3659 results for "RNA AND sequencing OR transcriptome"

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• UMCU_Molpheno_Restricted

  This dataset contains Whole Genome Sequencing and, if available, RNA-sequencing and/or ATAC-sequencing data obtained from PBMCs derived from blood samples of 34 patients with intellectual disability and/or multiple congenital anomalies and their biological parents (58) included in the University Medical Center Utrecht (The Netherlands).

  Dataset EGAD00001004865

• Evolutionary Analysis of Chronic Lymphocytic Leukemia Cells During Relapse After Allogeneic Hematopoietic Stem Cell Transplant

  We investigated the molecular dynamics driving relapse of chronic lymphocytic leukemia (CLL) following allogeneic hematopoietic stem cell transplant (allo-HSCT) through an integrated analysis of whole exome, bulk transcriptome, bulk methylome and single cell transcriptional data from paired leukemic samples representing 19 patients. We found that their clinical kinetics corresponded to distinct genetic and epigenetic evolutionary trajectories and suggest that the selection pressures of the post-transplant, immunologic bottleneck are distinct from those imposed by chemotherapy.In order to discover cancer antigens derived from annotated and unannotated protein-coding regions of the genome, we carried out ribosome profiling (Ribo-seq) and RNA-sequencing on CLL samples and isolated primary B cells from healthy donors. We discovered novel or unannotated open reading frames (nuORFs), their expression levels, as well as somatic mutations within them to predict potential neoantigens.

  Study phs001998

• Identification and characterization of tertiary lymphoid structures in brain metastases

  Brain metastases (BrM) are the most common cancers in the brain. We performed transcriptome-wide gene expression profiling combined with spatial immune cell profiling to characterize the tumor immune microenvironment in BrM from different primary tumors. We found that BrM from lung carcinoma and malignant melanoma showed overall higher immune cell infiltration as compared to BrM from breast carcinoma. RNA sequencing-based immune cell deconvolution revealed gene expression signatures indicative of tertiary lymphoid structures (TLS) in subsets of BrM from lung cancer and melanoma. This finding was corroborated by multiplex immunofluorescence staining of immune cells in BrM tissue sections. Detection of TLS signatures was associated with prolonged survival after BrM diagnosis in lung cancer patients. Our findings highlight the cellular diversity of the tumor immune microenvironment in BrM of different cancer types and suggest a role of TLS formation for BrM patient outcome.

  Study EGAS50000000563

• RNA-seq

  RNA-sequencing data

  Dataset EGAD00010001719

• Identification of the Global miR-130a Targetome Reveals a Novel Role for TBL1XR1 in Hematopoietic Stem Cell Self-Renewal and t(8;21) AML

  In this study, we identified miR-130a as a regulator of HSC self-renewal and differentiation. To characterize gene expression changes following enforced expression of miR-130a OE, we performed RNA-seq in CD34+ cord blood (CB) cells transduced with control and miR-130a OE lentiviruses. To capture miRNA targets in an unbiased, transcriptome-wide manner, we perfomed enhanced CLIPseq procol in 2 replicates of CD34+ CB cells and Kasumi-1 cell line, which represent a model system for t(8;21) AML. We chose this cell line, as we found miR-130a to be highly expressed in this AML subtype where it is critical for maintaining the oncogenic molecular program mediated by AML1-ETO. Chimeric Ago2 eCLIPseq in CD34+ CB cells combined with Mass Spectrometry data analysis identified TBL1XR1 as a principal target of miR-130a. To elucidate gene expression changes associated with TBL1XR1 loss of function, we performed RNA-seq in CD34+CD38- CB cells transduced with control and shRNA targeted against TBL1XR1. To determine the functional significance of high miR-130a expression levels in Kasumi-1 cells on the molecular network controlled by AML1-ETO, we performed CUT&RUN assay and RNA-seq in Kasumi-1 cells following miR-130a knock-down (KD). Collectively, our findings reveal a unique role of miR-130a in regulating normal hematopoietic stem cell self-renewal and how elevated levels of miR-130a in t(8;21) AML contribute to the leukemogenesis of this AML subtype.

  Dataset EGAD00001008412

• Characterization of Human Transcriptome by Computational and HTS Approaches

  We have deeply sequenced total RNA and whole exome of six different post-mortem human snap-frozen tissues (brain, liver, lung, striated muscle, kidney, heart) from three unrelated healthy Caucasian individuals (males, aged 47-54) with the aim to characterize post-transcriptional events due to alternative splicing and RNA editing. In addition, to facilitate the detection of RNA editing sites we have also resequenced the entire genome of each individual. Data are also used to investigate tissue-specific abundance of mitochondrial DNA from exomes and its correlation with mitochondrial transcription, mass and respiratory activity. Tissues were obtained from Cureline (South San Francisco, CA, USA). DNA and RNA were purified using the DNeasy Blood and Tissue Kit (Qiagen, Hilden, Germany) and the RNeasy Plus Mini Kit (Qiagen, Hilden, Germany), respectively. Exome capture was performed using the TruSeq Exome Enrichment Kit (Illumina, San Diego, CA) and the sequencing was carried out at IGA Technology Services in Udine (Italy) on Illumina HiSeq 2000 (generating for each tissue approximately 40 millions of 100bp paired-end reads). Strand-oriented RNA reads (2x100bp) were generated using the TruSeq Stranded Total RNA Sample Prep Kit (Illumina, San Diego, CA, USA) and sequenced at IGA Technology Services in Udine (Italy) on Illumina HiSeq 2000 platform. Whole genome resequencing was performed at Personal Genomics in Italy on an Illumina HiSeq 2000 platform (2x100bp) with a mean coverage of 30X. MiRNA-Seq was instead performed at IBBE Institute (Italy) using the TruSeq Small RNA Sample Prep Kit on Illumina MiSeq platform. Preliminary bioinformatics analyses have been performed to check quality using FASTQC software and inconsistent read regions have been trimmed using trim_galore. All reads were mapped onto the human reference genome (version hg19) using GSNAP.

