Project description:CTCF ChIP-seq of 39 primary samples derived from human acute leukemias, namely AML, T-ALL and mixed myeloid/lymphoid leukemias with CpG Island Methylator Phenotype (CIMP). 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); EGAD00001011059 (dataset).
Project description:Following fertilization, the new embryo reprograms parental genomes to begin transcription (embryonic genome activation, EGA). EGA is indispensable for development, but its dynamics, profile or when it initiates in vertebrates are unknown. We here characterize the onset of transcription in mouse one-cell embryos. Precise embryo staging eliminated noise to reveal a cascading program of de novo transcription initiating within six hours of fertilization. This immediate EGA (iEGA) utilized canonical promoters, produced spliced transcripts, was distinctive and predominantly driven by the maternal genome. Expression represented pathways not only associated with embryo development but with cancer. In human one-cell embryos, hundreds of genes were up-regulated, days earlier than thought, with conservation to mouse iEGA. These findings provide a functional basis for epigenetic analysis in early-stage embryos and illuminate networks governing totipotency and other cell-fate transitions.
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.
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.
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.
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).
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.
Project description:This is a dataset generated by the Drosophila Regulatory Elements modENCODE Project led by Kevin P. White at the University of Chicago. It contains genome-wide binding profile of the factor sc from E0-12 generated by ChIP and analyzed on Illumina Genome Analyzer. For data usage terms and conditions, please refer to http://www.genome.gov/27528022 and http://www.genome.gov/Pages/Research/ENCODE/ENCODEDataReleasePolicyFinal2008.pdf A validated dataset is comprised of three biological replicates for ChIP-chip experiments and two replicates for ChIP-seq and meet the modENCODE quality standards. The control sample is the chromatin Input used for ChIP. Most factors binding profiles are generated by using specific antibodies for the protein of interest. However, some factors have been tagged by GFP in a transgenic line. In that case, ChIP is generated using an anti-GFP antibody. This submission represents the ChIP-seq component of the study.
Project description:This is a dataset generated by the Drosophila Regulatory Elements modENCODE Project led by Kevin P. White at the University of Chicago. It contains genome-wide binding profile of the factor sc from E0-8 generated by ChIP and analyzed on Illumina Genome Analyzer. For data usage terms and conditions, please refer to http://www.genome.gov/27528022 and http://www.genome.gov/Pages/Research/ENCODE/ENCODEDataReleasePolicyFinal2008.pdf A validated dataset is comprised of three biological replicates for ChIP-chip experiments and two replicates for ChIP-seq and meet the modENCODE quality standards. The control sample is the chromatin Input used for ChIP. Most factors binding profiles are generated by using specific antibodies for the protein of interest. However, some factors have been tagged by GFP in a transgenic line. In that case, ChIP is generated using an anti-GFP antibody. This submission represents the ChIP-seq component of the study.