Transcription Initiation Events Research Articles

Core promoterome of barley embryo

Precise localization and dissection of gene promoters are key to understanding transcriptional gene regulation and to successful bioengineering applications. The core RNA polymerase II initiation machinery is highly conserved among eukaryotes, leading to a general expectation of equivalent underlying mechanisms. Still, less is known about promoters in the plant kingdom. In this study, we employed cap analysis of gene expression (CAGE) at three embryonic developmental stages in barley to accurately map, annotate, and quantify transcription initiation events. Unsupervised discovery of de novo sequence clusters grouped promoters based on characteristic initiator and position-specific core-promoter motifs. This grouping was complemented by the annotation of transcription factor binding site (TFBS) motifs. Integration with genome-wide epigenomic data sets and gene ontology (GO) enrichment analysis further delineated the chromatin environments and functional roles of genes associated with distinct promoter categories. The TATA-box presence governs all features explored, supporting the general model of two separate genomic regulatory environments. We describe the extent and implications of alternative transcription initiation events, including those that are specific to developmental stages, which can affect the protein sequence or the presence of regions that regulate translation. The generated promoterome dataset provides a valuable genomic resource for enhancing the functional annotation of the barley genome. It also offers insights into the transcriptional regulation of individual genes and presents opportunities for the informed manipulation of promoter architecture, with the aim of enhancing traits of agronomic importance.

BurstDECONV: a signal deconvolution method to uncover mechanisms of transcriptional bursting in live cells.

Monitoring transcription in living cells gives access to the dynamics of this complex fundamental process. It reveals that transcription is discontinuous, whereby active periods (bursts) are separated by one or several types of inactive periods of distinct lifetimes. However, decoding temporal fluctuations arising from live imaging and inferring the distinct transcriptional steps eliciting them is a challenge. We present BurstDECONV, a novel statistical inference method that deconvolves signal traces into individual transcription initiation events. We use the distribution of waiting times between successive polymerase initiation events to identify mechanistic features of transcription such as the number of rate-limiting steps and their kinetics. Comparison of our method to alternative methods emphasizes its advantages in terms of precision and flexibility. Unique features such as the direct determination of the number of promoter states and the simultaneous analysis of several potential transcription models make BurstDECONV an ideal analytic framework for live cell transcription imaging experiments. Using simulated realistic data, we found that our method is robust with regards to noise or suboptimal experimental designs. To show its generality, we applied it to different biological contexts such as Drosophila embryos or human cells.

DeepTSS: multi-branch convolutional neural network for transcription start site identification from CAGE data

BackgroundThe widespread usage of Cap Analysis of Gene Expression (CAGE) has led to numerous breakthroughs in understanding the transcription mechanisms. Recent evidence in the literature, however, suggests that CAGE suffers from transcriptional and technical noise. Regardless of the sample quality, there is a significant number of CAGE peaks that are not associated with transcription initiation events. This type of signal is typically attributed to technical noise and more frequently to random five-prime capping or transcription bioproducts. Thus, the need for computational methods emerges, that can accurately increase the signal-to-noise ratio in CAGE data, resulting in error-free transcription start site (TSS) annotation and quantification of regulatory region usage. In this study, we present DeepTSS, a novel computational method for processing CAGE samples, that combines genomic signal processing (GSP), structural DNA features, evolutionary conservation evidence and raw DNA sequence with Deep Learning (DL) to provide single-nucleotide TSS predictions with unprecedented levels of performance.ResultsTo evaluate DeepTSS, we utilized experimental data, protein-coding gene annotations and computationally-derived genome segmentations by chromatin states. DeepTSS was found to outperform existing algorithms on all benchmarks, achieving 98% precision and 96% sensitivity (accuracy 95.4%) on the protein-coding gene strategy, with 96.66% of its positive predictions overlapping active chromatin, 98.27% and 92.04% co-localized with at least one transcription factor and H3K4me3 peak.ConclusionsCAGE is a key protocol in deciphering the language of transcription, however, as every experimental protocol, it suffers from biological and technical noise that can severely affect downstream analyses. DeepTSS is a novel DL-based method for effectively removing noisy CAGE signal. In contrast to existing software, DeepTSS does not require feature selection since the embedded convolutional layers can readily identify patterns and only utilize the important ones for the classification task.This study highlights the key role that DL can play in Molecular Biology, by removing the inherent flaws of experimental protocols, that form the backbone of contemporary research. Here, we show how DeepTSS can unleash the full potential of an already popular and mature method such as CAGE, and push the boundaries of coding and non-coding gene expression regulator research even further.

