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• Single-nucleus RNA-sequencing data of kidney biopsies from patients with primary FSGS, maladaptive FSGS, proteinuric controls and healthy controls

  This dataset includes FASTQ files of single-nucleus RNA sequencing of cryopreserved kidney biopsy cores from adult patients with diagnosed primary FSGS (n = 9, all nephrotic), maladaptive FSGS (n = 9, not nephrotic), proteinuric controls (PLA2R-positive membranous nephropathy, n = 3), and healthy controls (n = 4). A total of 120,751 high-quality nuclei were identified, including 2,471 podocytes and 1,574 parietal epithelial cells (PECs). In addition to the raw FASTQ files, the dataset includes processed data files from all 25 samples, generated using Seurat in R: barcode files, features, count matrices, and associated metadata. Details regarding the bioinformatics pipeline can be found at https://github.com/lambrechtslab/FSGS_Deleersnijder_et_al

  Dataset EGAD50000001557

• EuCANCan: EUropean-CANadian Cancer network

  The EUropean-CANadian Cancer network (EuCANCan) is a project aiming to develop a federated network of aligned and interoperable infrastructures for the homogeneous analysis, management and sharing of genomic oncology data for Personalized Medicine. This initiative, funded by the European Commission and the Canadian Institutes of Health and coordinated by the Barcelona Supercomputing Center (BSC), is expected to process and provide the scientific community with around 30-35 thousand patient samples from different types of cancer, coming from different nodes involved in this project, during the four years of the project. Data generated as part of primary studies, often in small hospitals or research centers, is hardly reused by other projects or groups. EuCANCan is proposed to foster the homogenisation and discoverability of cancer samples from very different sources for the whole community. These efforts will help paving the way to future standardised and global genomics projects, specially for those participant countries that eventually integrate the methodology and infrastructure generated during the project. “The more data we have access to the more and better discoveries. We attempt to overcome the legal and technical limitations in order to generate, gather and exploit bigger datasets as well as answer more ambitious questions”. These were some of the words Dr. David Torrents, main coordinator of the project, shared with a regional radio during the kick-off meeting of the project, on February 11th, 2019. The EUCANCan network will be composed of reference nodes in Amsterdam, Barcelona, Berlin, Heidelberg, Paris and Toronto which have established strong research and clinical programs in the field of genomic oncology. The Centre for Genomic Regulation (CRG), specifically the European Genome-phenome Archive (EGA), is among the leading institutions. Its exhaustive experience in biomedical data archival and secure distribution is considered key for crucial developments within the project. It is also notable the recent inclusion of EUCANCan in the list of GA4GH driver projects. Further information and details can be found in the following links: InsideHPC BSC official description Techweek (Spanish)

  Blog eucancan

• Genome-wide DNA-methylation assessment by MethylCap-seq and Infinium HumanMethylation450 BeadChips: an independent large-scale comparison

  DNA-methylation is an important epigenetic feature in health and disease. Two cost-efficient genome-scale methodologies to assess DNA-methylation are MethylCap-seq and Illumina's Infinium HumanMethylation450 BeadChips (HM450). However, objective information regarding the best-suited methodology for a specific research question is scant. Therefore, we performed a large-scale evaluation on a set of 70 brain tissue samples obtained from 65 glioblastoma and 5 non-tumoral brain tissues, using a gold standard free Bayesian modeling procedure. While conditional specificity was adequate for both approaches, conditional sensitivity was systematically higher for HM450. Also the genome-wide characteristics were compared, revealing that the HM450 probes assess less than 10% of the regions identified as methylated by MethylCap-seq. Hence the latter method may detect more potentially relevant DNA-methylation, defined by either functional location or previously reported differentially methylated candidate regions. Our results therefore indicate that – at least for the tissue under study - both methodologies are complementary, with a higher sensitivity for HM450, but a far larger genome-wide coverage for MethylCap-seq. Note that here only the relevant MethylCap-seq data is deposited, for the HM450 data we refer to GEO (GSE60274).

