12302 results for "cancer rna-seq"

in 80.03 milliseconds.

• Deciphering Maternal-Fetal Crosstalk in the Human Placenta During Parturition Using Single-Cell RNA-Sequencing

  Labor is a complex physiological process requiring a well-orchestrated dialogue between the mother and fetus. However, the cellular contributions and communications that facilitate maternal-fetal crosstalk in labor have not been fully elucidated. In this latest version (#5), scRNA-seq was applied to decipher maternal-fetal signaling in the human placenta and chorioamniotic membranes during term labor. Samples were obtained from women who underwent spontaneous labor (n = 24) or who were delivered in the absence of spontaneous labor (n = 18) at term. Samples from previous versions (#1-3) of this study include the placental villous tree, basal plate, and chorioamniotic membranes of women across a range of pregnancy physiologic and pathologic conditions, including the processes of labor (term labor and preterm labor), and COVID-19 (version #3). Version #4 includes samples from the human myometrium during spontaneous term labor.

  Study phs001886

• Medulloblastoma exome sequence analysis

  Medulloblastomas are the most common malignant brain tumors in children. Identifying and understanding the genetic events that drive these tumors is critical for the development of more effective diagnostic, prognostic and therapeutic strategies. Recently, our group and others described distinct molecular subtypes of medulloblastoma based on transcriptional and copy number profiles. Here, we utilized whole exome hybrid capture and Illumina sequencing to identify somatic mutations across the coding regions of 92 primary medulloblastoma/normal pairs. Overall, medulloblastomas exhibit low mutation rates consistent with other pediatric tumors, with a median of 0.35 non-silent mutations per megabase. We identified twelve genes mutated at statistically significant frequencies, including previously known mutated genes in medulloblastoma such as CTNNB1, PTCH1, MLL2, SMARCA4 and TP53. Recurrent somatic mutations were identified in an RNA helicase gene, DDX3X, often concurrent with CTNNB1 mutations, and in the nuclear co-repressor (N-CoR) complex genes GPS2, BCOR, and LDB1, to our knowledge novel findings in medulloblastoma and all cancer. We show that mutant DDX3X potentiates transactivation of a TCF promoter and enhances cell viability in combination with mutant but not wild type beta-catenin. Together, our study reveals the alteration of Wnt, Hedgehog, histone methyltransferase and now N-CoR pathways across medulloblastomas and nominates the RNA helicase DDX3X as a component of pathogenic beta-catenin signaling in medulloblastoma. "Reprinted from 'MEDULLOBLASTOMA EXOME SEQUENCING UNCOVERS SUBTYPE-SPECIFIC SOMATIC MUTATION', with permission from Nature"

  Study phs000504

• A novel orthotopic patient-derived xenograft model of radiation-induced glioma following medulloblastoma

  Radiation-induced glioma (RIG) is a highly aggressive brain cancer arising as a consequence of radiation therapy. We report a case of RIG that arose in the brain stem following treatment for paediatric medulloblastoma, and the development and characterisation of a matched orthotopic patient-derived xenograft (PDX) model (TK-RIG915). Patient and PDX tumours were analysed using DNA methylation profiling, whole genome sequencing (WGS) and RNA sequencing. While initially thought to be a diffuse intrinsic pontine glioma (DIPG) based on disease location, results from methylation profiling and WGS were not consistent with this diagnosis. Furthermore, clustering analyses based on RNA expression suggested the tumours were distinct from primary DIPG. Additional gene expression analysis demonstrated concordance with a published RIG expression profile. Multiple genetic alterations that enhance PI3K/AKT and Ras/Raf/MEK/ERK signalling were discovered in TK-RIG915 including an activating mutation in PIK3CA, upregulation of PDGFRA and AKT2, inactivating mutations in NF1, and a gain-of-function mutation in PTPN11. Additionally, deletion of CDKN2A/B, increased IDH1 expression, and decreased ARID1A expression were observed. Detection of phospho-S6, -4EBP1 and -ERK via immunohistochemistry confirmed PI3K pathway and ERK activation. Here, we report one of the first PDX models for RIG, which recapitulates the patient disease and is molecularly distinct from primary brain stem glioma. Genetic interrogation of this model has enabled the identification of potential therapeutic vulnerabilities in this currently incurable disease.

  Study EGAS00001004709

• Stem-like peripheral helper T cells seed their effector counterpart in rheumatoid arthritis

  The dynamics of helper T cells in the synovium of rheumatoid arthritis was investigated using scRNA-seq, scTCR-seq, and spatial transcriptome.

  Study JGAS000774

• Immune Landscape of Cervical Lymph Nodes in Multiple Sclerosis

  This study aimed to investigate the cellular compartment of deep cervical lymph nodes (dcLNs) during early MS before the influence of immunosuppressive treatments. We used ultrasound-guided FNAs followed by scRNA-seq,CITE-seq, TCR and BCR seq to characterize the immune landscape in MS patients compared to controls within the dcLNs.

  Study EGAS50000000843

• BLUEPRINT EpiVar ChIP-seq of Monocytes & Neutrophils

  BLUEPRINT EpiVar ChIP-seq of Monocytes & Neutrophils

  Study EGAS00001000870

• Osteosarcoma mate-pair and RNA-sequencing

  DNA mate pair and RNA sequencing data of conventional osteosarcomas. Mate pair libraries, with average insert sizes of 2-4 kb, were prepared for sequencing using the Nextera Mate Pair Library Preparation Kit. Paired-end 76 base pair reads were generated using an Illumina NextSeq 500 sequencing instrument. Total RNA was enriched for polyadenylated RNA using magnetic oligo(dT) beads. Enriched RNA was prepared for sequencing using the TruSeq RNA Sample Preparation Kit v2 and paired-end 151 base pair reads were generated from the cDNA libraries using an Illumina NextSeq 500 instrument.

