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• Type 2 Diabetes Genetic Exploration by Next-Generation Sequencing in Multi-Ethnic Samples (T2D-GENES) Follow-Up Study: BioMe Biobank Program

  The ~52,000 sample Type 2 Diabetes Exome Sequencing project is a collaboration of six consortia with various funding mechanisms that have joined together to investigate genetic variants for type 2 diabetes (T2D) using the largest T2D case/control sample set compiled to date. This includes samples from: Type 2 Diabetes Genetic Exploration by Next-generation sequencing in Multi-Ethnic Samples (T2D-GENES) Genetics of Type 2 Diabetes (GoT2D) Exome Sequencing Project (ESP) Slim Initiative in Genomic Medicine for the Americas (SIGMA) Lundbeck Foundation Centre for Applied Medical Genomics in Personalised Disease Prediction, Prevention, and Care (LuCAMP) Progress in Diabetes Genetics in Youth (ProDIGY) This data generated from the BioMe Biobank cohort was part of the T2D-GENES (Type 2 Diabetes Genetic Exploration by Next-generation sequencing in multi-Ethnic Samples) consortium, which is a NIDDK-funded international research consortium that seeks to identify genetic variants for type 2 diabetes (T2D) through multiethnic sequencing studies. The T2D-GENES Project is a multi-ethnic sequencing study designed to assess whether less common variants play a role in T2D risk and to assess similarities and differences in the distribution of T2D risk variants across ancestry groups. The individuals were obtained from over 20 cohorts across the 6 consortia that are listed in Table 1. The strategy was to perform deep exome sequencing of individuals, 24,991 with T2D and 24,953 controls, divided among five ancestry groups: Europeans, East Asians, South Asians, American Hispanics, and African Americans. The T2D-GENES, ProDIGY and SIGMA studies, sequencing was performed at the Broad Institute using the Agilent v2 capture reagent or Illumina Rapid Capture on Illumina HiSeq machines. Please note that while we summarize the full sample list in publications and below, two of the cohorts below are not in dbGAP, due to the samples not being consented for deposition. This includes the Kooperative Gesundheitsforschung in der Region Augsburg (KORA) study and Lundbeck Foundation Centre for Applied Medical Genomics in Personalised Disease Prediction, Prevention, and Care (LuCamp) study. The Exome Sequencing Project (ESP) was deposited in dbGAP as part of their initial study and the phs numbers for that project can be found here: https://esp.gs.washington.edu/drupal/dbGaP_Releases. Table 1. 52,000 sample T2D Case/Control Whole Exome Sequencing Studies Ancestry Consortia Study Countries of Origin # Cases # Controls African American T2D-GENES Project 1 Jackson Heart Study US 502 527 African American T2D-GENES Project 1 Wake Forest School of Medicine Study US 518 532 African American ESP Exome Sequencing Project (ESP) US 467 1374 African American T2D-GENES Follow-Up Study BioMe Biobank Program (BioMe) US 1294 1254 East Asian T2D-GENES Project 1 Korea Association Research Project Korea 526 561 East Asian T2D-GENES Project 1 and Follow-Up Study Singapore Diabetes Cohort Study; Singapore Prospective Study Program Singapore (Chinese) 1486 1568 East Asian T2D-GENES Follow-Up Study Korea SNUH South Korea 450 475 East Asian T2D-GENES Follow-Up Study Research Studies in Hong Kong (Hong Kong) Hong Kong 493 485 European T2D-GENES Project 1 Ashkenazi US, Israel 506 355 European T2D-GENES Project 1 Metabolic Syndrome in Men Study (METSIM) Finland 484 498 European GoT2D Finland-United States Investigation of NIDDM Genetics (FUSION) Study Finland 472 476 European GoT2D Kooperative Gesundheitsforschung in der Region Augsburg (KORA) Germany 97 90 European GoT2D UK Type 2 Diabetes Genetics Consortium (UKT2D) UK 322 320 European GoT2D Malmö-Botnia Study Finland, Sweden 478 443 European LuCamp Lundbeck Foundation Centre for Applied Medical Genomics in Personalised Disease Prediction, Prevention, and Care (LuCamp) Denmark 997 997 European ESP Exome Sequencing Project (ESP) US 390 2843 European T2D-GENES Follow-Up Study Genetics of Diabetes and Audit Research Tayside Study (GoDARTS) Scotland, UK 960 966 European T2D-GENES Follow-Up Study Framingham Heart Study (FHS) US 396 596 Hispanic T2D-GENES Project 1 San Antonio Family Heart Study, San Antonio Family Diabetes/ Gallbladder Study, Veterans Administration Genetic Epidemiology Study, and the Investigation of Nephropathy and Diabetes Study Family Component US 272 218 Hispanic T2D-GENES Project 1 and SIGMA v2 Starr County, Texas US 1762 1738 Hispanic SIGMA v1 Mexico City Diabetes Study Mexico 281 549 Hispanic SIGMA v1 and SIGMA v2 Multiethnic Cohort (MEC) US 1476 1443 Hispanic SIGMA v1 and SIGMA v2 UNAM/INCMNSZ Diabetes Study (UIDS) Mexico 1998 1977 Hispanic SIGMA v1 and SIGMA v2 Diabetes in Mexico Study (DMS) Mexico 1522 1546 Multiethnic ProDIGY Treatment Options for Type 2 Diabetes in Adolescents and Youth (TODAY) US 3097 0 Multiethnic ProDIGY SEARCH for Diabetes in Youth (SEARCH) US 553 0 South Asian T2D-GENES Project 1 London Life Sciences Population Study (LOLIPOP) UK (Indian Asian) 531 538 South Asian T2D-GENES Project 1 and Follow-Up Study Singapore Indian Eye Study Singapore (Indian Asian) 1640 1478 South Asian T2D-GENES Follow-Up Study Pakistan Genomic Resource (PGR) Pakistan 914 932 The BioMe Biobank study contributed 1294 cases and 1254 controls to T2D-GENES Follow-Up Study.

