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Caenorhabditis elegans can enter a diapause stage called "dauer" when it senses that the environment is not suitable for development. This implies a detour from the typical developmental trajectory and requires a tight control of the developmental clock and a massive tissue remodeling. In the last decades, core components of the signaling pathways that govern the dauer development decision have been identified, but the tissues where they function for the acquisition of dauer-specific traits are still under intense study. Growing evidence demonstrates that these pathways engage in complex cross-talk and feedback loops. In this review, we summarize the current knowledge regarding the transcriptional regulation of the dauer program and the relevant tissues for its achievement. A better understanding of this process will provide insight on how developmental plasticity is achieved and how development decisions are under a robust regulation to ensure an all-or-nothing response. Furthermore, this developmental decision can also serve as a simplified model for relevant developmental disorders.Abbreviations: AID Auxin Induced Degron DA dafachronic acid Daf-c dauer formation constitutive Daf-d dauer formation defective DTC Distal Tip Cells ECM modified extracellular matrix GPCRs G protein-coupled receptors IIS insulin/IGF-1 signaling ILPs insulin-like peptides LBD Ligand Binding Domain PDL4 Post Dauer L4 TGF-β transforming growth factor beta WT wild-type.

Eukaryotic cells rely upon dynamic, multifaceted regulation at each step of RNA biogenesis to maintain mRNA pools and ensure normal protein synthesis. Studies in budding yeast indicate a buffering phenomenon that preserves global mRNA levels through the reciprocal balancing of RNA synthesis rates and mRNA decay. In short, changes in transcription impact the efficiency of mRNA degradation and defects in either nuclear or cytoplasmic mRNA degradation are somehow sensed and relayed to control a compensatory change in mRNA transcription rates. Here, we review current views on molecular mechanisms that might explain this apparent bidirectional sensing process that ensures homeostasis of the stable mRNA pool.

RNA polymerase II (Pol II) is composed of 12 subunits that collaborate to synthesize mRNA within the nucleus. Pol II is widely recognized as a passive holoenzyme, with the molecular functions of its subunits largely ignored. Recent studies employing auxin-inducible degron (AID) and multi-omics techniques have revealed that the functional diversity of Pol II is achieved through the differential contributions of its subunits to various transcriptional and post-transcriptional processes. By regulating these processes in a coordinated manner through its subunits, Pol II can optimize its activity for diverse biological functions. Here, we review recent progress in understanding Pol II subunits and their dysregulation in diseases, Pol II heterogeneity, Pol II clusters and the regulatory roles of RNA polymerases.

Microsporidia are eukaryotic obligate intracellular parasites closely related to fungi. Co-evolving with infected hosts, microsporidia have highly reduced their genomes and lacked several biological components. As it is beneficial for intracellular parasites like microsporidia to reduce their genome size, it is therefore reasonable to assume that genes encoding multifactorial complex machinery of transcription could be a potential target to be excluded from microsporidian genomes during the reductive evolution. In such a case, an evolutionary dilemma occurs because microsporidia cannot remove all transcription-machinery-encoding genes, products of which are essential for initialthe initial steps of gene expression. Here, I propose that while genes encoding core machinery are conserved, several genes known to function in fine-tune regulation of transcription are absent. This genome compaction strategy may come at the cost of loosely regulated or less controllable transcription. Alternatively, analogous to microsporidian polar tube, the parasites may have specialized factors to regulate their RNA synthesis.

Cell type-specific gene expression is coordinated by DNA-encoded enhancers and the transcription factors (TFs) that bind to them in a sequence-specific manner. As such, these enhancers and TFs are critical mediators of normal development and altered enhancer or TF function is associated with the development of diseases such as cancer. While initially defined by their ability to activate gene transcription in reporter assays, putative enhancer elements are now frequently defined by their unique chromatin features including DNase hypersensitivity and transposase accessibility, bidirectional enhancer RNA (eRNA) transcription, CpG hypomethylation, high H3K27ac and H3K4me1, sequence-specific transcription factor binding, and co-factor recruitment. Identification of these chromatin features through sequencing-based assays has revolutionized our ability to identify enhancer elements on a genome-wide scale, and genome-wide functional assays are now capitalizing on this information to greatly expand our understanding of how enhancers function to provide spatiotemporal coordination of gene expression programs. Here, we highlight recent technological advances that are providing new insights into the molecular mechanisms by which these critical cis-regulatory elements function in gene control. We pay particular attention to advances in our understanding of enhancer transcription, enhancer-promoter syntax, 3D organization and biomolecular condensates, transcription factor and co-factor dependencies, and the development of genome-wide functional enhancer screens.

