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• Sequencing of pancreatic cancer primary tumors and metastases

  The extent of heterogeneity of driver gene mutations present in naturally occurring metastases is largely unknown, i.e. treatment-naïve metastatic disease. To address this issue, 60x whole genome sequencing of 26 metastases from 4 patients was carried out. We found that the identical driver gene mutations were present in every metastatic lesion of each patient studied. Passenger gene mutations not known or predicted to have functional consequences accounted for all intratumoral heterogeneity. Even with respect to these passenger gene mutations, the genetic similarity among the founding cells of metastases was markedly higher than that expected for any two cells randomly taken from a normal tissue. The uniformity of driver gene mutations among metastases in the same patient has critical, encouraging implications for the success of future targeted therapies in advanced stage disease.

  Study EGAS00001002186

• Germline RUNX1 Variation and Predisposition to Childhood Acute Lymphoblastic

  Somatic mutations of RUNX1, which encodes the myeloid and lymphoid transcriptional factor RUNX1, are common in both B- and T- acute lymphoid leukemia (ALL) and are associated with poor prognosis of T-ALL. However, there has been no comprehensive investigation of the pattern or prevalence of RUNX1 germline mutation in both B- and T-ALL. Here we report germline RUNX1 variants in 1.23% of B-ALL and 2.11% of T-ALL, identifying 31 unique variants in 62 B-ALL and 18 unique variants in 26 T-ALL children. The majority of frameshift and nonsense variants affected RUNX1 function in transcriptional regulation, hematopoiesis, and cellular proliferation. We identified JAK3 as the most frequent somatic mutation in T-ALL with RUNX1 variants. These results not only identify RUNX1 as a leukemia predisposition gene but also further underline the importance of germline genetic variants to the development of ALL

  Study EGAS00001005403

• Test Study for EGA using data from 1000 Genomes Project - Phase 3

  The 1000 Genomes Project set out to provide a comprehensive description of common human genetic variation by applying whole-genome sequencing to a diverse set of individuals from multiple populations. Here we report completion of the project, having reconstructed the genomes of 2,504 individuals from 26 populations using a combination of low-coverage whole-genome sequencing, deep exome sequencing, and dense microarray genotyping. We characterized a broad spectrum of genetic variation, in total over 88 million variants (84.7 million single nucleotide polymorphisms (SNPs), 3.6 million short insertions/deletions (indels), and 60,000 structural variants), all phased onto high-quality haplotypes. This resource includes >99% of SNP variants with a frequency of >1% for a variety of ancestries. We describe the distribution of genetic variation across the global sample, and discuss the implications for common disease studies...

  Study EGAS00001005042

• Nulliparous Pregnancy Outcomes Study: Monitoring Mothers-to-be Heart Health Study (nuMoM2b Heart Health Study)

  Participants from study sites that recruited during the original study funded by NICHD of pregnant people, called nuMoM2b, participated in this study. The nuMoM2b-HHS1 was a prospective observational follow-up study of the nuMoM2b cohort consisting of interval contacts via phone or web every 6 months to about a year, and an in-person visit 2 to 7 years after the end of the nuMoM2b pregnancy including: Demographics Self-administered questionnaires Clinical measurements Lab results An in-home sleep breathing assessment for the subset of participants with at least one valid sleep breathing assessment during nuMoM2b Abstraction of medical records for pregnancies subsequent to nuMoM2b involving self-reported adverse pregnancy outcomes or multiple births Abstraction of medical records of selected cardiovascular risk-related events or procedures reported by participants. The study capitalized on the rich and unique data prospectively collected during nuMoM2b (biomarkers, uterine artery Doppler studies, fetal growth, psychosocial determinants, sleep, and blood pressure) and rigorous definitions of adverse pregnancy outcomes. These data are stored in the NICHD repository DASH (https://dash.nichd.nih.gov/study/226675). A total of 8,838 nuMoM2b participants were targeted for contact during nuMoM2b-HHS and 7,872 participants were reached, of whom 7,003 completed one or more interval contacts. Of these, 5,206 agreed to the visit, and 4,508 attended an in-person visit.