  Study phs001490

• Type 2 Diabetes Genetic Exploration by Next-generation Sequencing in Multi-Ethnic Samples (T2D-GENES) Follow up Study: Pakistan Genomic Resource (PGR)

  The ~52,000 sample Type 2 Diabetes Exome Sequencing project is a collaboration of six consortia with various funding mechanisms that have joined together to investigate genetic variants for type 2 diabetes (T2D) using the largest T2D case/control sample set compiled to date. This includes samples from: Type 2 Diabetes Genetic Exploration by Next-generation sequencing in Multi-Ethnic Samples (T2D-GENES) Genetics of Type 2 Diabetes (GoT2D) Exome Sequencing Project (ESP) Slim Initiative in Genomic Medicine for the Americas (SIGMA) Lundbeck Foundation Centre for Applied Medical Genomics in Personalised Disease Prediction, Prevention, and Care (LuCAMP) Progress in Diabetes Genetics in Youth (ProDIGY) This data generated from the Pakistan Genomic Resource (PGR) cohort was part of the T2-GENES (Type 2 Diabetes Genetic Exploration by Next-generation sequencing in multi-Ethnic Samples) consortium, which is a NIDDK-funded international research consortium that seeks to identify genetic variants for type 2 diabetes (T2D) through multiethnic sequencing studies. The T2D-GENES Project is a multi-ethnic sequencing study designed to assess whether less common variants play a role in T2D risk and to assess similarities and differences in the distribution of T2D risk variants across ancestry groups. The individuals were obtained from over 20 cohorts across the 6 consortia that are listed in Table 1. The strategy was to perform deep exome sequencing of individuals, 24,991 with T2D and 24,953 controls, divided among five ancestry groups: Europeans, East Asians, South Asians, American Hispanics, and African Americans. The T2D-GENES, ProDIGY and SIGMA studies, sequencing was performed at the Broad Institute using the Agilent v2 capture reagent or Illumina Rapid Capture on Illumina HiSeq machines. Please note that while we summarize the full sample list in publications and below, two of the cohorts below are not in dbGAP, due to the samples not being consented for deposition. This includes the Kooperative Gesundheitsforschung in der Region Augsburg (KORA) study and Lundbeck Foundation Centre for Applied Medical Genomics in Personalised Disease Prediction, Prevention, and Care (LuCamp) study. The Exome Sequencing Project (ESP) was deposited in dbGAP as part of their initial study and the phs numbers for that project can be found here: https://esp.gs.washington.edu/drupal/dbGaP_Releases. Table 1. 