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• RNA-seq study of human long-term and short-term hematopoietic stem cells from umblical cord blood with lentiviral overexpression of S1PR3

  To investigate the molecular and biological pathways altered by S1PR3OE in human hematopoietic stem cells (HSC), we performed RNA-sequencing (RNA-seq) of LT- and ST-HSC 3 days after transduction with control or S1PR3 overexpression (OE) lentiviral vectors. LT-HSC and ST-HSC from 3 pool of CB lin- were FACS-purified, cells were prestimulated for 4 hours and transduced with lentiviral vectors. At day 3, 2000-5300 BFP+ cells were FACS-purified for RNA isolation with a PicoPure kit. We were able to isolate only 1600-1800 BFP+ cells from LT-HSC control samples as opposed to 4000-5400 BFP+ cells from S1PR3OE samples. Thus, we pooled all control BFP+ LT-HSC cells into one sample for RNA-seq analysis. BFP- LT-HSC from control vector transduction were purified from CB1 as an additional LT-HSC control. Nextera libraries generated from 10 ng RNA from 5 LT-HSC samples (2 controls, 3 S1PR3OE) and 6 ST-HSC samples (3 controls, 3 S1PR3OE) were subjected to 125 bp, paired-end RNA-sequencing on the Illumina HiSeq 2500 with an average of 50 million reads/sample at the Center for Applied Genomics, Sick Kids Hospital.

  Study EGAS00001004798

• Integrated genomic analysis for HCC

  Liver cancer is a common malignancy and is the third cause of cancer-related death in the world and hepatocellular carcinoma (HCC) is the major type of liver cancer, accounting for ~90% of cases. Only 20 ~ 30% of patients can benefit from combined immunotherapy and targeted therapy due to the high inter-tumor heterogeneity of HCC. This work aims to identify homogeneous and robust molecular subtypes in HCC based on a large, homogenous and well-annotated cohort. We performed whole genome/exome sequencing (WGS/WES) and/or RNA sequencing (RNA-seq) on 529 HCC from 461 patients collected mainly in France. Based on the great consistence between genomic and transcriptomic data, we identified 9 robust HCC subtypes mainly based on driver mutations. And we further characterized HCC subtypes using genomic, transcriptomic and clinicopathological features. Among 9 subtypes, 5 subtypes belonged to chromosome instable tumors, while 3 subtypes belonged to chromosome stable tumors. In addition, our subtypes were associated with prognosis and we also found different distributions of subtypes across various features, such as etiology and gender. Our study provided a robust molecular classification based on a large HCC dataset from Western country, it improves our understanding of the mechanisms of carcinogenesis and will facilitate development of genome-based precision medicine in HCC.

  Study EGAS00001007957

• RNA-Seq in Patients with Primordial Dwarfism

  Transcriptome studies in patients with rare genetic diseases can potentially aid in the interpretation of likely causal genetic variation through identification of altered transcript abundance and/or structure. RNA-Seq is the most sensitive assay for both investigating transcript structure and abundance The primary aim of this pilot project is to investigate to what degree integrating exome-Seq and RNA-Seq data on the same individual can accelerate the identification of causal alleles for rare genetic diseases. There are two main strands to this: (i) identifying which variants discovered in exome-seq appear to be having a functional impact on transcripts, and (ii) identifying transcript outliers, especially among known causal genes, that may not necessarily have a causal variant identified from exome sequencing. The latter may identify the presence of causal variants that lie far from coding regions (e.g. the formation of cryptic splice sites deep within introns, or loss of long range regulatory elements), which can be confirmed with further targeted genetic assays. Just over 50% of all disease-causing variants recorded in the Human Gene Mutation Database (HGMD) affect transcript structure and abundance (e.g. nonsense SNVs, essential splice site SNVs, frameshifting indels, CNVs). This pilot project will study RNA from lymphoblastoid cell-lines from 12 patients with primordial dwarfism syndromes, for 10 of these samples we have previously generate exome data as part of our collaboration with the group of Prof Andrew Jackson. The two remaining samples are positive controls where the causal mutation is known, and is known to affect transcript structure and/or abundance. Primordial dwarfism is a prime candidate for these RNA-seq studies because all known causal mutations to date have key roles in DNA replication and thus, unsurprisingly, the products of the causal genes are typically ubiquitously expressed. Each RNA will be sequenced, with two technical replicates (independent RT-PCR and libraries) per sample, and each replicate run in 1/2 of a HiSeq lane using 100bp paired reads. Samples preparation was as follows :The cells were grown to confluency, then pellets frozen at -80. RNA samples were prepared using the Qiagen RNeasy kit, then nanodropped and analyzed using the bioanalyzer to determine concentration and purity. 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 EGAD00001000640

