Transcription-Austin最新文献

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.

Proximity ligation assay (PLA) is an immunofluorescence assay, which determines in situ interaction of two biomolecules present within 40 nm close proximity. Here, we describe a modification of PLA for visual detection of in situ protein interactions with nascent RNA in a single cell (IPNR-PLA). In IPNR-PLA, nascent RNA is labeled by incorporating 5-fluorouridine (FU), a uridine nucleotide analogue, followed by covalent cross-linking of the interacting partners in proximity to newly synthesized RNA. By using combination of anti-BrdU antibody, which specifically binds to FU, and primary antibody against a protein of interest, the IPNR reaction results in fluorescent puncta as a positive signal, only if the candidate proteins are in proximity to nascent RNA. We have validated this method by demonstrating known CDK9 and elongating RNA pol II interaction with nascent RNA. Finally, we used this method to test for the presence of DNA double strand breaks as well as Poly (ADP-ribose) polymerase 1 (PARP1), an RNA binding protein, in the vicinity of nascent RNA in cancer cells. The capability of performing parallel IF labeling and quantifiable multiparameter measurements within heterogeneous cell populations makes IPNR-PLA very attractive for use in biological studies. Overall, we have developed the IPNR-PLA method for analysis of protein association with nascent RNA with single-cell resolution, which is highly sensitive, quantitative, efficient, and requires little starting experimental material.

Transcription termination is known to occur via two mechanisms in bacteria, intrinsic termination (also frequently referred to as Rho-independent or factor-independent termination) and Rho-dependent termination. Based primarily on in vitro studies using Escherichia coli RNA polymerase, it was generally assumed that intrinsic termination and Rho-dependent termination are distinct mechanisms and that the signals required for intrinsic termination are present primarily within the nucleic acids. In this review, we detail recent findings from studies in Bacillus subtilis showing that intrinsic termination in this organism is highly stimulated by NusA, NusG, and even Rho. In NusA-stimulated intrinsic termination, NusA facilitates the formation of weak terminator hairpins and compensates for distal U-rich tract interruptions. In NusG-stimulated intrinsic termination, NusG stabilizes a sequence-dependent pause at the point of termination, which extends the time frame for RNA hairpins with weak terminal base pairs to form in either a NusA-stimulated or a NusA-independent fashion. In Rho-stimulated intrinsic termination, Rho prevents the formation of antiterminator-like RNA structures that could otherwise compete with the terminator hairpin. Combined, NusA, NusG, and Rho stimulate approximately 97% of all intrinsic terminators in B. subtilis. Thus, the general view that intrinsic termination is primarily a factor-independent process needs to be revised to account for recent findings. Moreover, the historical distinction between Rho-dependent and intrinsic termination is overly simplistic and needs to be modernized.

The processing of the proximal and distal poly(A) sites in alternative polyadenylation (APA) has long been thought to independently occur on pre-mRNAs during transcription. However, a recent study by our groups demonstrated that the proximal sites for many genes could be activated sequentially following the distal ones, suggesting a multi-cleavage-same-transcript mode beyond the canonical one-cleavage-per-transcript view. Here, we review the established mechanisms for APA regulation and then discuss the additional insights into APA regulation from the perspective of sequential polyadenylation, resulting in a unified leverage model for understanding the mechanisms of regulated APA.