52,000 sample T2D Case/Control Whole Exome Sequencing Studies Ancestry Consortia Study Countries of Origin # Cases # Controls African American T2D-GENES Project 1 Jackson Heart Study US 502 527 African American T2D-GENES Project 1 Wake Forest School of Medicine Study US 518 532 African American ESP Exome Sequencing Project (ESP) US 467 1374 African American T2D-GENES Follow-Up Study BioMe Biobank Program (BioMe) US 1297 1256 East Asian T2D-GENES Project 1 Korea Association Research Project Korea 526 561 East Asian T2D-GENES Project 1 and Follow-Up Study Singapore Diabetes Cohort Study; Singapore Prospective Study Program Singapore (Chinese) 1486 1568 East Asian T2D-GENES Follow-Up Study Korea SNUH South Korea 450 475 East Asian T2D-GENES Follow-Up Study Research Studies in Hong Kong (Hong Kong) Hong Kong 493 485 European T2D-GENES Project 1 Ashkenazi US, Israel 506 355 European T2D-GENES Project 1 Metabolic Syndrome in Men Study (METSIM) Finland 484 498 European GoT2D Finland-United States Investigation of NIDDM Genetics (FUSION) Study Finland 472 476 European GoT2D Kooperative Gesundheitsforschung in der Region Augsburg (KORA) Germany 97 90 European GoT2D UK Type 2 Diabetes Genetics Consortium (UKT2D) UK 322 320 European GoT2D Malmö-Botnia Study Finland, Sweden 478 443 European LuCamp Lundbeck Foundation Centre for Applied Medical Genomics in Personalised Disease Prediction, Prevention, and Care (LuCamp) Denmark 997 997 European ESP Exome Sequencing Project (ESP) US 390 2843 European T2D-GENES Follow-Up Study Genetics of Diabetes and Audit Research Tayside Study (GoDARTS) Scotland, UK 960 966 European T2D-GENES Follow-Up Study Framingham Heart Study (FHS) US 396 596 Hispanic T2D-GENES Project 1 San Antonio Family Heart Study, San Antonio Family Diabetes/ Gallbladder Study, Veterans Administration Genetic Epidemiology Study, and the Investigation of Nephropathy and Diabetes Study Family Component US 272 218 Hispanic T2D-GENES Project 1 and SIGMA v2 Starr County, Texas US 1762 1738 Hispanic SIGMA v1 Mexico City Diabetes Study Mexico 281 549 Hispanic SIGMA v1 and SIGMA v2 Multiethnic Cohort (MEC) US 1476 1443 Hispanic SIGMA v1 and SIGMA v2 UNAM/INCMNSZ Diabetes Study (UIDS) Mexico 1998 1977 Hispanic SIGMA v1 and SIGMA v2 Diabetes in Mexico Study (DMS) Mexico 1522 1546 Multiethnic ProDIGY Treatment Options for Type 2 Diabetes in Adolescents and Youth (TODAY) US 3097 0 Multiethnic ProDIGY SEARCH for Diabetes in Youth (SEARCH) US 553 0 South Asian T2D-GENES Project 1 London Life Sciences Population Study (LOLIPOP) UK (Indian Asian) 531 538 South Asian T2D-GENES Project 1 and Follow-Up Study Singapore Indian Eye Study Singapore (Indian Asian) 1640 1478 South Asian T2D-GENES Follow-Up Study Pakistan Genomic Resource (PGR) Pakistan 903 930 The PGR study contributed 903 cases and 930 controls to T2D-GENES Follow-Up Study.

