Browse
Submit Data
Databases
API
Help

Dataset Information

0 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

A Genome-Scale TF-DNA Interaction Network for Transcriptional Regulation of Arabidopsis Primary and Specialized Metabolism

ABSTRACT: A Genome-Scale TF-DNA Interaction Network for Transcriptional Regulation of Arabidopsis Primary and Specialized Metabolism

PROVIDER: PRJNA566089 | ENA |

REPOSITORIES: ENA

ACCESS DATA

Json Xml

Dataset's files

Source:

			Action	DRS
	SRR15122100.fastq.gz	Fastqsanger.gz
	SRR15122101.fastq.gz	Fastqsanger.gz
	SRR15122102.fastq.gz	Fastqsanger.gz
	SRR15122103.fastq.gz	Fastqsanger.gz
	SRR15122104.fastq.gz	Fastqsanger.gz

Items per page:

1 - 5 of 128

Similar Datasets

A genome-scale TF-DNA interaction network of transcriptional regulation of Arabidopsis primary and specialized metabolism.

Project description:Plant metabolism is more complex relative to individual microbes. In single-celled microbes, transcriptional regulation by single transcription factors (TFs) is sufficient to shift primary metabolism. Corresponding genome-level transcriptional regulatory maps of metabolism reveal the underlying design principles responsible for these shifts as a model in which master regulators largely coordinate specific metabolic pathways. Plant primary and specialized metabolism occur within innumerable cell types, and their reactions shift depending on internal and external cues. Given the importance of plants and their metabolites in providing humanity with food, fiber, and medicine, we set out to develop a genome-scale transcriptional regulatory map of Arabidopsis metabolic genes. A comprehensive set of protein-DNA interactions between Arabidopsis thaliana TFs and gene promoters in primary and specialized metabolic pathways were mapped. To demonstrate the utility of this resource, we identified and functionally validated regulators of the tricarboxylic acid (TCA) cycle. The resulting network suggests that plant metabolic design principles are distinct from those of microbes. Instead, metabolism appears to be transcriptionally coordinated via developmental- and stress-conditional processes that can coordinate across primary and specialized metabolism. These data represent the most comprehensive resource of interactions between TFs and metabolic genes in plants.

| S-EPMC8611409 | biostudies-literature

A Genome-Scale TF-DNA Interaction Network for Transcriptional Regulation of Arabidopsis Primary and Specialized Metabolism

Project description:We measured the transcriptional changes of dark grown seedlings in which CHA19, ENAP1, LBD16 and WRI3 translocation into the nucleus are controlled by a dexamethasone-inducible glucocorticoid receptor to investigate targets of these TFs in the TCA cycle and other sectors of primary metabolism.

2021-08-09 | GSE137623 | GEO

Desulfuromonas sp. TF strain:TF

Project description:Desulfuromonas sp. TF strain:TF Genome sequencing and assembly

| PRJNA175252 | ENA

DAP-seq was used to generate genome-wide DNA:TF interaction maps for ZmMYB73/DED1

Project description:DAP-seq was used to generate genome-wide DNA:TF interaction maps for ZmMYB73/DED1

2022-06-10 | GSE183303 | GEO

DAP-seq was used to generate genome-wide DNA:TF interaction maps for ZmMYB73/DED1

Project description:DAP-seq was used to generate genome-wide DNA:TF interaction maps for ZmMYB73/DED1

| PRJNA759900 | ENA

FloChIP TF benchmarking data

Project description:FloChIP TF benchmarking data

| PRJEB35684 | ENA

ArcZ regulation of specialized metabolites

Project description:ArcZ regulation of specialized metabolites

| PRJEB33827 | ENA

Dual threshold optimization and network inference reveal convergent evidence from TF binding locations and TF perturbation responses

Project description:Dual threshold optimization and network inference reveal convergent evidence from TF binding locations and TF perturbation responses

| PRJNA604506 | ENA

Multi-scale chromatin footprinting reveals wide-spread alterations to the structure of DNA regulatory elements [scATAC]

Project description:Cis-regulatory elements (CREs) are bound by diverse chromatin-associated proteins, cooperate to establish gene expression, and change in structure over time to alter cell fate and function1–3. Here, we develop a footprinting framework that uses deep learning to correct Tn5 sequence bias, improving accuracy and reducing false positives. This framework additionally identifies the interaction of DNA with objects of various sizes. Using these ‘multi-scale footprints’ we find that transcription factor (TF) binding occurs at well-defined distances from nucleosomes. Further, we demonstrate that multi-scale footprints, which include the positions of nucleosomes, enable more accurate inference of TF binding. Using multi-scale footprinting with single-cell multi-omics, we discover wide-spread structural and functional changes of CREs across hematopoiesis, wherein nucleosomes slide, expose DNA for TF binding, and promote gene expression. Finally, we apply this single-cell and footprint approach to characterize age-associated structural changes to CREs within hematopoietic stem cells and identify a spectrum of cells harboring age-associated changes to the epigenome. Interestingly, we find extensive changes to the structure of CREs upon aging, with many age-associated changes altering CRE structure while preserving overall accessibility. Collectively, we reveal the dynamics and functional importance of CRE structure, highlighting changes to gene regulation at single-cell and single-base-pair resolution.

2023-03-29 | GSE216406 | GEO