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.

The Δ40p53 isoform inhibits p53-dependent eRNA transcription and enables regulation by signal-specific transcription factors during p53 activation

The naturally occurring Δ40p53 isoform heterotetramerizes with wild-type p53 (WTp53) to regulate development, aging, and stress responses. How Δ40p53 alters WTp53 function remains enigmatic because their co-expression causes tetramer heterogeneity. We circumvented this issue with a well-tested strategy that expressed Δ40p53:WTp53 as a single transcript, ensuring a 2:2 tetramer stoichiometry. Human MCF10A cell lines expressing Δ40p53:WTp53, WTp53, or WTp53:WTp53 (as controls) from the native TP53 locus were examined with transcriptomics (precision nuclear run-on sequencing [PRO-seq] and RNA sequencing [RNA-seq]), metabolomics, and other methods. Δ40p53:WTp53 was transcriptionally active, and, although phenotypically similar to WTp53 under normal conditions, it failed to induce growth arrest upon Nutlin-induced p53 activation. This occurred via Δ40p53:WTp53-dependent inhibition of enhancer RNA (eRNA) transcription and subsequent failure to induce mRNA biogenesis, despite similar genomic occupancy to WTp53. A different stimulus (5-fluorouracil [5FU]) also showed Δ40p53:WTp53-specific changes in mRNA induction; however, other transcription factors (TFs; e.g., E2F2) could then drive the response, yielding similar outcomes vs. WTp53. Our results establish that Δ40p53 tempers WTp53 function to enable compensatory responses by other stimulus-specific TFs. Such modulation of WTp53 activity may be an essential physiological function for Δ40p53. Moreover, Δ40p53:WTp53 functional distinctions uncovered herein suggest an eRNA requirement for mRNA biogenesis and that human p53 evolved as a tetramer to support eRNA transcription.

A single transcript for the prognosis of disease severity in COVID-19 patients

With many countries strapped for medical resources due to the COVID-19 pandemic, it is highly desirable to allocate the precious resources to those who need them the most. Several markers have been found to be associated with the disease severity in COVID-19 patients. However, the established markers only display modest prognostic power individually and better markers are urgently needed. The aim of this study is to investigate the potential of S100A12, a prominent marker gene for bacterial infection, in the prognosis of disease severity in COVID-19 patients. To ensure the robustness of the association, a total of 1695 samples from 14 independent transcriptome datasets on sepsis, influenza infection and COVID-19 infection were examined. First, it was demonstrated that S100A12 was a marker for sepsis and severity of sepsis. Then, S100A12 was found to be a marker for severe influenza infection, and there was an upward trend of S100A12 expression as the severity level of influenza infection increased. As for COVID-19 infection, it was found that S100A12 expression was elevated in patients with severe and critical COVID-19 infection. More importantly, S100A12 expression at hospital admission was robustly correlated with future quantitative indexes of disease severity and outcome in COVID-19 patients, superior to established prognostic markers including CRP, PCT, d-dimer, ferritin, LDH and fibrinogen. Thus, S100A12 is a valuable novel prognostic marker for COVID-19 severity and deserves more attention.

Comparison of bias and resolvability in single-cell and single-transcript methods

Single-cell and single-transcript measurement methods have elevated our ability to understand and engineer biological systems. However, defining and comparing performance between methods remains a challenge, in part due to the confounding effects of experimental variability. Here, we propose a generalizable framework for performing multiple methods in parallel using split samples, so that experimental variability is shared between methods. We demonstrate the utility of this framework by performing 12 different methods in parallel to measure the same underlying reference system for cellular response. We compare method performance using quantitative evaluations of bias and resolvability. We attribute differences in method performance to steps along the measurement process such as sample preparation, signal detection, and choice of measurand. Finally, we demonstrate how this framework can be used to benchmark different methods for single-transcript detection. The framework we present here provides a practical way to compare performance of any methods.

ABE8e with Polycistronic tRNA-gRNA Expression Cassette Sig-Nificantly Improves Adenine Base Editing Efficiency in Nicotiana benthamiana

Adenine base editor containing TadA8e (ABE8e) has been reported in rice. However, the application of ABE8e in other plant species has not been described, and the comparison between ABE8e and ABE7.10, which is widely used in plants, has also been poorly studied. Here, we developed the ABE8e with the polycistronic tRNA-gRNA expression cassette (PTG-ABE8e) and PTG-ABE7.10 and compared their A-to-G editing efficiencies using both transient and stable transformation in the allotetraploid Nicotiana benthamiana. We found that the editing efficiency of PTG-ABE8e was significantly higher than that of PTG-ABE7.10, indicating that ABE8e was more efficient for A-to-G conversion in N. benthamiana. We further optimized the ABE8e editing efficiency by changing the sgRNA expression cassette and demonstrated that both PTG and single transcript unit (STU) enhanced ABE8e efficiency for A-to-G conversion in N. benthamiana. We also estimated the potential off-target effect of PTG-ABE8e at potential off-targeting sites predicted using an online tool in transgenic plants, and no off-target editing event was found for potential off-targeting sites selected, indicating that ABE8e could specifically facilitate A-to-G conversion. Our results showed that ABE8e with PTG structure was more suitable for A-to-G conversion in N. benthamiana and provided valuable clues for optimizing ABE tools in other plants.