  Study EGAS00001003842

• Reference epigenome Islet-derived_iPSC04 h3k4me1 ChIP-Seq data generated from KEP study

  Islet-derived_iPSC04 h3k4me1 ChIP-Seq paired end data

  Dataset EGAD00001007891

• Reference epigenome Islet-derived_iPSC04 h3k27ac ChIP-Seq data generated from KEP study

  Islet-derived_iPSC04 h3k27ac ChIP-Seq paired end data

  Dataset EGAD00001007888

• Reference epigenome Islet-derived_iPSC04 h3k27me3 ChIP-Seq data generated from KEP study

  Islet-derived_iPSC04 h3k27me3 ChIP-Seq paired end data

  Dataset EGAD00001007889

• Reference epigenome Islet-derived_iPSC04 h3k36me3 ChIP-Seq data generated from KEP study

  Islet-derived_iPSC04 h3k36me3 ChIP-Seq paired end data

  Dataset EGAD00001007890

• Reference epigenome Islet-derived_iPSC04 h3k4me3 ChIP-Seq data generated from KEP study

  Islet-derived_iPSC04 h3k4me3 ChIP-Seq paired end data

  Dataset EGAD00001007892

• Reference epigenome Islet-derived_iPSC04 h3k9me3 ChIP-Seq data generated from KEP study

  Islet-derived_iPSC04 h3k9me3 ChIP-Seq paired end data

  Dataset EGAD00001007893

• Reference epigenome Islet-derived_iPSC04 input ChIP-Seq data generated from KEP study

  Islet-derived_iPSC04 input ChIP-Seq paired end data

  Dataset EGAD00001007894

• Reference epigenome Islet-derived_MSC06 h3k27ac ChIP-Seq data generated from KEP study

  Islet-derived_MSC06 h3k27ac ChIP-Seq paired end data

  Dataset EGAD00001007895

• Reference epigenome Islet-derived_MSC06 h3k27me3 ChIP-Seq data generated from KEP study

  Islet-derived_MSC06 h3k27me3 ChIP-Seq paired end data

  Dataset EGAD00001007896

• Reference epigenome Islet-derived_MSC06 h3k36me3 ChIP-Seq data generated from KEP study

  Islet-derived_MSC06 h3k36me3 ChIP-Seq paired end data

  Dataset EGAD00001007897

• Reference epigenome Islet-derived_MSC06 h3k4me1 ChIP-Seq data generated from KEP study

  Islet-derived_MSC06 h3k4me1 ChIP-Seq paired end data

  Dataset EGAD00001007898

• Reference epigenome Islet-derived_MSC06 h3k4me3 ChIP-Seq data generated from KEP study

  Islet-derived_MSC06 h3k4me3 ChIP-Seq paired end data

  Dataset EGAD00001007899

• Reference epigenome Islet-derived_MSC06 h3k9me3 ChIP-Seq data generated from KEP study

  Islet-derived_MSC06 h3k9me3 ChIP-Seq paired end data

  Dataset EGAD00001007900

• Reference epigenome Islet-derived_MSC06 input ChIP-Seq data generated from KEP study

  Islet-derived_MSC06 input ChIP-Seq paired end data

  Dataset EGAD00001007901

• Reference epigenome Islet-derived_MSC08 h3k27ac ChIP-Seq data generated from KEP study

  Islet-derived_MSC08 h3k27ac ChIP-Seq paired end data

  Dataset EGAD00001007902

• Reference epigenome Islet-derived_MSC08 h3k27me3 ChIP-Seq data generated from KEP study

  Islet-derived_MSC08 h3k27me3 ChIP-Seq paired end data

  Dataset EGAD00001007903

• Reference epigenome Islet-derived_MSC08 h3k36me3 ChIP-Seq data generated from KEP study

  Islet-derived_MSC08 h3k36me3 ChIP-Seq paired end data

  Dataset EGAD00001007904

• Reference epigenome Islet-derived_MSC08 h3k4me1 ChIP-Seq data generated from KEP study

  Islet-derived_MSC08 h3k4me1 ChIP-Seq paired end data

  Dataset EGAD00001007905

• Reference epigenome Islet-derived_MSC08 h3k4me3 ChIP-Seq data generated from KEP study

  Islet-derived_MSC08 h3k4me3 ChIP-Seq paired end data

  Dataset EGAD00001007906

• Reference epigenome Islet-derived_MSC08 h3k9me3 ChIP-Seq data generated from KEP study

  Islet-derived_MSC08 h3k9me3 ChIP-Seq paired end data

  Dataset EGAD00001007907

• Reference epigenome Islet-derived_MSC08 input ChIP-Seq data generated from KEP study

  Islet-derived_MSC08 input ChIP-Seq paired end data

  Dataset EGAD00001007908

• STAG1 and STAG2-ChIP-seq in RAD21-mutant adult acute myeloid leukemia

  STAG1 and STAG2-ChIP-seq in RAD21-mutant adult acute myeloid leukemia

  Dataset EGAD00001015361

• SF11964 snATAC Seq Low Grade Astrocytoma IDHR132H mutant

  Single Nuclei ATAC Seq IDHR132H mutant Astrocytoma . Male, 64. Single Nuclei ATAC seq data from low grade human glioma sample. NovaSeq6000 was used for ATAC seq. The files uploaded are bam files created with grch38 reference.

  Dataset EGAD00001005414

• Myeloid-specific KDM6B inhibition sensitizes Glioblastoma to PD1 blockade

  This data set include FASTQ files for five experiments: Human scRNA-Seq data (6 samples), Human Visium spatial transcriptomic data (3 samples), Mouse scRNA-seq data (4 samples), Mouse scATAC-seq data (2 samples), Mouse ChIP-seq data (8 samples). For the mouse scATAC-seq data (2 samples), there are originally three FASTQ files, R1, R2 and R3 files. The R1 and R2 FASTQ files were merged into one larger file ("R1R2") per sample for submission as paired-end sequencing setting to follow the EGA guidelines. They can be split into individual R1 and R2 files in order to be processed by Cell Ranger software. The files with IC1 suffix are CHIP-seq Input control for anti-KDM6B antibody pull down experiments and the files with IC2 suffix are CHIP-seq Input control for anti-H3K27ME3 antibody pull down experiments in murine model.

  Dataset EGAD00001010073

• BLUEPRINT EpiVar ChIP-seq for naive CD4+ T-cells

  BLUEPRINT EpiVar ChIP-seq for naive CD4+ T-cells

  Study EGAS00001000753

• Mediator ChIP-Seq datasets in human islets

  6 ChIP-Seq datasets of Mediator in human pancreatic islets from 6 donors

  Dataset EGAD00001005202

• Cohesin ChIP-Seq datasets in human islets

  3 ChIP-Seq datasets of Cohesin in human pancreatic islets from 3 donors

  Dataset EGAD00001005203

• RNA, ATAC, ChIP datasets from Ankylosing Spondylitis patients and Healthy Controls

  This dataset consists of functional genomic data from 20 Ankylosing Spondylitis patients and 35 Healthy Controls taken from CD4+ T cells, CD8+ T cells and CD14 Monocytes. It contains 364 paired end fastq files consisting of 104 total RNA-seq samples and 116 ATAC samples, for ChIP there are 46 H3K4me3 samples, 46 H3K27ac samples and 3 H3K4me1 samples, along with 49 paired input samples. The samples were sequenced on Illumina HiSeq4000, Illumina NextSeq500 and Illumina NovaSeq 6000 platforms.

  Dataset EGAD00001008758

• Whole genome landscape of adult T-cell leukemia/lymphoma

  Whole-genome sequence (WGS) data of tumor-normal pairs from 139 ATL patients and RNA sequence (RNA-seq) data of tumors from 28 ATL patients.

