GTRD: a database on gene transcription regulation—2019 update

Yevshin, Ivan S.; Sharipov, Ruslan N.; Kolmykov, Semyon; Kondrakhin, Yury V.; Kolpakov, Fedor A.

doi:10.1093/nar/gky1128

Cited by 213 publications

(236 citation statements)

References 37 publications

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“…For transcription factors, we mapped the Gene Transcription Regulatory Database v18_06 50 to ±200 nucleotides to transcriptional start sites supplied by BioMart for the human reference genome build GRCh38.p12 and the mouse reference genome build GrCm38.p6. For miRNAs we used miRDB_v5.0 51 .…”

Section: Methodsmentioning

confidence: 99%

Aging is associated with a systemic length-driven transcriptome imbalance

Stoeger¹,

Grant²,

McQuattie‐Pimentel³

et al. 2019

Preprint

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Aging manifests itself through a decline in organismal homeostasis and a multitude of 26 cellular and physiological functions 1 . Efforts to identify a common basis for vertebrate aging 27 face many challenges; for example, while there have been documented changes in the 28 expression of many hundreds of mRNAs, the results across tissues and species have been 29 inconsistent 2 . We therefore analyzed age-resolved transcriptomic data from 17 mouse organs 30 and 51 human organs using unsupervised machine learning 3-5 to identify the architectural and 31 regulatory characteristics most informative on the differential expression of genes with age. We 32 report a hitherto unknown phenomenon, a systemic age-dependent length-driven 33 transcriptome imbalance that for older organisms disrupts the homeostatic balance between 34 short and long transcript molecules for mice, rats, killifishes, and humans. We also demonstrate 35 that in a mouse model of healthy aging, length-driven transcriptome imbalance correlates with 36 changes in expression of splicing factor proline and glutamine rich (Sfpq), which regulates 37 transcriptional elongation according to gene length 6 . Furthermore, we demonstrate that 38 length-driven transcriptome imbalance can be triggered by environmental hazards and 39 pathogens. Our findings reinforce the picture of aging as a systemic homeostasis breakdown 40 and suggest a promising explanation for why diverse insults affect multiple age-dependent 41 phenotypes in a similar manner. 42 43Main text: 44 45The transcriptome responds rapidly, selectively, strongly, and reproducibly to a wide variety of 46 molecular and physiological insults experienced by an organism 7 . While the transcripts of 47

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Section: Methodsmentioning

confidence: 99%

Aging is associated with a systemic length-driven transcriptome imbalance

Stoeger¹,

Grant²,

McQuattie‐Pimentel³

et al. 2019

Preprint

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“…RelA binding sites were identified at these regions by both MEME motif analysis and the intersection with IL-1-induced RelA ChIP-seq peaks ( Figure 3A) [21]. Further, interrogation of published ChIP-seq data at the Gene Transcription Regulation Database also indicated the presence of RelA binding sites (Supplementary Figure 5) [26]. We also used JEME (joint effect of multiple enhancers), which predicts enhancer-target gene interactions by leveraging enhancer features and gene expression levels from consortia datasets, to determine the target genes of all our accessible peaks [27].…”

Section: Newly Accessible Regions Following Il-1 Stimulation Can Actmentioning

confidence: 87%

Dynamic chromatin accessibility landscape changes following interleukin-1 stimulation

Barter

Cheung

Falk

et al. 2020

Preprint

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Genome-wide methods for examining chromatin modification provide detailed information on regulatory regions of the genome. Dynamic modifications of chromatin allow rapid access of the gene regulatory machinery to condensed genomic regions facilitating subsequent gene expression. Inflammatory cytokine stimulation of cells can cause rapid gene expression changes through direct signalling pathway-mediated transcription factor activation and regulatory element binding.Here we used the Assay for Transposase Accessible Chromatin with high-throughput sequencing (ATAC-seq) to assess regions of the genome that are differentially accessible following treatment of cells with interleukin-1 (IL-1). We identified 126,483 open chromatin regions, with 241 regions significantly differentially accessible following stimulation, with 64 and 177 more or less accessible, respectively. These differentially accessible regions predominantly correspond to regions of the genome marked as enhancers. Motif searching identified an overrepresentation of a number of transcription factors, most notably RelA in the regions becoming more accessible, with analysis of ChIP-seq data confirmed RelA binding to these regions. A significant correlation in differential chromatin accessibility and gene expression was also observed.Functionality in regulating gene expression was confirmed using CRISPR/Cas9 genome-editing to delete regions for that became more accessible following stimulation in the genes MMP13, IKBKE and C1QTNF1. These same regions were also accessible for activation using a dCas9-transcriptional activator and showed enhancer activity in a cellular model.Together, these data describe and functionally validate a number of dynamically accessible chromatin regions involved in inflammatory signalling.

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“…Для идентификации сайтов связывания транскрипционных факторов CREB, FOS и JUN семейств в промоторных областях генов NR4A2, NR4A3 и PPARGC1A, мы провели биоинформатический анализ баз данных позиционных весовых матриц TRANSFAC [51] и результатов ChIP-seq исследований, представленных в GTRD [52] Экспериментально идентифицированные случаи образования гетеродимерных комплексов между транскрипционными факторами этих семейств [49,50] и выявленные нами пересечения в их сайтах связывания в промоторных областях генов NR4A2, NR4A3 и PPARGC1A позволяют предположить наличие дополнительного кооперативного механизма регуляции транскрипционной активности целевых генов для этих факторов. Более того, поскольку после окончания физической нагрузки уровень фосфорилирования многих сигнальных киназ очень быстро падает до базального уровня, то, как следует из схемы сигнального пути (рис.…”

Section: рисunclassified

A Mathematical Model Linking Ca2+-Dependent Signaling Pathway and Gene Expression Regulation in Human Skeletal Muscle

Akberdin¹,

Vertyshev²,

Pintus³

et al. 2020

Math.Biol.Bioinf.

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The physiological adaptation to aerobic endurance exercises is provided by activation of signaling pathways in skeletal muscle cells. Training-induced activation of specific signaling pathways results in significant transcriptional responses. Despite the ongoing endeavours to experimentally investigate regulatory mechanisms and signal transduction pathways involved in the contraction-induced adaptation, quantitative contribution of certain signal molecules in expression regulation of genes responsible for intracellular response has not been studied МОДЕЛЬ Ca 2+ -ЗАВИСИМОГО СИГНАЛЬНОГО ПУТИ И РЕГУЛЯЦИИ ГЕНОВ В КЛЕТКАХ СКЕЛЕТНОЙ МЫШЦЫ ЧЕЛОВЕКА comprehensively yet. The paper presents novel developed model linking Ca 2+dependent signaling pathway and downstream transcription regulation of early and late response genes in human skeletal muscle during exercise. Numerical analysis of the model enabled to reveal crucial steps in this signal transduction pathway for the adaptation and demonstrated the necessity of consideration of additional transcription factors regulating transcription of late response genes in order to adequately reproduce gene expression data that were taken in human vastus lateralis muscle during and after acute cycling exercise.

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GTRD: a database on gene transcription regulation—2019 update

Cited by 213 publications

References 37 publications

Aging is associated with a systemic length-driven transcriptome imbalance

Aging is associated with a systemic length-driven transcriptome imbalance

Dynamic chromatin accessibility landscape changes following interleukin-1 stimulation

A Mathematical Model Linking Ca2+-Dependent Signaling Pathway and Gene Expression Regulation in Human Skeletal Muscle

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