  Study phs000870

• Deciphering molecular mechanisms underlying hematological malignancies and development of novel therapeutic approaches

  We aim to identify epigenomic features dysregulated in hematological malignancies through epigenetic analyses of hematological malignant cells. We also perform RNA sequencing to profile tumor cell-specific transcriptomes and target gene sequencing to profile somatic gene mutations in tumor cells. Regarding identified epigenomic abnormalities, we perform further analysis to determine whether they could be good candidates to translate into therapy development. To this end, we will modulate the activity of targets by using their activators and inhibitors in vitro and establish xenograft mouse models of hematological malignancies and manipulate their activity in vivo. Through these studies, we aim to develop new therapeutic agents or modalities that lead to improved patients��� prognosis.

  Study JGAS000603

• Effect of the Placental Transcriptome on Stunting in a Longitudinal African Cohort

  Mammals with placentas and flowering plants evolved genomic imprinting in nutritive tissues, the placenta and endosperm, respectively. In these tissues, the genomes inherited from the mother and father are in conflict over resource allocation to offspring. In imprinted genes, transcription is repressed on the paternal or the maternal allele, resulting in allele specific expression (ASE). We investigated the variation in ASE of imprinted genes in term human placentas in order to detect loss of imprinting (LOI), which leads to partial expression of the repressed allele. We collected the placental tissue from birth to women in our multigenerational, prospective cohort study in Mali, West Africa. We followed the women from their own infancies, early childhood to adulthood (age 18+ years). Contingent on prior informed consent, we collected placental tissue and umbilical cord tissue. We conducted RNA-Seq of the fetal compartment of the placentas and targeted DNA-Seq of the umbilical cord tissue, which is fetal, and of saliva samples from parents. Our sequencing effort produced two datasets. The first dataset is the whole transcriptome RNA-Seq dataset of 111 biopsies (59 placentas) and genotyping of 96 genes. Birth length, weight, and placental weight for the children associated with this dataset are listed in the phenotype file (DOI: 10.1093/molbev/msz226). The second dataset includes targeted RNA-Seq of 262 samples (251 placentas) and targeted DNA-Seq for 766 genes. The genes were selected because they met any one of the following criteria: (1) imprinted and reported in some studies, (2) highly expressed in placenta, or (3) relevant to diseases of interest in this cohort (https://doi.org/10.1093/g3journal/jkab176). This study provides the first systematic analysis of variation in LOI across genes and individuals in a human population, and should shed light on the hypothesis that the modulation of imprinting is an epigenetic mechanism and plays a role in the regulation of offspring growth.

  Study phs001782

• RNAseq data to study PRPF6 regulated splice forms in colon cancer cell lines

  Alternative splicing plays critical roles in differentiation, development, and cancer (Pettigrew et al., 2008; Chen and Manley, 2009). The recent identification of specific spliceosome inhibitors has generated interest in the therapeutic potential of targeting this cellular process (van Alphen et al., 2009). Using an integrated genomic approach, we have identified PRPF6, an RNA binding component of the pre-mRNA spliceosome, as an essential driver of oncogenesis in colon cancer. Importantly, PRPF6 is both amplified and overexpressed in colon cancer, and only colon cancer cells with high PRPF6 levels are sensitive to its loss. Our data clearly point to an important role for PRPF6 in colon cancer growth and suggest that a better understanding of its role in alternative splicing in colon cancer is warranted. To determine the specific alternative splice forms that PRPF6 regulates in colon cancer, we plan three experiments: 1. The first involves knocking down expression of PRPF6 in two different cancer cell lines with 3 different siRNAs, and then completing RNA-seq to determine the gene expression changes that occur relative to a non-targeting control siRNA. Because of the role for PRPF6 in pre-mRNA splicing, we especially want to quantify the changes in splice-specific forms of all genes genome-wide to identify genes whose splicing is altered upon PRPF6 knockdown. 2. The second involves immunoprecipitating PRPF6 from two different cancer cell lines and isolating any RNA that is bound to PRPF6, since PRPF6 is an RNA-binding protein. We then want to carry out RNA-seq to identify which RNA molecules co-immunoprecipitated with PRPF6. This will help us determine possible functions for PRPF6 in regulating colon cancer growth. 3. The third involves overexpressing PRPF6 in cell lines and then carrying out RNA-seq to identify any changes in splice-specific gene expression. This will allow us to determine whether increased PRPF6 expression is sufficient to drive alternative splicing changes.