  Study phs002808

• The Genetic Basis of Aggressive Prostate Cancer, The Role of Rare Variation

  In this study, we will apply a multi-staged approach to reveal genes harboring rare variants that are associated with aggressive PCa. Whole-exome sequencing (Aim 1a) of 2,774 aggressive cases and 2,776 non-aggressive cases of European ancestry will be conducted followed by rare variant analysis of single sites and gene burden testing to identify novel susceptibility loci/genes for aggressive disease. We will validate the most significantly associated genes (~500) through targeted sequencing in an additional 6,415 aggressive and 5,586 non-aggressive cases and 1,890 controls (Aim 1b). Next, we will investigate the clinical predictive utility of the genes/variants identified in 2,291 cases in the STHM3 trial who are undergoing biopsy based on PSA and genetic risk score stratification (Aim 2). Through this tiered approach we expect to significantly advance knowledge of aggressive PCa etiology and health disparities as well as guide the development of early detection and prognostic strategies for the subset of men who are most susceptible to this fatal form of disease. In this case-case study of aggressive vs non aggressive prostate cancer, aggressive cases are defined as prostate cancer as cause of death, (T4 disease or T3 disease) and Gleason 8+. Non-aggressive cases are men with T1/2 disease and Gleason ACKNOWLEDGMENTS and CONTRIBUTING SITES CAPS, PROCAP, STHM1, STHM2: Swedish Cancer Society (CAN 2016/818), Swedish Research Council (2014/2269).STHM3: Stockholm County Council (Stockholms Läns Landsting).MEC: Funding provided by the National Cancer Institute: Understanding Ethnic Differences in Cancer, 2U01CA164973 and The Genetic Basis of Aggressive Prostate Cancer, The Role of Rare Variation, 5R01CA196931-02.ATBC: The ATBC Study is supported by the Intramural Research Program of the U.S. National Cancer Institute, National Institutes of Health, and by U.S. Public Health Service contract HHSN261201500005C from the National Cancer Institute, Department of Health and Human Services.COSM: The Swedish Research Council/National Research Infrastructure Grant (VR 2014/6397; VR 2015/5997) The Swedish Cancer Foundation (CAN 2013/456; CAN 2016/727)CPSII: The authors express sincere appreciation to all Cancer Prevention Study II participants and to each member of the study and biospecimen management group. The American Cancer Society funds the creation, maintenance, and updating of the Cancer Prevention Study-II cohort.MCCS/APCS/PCFS: The Melbourne Collaborative Cohort Study (MCCS) recruitment was funded by VicHealth and Cancer Council Victoria and further supported by Australian National Health and Medical Research Council (NHMRC) grants 209057 and 396414. The Aggressive Prostate Cancer Case-Control Study (APCS) was funded by NHMRC grant 623204. The Prostate Cancer Family Study (PCFS) was fully funded by Cancer Council Victoria. Cancer Council Victoria funds the continuing maintenance and updating of the MCCS, APCS and PCFS. Cases and their vital status are ascertained and followed up through the Victorian Cancer Registry and the Australian Institute of Health and Welfare, including the National Death Index and the Australian Cancer Database.PLCO: The Prostate Lung Colorectal Ovarian Cancer Screening Trial (PLCO) was supported by the Intramural Research Program of the Division of Cancer Epidemiology and Genetics and by contracts from the Division of Cancer Prevention, National Cancer Institute, US National Institutes of Health, Department of Health and Human Services. EPIC: The coordination of EPIC is financially supported by International Agency for Research on Cancer (IARC) and also by the Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London which has additional infrastructure support provided by the NIHR Imperial Biomedical Research Centre (BRC). The national cohorts are supported by: Danish Cancer Society (Denmark); Ligue Contre le Cancer, Institut Gustave Roussy, Mutuelle Générale de l'Education Nationale, Institut National de la Santé et de la Recherche Médicale (INSERM) (France); German Cancer Aid, German Cancer Research Center (DKFZ), German Institute of Human Nutrition Potsdam- Rehbruecke (DIfE), Federal Ministry of Education and Research (BMBF) (Germany); Associazione Italiana per la Ricerca sul Cancro-AIRC-Italy, Compagnia di SanPaolo and National Research Council (Italy); Dutch Ministry of Public Health, Welfare and Sports (VWS), Netherlands Cancer Registry (NKR), LK Research Funds, Dutch Prevention Funds, Dutch ZON (Zorg Onderzoek Nederland), World Cancer Research Fund (WCRF), Statistics Netherlands (The Netherlands); Health Research Fund (FIS) - Instituto de Salud Carlos III (ISCIII), Regional Governments of Andalucía, Asturias, Basque Country, Murcia and Navarra, and the Catalan Institute of Oncology - ICO (Spain); Swedish Cancer Society, Swedish Research Council and County Councils of Skåne and Västerbotten (Sweden); Cancer Research UK (14136 to EPIC-Norfolk; C8221/A19170 and C8221/A29017 to EPIC-Oxford), Medical Research Council (1000143 to EPIC-Norfolk; MR/M012190/1 to EPIC-Oxford). (United Kingdom). DFCI: Linda and Arthur Gelb and Rebecca and Nathan Milikowsky. HPFS and PHS: The Health Professionals Follow-up Study was supported by U01 167552 and P01 CA228696 from the National Cancer Institute, and with support from the Prostate Cancer Foundation. The Physicians' Health Study was supported by grants CA34944, CA40360, CA097193, HL26490 and HL34595.Northwestern: P50CA180995 (Catalona) 08/01/15 – 07/31/20 NIH/NCI SPORE in Prostate Cancer; The Urological Research FoundationPROMPT: MRC UK - Project reference G0500966, Cambridge BRC infrastructure funding, Cambridge Biomedical Research Campus (BRC-1215-20014), CRUK Cambridge Cancer Centre infrastructure funding (they are requesting this statement is written in blue for publications).ICR: This work was supported by the NIH R01 grant 5R01CA196931-02. The samples from the UK were from UKGPCS and PrompT. The UKGPCS study was supported by Cancer Research UK (grant numbers C5047/A7357, C1287/A10118, C1287/A5260, C5047/A3354, C5047/A10692, C16913/A6135 and C16913/A6835). We would like to acknowledge the NCRN nurses and Consultants for their work in the UKGPCS study. We thank all the patients who took part in this study. We also acknowledge The Institute of Cancer Research, The National Cancer Research Network UK, The National Cancer Research Institute (NCRI) UK for their ongoing support. We are grateful for support of NIHR funding to the NIHR Biomedical Research Centre at The Institute of Cancer Research and The Royal Marsden NHS Foundation Trust.Funding:CIDR grant X01HG008336

