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• Laboratory of Applied Cancer Genomics team

  Dac EGAC00001002546

• Radboud University Medical Centre FSHD Clinical Team

  Dac EGAC00001003305

• How mitochondrial DNA research can benefit from data reuse through EGA?

  Mitochondria are the only cellular organelles harbouring their own DNA, which encodes for proteins essentials in its respiration process. Despite its discovery in 1960, Mitochondrial DNA is often overlooked compared to nuclear DNA. Indeed, not all sequencing technologies capture a good representation of mtDNA (mitochondrial DNA). Recently, Ed Reznik's team (The Ed Reznik Lab | Memorial Sloan Kettering Cancer Center) carried out a massive analysis and reanalysis of single cells WGS (whole genome sequencing) produced with an amplification-free protocol (Direct library prep, DLP). As they demonstrated in the paper Single-cell mtDNA dynamics in tumors is driven by coregulation of nuclear and mitochondrial genomes - PMC, DLP is more effective in catching mtDNA compared to classical single-cell sequencing. These data allowed the team to unravel mtDNA dynamics in tumoral and normal samples, highlighting how mtDNA and nuclear DNA are co-regulated and their ratio is critical for phenotype. Data reuse to achieve the greatest results For this project, Reznik's team re-used data from 3 studies stored at the European Genome-phenome Archive (EGAS00001006343, EGAS00001004448 and EGAS00001003190) that comprised a total of 602 datasets. All of them were initially produced by the teams of Sam Aparicio and Sohrab P. Shah at the Memorial Sloan Kettering Cancer Centre, where Ed Reznik is a promising group leader. This demonstrates, once again, that networking, collaboration and data sharing can achieve the greatest results when coupled with innovative and smart ideas. At the EGA we are proud to provide the scientific community with an infrastructure to enable all those very smart ideas out there to find the right data to be tested.

  Blog mitochondrial-dna-research

• Single-cell Multiomics Data Team

  Dac EGAC00001003380

• SGI Single-cell team GC Data Access Committee

  Dac EGAC00001001420

• Long-read trio sequencing Team Data Access Commitee

  Dac EGAC00001001532

• UZ Ghent Prostate Cancer Team Data Access Committee

  Dac EGAC00001001608

• Single-cell Omics Glioma Team Data Access Committee

  Dac EGAC00001002256

• Refractory Classic Hodgkins Lymphoma (cHL) sWGS

  Associated with the study: Blood-based Monitoring of Relapsed/Refractory Hodgkin Lymphoma Patients Predict Responses to Anti-PD-1 Treatment. 26 ctDNA Samples from 4 patients followed longitudinally. sWGS performed for copy number aberration (CNA) analysis.

  Dataset EGAD50000001163

• RNA-seq of tumor samples from clear cell renal cell carcinoma patients included in the Translational Program of the NIVOREN GETUG-AFU-26 trial.

  DAC for RNA-seq of tumor samples from clear cell renal cell carcinoma patients included in the Translational Program of the NIVOREN GETUG-AFU-26 trial.

  Dac EGAC50000000627

• Signal Transduction Team ICR (2011) Data Access Committee

  Dac EGAC00001000040

• INSERM U981 Team : Genomics of Non-Melanoma Skin Cancer

  Dac EGAC00001001644

• Single-cell Multiomics Clonal Hematopoiesis Team Data Access Committee

  Dac EGAC00001002735

• Queen Mary University of London Information Security Management Team

  Dac EGAC00001003071

• Queen Mary University of London Information Security Management Team

  Dac EGAC00001003083

• Characterization of chromatin accessibility in metastatic prostate cancer

  The development of resistance to second-generation AR-signaling inhibitors (ARSIs) and progression to metastatic castrate-resistant prostate cancer (mCRPC) represents a huge obstacle to the improvement of patients’ clinical outcomes. Lineage plasticity is a common mechanism that drives the development of mCRPC by changing chromatin conformation at regulatory elements affecting downstream gene activity. ATAC-seq is a popular technique that measures accessible chromatin regions. To better understand of potential epigenomic mechanisms of ARSI resistance in prostate cancer, in this study, we performed ATAC-seq on 70 mCRPC tissue biopsies from the SU2C/PCF West Coast Dream Team (WCDT) cohort.

  Study EGAS00001006698

• Queen Mary University of London Information Security Management Team

  Dac EGAC00001002266

• dataset1

  Contains 14 control samples and 26 case samples.

  Dataset EGAD00001008576

• Chemotherapy induces myeloid-driven spatial T-cell exhaustion in ovarian cancer

  Gene expression profiles of single cells from 26 chemo-naïve and IDS tumor tissue and ascites samples from 17 HGSC patients

  Study EGAS50000000607

• BLUEPRINT release August 2015, ChIP-Seq for CD8-positive, alpha-beta T cell, on genome GRCh38

  ChIP-Seq data for 5 CD8-positive, alpha-beta T cell sample(s). 26 run(s), 26 experiment(s), 26 alignment(s) on human genome GRCh38. Part of BLUEPRINT release August 2015. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20150820/homo_sapiens/README_chipseq_analysis_ebi_20150820

  Dataset EGAD00001001513

• “Human population genetics” team (Muséum national d’Histoire naturelle, Paris, France)

  Dac EGAC00001000147

• Cancer Biomarkers team at The ICR DAC

  DAC for Cancer Biomarkers

  Dac EGAC50000000200

• TAKEDA DAC

  Team of TAKEDA DAC: Members: - Amit - Vinu - Jay - Sachin

  Dac EGAC50000000779

• The Dutch retinoblastoma research team from the VU University medical center

  Dac EGAC00001000431

• Spatiotemporal single cell transcriptomic analysis of human gut macrophages team commitee

  Dac EGAC00001002166