite rapid degradation, the presence of HIF1α during normoxia contributes to lower mitochondrial oxidative efficiency and greater post-mitotic senescence in skeletal muscle. In vivo responses to HIF1α in skeletal muscle were differentially impacted by sex. KEY POINTS: Hypoxia-inducible factor -1α (HIF1α), a critical transcription factor, undergoes continuous synthesis and proteolysis, enabling rapid adaptive responses to hypoxia by reducing mitochondrial oxygen consumption. In mammals, skeletal muscle is the largest protein store which is determined by a balance between protein synthesis and breakdown and is sensitive to mitochondrial oxidative function. To investigate the functional consequences of transient HIF1α expression during normoxia in the basal state, myotubes and skeletal muscle from male and female mice with HIF1α knockout were studied using complementary multiomics, biochemical and metabolite assays. HIF1α knockout altered the electron transport chain, mitochondrial oxidative function, signalling molecules for protein homeostasis, and post-mitotic senescence markers, some of which were differentially impacted by sex. The cost of rapid adaptive responses mediated by HIF1α is lower mitochondrial oxidative efficiency and post-mitotic senescence during normoxia.

euAP2a, a key gene that regulates flowering time in peach (Prunus persica) by modulating thermo-responsive transcription programming

Frequent spring frost damage threatens temperate fruit production, and breeding of late-flowering cultivars is an effective strategy for preventing such damage. However, this effort is often hampered by the lack of specific genes and markers and a lack of understanding of the mechanisms. We examined a Late-Flowering Peach (LFP) germplasm and found that its floral buds require a longer chilling period to release from their dormancy and a longer warming period to bloom than the control cultivar, two key characteristics associated with flowering time. We discovered that a 983-bp deletion in euAP2a, an APETALA2 (AP2)-related gene with known roles in regulating floral organ identity and flowering time, was primarily responsible for late flowering in LFP. This deletion disrupts an miR172 binding site, resulting in a gain-of-function mutation in euAP2a. Transcriptomic analyses revealed that at different stages of floral development, two chilling-responsive modules and four warm-responsive modules, comprising approximately 600 genes, were sequentially activated, forming a unique transcription programming. Furthermore, we found that euAP2a was transiently downregulated during the activation of these thermal-responsive modules at various stages. However, the loss of such transient, stage-specific downregulation of euAP2a caused by the deletion of miR172 binding sites resulted in the deactivation or delay of these modules in the LFP flower buds, suggesting that euAP2a acts as a transcription repressor to control floral developmental pace in peaches by modulating the thermo-responsive transcription programming. The findings shed light on the mechanisms behind late flowering in deciduous fruit trees, which is instrumental for breeding frost-tolerant cultivars.

Mutant FOXO1 controls an oncogenic network via enhancer accessibility

Transcriptional dysregulation is a hallmark of diffuse large B cell lymphoma (DLBCL), as transcriptional regulators are frequently mutated. However, our mechanistic understanding of how normal transcriptional programs are co-opted in DLBCL has been hindered by a lack of methodologies that provide the temporal resolution required to separate direct and indirect effects on transcriptional control. We applied a chemical-genetic approach to engineer the inducible degradation of the transcription factor FOXO1, which is recurrently mutated (mFOXO1) in DLBCL. The combination of rapid degradation of mFOXO1, nascent transcript detection, and assessment of chromatin accessibility allowed us to identify the direct targets of mFOXO1. mFOXO1 was required to maintain accessibility at specific enhancers associated with multiple oncogenes, and mFOXO1 degradation impaired RNA polymerase pause-release at some targets. Wild-type FOXO1 appeared to weakly regulate many of the same targets as mFOXO1 and was able to complement the degradation of mFOXO1 in the context of AKT inhibition.

Human Breast Cancer Cell Lines Differentially Modulate Signaling from Distant Microenvironments, Which Reflects Their Metastatic Potential

Metastasis is the stage at which the prognosis substantially decreases for many types of cancer. The ability of tumor cells to metastasize is dependent upon the characteristics of the tumor cells, and the conditioning of distant tissues that support colonization by metastatic cells. In this report, we investigated the systemic alterations in distant tissues caused by multiple human breast cancer cell lines and the impact of these alterations on the tumor cell phenotype. We observed that the niche within the lung, a common metastatic site, was significantly altered by MDA-MB-231, MCF7, and T47 tumors, and that the lung microenvironment stimulated, to differing extents, an epithelial-to-mesenchymal transition (EMT), reducing proliferation, increasing transendothelial migration and senescence, with no significant impact on cell death. We also investigated the ability of an implantable scaffold, which supports the formation of a distant tissue, to serve as a surrogate for the lung to identify systemic alterations. The scaffolds are conditioned by the primary tumor similarly to the lung for each tumor type, evidenced by promoting a pro-EMT profile. Collectively, we demonstrate that metastatic and non-metastatic breast cancers condition distant tissues, with distinct effects on tumor cell responses, and that a surrogate tissue can distinguish the metastatic potential of human breast cancer cell lines in an accessible site that avoids biopsy of a vital organ.

Chemical-genetics refines transcription factor regulatory circuits

Transcriptional dysregulation is a key step in oncogenesis, but our understanding of transcriptional control has relied on genetic approaches that are slow and allow for compensation. Chemical-genetic approaches have shortened the time frame for the analysis of transcription factors from days or weeks to minutes. These studies show that while DNA-binding proteins bind to thousands of sites, they are directly required to regulate only a small cadre of genes. Moreover, these transcriptional control networks are far more distinct, with much less overlap and interconnectivity than predicted from DNA binding. The identified direct targets can then be used to dissect the mechanism of action of these factors, which could identify ways to therapeutically manipulate these oncogenic transcriptional control networks.

Mapping the landscape of lineage-specific dynamic regulation of gene expression using single-cell transcriptomics and application to genetics of complex disease

Single-cell transcriptome data can provide insights into how genetic variation influences biological processes involved in human biology and disease. However, the identification of gene-level associations in distinct cell types faces several challenges, including the limited reference resource from population scale studies, data sparsity in single-cell RNA sequencing, and the complex cell-state pattern of expression within individual cell types. Here we develop genetic models of cell type specific and cell state adjusted gene expression in mid-brain neurons in the process of specializing from induced pluripotent stem cells. The resulting framework quantifies the dynamics of the genetic regulation of gene expression and estimates its cell type specificity. As an application, we show that the approach detects known and new genes associated with schizophrenia and enables insights into context-dependent disease mechanisms. We provide a genomic resource from a phenome-wide application of our models to more than 1500 phenotypes from the UK Biobank. Using longitudinal genetically determined expression, we implement a predictive causality framework, evaluating the prediction of future values of a target gene expression using prior values of a putative regulatory gene. Collectively, this work demonstrates the insights that can be gained into the molecular underpinnings of diseases by quantifying the genetic control of gene expression at single-cell resolution.