• Presence of rare potential pathogenic variants in subjects under 65 years old with very severe or fatal COVID‑19

  Rare variants affecting host defense against pathogens could be involved in COVID‑19 severity and may help explain fatal outcomes in young and middle‑aged patients. Our aim was to report the presence of rare genetic variants in certain genes, by using whole exome sequencing, in a selected group of COVID‑19 patients under 65 years who required intubation or resulting in death (n = 44). To this end, different etiopathogenic mechanisms were explored using gene prioritization‑based analysis in which genes involved in immune response, immunodeficiencies or blood coagulation were studied. We detected 44 different variants of interest, in 29 different patients (66%). Some of these variants were previously described as pathogenic and were located in genes mainly involved in immune response. A network analysis, including the 42 genes with candidate variants, showed three main components, consisting of 25 highly interconnected genes related to immune response and two additional networks composed by genes enriched in carbohydrate metabolism and in DNA metabolism and repair processes. In conclusion, we have detected candidate variants that may potentially influence COVID‑19 outcome in our cohort of patients. Further studies are needed to confirm the ultimate role of the genetic variants described in the present study on COVID‑19 severity.

  Study EGAS00001006372

• Genomics of Colorectal Cancer Metastases - Massively Parallel Sequencing of Matched Primary and Metastatic tumours to Identify a Metastatic Signature of Somatic Mutations (MOSAIC)

  Genomics of Colorectal Cancer Metastases - Massively Parallel Sequencing of Matched Primary and Metastatic tumours to Identify a Metastatic Signature of Somatic Mutations (MOSAIC)

  Dataset EGAD00001000080

• Progressive multifocal leukoencephalopathy (PML)

  We generated RNAseq, ATACseq, Multiomics and CITEseq for patients with Progressive multifocal leukoencephalopathy (PML) to profile the chromatin accessibility, transcriptional profiles and surface proteins at single-cell level.

  Study EGAS50000000139

• Genome Wide Association Studies in Alopecia Areata

  1054 unrelated alopecia areata patients were genotyped with the Illumina HumanHap550v3.0 genotyping chip. Allele frequencies were compared to publically available data from three population cohorts of controls.

  Study phs000586

• WES and RNA-Seq of HCC biopsies and HCC derived Organoids

  We aimed to identify somatic mutations and transcriptional differences that could explain the resistance to Doxorubicin. This dataset includes RNA-Seq of HCC biopsies and Organoids and WES of Organoids.

  Dataset EGAD50000000060

• TCRseq

  T cell receptor sequencing of tumor samples. Briefly, DNAse I treated tumor RNA samples were subjected to library preparation using AmpliSeq Immune Repertoire Panel (Illumina) and sequenced using NextSeq500.

  Study EGAS50000000258

• Genome-wide array data from Eivissan and Menorcan Individuals

  VCF file with autosomal genotypes from 22 and 20 Eivissan and Menorcan samples. Affymetrix Human Origins array was used to genotype the samples and the variants were lifted over to the hg38 human genome reference.

  Dataset EGAD50000000614

• WES analysis of tumor samples

  Whole exome sequencing was performed on paired tumor (N=8) from ER+ advanced breast cancer, obtained prior to combined CDK4/6i and endocrine therapy and at disease progression.

  Study EGAS50000000430

• Whole Exome Sequencing of Multiple Myeloma Patients

  We used whole exome sequencing (WES) data from 35 MM patients to evaluate possible mutational signatures and driver mutations associated with the patient’s clinical and cytogenetic characteristics.

