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• Comprehensive Transcriptional Analysis of Early Stage Urothelial Carcinoma using whole transcriptome sequencing

  The expression profile and sequence variants of 476 early stage urothelial carcinoma were studied using whole transcriptome sequencing. RNA-Seq libraries were prepared by Ribo-Zero treatment of total-RNA followed by library preparation using ScriptSeq (both Epicentre/Illumina). RNA-Seq libraries were paired-end sequenced (2x 101 bp) on Illumina HiSeq 2000 and the resulting fastq files were processed using tools from the Genome Analysis Toolkit (GATK and from the Tuxedo suite. Access to the sequence data (mapped and un-mapped bam and vcf files), containing person identifying information, needs signature on a controlled access form, and can be accessed at The European Genome-phenome Archive (EGA) following request. An expression matrice of FPKM values are available without restriction at ArrayExpress (E-MTAB-4321).

  Study EGAS00001001236

• Radiation-induced gliomas represent H3-/IDH-wild type pediatric gliomas with recurrent PDGFRA amplification and loss of CDKN2A/B

  Long-term complications such as radiation-induced second malignancies occur in a subset of patients following radiation-therapy, particularly relevant in pediatric patients due to the long follow-up period in case of survival. Radiation-induced gliomas (RIGs) have been reported in patients after treatment with cranial irradiation for various primary malignancies such as acute lymphoblastic leukemia (ALL) and medulloblastoma (MB). We perform comprehensive (epi-) genetic and expression profiling of RIGs arising after cranial irradiation for MB (n=23) and ALL (n=9). Our study reveals a unifying molecular signature for the majority of RIGs, with recurrent PDGFRA amplification and loss of CDKN2A/B and an absence of somatic hotspot mutations in genes encoding histone 3 variants or IDH1/2, uncovering diagnostic markers and potentially actionable targets.

  Study EGAS00001005243

• A benchmarking resource for NGS testing of cancer predisposition genes

  A benchmarking resource of 639 individuals, to assess the analytical sensitivity of cancer predisposition gene (CPG) testing.The dataset includes sequencing data generated using the TruSight Cancer Panel (TSCP) a targeted NGS assay for analysis of CPGs and orthogonally generated data supporting at least one pathogenic variant in a CPG for a total of 645 pathogenic CPG variants.The set of pathogenic CPG variants includes strong representation of some of the most challenging types of pathogenic variants, with 339 indels, including 16 complex indels and 24 insertions or deletions with length greater than 5bp, and 74 exon CNVs, including 23 single exon CNVs. There are 502 pathogenic variants in BRCA1 or BRCA2, making this an important first-line validation dataset for laboratories performing NGS testing of BRCA1 and BRCA2.

  Study EGAS00001002993

• Synthetic data - Genome in a Bottle

  In May, the National Institute of Standards and Technology (NIST) released its first genome in a bottle, a reference sample of DNA for validating human genome sequences. This so-called truth sequence comes from a decades-old sample donated by a Utah woman for (other) research purposes (NA12878 cell line), which, over the years, has been one of the most studied, and hence best-characterized, human samples. Seeing genomic medicine moving toward mainstream healthcare, researchers at NIST recognized the need for a reference human genome and assembled a private-public consortium in 2012 to create one. As detailed in a 2014 Nature Biotechnology paper (Nat. Biotechnol.32, 246–251, 2014), the group integrated and arbitrated among sequences from 14 data sets, five sequencing technologies, seven read mappers and three variant callers.

  Study EGAS00001005591

• Integrative Profiling of T790M Negative EGFR Mutated NSCLC Reveals Pervasive Lineage Transition and Therapeutic Opportunities

  We performed whole exome and transcriptome analysis of 59 first- and second-generation EGFR TKI resistant metastatic EGFR mutated patients to characterize and compare molecular alterations mediating resistance in T790M positive and negative disease. Transcriptomic analysis revealed ubiquitous loss of adenocarcinoma lineage gene expression in T790M negative tumors, orthogonally validated using multiplex immunohistochemistry. There was enrichment of genomic features such as TP53 alterations, 3q chromosomal amplifications, whole genome doubling and non-aging mutational signatures in T790M negative tumors. Almost half of resistant tumors were further classified as Immunehot, with clinical outcomes conditional on immune cell infiltration state and T790M status. Finally, using a Bayesian statistical approach, we explored how T790M negative and positive disease might be predicted using comprehensive genomic and transcriptomic profiles of treatment-naïve patients.