  Dataset EGAD00001000817

• Single-cell spatiotranscriptomic dissection of ex vivo human heart right atrial appendage and pericardial fluid in ischemic heart disease and heart failure

  We use cardiac and pericardial fluid biopsies collected during open-heart surgery in control, ischemic heart disease, heart failure, and myocardial infarction context. For each sample, single-nuclei RNA sequencing experiment is performed. We also perform spatial transcriptomics on the heart samples. We annotate the cells in major cell types, in addition to subtypes annotation of vascular and immune cells. The disease annotation enables us to reveal substantial differences in gene expression at the cell subpopulation levels. Our results demonstrate the importance of high-resolution cellular type/state mapping in the elucidation of human cardiovascular disease pathogenesis.

  Study EGAS50000000653

• Oncogenic cooperation between the TCF7-SPI1 fusion and NRAS(G12D) requires β-catenin activity to drive T-cell acute lymphoblastic leukemia.

  In this study we investigate the role of TCF7-SPI1 fusions, more specifically in cooperation with RAS mutations. We make use of patients samples. This study contains paired-end RNA sequencing of the patients, Oxford Nanopore Technologies (ONT) sequencing, single cell RNA sequencing and RNA sequencing of treatment with inhibitors of these samples.

  Study EGAS00001005097

• NGS data of human NES cells and tumors

  Raw RNA-seq data for WT and 2 Gorlin NES cells, tumors derived from MYCN mis-expressed WT NES cells, tumors derived from Gorlin NES cells, and tumors derived from Gorlin NES cells transduced with mutant DDX3X (R351W and R534S) and CRISPR/Cas9 targeting GSE1 (each sample has 3 replicates/tumors except Gorlin NES cell tumors have 4). Raw whole exome sequencing data for WT and Gorlin 1 NES cells, tumors derived from MYCN mis-expressed WT NES cells, and tumors derived from Gorlin NES cells (each sample has 3 replicates/tumors except Gorlin NES cell tumors have 4). Raw data for amplicon sequencing of GSE1 and KDM3B at regions targeted by CRISPR/Cas9 in Gorlin NES cells.

  Dataset EGAD00001004990

• 'KOREAN' never-smoker female adenocarcinoma RNA-seq

  Multi-layered genomic studies such as the TCGA project have greatly advanced our understanding on molecular pathogenesis of lung cancer. For Asian nonsmoker patients, however, majority of studies have been limited to mutational analyses, emphasizing ethnic differences in driver mutations (e.g. more frequent EGFR mutations and ALK fusions). In essence, a comprehensive multi-layered characterization that could lead to molecular etiology and patient stratification scheme to be translated into clinical applications for this patient group is still missing. Here we report molecular profiling of tumor and matched normal tissues from 114 non-small-cell lung adenocarcinoma patients using whole exome sequencing, transcriptome sequencing, and array comparative genomic hybridization (CGH).

  Study EGAS00001003789

• Personalized RNA mutanome vaccines mobilize poly-specific therapeutic immunity against cancer RNA-Seq

  The goal of the sequencing study was to determine the neoantigen profile of melanoma patients. We performed whole exome sequening of the tumor and respective patien matched PBMC samples (2x50nt) and RNA-sqeuencing of the tumor samples. The was analyzed for somatic point mutaions, using the RNA-Seq data to determine mutation expression. This study contains the patient matched RNA-Sequencing data.

  Study EGAS00001003307

• 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

• IL-17 Signaling in Human iPSC-derived Midbrain Neurons in Parkinson's Disease

  To determine IL-17-induced global transcriptome changes in midbrain neurons derived from induced pluripotent stem cells (iPSC) from three sporadic Parkinson's disease (PD) patients and three age- and sex-machted controls, deep RNA sequencing (RNA-Seq) of IL-17-treated and untreated PD and control iPSC-dderived midbrain neurons was performed. Total RNA was isolated from untreated and IL-17-treated cells with the TruSeq RNA Sample Preparation Kit v2 (Illumina). RNA libraries were quantified using the KAPA SYBR FAST ABI Prism Library Quantification Kit (Kapa Biosystems) and cluster generation was performed on the cBot with the TruSeq SR Cluster Kit v3 (Illumina). The sequencing run was performed on a HiSeq 1000 instrument (Illumina) using the indexed, 50 cycles single read (SR) protocol and the TruSeq SBS v3 Kit (Illumina). Image analysis and base calling resulted in .bcl files that were then converted into .fastQ files by the CASAVA1.8.2 software. FastQ files were aligned to the human genome (hg19) using STAR.and annotated with gencode.v19. DESeq2 was used to determine differential expression. Criteria to determine significantly dysregulated genes were as follows: adjusted p-value below 0.05 and log2FC (fold change) of greater than one. Only genes with a mean expression value of greater than one RPKM (reads per kilobase per million mapped reads) throughout the dataset were considered. Control and PD samples were analyzed as two independent datasets. Upon IL-17 treatment only 17 genes were found to be dysregulated in controls but 125 genes were dysregulated in iPSC-derived midbrain neurons from PD patients. The 125 IL-17-dependent genes in PD iPSC-derived neurons separated the treated from untreated PD samples using an unsupervised, hierarchical clustering applying an Euclidean distance metric. More detailed study information can be found in Sommer A, Maxreiter F, Krach F, Fadler T, Grosch J, Maroni M, Graef D, Eberhardt E, Riemenschneider MJ, Yeo GW, Kohl Z, Xiang W, Gage FH, Winkler J, Prots I, Winner B. Th17 Lymphocytes Induce Neuronal Cell Death in a Human iPSC-Based Model of Parkinson's Disease. Cell Stem Cell. 2018 Jul 5;23(1):123-131.e6. doi: 10.1016/j.stem.2018.06.015. PMID: 29979986

  Study phs001686

• 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.