  Study phs001524

• Small cell number RNA-seq (400 cells per sample)

  Transcriptional profiles for stemB and proB cells harvested from either primary or secondary xenografts. This dataset contains six types of samples: - diagnostic stemB cells harvested from primary xenografts - diagnostic proB cells harvested from primary xenografts - relapse stemB cells harvested from secondary xenografts injected with stemB cells from primary xenografts - relapse proB cells harvested from secondary xenografts injected with stemB cells from primary xenografts - relapse stemB cells harvested from secondary xenografts injected with proB cells from primary xenografts - relapse proB cells harvested from secondary xenografts injected with proB cells from primary xenografts

  Dataset EGAD50000001830

• Paired-end Whole Exome-seq analysis of the 3D evolution of glioma cell populations. Part 2.

  Dataset contains paired-end Whole Exome sequencing data from 257 glioma samples from 28 patients. 26 normal blood samples are also included.

  Dataset EGAD00001009496

• Next generation sequencing of diffuse intrinsic pontine glioma samples to identify recurrent mutations, variations, and expression patterns to define novel therapies

  Diffuse intrinsic pontine glioma (DIPG) is an extremely rare (~350 cases/year) and universally fatal childhood brain cancer. Standard clinical strategies such as chemotherapy and radiotherapy show only transient improvement in patient condition and result in negligible change in survival, DIPG remains at below 1% survival after 5 years. Prioritization of panobinostat through previous cooperative work resulted in a phase 1 clinical trial. Nonetheless, new therapies for DIPG must be identified to further dramatically change the statistics for DIPG. To identify novel therapy strategies for DIPG, we performed whole exome(16 new samples, 22 previously published samples, 38 in total with 26 matched normal) and RNA deep sequencing (17 new samples, 11 previously published samples) on a cohort of new patient samples. Sequencing results aid in the identification of recurrent mutations/variations and endotypic expression profiling to identify new therapeutic and treatment strategies for DIPG.

