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558 results for “Transcription Dynamics”
Apical Localization of RNA Polymerases Modulate Transcription Dynamics and Supercoiling Domains Revealed by Cryo-ET
<p>Supplementary materials include all particle raw tilts, 3D reconstructions, models, FSC evaluations, statistical data analyses, gel images, and oxDNA molecular dynamics simulations for the manuscript titled "<strong>Apical Localization of RNA Polymerases Modulate Transcription Dynamics and Supercoiling Domains Revealed by Cryo-ET</strong>".</p>
Single-molecule analysis of transcription activation: dynamics of SAGA co-activator recruitment
<p>Source data for:</p> <p><strong>Single-molecule analysis of transcription activation: dynamics of SAGA co-activator recruitment</strong></p> <p><strong> </strong></p> <p>Jongcheol Jeon<sup>1</sup>, Larry J. Friedman<sup>2</sup>, Daniel H. Zhou<sup>2</sup>, Hogyu David Seo<sup>1</sup>, Oluwatobi A. Adeleke<sup>3</sup>, Bria Graham<sup>3</sup>, Emily F. Patteson<sup>3</sup>, Jeff Gelles<sup>2</sup>*, and Stephen Buratowski<sup>1,</sup>*</p> <p> </p> <p><sup>1</sup>Department of Biological Chemistry and Molecular Pharmacology,</p> <p>Harvard Medical School, Boston, MA 02115</p> <p><sup>2</sup> Department of Biochemistry, Brandeis University, Waltham, MA 02454</p> <p><sup>3</sup> EpiCypher Inc., Durham NC 27709</p> <p> </p> <p>*Corresponding authors</p> <p>Lead author contact information:</p> <p><a href="mailto:steveb@hms.harvard.edu">steveb@hms.harvard.edu</a></p> <p> </p> <p> </p> <p>The source data for the single molecule experiments are provided as "intervals" files and "CoSMoS parameters", which can be read and manipulated using the publicly available programs "Imscroll" and "Tapqir", respectively:</p> <p><a href="https://github.com/gelles-brandeis/CoSMoS_Analysis">https://github.com/gelles-brandeis/CoSMoS_Analysis</a></p> <p><a href="https://github.com/gelles-brandeis/tapqir">https://github.com/gelles-brandeis/tapqir</a></p>
Data from: Temporal transcriptional logic of dynamic regulatory networks underlying nitrogen signaling and use in plants
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Dissecting the in vivo dynamics of transcription locking due to positive supercoiling buildup
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Data from: Tracing the dynamics of gene transcripts after organismal death
In life, genetic and epigenetic networks precisely coordinate the expression of genes—but in death, it is not known if gene expression diminishes gradually or abruptly stops or if specific genes and pathways are involved. We studied this by identifying mRNA transcripts that apparently increase in relative abundance after death, assessing their functions, and comparing their abundance profiles through postmortem time in two species, mouse and zebrafish. We found mRNA transcript profiles of 1063 genes became significantly more abundant after death of healthy adult animals in a time series spanning up to 96 h postmortem. Ordination plots revealed non-random patterns in the profiles by time. While most of these transcript levels increased within 0.5 h postmortem, some increased only at 24 and 48 h postmortem. Functional characterization of the most abundant transcripts revealed the following categories: stress, immunity, inflammation, apoptosis, transport, development, epigenetic regulation and cancer. The data suggest a step-wise shutdown occurs in organismal death that is manifested by the apparent increase of certain transcripts with various abundance maxima and durations.
Data from: Linking dynamical complexities from activation signals to transcription responses
The transcription of inducible genes involves signaling pathways that induce DNA binding of the downstream transcription factors to form functional promoter states. How the transcription dynamics is linked to the temporal variations of activation signals is far to be fully understood. In this work, we develop a mathematical model with multiple promoter states to address this question. Each promoter state has its own activation and inactivation rates, and is selected randomly with a probability that may change in time. Under the activation of constant signals, our analysis shows that if only the activation rates differ among the promoter states, then the mean transcription level $m(t)$ displays only a monotone or monophasic growth pattern. In a sharp contrast, if the inactivation rates change with the promoter states, then $m(t)$ may display multiphasic growth patterns. Upon the activation of signals that oscillate periodically, $m(t)$ also oscillates later, almost periodically in the same frequency, but the magnitude decreases in the frequency and is almost completely attenuated at large frequencies. This gives a surprising indication that multiple promoter states could filter out the signal oscillation and the noise in the random promoter state selection, as observed in the transcription of a gene activated by p53 in breast carcinoma cells. Our approach may help develop a theoretical framework to integrate coherently the genetic circuit with the promoter states to elucidate the linkage from the activation signal to the temporal profile of transcription outputs.