Biosynthesis of Betalains Elicited by Methyl Jasmonate in Two Species of Alternanthera Genus: Antagonistic Regulations Result in Increase of Pigments

Natural pigments are components very important in the dye industry. The betalains are pigments found in plants from Caryophyllales order and are relevant in the food manufacturing. The main source of betalains is beetroot, which has unfavorable aftertaste. Therefore, the demand for alternative species producing betalains has increased. Elicitor molecules such as methyl jasmonate (MeJA) induce metabolic reprogramming acting in the biosynthesis of specialized metabolites and can enhance pigment concentrations. Here, we used this strategy to identify if treatment with MeJA at 100 µM can promote the accumulation of betalains and other bioactive compounds in Alternanthera philoxeroides and Alternanthera sessilis. We performed the gene expression, concentration of betalains, phenols, flavonoids, amino acids (phenylalanine and tyrosine), and antioxidant activity. The results showed that MeJA treatment increased betalains and other bioactive compounds in the two Alternanthera species but A. sessilis had a better performance. One key factor in this pathway is related to the phenylalanine and tyrosine concentration. However, the species have distinct metabolic regulation: in A. philoxeroides, high concentrations of betalain pigments increase the tyrosine concentration and gene expression (include ADH) under MeJA and in A. sessilis, high concentrations of betalain pigments reduce the gene expression and tyrosine concentration after 2 days under MeJA. This study brings new questions about betalain biosynthesis and sheds light on the evolution of this pathway in Caryophyllales.

Gene regulatory network inference in soybean upon infection by Phytophthora sojae

Phytophthora sojae is a soil-borne oomycete and the causal agent of Phytophthora root and stem rot (PRR) in soybean (Glycine max [L.] Merrill). Yield losses attributed to P. sojae are devastating in disease-conducive environments, with global estimates surpassing 1.1 million tonnes annually. Historically, management of PRR has entailed host genetic resistance (both vertical and horizontal) complemented by disease-suppressive cultural practices (e.g., oomicide application). However, the vast expansion of complex and/or diverse P. sojae pathotypes necessitates developing novel technologies to attenuate PRR in field environments. Therefore, the objective of the present study was to couple high-throughput sequencing data and deep learning to elucidate molecular features in soybean following infection by P. sojae. In doing so, we generated transcriptomes to identify differentially expressed genes (DEGs) during compatible and incompatible interactions with P. sojae and a mock inoculation. The expression data were then used to select two defense-related transcription factors (TFs) belonging to WRKY and RAV families. DNA Affinity Purification and sequencing (DAP-seq) data were obtained for each TF, providing putative DNA binding sites in the soybean genome. These bound sites were used to train Deep Neural Networks with convolutional and recurrent layers to predict new target sites of WRKY and RAV family members in the DEG set. Moreover, we leveraged publicly available Arabidopsis (Arabidopsis thaliana) DAP-seq data for five TF families enriched in our transcriptome analysis to train similar models. These Arabidopsis data-based models were used for cross-species TF binding site prediction on soybean. Finally, we created a gene regulatory network depicting TF-target gene interactions that orchestrate an immune response against P. sojae. Information herein provides novel insight into molecular plant-pathogen interaction and may prove useful in developing soybean cultivars with more durable resistance to P. sojae.

Biotinylated Tn5 transposase-mediated CUT&Tag efficiently profiles transcription factor-DNA interactions in plants

In contrast to CUT&Tag approaches for profiling bulk histone modifications, current CUT&Tag methods for analysing specific transcription factor (TF)-DNA interactions remain technically challenging due to TFs having relatively low abundance. Moreover, an efficient CUT&Tag strategy for plant TFs is not yet available. Here, we first applied biotinylated Tn5 transposase-mediated CUT&Tag (B-CUT&Tag) to produce high-quality libraries for interrogating TF-DNA interactions. B-CUT&Tag combines streptavidin-biotin-based DNA purification with routine CUT&Tag, optimizing the removal of large amounts of intact chromatin not targeted by specific TFs. The biotinylated chromatin fragments are then purified for construction of deep sequencing libraries or qPCR analysis. We applied B-CUT&Tag to probe genome-wide DNA targets of Squamosa promoter-binding-like protein 9 (SPL9), a well-established TF in Arabidopsis; the resulting profiles were efficient and consistent in demonstrating its well-established target genes in juvenile-adult transition/flowering, trichome development, flavonoid biosynthesis, wax synthesis and branching. Interestingly, our results indicate functions of AtSPL9 in modulating growth-defence trade-offs. In addition, we established a method for applying qPCR after CUT&Tag (B-CUT&Tag-qPCR) and successfully validated the binding of SPL9 in Arabidopsis and PHR2 in rice. Our study thus provides a convenient and highly efficient CUT&Tag strategy for profiling TF-chromatin interactions that is widely applicable to the annotation of cis-regulatory elements for crop improvement.

Functional characterization of transcriptional activator gene SIARRI in tomato reveals its role in fruit growth and ripening

Auxins regulate several characteristics of plant development and growth. Here, we characterized a new transcriptional activator SIARRI which binds specific DNA sequences and was revealed in Arabidopsis (ARR1). SIARRI acts as a two-component response regulator and its Arabidopsis homologous gene is AT3G16857. It belongs to the subfamily of type-B response regulators in the cytokinin signaling pathway. The study aimed to characterize the transgenic Micro-Tom plants by the overexpression of Solanum lycopersicum two-component response regulator ARR1. Overexpression of SIARRI results in a pleiotropic phenotype during fruit development and ripening. This study indicates that SIARRI is a primary regulator of leaf morphology and fruit development. Moreover, overexpressed plants showed variations in growth related to auxin as well as shorter hypocotyl elongation, enlarged leaf vascularization, and decreased apical dominance. The qRT-PCR investigation revealed that expression was downregulated at the breaker stage and high at Br+6 at various stages of fruit growth and ripening. In contrast to the fruit color, lycopene and β-carotene concentrations in red-yellow overexpression line fruits were reduced significantly, and also slightly reduced in some red fruits. The quantity of β-carotene in the transgenic fruits was lower than that of lycopene. This study showed that this gene might be a new transcriptional activator in fruit development and ripening. Furthermore, this study will provide new insights into tomato fruit ripening.

Building High-Confidence Gene Regulatory Networks by Integrating Validated TF-Target Gene Interactions Using ConnecTF

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.

