Mammalian embryo and cell line
Ontology highlight
ABSTRACT:
PROVIDER: PRJNA789047 | ENA |
REPOSITORIES: ENA
Similar Datasets
Project description:Mammalian sperm and oocytes have different epigenetic landscapes and are organized in different fashion. Following fertilization, the initially distinct parental epigenomes become largely equalized with the exception of certain loci including imprinting control regions. How parental chromatin becomes equalized and how imprinted genes escape this wave of reprogramming is largely unknown. Here we generated high-resolution maps of parental allele-specific DNase I hypersensitive sites (DHSs) in zygotes and morula embryos by using physically-isolated parental pronuclei, as well as parthenogenetic (PG) and androgenetic (AG) embryos. Allelic transcriptome analyses revealed a high correlation between allelic DHSs and allelic gene expression not only in known imprinted genes but also in dozens of genes not previously known to be imprinted. Interestingly, we found that many paternally- expressed genes harbor paternal allele-specific DHSs (Ps-DHSs) that are highly enriched for histone H3K27 tri-methylation (H3K27me3) but devoid of DNA methylation in maternal allele. Importantly, ectopic removal of the H3K27me3 turns Ps-DHSs into bi- allelic DHSs and induces maternal allele derepression in genes that include maternal DNA methylation-independent imprinted genes Gab1, Sfmbt2, Slc38a4, and Phf17 (also known as Jade1). Thus, our study not only reveals parental allele-specific chromatin accessibility of preimplantation embryos, but also identifies maternal H3K27me3 as a DNA methylation- independent mechanism for genomic imprinting.
2017-07-19 | GSE92605 | GEO
Project description:We performed profiling of allele-specific chromatin accessibility profiling in mouse spermatocytes. To this end, we isolated tetraploid spermatocytes using FACS-sorting from F1 crosses of the C57B6J and CAST/EiJ strains. We then performed ATAC-Seq (Corces et al. 2017) and analyzed allele-specific chromatin accessibility.
2023-12-01 | E-MTAB-12685 | biostudies-arrayexpress
Project description:We used cre-directed biotinylation of a GATA4 knockin allele with an AviTag epitope tag to measure GATA4 chromatin occupancy in endocardial and cardiomyocyte lineages in the E12.5 heart. These data are complemented by lineage selective measurement of gene expression and chromatin accessibility. Cardiomyocyte accessibility and gene expression data were reported in GSE124008.
2021-07-01 | GSE156001 | GEO
Project description:We hypothesized that LincGET/CARM1 complex activates ICM-specific genes at the 8-cell stage. And we examined chromatin accessibility of these genes by preforming an assay for transposase-accessible chromatin with high-throughput sequencing (ATAC-seq)
2018-12-13 | GSE110419 | GEO
Project description:We have sequenced 10 melanoma samples using 10X linked reads technology to obtain phased whole genome sequence data. Using this data, we created diploid personalized genomes for each sample and aligned functional genomics data obtained from the same samples in order to find allele specific events (such as allele-specific binding and allele-specific chromatin accessibility).
| EGAS00001004136 | EGA
Project description:Spatiotemporal gene regulation during embryonic development is driven by cis-regulatory DNA sequences called enhancers. Enhancers are activated through a combination of transcription factors (TFs) that bind to short sequence motifs within these sequences, but the order of events by which TFs read out motifs is not clear. Some TFs can only bind chromatin that is already accessible, while other TFs called pioneers can open chromatin themselves. Identifying motifs and the order by which they drive chromatin accessibility is very challenging. The recent implementation of convolutional neural networks, which learn complex cis-regulatory sequence rules that are predictive for genomics data, provides an unprecedented opportunity to dissect this problem. Here, we trained base-resolution deep learning models and applied them to high-resolution TF binding and chromatin accessibility data from the well-studied early Drosophila embryo. We uncover a clear hierarchical relationship between the pioneer Zelda and the TFs involved in the spatiotemporal patterning of the embryo, consistent with Zelda being a pioneer. However, the models predict that patterning TFs can also augment chromatin accessibility in a context-specific manner. Using a series of Drosophila mutant strains, we find that the two types of TFs increase chromatin accessibility by distinct mechanisms. Zelda’s pioneering is proportional to motif affinity, while the patterning TFs specifically increase chromatin accessibility when they mediate enhancer activation. This was conclusive because Dorsal can function both as activator and repressor, and the effect on chromatin accessibility depended on Dorsal’s transactivation effect and not on its binding per se. In conclusion, chromatin accessibility occurs in two phases: one through pioneering, which makes regions first accessible but not necessarily active, and a second when the correct combination of transcription factors lead to enhancer activation.
2022-12-20 | GSE218851 | GEO
Project description:We applied a combinatorial indexing assay, sci-ATAC-seq, to profile genome-wide chromatin accessibility in ~100,000 single cells from 13 adult mouse tissues. We identify 85 distinct patterns of chromatin accessibility, most of which can be assigned to cell types, and ~400,000 differentially accessible elements. We use these data to link regulatory elements to their target genes, to define the transcription factor grammar specifying each cell type, and to discover in vivo correlates of heterogeneity in accessibility within cell types. We develop a technique for mapping single cell gene expression data to single-cell chromatin accessibility data, facilitating the comparison of atlases. By intersecting mouse chromatin accessibility with human genome-wide association summary statistics, we identify cell-type-specific enrichments of the heritability signal for hundreds of complex traits. These data define the in vivo landscape of the regulatory genome for common mammalian cell types at single-cell resolution.
