Mus musculus
Ontology highlight
ABSTRACT:
PROVIDER: PRJNA195938 | ENA |
REPOSITORIES: ENA
Similar Datasets
Project description:Chromatin signature identifies monoallelic gene expression across mammalian cell types (RNA-seq)
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Project description:Single-cell RNA-seq reveals dynamic paracrine control of cellular variation
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Project description:Random monoallelic expression in the mouse: SNP array data
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Project description:Chromatin signature identifies monoallelic gene expression across mammalian cell types (ChIP-seq)
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Project description:Cellular heterogeneity can emerge from the expression of only one parental allele, however it has remained unknown to what degree patterns of random monoallelic expression of autosomal genes (aRME) are mitotically inherited (clonal) or stochastic (dynamic) in somatic cells. Here, we resolved this by applying allele-sensitive single-cell RNA-seq on primary mouse fibroblasts and in vivo human T-cells to simultaneously investigate clonal and dynamic aRME. Dynamic aRME affected a considerable portion of the transcriptome, with levels dependent on the cell’s transcriptional activity, but clonal aRME was surprisingly scarce (<1% of genes) and affected mainly lowly expressed genes. Consequently, the overwhelming portion of aRME occurs transiently and is scattered throughout somatic populations rather than, as previously hypothesized, confined to spatially restricted patches of clonally related cells.
2016-09-26 | GSE75659 | GEO
Project description:The developmental dynamics and disease potential of random monoallelic gene expression
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Project description:Random monoallelic expression is defined by the allele-specific expression of genes, and by the fact that for an individual cell this monoallelic expression is neither obligate nor necessarily coordinated with the allelic expression in other cells. In order to find novel examples of random monoallelic expression in mouse, we did a transcriptome-wide survey of allele-specific gene expression in two different immortalized cell types. Lymphoblast cell lines and fibroblast cell lines were established (both clonal and nonclonal) and were used as a source of both nuclear RNA and genomic DNA. These samples were assessed for allele-specific gene expression using a custom-designed Mouse SNP Chip. A large number of genes (over 10% of those that were assessed in lymphoblast clones) displayed random monoallelic expression.
2012-02-10 | GSE35678 | GEO
Project description:Random monoallelic expression is defined by the allele-specific expression of genes, and by the fact that for an individual cell this monoallelic expression is neither obligate nor necessarily coordinated with the allelic expression in other cells. In order to find novel examples of random monoallelic expression in mouse, we did a transcriptome-wide survey of allele-specific gene expression in two different immortalized cell types. Lymphoblast cell lines and fibroblast cell lines were established (both clonal and nonclonal) and were used as a source of both nuclear RNA and genomic DNA. These samples were assessed for allele-specific gene expression using a custom-designed Mouse SNP Chip. A large number of genes (over 10% of those that were assessed in lymphoblast clones) displayed random monoallelic expression. For each cell line, two replicate samples of ds-cDNA were assessed for monoallelic expression, while genomic DNA was assessed as a control for possible LOH events. Nonclonal samples were used as controls for cis-acting allelic bias.
2012-02-10 | E-GEOD-35678 | biostudies-arrayexpress
Project description:Single-nucleus RNA sequencing (snRNA-seq) was used to profile the transcriptome of 5,264 nuclei in mouse adult testis. This dataset includes two samples from two different individuals. This dataset is part of a larger evolutionary study of adult testis at the single-nucleus level (97,521 single-nuclei in total) across mammals including 10 representatives of the three main mammalian lineages: human, chimpanzee, bonobo, gorilla, gibbon, rhesus macaque, marmoset, mouse (placental mammals); grey short-tailed opossum (marsupials); and platypus (egg-laying monotremes). Corresponding data were generated for a bird (red junglefowl, the progenitor of domestic chicken), to be used as an evolutionary outgroup.
2021-11-08 | E-MTAB-11071 | biostudies-arrayexpress
Project description:Given the possible critical importance of placental gene imprinting and random monoallelic expression on fetal and infant health, most of those genes must be identified, in order to understand the risks that the baby might meet during pregnancy and after birth. Therefore, the aim of the current study was to introduce a workflow and tools for analyzing imprinted and random monoallelic gene expression in human placenta, by applying whole-transcriptome (WT) RNA sequencing of placental tissue and genotyping of coding DNA variants in family trios. Ten family trios, each with a healthy spontaneous single-term pregnancy, were recruited. Total RNA was extracted for WT analysis, providing the full sequence information for the placental transcriptome. Parental and child blood DNA genotypes were analyzed by exome SNP genotyping microarrays, mapping the inheritance and estimating the abundance of parental expressed alleles. Imprinted genes showed consistent expression from either parental allele, as demonstrated by the SNP content of sequenced transcripts, while monoallelically expressed genes had random activity of parental alleles. We revealed 4 novel possible imprinted genes (LGALS8, LGALS14, PAPPA2 and SPTLC3) and confirmed the imprinting of 4 genes (AIM1, PEG10, RHOBTB3 and ZFAT-AS1) in human placenta. The major finding was the identification of 4 genes (ABP1, BCLAF1, IFI30 and ZFAT) with random allelic bias, expressing one of the parental alleles preferentially. The main functions of the imprinted and monoallelically expressed genes included: i) mediating cellular apoptosis and tissue development; ii) regulating inflammation and immune system; iii) facilitating metabolic processes; and iv) regulating cell cycle. Placentas from ten family trios were analysed using RNA-Seq.
2014-09-01 | E-GEOD-56524 | biostudies-arrayexpress