  Study EGAS00001001659

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

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

  Study EGAS00001005237

• RNA-sequencing of HCC patients undergoing sorafenib treatment

  RNA-sequencing of hepatocellular carcinomas at various stages of sorafenib treatment

  Study EGAS00001005662

• Dataset for melanoma-RNA

  Rare cancer sequencing data of 49 runs in tumor/control pairs, which were uploaded to umbrella studies. The sequencing was always paired

  Dataset EGAD00001008858

• Dataset for gynecologic_cancer-RNA

  Rare cancer sequencing data of 48 runs in tumor/control pairs, which were uploaded to umbrella studies. The sequencing was always paired

  Dataset EGAD00001008856

• Dataset for hematopoietic_malignancy-RNA

  Rare cancer sequencing data of 47 runs in tumor/control pairs, which were uploaded to umbrella studies. The sequencing was always paired

  Dataset EGAD00001008860

• The Environmental Determinants of Diabetes in the Young Study (TEDDY)

  Study Overview The Environmental Determinants of Diabetes in the Young (TEDDY) Study is a longitudinal study that investigates genetic and genetic-environmental interactions, including gestational events, childhood infections, dietary exposures, and other environmental factors after birth, in relation to the development of islet autoimmunity and type 1 diabetes (T1D). A consortium of six clinical centers assembled to participate in the development and implementation of the study to identify environmental triggers for the development of islet autoimmunity and T1D in genetically susceptible individuals. Beginning in 2004, the TEDDY study screened over 400,000 newborns for high-risk HLA-DR, DQ genotypes from both the general population and families already affected by T1D. The TEDDY study enrolled around 8,676 participants across six clinical centers worldwide (Finland, Germany, Sweden and three in the United States) in the 15-year prospective follow-up. Participants are followed every three months for islet autoantibody (IA) measurements with blood sampling until four years of age and then at least every six months until the age of 15. After the age of four, autoantibody positive participants continue to be followed at three month intervals and autoantibody negative participants are followed at six-month intervals. In addition to the analysis of autoantibodies, additional data and sample collection are performed at each visit. Parents collect monthly stool samples in early childhood. The parents also fill out questionnaires at regular intervals in connection with study visits and record information about diet and health status in the child's TEDDY Book between visits. Continued long-term follow-up of the currently active TEDDY participants will provide important scientific information on early childhood diet, reported and measured infections, vaccinations, and psychosocial stressors that may contribute to the development of type 1 diabetes and islet autoimmunity. Additional information on the TEDDY study is available in the following articles: Rewers et al., 2008, PMID: 19120261 and Hagopian et al., 2006, PMID: 17130573. Details of the TEDDY protocol can be found in Hagopian et al., 2011, PMID: 21564455. TEDDY data currently available in dbGaP include: gene expression, SNPs, exome, microbiome (gut, nasal, and plasma), RNA sequencing, and whole genome sequencing. For more information on TEDDY Study version history please refer to TEDDY Study dbGaP README File. ImmunoChip SNP DNA from whole blood samples on study participants and their family members (mothers, fathers, and siblings) was obtained and used for SNP genotyping. Genotyping was performed by the Center for Public Health Genomics at the University of Virginia using the Illumina ImmunoChip SNP array, which contains around 196,000 SNPs from 186 regions associated with 12 autoimmune diseases (Hadley et al., 2015, PMID: 26010309). Data cleaning and validation included the removal of subjects with a low call rate (< 5% SNPs missing) and differences in reported sex and prior genotyping at the TEDDY HLA laboratory. Additionally, SNPs with a low call rate or Hardy-Weinberg equilibrium P value < 10-6, except for chromosome 6 due to HLA eligibility requirements, were removed from the final dataset (Törn et al., 2015, PMID: 25422107).TEDDY-T1DExome ArrayDNA from whole blood samples on study participants and their family members (mothers, fathers, and siblings) was obtained and used for genotyping. Genotyping was performed by the University of Virginia using the Illumina TEDDY-T1DExome array. The TEDDY-T1DExome array is a custom chip that contains 550,601 markers from the Infinium CoreExome-24 v1.1 BeadChip and an additional 90,214 tagSNPs specifically selected by the TEDDY investigators based on their associations with nutrients, vitamins, type 2 diabetes, autoimmune diseases, body-mass index, or other exposures and phenotypes measured by TEDDY study.The Illumina GenTrain2 algorithm was used for genotype calling. Sample quality control metrics included sample call rate, heterozygosity rate and concordance of gender between the information reported and genotyped. Gene Expression The TEDDY study collected peripheral blood for the extraction of total RNA from enrolled children starting at 3 months of age, and then at 3 month intervals up to 48 months and then biannually. Total RNA was extracted using a high throughput (96-well format) extraction protocol using magnetic (MagMax) beads technology at the TEDDY RNA Laboratory, Jinfiniti Biosciences in Augusta, GA. Purified RNA (200 ng) was further used for cRNA amplification and labeling with biotin using Target Amp cDNA synthesis kit (Epicenter catalog no. TAB1R6924). Labeled cRNA was hybridized to the Illumina HumanHT-12 Expression BeadChips based on the manufacturer's instructions. The HumanHT-12 Expression BeadChip provides coverage for more than 47,000 transcripts and known splice variants across the human transcriptome. Microbiome The TEDDY microbiome study aimed to characterize the longitudinal development of the microbiome, including bacteria, viruses and other microorganisms in the gut, plasma, and nasal cavity of prediabetic and diabetic subjects compared to autoantibody negative non-diabetic subjects. Stool samples used were collected monthly from 3 to 48 months, after which stool samples were collected every 3 months. Nasal swab samples were collected every 3 months starting at 9 months of age until 48 months, after which nasal swabs were collected every 6 months. Plasma samples were collected every 3 months starting at 3 months of age until 48 months, after which plasma samples were collected every 6 months. If the subject was autoantibody positive at 48 months then they remained on the 3 month collection interval for nasal swab and plasma samples. Samples underwent 16s rRNA gene sequencing, DNA and viral RNA metagenomics shotgun sequencing, and sequencing of the internal transcribed spacer (ITS) regions. Additional information on the TEDDY microbiome data is available in the following articles: Vatanen et al., 2018, PMID: 30356183, Stewart et al., 2018, PMID: 30356187, and Vehik et al., 2020, PMID: 31792456. RNA Sequencing The TEDDY study aimed to characterize the transcriptome in subjects with islet autoimmunity and type 1 diabetes compared to matched control subjects. Peripheral blood was collected to extract total RNA from enrolled children starting at 3 months of age, and then at 3 month intervals up to 48 months and then biannually. Total RNA was extracted using a high throughput (96-well format) extraction protocol using magnetic (MagMax) beads technology at the TEDDY RNA Laboratory, Jinfiniti Biosciences in Augusta, GA. Purified RNA was then sent to the Broad Institute for the generation of the TEDDY RNA sequencing (RNA-Seq) data. The RNA samples were prepped using Superscript III reverse transcriptase and Illumina's TruSeq Stranded mRNA Sample Prep Kit. The TruSeq libraries were run on the Illumina HiSeq2500 platform. Whole Genome Sequencing The TEDDY study aimed to conduct deep whole genome sequencing and examine the genomic variations in subjects with islet autoimmunity and type 1 diabetes compared to matched autoantibody negative and non-diabetic children. DNA from whole blood was obtained from TEDDY children for whole genome sequencing. The WGS data were generated on the Illumina HiSeq X Ten system.