  Study phs001526

• Transcriptomic Analysis of Human Hematopoietic Progenitors from Healthy Donors and Bone Marrow Failure Patients

  The purpose of this study was to define transcriptional changes that occur in the rare and heterogeneous bone marrow progenitors that are affected in Shwachman-Diamond Syndrome. Data are reported for four genetically confirmed SDS patients ranging from 11-26 years old, 3 male and 1 female, and four healthy donors ranging from 25-29 years old, 2 male and 2 female. Subjects provided written, informed consent in accordance with the Declaration of Helsinki's Ethical Principles of Medical Research Involving Human Subjects. Single CD34+ cells were purified from fresh bone marrow and cDNA libraries were prepared using the SMARTer Ultra Low RNA Kit (Clontech; pre-2015) or SMART-Seq v4 Ultra Low RNA Kit (Clontech; post-2015). Libraries were sequenced on a HiSeq 2500 Instrument (Illumina, San Diego, CA) to a read depth of ~3 M paired-end, 25 bp reads per single cell. Paired-end reads were mapped to the hg38 human transcriptome (Gencode v24) using STAR v2.4.2a.

  Study phs001845

• Circulating Tumor DNA as a Biomarker in Patients with Stage III and IV Wilms Tumor: Analysis from a Children's Oncology Group Trial, AREN0533

  We evaluated the utility of circulating tumor DNA (ctDNA) as a biomarker in the serum and urine of 50 patients with Stage III or Stage IV Wilms tumor (WT) that were enrolled on Children's Oncology Group (COG) trial AREN0533. 49 out of 50 patients had matched tumor samples available for comparison. We profiled samples with ultra-low pass whole genome sequencing (ULP-WGS) and detected ctDNA in 82% of serum samples and 26% of urine samples. We also identified copy-number changes and single-nucleotide variants in the serum and urine samples, and compared them to the tumor data. Our study highlights the advantages of using ctDNA as non-invasive prognostic biomarker with the potential to detect tumor heterogeneity in patients with WT. We believe that prospective validation of ctDNA as a prognostic biomarker in patients with WT is warranted. The ULP-WGS and targeted next-generation sequencing (OncoPanel) data are available in this study.

  Study phs002847

• International Age-Related Macular Degeneration Genomics Consortium - Exome Chip Experiment

  Advanced age-related macular degeneration (AMD) is the leading cause of blindness in the elderly, with limited therapeutic options. To further our understanding of AMD genetics, we examined the contribution of common and rare genetic variation in the International AMD Genomics Consortium that included ~50,000 samples of 26 AMD case - control cohorts that were jointly genotyped. Analyzing 16,144 patients with late stage AMD and 17,832 controls, we identified 52 independently associated common and rare variants distributed across 34 loci. Besides these single variant signals, we also observed gene-based enrichment of very rare coding variants (frequency < 0.1%) in cases that implicated causal roles for CFH, CFI and TIMP3 in three of the known AMD risk loci. Our results support the hypothesis that rare coding variants can pinpoint causal genes within known genetic loci and illustrate that applying the approach systematically to detect new loci requires extremely large sample sizes.