  Study EGAS00001005389

• Mullighan - PAX5-driven Subtypes

  Using integrated genomic analysis of 1.988 childhood and adult cases, we describe a revised taxonomy of B-cell acute lymphoblastic leukemia, which incorporates 23 subtypes defined by chromosomal rearrangements, sequence mutations, or heterogeneous genomic alterations. Two subtypes have frequent alterations of the B lymphoid transcription factor gene PAX5. One, PAX5alt, has diverse PAX5 alterations, and a second subtype is defined by a single mutation, PAX5 P80R. We show that P80R impairs B lymphoid development and promotes the development of B-ALL in vivo. These results demonstrate the utility of transcriptome sequencing to classify B-ALL and reinforce the central role of PAX5 as a checkpoint in B lymphoid maturation and leukemogenesis.

  Study EGAS00001003266

• Profiling of childhood neuroblastoma and the immune microenvironment by single-cell sequencing of RNA and TCR

  Neuroblastoma tumor cells and their tumor microenvironment are studied by single-cell RNA sequencing of primary neuroblastoma tumors and neuroblastoma-infiltrated tissues/metastases. Both diagnostic samples, taken pre-treatment and samples taken after induction chemotherapy at surgical resection and biopsies from relapse samples are included.  For a number of patients single-cell RNA sequencing of blood samples (controls) are included and additionally we performed single-cell T cell receptor sequencing (TCR) on the tumor and blood samples. With this study, we will focus on identifying differences in tumor cells and their (immune) microenvironment 1) before and after treatment or at relapse and 2) between primary tumors and infiltrated tissues/metastases. Moreover, with TCR sequencing we aim to unveil immune cell dynamics in patients with neuroblastoma.

  Study EGAS00001006823

• Microbiota 16S sequencing study in NSCLC patients eligible for surgery without neoadjuvant treatment

  18 non-small cell lung cancer patients eligible for surgery without neaodjuvant treatment were included in the study at Centre Jean Perrin (France). Patients did not take any antibiotics, food supplements or immunostimulants 2 months prior to inclusion. During surgery, patients underwent partial or complete lobectomy where samples of non-malignant lung tissue, peritumoural tissue and tumour were resected from the removed lobe. This was preceeded by the washing of the removed lobe and obtaining the broncho-alveolar lavage fluid. These four sample types were analysed by 16S sequencing in 17 from 18 patients. The study is a part of the project "Characterization of Microbiota (Intestinal, From Lungs, and Upper Airways) in Patients With Non-small Cell Lung Carcinoma: Exploratory Study " which is registered under ref. NCT03068663 (clinicaltrials.gov).

  Study EGAS00001004728

• RP-1843 Arcagen - Gastrointestinal rare cancers (GI)

  Arcagen is an EORTC/SPECTA pan-European project that aims to recruit 1000 rare cancer patients from different tumour domains of EURACAN. This study collected samples from advanced or metastatic rare cancer from patients older than 12, and analysed them using Foundation Medicine next-generation sequencing (NGS) panels (FoundationOne CDx for FFPE samples or FoundationOne Liquid CDx for blood samples). Here we are submitting two datasets that contain NGS files from gastrointestinal rare cancers (n=119): - Dataset 1 (32 patients): Mesothelioma of the peritoneum (n=21) and Pseudomyxoma peritonei/mucinous adenocarcinoma of the appendix (n=11) - Dataset 2 (87 patients): Intra-hepatic cholangiocarcinoma (n=47), Extra-hepatic, cholangiocarcinoma (n=16), Not specified Cholangiocarcinoma (n=9), Small bowel adenocarcinoma (n=6) and other rare GI cancer (n=9)

