Regulon: An overview of plant abiotic stress transcriptional regulatory system and role in transgenic plants

Population growth is increasing rapidly around the world, in these consequences we need to produce more foods to full fill the demand of increased population. The world is facing global warming due to urbanizations and industrialization and in this concerns plants exposed continuously to abiotic stresses which is a major cause of crop hammering every year. Abiotic stresses consist of Drought, Salt, Heat, Cold, Oxidative and Metal toxicity which damage the crop yield continuously. Drought and salinity stress severally affected in similar manner to plant and the leading cause of reduction in crop yield. Plants respond to various stimuli under abiotic or biotic stress condition and express certain genes either structural or regulatory genes which maintain the plant integrity. The regulatory genes primarily the transcription factors that exert their activity by binding to certain cis DNA elements and consequently either up regulated or down regulate to target expression. These transcription factors are known as masters regulators because its single transcript regulate more than one gene, in this context the regulon word is fascinating more in compass of transcription factors. Progress has been made to better understand about effect of regulons (AREB/ABF, DREB, MYB, and NAC) under abiotic stresses and a number of regulons reported for stress responsive and used as a better transgenic tool of Arabidopsis and Rice.

Transcriptional Regulatory Network Topology with Applications to Bio-inspired Networking: A Survey

The advent of the edge computing network paradigm places the computational and storage resources away from the data centers and closer to the edge of the network largely comprising the heterogeneous IoT devices collecting huge volumes of data. This paradigm has led to considerable improvement in network latency and bandwidth usage over the traditional cloud-centric paradigm. However, the next generation networks continue to be stymied by their inability to achieve adaptive, energy-efficient, timely data transfer in a dynamic and failure-prone environment—the very optimization challenges that are dealt with by biological networks as a consequence of millions of years of evolution. The transcriptional regulatory network (TRN) is a biological network whose innate topological robustness is a function of its underlying graph topology. In this article, we survey these properties of TRN and the metrics derived therefrom that lend themselves to the design of smart networking protocols and architectures. We then review a body of literature on bio-inspired networking solutions that leverage the stated properties of TRN. Finally, we present a vision for specific aspects of TRNs that may inspire future research directions in the fields of large-scale social and communication networks.

HY5: A Pivotal Regulator of Light-Dependent Development in Higher Plants

ELONGATED HYPOCOTYL5 (HY5), a bZIP-type transcription factor, acts as a master regulator that regulates various physiological and biological processes in plants such as photomorphogenesis, root growth, flavonoid biosynthesis and accumulation, nutrient acquisition, and response to abiotic stresses. HY5 is evolutionally conserved in function among various plant species. HY5 acts as a master regulator of light-mediated transcriptional regulatory hub that directly or indirectly controls the transcription of approximately one-third of genes at the whole genome level. The transcription, protein abundance, and activity of HY5 are tightly modulated by a variety of factors through distinct regulatory mechanisms. This review primarily summarizes recent advances on HY5-mediated molecular and physiological processes and regulatory mechanisms on HY5 in the model plant Arabidopsis as well as in crops.

Exosomal and Plasma Non-Coding RNA Signature Associated with Urinary Albumin Excretion in Hypertension

Non-coding RNA (ncRNA), released into circulation or packaged into exosomes, plays important roles in many biological processes in the kidney. The purpose of the present study is to identify a common ncRNA signature associated with early renal damage and its related molecular pathways. Three individual libraries (plasma and urinary exosomes, and total plasma) were prepared from each hypertensive patient (with or without albuminuria) for ncRNA sequencing analysis. Next, an RNA-based transcriptional regulatory network was constructed. The three RNA biotypes with the greatest number of differentially expressed transcripts were long-ncRNA (lncRNA), microRNA (miRNA) and piwi-interacting RNA (piRNAs). We identified a common 24 ncRNA molecular signature related to hypertension-associated urinary albumin excretion, of which lncRNAs were the most representative. In addition, the transcriptional regulatory network showed five lncRNAs (LINC02614, BAALC-AS1, FAM230B, LOC100505824 and LINC01484) and the miR-301a-3p to play a significant role in network organization and targeting critical pathways regulating filtration barrier integrity and tubule reabsorption. Our study found an ncRNA profile associated with albuminuria, independent of biofluid origin (urine or plasma, circulating or in exosomes) that identifies a handful of potential targets, which may be utilized to study mechanisms of albuminuria and cardiovascular damage.

Machine-learning from Pseudomonas putida transcriptomes reveals its transcriptional regulatory network

Bacterial gene expression is orchestrated by numerous transcription factors (TFs). Elucidating how gene expression is regulated is fundamental to understanding bacterial physiology and engineering it for practical use. In this study, a machine-learning approach was applied to uncover the genome-scale transcriptional regulatory network (TRN) in Pseudomonas putida, an important organism for bioproduction. We performed independent component analysis of a compendium of 321 high-quality gene expression profiles, which were previously published or newly generated in this study. We identified 84 groups of independently modulated genes (iModulons) that explain 75.7% of the total variance in the compendium. With these iModulons, we (i) expand our understanding of the regulatory functions of 39 iModulon associated TFs (e.g., HexR, Zur) by systematic comparison with 1,993 previously reported TF-gene interactions; (ii) outline transcriptional changes after the transition from the exponential growth to stationary phases; (iii) capture group of genes required for utilizing diverse carbon sources and increased stationary response with slower growth rates; (iv) unveil multiple evolutionary strategies of transcriptome reallocation to achieve fast growth rates; and (v) define an osmotic stimulon, which includes the Type VI secretion system, as coordination of multiple iModulon activity changes. Taken together, this study provides the first quantitative genome-scale TRN for P. putida and a basis for a comprehensive understanding of its complex transcriptome changes in a variety of physiological states.