  Study phs001039

• Integrative Age-Related Changes in Genome and Epigenome in Human Lung in Relation to Smoking

  The Integrative Age-Related Changes in Genome and Epigenome in Human Lung in Relation to Smoking study was designed to assess DNA methylation and gene expression profiles in cytologically normal bronchial progenitor "basal" cells. The cells were collected from 54 consented bronchoscopy specimen donors at standard airway locations during clinically indicated bronchoscopy, and then outgrown in primary cultures. DNA methylation profiles were assessed using Enzymatic-Methyl sequencing (EM-seq: 96% genomic coverage, 7.5x depth) in all 54 donors' samples. The gene expression profile was evaluated by bulk RNA-Seq in 39 donors' samples. The study participants were at the ages of 33 - 81 years old at enrollment. Of the 54 donors, 31 were newly diagnosed with lung cancer. As for tobacco smoke exposure, there were 19 current, 18, former, and 17 never smokers. There are 26 subjects whose specimens were used for single cell whole-genome sequencing study phs002758.

  Study phs003317

• Functional Variant rs9344 at 11q13.3 Regulates CCND1 Expression in Multiple Myeloma with t(11;14)

  Multiple myeloma (MM) is a plasma cell (PC) malignancy characterized by cytogenetic abnormalities, such as t(11;14)(q13;q32), resulting in CCND1 overexpression. The rs9344 G allele within CCND1 is the most significant susceptibility allele for t(11;14). We have found the G risk allele is enriched in both healthy individuals of African ancestry and African American individuals with MM. The overall aim of this study was to identify the mechanism behind why the G allele is enriched in t(11;14) MM. To reach this goal, we performed ATAC-seq from 100,000 CD138+ tumor cells from 26 patients with MM. In addition, we performed ChIP-seq using antibodies against H3K4me1, H3K27ac and H3K4me3 from 100,000 CD138+ tumor cells from 8 patients with MM. We used these data to evaluate whether the G allele of rs9344 is associated with elevated chromatin accessibility, H3K27ac and H3K4me3 in t(11;14) MM.

  Study phs003997

• SeqControl: Process Control for DNA Sequencing

  As next-generation sequencing (NGS) continues to increase in speed and throughput, routine clinical and industrial application draws steadily closer. These “production” uses of NGS will require enhanced quality-monitoring and quality-control to optimize output and reduce costs. We therefore developed a framework called SeqControl for predicting sequencing quality and coverage using a set of 15 metrics describing overall coverage, coverage distribution, base-wise coverage and base-wise quality. Using whole-genome sequences of 27 prostate cancers and 26 normal references we derive multivariate models that predict sequencing quality and depth. SeqControl robustly predicts how much sequencing is required to reach a given coverage depth (AUC = 0.993), accurately classifies clinically relevant formalin-fixed paraffin-embedded samples and makes predictions from as little as 1/8 of a lane of sequencing data (AUC = 0.967). These techniques can be immediately incorporated into existing NGS pipelines to monitor data quality in real-time. SeqControl represents a first step towards statistical process-control for NGS.

  Study EGAS00001000899

• Feasibility and safety of a multi-cancer blood test for screening and intervention

  We evaluated the feasibility and safety of blood testing for cancer in an interventional study of 10,006 women. Positive tests for DNA or protein were independently confirmed and diagnostic PET-CT imaging was used to localize disease. During the study, 26 cancers were first detected by blood testing, 24 more by standard-of-care screening, and 46 by neither approach. Surgicalexcision of the primary tumors was performed on 12 cancers first detected by blood testing.1.0% of participants underwent PET-CT imaging based on false positive blood tests, and 0.22% underwent a futile invasive diagnostic procedure. These data demonstrate that multi-cancer blood testing, when followed by PET-CT localization, can be safely incorporated into routineclinical care, in some cases leading to surgery with intent to cure. Further studies will be required to determine the clinical validity and utility of multi-cancer blood testing.

  Study EGAS00001004372

• Whole exome and Transcriptome sequencing of treatment-naïve esophageal adenocarcinoma biopsies and matched peripheral blood mononuclear cells