PAMP-triggered genetic reprogramming involves widespread alternative transcription initiation and an immediate transcription factor wave.

Immune responses triggered by pathogen-associated molecular patterns (PAMPs) are key to pathogen defense, but drivers and stabilizers of the growth-to-defense genetic reprogramming remain incompletely understood in plants. Here, we report a time-course study of the establishment of PAMP-triggered immunity (PTI) using cap analysis of gene expression. We show that around 15% of all transcription start sites (TSSs) rapidly induced during PTI define alternative transcription initiation events. From these, we identify clear examples of regulatory TSS change via alternative inclusion of target peptides or domains in encoded proteins, or of upstream open reading frames in mRNA leader sequences. We also find that 60% of PAMP response genes respond earlier than previously thought. In particular, a cluster of rapidly and transiently PAMP-induced genes is enriched in transcription factors (TFs) whose functions, previously associated with biological processes as diverse as abiotic stress adaptation and stem cell activity, appear to converge on growth restriction. Furthermore, examples of known potentiators of PTI, in one case under direct mitogen-activated protein kinase control, support the notion that the rapidly induced TFs could constitute direct links to PTI signaling pathways and drive gene expression changes underlying establishment of the immune state.

Development of ONT-cappable-seq to unravel the transcriptional landscape of Pseudomonas phages

RNA sequencing has become the method of choice to study the transcriptional landscape of phage-infected bacteria. However, short-read RNA sequencing approaches generally fail to capture the primary 5′ and 3′ boundaries of transcripts, confounding the discovery of key transcription initiation and termination events as well as operon architectures. Yet, the elucidation of these elements is crucial for the understanding of the strategy of transcription regulation during the infection process, which is currently lacking beyond a handful of model phages. We developed ONT-cappable-seq, a specialized long-read RNA sequencing technique that allows end-to-end sequencing of primary prokaryotic transcripts using the Nanopore sequencing platform. We applied ONT-cappable-seq to study transcription of Pseudomonas aeruginosa phage LUZ7, obtaining a comprehensive genome-wide map of viral transcription start sites, terminators, and complex operon structures that fine-regulate gene expression. Our work provides new insights in the RNA biology of a non-model phage, unveiling distinct promoter architectures, putative small non-coding viral RNAs, and the prominent regulatory role of terminators during infection. The robust workflow presented here offers a framework to obtain a global, yet fine-grained view of phage transcription and paves the way for standardized, in-depth transcription studies for microbial viruses or bacteria in general.

Signaling Mechanism of Transcriptional Bursting: A Technical Resolution-Independent Study.

Gene transcription has been uncovered to occur in sporadic bursts. However, due to technical difficulties in differentiating individual transcription initiation events, it remains debated as to whether the burst size, frequency, or both are subject to modulation by transcriptional activators. Here, to bypass technical constraints, we addressed this issue by introducing two independent theoretical methods including analytical research based on the classic two-model and information entropy research based on the architecture of transcription apparatus. Both methods connect the signaling mechanism of transcriptional bursting to the characteristics of transcriptional uncertainty (i.e., the differences in transcriptional levels of the same genes that are equally activated). By comparing the theoretical predictions with abundant experimental data collected from published papers, the results exclusively support frequency modulation. To further validate this conclusion, we showed that the data that appeared to support size modulation essentially supported frequency modulation taking into account the existence of burst clusters. This work provides a unified scheme that reconciles the debate on burst signaling.

