Browse
Submit Data
Databases
API
Help

Dataset Information

0 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

Characterizing the Key Metabolic Pathways of the Neonatal Mouse Heart Using a Quantitative Combinatorial Omics Approach

ABSTRACT: Characterizing the Key Metabolic Pathways of the Neonatal Mouse Heart Using a Quantitative Combinatorial Omics Approach

PROVIDER: PRJNA421308 | ENA |

REPOSITORIES: ENA

ACCESS DATA

Json Xml

Dataset's files

Source:

			Action	DRS
	SRR6353580_1.fastq.gz	Fastqsanger.gz
	SRR6353580_2.fastq.gz	Fastqsanger.gz
	SRR6353581_1.fastq.gz	Fastqsanger.gz
	SRR6353581_2.fastq.gz	Fastqsanger.gz
	SRR6353582_1.fastq.gz	Fastqsanger.gz

Items per page:

1 - 5 of 16

Similar Datasets

Characterizing the Key Metabolic Pathways of the Neonatal Mouse Heart Using a Quantitative Combinatorial Omics Approach.

Project description:The heart of a newborn mouse has an exceptional capacity to regenerate from myocardial injury that is lost within the first week of its life. In order to elucidate the molecular mechanisms taking place in the mouse heart during this critical period we applied an untargeted combinatory multiomics approach using large-scale mass spectrometry-based quantitative proteomics, metabolomics and mRNA sequencing on hearts from 1-day-old and 7-day-old mice. As a result, we quantified 1.937 proteins (366 differentially expressed), 612 metabolites (263 differentially regulated) and revealed 2.586 differentially expressed gene loci (2.175 annotated genes). The analyses pinpointed the fructose-induced glycolysis-pathway to be markedly active in 1-day-old neonatal mice. Integrated analysis of the data convincingly demonstrated cardiac metabolic reprogramming from glycolysis to oxidative phosphorylation in 7-days old mice, with increases of key enzymes and metabolites in fatty acid transport (acylcarnitines) and β-oxidation. An upsurge in the formation of reactive oxygen species and an increase in oxidative stress markers, e.g., lipid peroxidation, altered sphingolipid and plasmalogen metabolism were also evident in 7-days mice. In vitro maintenance of physiological fetal hypoxic conditions retained the proliferative capacity of cardiomyocytes isolated from newborn mice hearts. In summary, we provide here a holistic, multiomics view toward early postnatal changes associated with loss of a tissue regenerative capacity in the neonatal mouse heart. These results may provide insight into mechanisms of human cardiac diseases associated with tissue regenerative incapacity at the molecular level, and offer a prospect to discovery of novel therapeutic targets.

| S-EPMC5904546 | biostudies-literature

Characterizing the Key Metabolic Pathways of the Neonatal Mouse Heart Using a Quantitative Combinatorial Omics Approach

Project description:The heart of new-born mouse has exceptional capacity to regenerate from myocardial injury. However, the mouse heart loses this capacity within the first week of its life. In order to elucidate the molecular mechanisms taking place in the mouse heart during the loss of its regenerative potential, a systematic comparison of 1-day and 7-day-old mouse hearts was performed at the proteomic, metabolomic, and transcriptomic levels.

2018-12-01 | GSE107760 | GEO

Multi-omics atlas of combinatorial abiotic stress responses in wheat

Project description:Multi-omics atlas of combinatorial abiotic stress responses in wheat

| PRJNA758708 | ENA

Characterizing Neonatal Heart Maturation, Regeneration, and Scar Resolution Using Spatial Transcriptomics

Project description:Characterizing Neonatal Heart Maturation, Regeneration, and Scar Resolution Using Spatial Transcriptomics

| PRJNA780566 | ENA

Characterizing Neonatal Heart Maturation, Regeneration, and Scar Resolution Using Spatial Transcriptomics [spatial]

Project description:Characterizing Neonatal Heart Maturation, Regeneration, and Scar Resolution Using Spatial Transcriptomics [spatial]

| PRJNA780567 | ENA

Characterizing Neonatal Heart Maturation, Regeneration, and Scar Resolution Using Spatial Transcriptomics [RNA-seq]