Pan-genomic analysis of transcriptional modules across Salmonella Typhimurium reveals the regulatory landscape of different strains

Salmonella enterica Typhimurium is a serious pathogen that is involved in human nontyphoidal infections. Tackling Typhimurium infections is difficult due to the species' dynamic adaptation to its environment, which is dictated by a complex transcriptional regulatory network (TRN). While traditional biomolecular methods provide characterizations of specific regulators, it is laborious to construct the global TRN structure from this bottom-up approach. Here, we used a machine learning technique to understand the transcriptional signatures of S. enterica Typhimurium from the top down, as a whole and in individual strains. Furthermore, we conducted cross-strain comparison of 6 strains in serovar Typhimurium to investigate similarities and differences in their TRNs with pan-genomic analysis. By decomposing all the publicly available RNA-Seq data of Typhimurium with independent component analysis (ICA), we obtained over 400 independently modulated sets of genes, called iModulons. Through analysis of these iModulons, we 1) discover three transport iModulons linked to antibiotic resistance, 2) describe concerted responses to cationic antimicrobial peptides (CAMPs), 3) uncover evidence towards new regulons, and 4) identify two iModulons linked to bile responses in strain ST4/74. We extend this analysis across the pan-genome to show that strain-specific iModulons 5) reveal different genetic signatures in pathogenicity islands that explain phenotypes and 6) capture the activity of different phages in the studied strains. Using all high-quality publicly-available RNA-Seq data to date, we present a comprehensive, data-driven Typhimurium TRN. It is conceivable that with more high-quality datasets from more strains, the approach used in this study will continue to guide our investigation in understanding the pan-transcriptome of Typhimurium. Interactive dashboards for all gene modules in this project are available at https://imodulondb.org/ to enable browsing for interested researchers.

STREAMING-tag system reveals spatiotemporal relationships between transcriptional regulatory factors and transcriptional activity

Transcription is a dynamic process that stochastically switches between the ON and OFF states. To detect the dynamic relationship among protein clusters of RNA polymerase II (RNAPII) and coactivators, gene loci, and transcriptional activity, we inserted an MS2 repeat, a TetO repeat, and inteins with a selection marker just downstream of the transcription start site (TSS). By optimizing the individual elements, we have developed the Spliced TetO REpeAt, MS2 repeat, and INtein sandwiched reporter Gene tag (STREAMING-tag) system. Clusters of RNAPII and BRD4 were observed proximally to the TSS of Nanog when the gene was transcribed in mouse embryonic stem cells. In contrast, clusters of MED19 and MED22 Mediator subunits were constitutively located near the TSS. Thus, the STREAMING-tag system revealed the spatiotemporal relationships between transcriptional activity and protein clusters near the gene. This powerful tool is useful for quantitatively understanding dynamic transcriptional regulation in living cells.

Comparative Analysis of Physiological, Enzymatic, and Transcriptomic Responses Revealed Mechanisms of Salt Tolerance and Recovery in Tritipyrum

Salt stress results in the severe decline of yield and quality in wheat. In the present study, salt-tolerant Tritipyrum (“Y1805”) and salt-sensitive wheat “Chinese Spring” (“CS”) were selected from 121 wheat germplasms to test their physiological, antioxidant enzyme, and transcriptomic responses and mechanisms against salt stress and recovery. 56 chromosomes were identified in “Y1805” that comprised A, B, and D chromosomes from wheat parent and E chromosomes from Thinopyrum elongatum, adding to salt-tolerant trait. Salt stress had a greater inhibitory effect on roots than on shoots, and “Y1805” demonstrated stronger salt tolerance than “CS.” Compared with “CS,” the activities of superoxide dismutase and catalase in “Y1805” significantly increased under salt stress. “Y1805” could synthesize more proline and soluble sugars than “CS.” Both the net photosynthetic rate and chlorophyll a/b were affected by salt stress, though the level of damage in “Y1805” was significantly less than in “CS.” Transcriptome analysis showed that the differences in the transcriptional regulatory networks of “Y1805” were not only in response to salt stress but also in recovery. The functions of many salt-responsive differentially expressed genes were correlated closely with the pathways “peroxisome,” “arginine and proline metabolism,” “starch and sucrose metabolism,” “chlorophyll and porphyrin metabolism,” and “photosynthesis.”

Integrated genomic analysis of AgRP neurons reveals that IRF3 regulates leptin's hunger-suppressing effects

AgRP neurons in the arcuate nucleus of the hypothalamus (ARC) coordinate homeostatic changes in appetite associated with fluctuations in food availability and leptin signaling. Identifying the relevant transcriptional regulatory pathways in these neurons has been a priority, yet such attempts have been stymied due to their low abundance and the rich cellular diversity of the ARC. Here we generated AgRP neuron-specific transcriptomic and chromatin accessibility profiles during opposing states of fasting-induced hunger and leptin-induced hunger suppression. Cis-regulatory analysis of these integrated datasets enabled the identification of 28 putative hunger-promoting and 29 putative hunger-suppressing transcriptional regulators in AgRP neurons, 16 of which were predicted to be transcriptional effectors of leptin. Within our dataset, Interferon regulatory factor 3 (IRF3) emerged as a leading candidate mediator of leptin-induced hunger-suppression. Gain- and loss-of-function experiments in vivo confirm the role of IRF3 in mediating the acute satiety-evoking effects of leptin in AgRP neurons, while live-cell imaging in vitro indicate that leptin can activate neuronal IRF3 in a cell autonomous manner. Finally, we employ CUT&RUN to uncover direct transcriptional targets of IRF3 in AgRP neurons in vivo. Thus, our findings identify AgRP neuron-expressed IRF3 as a key transcriptional effector of the hunger-suppressing effects of leptin.