Homo sapiens
Ontology highlight
ABSTRACT:
PROVIDER: PRJNA269767 | ENA |
REPOSITORIES: ENA
Similar Datasets
Project description:Genome-wide perturbations by miRNA map onto functional cancer pathways identifying regulators of chromatin modifiers
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Project description:Genome-wide perturbations by miRNA map onto functional cancer pathways identifying regulators of chromatin modifiers Total RNA obtained from cancer cell lines transfected with miR-365-3p for 24 hours compared to controls.
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2021-06-15 | PXD018706 | Pride
Project description:Identifying processes occurring in early life affect subsequent life and health span is an urgent aim to improve human health. In this study, we identified a novel mechanism of dFOXO in longevity determination in Drosophila. We found that early adulthood induction of dFOXO is sufficient to reduce mortality in old age through different pathways than chronic dFOXO. We showed that dFOXO requires specific ATP-dependent chromatin modifiers to extend lifespan, and we could mimic this lifespan extension by modulating dFOXO’s targets in later life. Furthermore, dFOXO in early life induces a specific transcriptional programme that counteracts the natural transcriptomic changes occurring with age. Our findings provide a better understanding of transcriptional mechanisms related to longevity and opens new avenues for possible time-restricted interventions to improve human health in the future.
2022-09-28 | MTBLS3251 | MetaboLights
Project description:Pluripotent stem cells (PSCs) are capable of dynamic interconversion between distinct substates, but the regulatory circuits specifying these states and enabling transitions between them are not well understood. We set out to address this issue and map the landscape of gene expression variability in PSCs by single-cell expression profiling of PSCs under different chemical and genetic perturbations. We find that signaling factors and developmental regulators show highly variable expression in PSCs, with expression states for some variable genes heritable through multiple cell divisions. Expression variability and population heterogeneity can be influenced by perturbation of signaling pathways and chromatin regulators. Strikingly, either removal of mature miRNAs or pharmacologic blockage of external signaling pathways drives PSCs into a low-noise ground state characterized by a reconfigured pluripotency regulatory network, increased self-renewal efficiency, and a distinct chromatin state, an effect mediated by the action of opposing miRNA families on the c-myc / Lin28 / let-7 axis. These findings illuminate the causes of transcriptional heterogeneity in PSCs and their consequences for cellular decision-making. Single-cell RNA-Seq on 183 individual v6.5 mouse embryonic stem cells (mESCs) cultured in serum+LIF media, 94 v6.5 mESCs cultured in 2i+LIF media ('ground state' conditions), and 84 Dgcr8 -/- mESCs (constructed in a v6.5 background), that lack mature miRNAs due to knockout of a miRNA processing factor, cultured in serum+LIF. ChIP-Seq for RNA polymerase II, H3K4me3, H3K27me3, H3K27ac, H3K9me3, and H3K36me3 on the three populations of mESCs profiled by single-cell RNA-Seq. Single-cell RNA-Seq on 54 individual nestin-positive neural precursor cells derived from v6.5 mESCs.
2014-12-04 | E-GEOD-60749 | biostudies-arrayexpress
Project description:Single-cell perturbation dictionaries systematically measure how cells respond to genetic and chemical perturbations, creating the opportunity to assign causal interpretations to observational data. We introduce RNA fingerprinting, a statistical framework that maps transcriptional responses from new experiments onto reference perturbation dictionaries. RNA fingerprinting learns representations of perturbations, or ``fingerprints," from single-cell data, then probabilistically assigns query cells to one or more candidate perturbations. We benchmark our method across ground-truth datasets, demonstrating accurate assignments at single-cell resolution, scalability to genome-wide screens, and the ability to resolve combinatorial perturbations. We demonstrate its broad utility across diverse biological settings: identifying context-specific regulators of p53 under ribosomal stress, characterizing drug mechanisms of action and dose-dependent off-target effects, and uncovering cytokine-driven B cell heterogeneity during secondary influenza infection in vivo. Together, these results establish RNA fingerprinting as a versatile framework for interpreting single-cell datasets by linking cellular states to the underlying perturbations which generated them.