Dual-color 3D-dSTORM colocalization and quantification of ROXY1 and RNAPII variants throughout the transcription cycle in root meristem nuclei.

To unravel the function of a protein of interest, it is crucial to asses to what extent it associates via direct interactions or by overlapping expression with other proteins. ROXY1, a land plant-specific glutaredoxin, exerts a function in Arabidopsis flower development and interacts with TGA transcription factors in the nucleus. We detected a novel ROXY1 function in the root meristem. Root cells that lack chlorophyll reducing plant-specific background problems that can hamper colocalization 3D microscopy. Thus far, a super-resolution three-dimensional stochastic optical reconstruction microscopy (3D-dSTORM) approach has mainly been applied in animal studies. We established 3D-dSTORM using the roxy1 mutant complemented with green fluorescence protein-ROXY1 and investigated its colocalization with three distinct RNAPII isoforms. To quantify the colocalization results, 3D-dSTORM was coupled with the coordinate-based colocalization method. Interestingly, ROXY1 proteins colocalize with different RNA polymerase II (RNAPII) isoforms that are active at distinct transcription cycle steps. Our colocalization data provide new insights on nuclear glutaredoxin activities suggesting that ROXY1 is not only required in early transcription initiation events via interaction with transcription factors but likely also participates throughout further transcription processes until late termination steps. Furthermore, we showed the applicability of the combined approaches to detect and quantify responses to altered growth conditions, exemplified by analysis of H2 O2 treatment, causing a dissociation of ROXY1 and RNAPII isoforms. We envisage that the powerful dual-color 3D-dSTORM/coordinate-based colocalization combination offers plant cell biologists the opportunity to colocalize and quantify root meristem proteins at an increased, unprecedented resolution level <50nm, which will enable the detection of novel subcellular protein associations and functions.

Saccharomyces cerevisiae displays a stable transcription start site landscape in multiple conditions

One of the fundamental processes that determine cellular fate is regulation of gene transcription. Understanding these regulatory processes is therefore essential for understanding cellular responses to changes in environmental conditions. At the core promoter, the regulatory region containing the transcription start site (TSS), all inputs regulating transcription are integrated. Here, we used Cap Analysis of Gene Expression (CAGE) to analyze the pattern of TSSs at four different environmental conditions (limited in ethanol, limited in nitrogen, limited in glucose and limited in glucose under anaerobic conditions) using the Saccharomyces cerevisiae strain CEN.PK113-7D. With this experimental setup, we were able to show that the TSS landscape in yeast is stable at different metabolic states of the cell. We also show that the spatial distribution of transcription initiation events, described by the shape index, has a surprisingly strong negative correlation with measured gene expression levels, meaning that genes with higher expression levels tend to have a broader distribution of TSSs. Our analysis supplies a set of high-quality TSS annotations useful for metabolic engineering and synthetic biology approaches in the industrially relevant laboratory strain CEN.PK113-7D, and provides novel insights into yeast TSS dynamics and gene regulation.

Full-length mRNA sequencing uncovers a widespread coupling between transcription initiation and mRNA processing

BackgroundThe multifaceted control of gene expression requires tight coordination of regulatory mechanisms at transcriptional and post-transcriptional level. Here, we studied the interdependence of transcription initiation, splicing and polyadenylation events on single mRNA molecules by full-length mRNA sequencing.ResultsIn MCF-7 breast cancer cells, we find 2700 genes with interdependent alternative transcription initiation, splicing and polyadenylation events, both in proximal and distant parts of mRNA molecules, including examples of coupling between transcription start sites and polyadenylation sites. The analysis of three human primary tissues (brain, heart and liver) reveals similar patterns of interdependency between transcription initiation and mRNA processing events. We predict thousands of novel open reading frames from full-length mRNA sequences and obtained evidence for their translation by shotgun proteomics. The mapping database rescues 358 previously unassigned peptides and improves the assignment of others. By recognizing sample-specific amino-acid changes and novel splicing patterns, full-length mRNA sequencing improves proteogenomics analysis of MCF-7 cells.ConclusionsOur findings demonstrate that our understanding of transcriptome complexity is far from complete and provides a basis to reveal largely unresolved mechanisms that coordinate transcription initiation and mRNA processing.