  Dataset EGAD00001008289

• scRNAseq of colonic organoids derived from biopsies taken from healthy human individuals treated with IL22

  scRNAseq dataset of colonic organoids derived from epithelium from biopsies taken from three healthy human individuals. The organoids have either been grown in standard conditions (control) or treated with IL22 (treated). Includes 6 samples in total, one control from each individual (ctrl1, ctrl2, ctrl3) and one treated from each (treat1, treat2, treat3). The samples have been multiplexed using the antibody hashing technique. The 6 samples have been pooled into the one organoids sample. In order to analyse the raw files, they have to be demultiplexed first. Information necessary for demultiplexing, as well as which files belong to which sample, can be found in the map_file.csv, attached to each sample. Dataset includes raw Fastq files and processed csv count matrices. Fastq files are divided into HTO (hashtag) and RNA (transcriptome) files. HTO has one index (I1) and two read (R1, R2) files and RNA has two index (I1, I2) and two read (R1, R2) files. The fastq files are for the pooled (organoids) sample and need to be demultiplexed. Count matrices contain comma-separated values with cell barcodes as column names and gene names as row names. Since count matrices have been created after the demultiplexing step, there’s one matrix for each of the 6 individual samples. scRNA-seq data from human colon organoids was analysed in the same manner as for the Colitis dataset, apart from the following changes. Data was generated with the Cell Hashing technique, which uses oligo-tagged antibodies against surface proteins to barcode single cells. This allows for samples to be multiplexed together and run in a single experiment. The data was demultiplexed using the HTODemux() function from Seurat (Hao et al., 2021).

  Dataset EGAD00001010168

• Reference epigenome SMC05_ChIP-Seq(H3K27me3) data generated from KEP study

  A SMC05_ChIP-Seq(H3K27me3) paired end data for skeletal muscle cells

  Dataset EGAD00001003849

• Reference epigenome SMC06_ChIP-Seq(H3K27me3) data generated from KEP study

  A SMC06_ChIP-Seq(H3K27me3) paired end data for skeletal muscle cells

  Dataset EGAD00001003850

• Reference epigenome SMC01_ChIP-Seq(H3K27me3) data generated from KEP study

  A SMC01_ChIP-Seq(H3K27me3) paired end data for skeletal muscle cells

  Dataset EGAD00001003845

• Reference epigenome SMC02_ChIP-Seq(H3K27me3) data generated from KEP study

  A SMC02_ChIP-Seq(H3K27me3) paired end data for skeletal muscle cells

  Dataset EGAD00001003846

• Reference epigenome SMC03_ChIP-Seq(H3K27me3) data generated from KEP study

  A SMC03_ChIP-Seq(H3K27me3) paired end data for skeletal muscle cells

  Dataset EGAD00001003847

• Reference epigenome SMC04_ChIP-Seq(H3K27me3) data generated from KEP study

  A SMC04_ChIP-Seq(H3K27me3) paired end data for skeletal muscle cells

  Dataset EGAD00001003848

• Reference epigenome SMC07_ChIP-Seq(H3K27me3) data generated from KEP study

  A SMC07_ChIP-Seq(H3K27me3) paired end data for skeletal muscle cells

  Dataset EGAD00001003851

• Reference epigenome SMC08_ChIP-Seq(H3K27me3) data generated from KEP study

  A SMC08_ChIP-Seq(H3K27me3) paired end data for skeletal muscle cells

  Dataset EGAD00001003852

• Reference epigenome SMC09_ChIP-Seq(H3K27me3) data generated from KEP study

  A SMC09_ChIP-Seq(H3K27me3) paired end data for skeletal muscle cells

  Dataset EGAD00001003853

• STAG2-ChIP-Seq of STAG2-mutated and cohesin-wildtype adult AMLs

  ChIP-Seq targeting the cohesin subunit STAG2 in STAG2-mutant or cohesin wildtype adult AMLs.

  Dataset EGAD00001011205

• Integrated Analysis of Multimodal Single-Cell Datasets for SARS-CoV-2 Vaccination

  The study aimed to explore immune responses during a time course of BNT162b2 mRNA vaccination. To better characterize these responses, we utilize a suite of multi-modal single-cell sequencing technologies to identify and characterize antigen-specific CD8+ T cells. We leverage an integrative analysis strategy to characterize five molecular modalities in these cells. Our dataset enables the discovery of new subpopulations, molecular signatures, and developmental regulators of these cells. Moreover, we identify these cells in SARS-CoV-2 infected patients and demonstrate their positive predictive value for subsequent clinical recovery. The sequence data of CITE-seq, ASAP-seq and ECCITE-seq experiments are deposited in dbGaP. Peripheral blood mononuclear cell (PBMC) samples for CITE-seq and ASAP-seq were collected from six healthy donors at four time points: immediately before (Day 0) vaccination, after primary vaccination (Day 2, Day 10), and seven days after boost vaccination (Day 28). PBMC samples for ECCITE-seq were collected from eight healthy donors on Day 28.

  Study phs003322

• BLUEPRINT Bisulfite-seq and Whole Genome Sequencing of mantle cell lymphoma

  Bisulfite-seq and Whole Genome Sequencing of mantle cell lymphoma

  Study EGAS00001001638

• Bolleboom-Gao peri-tumoral snRNA-seq glioblastoma dataset 2022/A

  Bolleboom-Gao peri-tumoral snRNA-seq glioblastoma dataset 2022/A

  Study EGAS00001006935

• CPC-GENE H3K27ac ChIP-seq

  CPC-GENE H3K27ac ChIP-seq data comprises 48 tumour samples and 6 benign samples sequenced with single end Illumina HiSeq 2000.

  Dataset EGAD00001010296

• CTCF-ChIP-Seq of cohesin-mutated and wildtype adult AMLs

  ChIP-Seq targeting CTCF in cohesin-mutated (STAG2 or RAD21 mutations) and wildtype adult AMLs (CTRL-AMLs).

  Dataset EGAD00001011200

• Gene regulation of human CD4+ Treg ChM-seq

  This dataset maps gene expression regulation in human primary regulatory CD4+ T cells (Tregs). It includes whole genome sequence data for ChM-seq (118 H3K4me3, 118 H3K27ac and 6 inputs). The final quality filtered set included 91 individuals with H3K27ac ChM-seq and 88 with H3K4me3 ChM-seq.

