Extensive cellular heterogeneity of X inactivation revealed by single-cell allele-specific expression in human fibroblasts
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ABSTRACT:
PROVIDER: PRJNA507277 | ENA |
REPOSITORIES: ENA
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| SRR8249940.fastq.gz | Fastqsanger.gz | |||
| SRR8249950.fastq.gz | Fastqsanger.gz | |||
| SRR8249960.fastq.gz | Fastqsanger.gz | |||
| SRR8249970.fastq.gz | Fastqsanger.gz | |||
| SRR8249980.fastq.gz | Fastqsanger.gz |
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Project description:X-chromosome inactivation (XCI) provides a dosage compensation mechanism where, in each female cell, one of the two X chromosomes is randomly silenced. However, some genes on the inactive X chromosome and outside the pseudoautosomal regions escape from XCI and are expressed from both alleles (escapees). We investigated XCI at single-cell resolution combining deep single cellRNA sequencing with whole-genome sequencing to examine allelic-specific expression in 935 primary fibroblast and 48 lymphoblastoid single cells from five female individuals. In this framework we integrated an original method to identify and exclude doublets of cells. In fibroblast cells, we have identified 55 genes as escapees including five novel escapee genes. Moreover, we observed that all genes exhibit a variable propensity to escape XCI in each cell and cell type and that each cell displays a distinct expression profile of the escapee genes. A metric, the Inactivation Score—defined as the mean of the allelic expression profiles of the escapees per cell—enables us to discover a heterogeneous and continuous degree of cellular XCI with extremes represented by “inactive” cells, i.e., cells exclusively expressing the escaping genes from the active X chromosome and “escaping” cells expressing the escapees from both alleles. We found that this effect is associated with cell-cycle phases and, independently, with the XIST expression level, which is higher in the quiescent phase (G0). Single-cell allele-specific expression is a powerful tool to identify novel escapees in different tissues and provide evidence of an unexpected cellular heterogeneity of XCI.
2019-01-02 | GSE123028 | GEO
Project description:X-chromosome inactivation (XCI) provides a dosage compensation mechanism where, in each female cell, one of the two X chromosomes is randomly silenced. However, some genes on the inactive X chromosome and outside the pseudoautosomal regions escape from XCI and are expressed from both alleles (escapees). We investigated XCI at single-cell resolution combining deep single-cell RNA sequencing with whole-genome sequencing to examine allelic-specific expression in 935 primary fibroblast and 48 lymphoblastoid single cells from five female individuals. In this framework we integrated an original method to identify and exclude doublets of cells. In fibroblast cells, we have identified 55 genes as escapees including five undescribed escapee genes. Moreover, we observed that all genes exhibit a variable propensity to escape XCI in each cell and cell type and that each cell displays a distinct expression profile of the escapee genes. A metric, the Inactivation Score-defined as the mean of the allelic expression profiles of the escapees per cell-enables us to discover a heterogeneous and continuous degree of cellular XCI with extremes represented by "inactive" cells, i.e., cells exclusively expressing the escaping genes from the active X chromosome and "escaping" cells expressing the escapees from both alleles. We found that this effect is associated with cell-cycle phases and, independently, with the XIST expression level, which is higher in the quiescent phase (G0). Single-cell allele-specific expression is a powerful tool to identify novel escapees in different tissues and provide evidence of an unexpected cellular heterogeneity of XCI.
| S-EPMC6304968 | biostudies-literature
Project description:Extensive allele-specific translational regulation in hybrid mice
| PRJEB8233 | ENA
Project description:Extensive Heterogeneity and Intrinsic Variation in Spatial Genome Organization
| PRJNA418919 | ENA
Project description:A number of plasma glycoproteins are clinically useful as biomarkers in a variety of diseases. Although thousands of proteins are present in plasma, >95% of the plasma proteome by mass is represented by only 22 proteins. This necessitates strategies to deplete the abundant proteins and enrich other subsets of proteins. Although glycoproteins are abundant in plasma, in routine proteomic analyses, glycopeptides are not often investigated. Traditional methods such as lectin-based enrichment of glycopeptides followed by deglycosylation have helped understand the glycoproteome, but they lack any information about the attached glycans. Here, we apply size-exclusion chromatography (SEC) as a simple strategy to enrich intact glycopeptides based on their larger size which achieves broad selectivity regardless of the nature of attached glycans. Using this approach, we identified 1,317 glycopeptides belonging to 266 glycosylation sites on 154 plasma glycoproteins. The deep coverage achieved by this approach was evidenced by extensive heterogeneity that was observed. For instance, 20-100 glycopeptides were observed per protein for the top 15 glycoproteins. Overall, we found 615 novel glycopeptides of which 39 glycosylation sites (from 38 glycoproteins) are not including in protein databases such as Uniprot and GlyconnectDB. We also identified 12 novel glycopeptides containing di-sialic acid, which is a rare glycan epitope. Thus, SEC allows for efficient LC-MS/MS-based deep glycoproteomics from low amounts (~1 l) of human plasma. Overall, the SEC-based method described here is a simple, rapid and high-throughput strategy for characterization of the glycoproteome.