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Project description:Single-cell perturbation dictionaries systematically measure how cells respond to genetic and chemical perturbations, creating the opportunity to assign causal interpretations to observational data. We introduce RNA fingerprinting, a statistical framework that maps transcriptional responses from new experiments onto reference perturbation dictionaries. RNA fingerprinting learns representations of perturbations, or ``fingerprints," from single-cell data, then probabilistically assigns query cells to one or more candidate perturbations. We benchmark our method across ground-truth datasets, demonstrating accurate assignments at single-cell resolution, scalability to genome-wide screens, and the ability to resolve combinatorial perturbations. We demonstrate its broad utility across diverse biological settings: identifying context-specific regulators of p53 under ribosomal stress, characterizing drug mechanisms of action and dose-dependent off-target effects, and uncovering cytokine-driven B cell heterogeneity during secondary influenza infection in vivo. Together, these results establish RNA fingerprinting as a versatile framework for interpreting single-cell datasets by linking cellular states to the underlying perturbations which generated them.
2026-07-27 | GSE339457 | GEO
Project description:Single-cell perturbation dictionaries systematically measure how cells respond to genetic and chemical perturbations, creating the opportunity to assign causal interpretations to observational data. We introduce RNA fingerprinting, a statistical framework that maps transcriptional responses from new experiments onto reference perturbation dictionaries. RNA fingerprinting learns representations of perturbations, or ``fingerprints," from single-cell data, then probabilistically assigns query cells to one or more candidate perturbations. We benchmark our method across ground-truth datasets, demonstrating accurate assignments at single-cell resolution, scalability to genome-wide screens, and the ability to resolve combinatorial perturbations. We demonstrate its broad utility across diverse biological settings: identifying context-specific regulators of p53 under ribosomal stress, characterizing drug mechanisms of action and dose-dependent off-target effects, and uncovering cytokine-driven B cell heterogeneity during secondary influenza infection in vivo. Together, these results establish RNA fingerprinting as a versatile framework for interpreting single-cell datasets by linking cellular states to the underlying perturbations which generated them.
2026-07-27 | GSE339461 | GEO
Project description:<p>Our current understanding of autism spectrum disorders (ASD) delineates a highly heritable, yet etiologically heterogeneous disease. Forward genetic approaches to find disease associated mutations or common variation have been successful and continue to offer considerable power. Yet, given the accumulating evidence for very significant heterogeneity and environmental influences, complementary approaches to classic forward genetics become necessary. Genetic polymorphism and mutation data to date have identified dozens of causal or contributory variants, yet our preliminary data from autism brain suggest that common molecular pathways are involved in a significant subset of cases. This convergence at the tissue level suggests that other mechanisms, specifically epigenetic changes, combined with genetic background, are contributing to such final common pathways. We further tested this hypothesis by taking a comprehensive and integrative genome-wide approach to assessing brain gene-expression, miRNA levels and the related, causal epigenetic mechanisms in ASD etiology. </p> <p>We performed RNA-seq analyses of four cerebral cortical regions and cerebellum from ASD cases and controls, to assess mRNA, miRNA, and splicing isoform regulation. In parallel, we identified key differences in chromatin state and DNA methylation across multiple brain regions in the same ASD and control individuals used in the expression analyses using ChIP-Seq and MeDIP. We assessed the mechanisms by which changes in DNA methylation, histone modification, and DNA sequence contribute to the observed differences in gene expression. This work, which represents an unprecedented effort to unify these often disparate data (usually produced without integration in mind), delineates potential shared molecular pathways in ASD and the underlying mechanism of these differences at the level of miRNA, the chromatin regulatory apparatus, and DNA methylation.</p> <p>The following substudies are part of the PsychENCODE release at dbGaP and offer additional molecular data: <ul> <li>PsychENCODE: RNA-Sequencing - SRRM4 Splicing Study <a href="study.cgi?study_id=phs000872">phs000872</a></li> <li>PsychENCODE: Global Changes in Patterning, Splicing and lncRNAs <a href="study.cgi?study_id=phs001061">phs001061</a></li> <li>PsychENCODE: Chromatin Contact Map in Fetal Cortical Laminae <a href="study.cgi?study_id=phs001190">phs001190</a></li> <li>PsychENCODE: Epigenetic Dysregulation in Autism Spectrum Disorder <a href="study.cgi?study_id=phs001220">phs001220</a></li> </ul> </p>
| phs001022 | dbGaP