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• analysis of the off target effect after Prime editing in IPSC line KCNQ2 R201C. Comparison of parental KCNQ2 R201C with two corrected clonal lines.

  Short read whole genome sequencing analysis of the off target effect after Prime editing in IPSC line KCNQ2 R201C. Comparison of parental KCNQ2 R201C with two corrected clonal lines (3samples in total). Dataset contains CRAM files and VCF files for the respective samples.

  Dataset EGAD00001010904

• Single Cell RNA sequencing of Organoids from TSC2+/- patient IPSCs in H- and L-medium

  This dataset contains single cell RNA sequencing data from Organoids grown in high nutrient (H) and low nutrient (L) medium. Organoids were grown for 110 days. Organoids were grown from a patient IPS cell line with a heterozygous mutation in TSC2 (Patient 1 TSC2+/- iPSCs) and an isogenic control cell line (TSC2+/+).

  Dataset EGAD00001006332

• Low-depth whole genome sequencing across multiple isolated populations

  Isolated populations have unique population genetics characteristics that can help boost power in genetic association studies for complex traits. Leveraging these advantageous characteristics requires an in-depth understanding of parameters that have shaped sequence variation in isolates. This study performs a comprehensive investigation of these parameters using low-depth whole genome sequencing (WGS) across multiple isolates.

  Dataset EGAD00001002014

• Exome Sequencing to Identify Medically Relevant Associations in Finnish Sub-Isolate Samples from the FINRISK Cohort

  We propose to undertake, at the McDonnell Genome Institute of Washington University, a collaborative exome sequencing project of ~10,000 samples from a large Finnish population cohort, FINRISK, a participating component of the Sequencing Initiative Suomi (SISu) consortium. Together these sequenced samples will provide a unique resource for identification of infrequent or rare variants with a large impact on cardiovascular and metabolic disorders as well as on a wide range of heritable, disease-related quantitative phenotypes. Our collaborative group has already shown, in exome sequencing studies of smaller Finnish samples, that numerous loss of function variants are dramatically more frequent in Finland compared to other European populations, and that such variants demonstrate strong associations to several disease-related traits. Finland is the largest population isolate in Europe and the enrichment of these variants reflects its rapid growth from a severe population bottleneck about 100 generations ago. Northern and Eastern parts of Finland experienced additional, more recent bottlenecks, and therefore the enrichment of particular high-impact variants in these regions is even more extreme (Stoll et al., 2013, PMID: 23912948). We therefore propose to focus exome sequencing efforts on about 10,000 members of FINRISK who are specifically drawn from these sub-isolate regions. As a very wide range of phenotypes are available from this cohort (including cardiovascular and metabolic disease outcomes obtained from national registries) we hypothesize that the proposed exome sequencing will identify numerous new disease-related associations. Within the National Biobanks of Finland (www.nationalbiobanks.fi) we have DNA and tissue samples from over 200,000 individuals of whom 50,000 have GWAS data; these samples provide an exceptional resource for both imputation from the sequencing studies proposed here, as well as for replication of associations.

  Study phs000756

• An integrative model of pathway convergence in genetically heterogeneous blast crisis chronic myeloid leukemia (CML)

  Targeted therapies against the BCR-ABL1 kinase have revolutionized treatment of chronic phase (CP) chronic myeloid leukemia (CML). In contrast, management of blast crisis (BC) CML remains challenging because BC cells acquire complex molecular alterations that confer stemness features to progenitor populations and resistance to BCR-ABL1 tyrosine kinase inhibitors. Comprehensive models of BC transformation have proved elusive because of the rarity and genetic heterogeneity of BC, but are important for developing biomarkers predicting BC progression and effective therapies. To better understand BC, we performed an integrated multiomics analysis of 74 CP and BC samples using whole-genome and exome sequencing, transcriptome and methylome profiling, and chromatin immunoprecipitation followed by high-throughput sequencing. Employing pathway-based analysis, we found the BC genome was significantly enriched for mutations affecting components of the polycomb repressive complex (PRC) pathway. While transcriptomically, BC progenitors were enriched and depleted for PRC1- and PRC2-related gene sets respectively. By integrating our data sets, we determined that BC progenitors undergo PRC-driven epigenetic reprogramming toward a convergent transcriptomic state. Specifically, PRC2 directs BC DNA hypermethylation, which in turn silences key genes involved in myeloid differentiation and tumor suppressor function via so-called epigenetic switching, whereas PRC1 represses an overlapping and distinct set of genes, including novel BC tumor suppressors. On the basis of these observations, we developed an integrated model of BC that facilitated the identification of combinatorial therapies capable of reversing BC reprogramming (decitabine+PRC1 inhibitors), novel PRC-silenced tumor suppressor genes (NR4A2), and gene expression signatures predictive of disease progression and drug resistance in CP.

