Ontology highlight
ABSTRACT:
PROVIDER: PRJNA1014212 | ENA |
REPOSITORIES: ENA
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| SRR25949700_1.fastq.gz | Fastqsanger.gz | |||
| SRR25949700_2.fastq.gz | Fastqsanger.gz | |||
| SRR25949800_1.fastq.gz | Fastqsanger.gz | |||
| SRR25949800_2.fastq.gz | Fastqsanger.gz | |||
| SRR25949701_1.fastq.gz | Fastqsanger.gz |
Items per page: 5 1 - 5 of 292 |
Similar Datasets
Project description:The first GSSM of V. vinifera was reconstructed (MODEL2408120001). Tissue-specific models for stem, leaf, and berry of the Cabernet Sauvignon cultivar were generated from the original model, through the integration of RNA-Seq data. These models have been merged into diel multi-tissue models to study the interactions between tissues at light and dark phases.
2024-09-02 | MODEL2408160001 | BioModels
Project description:Multi-tissue RNA-seq data across three species
| PRJNA309284 | ENA
Project description:Variability of regenerative potential among animals has long perplexed biologists. Based on their amazing regenerative abilities, planarians have become important models for understanding the molecular basis of regeneration; however, planarian species with limited regenerative abilities are also found. Despite the importance of understanding the differences between closely related, regenerating and non-regenerating organisms, few studies have focused on the evolutionary loss of regeneration, and the molecular mechanisms leading to such regenerative loss remain obscure. Here we examine Procotyla fluviatilis, a planarian with restricted ability to replace missing tissues, utilizing next-generation sequencing to define the gene expression programs active in regeneration-permissive and regeneration-deficient tissues. We found that Wnt signaling is aberrantly activated in regeneration-deficient tissues. Remarkably, down-regulation of canonical Wnt signaling in regeneration-deficient regions restores regenerative abilities: blastemas form and new heads regenerate in tissues that normally never regenerate. This work reveals that manipulating a single signaling pathway can reverse the evolutionary loss of regenerative potential. RNA-seq experiments to identify gene expression changes following amputation in body regions with variable regenerative potential. Adult Procotyla fluviatilis were amputated at sites either anterior or posterior to the pharynx. After 24 hours post-amputation, tissues near the amputation site were excised and RNA was extracted. Similar tissues were excised from uncut control animals. Samples were processed for RNA-seq using Illumina procedures. We generated a de novo P. fluviatilis transcriptome and used RNA sequencing (RNA-seq) to characterize transcripts from excised tissue fragments in Reg+ and Reg- body regions 24 hours post-amputation. We performed parallel analyses on tissues excised from intact animals at identical body regions to account for regional differences in transcripts, thereby identifying changes resulting from amputation. Samples A1-A3 = Regeneration-proficient (Reg+) tissue excision 24 hours after amputation. Samples B1-B3 = Tissue excision from regeneration-proficient (Reg+) region but not amputated. Samples C1-C3 = Tissue excision from regeneration-deficient (Reg-) tissues 24 hours after amputation. Samples D1, D3-D4 = Tissue excision from regeneration-deficient (Reg-) region that was not amputated.
2013-07-04 | E-GEOD-48497 | biostudies-arrayexpress
Project description:Background: The multiome is an integrated assembly of distinct classes of molecules and molecular properties, or “omes,” measured in the same biospecimen. Freezing and formalin-fixed paraffin-embedding (FFPE) are two common ways to store tissues, and these practices have generated vast biospecimen repositories. However, these biospecimens have been underutilized for multi-omic analysis due to the low throughput of current analytical technologies that impede large-scale studies. Methods: Tissue sampling, preparation, and downstream analysis were integrated into a 96-well format multi-omics workflow, MultiomicsTracks96. Frozen mouse organs were sampled using the CryoGrid system, and matched FFPE samples were processed using a microtome. The 96-well format sonicator, PIXUL, was adapted to extract DNA, RNA, chromatin, and protein from tissues. The 96-well format analytical platform, Matrix, was used for chromatin immunoprecipitation (ChIP), methylated DNA immunoprecipitation (MeDIP), methylated RNA immunoprecipitation (MeRIP), and RNA reverse transcription (RT) assays followed by qPCR and sequencing. LCMS/ MS was used for protein analysis. The Segway genome segmentation algorithm was used to identify functional genomic regions, and linear regressors based on the multi-omics data were trained to predict protein expression. Results: MultiomicsTracks96 was used to generate 8-dimensional datasets including RNA-seq measurements of mRNA expression; MeRIP-seq measurements of m6A and m5C; ChIP-seq measurements of H3K27Ac, H3K4m3, and Pol II; MeDIP-seq measurements of 5mC; and LCMS/ MS measurements of proteins. We observed high correlation between data from matched frozen and FFPE organs. The Segway genome segmentation algorithm applied to epigenomic profiles (ChIP-seq: H3K27Ac, H3K4m3, Pol II; MeDIP-seq: 5mC) was able to recapitulate and predict organ-specific super-enhancers in both FFPE and frozen samples. Linear regression analysis showed that proteomic expression profiles can be more accurately predicted by the full suite of multi-omics data, compared to using epigenomic, transcriptomic, or epitranscriptomic measurements individually. Conclusions: The MultiomicsTracks96 workflow is well suited for high dimensional multi-omics studies – for instance, multiorgan animal models of disease, drug toxicities, environmental exposure, and aging as well as large-scale clinical investigations involving the use of biospecimens from existing tissue repositories.
2025-02-14 | PXD041462 | Pride
Project description:This model was reconstructed from single-nucleus RNA-seq (snRNA-seq) data of human postmortem brain and curated using published metabolomics data from human iPSC-derived neurons and cerebrospinal fluid (CSF), together with gene expression data from the Human Protein Atlas. It more accurately simulates human neuronal metabolic flux in neurodegenerative conditions such as Alzheimer's disease (AD).
2026-06-27 | MODEL2606170001 | BioModels
Project description:<p>Gene expression is a biological process regulated at different molecular levels, including chromatin accessibility, transcription, and RNA maturation and transport. In addition, these regulatory mechanisms have strong links with cellular metabolism. Here we present a multi-omics dataset that captures different aspects of this multi-layered process in yeast. We obtained RNA-seq, metabolomics, and H4K12Ac ChIP-seq data for wild-type and mip6delta strains during a heat-shock time course. Mip6 is an RNA-binding protein that contributes to RNA export during environmental stress and is informative of the contribution of post-transcriptional regulation to control cellular adaptations to environmental changes. The experiment was performed in quadruplicate, and the different omics measurements were obtained from the same biological samples, which facilitates the integration and analysis of data using covariance-based methods. We validate our dataset by showing that ChIP-seq, RNA-seq and metabolomics signals recapitulate existing knowledge about the response of ribosomal genes and the contribution of trehalose metabolism to heat stress.</p>
2020-02-14 | MTBLS1320 | MetaboLights
Project description:Genotype?Tissue Expression atlas of cattle using 7,180 publicly available RNA-sequencing (RNA-seq) samples
2023-02-10 | PRJEB59574 | EVA