  Study EGAS00001006299

• Single cell whole genome sequencing of high hyperdiploid acute lymphoblastic leukemia

  This dataset was collected from viable bone marrow cells obtained at diagnosis from nine patients with high hyperdiploid ALL and one normal bone marrow sample. All samples were subjected to low pass single cell whole genome sequencing with the median sequencing coverage of 0.02x. Single nuclei in G0/G1 phase were isolated using a fluorescence-activated cell sorting (FACS) cytometer. DNA libraries were constructed and associated next-generation sequencing was carried out by European Research Institute for the Biology of Ageing (ERIBA), University of Groningen, University Medical Center Groningen, Groningen, The Netherlands. Further details regarding the DNA libraries construction are available by Bos et. al., 2019 (https://link.springer.com/protocol/10.1007/978-1-4939-8931-7_15). The dataset has been used for copy number aberrations analysis.

  Study EGAS00001006347

• Upper respiratory microbiome of COVID-19 patients

  Understanding the pathology of COVID-19 is a global research priority. Early evidence suggests that the microbiome may be playing a role in disease progression, yet current studies report contradictory results. Here, we examine potential confounders in COVID-19 microbiome studies by analyzing the upper respiratory tract microbiome in well-phenotyped COVID-19 patients and controls combining microbiome sequencing, viral load determination, and immunoprofiling. We found that time in the intensive care unit and the type of oxygen support explained the most variation within the upper respiratory tract microbiome, dwarfing (non-significant) effects from viral load, disease severity, and immune status. Specifically, mechanical ventilation was linked to altered community structure, lower species- and higher strain-level diversity, and significant shifts in oral taxa previously associated with COVID-19.

  Study EGAS00001004951

• ATAC-Seq of inflamed and non-inflamed biopsies

  Inflamed and non-inflamed biopsies were digested for 45 minutes at 37ºC with collagenase from Clostridium histolyticum (Sigma). Suspension cells were then stained with an antibody cocktail to sort live CD8-CD4+ T cells. After isolating crude nuclei of two thousand live CD4+ T cells, they were treated with Tagment DNA buffer and Tagment DNA Enzyme (Nextera DNA Library Prep Kit, Illumina), and then the DNA was purified by MinElute PCR Purification Kit (Qiagen). Transposed DNA fragments were amplified using specific adapters followed by purification with MinElute PCR Purification Kit (Qiagen). Fragments from 240-360pb were selected in the PippinHT system (Sage Science). The quality of the library and its DNA concentration were assessed by Bioanalyzer instruments (Agilent Technologies) and ultimately submitted for sequencing using Illumina HiSeq 2500 sequencer, V4 chemistry.

  Study EGAS00001007344

• Gliomas, glioneuronal and neuronal tumors

  The dataset represents a total of 85 DNA samples from 22 male and 20 female pediatric patients affected with gliomas, glioneuronal, and neuronal tumors. The samples were subject to whole genome sequencing, WGS, [71 samples, (representing 18 male and 17 female individuals)] and whole exome sequencing, WES, [14 samples, (representing 4 males and 3 female individuals)]. One tumor tissue sample and one peripheral blood sample were analyzed from each of 84 patients, whereas two tumor tissue samples and one peripheral blood sample were analyzed from one patient. The WGS samples were sequenced 2x150 bp paired-end on an Illumina HiSeqX v2.5 instrument, and the WES samples were sequenced 2x100 bp paired-end on an Illumina HiSeq 2500 instrument. The FASTQ files generated were aligned to the human reference genome sequence GRCh38/hg38 using bwa-mem, with the ALT-aware option turned on. Sorting of reads and marking of PCR duplicates was performed with GATK. Base quality score recalibration and joint realignment of reads around insertions and deletions (indels) were conducted using GATK tools. The dataset consists of 85 files in the CRAM format (lossless compression) with a total file size of ~13,3 TB. Additional genomic and molecular data (FASTQ, BAM, IDAT, and VCF files) and limited clinical data can be requested by ethically approved projects conducting research in the field of pediatric cancer.