  Study phs001552

• HELIUS DAC The HELIUS data are owned by the Amsterdam University Medical Centers, location AMC in Amsterdam, The Netherlands. To allow sharing of microbiome data collected in HELIUS with (inter)national researchers, 16s rRNA sequence analysis has been stored at the European genome-phenome archive (EGA; accession code EGAD00001004106). This requires that access needs to be granted, also because the HELIUS data are stored with relevant phenotypical variables. Access is granted to all researchers affiliated with an internationally recognized research institution who request to use the HELIUS data within the EGA context, after having signed the data transfer agreement. Any researcher can request the data by submitting a proposal to the HELIUS Executive Board as outlined at http://www.heliusstudy.nl/en/researchers/collaboration, by email: heliuscoordinator at amsterdamumc dot nl. The HELIUS Executive Board will check proposals if they do not conflict with ethical approvals and informed consent forms of the HELIUS study.

  Dac EGAC00001000895

• Frequent mutation of the major cartilage collagen gene, COL2A1, in chondrosarcoma

  Chondrosarcoma (CHS) is a heterogeneous collection of malignant bone tumours and is the second most common primary malignancy of bone after osteosarcoma. Recent work has identified frequent, recurrent mutations in IDH1/2 in nearly half of central CHS. However, there has been little systematic genomic analysis of this tumour type and thus the contribution of other genes is unclear. Here we report comprehensive genomic analyses of 49 cases of CHS. We identified hypermutability of the major cartilage collagen COL2A1 with insertions, deletions and rearrangements identified in 37% of cases. The patterns of mutation were consistent with selection for variants likely to impair normal collagen biosynthesis. In addition we identified mutations in IDH1/2 (59%), TP53 (20%), the RB1 pathway (27%) and hedgehog signaling (22%).

  Dataset EGAD00001000358

• Counts: Brain transcriptome of hereditary cerebral haemorrhage with amyloidosis–Dutch type (HCHWA-D)

  These are the log2CPM (log2 counts per million) fragments per gene counts associated with the BAM files in EGAD00001003806, in tab separated format. Counts for 36 postmortem brain samples from 9 non-demented control subjects and 9 Hereditary cerebral hemorrhage with amyloidosis-Dutch type subjects are included (1 Frontal cortex sample and 1 Occipital cortex sample per subject). RNA samples were depleted for ribosomal RNA with the Ribo Zero Gold Human kit (Illumina) and strand specific RNA-Seq libraries were generated. Paired-end sequencing was performed on a HiSeq2500 Illumina system (2x50bp reads). Alignments were performed using GSNAP v2014-12-23 with setting "--npaths 1" on GRCh38 reference genome without the alternative contigs. Fragment per gene counting was performed using HTSeq-count v0.6.1p1 with setting "--stranded reverse". The gene annotation used for quantification were UCSC RefSeq genes for GRCh38 downloaded on 2015-07-13.

  Dataset EGAD00010001457

• UK_RCC_GWAS

  Renal cell carcinoma (RCC) cases comprised adult patients with histologically proven RCC were collected through two sources within the UK. First, 856 cases from SORCE, a MRC collection of surgically treated RCC cases ascertained through UK clinical oncology centres. Second, 189 RCC cases collected through the ICR and Royal Marsden NHS Hospitals Trust. Cases included 590 clear cell carcinomas (CCCs), 42 papillary carcinomas (PCs), 33 chromophobe carcinomas (CCs) and 19 mixed or other histological subtypes. DNA was extracted from EDTA-venous blood samples using the conventional methods and quantified using PicoGreen (Invitrogen). Cases were genotyped using the Human OmniExpress-12 BeadChip according to the manufacturer's recommendations (Illumina Inc, San Diego, CA, USA). After strict QC, 944 cases were retained. Data provided in plink format. Controls used were data from the Wellcome Trust Case Control Consortium 2 (WTCCC2) 1958 birth cohort and the UK Blood Service Control Group (available as EGAS00000000028). 