  Dataset EGAD00001004828

• ChIP-seq fastq and alignment files

  ChIP-seq experiments: fastq files; both ChIP and Input for each sample. Illumina HiSeq 2500. ChIP-seq alignment files for trimmed, mapping q20 and nonredundant reads; both ChIP and Input for each sample. Software: Trim Galore v0.3.7; Bowtie 2 v2.1.0; samtools v1.7

  Dataset EGAD00001006279

• Plasma RNA sequencing

  Plasma RNA sequencing

  Study EGAS00001000731

• Single Chromatin Fiber Profiling in the Human Brain

  We developed a human postmortem brain-applicable ‘Fiber-seq' protocol for genome-scale, PCR-free single molecule sequencing of on average 8-10kb long chromatin fibers, to map nucleosome positioning and nucleosome-depleted regions which include, for example, active promoters and enhancers. We generated two Fiber-seq reference sets, one from sorted non-neuronal NeuN- prefrontal cortex (PFC) nuclei from a 32 year old female donor, with total of 11,143,795 reads/fibers, and median of 30-fold genomic coverage. The other reference set was generated on sorted prefrontal NeuN+ neurons, from two 24 year old brain donors (1 female/1 male), with a combined total read/fiber count of 4,749,556 and median of 20-fold genomic coverage. Each of the peaks in the Fiber-seq libraries seq signal correlated with the ATAC peak levels in the neuronal and non-neuronal ATAC-seq libraries, respectively (promoters, clusters 1, 3; NeuN+, r = 0.574; NeuN-, r=0.683, PHowever, Fiber-seq detected 19,978 highly significant peaks which, while showing some non-significant/near-background ATAC-Seq alignments, lacked a corresponding site-specific enrichment in conventional short-read ATAC- and ChIP-seq datasets. However, 60% of these peaks were in repetitive DNA elements. Therefore, long read single chromatin fiber sequencing, which exceed the base pair length of conventional short-read libraries by two orders of magnitude, could capture many actively regulated repeat elements at the site of specific gene loci, that otherwise would remain unmappable by conventional ATAC-, and histone- ChiP-seq.

  Study phs003771

• ChIP-seq for G3-MB

  ChIP-seq for H3K27ac and NeuroD1 in Group 3 Medulloblastoma cell models. Input DNA for each sample and target is also included.

  Dataset EGAD50000002303

• Reference epigenome ADMSC01_ChIP-Seq(H3K27me3) data generated from KEP study

  A ADMSC01_ChIP-Seq(H3K27me3) paired end data for adipose-derived mesenchymal stroaml cells

  Dataset EGAD00001003854

• Reference epigenome ADMSC02_ChIP-Seq(H3K27me3) data generated from KEP study

  A ADMSC02_ChIP-Seq(H3K27me3) paired end data for adipose-derived mesenchymal stroaml cells

  Dataset EGAD00001003855

• Reference epigenome ADMSC03_ChIP-Seq(H3K27me3) data generated from KEP study

  A ADMSC03_ChIP-Seq(H3K27me3) paired end data for adipose-derived mesenchymal stroaml cells

  Dataset EGAD00001003856

• Reference epigenome ADMSC04_ChIP-Seq(H3K27me3) data generated from KEP study

  A ADMSC04_ChIP-Seq(H3K27me3) paired end data for adipose-derived mesenchymal stroaml cells

  Dataset EGAD00001003857

• RNA Splicing Dysregulation in the Pathogenesis of Chronic Lymphocytic Leukemia

  RNA splicing dysregulation is a hallmark of cancers, promoting the onset and progression of disease. In chronic lymphocytic leukemia (CLL), spliceosome mutations leading to aberrant splicing occurs in approximately 20% of patients. However, the underlying mechanism for splicing defects in spliceosome unmutated CLL cases remains elusive. To discover posttranscriptional regulation of RNA splicing, we performed RNA sequencing using RNA derived from B cells from 6 healthy donors and 36 CLL patients, along with MAZTER sequencing from 9 CLL patients (8 matched with RNA sequencing cohort) and B cells from 5 healthy donors. We found that CLL cells have dysregulated m6A modification sites on transcripts from splicing factors, suggesting a critical role of m6A modification in RNA splicing dysregulation.

  Study phs003191

• RNA-seq of MPNSTs

  Malignant Peripheral Nerve Sheath Tumors (MPNSTs) are highly aggressive soft-tissue sarcomas with a poor prognosis and a lack of therapeutic options. In this study, we analyse the whole-transcriptome MPNST and combine them with WGS data from a partially overlapping sample set. These analyses and the inclusion of another public dataset allow us to identify three genomic MPNST subgroups with distinct biological and clinicopathological features that can inform management and precision treatments. Published in "Identification of Malignant Peripheral Nerve Sheath Tumor (MPNST) subtypes with distinct genomic identities."

  Study EGAS50000001733

• Long read mRNA sequencing of human neural retinal samples - Usher syndrome transcript landscape

  Long-read (PacBio) RNA sequencing dataset of three neural retinal samples. Three PacBio libraries were prepared according the 'standard workflow' optimized for sequencing transcripts centered around 2kb. Additionally one Library (input HNR_S2) was prepared according an optimized 'long workflow' to enrich for larger transcripts up to >10kb. To further enhance the capture of full-length transcripts for USH2A and ADGRV1 (USH2C) genes, we also employed a targeted enrichment approach using the Samplix Xdrop System, followed by PacBio long-read sequencing. USH2A and ADGRV1 enrichment was performed by targeting '5- mid and 3' targets of the respective genes. Finally, we also added ONT (Oxford Nanopore technology) long-read mRNA sequencing of three independent neural retina samples. These data were used for the validation of events observed from the Iso-Seq and Samplix data. The ONT datasets contain sequencing data of the Usher-associated genes. Files are raw BAM, and CRAM format files generated by a Sequel II machine. Additionally, the ccs3 BAM format files are included.

  Dataset EGAD50000000720

• Single Cell RNAseq at various stages of HiPSCs differentiating toward definitive endoderm and endoderm derived lineages

  When comparing the differentiation capacities of pluripotent stem cell lines that have different genetic backgrounds, batch to batch experimental variablility poses a significant challenge, especially when trying to identify smaller effects. One way to address this issue is to differentiate several different lines in the same culture dish, thereby elimating experimental variation. In addition, it allows researchers to analyze many more lines with less experiments. Parallel single cell RNA-Seq exploits that individual cells are tagged and hence each cell can be reliably assigned to the donor of origin based on the genetic variants it contains. In addition, analyzing the genetic signature of single cells within a differentiating population can reveal differentation stages that are not easily detected in bulk RNAseq data. This data is part of a pre-publication release. For information on the proper use of pre-publication data shared by the Wellcome Trust Sanger Institute (including details of any publication moratoria), please see http://www.sanger.ac.uk/datasharing/

  Dataset EGAD00001005741

• RNAseq of circulating monocytes of familial hypercholesterolaemia (FH) patients before and after treatment, and healthy controls.