Tissue-specific activation of gene expression by the Synergistic Activation Mediator (SAM) CRISPRa system in mice

CRISPR-based transcriptional activation is a powerful tool for functional gene interrogation; however, delivery difficulties have limited its applications in vivo. Here, we created a mouse model expressing all components of the CRISPR-Cas9 guide RNA-directed Synergistic Activation Mediator (SAM) from a single transcript that is capable of activating target genes in a tissue-specific manner. We optimized Lipid Nanoparticles and Adeno-Associated Virus guide RNA delivery approaches to achieve expression modulation of one or more genes in vivo. We utilized the SAM mouse model to generate a hypercholesteremia disease state that we could bidirectionally modulate with various guide RNAs. Additionally, we applied SAM to optimize gene expression in a humanized Transthyretin mouse model to recapitulate human expression levels. These results demonstrate that the SAM gene activation platform can facilitate in vivo research and drug discovery.

Controlling gene expression in mammalian cells using multiplexed conditional guide RNAs for Cas12a

Spatiotemporal control of the activity of Cas proteins is of considerable interest for both basic research and therapeutics. Only few mechanisms have been demonstrated for regulating the activity of guide RNAs (gRNAs) for Cas12a in mammalian cells, however, and combining and compactly integrating multiple control instances on single transcripts has not been possible so far. Here, we show that conditional processing of the 3’ tail is a viable general approach towards switchable Pol II-transcribed Cas12a gRNAs that can activate gene expression in mammalian cells in an input-dependent manner. Processing of the 3’ tail can be achieved using microRNA and short hairpin RNA as inputs, via a guanine-responsive ribozyme, and also using an RNA strand displacement mechanism. We further show that Cas12a along with several independently switchable gRNAs can be integrated on a single transcript using stabilizing RNA triplexes, providing a route towards compact Cas12a-based gene regulation constructs with multi-input switching capabilities.

Expanding the scope of plant genome engineering with Cas12a orthologs and highly multiplexable editing systems

CRISPR-Cas12a is a promising genome editing system for targeting AT-rich genomic regions. Comprehensive genome engineering requires simultaneous targeting of multiple genes at defined locations. Here, to expand the targeting scope of Cas12a, we screen nine Cas12a orthologs that have not been demonstrated in plants, and identify six, ErCas12a, Lb5Cas12a, BsCas12a, Mb2Cas12a, TsCas12a and MbCas12a, that possess high editing activity in rice. Among them, Mb2Cas12a stands out with high editing efficiency and tolerance to low temperature. An engineered Mb2Cas12a-RVRR variant enables editing with more relaxed PAM requirements in rice, yielding two times higher genome coverage than the wild type SpCas9. To enable large-scale genome engineering, we compare 12 multiplexed Cas12a systems and identify a potent system that exhibits nearly 100% biallelic editing efficiency with the ability to target as many as 16 sites in rice. This is the highest level of multiplex edits in plants to date using Cas12a. Two compact single transcript unit CRISPR-Cas12a interference systems are also developed for multi-gene repression in rice and Arabidopsis. This study greatly expands the targeting scope of Cas12a for crop genome engineering.

Coordination of -1 Programmed Ribosomal Frameshifting by Transcript and Nascent Chain Features Revealed by Deep Mutational Scanning

SummaryProgrammed ribosomal frameshifting (PRF) is a translational recoding mechanism that enables the synthesis of multiple polypeptides from a single transcript. In the alphavirus structural polyprotein, -1PRF is coordinated by a “slippery” sequence in the transcript, an RNA stem-loop, and a conformational transition in the nascent polypeptide chain. To characterize each of these effectors, we measured the effects of 4,530 mutations on -1PRF by deep mutational scanning. While most mutations within the slip-site and stem-loop disrupt -1PRF, mutagenic effects upstream of the slip-site are far more variable. Molecular dynamics simulations of polyprotein biogenesis suggest many of these mutations alter stimulatory forces on the nascent chain through their effects on translocon-mediated cotranslational folding. Finally, we provide evidence suggesting the coupling between cotranslational folding and -1PRF depends on the translation kinetics upstream of the slip-site. These findings demonstrate how -1PRF is coordinated by features within both the transcript and nascent chain.