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• McGill Cord Blood Methylome Capture Sequencing Data

  The study includes methylC-capture sequencing (MCC-Seq) on 73 cord blood DNA samples from the result of natural pregnancies (control) and through the assisted reproductive technologies for infertile couples (ART/infertile). Samples were collected as a part of the Quebec-based 3D (Design, Develop, Discover) longitudinal pregnancy cohort study. All the data were generated with 100bp paired-end reads using the Illumina NovaSeq 6000 systems.

  Dataset EGAD00001009495

• Single-cell RNA sequencing of breast cancer lung metastasis and adjacent normal tissue

  This dataset contains single-cell RNA sequencing data from two samples: L1 (breast cancer metastasis to lung) and N3 (adjacent normal lung tissue) from a female patient. The samples were processed using 10X Chromium 3' technology and sequenced on Illumina NextSeq 500. This data supports the study "Endocrine therapy reprogramming of breast cancer facilitates metastatic escape via upregulation of P-Rex1/Rac1 signalling" which investigates how endocrine therapy reprograms breast cancer cells, leading to upregulation of P-Rex1/Rac1 signalling pathways that facilitate metastatic escape. The single-cell analysis reveals cellular reprogramming mechanisms in endocrine therapy-resistant breast cancer cells that form metastases in the lung.

  Dataset EGAD00001015769

• Multiregion Whole Exome sequencing of pHGG and DIPG

  The failure to develop effective therapies for paediatric glioblastoma (pGBM) and diffuse intrinsic pontine glioma (DIPG) is in part due to their intrinsic heterogeneity. Analysis of 142 sequenced cases revealed multiple tumour subclones, spatially and temporally co-existing in a stable manner as observed by multiple sampling strategies. This dataset provides multi region sequencing of high grade gliomas and diffuse intrinsic pontine gliomas from 15 patients. DNA was extracted from FFPE sections in 2-13 regions of each tumour and sequenced with Agilent SureSelect whole exome sequencing. Germline DNA was also sequenced in 14 cases. Data was aligned to hg19 with bwa and is provided as 79 separate BAM files.

  Dataset EGAD00001004114

• Bulk RNA-seq dataset of Single cell RNA sequencing reveals induced bifurcated differentiation after RUNX1::RUNX1T1 depletion in patient-derived leukemic blasts

  In this study, we demonstrate that primary AML cells harboring the chromosomal translocation t(8;21) are critically dependent on the corresponding fusion gene, RUNX1::RUNX1T1, to suppress differentiation and maintain stemness. Silencing RUNX1::RUNX1T1 expression using siRNA-loaded lipid nanoparticles induces significant changes in chromatin accessibility, redirecting the leukemia-associated transcriptional network towards a myeloid differentiation program. Single-cell analyses reveal that this transcriptional reprogramming is associated with the depletion of immature stem and progenitor-like cell populations, accompanied by an expansion of granulocytic and eosinophilic/mast cell-like populations with impaired self-renewal capacity.

  Dataset EGAD00001015508

• C9orf72 region reads of 3001 samples

  This dataset includes cram files from 3,001 samples. These cram files include all read pairs where at least one of the reads aligns within 1kb of the C9orf72 repeat expansion. Additionally, these cram files also contain reads that are aligned to any of 29 pre-determined off target locations where the aligners are known to mis-align reads associated with this repeat expansion. These samples were sequenced using a combination of 2x100bp reads on an Illumina HiSeq2000 and 2x150bp reads on an Illumina HiSeqX sequencer and aligned using the Isaac aligner.

  Dataset EGAD00001004834

• Role of Epigenetic Memory in Human Induced Pluripotent Stem Cells Pilot

  Fibroblasts have been shown to re-program into induced pluripotent stem (hiPS) cells, through over-expression of pluripotency genes. These hiPS cells show similar characteristics to embryonic stem cells including cell surface markers, epigenetic changes and ability to differentiate into the three germ layers. However it is unclear as to the extent of changes in gene expression through the re-programming process.. This data is part of a pre-publication release. For information on the proper use of pre-publication data shared by the Wellcome Trust Sanger Institute (including details of any publication moratoria), please see http://www.sanger.ac.uk/datasharing/