  Study phs001442

• Single cell RNA sequencing of human umbilical cord blood lymphoid progenitors

  We performed single cell RNA sequencing of human umbilical cord blood. To explore the differentiation pathway for human lymphoid lineage deeply, our target cells contain CD34+CD38+CD45RA+CD19-CD7-CD10+ cells (CD10SP). All these populations are evaluated by single cell RNA sequencing.

  Study JGAS000551

• CSER: Evaluating Utility and Improving Implementation of Genomic Sequencing for Pediatric Cancer Patients in the Diverse Population and Healthcare Settings of Texas: The KidsCanSeq Study

  Through this Clinical Sequencing Evidence-Generating Research (CSER) with Enhanced Diversity project we are completing a clinical study (The Texas KidsCanSeq Study) comparing the results of targeted cancer panel sequencing versus genome-scale testing in pediatric cancer patients across diverse clinical settings. We will compare the targeted pediatric cancer panel to germline whole exome sequencing (WES) of unselected childhood cancer patients. We will also compare an RNA/DNA targeted pediatric cancer panel versus WES, transcriptome sequencing and copy number array of FFPE tumor samples for the subset of patients with high-risk tumors. Exome sequencing is performed from a blood or saliva sample of the pediatric age (0-18) patient. We are building on our success completing the CSER program BASIC3 exome sequencing trial (which included 60% Hispanic and African-American patients from a single large academic center) in this large multi-institutional study of an even more diverse patient population from six pediatric oncology healthcare settings across Texas. Data from the Texas KidsCanSeq study will be submitted through the CSER Data Coordinating Center for access in NIH-supported databases.

  Study phs002378

• Understanding_Self__Organising_Capacity_of_Stem_Cells_during_Implantation_and_Early_Post_implantation_Development_in_vitro_and_in_vivo__Implications_for_Human_Development_

  The aim of this project is to differentiate human embryonic stem cells to an extra-embryonic fate, specifically the hypoblast. This is of uttermost importance given the current lack of human hypoblast stem cells. We hypothesized that the pluripotent characteristics of the starting human embryonic stem cell population may dictate the competency for extra-embryonic cell fate specification. Based on this hypothesis and using human embryonic stem cells maintained in different naïve-like culture regimes, we have now developed conditions that allow the differentiation of human embryonic stem cells to a stable GATA6+ SOX2- population. This suggests that these cells may be putative human hypoblast stem cells. To validate this finding here we propose to perform RNA sequencing experiments of the differentiated human embryonic stem cells. By comparing their RNA expression profile to the single cell sequencing data of the human embryo that we are currently generating, we will be able to determine the identity of our GATA6+ SOX2- cells, and establish whether they represent the in vivo human hypoblast.