Project description:Characterizing Neonatal Heart Maturation, Regeneration, and Scar Resolution Using Spatial Transcriptomics [RNA-seq]

| PRJNA780506 | ENA

Parallel single cell multi-omics analysis of neonatal skin reveals transitional fibroblast states that restrict differentiation into distinct fates

Project description:One of the keys to achieving skin regeneration lies within understanding the heterogeneity of neonatal fibroblasts, which support skin regeneration. However, the molecular underpinnings regulating the cellular states and fates of these cells are not fully understood. To investigate this, we performed a parallel multi-omics analysis by processing neonatal murine skin for single-cell ATAC-sequencing (scATAC-seq) and single-cell RNA-sequencing (scRNA-seq) separately. Our approach revealed that fibroblast clusters could be sorted into papillary and reticular lineages based on transcriptome profiling, as previously published. However, scATAC-seq analysis of neonatal fibroblast lineage markers, such as, Dpp4/CD26, Corin, and Dlk1 along with markers of myofibroblasts, revealed accessible chromatin in all fibroblast populations despite their lineage specific transcriptome profiles. These results suggests that accessible chromatin does not always translate to gene expression and that many fibroblast lineage markers reflect a fibroblast state, which includes neonatal papillary, reticular, and myofibroblasts. This analysis also provides a possible explanation as to why these marker genes can be promiscuously expressed in different fibroblast populations under different conditions. Our scATAC-seq analysis also revealed that the functional lineage restriction between dermal papilla and adipocytes fates are regulated by distinct chromatin landscapes. Finally, we have developed a webtool for our multi-omics analysis: https://skinregeneration.org/scatacseq-and-scrnaseq-data-from-thompson-et-al-2021-2/.

2021-11-24 | GSE189210 | GEO

Characterizing Neonatal Heart Maturation, Regeneration, and Scar Resolution Using Spatial Transcriptomics [spatial]

Project description:We use spatial transcriptomics to establish regional transcriptional profile of neonatal heart tissue obtained at indicated timpoints after apical resection surgery.

2021-12-20 | GSE188888 | GEO

Prediction of gene activity based on an integrated multi-omics approach.

Project description:An increasingly common method for predicting gene activity is genome-wide chromatin immunoprecipitation of M-bM-^@M-^XactiveM-bM-^@M-^Y chromatin modifications followed by massively parallel sequencing (ChIP-seq). Using a novel ChIP-seq quantification method (cRPKM), we tested the power of such ChIP-seq strategies to predict relative protein and RNA levels at the pre-pro-B and pro-B differentiation stages in early B cell lymphopoiesis. Using a multi-omics approach that compares promoter chromatin status (ChIP-seq; published in GSE:21978) with ongoing active transcription (GRO-seq; published in GSE:40173), steady state mRNA (RNA-seq), inferred mRNA stability, and relative proteome abundance measurements (iTRAQ), we demonstrate that active chromatin modifications at promoters are a good indicator of transcription and steady state mRNA levels. Moreover, we found that promoters with active chromatin modifications exclusively in one of these cell states frequently predicted differentially expressed proteins. However, we found that many genes whose promoters have non-differential but active chromatin modifications also displayed changes in expression of their cognate proteins. This large class of developmentally and differentially regulated proteins that was uncoupled from chromatin status used mostly post-transcriptional mechanisms. Interestingly, the most differentially expressed protein in our B-cell development system, 2410004B18Rik, was regulated by a post-transcriptional mechanism, which further analyses indicated was mediated by an identified miRNA. These data provide a striking example of how our integrated multi-omics data set can be useful in uncovering regulatory mechanisms. Total RNA from mouse pre-pro-B and pro-B cells, depleted of rRNA and small RNAs, was sequenced using a strand specific, single end sequencing strategy.

2013-11-19 | E-GEOD-52450 | biostudies-arrayexpress

A combinatorial approach to uncover a novel Integrator subunit

Project description:A combinatorial approach to uncover a novel Integrator subunit

| PRJNA842741 | ENA