DamID-seq: A Genome-Wide DNA Methylation Method that Captures Both Transient and Stable TF-DNA Interactions in Plant Cells

Capturing the dynamic and transient interactions of a transcription factor (TF) with its genome-wide targets whose regulation leads to plants' adaptation to their changing environment is a major technical challenge. This is a widespread problem with biochemical methods such as chromatin immunoprecipitation-sequencing (ChIP-seq) which are biased towards capturing stable TF-target gene interactions. Herein, we describe how DNA adenine methyltransferase identification and sequencing (DamID-seq) can be used to capture both transient and stable TF-target interactions by DNA methylation. The DamID technique uses a TF protein fused to a DNA adenine methyltransferase (Dam) from E. coli. When expressed in a plant cell, the Dam-TF fusion protein will methylate adenine (A) bases near the sites of TF-DNA interactions. In this way, DamID results in a permanent, stable DNA methylation mark on TF-target gene promoters, even if the target gene is only transiently "touched" by the Dam-TF fusion protein. Here we provide a step-by-step protocol to perform DamID-seq experiments in isolated plant cells for any Dam-TF fusion protein of interest. We also provide information that will enable researchers to analyze DamID-seq data to identify TF-binding sites in the genome. Our protocol includes instructions for vector cloning of the Dam-TF fusion proteins, plant cell protoplast transfections, DamID preps, library preparation, and sequencing data analysis. The protocol outlined in this chapter is performed in Arabidopsis thaliana, however, the DamID-seq workflow developed in this guide is broadly applicable to other plants and organisms.

PAX3-FOXO1 coordinates enhancer architecture, eRNA transcription, and RNA polymerase pause release at select gene targets

Transcriptional control is a highly dynamic process that changes rapidly in response to various cellular and extracellular cues, making it difficult to define the mechanism of transcription factor function using slow genetic methods. We used a chemical-genetic approach to rapidly degrade a canonical transcriptional activator, PAX3-FOXO1, to define the mechanism by which it regulates gene expression programs. By coupling rapid protein degradation with the analysis of nascent transcription over short time courses and integrating CUT&RUN, ATAC-seq, and eRNA analysis with deep proteomic analysis, we defined PAX3-FOXO1 function at a small network of direct transcriptional targets. PAX3-FOXO1 degradation impaired RNA polymerase pause release and transcription elongation at most regulated gene targets. Moreover, the activity of PAX3-FOXO1 at enhancers controlling this core network was surprisingly selective, affecting single elements in super-enhancers. This combinatorial analysis indicated that PAX3-FOXO1 was continuously required to maintain chromatin accessibility and enhancer architecture at regulated enhancers.

Transcription Factors Controlling the Rhizobium-Legume Symbiosis: Integrating Infection, Organogenesis and the Abiotic Environment

Legume roots engage in a symbiotic relationship with rhizobia, leading to the development of nitrogen-fixing nodules. Nodule development is a sophisticated process and is under the tight regulation of the plant. The symbiosis initiates with a signal exchange between the two partners, followed by the development of a new organ colonized by rhizobia. Over two decades of study have shed light on the transcriptional regulation of rhizobium-legume symbiosis. A large number of transcription factors (TFs) have been implicated in one or more stages of this symbiosis. Legumes must monitor nodule development amidst a dynamic physical environment. Some environmental factors are conducive to nodulation, whereas others are stressful. The modulation of rhizobium-legume symbiosis by the abiotic environment adds another layer of complexity and is also transcriptionally regulated. Several symbiotic TFs act as integrators between symbiosis and the response to the abiotic environment. In this review, we trace the role of various TFs involved in rhizobium-legume symbiosis along its developmental route and highlight the ones that also act as communicators between this symbiosis and the response to the abiotic environment. Finally, we discuss contemporary approaches to study TF-target interactions in plants and probe their potential utility in the field of rhizobium-legume symbiosis.

Concentration-dependent transcriptional switching through a collective action of cis-elements

Gene expression specificity of homeobox transcription factors has remained paradoxical. WUSCHEL activates and represses CLAVATA3 transcription at lower and higher concentrations, respectively. We use computational modeling and experimental analysis to investigate the properties of the cis-regulatory module. We find that intrinsically each cis-element can only activate CLAVATA3 at a higher WUSCHEL concentration. However, together, they repress CLAVATA3 at higher WUSCHEL and activate only at lower WUSCHEL, showing that the concentration-dependent interactions among cis-elements regulate both activation and repression. Biochemical experiments show that two adjacent functional cis-elements bind WUSCHEL with higher affinity and dimerize at relatively lower levels. Moreover, increasing the distance between cis-elements prolongs WUSCHEL monomer binding window, resulting in higher CLAVATA3 activation. Our work showing a constellation of optimally spaced cis-elements of defined affinities determining activation and repression thresholds in regulating CLAVATA3 transcription provides a previously unknown mechanism of cofactor-independent regulation of transcription factor binding in mediating gene expression specificity.

TGA transcription factors-Structural characteristics as basis for functional variability

TGA transcription factors are essential regulators of various cellular processes, their activity connected to different hormonal pathways, interacting proteins and regulatory elements. Belonging to the basic region leucine zipper (bZIP) family, TGAs operate by binding to their target DNA sequence as dimers through a conserved bZIP domain. Despite sharing the core DNA-binding sequence, the TGA paralogues exert somewhat different DNA-binding preferences. Sequence variability of their N- and C-terminal protein parts indicates their importance in defining TGA functional specificity through interactions with diverse proteins, affecting their DNA-binding properties. In this review, we provide a short and concise summary on plant TGA transcription factors from a structural point of view, including the relation of their structural characteristics to their functional roles in transcription regulation.

Regulation of both transcription and RNA turnover contribute to germline specification

The nuanced mechanisms driving primordial germ cells (PGC) specification remain incompletely understood since genome-wide transcriptional regulation in developing PGCs has previously only been defined indirectly. Here, using SLAMseq analysis, we determined genome-wide transcription rates during the differentiation of embryonic stem cells (ESCs) to form epiblast-like (EpiLC) cells and ultimately PGC-like cells (PGCLCs). This revealed thousands of genes undergoing bursts of transcriptional induction and rapid shut-off not detectable by RNAseq analysis. Our SLAMseq datasets also allowed us to infer RNA turnover rates, which revealed thousands of mRNAs stabilized and destabilized during PGCLC specification. mRNAs tend to be unstable in ESCs and then are progressively stabilized as they differentiate. For some classes of genes, mRNA turnover regulation collaborates with transcriptional regulation, but these processes oppose each other in a surprisingly high frequency of genes. To test whether regulated mRNA turnover has a physiological role in PGC development, we examined three genes that we found were regulated by RNA turnover: Sox2, Klf2 and Ccne1. Circumvention of their regulated RNA turnover severely impaired the ESC-to-EpiLC and EpiLC-to-PGCLC transitions. Our study demonstrates the functional importance of regulated RNA stability in germline development and provides a roadmap of transcriptional and post-transcriptional regulation during germline specification.