  Study EGAS00001001191

• Non-coding mutations reveal cancer driver cistromes in luminal breast cancer

  Whole-genome sequencing of primary breast tumors enabled the identification of cancer driver genes and non-coding cancer driver plexuses from somatic mutations. However, differentiating between driver and passenger events among non-coding genetic variants remains a challenge to understand the etiology of cancer and inform the delivery of personalized cancer medicine. Herein, we reveal enrichment of non-coding mutations in cis-regulatory elements that cover a subset of transcription factors linked to tumor progression in luminal breast cancers. Using a cohort of 26 primary luminal ER+PR+ breast tumors, we compiled a catalogue of ~100,000 unique cis-regulatory elements from ATAC-seq data. Integrating this catalogue with somatic mutations from 350 publicly available breast tumor whole genomes, we identified four recurrently mutated individual cis-regulatory elements. By then partitioning the non-coding genome into cistromes, defined as the sum of binding sites for a transcription factor, we uncovered cancer driver cistromes for ten transcription factors, namely CTCF, ELF1, ESR1, FOSL2, FOXA1, FOXM1 GATA3, JUND, TFAP2A, and TFAP2C in luminal breast cancer. Nine of these ten transcription factors were shown to be essential for growth in breast cancer, with four exclusive to the luminal subtype. Collectively, we present a strategy to find cancer driver cistromes relying on quantifying the enrichment of non-coding mutations over cis-regulatory elements concatenated into a functional unit drawn from an accessible chromatin catalogue derived from primary cancer tissues.

  Study EGAS00001005235

• RNA-seq of high grade serous ovarian tumours

  Somatic RNA for 40 samples matched to the WGS was extracted using the Qiagen Qiasymphony RNA protcol (cat no 931636). The tissue was initially homogenised using a Qiagen Bioruptor, followed by the manufacturers recommended protocol (including DNase digestion). The resulting RNA the underwent quality control as follows: firstly, A260 and A280nm were measured on a Denovix DS-11 Fx to qualitatively illustrate A260/280nm and A260/230nm ratios as measures of RNA purity. A260/280 had to be 2.0 and A260/230 had to be 2.0-2.2. Then RNA was quantified using LifeTechnologies Qubit RNA BR kit (cat no Q10210). RNAseq was carried out by the Edinburgh Clinical Research Facility on an Illumina NExtSeq500. Total RNA samples were assessed on the Agilent Bioanalyser (Agilent Technologies, #G2939AA) with the RNA 6000 Nano Kit (#5067-1512) for quality and integrity of total RNA, and then quantified using the Qubit 2.0 Fluorometer (Thermo Fisher Scientific Inc, #Q32866) and the Qubit RNA HS assay kit (#Q32855). Libraries were prepared from total-RNA sample using the NEBNext Ultra 2 Directional RNA library prep kit for Illumina (#E7760S) with the NEBNext rRNA Depletion kit (#E6310) according to the provided protocol. 400ng of totalRNA was then added to the ribosomal RNA (rRNA) depletion reaction using the NEBNext rRNA depletion kit (Human/mouse/rat) (#E6310). This step uses specific probes that bind to the rRNA in order to cleave it. rRNA-depleted RNA was then DNase treated and purified using Agencourt RNAClean XP beads (Beckman Coulter Inc, #66514). RNA was then fragmented using random primers before undergoing first strand and second strand synthesis to create cDNA. cDNA was end repaired before ligation of sequencing adapters, and libraries were enriched by PCR using the NEBNext Multiplex oligos for Illumina set 1 and 2 (#E7500). Final libraries had an average peak size of 271bp. Libraries were quantified by fluorometry using the Qubit dsDNA HS assay and assessed for quality and fragment size using the Agilent Bioanalyser with the DNA HS Kit (#5067-4626). Sequencing was performed using the NextSeq 500/550 High-Output v2 (150 cycle) Kit (# FC- 404-2002) on the NextSeq 550 platform (Illumina Inc, #SY-415-1002). Libraries were combined in an equimolar pool based on the library quantification results and run across 5 High-Output Flow Cell v2.5.

  Dataset EGAD00001009048

• Characterization of mutational signatures in human cancer cell lines reveals episodic APOBEC mutagenesis

  Multiple signatures of somatic mutations have been identified in human cancer genomes. To investigate whether mutational signatures continue to be generated, and if so their temporal patterns of activity, subsets of cell lines were cultured in vitro for extended periods and subjected to single cell cloning and whole genome or exome sequencing or directly to single cell whole genome sequencing. As expected, signatures of past exogenous exposures, such as tobacco smoke and ultraviolet light, were not generated in vitro. In contrast, signatures of normal and defective DNA repair and replication continued to be generated at essentially constant mutation rates. Signatures of APOBEC cytidine deaminase DNA-editing activity exhibited a distinctive pattern with substantial fluctuations in mutation rate over time and episodic bursts of mutations. The initiating factors for these bursts are unclear although retrotransposon mobilisation may play a role. This cell line set now constitutes a comprehensive resource of live experimental models of mutational processes of both known and unknown aetiologies potentially retaining the patterns of activity and regulatory influences operative in human cells in vivo.

