The snoGloBe interaction predictor reveals a broad spectrum of C/D snoRNA RNA targets
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ABSTRACT:
PROVIDER: PRJNA763506 | ENA |
REPOSITORIES: ENA
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| SRR15903754_1.fastq.gz | Fastqsanger.gz | |||
| SRR15903754_2.fastq.gz | Fastqsanger.gz | |||
| SRR15903755_1.fastq.gz | Fastqsanger.gz | |||
| SRR15903755_2.fastq.gz | Fastqsanger.gz | |||
| SRR15903756_1.fastq.gz | Fastqsanger.gz |
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Project description:Box C/D small nucleolar RNAs (snoRNAs) are a conserved class of RNA known for their role in guiding ribosomal RNA 2’-O-ribose methylation through base pairing with targeted sequences. Recently, C/D snoRNAs were also implicated in regulating the expression of non-ribosomal genes through different modes of binding. Large scale RNA-RNA interaction datasets detect many snoRNAs binding messenger RNA. However, these studies provide a narrow portrait of snoRNA targets forming under specific experimental conditions. To enable a more comprehensive study of C/D snoRNA interactions, we created snoGloBe, a human C/D snoRNA machine learning interaction predictor based on a gradient boosting classifier. SnoGloBe considers the target type, and position and sequence of the interactions, enabling it to outperform existing predictors. Interestingly, for specific snoRNAs, snoGloBe identifies strong enrichment of interactions near gene expression regulatory elements including splice sites. Abundance and splicing of predicted targets were altered upon the knockdown of their associated snoRNA. Strikingly, the predicted snoRNA interactions often overlap with the binding sites of functionally related RNA binding proteins, reinforcing their role in gene expression regulation. The interactions of snoRNAs are not randomly distributed but often accumulate in functionally related transcripts sharing common regulatory elements suggesting coordinated regulatory function. The wide scope of snoGloBe makes it an excellent tool for discovering viral RNA targets, which is evident from its capacity to identify snoRNAs targeting SARS-CoV-2 RNA, known to be heavily methylated. Overall, snoGloBe is capable of identifying experimentally validated binding sites and predicting novel sites with shared regulatory function.
2022-05-18 | GSE184173 | GEO
Project description:Box C/D small nucleolar RNAs (snoRNAs) are a conserved class of RNA known for their role in guiding ribosomal RNA 2'-O-ribose methylation. Recently, C/D snoRNAs were also implicated in regulating the expression of non-ribosomal genes through different modes of binding. Large scale RNA-RNA interaction datasets detect many snoRNAs binding messenger RNA, but are limited by specific experimental conditions. To enable a more comprehensive study of C/D snoRNA interactions, we created snoGloBe, a human C/D snoRNA interaction predictor based on a gradient boosting classifier. SnoGloBe considers the target type, position and sequence of the interactions, enabling it to outperform existing predictors. Interestingly, for specific snoRNAs, snoGloBe identifies strong enrichment of interactions near gene expression regulatory elements including splice sites. Abundance and splicing of predicted targets were altered upon the knockdown of their associated snoRNA. Strikingly, the predicted snoRNA interactions often overlap with the binding sites of functionally related RNA binding proteins, reinforcing their role in gene expression regulation. SnoGloBe is also an excellent tool for discovering viral RNA targets, as shown by its capacity to identify snoRNAs targeting the heavily methylated SARS-CoV-2 RNA. Overall, snoGloBe is capable of identifying experimentally validated binding sites and predicting novel sites with shared regulatory function.