  Dataset EGAD00010002310

• RNA sequencing from patient-derived intestinal organoids

  uman duodenal tissues for establishing organoid cultures used in this study were sourced from de-identified surgical specimens (n = 3) of the duodenum obtained from patients who had undergone biopsy procedures unrelated to CeD at Tampere University Hospital. The protocol was approved by the Ethics Committee of Tampere University Hospital, Tampere, Finland (ETL code R18082). RNA from the duodenal organoids was isolated using an RNeasy Kit (Qiagen, Hilden, Germany) following the manufacturer’s instructions. RNA purity and concentration were measured using a NanoDrop One spectrophotometer (NanoDrop Technologies, Wilmington, Delaware, USA). Preparation of the RNA library and transcriptome sequencing was conducted by Novogene Co., LTD (Cambridge, UK). Messenger RNA was purified from total RNA using polyA selection and subjected to library construction. Sequencing was performed on an Illumina platform, and 150 bp paired-end reads were generated.

  Dataset EGAD50000000492

• Single-nuclei RNA sequencing of pheochromocytoma and paraganglioma arising from germline SDHB mutations

  10x genomics single-nuclei RNA sequencing of 9 SDHB-deficient non-metastatic and metastatic pheochromocytoma and paraganglioma. snRNA-seq was performed using the ‘Frankenstein’ protocol (dx.doi.org/10.17504/protocols.io.bqxymxpw). Briefly, nuclei were extracted from frozen tissues and subjected to fluorescence-activated nuclei sorting (FANS) using 4′,6-diamidino-2-phenylindole (DAPI). Sorting was performed using a BD FACSaria 2 instrument, sorting between 3000 and 10,000 nuclei per sample, capturing both diploid and tetraploid populations. FAN-sorted nuclei were immediately processed using either the 10x Chromium Single Cell 5’ (PN-1000006, 4 samples) or 3’ (PN-1000075, 4 samples) Library & Gel Bead Kit (10x Genomics, USA). Once processed, snRNA-seq libraries were sequenced on the Illumina Nova-Seq 6000 (Illumina, USA) using 150bp paired-end sequencing. This dataset contains raw sequencing reads in FASTQ format.

  Dataset EGAD50000000505

• Cergentis FFPE-TLC sequencing of colorectal carcinoma

  In this study, formalin-fixed paraffin-embedded targeted locus capture (FFPE-TLC) sequencing is used as a novel technology for targeted detection of tumor-specific genomic structural variants (SVs) in the primary tumor of 29 colorectal cancer patients with metastatic disease. The tumor region was macrodissected and sequenced for 29 patients, and the "normal" region of the same slide was macrodissected and sequenced for 8 of these patients. SVs were found in the common fragile site (CFS)-associated genes MACROD2, PRKN, FHIT and WWOX as well as SVs caused by three LINE transposable elements. Tumor-specificity of selected SVs was independently verified by droplet digital PCR of tumor tissue DNA and their applicability as plasma circulating tumor DNA biomarkers was demonstrated. This dataset contains the hg19 reference alignment of the FFPE-TLC sequences for all 29 colorectal cancers and 8 adjacent normals.

  Dataset EGAD50000000618

• Whole genome and transcriptome sequencing of cancer of unknown primary tumours

  Whole genome and transcriptome sequencing of cancer of unknown primary tumours was used to determine yield of clinical biomarkers for a molecular guided trial or for resolving cancer type of origin. This study includes profiling of germline DNA and tumour DNA and RNA by whole genome and transcriptome sequencing. All samples are in BAM format aligned with GRCh38 reference genome. This dataset includes: 1. Whole genome sequencing (WGS) of 78 cancer of unknown primary tumour samples and 73 matched germline DNA. 2. Whole transcriptome sequencing (WTS) of 69 cancer of unknown primary tumour samples (matched to WGS cases) 3. Whole genome sequencing of 22 cell-free DNA samples from cancer of unknown primary patients and matched Germaine DNA(8 samples matched to tumour WGS)