Morphogen-directed cell fate boundaries: slow passage through bifurcation and the role of folded saddles

One of the fundamental mechanisms in embryogenesis is the process by which cells differentiate and create tissues and structures important for functioning as a multicellular organism. Morphogenesis involves diffusive process of chemical signalling involving morphogens that pre-pattern the tissue. These morphogens influence cell fate through a highly nonlinear process of transcriptional signalling. In this paper, we consider this multiscale process in an idealised model for a growing domain. We focus on intracellular processes that lead to robust differentiation into two cell lineages through interaction of a single morphogen species with a cell fate variable that undergoes a bifurcation from monostability to bistability. In particular, we investigate conditions that result in successful and robust pattern formation into two well-separated domains, as well as conditions where this fails and produces a pinned boundary wave where only one part of the domain grows. We show that successful and unsuccessful patterning scenarios can be characterised in terms of presence or absence of a folded saddle singularity for a system with two slow variables and one fast variable; this models the interaction of slow morphogen diffusion, slow parameter drift through bifurcation and fast transcription dynamics. We illustrate how this approach can successfully model acquisition of three cell fates to produce three-domain "French flag" patterning, as well as for a more realistic model of the cell fate dynamics in terms of two mutually inhibiting transcription factors.

ODORANT1 targets multiple metabolic networks in petunia flowers

Scent bouquets produced by the flowers of Petunia spp. (petunia) are composed of a complex mixture of floral volatile benzenoid and phenylpropanoid compounds (FVBPs), which are specialized metabolites derived from phenylalanine (Phe) through an interconnected network of enzymes. The biosynthesis and emission of high levels of these volatiles requires coordinated transcriptional activation of both primary and specialized metabolic networks. The petunia R2R3-MYB transcription factor ODORANT 1 (ODO1) was identified as a master regulator of FVBP production and emission; however, our knowledge of the direct regulatory targets of ODO1 has remained limited. Using chromatin immunoprecipitation followed by sequencing (ChIP-seq) in petunia flowers, we identify genome-wide ODO1-bound genes that are enriched not only in genes involved in the biosynthesis of the Phe precursor, as previously reported, but also genes associated with the specialized metabolic pathways involved in generating phenylpropanoid intermediates for FVBPs. ODO1-bound genes are also involved in methionine and S-adenosylmethionine metabolism, which could modulate methyl group supplies for certain FVBPs. Quantitative reverse transcription polymerase chain reaction (qRT-PCR) and RNA-seq analysis in an ODO1 RNAi knockdown line revealed that ODO1-bound targets are expressed at lower levels when ODO1 is suppressed. A cis-regulatory motif, CACCAACCCC, was identified as a potential binding site for ODO1 in the promoters of genes that are both bound and activated by ODO1, which was validated by in planta promoter reporter assays with wild-type and mutated promoters. Overall, our work presents a mechanistic model for ODO1 controlling an extensive gene regulatory network that contributes to FVBP production to give rise to floral scent.

Network inference with Granger causality ensembles on single-cell transcriptomics

Cellular gene expression changes throughout a dynamic biological process, such as differentiation. Pseudotimes estimate cells' progress along a dynamic process based on their individual gene expression states. Ordering the expression data by pseudotime provides information about the underlying regulator-gene interactions. Because the pseudotime distribution is not uniform, many standard mathematical methods are inapplicable for analyzing the ordered gene expression states. Here we present single-cell inference of networks using Granger ensembles (SINGE), an algorithm for gene regulatory network inference from ordered single-cell gene expression data. SINGE uses kernel-based Granger causality regression to smooth irregular pseudotimes and missing expression values. It aggregates predictions from an ensemble of regression analyses to compile a ranked list of candidate interactions between transcriptional regulators and target genes. In two mouse embryonic stem cell differentiation datasets, SINGE outperforms other contemporary algorithms. However, a more detailed examination reveals caveats about poor performance for individual regulators and uninformative pseudotimes.

The biology of time: dynamic responses of cell types to developmental, circadian and environmental cues

As sessile organisms, plants are finely tuned to respond dynamically to developmental, circadian and environmental cues. Genome-wide studies investigating these types of cues have uncovered the intrinsically different ways they can impact gene expression over time. Recent advances in single-cell sequencing and time-based bioinformatic algorithms are now beginning to reveal the dynamics of these time-based responses within individual cells and plant tissues. Here, we review what these techniques have revealed about the spatiotemporal nature of gene regulation, paying particular attention to the three distinct ways in which plant tissues are time sensitive. (i) First, we discuss how studying plant cell identity can reveal developmental trajectories hidden in pseudotime. (ii) Next, we present evidence that indicates that plant cell types keep their own local time through tissue-specific regulation of the circadian clock. (iii) Finally, we review what determines the speed of environmental signaling responses, and how they can be contingent on developmental and circadian time. By these means, this review sheds light on how these different scales of time-based responses can act with tissue and cell-type specificity to elicit changes in whole plant systems.

From gene to biomolecular networks: a review of evidences for understanding complex biological function in plants

Although at the infancy stage, biomolecular network biology is a comprehensive approach to understand complex biological function in plants. Recent advancements in the accumulation of multi-omics data coupled with computational approach have accelerated our current understanding of the complexities of gene function at the system level. Biomolecular networks such as protein-protein interaction, co-expression and gene regulatory networks have extensively been used to decipher the intricacies of transcriptional reprogramming of hundreds of genes and their regulatory interaction in response to various environmental perturbations mainly in the model plant Arabidopsis. This review describes recent applications of network-based approaches to understand the biological functions in plants and focuses on the challenges and opportunities to harness the full potential of the approach.

Rational gRNA design based on transcription factor binding data

The clustered regularly interspaced short palindromic repeats (CRISPR)/Cas9 system has become a standard tool in many genome engineering endeavors. The endonuclease-deficient version of Cas9 (dCas9) is also a powerful programmable tool for gene regulation. In this study, we made use of Saccharomyces cerevisiae transcription factor (TF) binding data to obtain a better understanding of the interplay between TF binding and binding of dCas9 fused to an activator domain, VPR. More specifically, we targeted dCas9–VPR toward binding sites of Gcr1–Gcr2 and Tye7 present in several promoters of genes encoding enzymes engaged in the central carbon metabolism. From our data, we observed an upregulation of gene expression when dCas9–VPR was targeted next to a TF binding motif, whereas a downregulation or no change was observed when dCas9 was bound on a TF motif. This suggests a steric competition between dCas9 and the specific TF. Integrating TF binding data, therefore, proved to be useful for designing guide RNAs for CRISPR interference or CRISPR activation applications.