  Dataset EGAD50000000300

• CCOC WGS for the study Genomic consequences of aberrant DNA repair mechanisms stratify ovarian cancer histotypes

  For CCOC cohorts, OvCaRe cases were reviewed, including frozen material, by at least two expert gynecopathologists prior to inclusion in the sequencing cohort who provided the confirmation on final selected cohort. Frozen H&E from Tokyo were also used for evaluation along with representative H&E photos and review done at the Jikei School of Medicine. All CCOC tumours are primary tumour samples. Library construction and sequencing Frozen specimens with >50% tumour cellularity (based on initial slide review) were used for cryosectioning and subsequent nucleic acid extraction. Patient tumour and normal blood samples derived from primary, untreated fresh frozen tumour specimens harvested at diagnosis during standard of care debulking surgery. Germline DNA was provided from peripheral blood buffy coat on all specimens except 13 from Tokyo, where non-cancer frozen tissue was used as a germline source. DNA extraction from both matched normal (blood) and tumour samples (frozen tissue) were performed using the QIAamp Blood and Tissue DNA kit (Qiagen) and quantified using a Qbit fluorometer and reagents (high-sensitivity assay). Three lanes of Illumina HiSeq 2500 v4 chemistry for normal samples and five lanes for tumour samples were obtained. The PCR-free protocol was adopted to eliminate the PCR-induced bias and improve coverage across the genome.

  Dataset EGAD00001003265

• GCT WGS for the study Genomic consequences of aberrant DNA repair mechanisms stratify ovarian cancer histotypes

  For GCT cohorts, OvCaRe cases were reviewed, including frozen material, by at least two expert gynecopathologists prior to inclusion in the sequencing cohort who provided the confirmation on final selected cohort. Frozen H&E from Tokyo were also used for evaluation along with representative H&E photos and review done at the Jikei School of Medicine. All GCT tumours are primary tumour samples. Library construction and sequencing Frozen specimens with >50% tumour cellularity (based on initial slide review) were used for cryosectioning and subsequent nucleic acid extraction. Patient tumour and normal blood samples derived from primary, untreated fresh frozen tumour specimens harvested at diagnosis during standard of care debulking surgery. Germline DNA was provided from peripheral blood buffy coat on all specimens except 13 from Tokyo, where non-cancer frozen tissue was used as a germline source. DNA extraction from both matched normal (blood) and tumour samples (frozen tissue) were performed using the QIAamp Blood and Tissue DNA kit (Qiagen) and quantified using a Qbit fluorometer and reagents (high-sensitivity assay). Three lanes of Illumina HiSeq 2500 v4 chemistry for normal samples and five lanes for tumour samples were obtained. The PCR-free protocol was adopted to eliminate the PCR-induced bias and improve coverage across the genome.

  Dataset EGAD00001003267

• Samples linked to the study "Performance comparison of three DNA extraction kits on human whole-exome data from formalin-fixed paraffin-embedded normal and tumor samples"

  We generated 42 human whole-exome sequencing data sets from fresh-frozen (FF) and FFPE samples. These samples include normal and tumor tissues from two different organs (liver and colon), that we extracted with three different FFPE extraction kits (QIAamp DNA FFPE Tissue kit and GeneRead DNA FFPE kit from Qiagen, Maxwell\textsuperscript{TM} RSC DNA FFPE Kit from Promega). Variant calling analysis shows a very high rate of concordance between matched FF / FFPE pairs and equivalent performance for the three kits we analyzed. We find a significant variation in the difference of total number of variants called between FF and FFPE samples for the three different FFPE DNA extraction kits. Coverage analysis shows that FFPE samples have less good indicators than FF samples, yet the coverage quality remains above accepted thresholds. We detect limited but significant variations in coverage indicator values between the three FFPE extraction kits. Globally, the GeneRead and QIAamp kits have better variant calling and coverage indicators than the Maxwell kit on the samples used in this study, although this kit performs better on some indicators and has advantages in terms of practical usage. Taken together, our results confirm the potential of FFPE samples analysis for clinical genomic studies, but also indicate that the choice of a FFPE DNA extraction kit should be done with careful testing and analysis beforehand in order to maximize the accuracy of the results.