  Dataset EGAD50000000656

• Raw sequencing data from chromosome conformation capture, RNA sequencing and chromatin assays in human primary monocytes

  This dataset contains raw sequencing data from eQTL Capture Hi-C, ATAC-seq and RNA-seq experiments in monocytes isolated from 34 healthy male donors, as well as from Hi-C, 4C-seq and CTCF ChIP-seq in subsets of individuals. The data are released as paired-end Illumina FASTQ files. Hi-C and Capture Hi-C used DpnII digestion and Tn5-based low-input library preparation. In Capture Hi-C, this was followed by targeted capture with custom-designed biotinylated RNA probes targeting ~1100 eQTL regions. ATAC-seq was performed on PFA-fixed cells using a digitonin-based protocol. 4C-seq and CTCF ChIP-seq were performed using standard protocols.

  Dataset EGAD50000001116

• EuroTARGET is a European study on mRCC, collecting clinical data, germline DNA, and tumor samples.

  For patients with metastatic renal cell cancer (mRCC), treatment choice is mainly based on clinical parameters. With many treatments available and the limited response to treatment and associated toxicities, there is much interest in identifying better biomarkers for personalized treatment. EuroTARGET aims to identify and characterize host- and tumor-related biomarkers for prediction of response to tyrosine kinase inhibitor therapy in mRCC. Here, we describe the EuroTARGET mRCC patient cohort.

  Study EGAS50000000798

• Long-read whole genome sequencing as a tool for variant detection in inherited retinal dystrophies

  Advances in whole-genome sequencing (WGS) have significantly enhanced our ability to detect genomic variants underlying inherited diseases. In this study, we performed long-read WGS on 24 patients with inherited retinal dystrophies (IRDs) to validate the utility of nanopore sequencing in detecting genomic variations. We confirmed the presence of all previously detected variants and demonstrated that this approach allows for precise refinement of structural variants (SVs). Furthermore, we could perform genotype phasing by sequencing only the probands, confirming variants were inherited in trans. Moreover, nanopore sequencing enabled the detection of complex variants, such as transposon insertions and structural rearrangements. This comprehensive assessment illustrates the power of long-read sequencing in capturing diverse forms of genomic variation and in improving diagnostic accuracy in IRDs.

  Dataset EGAD50000001238

• Cannabis impacts female fertility as evidenced by an in vitro investigation and a case-control study

  Single immature human oocytes were cultured in vitro (24h) either under control, THC1 () or THC2 (100 ng/mL Δ9-THC, 50 ng/mL 11-OH-THC, 200 ng/mL 11-COOH-THC) conditions. Oocytes were collected and subjected to SmartSeq v4 cDNA conversion, library prep (Nextera XT)), and sequencing (NovaSeq S4). The goal of this study was to determine the impact of THC on the human oocyte transcriptome.

  Study EGAS50000001052

• Dataset for study Genome-wide gene expression analysis following CRISPRi of transposable elements

  Transposable elements (TEs), once regarded as parasitic genomic remnants, are now recognized as key regulators of gene expression and genome evolution, yet the functional specificity of individual TE subfamilies remains largely unexplored. This dataset investigates the transcriptional consequences of targeted repression of MER57E3 and LTR10B2 elements using CRISPR interference (CRISPRi) in human induced pluripotent stem cells (hiPSCs). hiPSCs expressing CRISPRi machinery (n = 2 biological replicates) were transduced with guide RNAs targeting individual or grouped copies of MER57E3 and LTR10B2, as well as the ZNF678 promoter or a lacZ non-targeting control. Transduced cells were subsequently differentiated into neural progenitor cells (NPCs), and total RNA was extracted for mRNA library preparation and sequencing. The dataset comprises 24 single-end mRNA-seq FASTQ files generated from these NPCs and wild-type controls.