Initiation, Elongation, and Realignment during Influenza Virus mRNA Synthesis.

ABSTRACTThe RNA-dependent RNA polymerase (RdRp) of the influenza A virus replicates and transcribes the viral genome segments in the nucleus of the host cell. To transcribe these viral genome segments, the RdRp “snatches” capped RNA oligonucleotides from nascent host cell mRNAs and aligns these primers to the ultimate or penultimate nucleotide of the segments for the initiation of viral mRNA synthesis. It has been proposed that this initiation process is not processive and that the RdRp uses a prime-realign mechanism during transcription. Here we provide in vitro evidence for the existence of this transcriptional prime-realign mechanism but show that it functions efficiently only for primers that are short or cannot stably base pair with the template. In addition, we demonstrate that transcriptional elongation is dependent on the priming loop of the PB1 subunit of the RdRp. We propose that the prime-realign mechanism may be used to rescue abortive transcription initiation events or cope with sequence variation among primers. Overall, these observations advance our mechanistic understanding of how influenza A virus initiates transcription correctly and efficiently.IMPORTANCE Influenza A virus causes severe disease in humans and is considered a major global health threat. The virus replicates and transcribes its genome by using an enzyme called the RNA polymerase. To ensure that the genome is amplified faithfully and abundant viral mRNAs are made for viral protein synthesis, the viral RNA polymerase must transcribe the viral genome efficiently. In this report, we characterize a structure inside the polymerase that contributes to the efficiency of viral mRNA synthesis.

Transcription start site profiling of 15 anatomical regions of the Macaca mulatta central nervous system

Rhesus macaque was the second non-human primate whose genome has been fully sequenced and is one of the most used model organisms to study human biology and disease, thanks to the close evolutionary relationship between the two species. But compared to human, where several previously unknown RNAs have been uncovered, the macaque transcriptome is less studied. Publicly available RNA expression resources for macaque are limited, even for brain, which is highly relevant to study human cognitive abilities. In an effort to complement those resources, FANTOM5 profiled 15 distinct anatomical regions of the aged macaque central nervous system using Cap Analysis of Gene Expression, a high-resolution, annotation-independent technology that allows monitoring of transcription initiation events with high accuracy. We identified 25,869 CAGE peaks, representing bona fide promoters. For each peak we provide detailed annotation, expanding the landscape of ‘known’ macaque genes, and we show concrete examples on how to use the resulting data. We believe this data represents a useful resource to understand the central nervous system in macaque.

FANTOM5 CAGE profiles of human and mouse samples

In the FANTOM5 project, transcription initiation events across the human and mouse genomes were mapped at a single base-pair resolution and their frequencies were monitored by CAGE (Cap Analysis of Gene Expression) coupled with single-molecule sequencing. Approximately three thousands of samples, consisting of a variety of primary cells, tissues, cell lines, and time series samples during cell activation and development, were subjected to a uniform pipeline of CAGE data production. The analysis pipeline started by measuring RNA extracts to assess their quality, and continued to CAGE library production by using a robotic or a manual workflow, single molecule sequencing, and computational processing to generate frequencies of transcription initiation. Resulting data represents the consequence of transcriptional regulation in each analyzed state of mammalian cells. Non-overlapping peaks over the CAGE profiles, approximately 200,000 and 150,000 peaks for the human and mouse genomes, were identified and annotated to provide precise location of known promoters as well as novel ones, and to quantify their activities.

Controlling gene expression by DNA mechanics: emerging insights and challenges.