  RNAseq of circulating monocytes of familial hypercholesterolaemia (FH) patients before and after treatment, and healthy controls. Please cite original paper: Monocyte and macrophage lipid accumulation results in downregulated type-I interferon responses. Willemsen et al. Frontiers in Cardiovascular Medicine (2022) Familial hypercholesterolemic patients (n=10) and healthy subjects (n=9): the study population, design, and further processing of these human study subjects and their samples have been extensively described (Stiekema et al., 2021). Briefly, untreated FH patients who indicated to start lipid-lowering therapy (statin, PCSK9 antibody, and/or ezetimibe) according to their treating physician were included. The healthy controls were age, sex, and body mass index (BMI) matched with the FH patients. After inclusion, FH patients fasted for at least 9 hours before blood samples were drawn for lipid measurements and monocyte isolation. This was repeated after 12 weeks of lipid-lowering therapy. RNA-seq was performed on circulating monocytes. V1 = visit 1. V2 = visit 2.

  Dataset EGAD00001008967

• Melanoma and Cancer-Associated Fibroblast Short-Term Cultures Derived from Patient Metastases

  The purpose of this study was to obtain tissue specimens derived from patients with melanoma to generate research tools to advance our understanding of the genetics, pathogenesis, and therapeutics of melanoma. Briefly, tissue was obtained from metastatic lesions and used to generate clonal primary cell lines from melanoma cells and fibroblasts from the tumor microenvironment. RNA was extracted from low passage cell lines using Trizol reagent. cDNA libraries were prepared using the TruSeq mRNA sample preparation kit, v2 (Illumina) and sequenced on the HiSeq 2000 platform (Illumina). The submitted files are bam files that contain both unaligned and aligned reads (human genome, build hg19).

  Study phs001115

• Dynamics of tumor ecosystems and microbiome in response to neoadjuvant atezolizumab, bevacizumab, and FOLFOX treatment in patients with unresectable colorectal cancer with liver metastasis

  This study aims to explore the effects of neoadjuvant atezolizumab, bevacizumab, leucovorin, 5-fluorouracil, and oxaliplatin (ABFOLFOX) in patients with unresectable colorectal liver metastases (CRLM), focusing on the molecular dynamics of tumor ecosystems (TE) of CRLM and their impact on treatment outcomes. The study comprises two cohorts with CRLM tissue samples analyzed with RNA sequencing and immunohistochemical staining: cross-sectional cohort A (n = 60, CRLM treated with or without neoadjuvant chemotherapy) and prospective cohort B (n = 20 with serial sampling and treated with ABFOLFOX). Shotgun metagenomic sequencing was done for stool samples from cohort B.

  Study EGAS50000000677

• Chip-Seq sequencing data of Atypical teratoid/rhabdoid tumors (ATRT)

  Chip-Seq sequencing data of Atypical teratoid/rhabdoid tumors (ATRT)

  Dataset EGAD00001003408

• MuTHER_adipose_tissue_small_RNA_expression

  We investigate the naturally occurring variation of small RNA expression in conjunction with genetic and gene expression variation. We shall assess the variation in subabdominal fat tissue small RNA levels in 168 unrelated MuTHER individuals. Using gene expression data from the same samples, we can survey how much the small RNA expression contributes to the variance in gene expression profiles. We can also take advantage of the high density genotyping data on these samples to identify genetic associations of small RNA expression levels, and the downstream effect of the genetic variants in small RNA sequence. Previous small RNA sequencing efforts have also extended the repertoire of small RNAs, and we hope to potentially find additional small RNAs active in adipose tissue biology. Altogether, the project should provide an exciting view into small RNA biology in humans, and lead to development of new methodology for analysis of molecular phenotype data.

  Study EGAS00001000212

• Next generation sequencing of diffuse intrinsic pontine glioma samples to identify recurrent mutations, variations, and expression patterns to define novel therapies

  Diffuse intrinsic pontine glioma (DIPG) is an extremely rare (~350 cases/year) and universally fatal childhood brain cancer. Standard clinical strategies such as chemotherapy and radiotherapy show only transient improvement in patient condition and result in negligible change in survival, DIPG remains at below 1% survival after 5 years. Prioritization of panobinostat through previous cooperative work resulted in a phase 1 clinical trial. Nonetheless, new therapies for DIPG must be identified to further dramatically change the statistics for DIPG. To identify novel therapy strategies for DIPG, we performed whole exome(16 new samples, 22 previously published samples, 38 in total with 26 matched normal) and RNA deep sequencing (17 new samples, 11 previously published samples) on a cohort of new patient samples. Sequencing results aid in the identification of recurrent mutations/variations and endotypic expression profiling to identify new therapeutic and treatment strategies for DIPG.

  Study phs001526

• MP2PRT-MNG: Identifying Novel Molecular Markers of Response to Radiotherapy in Meningiomas Using Samples from the RTOG-0539 (NCT00895622)

  The Molecular Profiling to Predict Response to Treatment (MP2PRT) program is part of the NCI's Cancer Moonshot Initiative. The aim of this program is the retrospective characterization and analysis of biospecimens collected from completed NCI-sponsored trials of the National Clinical Trials Network and the NCI Community Oncology Research Program. NRG RTOG (Radiation Therapy Oncology Group)-0539, which was a nonrandomized phase II cooperative group trial in 2009, was selected for inclusion in this program. NRG RTOG-0539 assigned patients with histologically confirmed diagnosis of meningioma to 1 of 3 risk groups based on 2007 WHO grade, resection extent, and recurrence status, and radiotherapy was given per protocol to the intermediate- and high-risk cases. Under the MP2PRT program, DNA methylation profiling, RNA sequencing, and whole exome sequencing were performed on clinical trial cases with available tissue for molecular analyte extraction and subsequent sequencing. Raw molecular data with metadata are available for this study.

  Study phs003707

• Nivolumab plus chemotherapy or ipilimumab in gastroesophageal cancer: CheckMate 649 biomarker analyses

  First-line nivolumab-plus-chemotherapy demonstrated superior overall survival (OS) versus chemotherapy for advanced gastroesophageal adenocarcinoma (CheckMate 649). Nivolumab-plus-ipilimumab provided durable responses and higher survival rates versus chemotherapy; however, the prespecified OS significance boundary was not met. To identify biomarkers predictive of differential efficacy outcomes, exploratory analyses were performed using whole-exome sequencing and RNA sequencing. Nivolumab-based therapies demonstrated improved efficacy versus chemotherapy in hypermutated and, to a lesser degree, Epstein Bar Virus-positive tumors compared with chromosomally unstable and genomically stable tumors. Within the KRAS-altered subgroup, only patients treated with nivolumab-plus-chemotherapy demonstrated improved OS benefit versus chemotherapy. Low stroma gene expression signature scores were associated with OS benefit with nivolumab-based regimens; high regulatory T-cell signatures were associated with OS benefit only with nivolumab-plus-ipilimumab. Our analyses suggest that distinct and overlapping pathways contribute to the efficacy of nivolumab-based regimens in gastroesophageal adenocarcinoma.