  Dataset EGAD00001000828

• Archive growth Statistics

  EGA Statistics Bibliography Growth Community Archive Distribution Catalogue In this section, we expose the overall volume of data available to download and the different archived file types. EGA Archive growth in size and number of files The below figure represents the EGA archive growth in size (TB) and number of files. EGA Archive Growth per year lineChart('ega-archive-growth', 'https://stats.ega-archive.org/growth/archive', ['Volume (TB)'], ['T']) Archive files The below figure represents on a initial level, the percentage of archived files by data technology. The second level, acessible by clicking in the required extension, displays the number of files by extension archived in the ega archive. Please click over the extension to learn more about the files. EGA Archived Files barChart('ega-archived-files', 'https://stats.ega-archive.org/extensions', false ,'', true)

  Documentation about/statistics/archive

• Dichotomous regulation of lysosomes by MYC and TFEB controls hematopoietic stem cell fate

  We show that lysosomes are antagonistically controlled by TFEB and MYC to balance catabolic and anabolic processes required for activating LT-HSC and guiding their lineage fate. TFEB-mediated induction of the endolysosomal pathway for membrane receptor degradation limits LT-HSC metabolic and mitogenic activation; this promotes quiescence and self-renewal and governs erythroid-myeloid commitment. By contrast, MYC engages biosynthetic processes while repressing lysosomal catabolism to drive LT-HSC activation. Collectively, our study identifies lysosomes as a central regulatory hub for proper and coordinated stem cell fate determination.

  Dataset EGAD00001006884

• GeneSTAR (Genetic Study of Atherosclerosis Risk) NextGen Consortium: Functional Genomics of Platelet Aggregation Using iPS and Derived Megakaryocytes

  The causal mechanisms of common diseases and their therapies have been only marginally illuminated by genetic variants identified in genome wide association studies (GWAS) utilizing single nucleotide polymorphism (SNPs). Platelet activation pathways reflecting hemostasis and thrombosis are the underlying substrate for many cardiovascular diseases and related acute events. To overcome GWAS limitations, genomic studies are needed that integrate molecular surrogates for platelet-related phenotypes assayed in cell-based models derived from individuals of known genotypes and phenotypes. In our GWAS study of native platelet aggregation phenotypes and aggregation in response to low dose aspirin in 2200 subjects (GeneSTAR, Genetic Study of Aspirin Responsiveness), important genome wide "signals" (p<5x10-8) associated with native platelet aggregation and important "signals" associated with platelet responsiveness to aspirin were identified and replicated. Although we are currently performing functional genomics studies to elucidate our most promising findings in known genes (PEAR1, MET, PIKC3G), most "signals" occurred in intergenic regions or in introns. Mechanistic interpretation is limited by uncertainty as to which gene(s) are up- or down-regulated in the presence of most SNP modifications. In this 3 phase proposal, we will (1) create pluripotent stem cells (iPS) from peripheral blood mononuclear cells, and then differentiate these stem cells into megakaryocytes (2) develop an efficient strategy to produce iPS and megakaryocytes using a novel pooling method, and (3) produce iPS and megakaryocytes from 250 subjects in GeneSTAR (European Americans and African Americans), selected based on specific hypotheses derived from GWAS signals in native and post aspirin platelet function; characterize genetic mRNA transcripts using a comprehensive Affymetrix array; measure protein expression for transcripts of interest using mass spectrometry; examine mRNA and protein expression patterns for each GWAS signal to determine the functional pathway(s) involved in native platelet phenotypes; and examine the functional genomics of variations in responsiveness to aspirin using our prior genotyped and phenotyped population. Precise information about the exact functional processes in megakaryocytes and platelets may lead to innovative and tailored approaches to risk assessment and novel therapeutic targets to prevent first and recurrent cardiovascular and related thrombotic events.

  Study phs001074

• NICHD Genomic and Proteomic Network for Preterm Birth Research (GPN)