Molecular competition can shape enhancer activity in the Drosophila embryo

Transgenic reporters allow the measurement of regulatory DNA activity in vivo and consequently have long been useful tools for studying enhancers. Despite their utility, few studies have investigated the effects these reporters may have on the expression of other genes. Understanding these effects is required to accurately interpret reporter data and characterize gene regulatory mechanisms. By measuring the expression of Kruppel (Kr) enhancer reporters in live Drosophila embryos, we find reporters inhibit one another's expression and that of a nearby endogenous gene. Using synthetic transcription factor (TF) binding site arrays, we present evidence that competition for TFs is partially responsible for the observed transcriptional inhibition. We develop a simple thermodynamic model that predicts competition of the measured magnitude specifically when TF binding is restricted to distinct nuclear subregions. Our findings underline an unexpected role of the non-homogenous nature of the nucleus in regulating gene expression.

Effects of an environmentally relevant PFAS mixture on dopamine and steroid hormone levels in exposed mice

In the present study, we investigated the dopaminergic and steroid hormone systems of A/J mice fed environmentally relevant concentrations of a perfluoroalkyl substance (PFAS) mixture over a period of 10 weeks. The PFAS mixture was chosen based on measured PFAS concentrations in earthworms at a Norwegian skiing area (Trondheim) and consisted of eight different PFAS. Dietary exposure to PFAS led to lower total brain dopamine (DA) concentrations in male mice, as compared to control. On the transcript level, brain tyrosine hydroxylase (th) of PFAS exposed males was reduced, compared to the control group. No significant differences were observed on the transcript levels of enzymes responsible for DA metabolism, namely - monoamine oxidase (maoa and maob) and catechol-O methyltransferase (comt). We detected increased transcript level for DA receptor 2 (dr2) in PFAS exposed females, while expression of DA receptor 1 (dr1), DA transporter (dat) and vesicular monoamine transporter (vmat) were not affected by PFAS exposure. Regarding the steroid hormones, plasma and muscle testosterone (T), 11-ketotestosterone (11-KT) and 17β-estradiol (E2) levels, as well as transcripts for estrogen receptors (esr1 and esr2), gonadotropin releasing hormone (gnrh) and aromatase (cyp19) were unaltered by the PFAS treatment. These results indicate that exposure to PFAS doses, comparable to previous observation in earthworms at a Norwegian skiing area, may alter the dopaminergic system of mice with overt consequences for health, general physiology, cognitive behavior, reproduction and metabolism.

Protein mimetic amyloid inhibitor potently abrogates cancer-associated mutant p53 aggregation and restores tumor suppressor function

Missense mutations in p53 are severely deleterious and occur in over 50% of all human cancers. The majority of these mutations are located in the inherently unstable DNA-binding domain (DBD), many of which destabilize the domain further and expose its aggregation-prone hydrophobic core, prompting self-assembly of mutant p53 into inactive cytosolic amyloid-like aggregates. Screening an oligopyridylamide library, previously shown to inhibit amyloid formation associated with Alzheimer's disease and type II diabetes, identified a tripyridylamide, ADH-6, that abrogates self-assembly of the aggregation-nucleating subdomain of mutant p53 DBD. Moreover, ADH-6 targets and dissociates mutant p53 aggregates in human cancer cells, which restores p53's transcriptional activity, leading to cell cycle arrest and apoptosis. Notably, ADH-6 treatment effectively shrinks xenografts harboring mutant p53, while exhibiting no toxicity to healthy tissue, thereby substantially prolonging survival. This study demonstrates the successful application of a bona fide small-molecule amyloid inhibitor as a potent anticancer agent.

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.

A global search for novel transcription factors impacting the Neurospora crassa circadian clock

Eukaryotic circadian oscillators share a common circuit architecture, a negative feedback loop in which a positive element activates the transcription of a negative one that then represses the action of the former, inhibiting its own expression. While studies in mammals and insects have revealed additional transcriptional inputs modulating the expression of core clock components, this has been less characterized in the model Neurospora crassa, where the participation of other transcriptional components impacting circadian clock dynamics remains rather unexplored. Thus, we sought to identify additional transcriptional regulators modulating the N. crassa clock, following a reverse genetic screen based on luminescent circadian reporters and a collection of transcription factors (TFs) knockouts, successfully covering close to 60% of them. Besides the canonical core clock components WC-1 and -2, none of the tested transcriptional regulators proved to be essential for rhythmicity. Nevertheless, we identified a set of 23 TFs that when absent lead to discrete, but significant, changes in circadian period. While the current level of analysis does not provide mechanistic information about how these new players modulate circadian parameters, the results of this screen reveal that an important number of light and clock-regulated TFs, involved in a plethora of processes, are capable of modulating the clockworks. This partial reverse genetic clock screen also exemplifies how the N. crassa knockout collection continues to serve as an expedite platform to address broad biological questions.

Cross-species comparisons and in vitro models to study tempo in development and homeostasis

Time is inherent to biological processes. It determines the order of events and the speed at which they take place. However, we still need to refine approaches to measure the course of time in biological systems and understand what controls the pace of development. Here, we argue that the comparison of biological processes across species provides molecular insight into the timekeeping mechanisms in biology. We discuss recent findings and the open questions in the field and highlight the use of in vitro systems as tools to investigate cell-autonomous control as well as the coordination of temporal mechanisms within tissues. Further, we discuss the relevance of studying tempo for tissue transplantation, homeostasis and lifespan.

Holo-omics for deciphering plant-microbiome interactions

Host-microbiome interactions are recognized for their importance to host health. An improved understanding of the molecular underpinnings of host-microbiome relationships will advance our capacity to accurately predict host fitness and manipulate interaction outcomes. Within the plant microbiome research field, unlocking the functional relationships between plants and their microbial partners is the next step to effectively using the microbiome to improve plant fitness. We propose that strategies that pair host and microbial datasets-referred to here as holo-omics-provide a powerful approach for hypothesis development and advancement in this area. We discuss several experimental design considerations and present a case study to highlight the potential for holo-omics to generate a more holistic perspective of molecular networks within the plant microbiome system. In addition, we discuss the biggest challenges for conducting holo-omics studies; specifically, the lack of vetted analytical frameworks, publicly available tools, and required technical expertise to process and integrate heterogeneous data. Finally, we conclude with a perspective on appropriate use-cases for holo-omics studies, the need for downstream validation, and new experimental techniques that hold promise for the plant microbiome research field. We argue that utilizing a holo-omics approach to characterize host-microbiome interactions can provide important opportunities for broadening system-level understandings and significantly inform microbial approaches to improving host health and fitness. Video abstract.