  Dataset EGAD00001004202

• LCCC1122: Defining the Triple Negative Breast Cancer Kinome Response to GSK1120212

  In this study the investigators looked at adaptive reprogramming impact on the kinome when a MEK inhibitor called GSK1120212 (trametinib) was administered in a "window of opportunity" trial. GSK1120212 is not yet approved by the FDA for use in breast cancer patients. The investigators gave GSK1120212 for a short period of time (one week) to examine MEK and the other kinase expression in cancer cells both before and after the study drug is given. The investigators gave this drug for research purposes only. The length of time it was given is not intended to treat cancer. Recently researchers at UNC developed a process that can comprehensively profile the majority of the individual kinases in the kinome and examine the impact on kinase expression of kinase inhibitors (Duncan et al, Cell 2012, PMID: 22500798). This can tell us which kinases need to be concurrently blocked to augment responsiveness and prevent acquired resistance so that the investigators can design the best combinations of kinase blocking drugs for triple negative breast cancer. This is especially important for individuals with triple negative breast cancer (TNBC) because there are no targeted drugs available that can block molecules that affect tumor growth. The investigators believe that kinase-blocking drugs have the potential to be a more effective treatment for people with TNBC. In this recently published study (Zawistowski et al, Cancer Discovery 2017, PMID: 28108460), TNBC patients treated with trametinib for 7 days resulted in a transcriptional response characterized by significant reprogramming of the tyrosine kinome, and this adaptive bypass response in human tumors was found to be similar to that seen in preclinical models including TNBC cell lines and mouse xenografts. In this study we also examined whether reprogramming differed between TNBC molecular subtypes, finding that basal-like and claudin-low human TNBC cells and mouse tumor subtypes had different adaptive transcriptional responses to MEK-ERK inhibition. Mechanistically we found that genome-wide enhancer remodeling drove the adaptive transcriptional response, suggesting that epigenetic approaches to reprogramming may be more durable than kinase inhibitor polypharmacology.

  Study phs001405

• Error-corrected sequencing of 26 driver genes (additional cohort)

  An additional 320 swab samples were sequenced. The bam files contain consensus reads.

  Dataset EGAD50000000641

• Whole Exome Sequencing

  Whole Exome Sequencing Data for 10 patients for treatment with the ICI Nivolumab

  Dataset EGAD00001011117

• Center for Common Disease Genomics [CCDG] - Neuropsychiatric: Epilepsy: Epi25 Consortium

  Epilepsy genetics research is at an exciting stage where it is now feasible, with the power of a large cohort, to understand the more complex genetic components of epilepsy. The driving principle behind the Epi25 Consortium is collaboration and synergy - it is only possible to achieve this type of research by working together. The Epi25 Consortium was formed by the unification of various consortia, including Epi4K, EPIGEN, EuroEPINOMICS, the Epilepsy Phenome/Genome Project, EpiPGX, SANAD, and EpiCURE, and individual epilepsy investigators. The consortium's sample collection is the best resource in the world for this disease, both in terms of numbers of patients and quality of phenotypic information. As part of the NHGRI Centers for Common Disease Genomics (2016-2020), we aggregated a global sample collection from the various repositories for whole genome genotyping and whole exome sequencing (WES) at the Broad Institute (Cambridge, MA), initiating the largest and most ethnically diverse genetic study of epilepsy to date. The primary epilepsy phenotypes for Epi25 are based on strict standards agreed upon by the epilepsy community. The epilepsy cases contributed by Epi25 sites can be broadly defined as genetic generalized epilepsy (GGE), non-acquired focal epilepsy (NAFE), epileptic encephalopathies (EE), and lesional focal epilepsies. More information about eligibility criteria and phenotyping forms for Epi25, as well as the contributing centers, can be found here: epi-25.org The genomic data will be analyzed iteratively to identify genes and variants that explain these types of epilepsy. Summary clinical data compiled in the Epi25 clinical database will allow retrospective phenotypic analyses of groups of subjects with common genomic variant(s).

  Study phs001489