Homo sapiens
Ontology highlight
ABSTRACT:
PROVIDER: PRJNA148897 | ENA |
REPOSITORIES: ENA
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2017-03-31 | MSV000080829 | MassIVE
Project description:MicroRNAs (miRs) function primarily as post-transcriptional negative regulators of gene expression through binding to their mRNA targets. Reliable prediction of a miR’s targets is a considerable bioinformatic challenge of great importance for inferring the miR’s function. Sequence-based prediction algorithms have high false-positive rates, are not in agreement, and are not biological context specific. Here we introduce CoSMic (Context-Specific MicroRNA analysis), an algorithm that combines sequence-based prediction with miR and mRNA expression data. CoSMic differs from existing methods—it identifies miRs that play active roles in the specific biological system of interest and predicts with less false positives their functional targets. We applied CoSMic to search for miRs that regulate the migratory response of human mammary cells to epidermal growth factor (EGF) stimulation. Several such miRs, whose putative targets were significantly enriched by migration processes were identified. We tested three of these miRs experimentally, and showed that they indeed affected the migratory phenotype; we also tested three negative controls. In comparison to other algorithms CoSMic indeed filters out false positives and allows improved identification of context-specific targets. CoSMic can greatly facilitate miR research in general and, in particular, advance our understanding of individual miRs’ function in a specific context.
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Project description:microRNA dysregulation is a common feature of cancer cells, but the complex roles of microRNAs in cancer are not fully elucidated. Here we used functional genomics to identify oncogenic microRNAs in non-small cell lung cancer and to evaluate their impact on response to EGFR targeting therapy. Our data demonstrate that microRNAs with an AAGUGC-motif in their seed-sequence increase both cancer cell proliferation and sensitivity to EGFR inhibitors. Global transcriptomics, proteomics and target prediction resulted in the identification of several tumor suppressors involved in the G1/S transition as targets of AAGUGC-microRNAs. The clinical implications of our findings were evaluated by analysis of public domain data supporting the link between this microRNA seed-family, their tumor suppressor targets and cancer cell proliferation. In conclusion we propose that AAGUGC-microRNAs are an integral part of an oncogenic signaling network, and that these findings have potential therapeutic implications, especially in selecting patients for EGFR-targeting therapy.
2016-06-28 | PXD004163 | Pride
Project description:Identification of MicroRNAs Targeting to a Specific mRNA Loci
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Project description:Naïve CD8+ T cells are heterogenous, with subsets exhibiting divergent kinetics and functions post-activation. MicroRNAs (miRNAs) are post-transcriptional regulators, and certain miRNAs contribute to specification of different naïve T cell subsets. However, the microRNA regulatory circuits mediating functional specialization of naïve subsets have not been identified. In this work, we profiled microRNA expression in diverse subsets of naïve CD8+ T cells, revealing significant differences in their microRNA expression landscapes. We developed a novel framework, miR-Inf, to decipher microRNA regulatory programs. MiR-Inf has two key components: (i) an efficient method for estimating gene decay rates from the RNA seq profiles to better capture microRNA regulatory effects, and (ii) identification of functional microRNA targets by integrating decay rate data and microRNA expression data. We applied this framework to identify consequential miRNAs in naïve CD8+ T cell subsets and predicted their context-specific targets. Our analyses revealed that miR-29, a microRNA known to be important in CD8+ T cells, likely functions by modulating transcripts encoding epigenetic factors. Collectively, our data and framework defined microRNA regulatory circuits across diverse naïve CD8+ T cell subsets.
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Project description:Naïve CD8+ T cells are heterogenous, with subsets exhibiting divergent kinetics and functions post-activation. MicroRNAs (miRNAs) are post-transcriptional regulators, and certain miRNAs contribute to specification of different naïve T cell subsets. However, the microRNA regulatory circuits mediating functional specialization of naïve subsets have not been identified. In this work, we profiled microRNA expression in diverse subsets of naïve CD8+ T cells, revealing significant differences in their microRNA expression landscapes. We developed a novel framework, miR-Inf, to decipher microRNA regulatory programs. MiR-Inf has two key components: (i) an efficient method for estimating gene decay rates from the RNA seq profiles to better capture microRNA regulatory effects, and (ii) identification of functional microRNA targets by integrating decay rate data and microRNA expression data. We applied this framework to identify consequential miRNAs in naïve CD8+ T cell subsets and predicted their context-specific targets. Our analyses revealed that miR-29, a microRNA known to be important in CD8+ T cells, likely functions by modulating transcripts encoding epigenetic factors. Collectively, our data and framework defined microRNA regulatory circuits across diverse naïve CD8+ T cell subsets.