  Dataset EGAD00001004066

• Validation of AML Mutational Screening

  We recently worked-up a pulldown protocol for studying 21 genes recurrently mutated in AML (Study1770). Our manuscript is currently under revision and to address the reviewers' comments we need to validate some mutations by re-sequencing. In this add-on study we will be using PCR followed by MiSeq for this purpose.

  Dataset EGAD00001000445

• Whole Exome sequencing of colorectal cancer patients (SG-BULK)

  DNA-seq libraries were captured to exome regions using xGen Exome Research Panel v1.0 (IDT), and libraries were prepared using the KAPA Hyper prep kit. DNA libraries were sequenced to a target depth of ×200 for tumor sample, ×100 for normal samples on the Illumina HiSeq platform.

  Dataset EGAD00001008543

• A non-canonical lymphoblast in refractory childhood T cell leukaemia

  Refractory cancers may arise either through the acquisition of resistance mechanisms by cancer cells or represent distinct diseases. The origin of childhood T-cell acute lymphoblastic leukaemia (T-ALL) that does not respond to initial treatment, i.e. refractory disease, is unknown. Refractory T-ALL carries a poor prognosis and cannot be predicted at diagnosis. Here, we performed single cell mRNA sequencing of T-ALL from children who did or did not respond to initial treatment. We identified a transcriptionally distinctive blast population, exhibiting features of innate-like lymphocytes, as the major source of refractory disease. Evidence of such blasts at diagnosis heralded refractory disease across independent datasets and was associated with survival in a large, contemporary trial cohort. Our findings portray refractory T-ALL as a distinct disease. They may have immediate clinical utility.

  Dataset EGAD00001015381

• Correction of a Factor VIII genomic inversion with designer recombinases

  Despite advances in nuclease-based genome editing technologies, correcting human disease-causing genomic inversions remains a challenge. Here, we describe the potential use of a recombinase-based system to correct the 140 kb inversion of the F8 gene frequently found in patients diagnosed with severe Hemophilia A. Employing substrate-linked directed molecular evolution, we developed a coupled heterodimeric recombinase system (RecF8) achieving 30% inversion of the target sequence in human tissue culture cells. Transient RecF8 treatment of endothelial cells, differentiated from patient derived induced pluripotent stem cells (iPSCs) of a hemophilic donor, resulted in 12% correction of the inversion and restored Factor VIII mRNA expression. Our data suggests that designer-recombinases may represent efficient and specific means towards treatment of monogenic diseases caused by large gene inversions.

  Study EGAS00001005496

• Progress in Diabetes Genetics in Youth (ProDIGY) Exome Sequencing Study: SEARCH for Diabetes in Youth

  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 SEARCH for Diabetes in Youth cohort was part of the ProDIGY (Progress in Diabetes Genetics in Youth) consortium, which is a NIDDK-funded research consortium that investigated genetic variants for childhood type 2 diabetes (T2D). This consortium involved sequencing multiethnic samples from childhood T2D cases located across the United States. 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 table, th, td { border: 1px solid black; border-collapse: collapse; } Ancestry Consortia Study Countries of Origin # Cases # Controls African American T2D-GENES Project 1 Jackson Heart Study US 500 526 African American T2D-GENES Project 1 Wake Forest School of Medicine Study US 518 530 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& 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 Malmo-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 & SIGMAv2 Starr County, Texas US 1762 1738 Hispanic SIGMAv1 Mexico City Diabetes Study Mexico 281 549 Hispanic SIGMAv1 & v2 Multiethnic Cohort (MEC) US 1476 1443 Hispanic SIGMAv1 & v2 UNAM/INCMNSZ Diabetes Study (UIDS) Mexico 1998 1977 Hispanic SIGMAv1 & v2 Diabetes in Mexico Study (DMS) Mexico 1522 1546 Multi ethnic ProDIGY Treatment Options for Type 2 Diabetes in Adolescents and Youth (TODAY) US 3097 0 Multi ethnic 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) 551 538 South Asian T2D-GENES Project 1 & Follow up study Singapore Indian Eye Study Singapore (Indian Asian) 1640 1478 South Asian T2D-GENES Follow up study Pakistan Risk of Myocardial Infarction Study (PROMIS) Pakistan 914 932 The SEARCH study contributed 553 cases and 0 controls to 52k T2D exome sequencing study.