  Study EGAS50000000394

• Transcriptional Reference Map of Human Natural Killler Cells

  Here we performed single-cell RNA sequencing of both bulk NK and sorted NK subsets to establish a transcriptional reference map of human natural killer cells.

  Study EGAS50000000014

• BAM files from capture-based targeted sequencing of 12 agressive B-cell lymphoma tumour samples (IG-MCL-panel)

  This dataset contains BAM files from capture-based targeted sequencing of 12 agressive B-cell lymphoma tumour samples for cases 1 to 6 and 8 to 13. The sequencing panel used is a MCL-oriented panel containing 159 genes.

  Dataset EGAD50000000801

• SMPaeds PanelSeq of tumour tissue

  Deep sequencing of a targeted panel of 92 paediatric cancer related genes or 233 pan-cancer related genes for both relapse/archival disgnostic tumour tissue and germline DNA from whole blood cell pellet. Tumour tissue was sequenced to approximately 400X coverage and germline DNA was sequences to aproximately 100X coverage.

  Dataset EGAD50000000783

• Shallow Whole Genome Sequencing (sWGS) from REPEAT trial

  Samples associated to: "A phase Ib/II study of regorafenib and paclitaxel in patients with beyond first-line advanced esophagogastric carcinoma (REPEAT)". sWGS from 97 Esophagogastric Carcinoma samples. sWGS was done to carry out Copy Number Analysis. Dataset includes: .fastq, .bam and .bai files.

  Dataset EGAD50000001161

• Whole Exome Sequences from Eivissan and Menorcan Individuals

  We analyzed Exome sequences of present day Eivissan and Menorcan individuals in order to expand on the knowledge about their demographic history and its functional consequences.

  Study EGAS50000000428

• Altered Blood and Keratinocyte microRNA/transfer RNA Fragment Profiles Related to Fibromyalgia Syndrome and its Severity

  We show dysregulated microRNA and tRNA fragment profiles related to FMS pathopyhsiology and opening new perspectives for FMS diagnostics and symptom monitoring. This dataset includes all sequencing raw files from whole blood (tempus tube) and keratinocyte sequencing.

  Dataset EGAD50000000900

• Stanford Acute Myeloid Leukemia Single-Cell DNA Sequencing

  These are single-cell DNA sequencing data from acute myeloid leukemia samples from Stanford University. They were used in multiple publications to understand clonal evolution in AML.

  Study phs003853

• Whole Exome Sequencing Data of 34 indolent primary renal B-Cell lymphoma cases

  Here, 34 iNHL samples were sequenced using whole exome sequencing to describe the mutational landscape of indolent primary renal B-Cell lymphomas. Mutational profiles were compared to other Marginal Zone Lymphomas.

  Dataset EGAD50000001136

• LongVar low-coverage data

  This dataset includes sequencing data from participants of the LongVar study. Specifically, it comprises low-coverage whole genome sequencing (WGS) data which was derived from cell-free DNA from blood samples. These data were generated to compare imputation accuracy. 133 individuals agreed to share their data, and are healthy volunteers.

  Dataset EGAD50000001607

• Exploring Genomic Mutations in Gastric Cancer among Japanese Populations

  We conducted a comprehensive analysis of whole-genome and RNA sequences obtained from biopsy samples of 65 patients with advanced gastric cancer prior to chemotherapy treatment.

  Study JGAS000754

• Integrated diagnosis based on transcriptome analysis in suspected pediatric sarcomas

  We performed RNA-sequencing in 47 patients with suspected pediatric sarcomas, to evaluate the potential utility of RNA-seq in the diagnostic process of pediatric sarcoma.

  Study JGAS000284

• Whole-genome-sequencing, Whole-exome-sequencing and RNA-sequencing in Sporadic ALS

  To identify the genetic cause and modifiers of Sporadic ALS, we performed Whole-genome-sequencing, Whole-exome-sequencing and RNA-sequencing of Sporadic ALS patients.

  Study JGAS000393

• Genome editing strategies to generate working models in Polycystic Kidney Disease

  Bulk RNA-seq of genome-edited HEK293T cell lines engineered to model specific PKD1 variants. These clones were created with the purpose of enabling the exploration of genotype-phenotype correlations in Polycystic Kidney Disease (PKD)

  Dataset EGAD50000001694