Ontology highlight
ABSTRACT:
PROVIDER: PRJNA699405 | ENA |
REPOSITORIES: ENA
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| SRR13626600.fastq.gz | Fastqsanger.gz | |||
| SRR13626700.fastq.gz | Fastqsanger.gz | |||
| SRR13626601.fastq.gz | Fastqsanger.gz | |||
| SRR13626701.fastq.gz | Fastqsanger.gz | |||
| SRR13626602.fastq.gz | Fastqsanger.gz |
Items per page: 5 1 - 5 of 188 |
Similar Datasets
Project description:The chromatin interaction assays, particularly Hi-C, enabled detailed studies of chromatin architecture in multiple organisms and model systems, resulting in a deeper understanding of gene expression regulation mediated by epigenetics mechanisms. However, the analysis and interpretation of Hi-C data remain challenging due to technical biases, limiting direct comparisons of datasets obtained in different experiments and laboratories. As a result, removing biases from Hi-C-generated chromatin contact matrices is a critical data analysis step. Our novel approach HiConfidence eliminates biases from the Hi-C data by weighing chromatin contacts according to their consistency between replicates so that low-quality replicates do not influence the result. The algorithm is effective for the analysis of global changes in chromatin structures such as compartments and TADs. We apply the HiConfidence approach to several Hi-C datasets with significant technical biases that could not be analyzed effectively using existing methods, and obtain meaningful biological conclusions. In particular, HiConfidence aids in the study of how changes in the histone acetylation pattern affect chromatin organization in Drosophila cells.
2023-02-05 | GSE200078 | GEO
Project description:Glioblastoma progression remains elusive, especially in its first stages. Here, by simultaneous transfer of PDGFB and genetic barcode in mouse brain, we triggered gliomagenesis in univocally labelled cells in vivo, hence enabling direct tracing of glioblastoma evolution from the earliest possible stage. We observed an unexpectedly high incidence of clonal extinction events and progressive clonal size divergence, even after the acquisition of a malignant phenotype. Computational modelling suggests these dynamics as the consequence of a clonal-based cell-cell competition. Bulk and single-cell transcriptome analyses, coupled to lineage tracing, revealed that the strongest correlation with clonal size unbalancing is shown by Myc transcriptional targets. Additionally, higher levels of Myc signalling discriminate "winner" from "loser" clones in early gliomagenesis. These results agree with recent understanding of the Myc-mediated induction of supercompetitive phenotype in mammalian embryo. Our findings shed light on aspects of glioblastoma evolution inaccessible by conventional retrospective approaches and highlight the potential of the combined use of clonal tracing and transcriptomic analyses in this field.
2023-07-18 | GSE189577 | GEO
Project description:Glioblastoma progression remains elusive, especially in its first stages. Here, by simultaneous transfer of PDGFB and genetic barcode in mouse brain, we triggered gliomagenesis in univocally labelled cells in vivo, hence enabling direct tracing of glioblastoma evolution from the earliest possible stage. We observed an unexpectedly high incidence of clonal extinction events and progressive clonal size divergence, even after the acquisition of a malignant phenotype. Computational modelling suggests these dynamics as the consequence of a clonal-based cell-cell competition. Bulk and single-cell transcriptome analyses, coupled to lineage tracing, revealed that the strongest correlation with clonal size unbalancing is shown by Myc transcriptional targets. Additionally, higher levels of Myc signalling discriminate "winner" from "loser" clones in early gliomagenesis. These results agree with recent understanding of the Myc-mediated induction of supercompetitive phenotype in mammalian embryo. Our findings shed light on aspects of glioblastoma evolution inaccessible by conventional retrospective approaches and highlight the potential of the combined use of clonal tracing and transcriptomic analyses in this field.
2023-07-18 | GSE189517 | GEO
Project description:The interplay between phenotypic plasticity and adaptive evolution has long been an important topic of evolutionary biology. This process is critical to our understanding of a species evolutionary potential in light of rapid climate changes. Despite recent theoretical work, empirical studies of natural populations, especially in marine invertebrates, are scarce. In this study, we investigated the relationship between adaptive divergence and plasticity by integrating genetic and phenotypic variation in Pacific oysters from its natural range in China. Genome resequencing of 371 oysters revealed unexpected fine-scale genetic structure that is largely consistent with phenotypic divergence in growth, physiology, thermal tolerance and gene expression across environmental gradient. These findings suggest that selection and local adaptation are pervasive and together with limited gene flow shape adaptive divergence. Plasticity in gene expression is positively correlated with evolved divergence, indicating that plasticity is adaptive and likely favored by selection in organisms facing dynamic environments such as oysters. Divergence in heat response and tolerance implies that the evolutionary potential to a warming climate differs among oyster populations. We suggest that trade-offs in energy allocation are important to adaptive divergence with acetylation playing a role in energy depression under thermal stress.