  Study EGAS00001001751

• RNA sequencing of baseline HCC PDX models

  To establish the baseline transcriptional profiles, we performed bulk RNA-seq for 36 of our HCC PDX models. 2-6 samples were collected for each model resulting in a total of 68 samples. Isolated RNA was used as input for library preparation using TruSeq RNA Sample Preparation Kit v2 (Illumina). The libraries were multiplexed and sequenced on Illumina HiSeq 2500 (Illumina) to produce FASTQ files.

  Dataset EGAD50000000736

• ESGI - Molecular diagnosis for mitochondrial disorders (2017-08-29)

  The MITOEXME project aims to improve protocols for molecular diagnosis of patients with OXPHOS disorders with a focus on a next generation sequencing methods and to increase the knowledge of pahtophysiological mechanisms by identification of new targets and cellular studies. In this project we will sequence the exomes fo 120 patients. This dataset contains all the data available for this study on 2017-08-29.

  Dataset EGAD00001003596

• Paired-end Whole Exome-seq analysis of multi-centric lower grade glioma

  This dataset includes Nimblegen SeqCap EZ Exome v3 data for each lesion of three patients with multicentric glioma. For two patients, each lesion was sequenced along with whole blood. For a third patient, 3 pieces from the right lesion and 4 pieces from the left were sequenced along with whole blood. In each case BAM files that have been aligned with BWA mem alignment are available.

  Dataset EGAD00001003795

• Colon Cancer Family Registry (Colon CFR)

  The Colon Cancer Family Registry Cohort (CCFRC www.coloncfr.org) is a cohort of families recruited through six study sites located in the USA, Canada, Australia, and New Zealand. The CCFRC was formed as a resource to support studies on the etiology, prevention, and clinical management of colorectal cancer. Recruitment protocols fall broadly into two main categories: population-based and clinic-based ascertainment. Between 1998 and 2013, the CCFR recruited and interviewed probands who were either recently diagnosed with colorectal cancer that was reported to state or regional population cancer registries in the United States (Washington, California, Arizona, Minnesota, Colorado, New Hampshire, North Carolina, and Hawaii), Australia (Victoria), and Canada (Ontario) or were from multiple-case families referred to family-cancer clinics in the United States (Mayo Clinic in Rochester, Minnesota, and Cleveland Clinic in Cleveland, Ohio), Australia (Melbourne, Adelaide, Perth, Brisbane, and Sydney), New Zealand (Auckland), and Canada. Cases with known familial adenomatous polyposis were excluded. Once recruited, probands were asked for permission to contact their relatives for recruitment. Collectively, we have enrolled 42,49874 participants in 15,048 families who participated in standardized protocols used to collect information regarding family cancer history and colorectal cancer risk factors and biospecimens. All participants of population-based case families (excluding control-families) and clinic-based families are asked to provide updates on their personal and family history of cancer as well as their history of surgery, cancer screening, and some risk factors every 4-5 years either by telephone interview or by self-completed questionnaire via mail or online (PMID: 17982118).

  Study phs002733

• Single cell transcriptomics in expanded Tregs of APS-1 patients

  Aim of study: Exploring single cell transcriptomics in expanded Tregs of with autoimmune polyendocrine syndrome type 1 (APS-1) patients (global gene expression, immune panel, TCR). N= 9 APS-1 patients and 9 healthy controls Protocol 1. Regulatory T cells (Tregs) were isolated from EDTA-blood, activated with anti-CD3/CD28 and IL2, expanded in cell culture for 14 days and stored at -150℃ in AB serum or FBS + 5% DMSO until use. 2. Cells were thawed, run through a Live/Dead column and carefully counted. 10000 Tregs were used as input for the 10x protocol. 3. cDNA was generated and amplified using Single Cell VDJ 5’ Gel Beads, Chromium Next GEM Chip K Single cell Kit, Next GEM Single Cell 5’ GEM Kit v2 and 5’ Feature Barcode Kit (all from 10x genomics). 4. Gene expression (GEX) libraries were generated by using the Library Construction Kit from 10x genomics. 5. T-cell receptor (TCR) libraries were generated using the Single Cell Human TCR Amplification Kit and the Library Construction Kit from 10x genomics. 6. 10x Genomics Target Hybridization Kit and Human Immunology Panel was used with GEX libraries. Only 8 patient samples and 8 control samples were used for the immune panel. 7. All libraries have a unique sample index (Dual Index TT Set A). 8. All samples were sequenced on Illumina NovaSeq 6000 on a NovaSeq S2 flow cell.

  Study EGAS50000000181