  We performed genome-wide association studies (GWAS) to study the Spontaneous Preterm birth (SPTB). Maternal and neonatal DNA from 743 SPTB (20 to and less than 34 weeks), and 752 controls (39 to and less than 42 weeks) who fully consented for public research usage were collected from participants in several clinical centers in Alabama, Illinois, New York, North Carolina, Rhode Island, Texas, and Utah. Cases were 1:1-matched with controls according to race/ethnicity (White, Hispanics, African Americans, and Others), maternal age (<20, 20-29, 30-39, 40+), and parity (yes or no). To determine the case-control status for each participant, a Gestational Age (GA) was determined. DNA samples were taken from blood or saliva if blood was not available. Automated DNA extractions were performed on the Qiagen M48 robot, and samples were organized in 96-well plates with barcoding and sample tracking systems. Subsequent manipulations were performed on the Biomek FX liquid handling workstation with 96-channel pipetting. DNA quantitation was performed by dye-based assay on a Molecular Devices SpectraMax Plus plate reader. Samples were genotyped using Affymetrix Genome-Wide Human SNP Array 6.0. This work was conducted at the Microarray Facility at the University of Pennsylvania. Patient data were collected through chart reviews and patient interviews, which included Demographic information (parental age, race, ethnicity, etc.); Medical history (pre-pregnancy weight, height, medications, STD history, medical conditions, etc.); Social history (marital status, years of education, alcohol use and tobacco use); Obstetrical history including outcome of all prior pregnancies and dates of termination; History of preterm labor or premature rupture of membranes symptoms, evaluation or hospitalization for those symptoms in current pregnancy; Medications taken during current pregnancy; History of cervical evaluation (manually or ultrasonographically) or fetal fibronectin measurements; Pregnancy complications; Labor (type, indications, membrane status, and induction method); Delivery type and indications for cesarean section; Neonatal outcome (sex, weight, length, Apgar score, neonatal complications, admission to intensive care unit, etc.); and Maternal family history of SPTB.

  Study phs000714

• Type 1 Diabetes Genetics Consortium (T1DGC): Genome-Wide Association Study in Type 1 Diabetes, 2008

  Cases with Type 1 Diabetes (T1D) in the UK, were part of the Wellcome Trust Case Control Consortium (WTCCC) - http://www.wtccc.org.uk - that first reported in 2007: Wellcome Trust Case Control Consortium (2007) Genome-wide association study of 14,000 cases of seven common diseases and 3,000 shared controls. Nature, 447, 661-678. [PubMed: 17554300] In this genome-wide association study (GWAS), funded by the NIH and JDRF, and sponsored by the Type 1 Diabetes Genetics Consortium (T1DGC), we were able to extend the case and control groups used in the WTCCC, with the intention of performing a well-powered meta-analysis. The study is written up as: Barrett, J.C., Clayton, D.G., Concannon, P., Akolkar, B., Cooper, J.D., Erlich, H.A., Julier, C., Morahan, G., Nerup, J., Nierras, C., Plagnol, V., Pociot, F., Schuilenburg, H., Smyth, D.J., Stevens, H., Todd, J.A., Walker, N.M., Rich, S.S. and The Type 1 Diabetes Genetics Consortium Genome-wide association study and meta-analysis find that over 40 loci affect risk of type 1 diabetes. Nature Genetics, PMID: 19430480. Resources - data: * Case data from this study is deposited here (i.e. in dbGaP) * Control data from this experiment - with subjects from the 1958 British Birth Cohort - is deposited with the European Genotype Archive (EGA): http://www.ebi.ac.uk/ega/ from where the WTCCC data is also available. * A complete description of how to request all components of the meta-analysis is available at: http://www.t1dbase.org/page/PosterView/display/poster_id/324 * Additional genetic data on the same case subjects, including some HLA types, are available from the Juvenile Diabetes Research Foundation/Wellcome Trust Diabetes and Inflammation Laboratory (JDRF/WT-DIL): http://www-gene.cimr.cam.ac.uk/todd/ Resources - samples: Case and control DNA samples are also available: * Case DNA samples are available from the JDRF/WT-DIL, as above, and will be available from the NIDDK Genetics Repository at Rutgers: https://www.niddkrepository.org * Control DNA samples are available from the 1958 British Birth Cohort (aka National Child Development Study): http://www.cls.ioe.ac.uk/studies.asp?section=000100020003 Use restrictions: There are access limitations to both data and samples, in order to keep their use in line with subjects' consent.