  Study EGAS50000000747

• Epigenomics and Single-cell Sequencing Define a Developmental Hierarchy in Langerhans Cell Histiocytosis

  Langerhans cell histiocytosis (LCH) is a rare neoplasm predominantly affecting children. It occupies a hybrid position between cancers and inflammatory diseases, and it provides an attractive model for studying cancer development. To explore the molecular mechanisms underlying the pathophysiology of LCH and its characteristic clinical heterogeneity, we investigated the transcriptomic and epigenomic diversity in primary LCH lesions. Using single-cell RNA sequencing, we identified multiple recurrent types of LCH cells within these biopsies, including putative LCH progenitor cells and several subsets of differentiated LCH cells. We confirmed the presence of proliferative LCH cells in all analysed biopsies using immunohistochemistry, and we defined an epigenomic and gene-regulatory basis of the different LCH cell subsets by chromatin accessibility profiling. In summary, our single-cell analysis of LCH uncovered an unexpected degree of cellular, transcriptomic, and epigenomic heterogeneity among LCH cells, indicative of complex developmental hierarchies in LCH lesions.

  Study EGAS00001003822

• Comprehensive Genomic and Transcriptomic Analysis of Rare Cancers for Guiding of Therapy (H021)

  Here we analyzed the molecular profiles and clinical outcomes of 1,310 patients (proportion of rare cancers, 75%) enrolled in a prospective observational study by the German Cancer Consortium that applies whole-genome/exome and RNA sequencing to inform the care of adults with incurable cancers. Based on 472 single and six composite biomarkers, a cross-institutional molecular tumor board provided evidence-based management recommendations, including diagnostic reevaluation, genetic counseling, and experimental treatment, in 88% of cases. Recommended therapies were administered in 362 of 1,138 patients (31.8%) and resulted in significantly improved response and disease control rates (23.9% and 55.3%, respectively) compared to previous therapies, translating into a progression-free survival ratio >1.3 in 35.7% of patients.

  Study EGAS00001004813

• The Proteogenomic Subtypes of Acute Myeloid Leukemia

  Acute myeloid leukemia (AML) is an aggressive blood cancer with poor prognosis. We report a comprehensive proteogenomic analysis of bone-marrow biopsies from 252 uniformly treated AML patients to elucidate the molecular pathophysiology of AML in order to inform future diagnostic and therapeutic approaches. In addition to in-depth quantitative proteomics, our analysis includes cytogenetic profiling and DNA/RNA sequencing. We identify five proteomic AML subtypes, each reflecting specific biological features spanning genomic boundaries. Two of these proteomic subtypes correlate with patient outcome, but none are exclusively associated with specific genomic aberrations. Remarkably, one subtype (Mito-AML), which is only captured in the proteome, is characterized by high expression of mitochondrial proteins and confers poor outcome, with reduced remission rate and shorter overall survival upon treatment with intensive induction chemotherapy. Functional analyses reveal that Mito-AML is metabolically wired towards stronger complex I dependent respiration and is more responsive to treatment with the BCL2 inhibitor venetoclax.

  Study EGAS00001005950

• bulk TCR seq

  bulk TCR-seq data IMCISION on the PBMCs of responding patients bulkTCR-seq data generated with the immunoSEQ platform (Adaptive Biotechnologies) on PBMCs of responding patients, pre- and post-treatment.

  Dataset EGAD00010002546

• H3K27ac ChIP-Seq datasets from human islets in low glucose conditions

  7 H3K27ac ChIP-Seq datasets from 7 donors where islets were treated in low (4mM) glucose conditions.

  Dataset EGAD00001005205

• ChIP-seq for AR, FOXA1 and HOXB13 on 8 prostectomy samples

  ChIP-seq for AR, FOXA1 and HOXB13 on 8 prostectomy samples, both regions with/-out tumor cells, Fastq files.

  Dataset EGAD00001005374

• MethylScan data of plasma samples

  10ng from each cfDNA sample was used as the input material. For gDNA samples, 1.5-2ug each was first sonicated by Covaris R230 system (Woburn, MA). Next, size-selection with 0.8x-1.5x two-step Ampure XP beads was performed to enrich the 150-200bp fragments. 200ng of the size-selected gDNA was used as input material. The pre-capture library construction was performed with NEB UltraII DNA library prep kit for Illumina (Ipswich, MA) and the adapter was the methylated EM-seq adapter. Before the first PCR amplification, the gDNA samples were subjected to bisulfite conversion by QIAGEN Epitect kit, and cfDNA samples were subjected to enzymatic conversion by NEBNext enzymatic methyl-seq kit if the hybrid capture panel designed for converted DNA was used downstream. Twist panel hybrid capture was performed with their standard protocol (Twist Bioscience, South San Francisco, CA). The concentration of the post-capture library after the second PCR amplification was measured by Qubit 1xdsDNA HS kit (ThermoFisher, Waltham, MA). Their quality was examined by TBE-UREA PAGE and Bioanalyzer before sequencing. Libraries were then sequenced with 150bp paired-end reads on Illumina machines by Genewiz, Inc. (South Plainfield, NJ, USA). This dataset contains MethylScan data of the plasma samples from 248 noncancer individuals and 27 cancer patients (17 liver and 10 GI-tract cancers).

  Dataset EGAD00001015815

• Altered oligodendrocyte heterogeneity in Multiple sclerosis revealed by single nuclei RNA sequencing

  This study is currently hosted by the European Nucleotide Archive. To access the data contained within the Study please follow the link below: https://www.ebi.ac.uk/ena/browser/view/PRJEB39323 Oligodendrocyte (OL) pathology is increasingly implicated in neurodegenerative diseases, as they are involved in metabolic support of axons and functional cross-talk with other brain cells. Rodent OLs are heterogeneous, with developmental and biological differences, but the extent of heterogeneity in the normal human brain and its contribution to any changes to disease remains unknown. Here we performed single nuclei RNA-sequencing (snRNA-seq) from white matter (WM) areas of post mortem human brain both in control (Ctr) and multiple sclerosis (MS) patients. We identified several sub-clusters of oligodendroglia in the Ctr human WM, some similar to those in mouse, and defined new markers for these cell states. Strikingly, some of these sub-clusters were under-represented in MS tissue, while others were more prevalent than in controls. We found a lack of OL precursor cells (OPCs) and an OL subcluster in an intermediate stage of differentiation in MS lesions and in normal appearing white matter (NAWM), suggesting either depletion by the disease or by a regenerative response. The differences in mature OL sub-clusters indicate different functional states of OLs in MS tissue and, as this is similar in NAWM to lesions, that MS is a more diffuse brain disease than the focal demyelinating lesions suggest. We were also able to identify new putative markers of different MS lesion subtypes. Our findings of an altered heterogeneity of oligodendroglia in MS may have an important contribution to our understanding of disease progression and may alter therapeutic approaches to MS.