  Study phs001511

• Slim Initiative in Genomic Medicine for the Americas (SIGMA): Mexico City Diabetes Study (MCDS)

  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: Type 2 Diabetes (SIGMA T2D) 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 SIGMA Mexico City Diabetes Study was part of the Slim Initiative in Genomic Medicine for the Americas: Type 2 Diabetes (SIGMA T2D), which is an international research consortium funded by the Carlos Slim Foundation that seeks to identify the genetic risk factors for type 2 diabetes (T2D) in Mexico and Latin America and translate those findings into improved treatment and prevention of diabetes. The SIGMA T2D project has sequenced and genotyped more than 13,000 samples from Mexican and Mexican Americans. 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 500 526 African American T2D-GENES Project 1 Wake Forest School of Medicine Study US 518 530 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& 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 Malmo-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 & SIGMAv2 Starr County, Texas US 1762 1738 Hispanic SIGMAv1 Mexico City Diabetes Study Mexico 281 549 Hispanic SIGMAv1 & v2 Multiethnic Cohort (MEC) US 1476 1443 Hispanic SIGMAv1 & v2 UNAM/INCMNSZ Diabetes Study (UIDS) Mexico 1998 1977 Hispanic SIGMAv1 & v2 Diabetes in Mexico Study (DMS) Mexico 1522 1546 Multi ethnic ProDIGY Treatment Options for Type 2 Diabetes in Adolescents and Youth (TODAY) US 3097 0 Multi ethnic 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 & 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

  Study phs001375

• National Eye Institute Glaucoma Human Genetics Collaboration (NEIGHBOR) Consortium Glaucoma Genome-Wide Association Study: Whole Exome Resequencing in Glaucoma

  This is a study of primary open angle glaucoma (POAG) conducted through exome sequencing of cases and comparison of variant frequencies with general population frequencies available in dbGAP and controlled for sequencing platform artifact to minimize false positives. POAG is an intraocular pressure (IOP) related progressive optic neuropathy that ultimately leads to blindness. This study builds upon the efforts of an on-going collaborative consortium that studied 2,170 POAG cases and 2,347 controls with a unified definition of POAG (the NEIGHBOR consortium: NEI Glaucoma Human genetic collaBORation). The case definition for NEIGHBOR was harmonized with an additional 976 cases and 1140 controls from the NHGRI supported GENEVA (gene-environment) study of glaucoma (GLAUGEN) (NIH/NHGRI U01HG004728, Pasquale PI). In NEIGHBOR, cases and controls were recruited from ophthalmology clinics and were examined by ophthalmologists. For cases, the clinical exam included intraocular pressure measurements, optic nerve assessment and visual field evaluation. Controls had no family history of glaucoma, normal intraocular pressure and normal optic nerves. Cases and controls were also drawn from two clinical trial populations: Advanced Glaucoma Intervention Study (AGIS, NEI U10EY006827, D. Gaasterland PI) and Collaborative Initial Glaucoma Treatment Study (CIGTS, NEI U10 EY009149, P. Lichter PI). The Glaucoma Exome Sequencing study has one Principal Investigator: Theresa Gaasterland (UCSD) and two Co-Investigators: Robert Weinreb, MD, and Kang Zhang, MD, PhD, all of whom are part of the NEIGHBOR, subsequently NEIGHBORHOOD, consortium, which in turn has two Co-Principal Investigators: J. Wiggs (Harvard, MEEI), and M. Hauser (Duke). NEIGHBOR collaborators who contributed samples and/or expertise to the Glaucoma Exome Sequencing study included the following: Harvard Medical School (Massachusetts Eye and Ear Infirmary) (J. Wiggs, L. Pasquale); Duke University Medical Center (M. Hauser, E. Hauser, R. Allingham, S. Schmidt); University of Michigan (J. Richards, S. Moroi, P. Lichter); University of Miami (M. Pericak-Vance, R. Lee, D. Budenz); Vanderbilt University (J. Haines); University of California San Diego (K. Zhang, R. Weinreb; T. Gaasterland); University of Pittsburgh (J. Schuman, G. Wollenstein); University of West Virginia (A. Realini, J. Charlton, S. Zareparsi); Johns Hopkins University (D. Friedman); Stanford University (D. Vollrath, K. Singh), Eye Doctors of Washington (D. Gaasterland), Marshfield Clinic (Cathy McCarty). Hemin Chin serves as the NEI Staff Collaborator. This national collaborative study is supported by multiple NIH grants: NEI R01 EY015543 (Allingham); NEI U10 EY006827 (D. Gaasterland); NHLBI R01 HL073389 (E. Hauser); NEI R01 EY13315 (M. Hauser); NEI U10 EY009149 (Lichter); NEI R01 EY015473 (Pasquale); NEI U10 EY012118 (Pericak-Vance); NEI R03 EY015682 (Realini); NEI R01 EY011671 (Richards); NEI R01 EY09580 (Richards); NEI R01 EY013178 (Schuman); NEI R01 EY015872 (Wiggs); NEI R01 EY009847 (Wiggs); NEI R01 EY010886 (Wiggs); NEI R01 EY144428 (Zhang); NEI R01 EY144448 (Zhang); NEI R01 EY18660 (Zhang). Funding support for genotyping through exome sequencing, which was performed at the University of California, San Diego, was provided by the National Eye Institute (RC2 EY020678-01).

