Mus musculus
Ontology highlight
ABSTRACT:
PROVIDER: PRJNA338506 | ENA |
REPOSITORIES: ENA
Similar Datasets
Project description:The goal of this study was to investigate whether mammalian cell types intrinsically differ in global coordination of gene splicing and expression levels. We analyzed RNA-seq transcriptome profiles of 8 different purified mouse cell types. We found that different cell types vary in proportion of highly expressed genes and the number of alternatively spliced transcripts expressed per gene, and that the cell types that express more variants of alternatively spliced transcripts per gene are those that have higher proportion of highly expressed genes. Cell types segregated into two clusters based on high or low proportion of highly expressed genes. Biological functions involved in negative regulation of gene expression were enriched in the group of cell types with low proportion of highly expressed genes, and biological functions involved in regulation of transcription and RNA splicing were enriched in the group of cell types with high proportion of highly expressed genes. These data reveal specific candidate genes, which may be involved in global coordination of balance in the transcriptome.
2016-08-11 | GSE85458 | GEO
Project description:<p>While many genetic variants have been associated with risk for human diseases, how these variants affect gene expression in various cell types remains largely unknown. To address this gap, the DICE (Database of Immune Cell Expression, Expression quantitative trait loci (eQTLs) and Epigenomics) project was established. Considering all human immune cell types and conditions studied, we identified cis-eQTLs for a total of 12,254 unique genes, which represent 61% of all protein-coding genes expressed in these cell types. Strikingly, a large fraction (41%) of these genes showed a strong cis- association with genotype only in a single cell type. We also found that biological sex is associated with major differences in immune cell gene expression in a highly cell- specific manner. These datasets will help reveal the effects of disease risk-associated genetic polymorphisms on specific immune cell types, providing mechanistic insights into how they might influence pathogenesis (<a href="http://dice-database.org">http://dice-database.org</a>). </p>
| phs001703 | dbGaP
Project description:Standardisation of Immunopeptidomics experiments across laboratories is a pressing issue within the field, and currently a variety of different methods for sample preparation and data analysis tools are applied. Here, we compared different software packages commonly used to interrogate immunopeptidomics datasets, in order to understand to which extent differences in performance can be observed. We found that a de novo-assisted database search reports substantially more peptide sequences (~30-70%) compared to three database search engines at a global FDR of <1%. This effect was reproducible across four immunopeptidomic datasets. We validated the results using data generated with a synthetic library of 2000 HLA-associated peptides from four HLA alleles, half of which were previously observed by LC-MS, and half were predicted only. Our investigation reveals that search engines create a bias in peptide sequence length distribution and peptide amino acid composition. Therefore, the choice of peptide identification method highly influences the proportion of peptide sequences identified for each HLA allele, and resulting data should be interpreted with caution.
2021-08-10 | PXD025655 | Pride
Project description:We used single cell RNA sequencing to retrieve transcriptomics of different cell types in human airway epithelial organoids following RV1A infection. By aligning the raw reads to the viral genome, we also quantified viral RNA copies in each cell. The sequencing obtained transcription profile of 6260 cells with 53153 mean reads per cell in the mock sample, and 5727 cells with 61652 mean reads in the RV1A infected sample, before filtering in downstream analysis. We found that RV1A copies is only detected in a small proportion of the entire cell population, however, nearly all cells regardless of cell types showed ISG induction when comparing the mock and RV1A infected sample. We also characterized the expression profile genes related to viral entry: RV1A receptors of LDLR family are ubiquitously expressed in the culture.
2021-05-25 | GSE164982 | GEO
Project description:Deep sequencing datasets are used for gRNA library analysis for large-scale screens. Using a lentiviral library that targets sequences across back-splicing sites of highly expressed human circRNAs, we show that a group of circRNAs are important for cell growth mostly in a cell-type specific manner and that a common oncogenic circRNA, circFAM120A, promotes cell proliferation in vitro and in vivo.
2020-10-09 | GSE149692 | GEO
Project description:Transcription profiling of two cancer cell lines: K562 and U937. It has recently been shown that nucleosome distribution, histone modifications and RNA polymerase II (Pol II) occupancy show preferential association with exons ("exon-intron marking"), linking chromatin structure and function to co- transcriptional splicing in a variety of eukaryotes. Previous ChIP-sequencing studies suggested that these marking patterns reflect the nucleosomal landscape. By analyzing ChIP-chip datasets across the human genome in three cell types, we have found that this marking system is far more complex than previously observed. We show here that a range of histone modifications and Pol II are preferentially associated with exons. However, there is noticeable cell-type specificity in the degree of exon marking by histone modifications and, surprisingly, this is also reflected in some histone modifications patterns showing biases towards introns. Exon-intron marking is laid down in the absence of transcription on silent genes, with some marking biases changing or becoming reversed for genes expressed at different levels. Furthermore, the relationship of this marking system with splicing is not simple, with only some histone modifications reflecting exon usage/inclusion, while others mirror patterns of exon exclusion. By examining nucleosomal distributions in all three cell types, we demonstrate that these histone modification patterns cannot solely be accounted for by differences in nucleosome levels between exons and introns. In addition, because of inherent differences between ChIP-chip array and ChIP-sequencing approaches, these platforms report different nucleosome distribution patterns across the human genome. Our findings confound existing views and point to active cellular mechanisms which dynamically regulate histone modification levels and account for exon-intron marking. We believe that these histone modification patterns provide links between chromatin accessibility, Pol II movement and co-transcriptional splicing.
