Browse
Submit Data
Databases
API
Help

Dataset Information

0 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

Illumina NGS RNA-seq and RRBS Sequencing on Spaceflight Mouse Retina

ABSTRACT: We reported the retinal transcriptome and methylome profiles of spaceflight and habitat control mice. The retinal transcrtiome was generated including 764 million paired-end 75x2 bp RNA-seq data. The methylome was generated including 788 million 75-bp RRBS DNA methylation data. We identified 177 differentially expressed genes (DEGs) induced by spaceflight based on the RNA-seq dataset, and 643 differentially methylated genes (DMGs) based on RRBS dataset. Functional enrichement analysis based on DEGs and DMGs revealed that spaceflight altered extracellular matrix component (EMC), cell to cell junction, inflammation pathway, wound-healing process, etc. Integration analysis based on transcriptome and methylome suggested that modifications on DNA methylation were correlated with transcriptome changes for several significant biological processes and/or pathways.

ORGANISM(S): Mus musculus

PROVIDER: GSE159771 | GEO | 2021/06/30

REPOSITORIES: GEO

ACCESS DATA

Json Xml

Dataset's files

Source:

			Action	DRS
		Other

Items per page:

1 - 1 of 1

Similar Datasets

Illumina NGS RNA-seq and RRBS Sequencing on Rat Kidney

Project description:We reported the kidney transcriptome and methylome profiles of rat Brown Norway (BN) and Sprague Dawley (CD) strains at late pregnancy (day 18/21) compared to non-pregnancy. The renal transcriptome was characterized from 326 million single-end 100bp RNA-seq data. The methylome dataset included 234 million 75-bp RRBS DNA methylation reads. We identified 297 differentially expressed genes (DEGs) induced by pregnancy in CD rats and 174 DEGs induced in BN rats, based on the RNA-seq dataset. 237 of the 297 DEGs in CD pregnant rats and 114 of the 174 DEGs in BN pregnant rats are strain specific, indicating differential adaptation to pregnancy. Methylome data reveals that strain differences is the major factor in determining methylation differences. We also found that pregant BN showed higher methylation than non-pregnant BN at transcription starter site (TSS) and promoter regions. Functional analysis based on DEGs and DMGs revealed that pregnant BN rats showed renal transcriptomic changes that induce vitamin D deficiency and renal pro-inflammatory gene expression that can partly explain pregnancy-specific proteinuria. Integrated analysis based on transcriptome and methylome suggested that modifications on DNA methylation were correlated with transcriptome changes for several significant biological processes and/or pathways.

2022-06-22 | GSE173380 | GEO

Genome-wide profiling of DNA methylation at single-base resolution based on MeDIP-bisulfite high-throughput sequencing and ridge regression (MethyC + MeDIP)

Project description:Unraveling complexity of DNA methylome is essential to decipher DNA methylation mechanism in life. However, this has been subjected to technological constraints to balance between cost and accurate measurement of the DNA methylation level. In this study, by innovatively introducing C-hydroxylmethylated adapters, we have developed MeDIP-Bisulfite sequencing (MB-seq), which could obtain DNA methylome of repertoire CpGs at single-base resolution. We found MB-seq only costs 10% of MethylC-seq, but covers 85% of total CpGs in human genome. Unlike absolute methylation levels determined by MethylC-seq and RRBS, MB-seq presented relative methylation levels that are linearly inflated. This has enlightened us to develop a MB-seq corresponding correction method for methylation level based on ridge regression, which integrates the data of MB-seq and RRBS to predict the methylation level of total 28.2 million CpGs on human genome with high accuracy (Pearson correlation coefficient, PCC=0.90). Moreover, by employing MB-seq, we generated the DNA methylome of an ovarian epithelial cell line (T29) and its oncogenic counterpart (T29H), respectively. After ridge regression, we identified 131,790 differential methylation regions (DMRs) with high accuracy between T29 and T29H, far more than 7,567 obtained from RRBS. Taken together, our result demonstrated that the MB-seq combined with ridge regression is a wide applicable approach for profiling of DNA methylome.

2015-10-01 | GSE62277 | GEO

Genome-wide profiling of DNA methylation at single-base resolution based on MeDIP-bisulfite high-throughput sequencing and ridge regression (RNA)

2015-10-01 | GSE62276 | GEO

Genome-wide profiling of DNA methylation at single-base resolution based on MeDIP-bisulfite high-throughput sequencing and ridge regression (MB)

2015-10-01 | GSE62279 | GEO

Single cell methylome landscapes of mouse embryonic stem cells and early embryos analyzed by reduced representation bisulfite sequencing

Project description:We develop a single cell methylome analysis technique based on RRBS, which works robustly for mouse embryonic stem cells (mESCs), sperm, metaphase II oocytes, and zygotes.