2021-08-18 | PXD025414 | Pride
Project description:Background: During early embryonic development, one of the two X chromosomes in mammalian female cells is inactivated to compensate for a potential imbalance in transcript levels with male cells containing a single X chromosome. We use mouse female Embryonic Stem Cells (ESCs) with nonrandom XCI and polymorphic X chromosomes to study the dynamics of gene silencing over the inactive X chromosome (Xi) by high-resolution allele-specific RNA-Seq. Results: Induction of XCI by differentiation of female ESCs shows that genes proximal to the X-inactivation center (XIC) are silenced earlier than distal genes, while lowly expressed genes show faster XCI dynamics than highly expressed genes. The active X chromosome shows a minor but significant increase in gene activity during differentiation, resulting in complete dosage compensation in differentiated cell types. Genes escaping XCI show little or no silencing during early propagation of XCI. Using allele-specific RNA-Seq of Neural Progenitor Cells (NPCs) generated from the female ESCs, we identify three regions distal to the XIC that stably escape XCI during differentiation of the female ESCs, as well as during propagation of the NPCs. These regions coincide with Topologically Associated Domains (TADs) as determined in the undifferentiated female ESCs. Also the previously characterized human gene clusters escaping XCI correlate with TADs. Conclusions: Together, the dynamics of gene silencing observed over the Xi during XCI provide further insight in the formation and maintenance of the repressive Xi complex. The association of regions of escape with TADs, in mouse and human, suggests a regulatory role for TADs during propagation of XCI. 19 RNA-Seq profiles of mouse ESCs, EpiSCs and NPCs, mostly from distant crosses to allow allele specific mapping. 1 HiC profile of an undifferentiated mouse female ESC line containing a Tsix mutation. Mainly focusing on X inactivation.
2015-06-15 | E-GEOD-60738 | biostudies-arrayexpress
Project description:Transcript function is determined by sequence elements arranged on an individual RNA molecule. Variation in transcripts can affect messenger RNA stability, localization and translation, or produce truncated proteins that differ in localization or function. Given the existence of overlapping, variable transcript isoforms, determining the functional impact of the transcriptome requires identification of full-length transcripts, rather than just the genomic regions that are transcribed. Here, by jointly determining both transcript ends for millions of RNA molecules, we reveal an extensive layer of isoform diversity previously hidden among overlapping RNA molecules. Variation in transcript boundaries seems to be the rule rather than the exception, even within a single population of yeast cells. Over 26 major transcript isoforms per protein-coding gene were expressed in yeast. Hundreds of short coding RNAs and truncated versions of proteins are concomitantly encoded by alternative transcript isoforms, increasing protein diversity. In addition, approximately 70% of genes express alternative isoforms that vary in post-transcriptional regulatory elements, and tandem genes frequently produce overlapping or even bicistronic transcripts. This extensive transcript diversity is generated by a relatively simple eukaryotic genome with limited splicing, and within a genetically homogeneous population of cells. Our findings have implications for genome compaction, evolution and phenotypic diversity between single cells. These data also indicate that isoform diversity as well as RNA abundance should be considered when assessing the functional repertoire of genomes.
| S-EPMC3705217 | biostudies-literature
Project description:<p>This study of DNA and RNA sequencing of 5 parent-offspring trios is a single center study. The goal of this study is to characterize X chromosome inactivation (XCI) ratio in females using phased genomic variations obtained through whole genome or exome sequencing in trios, followed by allele-specific expression analysis of the phased, heterozygous alleles in the mRNA of the female offspring, and to apply this method to clinical diagnosis. The distribution of allele ratios across X obtained from mRNA sequencing allows for the estimation of X inactivation status of inherited X chromosomes, and the parameters of each parental allele distributions in the offspring's mRNA data can be used as determinants for XCI ratio. This approach was used to evaluate the contribution of skewed XCI ratio to phenotypic heterogeneity in an undiagnosed, mild neurological condition.</p>
| phs000816 | dbGaP
Project description:Species-specific factors mediate extensive heterogeneity of mRNA 3' ends in yeasts
| PRJNA207281 | ENA
Project description:Several general principles of global 3D genome organization have recently been established, including non-random positioning of chromosomes and genes in the cell nucleus, distinct chromatin compartments, and topologically associating domains (TADs). However, the extent and nature of cell-to-cell and cell-intrinsic variability in genome architecture are still poorly characterized. Here, we systematically probe heterogeneity in genome organization. High-throughput optical mapping of several hundred intra-chromosomal interactions in individual human fibroblasts demonstrates low association frequencies, which are determined by genomic distance, higher-order chromatin architecture, and chromatin environment. The structure of TADs is variable between individual cells, and inter-TAD associations are common. Furthermore, single-cell analysis reveals independent behavior of individual alleles in single nuclei. Our observations reveal extensive variability and heterogeneity in genome organization at the level of individual alleles and demonstrate the coexistence of a broad spectrum of genome configurations in a cell population.
2018-11-17 | GSE107051 | GEO