  Study EGAS00001003412

• RNA-sequencing of ex situ stimulated donors blood cells

  Cells from whole blood stimulation assay were cryopreserved. The cryopreserved cells were thawed and subjected to RNA preparation. RNA obtained were subjected to for bulk sequencing.

  Study EGAS50000001077

• Transcriptome of CD4+ T cells and CD8+ T cells in glioblastoma multiforme

  Patients included in this study were over 18 years of age and had a histology-confirmed diagnosis of glioblastoma multiforme (GBM). Exclusion criteria were the previous administration of any anti-tumor therapy including radiation therapy. All patients gave written informed consent. The study was approved by the local ethics committee (TUM Medical school) and conducted following the Declaration of Helsinki. During resection of the tumors, tumor tissue and tissue from normal appearing brain within the operative channel was collected. Blood was drawn during the surgical procedure. Single cell suspensions were prepared from the tumor tissue, the normal appearing brain, and the blood. CD4+ T cells and CD8+ T cells were sorted by flow cytometry. Only patients with a complete set of specimens (CD4+ tumor infiltrating lymphocytes (TIL), CD8+ TIL, CD4+ T cells from normal appearing brain, CD8+ T cells from normal appearing brain, blood-derived CD4+ and CD8+ T cells) containing a minimum of 1000 cells in each sorted sample were further analyzed (n=9). Total RNA was isolated from sorted cell populations using the RNAeasy Plus micro kit (Qiagen, 74034). Quality and integrity of total RNA was controlled on a Bioanalyzer 2100 (Agilent Technologies). Library preparation for bulk-sequencing of poly(A)-RNA was done as described previously (Parekh et al., 2016). Briefly, barcoded cDNA of each sample was generated with a Maxima RT polymerase (ThermoFisher Scientific, EP0742) using oligo-dT primer containing barcodes, unique molecular identifiers (UMIs) and an adaptor. Ends of the cDNAs were extended by a template switch oligo (TSO) and full-length cDNA was amplified with primers binding to the TSO-site and the adaptor. NEB UltraII FS kit was used to fragment cDNA. After end repair and A-tailing, a TruSeq adapter was ligated and 3'-end-fragments were finally amplified using primers with Illumina P5 and P7 overhangs. In comparison to previous descriptions (Parekh et al., 2016), the P5 and P7 sites were exchanged to allow sequencing of the cDNA in read 1 and barcodes and UMIs in read 2 to achieve a better cluster recognition. The library was sequenced on a NextSeq 500 (Illumina) with 59 cycles for the cDNA in read 1 and 16 cycles for the barcodes and UMIs in read 2. Data were processed using the published Drop-seq pipeline (v1.0) to generate sample- and gene-wise UMI tables (Macosko et al., 2015). Reference genome (GRCh38) was used for alignment. Transcript and gene definitions were used according to the Genecode Annotation Version 35.

  Study EGAS50000000156

• Integrated clinical, whole genome, and transcriptome analysis of multisampled lethal metastatic prostate cancer

  We report the first combined analysis of whole genome sequence, detailed clinical history, and transcriptome sequence of multiple prostate cancer metastases in a single patient (A21). Whole genome and transcriptome sequence was obtained from 9 anatomically separate metastases, and targeted DNA sequencing was performed in cancerous and noncancerous foci within the primary tumor specimen removed 5 years prior to death. Transcriptome analysis revealed increased expression of AR-regulated genes in liver metastases that harbored an AR p.L702H mutation, suggesting a dominant effect by the mutation despite being present in only 1 of an estimated 16 copies per cell. The metastases harbored several alterations to the PI3K/AKT pathway, including a clonal truncal mutation in PIK3CG and present in all metastatic sites studied. The list of truncal genomic alterations shared by all metastases included homozygous deletion of TP53, hemizygous deletion of RB1 and CHD1, and amplification of FGFR1. If the patient were treated today given this knowledge, use of second-generation androgen-directed therapies, cessation of glucocorticoid administration, and therapeutic inhibition of the PI3K/AKT pathway or FGFR1 receptor could provide personalized benefit. Three previously unreported truncal clonal missense mutations (ABCC4 p.R891L, ALDH9A1 p.W89R, and ASNA1 p.P75R) were expressed at the RNA level and assessed as druggable. The truncal status of mutations is critical for actionability, and can only be determined through analysis of multiple sites of metastasis. Our findings suggest that a large set of deeply analyzed cases could serve as powerful guide to more effective prostate cancer basic science and personalized cancer medicine clinical trials.

  Dataset EGAD00001001869

• Primary Neuroblastoma Circle-seq

  We generated Circle-seq data for primary neuroblastoma to describe the landscape of extrachromosomal circular DNA in neuroblastoma.

  Study EGAS00001004797

• DNMT3A MOPD patient ChIP-seq data

  ChIP-seq data from controls and patients with de novo DNMT3A mutations resulting in microcephalic primordial dwarfism.

  Dataset EGAD00001004473

• RNA sequencing of lung fibroblasts

  RNA sequencing of lung fibroblasts

  Study EGAS00001007857

• scRNA-seq data of human nuclei collected from the temporal cortex of 17 individuals.

  Transcriptome analysis of single cells has tremendously increased our understanding of cellular heterogeneity in complex tissues. However, whole-cell transcriptomics cannot be applied to frozen tissue due to poor cell recovery after freezing. Human tissue is usually limited to tissue banks containing frozen material, and since single nuclei can be readily isolated from frozen tissues, human cell nuclei can substitute whole-cell analysis to extract single cell transcriptomes from human cells. Despite the importance of human tissue analysis, single-nucleus RNA-sequencing protocols are less developed than those for whole cells. SMARTSeq, either in form of custom-made SMARTSeq2 or as part of the Fluidigm C1 platform, provides a high resolution view of the transcriptome, has proven effective for whole-cell analysis and has recently been adapted to nuclei. Here, we show that the standard SMARTSeq2 protocol applied to single nuclei biases the amplification of single-nucleus transcriptomes due to unspecific capturing of transcripts, which can comprise the majority of reads in single-nucleus RNA-sequencing libraries. We demonstrate that modification of the SMARTSeq2 protocol with respect to template switching and cDNA amplification conditions generates sequencing libraries of higher complexity, allows for detection of more genes and reduces biases of the amplified transcriptome. In addition, modification of SMARTSeq2 chemistry allows for gene detection at shallower sequencing depth, thus increasing efficiency and decreasing cost.

  Study EGAS00001002882

• Characterization of genetic intratumor heterogeneity in colorectal cancer and matching patient-derived spheroid cultures.