  Study phs000180

• Copy-Number Analysis of Understudied Black Women Ovarian Cancers

  Two general types of genetic alterations drive cancer progression: mutations and copy number alterations (CNAs). With the exception of p53, single nucleotide variant mutations (here, simply "mutations") are not drivers of 80% of tumors within the most frequent and deadly histotype of ovarian cancer: serous ovarian cancer (SOC). Rather, CNAs are more prevalent in SOC than any other cancer type studied by phs000178 The Cancer Genome Atlas (TCGA). Fully two-thirds of genes are altered by CNAs in the average SOC. Bioinformatic methods have shown that these CNAs modulate specific molecular pathways, such as autophagy, and this finding enabled effective pathway-targeted therapies1. Unfortunately, TCGA ovarian cancer data lacks racial diversity. Only 6% of SOC tumors (n=32) studied are from African origin. Black women diagnosed with ovarian cancer are more likely to die from their disease than white women. Five-year survival after diagnosis is 31% among blacks versus 42% among whites, and this disparity is seen in every age group and tumor stage distribution. Dr. Kelemen examined data from 365 white and 95 black ovarian cancer patients from the Hollings Cancer Center (HCC) Cancer Registry between 2000 and 2015 and found that black women had an 81% higher risk of death after diagnosis compared to white women (HR 1.81, 95% CI 1.35-2.43), independent of diagnosis center (98% were treated at HCC but half were diagnosed elsewhere), tumor stage, histology, extent of residual tumor remaining following surgery, insurance status, smoking, type of treatment for ovarian cancer, and age-adjusted Charlson comorbidity index. This disparity remained even when restricted to women who received the standard of care, surgery-chemotherapy sequence (HR 1.79, 95% CI 1.10-2.89). Despite receiving the same treatment, black race was still associated with inferior survival. A similar disparity has been reported by others, indicating that the HCC experience is representative of national data. Here, an additional set of high-grade serous ovarian cancer primary tumors were acquired from biorepositories with a focus on expanding data originating from African American women. Data were analyzed for copy-number alterations using exome sequencing and control-FREEC software.

  Study phs002313

• RNA-Seq of Whole Blood from Patients with Intracranial Aneurysms

  Rupture of intracranial aneurysms (IAs) causes intracranial hemorrhaging that leads to high rates of neurological deficits and death. Although rupture rates are low, clinicians must decide whether to treat or monitor these potentially dangerous lesions. In the current clinical practice, the most common metric to measure risk of rupture is aneurysm size. However, clinical data show that small aneurysms can also rupture. As a result, alternative clinical stratification scores have been proposed, including the PHASES (Population, Hypertension, Age, Size, Earlier subarachnoid hemorrhage, and Site) score based on patient demographics and IA characteristics to stratify ruptured and unruptured IAs, and the Rupture Resemblance Score (RRS) that stratifies ruptured and unruptured IAs based on hemodynamic and morphological properties. However, all metrics require imaging on digital subtraction angiography (DSA), which is invasive, expensive, requires the use of X-rays, and is associated with transient or permanent neurological and non-neurological complications. We hypothesize that individuals with dangerous IAs have detectable gene expression differences in their blood that could be used as biomarkers to determine rupture risk. We propose to use whole blood transcriptomes to develop a "one-stop" diagnostic test that can detect the presence of IAs and determine the risk of rupture based on circulating RNA expression biomarkers using our prototype AneuScreenTM platform. We aim to develop and validate biomarkers to predict risk, as calculated by the currently-used metric of aneurysm size, the clinical PHASES score, and the RRS. Here, we collected blood samples from consented individuals who were receiving cerebral imaging at the Gates Vascular Institute (Buffalo, NY) for intracranial aneurysm. RNA extracted from blood samples (n=43) was subjected to RNA-sequencing and added to our existing database (n=44). When combined with our previous data, we had transcriptome data from 68 aneurysms (after additional sample filtering). This dataset was stratified into low- and high-risk according to IA size, PHASES score, and RRS score. Differentially expressed genes were identified and used to construct predictive models. Fastq files and basic demographic information for the 43 newly-sequenced intracranial aneurysm samples on this project will be available through dbGaP.