  Study EGAS00001003571

• Single-cell RNA sequencing of human IL-18R supported CAR T cells targeting oncofetal Tenascin C

  C.TNC-CAR.Zip18R CAR-T cells are from 2 donors and multiplexed 10x Genomics scRNA-seq were performed with a hashtag to label each sample. For tumor and CAR-T cell cocluture samples, CAR-T cells were extracted from 3 time points. The raw data are fastq format for total 20 samples considering sequencing lanes. The multiplexing information, CAR and Zip18R sequences are deposited in analyses.

  Study EGAS50000000772

• Single cell RNA sequencing of colorectal cancer patients (CRC-SG1)

  Raw sequencing reads were processed as single end sequencing, aligned to the human reference genome GRCh38 and processed using CellRanger 3.1.

  Dataset EGAD00001008555

• Luminal progenitor cell line iHBEC(CD117)

  Basal-like breast cancer originates in luminal progenitors, frequently with an altered PI3K pathway, and focally in close association with genetically altered myoepithelial cells at the site of tumor initiation. The exact trajectory behind this bi-lineage phenomenon remains poorly understood. Here we used a breast cancer relevant transduction protocol including hTERT, shp16, shp53, and PIK3CA(H1047R) to immortalize FACS isolated luminal cells, and we identified a candidate multipotent progenitor. We found that the apparent luminal phenotype of these oncogene transduced progenitors was metastable giving rise to basal-like cells dependent on culture conditions. After culturing the cells for more than 60 passages, cells were subjected to scRNA-seq as well as bulk RNA sequencing of two subpopulations (CD271+ and CD271-).

  Dataset EGAD50000000723

• Unravelling the contribution of HIF pathway and its therapeutic potential in human AML leukemia-initiating cells

  We performed single cell RNA sequencing (scRNA-seq) from bone marrow on 11 pediatric (0-14 years-old) and adolescent and young adult (AYA) (15-39 years-old) de novo AML samples (Dx) (4 inv(16), 3 t(8;21) and 4 rMLL). In addition, for some patients also relapse sample was sequenced (2 inv(16), 2 t(8;21) and 3 rMLL). Cells were sorted into CD34+/CD38- and CD34-/CD38+ and sequenced separately.

  Dataset EGAD00001008514

• Massive parallel RNA sequencing of highly purified mesenchymal cells derived from bone marrow specimens of 3 Diamond-Blackfan anemia cases

  Highly purified mesenchymal cells (CD45-/7AAD-/CD235a-/CD31-/CD271+/CD105+) were prospectively FACS-isolated from bone marrow specimens of 3 Diamond-Blackfan anemia (DBA) cases. This data set, comprising 3 DBA cases, is used as complement to 45 low-risk myelodysplastic syndrome (LRMDS) and 4 Shwachman-Diamond syndrome (SDS) cases to demonstrate aberrant inflammatory signaling as a common mechanism in pre-leukemia syndromes to induce genotoxic stress in hematopoietic stem cells. In addition, this data set is used to determine different overlapping gene expression signatures in pre-leukemia syndromes compared to gene expression profiles of highly purified mesenchymal cells of healthy donors.

  Dataset EGAD00001002661

• T-VEC CBCL scRNA

  We are presenting raw and processed data of our study where we analyze fine-needle aspirate (FNA) samples of primary cutaneous B-cell lymphoma patients undergoing oncolytic virotherapy (https://clinicaltrials.gov/ct2/show/NCT03458117). We are uploading single cell RNA-sequencing and immune repertoire profiling data of 29 FNA samples from four pCBCL patients. The four patients have three different subtypes of primary cutaneous B-cell lymphoma: pCDLBCL-LT, pCFCL and pCMZL. The samples are taken at different time points following T-VEC injection (from baseline up to 91 days after injection). We are uploading the sequences in BAM format and the outputs of the cellranger pipeline (count matrices and filtered VDJ contigs) in CSV format.

  Dataset EGAD00001006829

• ScRNA-seq of PBMC and whole blood samples reveales a dysregulated myeloid cell compartment in severe COVID-19

  In a dual-center, two-cohort study, we performed single-cell RNA-sequencing of whole blood and peripheral blood mononuclear cells to determine changes in immune cell composition and activation in mild vs. severe COVID-19 over time. This study provides detailed insights into the systemic immune response to SARS-CoV-2 infection and reveals profound alterations in the myeloid cell compartment associated with severe COVID-19.

  Dataset EGAD00001006550

• MPM cell lines

  RNA-sequencing data for 12 MPM cell lines treated with 0.1% DMSO or 1 µM palbociclib for 9-10 days. Experiment was performed in duplicates for sensitive cells (MPM08, MPM21, MPM38, MPM57, MPM59, Meso11, Meso13, Meso34 and Meso56) and only once for resistant cells (MPM31, MPM34 and MPM36) except for Meso11 which was done in triplicates. For Meso11, Meso13, Meso34 and Meso56, a drug washout of 48 hours was also performed. 4 MPM cell lines (MPM31, MPM34, MPM59 and MPM66) were also analyzed in untreated condition. 2 FASTQ files for each sample (n=56) (paired)

  Dataset EGAD00001008741

• Gene expression profiles of single disseminated breast cancer cells

  A set of 56 EpCAM-positive cells derived from bone marrow aspirates of breast cancer patients or patients without a cancererous disease (30 cells from 21 M0-stage and 11 cells from five M1-stage breast cancer patients, 15 cells from seven non-cancer patients serving as controls). EpCAM-positive cells from breast cancer patients were considered disseminated tumor cells as they harbored copy number alterations and showed high expression of the epithelial marker EpCAM and the mammary luminal progenitor marker KIT in comparison to EpCAM-positive bone marrow cells from non-cancer patients. Paired-end RNA-Sequencing of the samples was performed on Illumina NovaSeq6000, raw data are provided in the Fastq format.