Transcription initiation is a major control point for the precise regulation of gene expression. Our knowledge of this process has been mainly derived from protein-centric studies wherein cis-regulatory DNA sequences play a passive role, mainly in arranging the protein machinery to coalesce at the transcription start sites of genes in a spatial and temporal-specific manner. However, this is a highly dynamic process in which molecular motors such as RNA polymerase II (RNAPII), helicases, and other transcription factors, alter the level of mechanical force in DNA, rather than simply a set of static DNA-protein interactions. The double helix is a fiber that responds to flexural and torsional stress, which if accumulated, can affect promoter output as well as change DNA and chromatin structure. The relationship between DNA mechanics and the control of early transcription initiation events has been under-investigated. Genomic techniques to display topological stress and conformational variation in DNA across the mammalian genome provide an exciting new insight on the role of DNA mechanics in the early stages of the transcription cycle. Without understanding how torsional and flexural stresses are generated, transmitted, and dissipated, no model of transcription will be complete and accurate.

Controlling gene expression by DNA mechanics: emerging insights and challenges

Transcription initiation is a major control point for the precise regulation of gene expression. Our knowledge of this process has been mainly derived from protein-centric studies wherein cis-regulatory DNA sequences play a passive role, mainly in arranging the protein machinery to coalesce at the transcription start sites of genes in a spatial and temporal-specific manner. However, this is a highly dynamic process in which molecular motors such as RNA polymerase II (RNAPII), helicases, and other transcription factors, alter the level of mechanical force in DNA, rather than simply a set of static DNA-protein interactions. The double helix is a fiber that responds to flexural and torsional stress, which if accumulated, can affect promoter output as well as change DNA and chromatin structure. The relationship between DNA mechanics and the control of early transcription initiation events has been under-investigated. Genomic techniques to display topological stress and conformational variation in DNA across the mammalian genome provide an exciting new insight on the role of DNA mechanics in the early stages of the transcription cycle. Without understanding how torsional and flexural stresses are generated, transmitted, and dissipated, no model of transcription will be complete and accurate.

Landscape and Dynamics of Transcription Initiation in the Malaria Parasite Plasmodium falciparum.

A comprehensive map of transcription start sites (TSSs) across the highly AT-rich genome of P. falciparum would aid progress toward deciphering the molecular mechanisms that underlie the timely regulation of gene expression in this malaria parasite. Using high-throughput sequencing technologies, we generated a comprehensive atlas of transcription initiation events at single-nucleotide resolution during the parasite intra-erythrocytic developmental cycle. This detailed analysis of TSS usage enabled us to define architectural features of plasmodial promoters. We demonstrate that TSS selection and strength are constrained by local nucleotide composition. Furthermore, we provide evidence for coordinate and stage-specific TSS usage from distinct sites within the same transcription unit, thereby producing transcript isoforms, a subset of which are developmentally regulated. This work offers a framework for further investigations into the interactions between genomic sequences and regulatory factors governing the complex transcriptional program of this major human pathogen.

Genomic Organization of Human Transcription Initiation Complexes.

A repertoire of transcription initiation factors engage the core promoter of mRNA genes to recruit RNA polymerase (Pol) II to initiate transcription, yet their precise spatial organization remains unclear. Using ChIP-exo, here we detail the interactions and genomic organization of initiation factors TBP, TFIIB, and Pol II at mRNA genes and within CpG islands. We find that when Pol II moves into a transcriptionally paused state, TBP/TFIIB remain at the promoter. We show that TBP and TFIIB bound to the core promoter at two separate, resolvable locations that coincided with sites of divergent transcription initiation. We also examine the precise binding of TBP at Pol III transcribed tRNA genes. We find that TBP crosslinked to tRNA genes in a similar manner as at Pol II transcribed genes. This comprehensive and high resolution genome-wide detection of the initiation machinery produces a consolidated view of transcription initiation events humans at Pol II coding and Pol III transcribed tRNA genes.