2010-12-03 | E-MTAB-335 | biostudies-arrayexpress
Project description:Whole genome profiling of 4 histone modifications (H3K27me1, H3K27me3,H3K36me1 and H3K36me3) using ChIP-on-chip. It has recently been shown that nucleosome distribution, histone modifications and RNA polymerase II (Pol II) occupancy show preferential association with exons ("exon-intron marking"), linking chromatin structure and function to co- transcriptional splicing in a variety of eukaryotes. Previous ChIP-sequencing studies suggested that these marking patterns reflect the nucleosomal landscape. By analyzing ChIP-chip datasets across the human genome in three cell types, we have found that this marking system is far more complex than previously observed. We show here that a range of histone modifications and Pol II are preferentially associated with exons. However, there is noticeable cell-type specificity in the degree of exon marking by histone modifications and, surprisingly, this is also reflected in some histone modifications patterns showing biases towards introns. Exon-intron marking is laid down in the absence of transcription on silent genes, with some marking biases changing or becoming reversed for genes expressed at different levels. Furthermore, the relationship of this marking system with splicing is not simple, with only some histone modifications reflecting exon usage/inclusion, while others mirror patterns of exon exclusion. By examining nucleosomal distributions in all three cell types, we demonstrate that these histone modification patterns cannot solely be accounted for by differences in nucleosome levels between exons and introns. In addition, because of inherent differences between ChIP-chip array and ChIP-sequencing approaches, these platforms report different nucleosome distribution patterns across the human genome. Our findings confound existing views and point to active cellular mechanisms which dynamically regulate histone modification levels and account for exon-intron marking. We believe that these histone modification patterns provide links between chromatin accessibility, Pol II movement and co-transcriptional splicing.
2010-12-03 | E-MTAB-336 | biostudies-arrayexpress
Project description:Here, we set out to understand if and how splicing kinetics are coordinated beyond individual intron removal and if this potential coordination could regulate alternative splicing outcomes. By measuring rates of transcription and splicing genome-wide, we found that the rate of splicing is coordinated across introns within individual genes. Furthermore, we found that elongation rates and splicing rates are coordinated within TADs, as are alternative splicing changes that result from cell type differences, differentiation programs, and alterations in splicing factor levels. Overall, our work establishes that the kinetics of transcription and splicing are coordinated within the spatial organization of the genome, which could be a control point for alternative splicing regulation that can modulate the function of a cell.
2021-05-23 | GSE146161 | 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
Project description:<p>RNA sequencing was performed on human DRGs and relative gene abundances were calculated.</p> <p>Various analyses were performed:</p> <p> <ol> <li>Human DRG gene expression profiles were contrasted with a panel of gene expression profiles of relevant tissues in human and mouse ( integrating, among other sources, datasets from ENCODE and GTex ) in order to identify.</li> <ol type="a"> <li>DRG-enriched gene expression, co-expression modules of DRG-expressed genes, and key transcriptional regulators in humans.</li> <li>Contrasting the human and mouse DRG transcriptomes to identify DRG-enriched gene expression patterns that were conserved between human and mouse, identifying putative cell types of expression of these genes, and potential known drugs that might target the corresponding gene products.</li> <li>Characterization of non-coding RNA profile of human and mouse DRGs.</li> <li>Characterization of DRG-enriched alternative splicing and alternative transcription start site usage based transcript variants in humans and mouse, and the overlap between these two species.</li> <li>Contrasting of human DRG and GTex human tibial nerve samples to identify putative axonally transported mRNAs in sensory neurons.</li> </ol> <li>Human DRG transcriptomes from donors suffering from neuropathic and/or chronic pain were contrasted with controls to identify.</li> <ol type="a"> <li>Differentially expressed genes, pathways and regulators path play a potential role in neuronal plasticity, electrophysiological activity, immune signaling and response.</li> <li>Predictive models (Random Forests) were built to jointly predict the sex and pain state of samples based on information contained solely in autosomal gene expression profile.</li> <li>Gene co-expression modules were identified and gene set enrichment analysis performed.to identify sample - pathway associations, and to broadly characterize plasticity in human DRG cell types.</li> </ol> </ol> </p>
| phs001158 | dbGaP