  Study phs003072

• NHLBI GO-ESP: Early-Onset Myocardial Infarction (Broad EOMI)

  The NHLBI "Grand Opportunity" Exome Sequencing Project (GO-ESP), a signature project of the NHLBI Recovery Act investment, was designed to identify genetic variants in coding regions (exons) of the human genome (the "exome") that are associated with heart, lung and blood diseases. These and related diseases that are of high impact to public health and individuals from diverse racial and ethnic groups will be studied. These data may help researchers understand the causes of disease, contributing to better ways to prevent, diagnose, and treat diseases, as well as determine whether to tailor prevention and treatments to specific populations. This could lead to more effective treatments and reduce the likelihood of side effects. GO-ESP is comprised of five collaborative components: 3 cohort consortia - HeartGO, LungGO, and WHISP - and 2 sequencing centers - BroadGO and SeattleGO. In the Grand Opportunities Exome Sequencing Program Early MI Project (GO ESP - EOMI), we are sequencing cases with extremely early-onset MI drawn from 8 cohorts. These cohorts include five hospital or community-based studies that ascertained individuals based on MI status. These include PennCATH, Cleveland Clinic Genebank, Massachusetts General Hospital Premature Coronary Artery Disease Study (MGH-PCAD), Heart Attack Risk in Puget Sound (HARPS), and Translational Research Investigating Underlying Disparities in Myocardial Infarction Patients' Health Status (TRIUMPH). Cases were selected based on MI occurring in men aged ≤50 years and women aged ≤60 years. In addition, early-MI cases are being drawn from three population-cohort studies including the Framingham Heart Study, the Women's Health Initiative, and the Atherosclerosis Risk in Communities Study. MI-free controls are being drawn from five population-based cohort studies including the Framingham Heart Study, the Women's Health Initiative, Atherosclerosis Risk in Communities Study, Cardiovascular Health Study, and the Jackson Heart Study. Controls were selected based on two factors: (1) highest predicted risk for MI based on Framingham risk score; and (2) absence of prevalent or incident MI despite a high predicted risk.

  Study phs000279

• Centers for Common Disease Genomics (CCDG) - Whole Genome Sequencing in Type 1 Diabetes (T1DGC)

  The Type 1 Diabetes Genetics Consortium (T1DGC) was established to collect resources (biological samples and data) and conduct research to better understand the genetic basis of type 1 diabetes (T1D). Collection was initiated by ascertaining affected sib-pair families (both parents, two affected siblings and, when available, an unaffected sibling), collected from five geographic regions through four recruitment networks (Asia-Pacific, Europe, North America, United Kingdom). In addition, the T1DGC collected trio families (both parents and affected child) and cases and controls from low-prevalence populations (African-American, with four grandparents self-reporting as African ancestry; Mexican-American, with four grandparents self-reporting as ancestry from Mexico). The T1DGC also served as a repository for contributed collections from other studies, all meeting the broad data-sharing policy of the T1DGC, for inclusion in the genetic studies. These collections include T1D case samples ascertained from the UK Genetic Resource Investigating Diabetes (UK GRID) cohort, SEARCH for Diabetes in Youth (SEARCH), The Genetics of Kidneys in Diabetes (GoKinD), and control samples obtained from the British 1958 Birth Cohort, the UK National Blood Services collection, CLEAR (Consortium for the Longitudinal Evaluation of African-Americans with Early Rheumatoid Arthritis), the New York Cancer Project (NYCP), and other cohorts. For the NHGRI-funded Centers for Common Disease Genomics (CCDG) project, participants with T1D and ancestry-matched controls were identified through the T1DGC, either through direct ascertainment or by contribution from other sources to the T1DGC. As the CCDG has focused initially on non-Caucasian populations for whole genome sequencing, T1DGC participants of African, Mexican and Asian ancestry (targeting ~1200 cases and ~1200 controls in each ancestral group) and a small group of participants of Northern European ancestry (~100 cases, ~100 controls) were to be contributed to the study. Whole genome sequencing of T1DGC samples would be conducted at Washington University McDonnell Genome Institute and based upon matching case-control status within an ancestry group and prioritization by the CCDG.