  Patient-derived in vitro cultures of colorectal cancer (CRC) may help guide treatment strategies prior to patient treatment. However, most previous studies have been performed on a single biopsy per tumor. The purpose of this study was to analyze multiple spatially distinct biopsies from CRCs and see how well intratumor heterogeneity (ITH) was recapitulated in matching patient-derived spheroids. Three to five biopsies were collected from six CRC tumors. Each biopsy was split in two; one half was used for spheroid culturing, the other half was used for direct DNA and RNA purification. For two of the patients, lymph node metastases were analyzed. Somatic mutations were called from whole exome sequencing data. Each tumor contained multiple mutations shared across all biopsies and spheroids, including major CRC drivers such as APC, KRAS, and TP53. At the same time, all tumors exhibited ITH on both mutation and copy number level. The concordance between biopsies and spheroids ranged between 40-70% for coding mutations. For three of the patients the biopsy and spheroid from matching areas clustered together, meaning that the spheroid resembled the area of origin more than the other areas. However, all biopsies and spheroids contained private mutations. Thereby, multiple cultures from spatially distinct sites of the tumor increase the insight into the genetic profile of the entire tumor. RNA sequencing based molecular subtyping was stable and seemed independent of genetic ITH. In conclusion, all examined CRC tumors contained genetic ITH on mutation and copy number level. Spheroid cultures partly reflected this ITH, meaning that multiple cultures from distinct sites of the tumor improved the representation of the different genetic subclones in the primary tumor. This should be taken in to account when establishing patient-derived models for drug screening.

  Study EGAS00001002684

• Simultaneous Trimodal Single Cell Measurement of Transcripts, Epitopes, and Chromatin Accessibility Using TEA-Seq

  Single-cell measurements of cellular characteristics have been instrumental in understanding the heterogeneous pathways that drive differentiation, cellular responses to signals, and human disease. Recent advances have allowed paired capture of protein abundance and transcriptomic state, but a lack of epigenetic information in these assays has left a missing link to gene regulation. Using the heterogeneous mixture of cells in human peripheral blood as a test case, we developed a novel scATAC-seq workflow that increases signal-to-noise and allows paired measurement of cell surface markers and chromatin accessibility: Integrated Cellular Indexing of Chromatin Landscape and Epitopes (ICICLE-seq). We extended this approach using a droplet-based multiomics platform to develop a trimodal assay that simultaneously measures Transcriptomics (scRNA-seq), Epitopes, and chromatin Accessibility (scATAC-seq) from thousands of single cells, which we term TEA-seq. Together, these multimodal single-cell assays provide a novel toolkit to identify type-specific gene regulation and expression grounded in phenotypically defined cell types.

  Study phs002316

• Cell targeted amplification sequencing (cta-seq) of scRNA-seq sample

  This data-set contains two sequencing runs of the same scRNA-seq library. Once with and once without cell targeted amplification of transcripts.

  Dataset EGAD50000001338

• H3K27ac ChIP-seq in Insulinomas

  H3K27ac ChIP-seq datasets in human insulinoma samples

  Dataset EGAD50000000461

• RAD21-ChIP-Seq of cohesin-mutated and wildtpye adult AMLs

  ChIP-Seq targeting the major cohesin core subunit RAD21 to represent cohesin occupancy and binding sites in cohesin-mutated (STA2 or RAD21 mutations) and wildtpye adult AMLs.

  Dataset EGAD00001011199

• Dataset for ChIP-seq data for neuroblastoma tumor samples(NB,Neuroblastoma)

  Dataset for H3K27me3 ChIP-seq data of neuroblastoma tumor samples. The sequencing was performed on Illumina HiSeq 2000 and Illumina HiSeq 2500

  Dataset EGAD00001015813

• H3K27me3 ChIP-Seq of 6 samples and H3K27ac ChIP-Seq of 4 samples with respective input controls

  H3K27me3 ChIP-Seq of 6 samples and H3K27ac ChIP-Seq of 4 samples with respective input controls

  Dataset EGAD00001004992

• Location and Function of NSun2-Mediated Cytosine-5 Methylation in RNA and its Effect on Translation

  Mutations in the cytosine-5 RNA methyltransferase NSun2 can cause neurodevelopmental disorders and symptoms commonly found in patients with Dubowitz-like syndrome. Some tRNAs are known to be methylated NSun2, however the occurrence of cytosine-5 methylation (m5C) in other RNA biotypes is still under debate. Location in RNA and function of m5C has not been studied yet. This study is aimed at identifying new m5C methylated RNA biotypes, as well as the location at specific structures or sequences and the ultimate biological function. The impact of the loss of NSun2-mediated methylation is also determined by comparing gene expression data with the global cytosine-5 RNA methylome in Dubowitz-like syndrome patients. We also use ribosomal profiling to assess the impact of the loss and rescue of Nsun2-mediated cytosine-5 RNA methylation on translation rates and ribosome occupancy.

  Study phs000645

• A Multi-Omic Single-Cell Atlas of Human Gynecological Malignancies

  Matched single-cell transcriptomic sequencing (scRNA-seq) and single-cell chromatin accessibility sequencing (scATAC-seq) were performed for 11 fresh human tumors collected from the endometrium or ovary. More detailed information for each patient tumor will be provided in selected phenotype/attributes data. Both scRNA-seq and scATAC-seq assays revealed the underlying cellular heterogeneity in transcriptional output and in chromatin accessibility for each patient tumor specimen. In this work, we identified potential non-coding regulatory elements that mediate cell type-specific gene expression patterns. These data will serve as an important reference for the single-cell genomics and gynecologic oncology research communities.

  Study phs002340

• Total RNA sequencing of fibroblasts from unmethylated full mutation carrier 1

  Total RNA sequencing of fibroblasts from an individual with a fragile X syndrome related unmethylated full mutation (UFM1). Libraries were prepared with total RNA with Ribo-Zero ribosomal RNA depletion (illumina), and sequenced paired-end, 75bp on a NextSeq 550 system. This dataset contains three RNA-sequencing replicates from the same cell line.

  Dataset EGAD50000000918

• Total RNA sequencing of fibroblasts from an control individual

  Total RNA sequencing of fibroblasts from an individual with 30-55x GCC repeats in the FMR1 5'UTR. Libraries were prepared with total RNA with Ribo-Zero ribosomal RNA depletion (illumina), and sequenced paired-end, 75bp on a NextSeq 550 system. This dataset contains three RNA-sequencing replicates from the same cell line.

  Dataset EGAD50000000922

• Post Mortem brain data used in paper "Significant and pervasive effects of RNA degradation on Nanopore direct RNA sequencing"

  This dataset contains data used in the paper titled "Significant and pervasive effects of RNA degradation on Nanopore direct RNA sequencing. The data consists of one post mortem sample that was sequenced with direct RNA sequencing form Oxford Nanopore Technologies on a promethION flow cell.

  Dataset EGAD00001009308