  Study phs000558

• Elucidating Transcription Regulation by Epigenetics in Neuroblastoma

  PURPOSE Whole-genome profiles of the epigenetic modification 5-hydroxymethylcytosine (5-hmC) are robust diagnostic biomarkers in adult patients with cancer. We investigated if 5-hmC profiles would serve as novel prognostic markers in neuroblastoma, a clinically heterogeneous pediatric cancer. Because this DNA modification facilitates active gene expression, we hypothesized that 5-hmC profiles would identify transcriptomic networks driving the clinical behavior of neuroblastoma. PATIENTS AND METHODS Nano-hmC-Seal sequencing was performed on DNA from Discovery (n = 51), Validation (n = 38), and Children's Oncology Group (n = 20) cohorts of neuroblastoma tumors. RNA was isolated from 48 tumors for RNA sequencing. Genes with differential 5-hmC or expression between clusters were identified using DESeq2. A 5-hmC model predicting outcome in high-risk patients was established using linear discriminant analysis. RESULTS Comparison of low- versus high-risk tumors in the Discovery cohort revealed 577 genes with differential 5-hmC. Hierarchical clustering of tumors from the Discovery and Validation cohorts using these genes identified two main clusters highly associated with established prognostic markers, clinical risk group, and outcome. Genes with increased 5-hmC and expression in the favorable cluster were enriched for pathways of neuronal differentiation and KRAS activation, whereas genes involved in inflammation and the PRC2 complex were identified in the unfavorable cluster. The linear discriminant analysis model trained on high-risk Discovery cohort tumors was prognostic of outcome when applied to high-risk tumors from the Validation and Children's Oncology Group cohorts (hazard ratio, 3.8). CONCLUSION 5-hmC profiles may be optimal DNA-based biomarkers in neuroblastoma. Analysis of transcriptional networks regulated by these epigenomic modifications may lead to a deeper understanding of drivers of neuroblastoma phenotype. "Reprinted from Applebaum et. JCO Precision Oncology, 2019, with permission from creative commons license."

  Study phs001831

• Blueprint Data Access Committee.

  Access to the sequence and alignment and genotype level data produced by the Blueprint Consortium is controlled by the Blueprint Data Access Committee (DAC). Access to data will be granted to qualified investigators for appropriate use. Please email blueprint-dac@ebi.ac.uk to request the Data Access Application and Data Access Agreement.

  Dac EGAC00001000135