2018-07-27 | PXD008057 | Pride
Project description:Clinical study participation percentages haven’t always been fully representative of a given demographic.
Participation in this observational clinical research is extremely valuable since it allows people with colorectal cancer to contribute their own experiences and unique viewpoints.
These vital contributions have the potential to affect the development of novel therapies and support services dramatically.
Trial’s findings will be critical in furthering the understanding of colorectal cancer, ultimately leading to better patient outcomes.
| 62516 | ecrin-mdr-crc
Project description:Physiologically based modelling using DEBtox (dynamic energy budget in toxicology) and transcriptional profiling were used in Caenorhabditis elegans to identify how physiological modes of action, as indicated by effects on system level resource allocation were associated with changes in gene expression following exposure to fluoranthene (FA). DEBtox modelling showed an effect of FA on costs for growth and reproduction (i.e. for production of new and differentiated biomass). The microarray analysis supported this effect, showing an effect of FA on protein integrity and turnover that would be expected to have consequences for rates of somatic growth. Our results have established that outputs from process based models and transcriptomics analyses can help to link mechanisms of action of toxic chemicals with resulting demographic effects. Such complimentary analyses can assist in the categorisation of chemicals for risk assessment purposes.
2010-03-23 | GSE21011 | GEO
Project description:Background RNA sequencing (RNA-seq) is a powerful technique for identifying and quantifying transcription and splicing events, both known and novel. However, given its recent development and the proliferation of library construction methods, understanding the bias it introduces is incomplete but critical to realizing its value. Results Here we present a method, in vitro transcription sequencing (IVT-seq), for identifying and assessing the technical biases in RNA-seq library generation and sequencing at scale. We created a pool of > 1000 in vitro transcribed (IVT) RNAs from a full-length human cDNA library and sequenced them with poly-A and total RNA-seq, the most common protocols. Because each cDNA is full length and we show IVT is incredibly processive, each base in each transcript should be equivalently represented. However, with common RNA-seq applications and platforms, we find ~50% of transcripts have > 2-fold and ~10% have > 10-fold differences in within-transcript sequence coverage. Strikingly, we also find > 6% of transcripts have regions of high, unpredictable sequencing coverage, where the same transcript varies dramatically in coverage between samples, confounding accurate determination of their expression. To get at causal factors, we used a combination of experimental and computational approaches to show that rRNA depletion is responsible for the most significant variability in coverage and that several sequence determinants also strongly influence representation. Conclusions In sum, these results show the utility of IVT-seq in promoting better understanding of bias introduced by RNA-seq and suggest caution in its interpretation. Furthermore, we find that rRNA-depletion is responsible for substantial, unappreciated biases in coverage. Perhaps most importantly, these coverage biases introduced during library preparation suggest exon level expression analysis may be inadvisable. 5 rRNA-depleted samples with duplicates, 1 polyA selected, 1 total RNA, and 1 plasmid library all without replicates.
2014-05-21 | E-GEOD-50445 | biostudies-arrayexpress
Project description:Transposon screens are powerful in vivo assays used to identify loci driving carcinogenesis. These loci are identified as Common Insertion Sites (CIS), i.e. regions with more transposon insertions than expected by chance. However, the identification of CIS is strongly affected by biases in the insertion behaviour of transposon systems. Here, we introduce Transmicron, a novel method that differs from previous methods by i) modelling neutral insertion rates based on chromatin accessibility, transcriptional activity, and sequence context, and ii) estimating oncogenic selection for each genomic region using Poisson regression to model insertion counts while controlling for neutral insertion rates. To assess the benefits of our approach, we generated a dataset applying two different transposon systems under comparable conditions. Benchmarking for enrichment of known cancer genes showed improved performance of Transmicron against state-of-the-art methods. Modelling neutral insertion rates allowed for better control of false positives and stronger agreement of the results between transposon systems. Moreover, using Poisson regression to consider intra-sample and inter-sample information proved beneficial in small and moderately-sized datasets. Transmicron is open-source and freely available. Overall, this study contributes to the understanding of transposon biology and introduces a novel approach to use this knowledge for discovering cancer driver genes.
2022-10-01 | GSE214379 | GEO