Data from: Dynamic antagonism between phytochromes and PIF-family bHLHs induces selective reciprocal responses to light and shade in a rapidly responsive transcriptional network in Arabidopsis
Plants respond to shade-modulated light-signals, via the phytochrome (phy) system, by adaptive changes, collectively termed the shade avoidance syndrome (SAS). To examine the roles of the Phy-Interacting bHLH Factors, PIF1, 3, 4 and 5, in relaying this information to the transcriptional network, we compared the genome-wide expression profiles of wild-type and quadruple pif (pifq) mutants in response to shade. The data identify a subset of genes, enriched in transcription-factor-encoding loci, that respond rapidly (within 1 h), in a PIF-dependent manner, to the shade signal, and that contain promoter-located G-box-sequence motifs (CACGTG), known to be preferred PIF binding sites. These genes are thus potential direct targets of phy-PIF signaling that function in the primary transcriptional circuitry controlling downstream response-elaboration. A second subset of PIF-dependent, early-response genes, lacking G-box motifs, are enriched for auxin-responsive loci, suggestive of being indirect targets of phy-PIF signaling involved in the rapid cell-expansion known to be induced by shade. A meta-analysis comparing deetiolation- and shade-responsive transcriptomes identifies a further subset of G-box-containing genes that reciprocally display rapid repression and induction in response to light and shade signals at the inception of deetiolation and shade-avoidance, respectively. Collectively, these data define a core set of transcriptional and hormonal (auxin, cytokinin) processes that appear to be dynamically poised to react rapidly to changes in the light environment via perturbations in the mutually antagonistic actions of the phys and PIFs. Data from comparative analysis of the quadruple pifq and all triple pif-mutant combinations in response to light and shade, confirm that the PIF-quartet members act with overlapping redundancy on seedling morphogenesis and transcriptional regulation, but that the individual PIFs contribute differentially to these responses.
Data from: Dynamic antagonism between phytochromes and PIF-family bHLHs induces selective reciprocal responses to light and shade in a rapidly responsive transcriptional network in Arabidopsis
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Data from: Tracing the dynamics of gene transcripts after organismal death
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Data from: Spatially coordinated dynamic gene transcription in living pituitary tissue
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Data from: Linking dynamical complexities from activation signals to transcription responses
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Transcriptional Reprogramming and Epigenomic Landscape Dynamics During Grapevine Somatic Embryogenesis Process
GEO Series GSE133761. Vitis vinifera. 24 samples. Type: Expression profiling by high throughput sequencing.
Dynamic Lineage Priming by ERK is Driven by Transcription Factor-Independent Enhancer Regulation [mRNA_TC]
GEO Series GSE132497. Mus musculus. 12 samples. Type: Expression profiling by high throughput sequencing.
Transcriptional dynamics driving MAMP-triggered immunity and pathogen effector-mediated immunosuppression in Arabidopsis leaves following infection with Pseudomonas syringae pv. tomato DC3000.
GEO Series GSE56094. Arabidopsis thaliana. 156 samples. Type: Expression profiling by array.
Dynamic regulation of histone modifications and long-range chromosomal interactions during post-mitotic transcriptional reactivation
GEO Series GSE141139. Homo sapiens. 114 samples. Type: Other; Genome binding/occupancy profiling by high throughput sequencing; Expression profiling by high throughput sequencing.
Fasting and feeding hormones differentially impact activity dynamics of transcriptionally distinct lateral hypothalamic glutamate projection neurons
GEO Series GSE169176. Mus musculus. 3 samples. Type: Expression profiling by high throughput sequencing.
Collagen Dynamics and Transcriptional Profiling in Bleomycin-induced Pulmonary Fibrosis
GEO Series GSE37635. Mus musculus. 38 samples. Type: Expression profiling by array.
Transcriptional Regulationand Chromatin Dynamics inHuman Epithelial Cell Differentiation
GEO Series GSE64328. Homo sapiens. 20 samples. Type: Expression profiling by array; Expression profiling by high throughput sequencing; Genome binding/occupancy profiling by high throughput sequencing.
Transcription factor dynamics, oscillation, and functions in human enteroendocrine cell differentiation [Cut&Run]
GEO Series GSE238272. Homo sapiens. 12 samples. Type: Other.
Dynamic regulation of chromatin accessibility by pluripotency transcription factors across the cell cycle [OCT4OFF SOX2OFF ChIP-seq]
GEO Series GSE134669. Mus musculus. 16 samples. Type: Genome binding/occupancy profiling by high throughput sequencing.
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Allen Brain Atlas
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The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
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