Browse
Submit Data
Databases
API
Help

Dataset Information

0 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

Integrating ATAC-seq and RNA-seq reveals tissue-specific genes and repressed networks in the placenta

ABSTRACT: Integrating ATAC-seq and RNA-seq reveals tissue-specific genes and repressed networks in the placenta

PROVIDER: PRJNA493666 | ENA |

REPOSITORIES: ENA

ACCESS DATA

Json Xml

Dataset's files

Source:

			Action	DRS
	SRR7912013_1.fastq.gz	Fastqsanger.gz
	SRR7912013_2.fastq.gz	Fastqsanger.gz
	SRR7912014_1.fastq.gz	Fastqsanger.gz
	SRR7912014_2.fastq.gz	Fastqsanger.gz
	SRR7912015_1.fastq.gz	Fastqsanger.gz

Items per page:

1 - 5 of 6

Similar Datasets

Integrating ATAC-seq and RNA-seq reveals tissue-specific genes and repressed networks in the placenta

Project description:We performed ATAC-seq on placenta dissected from e9.5 timed-pregnant mice in order to generate genome-wide chromatin accessibility maps. Integrating this data with previously published RNA-seq data showed that: 1) genes that have high expression and high ATAC-seq read coverage at the transcription start site (TSS) were enriched for house-keeping functions; 2) genes that have high expression and medium-low coverage at the TSS were enriched for placenta-specific genes and functions; 3) genes that have low expression and high TSS coverage are actively repressed. From the actively repressed genes, we extracted a protein-protein interaction network enriched for neuronal functions. These data increase our understanding of active and repressed gene networks in the e9.5 placenta. The analysis also provides a method for identifying repressed networks and tissue-specific genes by integrating ATAC-seq and RNA-seq data. Please note that the RNA-Seq data are already deposited and available under GSE65808.

2019-02-28 | GSE120599 | GEO

Integrating Large-Scale Functional Genomic Data to Dissect the Complexity of Yeast Regulatory Networks

Project description:A major goal of biology is the construction of networks that predict complex system behavior. We combine multiple types of molecular data, including genotypic, expression, transcription factor binding site (TFBS), and protein-protein interaction (PPI) data previously generated from a number of yeast experiments in order to reconstruct causal gene networks. Networks based on different types of data are compared using metrics devised to assess the predictive power of a network. A network reconstructed by integrating genotypic, TFBS and PPI data is shown to be the most predictive. This network is used to predict causal regulators responsible for hot spots of gene expression activity in a segregating yeast population. The network is also shown to elucidate the mechanisms by which causal regulators give rise to larger-scale changes in gene expression activity. Predictions are prospectively validated to provide direct experimental evidence that predictive networks can be constructed by integrating multiple, appropriate data types. Keywords: allele replacement Allele replacement strains were created in two backgrounds: BY (BY4724 and BY4742), and RM11-1a, and compared to the parental type (BY4716 and RM11-1a). BY7g, BY9g, BY11g are BY4716, while RM7g, RM9g, and RM11g are RM11-1a. YAD350 is a MKT1 D30G replacement strain in BY4742 background. YLK804 is a SAL1-RM allele in BY4724 and YLK806 is a SAL1-BY allele in RM11-1a. All strains were grown in YNB + 2% glucose, with leucine, lysine, and uracil. YAD350 was also grown with histidine.

2008-06-15 | E-GEOD-11111 | biostudies-arrayexpress

Integrating Large-Scale Functional Genomic Data to Dissect the Complexity of Yeast Regulatory Networks

2008-06-15 | GSE11111 | GEO

ChIP-Seq for human placenta

Project description:ChIP-Seq for human placenta

| PRJNA659727 | ENA

Mouse Klf14matKO Placenta mRNA-seq

Project description:Mouse Klf14matKO Placenta mRNA-seq

| PRJNA573881 | ENA

Identification of altered miRNAs and their targets in Placenta Accreta

Project description:We aim to elucidate regulatory miRNA and target networks contributing to Placenta accreta spectrum development using smallRNA-Seq.

2022-11-01 | GSE216742 | GEO

RNA-Seq for Rhesus monkey placenta

Project description:RNA-Seq for Rhesus monkey placenta

| PRJNA641402 | ENA

ChIP-Seq for Rhesus monkey placenta

Project description:ChIP-Seq for Rhesus monkey placenta

| PRJNA641404 | ENA

Transcriptomic analyses identifies novel regulators of placental development

Project description:The placenta is a transient organ that is repsonsible for multiple processes during pregnancy. Here we aim to study the development of the placenta using mouse models at embryonic day (e) e7.5, e8.5 and e9.5 by integrating RNA-seq data at the three timepoints to identify important genes, inferring their interaction networks, and predict novel regulators of placental development.

2022-11-21 | GSE202243 | GEO

Examination of gene expression in human placenta using RNA-seq

Project description:As genome-scale DNA methylation sequencing technologies have improved it has become apparent that tissue-specific methylation can occur not only at promoters, enhancers, and CpG islands but also over larger genomic regions. In most human tissues, the vast majority of the genome is highly methylated (>70%). However, genomic sequencing of bisulfite-treated DNA (MethylC-seq) has revealed large partially methylated domains (PMDs) in some human cell lines. However, to date only cultured cells and some cancers have shown evidence for PMDs, suggesting that PMDs may not be observed in normal human tissues. Here we performed MethylC-seq in a set of human tissues and found that full-term human placenta shows clear evidence of PMDs. Examination of gene expression in human placenta using RNA-seq, with one biological replicate (taken from same placenta)

2013-03-28 | E-GEOD-39776 | biostudies-arrayexpress

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