Ontology highlight
ABSTRACT:
PROVIDER: PRJNA625169 | ENA |
REPOSITORIES: ENA
Similar Datasets
Project description:Lifespan varies both within and across species, but the general principles of its control are not understood. To identify transcriptomic signatures of mammalian longevity, we sequenced multiple organs of young adult mammals corresponding to 8 different species, including Canadian beaver, long-tailed macaque, greater tube-nosed bat, baboon, white-footed mouse, sugar glider, Siberian chipmunk and American black bear. We aggregated this dataset with publicly available pan-mammalian data and performed multi-tissue gene expression analyses across 41 mammalian species. This allowed us to identifiy signatures of species longevity and assess their relationship with biomarkers of aging and lifespan-extending interventions. This dataset complements RNAseq profiles of tissues from 23 mammalian species stored at GSE43013.
2023-06-01 | GSE227359 | GEO
Project description:The function of a gene is closely connected to its expression specificity across tissues and cell types. RNA-Seq is a powerful quantitative tool to explore genome wide expression. The aim of the present study is to provide a comprehensive RNA-Seq dataset across the same 13 tissues for mouse and rat, two of the most relevant species for biomedical research. The dataset provides the transcriptome across tissues from three male C57BL6 mice and three male Han Wistar rats. We also describe our bioinformatics pipeline to process and technically validate the data. Principal component analysis shows that tissue samples from both species cluster similarly. By comparative genomics we show that many genes with high sequence identity with respect to their human orthologues have also a highly correlated tissue distribution profile and are in agreement with manually curated literature data for human. These results make us confident that the present study provides a unique resource for comparative genomics and will facilitate the analysis of tissue specificity and cross-species conservation in higher organisms.
2017-10-25 | E-MTAB-6081 | biostudies-arrayexpress
Project description:As part of the EcoToxChip project, 49 distinct exposure studies were conducted on three lab model species (Japanese quail, fathead minnow, African clawed frog) and three ecologically relevant species (double crested cormorant, rainbow trout, northern leopard frog), at multiple life stages (embryo, adult), exposed to eight chemicals of environmental concern (ethinyl estradiol-EE2, hexabromocyclododecane-HBCD, lead-Pb, selenomethionine-SeMe, 17β trenbolone-TB, chlorpyrifos-CPF, fluoxetine-FLX, and benzo [a] pyrene-BaP. Whole transcriptome analyses were conducted on these samples resulting in a rich RNA seq dataset covering various species, life stages and chemicals, which is one of the largest purposeful complications of RNA seq data within ecotoxicology. Recently, a unified bioinformatics platform of relevance to ecotoxicology, EcoOmicsAnalyst and ExpressAnalyst, was developed to facilitate RNA Seq analysis of non-model species lacking a reference transcriptome. The platform uses the Seq2Fun algorithm to map RNA-seq reads from eukaryotic species to an ortholog database comprised of protein sequences from >600 eukaryotic species (EcoOmicsDB) with a translated search. The availability of these tools presents a unique opportunity to examine the EcoToxChip RNA Seq dataset for cross species comparisons. This work shows the potential of the EcoOmicsAnalyst and Seq2Fun platform to facilitate fast and simple analysis of RNA Seq datasets from non-model organisms with unannotated genomes and conduct comparative transcriptomic analysis across various species and life stages for cross-species extrapolation.
2023-12-05 | GSE239776 | GEO
Project description:The role of non-coding RNAs in different biological processes and diseases is continuously expanding. Next-generation sequencing together with the parallel improvement of bioinformatics analyses allows the accurate detection and quantification of an increasing number of RNA species. With the aim of exploring new potential biomarkers for disease classification, a clear overview of the expression levels of common/unique small RNA species among different biospecimens is necessary. However, except for miRNAs in plasma, there are no substantial indications about the pattern of expression of various small RNAs in multiple specimens among healthy humans. Overall, the data reported hereby provide an insight of the constitution of the human miRNome and other small non-coding RNAs in various specimens of healthy individuals. This dataset was submitted by the Extracellular RNA Atlas (http://exrna-atlas.org/exat/datasets/EXR-ANACC1S6lJ1C-AN), and the selected raw and processed data for this dataset corresponds to what is available in that resource. Submitter indicates: "The publication associated with the citation below refers to a slightly larger set of samples (includes cervical scrape samples) and contains an alternative analysis to the processed data files provided here."
2019-03-16 | GSE128359 | GEO
Project description:Methylation dataset of multi regional colorectal carcinoma.
| PRJNA348738 | ENA
Project description:Inferring in humans biological responses to external cues such as drugs, chemicals, viruses and hormones, is an essential question in biomedicine and cannot be easily studied in humans. Thus, biomedical research has continuously relied on animal models for studying the impact of these compounds and attempted to M-^StranslateM-^T the results to humans. In this context, the Systems Biology Verification for Industrial Methodology for Process Verification in Research (SBV IMPROVER) initiative had run a Species Translation Challenge for the scientific community to explore and understand the limit of translatability from rodent to human using systems biology. Therefore, a multi-layer omics dataset was generated that comprised of phosphoproteomics, transcriptomics and cytokine data derived from normal human (NHBE) and rat (NRBE) bronchial epithelial cells exposed in parallel to more than 50 different stimuli under identical conditions. The present manuscript describes in detail the experimental settings, the generation, processing and quality control analysis of the multi-layer omics dataset. The datasets are accessible in public repositories could be leveraged for further translation studies.
2014-06-10 | E-MTAB-2091 | biostudies-arrayexpress