  Study phs001222

• NIDDK IBD Genetics Consortium Ulcerative Colitis Genome-Wide Association Study

  This dataset contains data for 1,028 white, non-Hispanic, European ancestry individuals with ulcerative colitis who were included in a genome-wide association study published by Silverberg et al. (2009). These individuals were ascertained in North America and selected to have either left-sided or extensive disease (i.e., individuals with proctitis only were excluded). Genotyping was performed using the Illumina HumanHap300v2 (n = 540) and HumanHap550v3 (n = 488) Genotyping BeadChips at the Feinstein Institute for Medical Research. Control data (not included) were obtained from the NIDDK IBD Genetics Consortium's Crohn's Disease GWAS (available from dbGaP) and from studies 64 and 65 deposited in the Illumina iControlDB. Seven hundred eighty individuals in this dataset were taken from the NIDDK IBD Genetics Consortium cell line repository (http://www.niddkrepository.org). These individuals are identified in the file dbGaP_SubjectDS.txt. The subject IDs for these individuals may be used to request corresponding samples for follow-up research through the repository. In addition, complete phenotype data for these individuals are included, collected using the Consortium's forms and phenotyping manual (both included). The remaining 248 individuals were identified from pre-existing collections ascertained by members of the Consortium or their collaborators. For these samples, several of the items in the phenotype file are incomplete. Those who wish to replicate the results in Silverberg et al. should note that 6 individuals with missing genotype rates > 0.07 were excluded from that analysis (leaving 1,022 affected samples total). In addition, the minor allele frequencies (MAFs) reported in the publication were calculated using only those individuals who were included in the allelic association tests (n = 977 for SNPs included in the HumanHap300 and n = 476 for SNPs included only in the HumanHap550). These tests were performed using conditional logistic regression on gender-ancestry strata; individuals who were not placed in a stratum (using the procedure described in the supplementary information for Silverberg et al.) were excluded. The indicator variables hh300 and hh550 in the file dbGaP_PhenotypeDS.txt identify the samples included in the allelic association tests, and may be used to replicate the published MAFs among affected individuals.

  Study phs000345

• Genome-Wide Pleiotropy Scan Across Multiple Cancers

  A whole-exome sequencing (WES) study was conducted in 3,233 cases diagnosed with multiple primary cancers and 3,229 matched cancer-free controls (90% non-Hispanic white, 3% African-American, 3% East Asian, and 4% Latino) selected from individuals in the Kaiser Permanente Research Bank (KPRB) who were members of the Kaiser Permanente Northern California (KPNC) health plan. Cancer-free controls were matched to cases on age at specimen collection (within 2 years), sex, genotyping array (which matched on self-reported race/ethnicity), closest distance using the first two principal components for genetic ancestry, and reagent kit. Cases and controls were drawn from two prospective KPRB cohorts: the Research Program on Genes, Environment and Health (RPGEH) and the ProHealth study. Participants were sequenced by the Regeneron Genetics Center using the Illumina NovaSeq 6000 platform, and sample preparation and quality control were performed using a high-throughput, fully-automated system [PMID: 33087929]. Reads were aligned to the GRCh38 reference genome, and variants were called using WeCall [PMID: 33087929]. Participants with sex discordance, 20x coverage at less than 80% of targeted sites, and/or contamination greater than 5% were excluded. After quality control, we retained n = 6,247 (3,111 cases, 3,136 controls) individuals for downstream analyses. Among participants selected for this WES study, n = 5,432 (2,299 cases; 3,133 controls) consented to deposition of data to the National Institutes of Health (NIH).Further quality control was applied to filter low quality variants. Genotype calls with low depth of coverage (DP) were updated to missing (DP < 7 for SNPs and DP < 10 for indels), after which sites with low allele balance (AB) - variants without at least one sample having AB ≥ 15% for SNPs or AB ≥ 20% for indels - were removed. Lastly, variants with missingness > 10% and Hardy-Weinberg equilibrium p-value < 10-15 were excluded. Further description of quality control and downstream single-variant and gene-based analyses is available in Cavazos et al, 2022 [medRxiv].

  Study phs002809

• B cell receptor silencing reveals origin and dependencies of high-grade B cell lymphomas with MYC and BCL2 rearrangements