Genome-wide binding of SEPALLATA3 and AGAMOUS complexes determined by sequential DNA-affinity purification sequencing

The MADS transcription factors (TF), SEPALLATA3 (SEP3) and AGAMOUS (AG) are required for floral organ identity and floral meristem determinacy. While dimerization is obligatory for DNA binding, SEP3 and SEP3–AG also form tetrameric complexes. How homo and hetero-dimerization and tetramerization of MADS TFs affect genome-wide DNA-binding and gene regulation is not known. Using sequential DNA affinity purification sequencing (seq-DAP-seq), we determined genome-wide binding of SEP3 homomeric and SEP3–AG heteromeric complexes, including SEP3^Δtet-AG, a complex with a SEP3 splice variant, SEP3^Δtet, which is largely dimeric and SEP3–AG tetramer. SEP3 and SEP3–AG share numerous bound regions, however each complex bound unique sites, demonstrating that protein identity plays a role in DNA-binding. SEP3–AG and SEP3^Δtet-AG share a similar genome-wide binding pattern; however the tetrameric form could access new sites and demonstrated a global increase in DNA-binding affinity. Tetramerization exhibited significant cooperative binding with preferential distances between two sites, allowing efficient binding to regions that are poorly recognized by dimeric SEP3^Δtet-AG. By intersecting seq-DAP-seq with ChIP-seq and expression data, we identified unique target genes bound either in SEP3–AG seq-DAP-seq or in SEP3/AG ChIP-seq. Seq-DAP-seq is a versatile genome-wide technique and complements in vivo methods to identify putative direct regulatory targets.

Network-based approaches for understanding gene regulation and function in plants

Expression reprogramming directed by transcription factors is a primary gene regulation underlying most aspects of the biology of any organism. Our views of how gene regulation is coordinated are dramatically changing thanks to the advent and constant improvement of high-throughput profiling and transcriptional network inference methods: from activities of individual genes to functional interactions across genes. These technical and analytical advances can reveal the topology of transcriptional networks in which hundreds of genes are hierarchically regulated by multiple transcription factors at systems level. Here we review the state of the art of experimental and computational methods used in plant biology research to obtain large-scale datasets and model transcriptional networks. Examples of direct use of these network models and perspectives on their limitations and future directions are also discussed.

PRL3-DDX21 Transcriptional Control of Endolysosomal Genes Restricts Melanocyte Stem Cell Differentiation

Melanocytes, replenished throughout life by melanocyte stem cells (MSCs), play a critical role in pigmentation and melanoma. Here, we reveal a function for the metastasis-associated phosphatase of regenerating liver 3 (PRL3) in MSC regeneration. We show that PRL3 binds to the RNA helicase DDX21, thereby restricting productive transcription by RNAPII at master transcription factor (MITF)-regulated endolysosomal vesicle genes. In zebrafish, this mechanism controls premature melanoblast expansion and differentiation from MSCs. In melanoma patients, restricted transcription of this endolysosomal vesicle pathway is a hallmark of PRL3-high melanomas. Our work presents the conceptual advance that PRL3-mediated control of transcriptional elongation is a differentiation checkpoint mechanism for activated MSCs and has clinical relevance for the activity of PRL3 in regenerating tissue and cancer.

Gene Regulatory Network Inference: Connecting Plant Biology and Mathematical Modeling

Plant responses to environmental and intrinsic signals are tightly controlled by multiple transcription factors (TFs). These TFs and their regulatory connections form gene regulatory networks (GRNs), which provide a blueprint of the transcriptional regulations underlying plant development and environmental responses. This review provides examples of experimental methodologies commonly used to identify regulatory interactions and generate GRNs. Additionally, this review describes network inference techniques that leverage gene expression data to predict regulatory interactions. These computational and experimental methodologies yield complex networks that can identify new regulatory interactions, driving novel hypotheses. Biological properties that contribute to the complexity of GRNs are also described in this review. These include network topology, network size, transient binding of TFs to DNA, and competition between multiple upstream regulators. Finally, this review highlights the potential of machine learning approaches to leverage gene expression data to predict phenotypic outputs.

Identification and evolution of gene regulatory networks: insights from comparative studies in plants

The availability of genome sequences, genome-wide assays of transcription factor binding, and accessible chromatin maps have unveiled gene regulatory landscapes in plants. This understanding has ushered in comparative gene regulatory network studies that assess network rewiring between species, across time, and between biological tissues. Comparisons of cis-regulatory elements across the plant kingdom have uncovered examples of conserved sequences, but also of divergence, indicating that selective pressures can vary in different plant families. Transcription factor duplication, followed by spatiotemporal expression divergence of the duplicates, also appears to be a key mechanism of network evolution. Here, we review recent literature describing the regulation of gene expression in plants, and how comparative studies provide insights into how these regulatory interactions change and lead to gene regulatory network rewiring.

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.

A developmental gene regulatory network for C. elegans anchor cell invasion

Cellular invasion is a key part of development, immunity and disease. Using an in vivo model of Caenorhabditis elegans anchor cell invasion, we characterize the gene regulatory network that promotes cell invasion. The anchor cell is initially specified in a stochastic cell fate decision mediated by Notch signaling. Previous research has identified four conserved transcription factors, fos-1 (Fos), egl-43 (EVI1/MEL), hlh-2 (E/Daughterless) and nhr-67 (NR2E1/TLX), that mediate anchor cell specification and/or invasive behavior. Connections between these transcription factors and the underlying cell biology that they regulate are poorly understood. Here, using genome editing and RNA interference, we examine transcription factor interactions before and after anchor cell specification. Initially, these transcription factors function independently of one another to regulate LIN-12 (Notch) activity. Following anchor cell specification, egl-43, hlh-2 and nhr-67 function largely parallel to fos-1 in a type I coherent feed-forward loop with positive feedback to promote invasion. Together, these results demonstrate that the same transcription factors can function in cell fate specification and differentiated cell behavior, and that a gene regulatory network can be rapidly assembled to reinforce a post-mitotic, pro-invasive state.