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Project description:Naïve CD8+ T cells are heterogenous, with subsets exhibiting divergent kinetics and functions post-activation. MicroRNAs (miRNAs) are post-transcriptional regulators, and certain miRNAs contribute to specification of different naïve T cell subsets. However, the microRNA regulatory circuits mediating functional specialization of naïve subsets have not been identified. In this work, we profiled microRNA expression in diverse subsets of naïve CD8+ T cells, revealing significant differences in their microRNA expression landscapes. We developed a novel framework, miR-Inf, to decipher microRNA regulatory programs. MiR-Inf has two key components: (i) an efficient method for estimating gene decay rates from the RNA seq profiles to better capture microRNA regulatory effects, and (ii) identification of functional microRNA targets by integrating decay rate data and microRNA expression data. We applied this framework to identify consequential miRNAs in naïve CD8+ T cell subsets and predicted their context-specific targets. Our analyses revealed that miR-29, a microRNA known to be important in CD8+ T cells, likely functions by modulating transcripts encoding epigenetic factors. Collectively, our data and framework defined microRNA regulatory circuits across diverse naïve CD8+ T cell subsets.
2025-08-25 | GSE280665 | GEO
Project description:Naïve CD8+ T cells are heterogenous, with subsets exhibiting divergent kinetics and functions post-activation. MicroRNAs (miRNAs) are post-transcriptional regulators, and certain miRNAs contribute to specification of different naïve T cell subsets. However, the microRNA regulatory circuits mediating functional specialization of naïve subsets have not been identified. In this work, we profiled microRNA expression in diverse subsets of naïve CD8+ T cells, revealing significant differences in their microRNA expression landscapes. We developed a novel framework, miR-Inf, to decipher microRNA regulatory programs. MiR-Inf has two key components: (i) an efficient method for estimating gene decay rates from the RNA seq profiles to better capture microRNA regulatory effects, and (ii) identification of functional microRNA targets by integrating decay rate data and microRNA expression data. We applied this framework to identify consequential miRNAs in naïve CD8+ T cell subsets and predicted their context-specific targets. Our analyses revealed that miR-29, a microRNA known to be important in CD8+ T cells, likely functions by modulating transcripts encoding epigenetic factors. Collectively, our data and framework defined microRNA regulatory circuits across diverse naïve CD8+ T cell subsets.
2025-08-25 | GSE280664 | GEO
Project description:Naïve CD8+ T cells are heterogenous, with subsets exhibiting divergent kinetics and functions post-activation. MicroRNAs (miRNAs) are post-transcriptional regulators, and certain miRNAs contribute to specification of different naïve T cell subsets. However, the microRNA regulatory circuits mediating functional specialization of naïve subsets have not been identified. In this work, we profiled microRNA expression in diverse subsets of naïve CD8+ T cells, revealing significant differences in their microRNA expression landscapes. We developed a novel framework, miR-Inf, to decipher microRNA regulatory programs. MiR-Inf has two key components: (i) an efficient method for estimating gene decay rates from the RNA seq profiles to better capture microRNA regulatory effects, and (ii) identification of functional microRNA targets by integrating decay rate data and microRNA expression data. We applied this framework to identify consequential miRNAs in naïve CD8+ T cell subsets and predicted their context-specific targets. Our analyses revealed that miR-29, a microRNA known to be important in CD8+ T cells, likely functions by modulating transcripts encoding epigenetic factors. Collectively, our data and framework defined microRNA regulatory circuits across diverse naïve CD8+ T cell subsets.
2025-08-25 | GSE280662 | GEO
Project description:Among the Chordates tunicates demonstrate the highest capacity for regeneration, ranging from full-body regeneration in colonial ascidians to appendage regeneration in solitary ascidians. Here we present a parallel study of mRNA and microRNA expression at three stages of oral siphon regeneration in the solitary ascidian Ciona robusta (a.k.a., Ciona intestinalis), and the derived network of their interactions. In the process of identifying 248 mRNAs and 15 microRNAs as differentially expressed (DE) across the course of regeneration, we also identified 57 novel microRNAs, several of which are among the most highly DE. Analysis functional categories identified transcripts related to stress responses and apoptosis enriched at the wound healing stage, various signaling pathways including Wnt and TGF-β enriched during early regrowth, and negative regulation of extracellular remodeling proteases as enriched in late stage regeneration. Additionally, comprehensive 3’-UTR binding site prediction and probability of conserved targeting for all C. robusta microRNAs (including those identified here) was calculated using TargetScanS. A microRNA-target network was subsequently constructed by calculating Pearson correlation coefficients for all predicted microRNA-mRNA target pairs expressed during regeneration. Network based clustering associated one or more microRNAs and their targets into 22 non-overlapping groups. Functional analysis of mRNA targets in each network cluster showed that enrichment of stress response, signaling pathway and extracellular remodeling categories associated with specific stages could also be associated with specific microRNAs. Finally, predicted targets of the miR-9 network cluster suggest a role in regulating differentiation and proliferative state of neural progenitors through regulation of the cytoskeleton and cell cycle. This work represents a significant advance in the prediction of microRNA effects on appendage regeneration and provides a foundation for investigating evolutionary conservation of microRNAs during regeneration in chordates.
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