  Exome sequencing was performed on n=28 treatment-naïve esophageal adenocarcinoma (EACs). Three to four biopsies sampling different areas of each tumor were pooled before nucleic acid extractions to mitigate the elevated heterogeneity described for EAC. WES was performed on EAC biopsies at 120X average coverage, with autologous PBMCs used as germline controls at 80X average coverage. Libraries were prepared from 30 ng of input DNA using the SureSelect QXT Human All Exon V7 kit (Agilent Technologies) and sequenced on the NextSeq 550 (Illumina), 2x150 bp. BCL files were demultiplexed to FastQ files using bcl2fastq2 software (Illumina). Three paired end sequencing batches were analyzed independently (Batch1: samples 8, 10, 11, 12, 15, 17, 18; Batch2: samples 20, 24, 25, 26, 27, 29, 30, 31, 33, 34 ; Batch3: samples 35, 37, 39, 40, 41, 43, 45, 48, 54, 55, 57). RNA sequencing was performed on n=26 treatment-naïve esophageal adenocarcinoma (EACs). Three to four biopsies sampling different areas of each tumor were pooled before nucleic acid extractions to mitigate the elevated heterogeneity described for EAC. RNAseq libraries were prepared on 50 ng of total RNA (with RNA integrity index RIN >=7) with the TruSeq Stranded mRNA library preparation kit (Illumina) in accordance with low-throughput protocol. After PCR enrichment (15 cycles) and purification of adapter-ligated fragments, the concentration and length of DNA fragments were measured using D1000 Screen Tape System (Agilent), obtaining a median insert size of 311 nucleotides. Then, RNAseq libraries were sequenced using the Illumina NovaSeq platform, 1x100 bp, obtaining on average 100 million single reads per sample.

  Dataset EGAD00001010876

• Genome-wide cell-free DNA termini in patients with cancer

  The structure, fragmentation patterns and terminal sequences of cell-free DNA (cfDNA) are altered by nucleases and biological mechanisms in the blood of cancer patients. The cfDNA fragment-end composition recovered from low coverage WGS (<1 fold coverage) using a bespoke software (FrEIA) is aberrant in the plasma from cancer patient (n = 418, 655 samples) compared to controls (n = 117). As a standalone test FrEIA allows detection down to ~0.2% tumor fraction in vitro and in silico at 95% specificity, leading to a sensitivity of ~71% for detecting lung cancer (14/22 stage I-II, 27/38 stage III, 92/127 stage IV) and ~68% for detecting esophageal adenocarcinoma (26/44 stage II, 46/62 stage III). Additional cfDNA biological patterns can be combined with FrEIA increasing the diagnostic potential of low coverage WGS at minimal cost (mean AUROC = 0.96). Integrating multiple cfDNA biological signal augments the diagnostic performance of liquid biopsy.

  Study EGAS00001006142

• A panel of reference haplotypes for imputing complement component 4 (C4) gene structural variation

  Neuropsychiatric and autoimmune disorders have substantial epidemiological correlations (Benros et al., JAMA Psychiatry 2013, PMID: 23760347) and broad, genome-wide patterns of shared genetic risk (Pouget et al., Hum Mol Genet, PMID: 31211845; Tylee et al., Am J Med Genet B Neuropsychiatr Genet 2018, PMID: 30325587). Some cases of psychosis involve autoantibodies against the NMDA receptor, AMPA receptor, or other synaptic proteins (reviewed in Dalmau et al, Lancet Neurol 2011, PMID: 21163445). The related autoimmune conditions lupus and Sjogren's Syndrome also involve the development of autoantibodies. The possibility that neuropsychiatric disorders can have molecular mechanisms in common with autoimmune disorders - for example, that psychosis involves an inflammatory or autoimmune component in some patients, or that immune molecules are re-used in the brain to underlie other important biological activities (Stevens et al., Cell 2007, PMID: 18083105) - could open novel therapeutic possibilities for neuropsychiatric disorders. At a genetic level, the strongest genetic associations of schizophrenia, lupus, and Sjogren's Syndrome to common genetic variation involve associations to genetic markers in the Major Histocompatibility Complex (MHC) locus. Bipolar disorder in some studies also associates with variation in or near the MHC locus, though less strongly than schizophrenia does. Intriguingly, the same specific SNPs appear to associate strongly with schizophrenia, lupus, and Sjogren's; these strongly associating SNPs span a genomic segment that includes the HLA class II genes (which have an important role in antibody production) and the complement component 4 (C4) genes. The specific genes and alleles responsible for these associations need to be completely defined, and the extent to which they represent shared or distinct genetic influences in neuropsychiatric and autoimmune illnesses needs to be clarified. The complement component 4 (C4A and C4B) genes are present in the MHC locus, between the class I and class II HLA genes. C4A and C4B commonly vary in genomic copy number and encode complement proteins with distinct affinities for molecular targets. The complex genetic variation at C4 - arising from many alleles with different numbers of C4A and C4B genes - has been challenging to analyze in large cohorts. We recently developed an approach to this problem based on imputation: people share long haplotypes with the same combinations of SNP and C4 alleles, such that C4A and C4B gene copy numbers can be imputed from SNP data (Sekar et al., Nature 2016, PMID: 26814963). In the current work, to analyze C4 in large cohorts, we developed a way to identify C4 alleles from whole-genome sequence (WGS) data, then analyzed WGS data from 1,234 individuals to create a large multi-ancestry panel of 2,530 reference haplotypes of MHC SNPs and C4 alleles that can then be imputed into still-larger cohorts for which SNP data are available. With this dbGaP submission, we make this reference panel available for other studies. Protocols and software for imputing C4 alleles into genome-wide SNP data, and for performing molecular analyses on the C4 genes (such as direct measurement of copy number from genomic DNA), can be found on the McCarroll Lab web site (http://mccarrolllab.org/resources). We are also working to create additional reference panels for imputation of C4 alleles that will be based on still-larger and more diverse population samples; links to these will also be available on the McCarroll Lab web site as we create and validate them.