SDG8-Mediated Histone Methylation and RNA Processing Function in the Response to Nitrate Signaling

Chromatin modification has gained increased attention for its role in the regulation of plant responses to environmental changes, but the specific mechanisms and molecular players remain elusive. Here, we show that the Arabidopsis (Arabidopsis thaliana) histone methyltransferase SET DOMAIN GROUP8 (SDG8) mediates genome-wide changes in H3K36 methylation at specific genomic loci functionally relevant to nitrate treatments. Moreover, we show that the specific H3K36 methyltransferase encoded by SDG8 is required for canonical RNA processing, and that RNA isoform switching is more prominent in the sdg8-5 deletion mutant than in the wild type. To demonstrate that SDG8-mediated regulation of RNA isoform expression is functionally relevant, we examined a putative regulatory gene, CONSTANS, CO-like, and TOC1 101 (CCT101), whose nitrogen-responsive isoform-specific RNA expression is mediated by SDG8. We show by functional expression in shoot cells that the different RNA isoforms of CCT101 encode distinct regulatory proteins with different effects on genome-wide transcription. We conclude that SDG8 is involved in plant responses to environmental nitrogen supply, affecting multiple gene regulatory processes including genome-wide histone modification, transcriptional regulation, and RNA processing, and thereby mediating developmental and metabolic processes related to nitrogen use.

Pre-marked chromatin and transcription factor co-binding shape the pioneering activity of Foxa2

Pioneer transcription factors (PTF) can recognize their binding sites on nucleosomal DNA and trigger chromatin opening for recruitment of other non-pioneer transcription factors. However, critical properties of PTFs are still poorly understood, such as how these transcription factors selectively recognize cell type-specific binding sites and under which conditions they can initiate chromatin remodelling. Here we show that early endoderm binding sites of the paradigm PTF Foxa2 are epigenetically primed by low levels of active chromatin modifications in embryonic stem cells (ESC). Priming of these binding sites is supported by preferential recruitment of Foxa2 to endoderm binding sites compared to lineage-inappropriate binding sites, when ectopically expressed in ESCs. We further show that binding of Foxa2 is required for chromatin opening during endoderm differentiation. However, increased chromatin accessibility was only detected on binding sites which are synergistically bound with other endoderm transcription factors. Thus, our data suggest that binding site selection of PTFs is directed by the chromatin environment and that chromatin opening requires collaboration of PTFs with additional transcription factors.

Challenges of Translating Gene Regulatory Information into Agronomic Improvements

Improvement of agricultural species has exploited the genetic variation responsible for complex quantitative traits. Much of the functional variation is regulatory, in cis-regulatory elements and trans-acting factors that ultimately contribute to gene expression differences. However, the identification of gene regulatory network components that, when modulated, will increase plant productivity or resilience, is challenging, yet essential to provide increased predictive power for genome engineering approaches that are likely to benefit useful traits. Here, we discuss the opportunities and limitations of using data obtained from gene coexpression, transcription factor binding, and genome-wide association mapping analyses to predict regulatory interactions that impact crop improvement. It is apparent that a combination of information from these data types is necessary for the reliable identification and utilization of important regulatory interactions that underlie complex agronomic traits.

Network Walking charts transcriptional dynamics of nitrogen signaling by integrating validated and predicted genome-wide interactions

Charting a temporal path in gene networks requires linking early transcription factor (TF)-triggered events to downstream effects. We scale-up a cell-based TF-perturbation assay to identify direct regulated targets of 33 nitrogen (N)-early response TFs encompassing 88% of N-responsive Arabidopsis genes. We uncover a duality where each TF is an inducer and repressor, and in vitro cis-motifs are typically specific to regulation directionality. Validated TF-targets (71,836) are used to refine precision of a time-inferred root network, connecting 145 N-responsive TFs and 311 targets. These data are used to chart network paths from direct TF₁-regulated targets identified in cells to indirect targets responding only in planta via Network Walking. We uncover network paths from TGA1 and CRF4 to direct TF₂ targets, which in turn regulate 76% and 87% of TF₁ indirect targets in planta, respectively. These results have implications for N-use and the approach can reveal temporal networks for any biological system.

Temporal control of transcriptional networks enables organisms to adapt to changing environment. Here, the authors use a scaled-up cell-based assay to identify direct targets of nitrogen-early responsive transcription factors and validate a network path mediating dynamic nitrogen signaling in Arabidopsis.

Apigenin Inhibits IL-31 Cytokine in Human Mast Cell and Mouse Skin Tissues

IL-31 is a recently discovered cytokine that is produced not only in T-cells but also in mast cells. It is strongly implicated to play a key role in inflammatory diseases and in the pathogenesis of itch in atopic dermatitis. Apigenin, a flavonoid of plant origin has numerous biological applications. In this study, we showed that apigenin modulates IL-31 mRNA, protein expression, and release in stimulated human mast (HMC-1) by inhibiting the phosphorylation activation of MAPK and NF-κB. To determine whether apigenin has similar effects in vivo, using Compound 48/80, we developed an atopic dermatitis itch model in mice and found an increase in IL-31 expression in the skin. We also revealed that apigenin prevents the infiltration and degranulation of mast cells and suppressed mRNA and protein expression of IL-31 in the skin of mice. These results provide a new suggestion of the potential applicability of apigenin for treatment of various inflammatory diseases and itch mediated by IL-31.

Transcriptional factor regulation network and competitive endogenous RNA (ceRNA) network determining response of esophageal squamous cell carcinomas to neoadjuvant chemoradiotherapy

Background

Neoadjuvant chemoradiotherapy (nCRT) followed by surgery benefits survival for patients with esophageal squamous cell carcinomas (ESCC) compared with surgery alone, but the clinical outcomes of nCRT are heterogeneous. This study aimed to elucidate transcriptional factor (TF) regulation network and competitive endogenous RNA (ceRNA) network determining response of ESCC to nCRT.

Materials and Methods

RNA microarray data of GSE59974 and GSE45670 were analyzed to investigate the significant changes of lincRNAs, miRNAs, mRNAs in responders and non-responders of nCRT in ESCC. Functional and enrichment analyses were conducted by clusterProfiler. The target lincRNAs and mRNAs of miRNAs were predicted by miRWalk. The ceRNA and TF regulatory networks were constructed using Cytoscape.