  Dataset EGAD00001015689

• Profiling the genomic landscape and evolutionary history of polyploid giant cancer cells in undifferentiated pleomorphic sarcomas

  In this study, we characterise PGCCs in ten pleomorphic sarcomas and use topographic single-cell DNA sequencing (scDNA-seq) to investigate their genomic landscape. We selected PGCCs based on their nuclear morphology, including mononucleated or multinucleated bizarre, misshapen nuclei, and analysed them at single-cell resolution. Histopathological analysis showed that PGCCs were often randomly distributed throughout the tumour and did not appear in clusters, suggesting that they arise de novo rather than through clonal expansion. scDNA-seq revealed that PGCCs originate from the dominant tumour population and exhibit extensive copy number heterogeneity, either due to subsequent or ongoing chromosomal instability. Both clonal and subclonal chromothripsis-like events were identified in PGCCs, indicating that chromothripsis is a key driver of heterogeneity in these cells and is linked to multinucleation rather than mononuclear PGCC formation.

  Dataset EGAD50000002084

• Hashed data from three immortalized fibroblastic reticular cells (iFRCs)

  Co-culture experiments of primary lymphoid and DLBCL-derived immortalized FRCs (iFRC) followed by scRNA-seq. iFRCs as well as lymphocytes from DLBCL samples (n=3) were harvested after 24h of incubation and different experimental conditions were multiplexed using in-house cell multiplexing oligonucleotides (CMOs; full list of barcodes provided in Table S9). Cells were incubated with CMOs at a final concentration of 1.8 μM for 20 minutes on ice, followed by four washes with PBS (centrifugation at 400 × g for 3 minutes at 4 °C). Single-cell RNA sequencing (scRNA-seq) and multiplexing libraries were prepared using the 10x Genomics Single Cell 3′ Gene Expression v4 assay, according to the manufacturer’s protocol. Sequencing was performed on an Illumina NovaSeq 6000 platform using paired-end 100 bp reads on an S4 flow cell.

  Dataset EGAD50000001779

• PTEN homozygous deletion is a negative prognostic factor in Tumor Treating Fields-treated glioblastoma, IDH wildtype patients

  This study investigates genomic determinants of outcome in glioblastoma, IDH-wildtype patients treated with Tumor Treating Fields (TTFields) in addition to standard radiochemotherapy. Tumor tissue from primary glioblastoma at initial diagnosis was profiled using the Illumina TruSight Oncology 500 (TSO500) targeted sequencing panel to characterise somatic alterations. The overarching goal is to provide exploration of genomic determinants of survival and treatment response in TTFields-treated glioblastoma, IDH-wildtype.

  Study EGAS50000001469

• Circulating Tumor DNA Analysis Profiles of Repotrectinib in NTRK fusion–positive advanced solid tumors: a phase 1/2 trial

  The dataset contains circulating tumor DNA (ctDNA) profiles from frozen plasma samples of 593 patients from the TRIDENT-1 clinical trial. Plasma was processed with centrifugation and automated liquid handling systems, and cell-free DNA was extracted using the Qiagen QIAsymphony platform. ctDNA libraries were constructed with the Guardant360 2.11 assay, which used targeted, hybridization-based capture and barcoding of cfDNA fragments for digital analysis, followed by high-throughput sequencing on the Illumina NextSeq 550 instrument. Sequencing data were processed and interpreted using the Bioinformatics Pipeline (BIP v3.5.2 or later) for variant calling and quantification and managed within LabVantage LIMS (v3.7 or later) to support sample tracking and workflow integration. Aligned read files are provided in bam and bai formats.

  Dataset EGAD50000002249

• Whole Genome Sequencing from patients with multiple myeloma treated with BCL2 inhibitor based treatment

  Samples was collected at the Mayo Clinic. MM tumor samples were enriched using the StemCell EasySep Human CD138 positive selection kit II (StemCell, Cambridge, MA). DNA from CD138+ MM cell (tumor) or peripheral blood samples (germline control) at Mayo Clinic (Rochester or Arizona) underwent WGS. For samples collected at Mayo Clinic Rochester, library preparation was completed using the NEB Ultra II (New England Biolabs, Ipswich, MA) and the Nextera Flex systems (Illumina, San Diego, CA) and sequenced at the Mayo Clinic Genome Analysis Core with an approximate depth of 30X for tumor samples and 60X for the germline control. For samples collected at Mayo Clinic Arizona, Novogene was used for WGS following random shearing of the DNA, end-repairs, A-tailed and ligated with Illumina adapters. Sequencing was performed on the Illumina Novaseq 6000 sequencer Reference Genome: GRCh38.

