6691eeee-df0d-4de7-bf07-3ce4713600f6 - samples
Ontology highlight
ABSTRACT:
PROVIDER: EGAD00001008303 | EGA |
REPOSITORIES: EGA
Similar Datasets
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Project description:H3K27ac ChIP-seq of 79 primary samples derived from human acute leukemias, namely AML, T-ALL and mixed myeloid/lymphoid leukemias with CpG Island Methylator Phenotype (CIMP). In addition, 4 samples derived from CD34+ cord blood cells of healthy donors were included. Due to patient confidentiality considerations, the raw data files for this dataset have been deposited to the EGA controlled-access archive under the accession numbers EGAS00001007094 (study); EGAD00001011060 (dataset).
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Project description:Embryonic genome activation (EGA) marks the onset of embryonic program and enables the transition toward the first lineage specification. However, the molecular features of EGA and the transcription factors (TFs) orchestrating this process remain unclear. Here, by performing single-cell RNA-seq on bovine embryos, we reveal that major EGA is asynchronously initiated among blastomeres at the 8-cell stage. Integrative analyses reveal distinctive protein accumulation compared to transcription and translation activation during bovine EGA. Furthermore, we investigate the role of SP1, a TF activated at the minor EGA stage, with motifs enriched in accessible chromatin during major EGA stage in bovine and human embryos. SP1 deficiency leads to morula arrest in bovine and impairs EGA in human embryos. Multi-omics analysis demonstrates that SP1 promotes early lineage gene expression by modulating nearby chromatin states in bovine and directly targets key EGA genes in human embryos. Together, our study delineates the dynamics of bovine EGA and uncovers the conserved and species-specific roles of SP1 in regulating EGA and early development in mammals.
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Project description:Embryonic genome activation (EGA), a pivotal transcriptional event during preimplantation development, is accompanied by post-transcriptional regulation of maternal mRNAs. Disentangling the transcriptional output of the newly activated embryonic genome from concomitant post-transcriptional processing is important for decoding EGA dynamics.Here, using optimized low-input SLAM-seq (thiol(SH)-linked alkylation for the metabolic sequencing) in mouse embryos, we delineates the temporal hierarchy of EGA nascent transcription during mouse preimplantation embryogenesis and uncovers a mechanistic link between EGA and the first lineage specification, providing new insights into the regulatory architecture of early mammalian development.
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Project description:This single cell RNA-seq experiment was performed to quantify DLL3 expression in tumor cells in small cell lung cancer patients.Tumors were rapidly dissociated after the surgical procedure using the Miltenyi Biotec Human Tumor Dissociation kit (cat# 130-095-929). Libraries were constructed using the VDJ NextGEM v1.1 10x Genomics Chromium kit according to the manufacturer's instructions. Samples were sequenced on a NextSeq 550 sequencer (Illumina). Corresponding EGA study number: EGAS50000001400, EGA dataset number: EGAD50000002034.
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Project description:Milk production during the early postpartum in dairy cows can impact the circulating metabolites and negatively affects embryo survival. However, the molecular consequences for the embryo during its development in the oviduct are still unknown. The objective was to determine the impact of metabolic status on embryonic genome activation (EGA) using high-throughput sequencing to generate comprehensive transcriptome profiles of bovine 16-cell stage embryos which had undergone EGA in vitro or in the oviducts of primiparous postpartum dry or postpartum lactating Holstein Friesian cows.
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Project description:In the past decades, the incidence of esophageal adenocarcinoma has increased dramatically in Western populations. Better understanding of disease etiology along with the identification of novel prognostic and predictive biomarkers are urgently needed to improve the dismal survival probabilities. Here, we performed comprehensive RNA (both coding and non-coding) profiling in various samples from 17 patients diagnosed with esophageal adenocarcinoma, high-grade dysplastic or non-dysplastic Barrett’s esophagus. Per patient, a blood plasma sample, and a healthy esophageal and disease tissue sample were included. In total, this comprehensive dataset consists of 102 RNA-seq libraries from 51 samples. The raw data for this study have been deposited to the controlled access archive EGA under submission EGAS00001004939.
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Project description:In the past decades, the incidence of esophageal adenocarcinoma has increased dramatically in Western populations. Better understanding of disease etiology along with the identification of novel prognostic and predictive biomarkers are urgently needed to improve the dismal survival probabilities. Here, we performed comprehensive RNA (both coding and non-coding) profiling in various samples from 17 patients diagnosed with esophageal adenocarcinoma, high-grade dysplastic or non-dysplastic Barrett’s esophagus. Per patient, a blood plasma sample, and a healthy esophageal and disease tissue sample were included. In total, this comprehensive dataset consists of 102 RNA-seq libraries from 51 samples. The raw data for this study have been deposited to the controlled access archive EGA under submission EGAS00001004939.
2022-01-01 | E-MTAB-10005 | biostudies-arrayexpress
Project description:In the past decades, the incidence of esophageal adenocarcinoma has increased dramatically in Western populations. Better understanding of disease etiology along with the identification of novel prognostic and predictive biomarkers are urgently needed to improve the dismal survival probabilities. Here, we performed comprehensive RNA (both coding and non-coding) profiling in various samples from 17 patients diagnosed with esophageal adenocarcinoma, high-grade dysplastic or non-dysplastic Barrett’s esophagus. Per patient, a blood plasma sample, and a healthy esophageal and disease tissue sample were included. In total, this comprehensive dataset consists of 102 RNA-seq libraries from 51 samples. The raw data for this study have been deposited to the controlled access archive EGA under submission EGAS00001004939.
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