Results

Differentially expressed genes between responders and non-responders mainly enriched in biological process including Wnt signaling pathway and regulation of cell development and morphogenesis involved in differentiation. Besides, these genes showed enrichment in molecular function of glycosaminoglycan binding, metalloendopeptidase inhibitor and growth factor activity. KEGG analysis enriched these genes in pathways of neurotrophin signaling pathway, cell adhesion molecules and Wnt signaling pathway. We also constructed ceRNA network and TF network regulating response of ESCC to nCRT. Core regulatory miRNAs were miR-520a, miR-548am, miR-3184, miR-548d, miR-4725, miR-148a, miR-4659a and key regulatory TFs included MBNL1, SLC26A3, BMP4, ZIC1 and ANKRD7.

Conclusion

We identified significantly altered lincRNAs, miRNAs and mRNAs involved in the nCRT response of ESCC. In addition, the ceRNA regulatory network of lincRNA-miRNA-mRNA and TF regulatory network were constructed, which would elucidate novel molecular mechanisms determining nCRT response of ESCC, thus providing promising clues for clinical therapy.

Gynoecium development: networks in Arabidopsis and beyond

Life has always found a way to preserve itself. One strategy that has been developed for this purpose is sexual reproduction. In land plants, the gynoecium is considered to be at the top of evolutionary innovation, since it has been a key factor in the success of the angiosperms. The gynoecium is composed of carpels with different tissues that need to develop and differentiate in the correct way. In order to control and guide gynoecium development, plants have adapted elements of pre-existing gene regulatory networks (GRNs) but new ones have also evolved. The GRNs can interact with internal factors (e.g. hormones and other metabolites) and external factors (e.g. mechanical signals and temperature) at different levels, giving robustness and flexibility to gynoecium development. Here, we review recent findings regarding the role of cytokinin-auxin crosstalk and the genes that connect these hormonal pathways during early gynoecium development. We also discuss some examples of internal and external factors that can modify GRNs. Finally, we make a journey through the flowering plant lineage to determine how conserved are these GRNs that regulate gynoecium and fruit development.

Intracellular Regulome Variability Along the Organ of Corti: Evidence, Approaches, Challenges, and Perspective

The mammalian hearing organ is a regular array of two types of hair cells (HCs) surrounded by six types of supporting cells. Along the tonotopic axis, this conserved radial array of cell types shows longitudinal variations to enhance the tuning properties of basilar membrane. We present the current evidence supporting the hypothesis that quantitative local variations in gene expression profiles are responsible for local cell responses to global gene manipulations. With the advent of next generation sequencing and the unprecedented array of technologies offering high throughput analyses at the single cell level, transcriptomics will become a common tool to enhance our understanding of the inner ear. We provide an overview of the approaches and landmark studies undertaken to date to analyze single cell variations in the organ of Corti and discuss the current limitations. We next provide an overview of the complexity of known regulatory mechanisms in the inner ear. These mechanisms are tightly regulated temporally and spatially at the transcription, RNA-splicing, mRNA-regulation, and translation levels. Understanding the intricacies of regulatory mechanisms at play in the inner ear will require the use of complementary approaches, and most probably, a combinatorial strategy coupling transcriptomics, proteomics, and epigenomics technologies. We highlight how these data, in conjunction with recent insights into molecular cell transformation, can advance attempts to restore lost hair cells.

Similar bowtie structures and distinct largest strong components are identified in the transcriptional regulatory networks of Arabidopsis thaliana during photomorphogenesis and heat shock

Photomorphogenesis and heat shock are critical biological processes of plants. A recent research constructed the transcriptional regulatory networks (TRNs) of Arabidopsis thaliana during these processes using DNase-seq. In this study, by strong decomposition, we revealed that each of these TRNs can be represented as a similar bowtie structure with only one non-trivial and distinct strong component. We further identified distinct patterns of variation of a few light-related genes in these bowtie structures during photomorphogenesis. These results suggest that bowtie structure may be a common property of TRNs of plants, and distinct variation patterns of genes in bowtie structures of TRNs during biological processes may reflect distinct functions. Overall, our study provides an insight into the molecular mechanisms underlying photomorphogenesis and heat shock, and emphasizes the necessity to investigate the strong connectivity structures while studying TRNs.

Combinatorial Transcriptional Control of Plant Specialized Metabolism

Plants produce countless specialized compounds of diverse chemical nature and biological activities. Their biosynthesis often exclusively occurs either in response to environmental stresses or is limited to dedicated anatomical structures. In both scenarios, regulation of biosynthesis appears to be mainly controlled at the transcriptional level, which is generally dependent on a combined interplay of DNA-related mechanisms and the activity of transcription factors that may act in a combinatorial manner. How environmental and developmental cues are integrated into a coordinated cell type-specific stress response has only partially been unraveled so far. Building on the available examples from (metabolic) gene expression, here we propose theoretical models of how this integration of signals may occur at the level of transcriptional control.

From network to phenotype: the dynamic wiring of an Arabidopsis transcriptional network induced by osmotic stress

Plants have established different mechanisms to cope with environmental fluctuations and accordingly fine-tune their growth and development through the regulation of complex molecular networks. It is largely unknown how the network architectures change and what the key regulators in stress responses and plant growth are. Here, we investigated a complex, highly interconnected network of 20 Arabidopsis transcription factors (TFs) at the basis of leaf growth inhibition upon mild osmotic stress. We tracked the dynamic behavior of the stress-responsive TFs over time, showing the rapid induction following stress treatment, specifically in growing leaves. The connections between the TFs were uncovered using inducible overexpression lines and were validated with transient expression assays. This study resulted in the identification of a core network, composed of ERF6, ERF8, ERF9, ERF59, and ERF98, which is responsible for most transcriptional connections. The analyses highlight the biological function of this core network in environmental adaptation and its redundancy. Finally, a phenotypic analysis of loss-of-function and gain-of-function lines of the transcription factors established multiple connections between the stress-responsive network and leaf growth.

Stochastic timing in gene expression for simple regulatory strategies

Timing is essential for many cellular processes, from cellular responses to external stimuli to the cell cycle and circadian clocks. Many of these processes are based on gene expression. For example, an activated gene may be required to reach in a precise time a threshold level of expression that triggers a specific downstream process. However, gene expression is subject to stochastic fluctuations, naturally inducing an uncertainty in this threshold-crossing time with potential consequences on biological functions and phenotypes. Here, we consider such ‘timing fluctuations’ and we ask how they can be controlled. Our analytical estimates and simulations show that, for an induced gene, timing variability is minimal if the threshold level of expression is approximately half of the steady-state level. Timing fluctuations can be reduced by increasing the transcription rate, while they are insensitive to the translation rate. In presence of self-regulatory strategies, we show that self-repression reduces timing noise for threshold levels that have to be reached quickly, while self-activation is optimal at long times. These results lay a framework for understanding stochasticity of endogenous systems such as the cell cycle, as well as for the design of synthetic trigger circuits.