Browse
Submit Data
Databases
API
Help

Dataset Information

0 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

Aggregated gene co-expression networks for predicting transcription factor regulatory landscapes in a non-model plant species

ABSTRACT: Aggregated gene co-expression networks for predicting transcription factor regulatory landscapes in a non-model plant species

PROVIDER: PRJNA957804 | ENA |

REPOSITORIES: ENA

ACCESS DATA

Json Xml

Dataset's files

Source:

			Action	DRS
	SRR24229766.fastq.gz	Fastqsanger.gz
	SRR24229767.fastq.gz	Fastqsanger.gz
	SRR24229768.fastq.gz	Fastqsanger.gz
	SRR24229769.fastq.gz	Fastqsanger.gz

Items per page:

1 - 4 of 4

Similar Datasets

Aggregated gene co-expression networks for predicting transcription factor regulatory landscapes in a non-model plant species

Project description:Gene co-expression networks (GCNs) have not been extensively studied in non-model plants. However, the rapid accumulation of transcriptome datasets in these species represents an opportunity to explore underutilized network aggregation approaches that highlight robust co-expression interactions and improve functional connectivity. We applied and evaluated two different aggregation methods on public grapevine RNA-Seq datasets belonging to three different tissue conditions (leaf, berry and ‘all organs’). Our results show that co-occurrence-based aggregation generally yielded the best-performing networks. We applied GCNs to study several TF gene families, showing its capacity of detecting both already-described and novel regulatory relationships between R2R3-MYBs, bHLH/MYC and multiple secondary metabolism pathway reactions. Specifically, using TF gene- and pathway-centered network analyses, we ascertained the previously demonstrated role of VviMYBPA1 in controlling the accumulation of proanthocyanidins while providing novel insights into its role as a potential regulator of p-coumaroyl-CoA biosynthesis as well as the shikimate and aromatic amino-acid pathways. This network was validated using DNA Affinity Purification Sequencing data, demonstrating that co-expression networks of activational transcription factors can serve as a proxy of gene regulatory networks. This study presents an open repository to reproduce networks and a GCN application within the Vitviz platform, a user-friendly tool for exploring co-expression relationships.

2023-04-28 | GSE230186 | GEO

Phylogenetic rewiring in mutualistic networks increases community stability in fragmented landscapes

Project description:Phylogenetic rewiring in mutualistic networks increases community stability in fragmented landscapes Targeted loci

| PRJNA516318 | ENA

Predicting the Prevalence of Complex Genetic Diseases from Individual Genotype Profiles Using Capsule Networks

Project description:Predicting the Prevalence of Complex Genetic Diseases from Individual Genotype Profiles Using Capsule Networks

| PRJNA909910 | ENA

Predicting the Prevalence of Complex Genetic Diseases from Individual Genotype Profiles Using Capsule Networks

Project description:Predicting the Prevalence of Complex Genetic Diseases from Individual Genotype Profiles Using Capsule Networks

| PRJNA909909 | ENA

Chromatin accessibility landscapes revealed the subgenome-divergent regulation networks during wheat grain development.

Project description:Chromatin accessibility landscapes revealed the subgenome-divergent regulation networks during wheat grain development.

| PRJNA886975 | ENA

DeepC: Predicting chromatin interactions using megabase scaled deep neural networks and transfer learning (Tiled-C)

Project description:DeepC: Predicting chromatin interactions using megabase scaled deep neural networks and transfer learning (Tiled-C)

| PRJNA565433 | ENA

DeepC: Predicting chromatin interactions using megabase scaled deep neural networks and transfer learning (NG Capture-C)

Project description:DeepC: Predicting chromatin interactions using megabase scaled deep neural networks and transfer learning (NG Capture-C)

| PRJNA565432 | ENA

Transcriptome and proteome derived networks reveal distinct and complementary gene relationships

Project description:Co-expression networks and gene regulatory networks (GRNs) are emerging as important tools for predicting the functional roles of individual genes at a system-wide scale. To enable network reconstructions we built a large-scale gene expression atlas comprised of 62,547 mRNAs, 17,862 non-modified proteins, and 6,227 phosphoproteins harboring 31,595 phosphorylation sites quantified across maize development. There was little edge conservation in co-expression and GRNs reconstructed using transcriptome versus proteome data yet networks from either data type were enriched in ontological categories and effective in predicting known regulatory relationships. This integrated gene expression atlas provides a valuable community resource. The networks should facilitate plant biology research and they provide a conceptual framework for future systems biology studies highlighting the importance of studying gene regulation at several levels.

| MSV000079290 | MassIVE

Chromatin accessibility landscapes revealed the subgenome-divergent regulation networks during wheat grain development [ATAC-seq]

Project description:Chromatin accessibility landscapes revealed the subgenome-divergent regulation networks during wheat grain development [ATAC-seq]

| PRJNA886977 | ENA

Chromatin accessibility landscapes revealed the subgenome-divergent regulation networks during wheat grain development [RNA-seq]

Project description:Chromatin accessibility landscapes revealed the subgenome-divergent regulation networks during wheat grain development [RNA-seq]

| PRJNA886978 | ENA

OmicsDI is part of the ELIXIR infrastructure

OmicsDI is an Elixir interoperability service. Learn more ›

Tweets

OmicsDI Databases

PRIDE
PeptideAtlas
MassIVE
JPOST Repository
Physiome Model Repository

EGA
EVA
ENA
LINCS
PAXDB
Cell Collective

MetaboLights
Metabolomics Workbench
MetabolomeExpress
GNPS
BioModels
FAIRDOMHub

ArrayExpress
dbGaP
ExpressionAtlas
GEO
NODE

Information

Databases
Help
API
Contact us
Code on GitHub
Terms of use
Submit Data