  Dataset EGAD50000002132

• Effect of inflammation on human hematopoietic stem cells in a xenograft model

  Transcriptional heterogeneity in cord blood HSCs was investigated by 10X single-cell Multiome (RNA+ATAC). To investigate the effect of inflammatory stress on human HSC, 10X single-cell Multiome profiling of cells from xenografted mice recovered from repeated inflammatory challenge was performed. To investigate transmission of inflammatory stress-related molecular programs from HSC to their progeny, 10X single-cell RNA sequencing was performed on committed progenitor and myeloid cells from the same mice.

  Study EGAS50000001624

• Evaluation of protocols for rRNA depletion-based RNA sequencing of nanogram inputs of mammalian total RNA

  Next generation RNA-Sequencing (RNA-seq) is a flexible approach that can be applied to e.g. global quantification of transcript expression, the characterization of RNA structure such as splicing patterns and profiling of expressed mutations. Many RNA-seq protocols require up to microgram levels of total RNA input amounts to generate high quality data, and thus remain impractical for the limited starting material amounts typically obtained from rare cell populations, such as those from early developmental stages or from laser micro-dissected clinical samples. Here, we present an assessment of the contemporary ribosomal RNA depletion-based protocols, and identify those that are suitable for inputs as low as 1-10 ng of intact total RNA and 100-500 ng of partially degraded RNA from formalin-fixed paraffin-embedded tissues.

  Dataset EGAD00001005316

• Combination Immune Checkpoint Inhibition in Australian Rare Cancers_WES

  Combination immune checkpoint inhibition (ICI) with anti-CTLA-4 and anti-PD-1 blockade has demonstrated significant clinical activity across tumour types. Rare cancer patients have limited treatment options due to the scarcity of studies of novel treatment options, so they are often offered chemotherapies untested in their disease. ONJ2016-001/CA209-538 is a prospective, multicentre clinical trial of combination ICI (ipilimumab and nivolumab) in patients with advanced rare cancers, including biliary tract, adrenocortical, rare gynaecological and neuroendocrine cancers (https://clinicaltrials.gov/ct2/show/NCT02923934). The primary endpoint is clinical benefit rate (complete response + partial response + stable disease >3 months) by RECIST 1.1. This study involves generation and analysis of pre-treatment formalin fixed paraffin embedded (FFPE) tumour DNA sequencing data, paired with germline DNA sequencing data, to potentially identify genomic biomarkers that may associate with clinical benefit or other clinical efficacy / toxicity metrics.

  Dataset EGAD00001015465

• RNA-sequencing of a representative cohort of 209 AML cases

  Sample libraries were prepped using 500 ng of input RNA according to the KAPA RNA HyperPrep Kit with RiboErase (HMR) (Roche) using Unique Dual Index adapters (Integrated DNA Technologies, Inc.). Amplified sample libraries were paired-end sequenced (2x100 bp) on the Novaseq 6000 platform (Illumina) and aligned against the human genome (hg19) using STAR v2.5.4b2.

  Dataset EGAD00001007581

• WGS of peripheral blood leukocytes from patients with Li-Fraumeni syndrome

  We performed whole genome sequencing on 84 LFS family members from 47 families: 22 with wildtype TP53 and 62 with variant TP53. The variant TP53 cohort consists of 49 individuals who developed cancer and 13 individuals who remain cancer-free; 34 were from 13 families with 2-4 individuals sequenced within a given family and the remaining 28 had no family members sequenced. The wildtype cohort consists of 14 individuals who developed cancer and 8 individuals who are cancer-free, from 6 families.

  Dataset EGAD00001010200