2018-08-02 | GSE111586 | GEO
Project description:Spatiotemporal gene regulation during embryonic development is driven by cis-regulatory DNA sequences called enhancers. Enhancers are activated through a combination of transcription factors (TFs) that bind to short sequence motifs within these sequences, but the order of events by which TFs read out motifs is not clear. Some TFs can only bind chromatin that is already accessible, while other TFs called pioneers can open chromatin themselves. Identifying motifs and the order by which they drive chromatin accessibility is very challenging. The recent implementation of convolutional neural networks, which learn complex cis-regulatory sequence rules that are predictive for genomics data, provides an unprecedented opportunity to dissect this problem. Here, we trained base-resolution deep learning models and applied them to high-resolution TF binding and chromatin accessibility data from the well-studied early Drosophila embryo. We uncover a clear hierarchical relationship between the pioneer Zelda and the TFs involved in the spatiotemporal patterning of the embryo, consistent with Zelda being a pioneer. However, the models predict that patterning TFs can also augment chromatin accessibility in a context-specific manner. Using a series of Drosophila mutant strains, we find that the two types of TFs increase chromatin accessibility by distinct mechanisms. Zelda’s pioneering is proportional to motif affinity, while the patterning TFs specifically increase chromatin accessibility when they mediate enhancer activation. This was conclusive because Dorsal can function both as activator and repressor, and the effect on chromatin accessibility depended on Dorsal’s transactivation effect and not on its binding per se. In conclusion, chromatin accessibility occurs in two phases: one through pioneering, which makes regions first accessible but not necessarily active, and a second when the correct combination of transcription factors lead to enhancer activation.
2022-12-20 | GSE218850 | GEO
Project description:Spatiotemporal gene regulation during embryonic development is driven by cis-regulatory DNA sequences called enhancers. Enhancers are activated through a combination of transcription factors (TFs) that bind to short sequence motifs within these sequences, but the order of events by which TFs read out motifs is not clear. Some TFs can only bind chromatin that is already accessible, while other TFs called pioneers can open chromatin themselves. Identifying motifs and the order by which they drive chromatin accessibility is very challenging. The recent implementation of convolutional neural networks, which learn complex cis-regulatory sequence rules that are predictive for genomics data, provides an unprecedented opportunity to dissect this problem. Here, we trained base-resolution deep learning models and applied them to high-resolution TF binding and chromatin accessibility data from the well-studied early Drosophila embryo. We uncover a clear hierarchical relationship between the pioneer Zelda and the TFs involved in the spatiotemporal patterning of the embryo, consistent with Zelda being a pioneer. However, the models predict that patterning TFs can also augment chromatin accessibility in a context-specific manner. Using a series of Drosophila mutant strains, we find that the two types of TFs increase chromatin accessibility by distinct mechanisms. Zelda’s pioneering is proportional to motif affinity, while the patterning TFs specifically increase chromatin accessibility when they mediate enhancer activation. This was conclusive because Dorsal can function both as activator and repressor, and the effect on chromatin accessibility depended on Dorsal’s transactivation effect and not on its binding per se. In conclusion, chromatin accessibility occurs in two phases: one through pioneering, which makes regions first accessible but not necessarily active, and a second when the correct combination of transcription factors lead to enhancer activation.
2022-12-20 | GSE218849 | GEO
Project description:Spatiotemporal gene regulation during embryonic development is driven by cis-regulatory DNA sequences called enhancers. Enhancers are activated through a combination of transcription factors (TFs) that bind to short sequence motifs within these sequences, but the order of events by which TFs read out motifs is not clear. Some TFs can only bind chromatin that is already accessible, while other TFs called pioneers can open chromatin themselves. Identifying motifs and the order by which they drive chromatin accessibility is very challenging. The recent implementation of convolutional neural networks, which learn complex cis-regulatory sequence rules that are predictive for genomics data, provides an unprecedented opportunity to dissect this problem. Here, we trained base-resolution deep learning models and applied them to high-resolution TF binding and chromatin accessibility data from the well-studied early Drosophila embryo. We uncover a clear hierarchical relationship between the pioneer Zelda and the TFs involved in the spatiotemporal patterning of the embryo, consistent with Zelda being a pioneer. However, the models predict that patterning TFs can also augment chromatin accessibility in a context-specific manner. Using a series of Drosophila mutant strains, we find that the two types of TFs increase chromatin accessibility by distinct mechanisms. Zelda’s pioneering is proportional to motif affinity, while the patterning TFs specifically increase chromatin accessibility when they mediate enhancer activation. This was conclusive because Dorsal can function both as activator and repressor, and the effect on chromatin accessibility depended on Dorsal’s transactivation effect and not on its binding per se. In conclusion, chromatin accessibility occurs in two phases: one through pioneering, which makes regions first accessible but not necessarily active, and a second when the correct combination of transcription factors lead to enhancer activation.
2022-12-20 | GSE218848 | GEO