  Study phs001992

• 10x Genomics raw data of intestinal plasma cells

  The dataset contains raw fastq files (fastq.gz) for Chromium Single Cell 5’ gene expression (GEX), human B cell VDJ and feature barcode (CSP) sequencing from transglutaminase 2-specific and other small intestinal plasma cells isolated from four untreated celiac disease patients. Single cell 5’ gene expression, V(D)J-enriched and cell surface protein libraries were generated using Chromium single cell kits, and barcoded cDNA from a total of 5,000-10,000 cells per sample was generated using the 10x Genomics Chromium Controller. The libraries were pooled prior to sequencing on a NovaSeq 6000 instrument (Illumina) using the following configuration: read 1: 26 cycles, read 2: 89 cycles, index read 1: 8 cycles.

  Dataset EGAD50000000342

• ICR96 exon CNV validation series

  A resource for assessment of exon CNV calling methods in targeted NGS data, we here present the ICR96 exon CNV validation series. The dataset includes high-quality sequencing data from a targeted NGS assay (the TruSight Cancer Panel) together with Multiplex Ligation-dependent Probe Amplification (MLPA) results for 96 independent samples. 66 samples contain at least one validated exon CNV and 30 samples have validated negative results for exon CNVs in 26 genes. The dataset includes 46 exon CNVs in BRCA1, BRCA2, TP53, MLH1, MSH2, MSH6, PMS2, EPCAM and PTEN, giving excellent representation of the cancer predisposition genes most frequently tested in clinical practice. Moreover, the validated exon CNVs include 25 single exon CNVs the most difficult exon CNV to detect.