2013-08-31 | GSE47343 | GEO

Genome-Wide Profiling of DNA Methylation and Gene Expression Identifies Candidate Genes for Human Diabetic Neuropathy (RRBS)

Project description:We perfomed transcriptomic and methylomic analysis of sural nerve biopsies from type 2 diabetic patients with neuropathy. Sural nerve transcriptomic and methylomic profiles were integrated and subsequent biological meaning investigated using KEGG pathway analysis of overlapping differentially expressed genes (DEGs) and differentially methylated genes (DMGs). A gene interation network was also generated including DEGs and DMGs, and common biological pathways were identified.

2020-08-24 | GSE148060 | GEO

Genome-Wide Profiling of DNA Methylation and Gene Expression Identifies Candidate Genes for Human Diabetic Neuropathy (RNA-Seq)

2020-08-24 | GSE148059 | GEO

Spaceflight causes changes in gene expression, photoreceptor integrity, and oxidative stress-related damage in the murine retina

Project description:Purpose:The purpose of this study was to determine whether the spaceflight environment induces oxidative damage on ocular structure and how gene expression profiles change during spaceflight. Methods: RNA sequencing, immunofluorescence, and microCT assays were performed on two groups of mice to assess the effects of spaceflight on the mammalian retina. Ten week old adult C57BL/6 mice was flown aboard the ISS for 35 days and returned to Earth alive. Ground control mice were maintained on Earth in identical flight hardware. Within 38 (+/-4) hours of splashdown, mice were euthanized and ocular tissues were collected for analysis. Results:RNA sequencing detected 600 differentially expressed genes in spaceflight retina. This set of differentially expressed genes is enriched for genes related to visual perception, the phototransduction pathway, and numerous retina and photoreceptor phenotype categories. Eleven of the differentially expressed genes are associated with the disease retinitis pigmentosa, a retinal disease characterized by dystrophy of the rods and cones of the photoreceptor layer. Analysis of differentially expressed transcription factors indicate changes in chromatin structure, offering clues to the causes of the phenotypic changes observed. Additionally, immunofluorescence assays showed degradation of cone photoreceptors and increased oxidative stress in the retina. Retinal thickness, as well as thickness of the retinal pigment epithelium and choroid layers, were significantly reduced after spaceflight. Conclusions: These results indicate that retinal performance may decrease over extended periods of spaceflight and cause visual impairment.

2019-05-31 | GSE131954 | GEO

Genome-wide transcriptional changes of ramie (Boehmeria nivea LM-oM-<M-^NGaud) in response to the infection of root-lesion nematode

Project description:The Root-lesion nematode (RLN) Pratylenchus coffeae is a major ramie pest causing severe fiber yield loss annual in China. The response mechanism of ramie to RLN-infection is poorly understood. Two RLN-infected plants (Inf1 and Inf2) and two control plants (CO1 and CO2) were individually used to sequence by Illumina pair-end sequencing. About 56.3, 51.7, 43.4 and 45.0 million sequencing reads were generated from the libraries of CO1, CO2, Inf1 and Inf2, respectively. De novo assembly for these 196 million reads yielded 50,486 unigenes with an average length of 853.3 bp. Based on sequence similarity search with known proteins, a total of 24,820 (49.2%) genes were annotated for their function. Comparison of gene expression level between CO and Inf ramie based on the normalized value of read counts per kilobase of exon model per million reads (RPKM) revealed that there were 777 differentially expressed genes (DEGs). Further, these functional category of DEGs were classified by assigning them to gene ontology (GO) and clusters of orthologous group (COG). Pathway enrichment analysis showed that three pathways (Phenylalanine metabolism, Carotenoid biosynthesis and Phenylpropanoid biosynthesis) were severely influenced by RLN-infection. The genome-wide expression profiling of ramie responding to RLN-infection was first characterized. A series of candidate genes and pathways that may contribute to defense response against RLN in ramie will be helpful for further improving the resistance to RLN-infection. A total of four samples, two replicates of control plant (CO1 and CO2) and two replicates of RLN-infected plants (Inf1 and Inf2) were used for RNA-seq.

2014-04-28 | E-GEOD-51900 | biostudies-arrayexpress

Identification of potential abnormal methylation modified genes in coronary artery ectasia

Project description:Coronary artery ectasia (CAE) is a rare but easily recognized abnormality of coronary artery anatomy and morphology. Up to now, the pathogenesis of CAE remains unclear. Firstly, the peripheral venous blood samples of patients with CAE were obtained for the RNA sequencing to identify differentially expressed genes (DEGs), followed by functional analysis. Secondly, DNA methylation profile in CAE was downloaded from the dataset of GSE87016 to identify differentially methylated genes (DMGs). Lastly, after taking interaction genes between DEGs and DMGs, abnormal methylation modified genes were identified.

2023-09-06 | GSE222041 | GEO

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