The profiling of gene expression patterns to glean biological insights from single cells has become commonplace over the last few years. However, this approach overlooks the transcript contents that can differ between individual cells and cell populations. In this review, we describe early work in the field of single-cell short-read sequencing as well as full-length isoforms from single cells. We then describe recent work in single-cell long-read sequencing wherein some transcript elements have been observed to work in tandem. Based on earlier work in bulk tissue, we motivate the study of combination patterns of other RNA variables. Given that we are still blind to some aspects of isoform biology, we suggest possible future avenues such as CRISPR screens which can further illuminate the function of RNA variables in distinct cell populations.

Across all kingdoms of life, gene regulatory mechanisms underlie cellular adaptation to ever-changing environments. Regulation of gene expression adjusts protein synthesis and, in turn, cellular growth. Messenger RNAs are key molecules in the process of gene expression. Our ability to quantitatively measure mRNA expression in single cells has improved tremendously over the past decades. This revealed an unexpected coordination between the steps that control the life of an mRNA, from transcription to degradation. Here, we provide an overview of the state-of-the-art imaging approaches for measurement and quantitative understanding of gene expression, starting from the early visualizations of single genes by electron microscopy to current fluorescence-based approaches in single cells, including live-cell RNA-imaging approaches to FISH-based spatial transcriptomics across model organisms. We also highlight how these methods have shaped our current understanding of the spatiotemporal coupling between transcriptional and post-transcriptional events in prokaryotes. We conclude by discussing future challenges of this multidisciplinary field.Abbreviations: mRNA: messenger RNA; rRNA: ribosomal rDNA; tRNA: transfer RNA; sRNA: small RNA; FISH: fluorescence in situ hybridization; RNP: ribonucleoprotein; smFISH: single RNA molecule FISH; smiFISH: single molecule inexpensive FISH; HCR-FISH: Hybridization Chain-Reaction-FISH; RCA: Rolling Circle Amplification; seqFISH: Sequential FISH; MERFISH: Multiplexed error robust FISH; UTR: Untranslated region; RBP: RNA binding protein; FP: fluorescent protein; eGFP: enhanced GFP, MCP: MS2 coat protein; PCP: PP7 coat protein; MB: Molecular beacons; sgRNA: single guide RNA.

The development of highly parallel and affordable high-throughput single-cell transcriptomics technologies has revolutionized our understanding of brain complexity. These methods have been used to build cellular maps of the brain, its different regions, and catalog the diversity of cells in each of them during development, aging and even in disease. Now we know that cellular diversity is way beyond what was previously thought. Single-cell transcriptomics analyses have revealed that cell types previously considered homogeneous based on imaging techniques differ depending on several factors including sex, age and location within the brain. The expression profiles of these cells have also been exploited to understand which are the regulatory programs behind cellular diversity and decipher the transcriptional pathways driving them. In this review, we summarize how single-cell transcriptomics have changed our view on the cellular diversity in the human brain, and how it could impact the way we study neurodegenerative diseases. Moreover, we describe the new computational approaches that can be used to study cellular differentiation and gain insight into the functions of individual cell populations under different conditions and their alterations in disease.

Single-cell sequencing of RNA (scRNA-seq) has advanced our understanding of cellular heterogeneity and signaling in developmental biology and disease. A large number of complementary assays have been developed to profile transcriptomes of individual cells, also in combination with other readouts, such as chromatin accessibility or antibody-based analysis of protein surface markers. As scRNA-seq technologies are advancing fast, it is challenging to establish robust workflows and up-to-date protocols that are best suited to address the large range of research questions. Here, we review scRNA-seq techniques from mRNA end-counting to total RNA in relation to their specific features and outline the necessary sample preparation steps and quality control measures. Based on our experience in dealing with the continuously growing portfolio from the perspective of a central single-cell facility, we aim to provide guidance on how workflows can be best automatized and share our experience in coping with the continuous expansion of scRNA-seq techniques.