  Dataset EGAD00001006359

• G-SAM: Transcriptional Evolution of Glioblastomas Treated With Standard of Care

  Collection of mostly matching primary and recurrent glioblastoma RNA-seq sample pairs, also matching with an earlier DNA sequencing study

  Dataset EGAD00001007860

• Massive parallel RNA sequencing of highly purified mesenchymal cells derived from bone marrow specimens of 4 Shwachman-Diamond syndrome cases

  Highly purified mesenchymal cells (CD45-/7AAD-/CD235a-/CD31-/CD271+/CD105+) were prospectively FACS-isolated from bone marrow specimens of 4 Shwachman-Diamond syndrome (SDS) cases. This data set, comprising 4 SDS cases, is used as complement to 45 low-risk myelodysplastic syndrome (LRMDS) and 3 Diamond-Blackfan anemia (DBA) cases to demonstrate aberrant inflammatory signaling as a common mechanism in pre-leukemia syndromes to induce genotoxic stress in hematopoietic stem cells. In addition this data set is used to determine different overlapping gene expression signatures in pre-leukemia syndromes compared to gene expression profiles of highly purified mesenchymal cells of healthy donors.

  Dataset EGAD00001002660

• FASTQ Files from Breast Tumor Biopsies Collected Across Five Timepoints in the PROMETEO Phase II Trial

  The dataset contains RNA sequencing raw data from tumor biopsies collected at five time points during the SOLTI-1503 PROMETEO trial: baseline (pre-NAC), post-NAC screening, Cycle 2 Day 1, Cycle 3 Day 1, and surgery. The study intervention consisted of intratumoral injections of T-VEC followed by intravenous administrations of atezolizumab prior to surgery. The data is obtained from tumor samples of patients included in the study: female breast cancer patients with residual disease after neoadjuvant chemotherapy, including both triple-negative and Luminal B-like subtypes. Each sample includes raw paired-end RNAseq reads (~110 million reads per library) aligned to the GRCh38/hg38 reference genome

  Dataset EGAD50000002165

• scRNA-seq dataset of Single cell RNA sequencing reveals induced bifurcated differentiation after RUNX1::RUNX1T1 depletion in patient-derived leukemic blasts

  In this study, we demonstrate that primary AML cells harboring the chromosomal translocation t(8;21) are critically dependent on the corresponding fusion gene, RUNX1::RUNX1T1, to suppress differentiation and maintain stemness. Silencing RUNX1::RUNX1T1 expression using siRNA-loaded lipid nanoparticles induces significant changes in chromatin accessibility, redirecting the leukemia-associated transcriptional network towards a myeloid differentiation program. Single-cell analyses reveal that this transcriptional reprogramming is associated with the depletion of immature stem and progenitor-like cell populations, accompanied by an expansion of granulocytic and eosinophilic/mast cell-like populations with impaired self-renewal capacity.

  Dataset EGAD00001015510

• Molecular profiling of tissue autopsies and ctDNA

  The dataset contains high-throughput sequencing data derived from a cancer autopsy series of 10 patients. As part of this study, whole-exome sequencing and RNA-seq were performed for spatially distinct tissue biopsies from the patients. In addition, plasma samples from the patients were sequenced using a custom panelt to profile ctDNA. There are 106 files containing whole-exome sequencing data, 107 files containing RNA-seq data, and 9 files containing plasma sequencing data.

  Dataset EGAD00001007040

• Raw RNA sequencing of hepatoblastoma PDX cell line HB-303-LEF

  Raw RNA sequencing of hepatoblastoma PDX cell line HB-303-LEF

  Study EGAS50000000928

• Encompassing view of spatial and single-cell RNA-seq renews the role of the microvasculature in human atherosclerosis

  Atherosclerosis is a pervasive contributor to ischemic heart disease and stroke. Despite the advance of lipid lowering-therapies and antihypertensive agents, the residual risk of an atherosclerotic event remains high and developing therapeutic strategies has proven challenging. This is due to the complexity of atherosclerosis with a spatial interplay of multiple cell types within the vascular wall. Here we generate an integrative high-resolution map of human atherosclerotic plaques combining single-cell RNA-seq from multiple studies and spatial transcriptomics data from 12 human specimens, with different stages of atherosclerosis. We show cell-type and atherosclerosis-specific expression changes and spatially constrained alterations in cell-cell communication. We highlight the possible recruitment of lymphocytes via ACKR1 endothelial cells of the vasa vasorum, the migration of vascular smooth muscle cells towards the lumen by transforming into fibromyocytes, and cell-cell communication in the plaque region, indicating an intricate cellular interplay within the adventitia and the subendothelial space in human atherosclerosis.