| S-EPMC9226514 | biostudies-literature
Project description:Broad-spectrum antibiotics disrupt homeostatic efferocytosis
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Project description:Background: Fetal alcohol spectrum disorder (FASD) is a developmental disorder that manifests through a range of cognitive, adaptive, physiological, and neurobiological deficits resulting from prenatal alcohol exposure. Although the North American prevalence is currently estimated at 2-5%, FASD has proven difficult to identify in the absence of the overt physical features characteristic of fetal alcohol syndrome. As interventions may have the greatest impact at an early age, accurate biomarkers are needed to identify children at risk for FASD. Building on our previous work identifying distinct DNA methylation patterns in children and adolescents with FASD, we have attempted to validate these associations in a different clinical cohort and to use our DNA methylation signature to develop a possible epigenetic predictor of FASD. Methods: Genome-wide DNA methylation patterns were analyzed using the Illumina HumanMethylation450 array in the buccal epithelial cells of a cohort of 48 individuals aged 3.5-18 (24 FASD cases, 24 controls). The DNA methylation predictor of FASD was built using a stochastic gradient boosting model on our previously published dataset FASD cases and controls (GSE80261). The predictor was tested on the current dataset and an independent dataset of 48 autism spectrum disorder cases and 48 controls (GSE50759). Results: We validated findings from our previous study that identified a DNA methylation signature of FASD, replicating the altered DNA methylation levels of 161/648 CpGs in this independent cohort, which may represent a robust signature of FASD in the epigenome. We also generated a predictive model of FASD using machine learning in a subset of our previously published cohort of 179 samples (83 FASD cases, 96 controls), which was tested in this novel cohort of 48 samples and resulted in a moderately accurate predictor of FASD status. Upon testing the algorithm in an independent cohort of individuals with autism spectrum disorder, we did not detect any bias towards autism, sex, age, or ethnicity. Conclusion: These findings further support the association of FASD with distinct DNA methylation patterns, while providing a possible entry point towards the development of epigenetic biomarkers of FASD.
2018-02-23 | GSE109042 | GEO
Project description:DNA methylation as a predictor of fetal alcohol spectrum disorder
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Project description:Broad-spectrum antibiotics disrupt homeostatic efferocytosis [scRNA-seq]
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Project description:Broad-spectrum antiviral inhibitors targeting pandemic potential RNA viruses
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Project description:Broad-spectrum antibiotics disrupt homeostatic efferocytosis [bulk RNA-seq]
| PRJNA1127440 | ENA
Project description:The phagocytic clearance of apoptotic cells, termed efferocytosis, is essential for both tissue homeostasis and tissue health during cell death-inducing treatments. Failure to efficiently clear apoptotic cells augment the risk of pathological inflammation and has been linked to a myriad of autoimmune and inflammatory diseases. Although past studies have elucidated local molecular signals that regulate homeostatic efferocytosis in a tissue, whether signals arising distally also regulate homeostatic efferocytosis remains elusive. Interestingly, clinical evidence suggests that prolonged use of broad-spectrum antibiotics is associated with an increased risk of autoimmune and inflammatory disease development. We therefore hypothesized that intestinal microbes produce molecular signals that regulate efferocytotic ability in tissue phagocytes beyond the intestines. Here, we find that macrophages, the body’s professional phagocyte, display impaired efferocytosis in the peritoneum of broad-spectrum antibiotics (ABX)-treated, vancomycin-treated, and germ-free mice in vivo, the latter of which could be rescued by fecal microbiota transplantation. Mechanistically, the microbiota-derived short-chain fatty acid butyrate directly boosted efferocytosis efficiency and capacity in mouse and human macrophages, with both intestinal and local delivery of butyrate capable of rescuing ABX-induced large peritoneal macrophage (LPM) efferocytosis defects. Bulk mRNA sequencing of butyrate-treated primary macrophages in vitro and single cell mRNA sequencing of LPMs isolated from ABX-treated and butyrate-rescued mice revealed specific regulation of efferocytosis-supportive transcriptional programs. Specifically, we found that the efferocytosis receptor T-cell immunoglobulin and mucin domain containing 4 (TIM-4, Timd4) was downregulated in LPMs of ABX-treated mice which was rescued by oral butyrate and that TIM-4 was required for the butyrate-induced enhancement of LPM efferocytosis capacity in vivo. Strikingly, LPM efferocytosis was impaired well-beyond withdrawal of ABX and, importantly, ABX-treated mice exhibited significantly worse disease in a mouse model of system lupus erythematosus. Collectively, our results demonstrate that homeostatic efferocytosis relies on distal molecular signals and suggest that a defect in homeostatic efferocytosis may contribute to the clinically observed link between broad-spectrum antibiotics use and inflammatory disease.
2025-06-24 | GSE270751 | GEO
Project description:Comparative Transcriptomics of Broad-Spectrum and Synthetic Cannabidiol Treated Skeletal Myotubes
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