  High-grade B cell lymphomas with MYC and BCL2 rearrangements (HGBCL-DH-BCL2) represent highly aggressive Germinal center (GC) derived B cell malignancies with dismal prognosis and limited therapeutic options. In the present study, we investigated the expression of BCR complex components, including immunoglobulin (IG) heavy (H) and light (L) chains, and CD79A and CD79B signaling subunits in HGBCL-DH-BCL2, scoring 65% of cases with undetectable IGH immunoreactivity (IGHUND). Transcriptomics (bulk RNA-seq) and genetic (whole exome/genome sequencing) analyses indicated that IGHUND and IGH+ HGBCL-DH-BCL2 lymphomas represent distinct biological entities. Specifically, IGHUND HGBCL-DH-BCL2 exhibit a GC DZ-like molecular program, and select subset-specific gene mutations pointing to distinct evolutionary trajectories respect to the IGH+ counterparts. IG profiling revealed that IGHUND HGBCL-DH-BCL2 preserved potentially productive, hypermutated IGH variable (V) gene rearrangements, indicating a selective advantage conferred to the malignant B cells by residual IGH molecules. Accordingly, disruption of the productively rearranged IGHG1 gene in BCRnull HGBCL-DH-BCL2 cell line model confirmed the dependency on IGH expression for optimal fitness. Using transcriptomics and in situ RNA-scope analysis, we reported that IGHUND HGBCL-DH-BCL2 originated from IG-class switched GC B cells, while IGH-expressing tumors were selected for continuous IGM expression. Moreover, while IGH+ HGBCL-DH-BCL2 favor IGM/IG-Kappa expression, IGHUND counterparts complete IG-Lambda light chain rearrangements. Notably, BCR silencing, caused by accelerated IGH turnover and reduced IGH expression, precedes HGBCL-DH-BCL2 onset, inducing RAG1/2-dependent IG light chain editing and eventually facilitating t(8;22)/IGL::MYC translocations. Finally, IGH silencing observed in HGBCL-DH-BCL2 cell models, which leads to intracellular retention/silencing of CD79B, results in reduced sensitivity to the CD79B-targeting antibody-drug conjugate Polatuzumab-vedotin. Collectively, HGBCL-DH-BCL2 originates from isotype-switched t(14;18)+ GC B cells that undergo IG light chain editing fuelling intra-clonal diversification, BCR silencing, and the acquisition of t(8;22) translocation, while preserving IGH dependency.

  Study EGAS50000001047

• Geographical structure and differential natural selection among North European populations

  European populations and epidemiological cohorts are of special significance in the current era of genomic research aiming to characterize the background of common human diseases. The genome sequence, detailed information of genetic variations between individuals, high-throughput molecular technologies and novel statistical strategies create new possibilities to define genetic and life-style risk factors behind common health problems. Studies of large population cohorts are needed to transform the genetic information to detailed understanding of the predisposing factors in diseases affecting most human populations. European twin cohorts provide a unique competitive advantage for investigations of the role of genetics and environment or life style in the etiology of common diseases. This project will apply and develop new molecular and statistical strategies to analyze unique European twin and other population cohorts to define and characterise the genetic, environmental and life-style components in the background of health problems like obesity, migraine, coronary heart disease and stroke, representing major health care problems worldwide.

  Study EGAS00000000033

• Karyotype Evolution in Response to Chemoradiotherapy and Upon Recurrence of Esophageal Adenocarcinomas

  The genome of esophageal adenocarcinoma (EAC) is highly unstable and might evolve over time. Here, we track karyotype evolution in EACs in response to treatment and upon recurrence through multi-region and longitudinal analysis. To this end, we introduce L-PAC, a bio-informatics technique that allows inference of absolute copy number aberrations (CNA) of low-purity samples by leveraging information of high-purity samples from the same cancer. Quantitative analysis of matched absolute CNAs reveals that the amount of karyotype evolution induced by chemoradiotherapy (CRT) is predictive for early recurrence and depends on the initial level of karyotype intra-tumor heterogeneity. We observe that CNAs acquired in response to CRT are partially reversed back to the initial state upon recurrence. CRT hence alters the fitness landscape to which tumors can adjust by adapting their karyotype. Together, our results indicate that karyotype plasticity contributes to therapy resistance of EACs.

  Study EGAS00001007711

• Multiomic spatial landscape of innate immune cells at central nervous system borders

  The innate immune compartment of the human central nervous system (CNS) is highly diverseand includes several immune cell populations such as macrophages that are frequent in the brain parenchyma (microglia) and less numerous at the brain interfaces as CNS-associated macrophages (CAMs).Due to their scantiness and particular location, little is known about the presence of temporally and spatially restricted CAM subclasses during development, health and perturbation. Here, we combined single-cell RNA-sequencing, time-of-flight mass cytometry and single-cell spatial transcriptomics with fate mapping and advanced immunohistochemistry to comprehensively characterize the immune system at human CNS interfaces. We also provide a comprehensive analysis of resident and engrafted myeloid cells in the brains of 15 individuals with peripheral blood stem cell transplantation, revealing compartment-specific engraftment rates across different CNS interfaces... Our results highlight myeloid diversity at the interfaces of the human CNS with the periphery and provide insights into the complexities of the human brain’s immune system.

