Allele specific chromatin signals and 3D interactions
Ontology highlight
ABSTRACT:
PROVIDER: PRJEB25327 | ENA |
REPOSITORIES: ENA
Similar Datasets
Project description:Copy number analysis was performed using genotyping microarrays for 20 choroid plexus tumors. Genomic aberrations were investigated by tumor histological classification and the pattern observed in each subgroup was further refined. Allele-specific copy number analysis also allowed us to identify regions of acquired uniparental disomy with neutral copy number values.
2014-11-01 | GSE61363 | GEO
Project description:Copy number analysis was performed using genotyping microarrays for 55 choroid plexus tumors. Genomic aberrations were investigated by tumor histological classification and the pattern observed in each subgroup was further refined. Allele specific copy number analysis also allowed us to identify regions of acquired uniparental disomy with neutral copy number values.
2014-11-01 | GSE60899 | GEO
Project description:The identification of cell-type-specific 3D chromatin interactions between regulatory elements can help to decipher gene regulation and to interpret the function of disease-associated non-coding variants. However, current chromosome conformation capture (3C) technologies are unable to resolve interactions at this resolution when only small numbers of cells are available as input. We therefore present ChromaFold, a deep learning model that predicts 3D contact maps and regulatory interactions from single-cell ATAC sequencing (scATAC-seq) data alone. ChromaFold uses pseudobulk chromatin accessibility, co-accessibility profiles across metacells, and predicted CTCF motif tracks as input features and employs a lightweight architecture to enable training on standard GPUs. Once trained on paired scATAC-seq and Hi-C data in human cell lines and tissues, ChromaFold can accurately predict both the 3D contact map and peak-level interactions across diverse human and mouse test cell types. In benchmarking against a recent deep learning method that uses bulk ATAC-seq, DNA sequence, and CTCF ChIP-seq to make cell-type-specific predictions, ChromaFold yields superior prediction performance when including CTCF ChIP-seq data as an input and comparable performance without. Finally, fine-tuning ChromaFold on paired scATAC-seq and Hi-C in a complex tissue enables deconvolution of chromatin interactions across cell subpopulations. ChromaFold thus achieves state-of-the-art prediction of 3D contact maps and regulatory interactions using scATAC-seq alone as input data, enabling accurate inference of celltype- specific interactions in settings where 3C-based assays are infeasible.
2024-08-31 | GSE246859 | GEO
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2023-09-13 | GSE209570 | GEO
Project description:Here we present complete genomic and biochemical annotations of the signals required for RNA degradation by the dsRNA specific ribonuclease III (Rnt1p) and examine its impact on transcriptome stability. Rnt1p cleavage signals are randomly distributed in the yeast genome and encompass wide variety of sequence indicating that transcriptome stability is not determined by the recurrence of a fixed cleavage motif. Instead, RNA reactivity is defined by the sequence and structural context in which the cleavage sites are located. Reactive signals are often associated with transiently expressed genes and their impact on RNA expression is linked to growth conditions. Together the data suggest that stability of the yeast transcriptome is regulated by malleable RNA degradation signals that permit dynamic response to changes in growth conditions. WT, rnt1 delta and rrp6 delta strains where grown independently and analyzed by Affymetrix yeast tiling microarray analysis
2015-02-16 | E-GEOD-57390 | biostudies-arrayexpress
Project description:Genomic information is encoded on a wide range of distance scales, ranging from tens of base pairs to megabases. We developed a multiscale framework to analyze and visualize the information content of genomic signals. Different types of signals, such as GC content or DNA methylation, are characterized by distinct patterns of signal enrichment or depletion across scales spanning several orders of magnitude. These patterns are associated with a variety of genomic annotations, including genes, nuclear lamina associated domains, and repeat elements. By integrating the information across all scales, as compared to using any single scale, we demonstrate improved prediction of gene expression from Polymerase II ChIP-seq measurements and we observed that gene expression differences in colorectal cancer are not most strongly related to gene body methylation, but rather to methylation patterns that extend beyond the single-gene scale.
2014-04-13 | GSE54414 | GEO
Project description:Here we present complete genomic and biochemical annotations of the signals required for RNA degradation by the dsRNA specific ribonuclease III (Rnt1p) and examine its impact on transcriptome stability. Rnt1p cleavage signals are randomly distributed in the yeast genome and encompass wide variety of sequence indicating that transcriptome stability is not determined by the recurrence of a fixed cleavage motif. Instead, RNA reactivity is defined by the sequence and structural context in which the cleavage sites are located. Reactive signals are often associated with transiently expressed genes and their impact on RNA expression is linked to growth conditions. Together the data suggest that stability of the yeast transcriptome is regulated by malleable RNA degradation signals that permit dynamic response to changes in growth conditions. Total RNA from rnt1d strain was divided in two samples. One sample was treated with purified Rnt1p. The other was only incubated with buffer. The two samples were then enriched for small RNA.
2015-02-16 | E-GEOD-57448 | biostudies-arrayexpress
Project description:Here we present complete genomic and biochemical annotations of the signals required for RNA degradation by the dsRNA specific ribonuclease III (Rnt1p) and examine its impact on transcriptome expression. Rnt1p cleavage signals are randomly distributed in the yeast genome and encompass wide variety of sequence indicating that transcriptome stability is not determined by the recurrence of a fixed cleavage motif. Instead, RNA reactivity is defined by the sequence and structural context in which the cleavage sites are located. Reactive signals are often associated with transiently expressed genes and their impact on RNA expression is linked to growth conditions. Together the data suggest that Rnt1p reactivity is triggered by malleable RNA degradation signals that permit dynamic response to changes in growth conditions. Total RNA and whole cell extract from rnt1d strain was divided in two samples. One sample was treated with purified Rnt1p. The other was only incubated with buffer. The two samples were then treated with recombinant Xrn1p.
2015-02-16 | E-GEOD-57447 | biostudies-arrayexpress