  Dataset EGAD00001003335

• MicroRNAs, Hypertension and End Organ Damage in Humans

  Study 1) Profiling of microRNAs in plasma of patients with hypertension complicated or not by metabolic syndrome or chronic kidney disease Hypertension (HTN) or high blood pressure is associated with subclinical target organ damage such as cardiac, vascular and kidney injury, which may lead to complications and death. In this study, we investigated circulating microRNAs as biomarkers of target organ damage in HTN patients. We profiled circulating microRNAs by RNA sequencing in platelet-poor plasma of normotensive subjects and patients with HTN complicated or not by metabolic syndrome (MetS) or chronic kidney disease (CKD) (n=15 each group). Differentially expressed microRNAs were identified with a threshold of false discovery rate <0.1. Differentially expressed microRNAs were identified uniquely to associate with HTN (8), MetS (1) or CKD (13), and 8 were similarly differentially expressed in different groups. This study identified the association of differentially expressed circulating microRNAs with target organ damage in HTN patients, which could have some pathophysiological and therapeutic implications. Study 2) Profiling of microRNAs in gluteal subcutaneous small arteries of patients with hypertension complicated or not by chronic kidney disease Hypertension (HTN) is associated with vascular damage characterized by endothelial dysfunction and vascular remodeling and stiffening, which contributes to kidney injury leading to chronic kidney disease (CKD). MicroRNAs are short non-coding RNAs which repress/degrade target mRNAs. The microRNA role in vascular injury in HTN remains unclear. In this study, we aimed to identify differentially expressed microRNAs in small arteries of patients with HTN associated or not with CKD, in order to shed light on the pathophysiological molecular mechanisms. Normotensive subjects and HTN patients associated or not with CKD grades 3-4 were studied (n=15-16). Small arteries were isolated from subcutaneous gluteal biopsies, RNAs were extracted, and small and total RNA sequencing was performed by Illumina HiSeq-2500. Differentially expressed genes were identified with a P<0.05 and fold change (FC) >1.3. Differentially expressed microRNAs and mRNAs were identified uniquely to associate with HTN (microRNAs: 10, mRNAs: 68), CKD (microRNAs: 68, mRNAs: 395), and both groups (microRNAs: 2, mRNAs: 32). This study identified differentially expressed microRNAs and mRNAs in small arteries with target organ damage in HTN, which could have some pathophysiological and therapeutic implications.

  Study phs002389

• 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

• Dataset for NSCLC-RNA

  Rare cancer sequencing data of 45 runs in tumor/control pairs, which were uploaded to umbrella studies. The sequencing was always paired

  Dataset EGAD00001008846

• The Mutational Landscape of CTCL and Sezary Syndrome

  Sezary syndrome is a leukemic and aggressive form of cutaneous T-cell lymphoma (CTCL) resulting from the malignant transformation of skin-homing central memory CD4+ T cells. To identify new genetic alterations involved in Sezary syndrome and CTCL transformation we performed whole-exome sequencing of tumor-normal sample pairs from 26 Sezary syndrome and 16 CTCL patients. These analyses revealed a distinctive pattern of somatic copy number alterations in Sezary syndrome including highly prevalent recurrent chromosomal deletions involving the TP53, RB1, PTEN, DNMT3A, and CDKN1B tumor suppressor genes. Mutation analysis identified a broad spectrum of somatic mutations involving key genes involved in epigenetic regulation (TET2, CREBBP, MLL3, BRD9, SMARCA4 and CHD3) and signaling, including mutations in MAPK1, BRAF, CARD11 and PRKG1 driving increased MAPK, NFKB and NFAT activity upon T-cell receptor stimulation. Collectively, our findings provide new insights into the genetics of Sezary syndrome and CTCL and support the development of personalized therapies targeting key oncogenically activated signaling pathways for the treatment of these diseases.

  Study phs000994

• Genetics of Glucose Regulation in Gestation and Growth (Gen3G) Cohort - Placenta Transcriptomics RNA Sequencing

  The overarching goals of Genetics of Glucose regulation in Gestation and Growth (Gen3G) are to increase our understanding of biological, environmental, and genetic determinants of glucose regulation during pregnancy and their impact on fetal/child development. Gen3G is a prospective cohort study: we initially recruited 1,024 pregnant women between 2010-2013 at Blood Sampling in Pregnancy Clinic during the first trimester of pregnancy (median 9 weeks of gestation) in Sherbrooke, Québec, Canada. We assessed 898 pregnant women at second trimester (median 26 weeks of gestation), when participants completed a 75g oral glucose tolerance test (OGTT) as clinically indicated for screening of gestational diabetes mellitus (GDM). We collected data for 854 mother-child dyads at delivery (from medical records), in addition to placenta and/or cord blood samples in majority of newborns.The overall goal of the grant that supported data that is included in this dbGaP submission was to discover novel placental factors that regulate glucose metabolism in pregnancy and predict GDM by conducting genome-wide transcriptomics (RNA and miRNA) in carefully collected placenta samples from Gen3G.

  Study phs003151