  Dataset EGAD50000000936

• The effect of freezing delay of cell-type specific transcriptome responses in human brain via snRNA-seq

  In other analysis in the current manuscript, we find a similar gene signature (to dissociation based artifacts in mouse and human tissue) is present in post-mortem microglia and astrocytes, across all snRNA-seq datasets analyzed, although it is highly variable between subjects. ​ Using acutely-resected neurosurgical tissue, we performed single-nucleus RNA-seq and reveal that a similar signature can be detected in microglia following prolonged exposure to room temperature. Tissue handling and methods details, as well as sequencing and analysis details) can be found in the methods section of related manuscript (Marsh et al., 2022). Together, these results suggest that the presence of this signature in post-mortem brain samples may be the result of a combination of acute pre-mortem (agonal state, cause of death, comorbidities, etc.) and post-mortem (post-mortem interval (PMI), storage time, RNA quality, etc.) variables and may not represent normally present cell state.

  Dataset EGAD00001008541

• scRNA dataset for 15 samples

  This dataset includes single cell (sc)RNA-seq of N=3 patient-derived xenograft (PDX) samples profiled at baseline (no drug treatment) and N=12 samples from one PDX profiled during the course of treatment (N=1 sample each for 4 treatment arms x 3 timepoints). The dataset includes bam files that have been purged of reads mapping to cells where a majority of the reads from that cell mapped to the mouse genome. All scRNA-seq data were generated using the Chromium Next GEM Single Cell 5' Reagent Kits v2 (Dual Index) from 10X Genomics.

  Dataset EGAD50000001424

• Small cell number RNA-seq (400 cells per sample)

  Transcriptional profiles for stemB and proB cells harvested from either primary or secondary xenografts. This dataset contains six types of samples: - diagnostic stemB cells harvested from primary xenografts - diagnostic proB cells harvested from primary xenografts - relapse stemB cells harvested from secondary xenografts injected with stemB cells from primary xenografts - relapse proB cells harvested from secondary xenografts injected with stemB cells from primary xenografts - relapse stemB cells harvested from secondary xenografts injected with proB cells from primary xenografts - relapse proB cells harvested from secondary xenografts injected with proB cells from primary xenografts

  Dataset EGAD50000001830

• R compatible Seurat's objetc .rds files with count data and metadata from single cell RNA seq analysis to characterize the prostate cancer tumoral microenviroment of 31 fusion biopses.

  Pre-processed Seurat objects with cellular and functional annotation information from the scRNAseq study on PC fusion biopsy samples. The data consists of rds files composed of normalised counts matrices, normalised and scaled counts, functional enrichment counts at the cellular level and metadata with patient grouping and cellular annotation variables. There are 3 .rds files, one with the total cells (SCP_data_analysis), with the selection of cells annotated as cancerous (selected_cancer_analysis) and cancer-associated fibroblasts (selected_caf_analysis).

  Dataset EGAD50000001298

• Orthotopic murine Group 3 medulloblastoma in C57Bl/6 mice treated with saline, cyclophosphamide or gemcitabine

  Mice with medulloblastoma (Group 3) were treated with saline, cyclophosphamide, or gemcitabine as described by Abbas et al (2020). Total RNA was isolated with RNeasy Plus Mini Kit (Qiagen), library preparation (SureSelect, Agilent), rRNA depletion (Ribo-Zero Plus, Illumina) and sequencing were carried out by GenomicsWA or Australian Genome Research Facility. Libraries were sequenced on NovaSeq 6000 S1 flow cells as paired-end 150bp reads (Illumina).

  Dataset EGAD00001008511

• T cell transcriptional gradient

  There are two datasets: 1. scRNA-seq of human cutaneous immune cells from psoriasis patients. These include pre- and post-Tildrakizumab treated patients and come in a BAM file format. 19006FL-25-01 19006FL-38-01 19006FL-32-01-03 19006FL-33-01 19006FL-28-01-05 19006FL-35-01-01 2. RNA-seq of ZFP36L2 CRISPIR deleted Human T cells are FASTQ files. 19006XR-30-05 19006XR-30-04 19006XR-30-02 19006XR-30-01 19006XR-26-05 19006XR-26-04 19006XR-26-02 19006XR-26-01 19006R-22-04 19006R-22-08 19006R-22-05 19006R-22-01

  Dataset EGAD00001009677

• Single cell RNA sequencing of human cord Blood CD34 Cells

  We performed single cell RNA sequencing and ATAC e valuation of human umbilical cord blood. To explore the differentiation pathway for human lymphoid lineage, our target cells contain CD34-positive cord blood. That population is evaluated by single cell RNA sequencing and single cell ATAC.

  Study JGAS000528

• HuBMAP: High Resolution 3D Mapping of Cellular Heterogeneity Within Multiple Types of Mineralized Tissues

  The overall goal of the study was to generate 3D single cell maps of healthy human knee cartilage. Articular cartilage from the weightbearing and non-weightbearing regions of the femoral condyles in healthy knees from young donors (n=12) was analyzed by bulk RNA-sequencing (RNA-Seq), single nuclei RNA (snRNA-seq) and ATAC-sequencing and by spatial transcriptomic methods (GeoMx, MERFISH and Xenium). These multimodal data and additional single cell RNA-sequencing (scRNA-seq) data were integrated to generate a comprehensive molecular, genomic and function annotation of chondrocyte populations. Regulatory mechanisms were derived by linking motifs in expressed genes, transcription factors and chromatin organization.

  Study phs003721