A systematic mutational analysis of a histone H3 residue in budding yeast provides insights into chromatin dynamics.

In previous work using the Saccharomyces cerevisiae model system, a mutant version of histone H3—H3-L61W—was found to confer a variety of abnormal growth phenotypes and defects in specific aspects of the transcription process, including a pronounced alteration in the distribution pattern of the transcription elongation factor Spt16 across transcribed genes and promotion of cryptic transcription initiation within the FLO8 gene. To gain insights into the contribution of the H3-L61 residue to chromatin function, we have generated yeast strains expressing versions of histone H3 harboring all possible natural amino acid substitutions at position 61 (H3-L61X mutants) and tested them in a series of assays. We found that whereas 16 of the 19 H3-L61X mutants support viability when expressed as the sole source of histone H3 in cells, all 19 confer abnormal phenotypes ranging from very mild to severe, a finding that might in part explain the high degree of conservation of the H3-L61 residue among eukaryotes. An examination of the strength of the defects conferred by each H3-L61X mutant and the nature of the corresponding substituted residue provides insights into structural features of the nucleosome required for proper Spt16−gene interactions and for prevention of cryptic transcription initiation events. Finally, we provide evidence that the defects imparted by H3-L61X mutants on Spt16−gene interactions and on repression of intragenic transcription initiation are mechanistically related to each other.

Twenty years of RNA: reflections from the RNP world.

Twenty years of RNA: reflections from the RNP world.

RECLU: a pipeline to discover reproducible transcriptional start sites and their alternative regulation using capped analysis of gene expression (CAGE).

BackgroundNext generation sequencing based technologies are being extensively used to study transcriptomes. Among these, cap analysis of gene expression (CAGE) is specialized in detecting the most 5’ ends of RNA molecules. After mapping the sequenced reads back to a reference genome CAGE data highlights the transcriptional start sites (TSSs) and their usage at a single nucleotide resolution.ResultsWe propose a pipeline to group the single nucleotide TSS into larger reproducible peaks and compare their usage across biological states. Importantly, our pipeline discovers broad peaks as well as the fine structure of individual transcriptional start sites embedded within them. We assess the performance of our approach on a large CAGE datasets including 156 primary cell types and two cell lines with biological replicas. We demonstrate that genes have complicated structures of transcription initiation events. In particular, we discover that narrow peaks embedded in broader regions of transcriptional activity can be differentially used even if the larger region is not.ConclusionsBy examining the reproducible fine scaled organization of TSS we can detect many differentially regulated peaks undetected by previous approaches.

Detection and classification of peaks in 5' cap RNA sequencing data.

BackgroundThe large-scale sequencing of 5' cap enriched cDNA promises to reveal the diversity of transcription initiation across entire genomes. The process of transcription is noisy, and there is often no single, exact start site. This creates the need for a fast and simple method of identifying transcription start peaks based on this type of data. Due to both biological and technical noise, many of the peaks seen are not real transcription initiation events. Classification of the observed peaks is an essential filtering step in the discovery of genuine initiation locations.ResultsWe develop a two-stage approach consisting of a fast and simple algorithm based on a sliding window with Poisson null distribution for detecting the genomic locations of peaks, followed by a linear support vector machine classifier to distinguish between peaks which represent the initiation of transcription and peaks that do not. Comparison of classification performance to the best existing method based on whole genome segmentation showed comparable precision and improved recall. Internal features, which are intrinsic to the data and require no further experiments, had high precision and recall rates. Addition of pooled external data or matched RNA sequencing data resulted in gains of recall with equivalent precision.ConclusionsThe Poisson sliding window model is an effective and fast way of taking the peak neighbourhood into account, and finding statistically significant peaks over a range of transcript expression values. It is orders of magnitude faster than doing whole genome segmentation. The support vector classification scheme has better precision and recall than existing methods. Integrating additional datasets is shown to provide minor gains in recall, in comparison to using only the cap-sequencing data.