  Study EGAS50000000030

• Analysis of AR Gene Rearrangements in Prostate Cancer

  Molecularly-targeted therapies for advanced prostate cancer include castration modalities that suppress ligand-dependent transcriptional activity of the androgen receptor (AR). However, persistent AR signaling undermines therapeutic efficacy and promotes progression to lethal castration-resistant prostate cancer (CRPC), even when patients are treated with potent second-generation AR-targeted therapies abiraterone and enzalutamide. Here we define diverse AR genomic structural rearrangements (AR-GSRs) as a class of molecular alterations occurring in one third of CRPC-stage tumors. AR-GSRs occur in the context of copy-neutral and amplified AR and display heterogeneity in breakpoint location, rearrangement class, and sub-clonal enrichment in tumors within and between patients. Despite this heterogeneity, one common outcome in tumors with high sub-clonal enrichment of AR-GSRs is outlier expression of diverse AR variant species lacking the ligand binding domain and possessing ligand-independent transcriptional activity. Collectively, these findings reveal AR-GSRs as important drivers of persistent AR signaling in CRPC.

  Study phs001223

• Genome-Wide Association Study of Endometrial Cancer in the Epidemiology of Endometrial Cancer Consortium (E2C2)

  Endometrial cancer, the most common gynecological malignancy in the United States, has both an environmental and genetic component. To this end, we conducted a genome-wide association study to identify genes involved in endometrial cancer using studies from the NCI-supported Epidemiology of Endometrial Cancer Consortium (E2C2). For the discovery stage we included samples from 6 cohort and 7 case control studies through 2007. The total number of cases genotyped were 2,307, white women of European descent, and 2,307 matched controls using the Illumina HumanOmniExpress platform. We conducted the replication using the Infinium HumanExome BeadChip, which successfully genotyped 177,139 variants in 1055 cases and 1778 controls from four ethnically diverse studies that are part of the Epidemiology of Endometrial Cancer Consortium (E2C2). The overall goal is to determine whether certain genotypes are predictive of future endometrial cancer risk, and whether the genotypes interact with established endometrial risk factors.

  Study phs000893

• Genetic Effects on Gene Expression and Splicing during Human Neurogenesis

  Interpretation of the function of non-coding risk loci for neuropsychiatric disorders and brain-relevant traits via gene expression and alternative splicing quantitative trait locus (e/sQTL) analyses is generally performed in bulk post-mortem adult tissue. However, genetic risk loci are enriched in regulatory elements active during neocortical differentiation, and regulatory effects of risk variants may be masked by heterogeneity in bulk tissue. Here, we map e/sQTLs, and allele-specific expression in cultured cells representing two major developmental stages, primary human neural progenitors (n=85) and their sorted neuronal progeny (n=74), identifying numerous loci not detected in either bulk developing cortical wall or adult cortex. Using colocalization and genetic imputation via transcriptome-wide association, we uncover cell-type specific regulatory mechanisms underlying risk for brain-relevant traits that are active during neocortical differentiation. Specifically, we identified a progenitor-specific eQTL for CENPW co-localized with common variant associations for cortical surface area and educational attainment.

  Study phs002493

• Nasopharynx Cancer Whole Exome Sequencing

  Nasopharyngeal carcinoma (NPC) is an aggressive head and neck cancer characterized by Epstein-Barr virus (EBV) infection and dense lymphocyte infiltration. The scarcity of NPC genomic data hinders the understanding of NPC biology, disease progression, and rational therapy design. Here, we performed whole-exome sequencing (WES) on 111 micro-dissected EBV-positive NPCs, with 15 cases subjected to further whole-genome sequencing (WGS), to determine its mutational landscape. We identified enrichment for genomic aberrations of multiple negative regulators of the NF-kB pathway in a total of 41% of cases including CYLD, TRAF3, NFKBIA and NLRC5. Functional analysis confirmed novel inactivating CYLD mutations as drivers for NPC cell growth. The EBV oncoprotein latent member protein 1 (LMP1) functions to constitutively activate NF-kB signaling, and we observed mutual exclusivity among somatic NF-kB pathway aberrations and LMP1-overexpression, suggesting that NF-kB activation is selected for by both somatic and viral events during NPC pathogenesis.

  Study phs001244