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• CRLF2_sequencing_project_

  I hope to gain insight into novel genetic aberrations present in these patients that will highlightimportant pathways that are involved in this subtype of leukaemia. It would be interesting to see ifthe mutations and pathways that are activated are consistent between the patients, or differencesare observed dependent upon whether the patient has the translocation or the PAR1 deletion. Ofnote is the high association with either numerical gains of chromosome X or numerical/structuralabnormalities of chromosome 21 (Down syndrome, iAMP21) in patients with CRLF2 deregulation. Ihope to find abnormalities linking chromosomes X and 21 to CRLF2 deregulation in BCP‐ALL. Byincluding the three patients that are normal for CRLF2, but have consistent genetic abnormalitiesfound in the experimental cohort, I expect to find genetic differences between these two groupsthat will help us to identify novel molecular targets specific to CRLF2 deregulation.

  Study EGAS00001000080

• TP53_KO_RPE1_SNPs

  Allelic imbalance data for cell lines derived from RPE1 with TP53 knockout

  Dataset EGAD00010001566

• WGS and RNA-Seq data from a GBM patient PT-AB6372

  WGS and RNA-Seq data from a GBM patient PT-AB6372

  Dataset EGAD00001004222

• WGS and RNA-Seq data from a GBM patient PT-PR5617

  WGS and RNA-Seq data from a GBM patient PT-PR5617

  Dataset EGAD00001008525

• Characterization of a novel MEF2D-BCL9 fusion positive acute lymphoblastic leukemia cell line RNA-Seq

  A novel in-house-made pediatric MEF2D-BCL9 fusion positive acute lymphoblastic leukemia cell line was characterized

  Dataset EGAD00001009759

• WGS and RNA-Seq data from a GBM patient PT-CM3220

  WGS and RNA-Seq data from a GBM patient PT-CM3220

  Dataset EGAD00001008517

• WGS and RNA-Seq data from a GBM patient PT-DM9089

  WGS and RNA-Seq data from a GBM patient PT-DM9089

  Dataset EGAD00001008518

• Whole exome sequencing of a sinonasal glomangiopericytoma case

  The is dataset includes the whole exome sequencing of the tumor from a sinonasal glomangiopericytoma case together with the matching blood. The whole exome sequencing revealed somatic PIK3CA and CTNNB1 mutations.

  Dataset EGAD00001008291

• WGS and RNA-Seq data from a GBM patient PT-CM1209

  WGS and RNA-Seq data from a GBM patient PT-CM1209

  Dataset EGAD00001004231

• Rare Genetic Steroid Disease Consortium (GSD) Apparent Mineralocorticoid Excess (AME) Syndrome Natural History Clinical Protocol

  The objective of this project is to observe the natural history of apparent mineralocorticoid excess (AME). AME is a rare monogenic hypertensive disease first described by the Principal Investigator, Dr. Maria I. New, in 1977 [1], for which the first mutation in the causative HSD11B2 gene was reported by her group in 1995. [2] Little is known about the progression of this rare hypertensive disorder, which is defined by the presence of hypertension in conjunction with low renin, low to absent levels of the mineralocorticoid aldosterone, elevated urinary cortisol/cortisone metabolite ratio 5β-tetrahydrocortisol (THF) + allo-THF/ tetrahydrocortisone (THE) (i.e., THF+αTHF/THE) and the presence of mutations in the HSD11B2 gene on both alleles. The range of symptoms reflecting progressive end-organ damage is wide in the small number of affected individuals studied to date. It is important to develop accurate information on the longitudinal pattern of progression (natural history) of AME not only because it may improve the care of affected individuals, but also because it may serve as a platform for understanding the role of mineralocorticoid excess in other forms of low-renin hypertension, which constitute 40% of all forms of hypertension. In this study, we will recruit as widely as possible through the Rare Diseases Clinical Research Network (RDCRN) to identify individuals with the triad of low renin, low aldosterone, and elevated urinary THF+αTHF/THE and confirm their disorder as AME by molecular genetic testing of the HSD11B2 gene. We will gather clinical and biochemical data yearly for the duration of the grant. We will describe phenotype and genotype at diagnosis and follow the progression or regression of symptoms over time under standard treatment, with rigorous review of end organs potentially damaged by chronic hypertension. Finally, we will study the natural history of the carriers of HSD11B2 mutations, i.e., the heterozygote relatives of the probands, in order to ascertain evidence of existing or developing hypertension and resulting end-organ damage. This will be the first rigorous study of AME heterozygotes. The participant accrual for AME-affected patients and the carriers of HSD11B2 mutations will be at least two years, but as long as seven years.

  Study phs000603

• Institut Curie Neuroblastoma Whole Genome Sequencing Diagnosis Relapse

  Neuroblastoma, a clinically heterogeneous pediatric cancer, is characterized by distinct genomic profiles but few recurrent mutations. As neuroblastoma is expected to have high degree of genetic heterogeneity, study of neuroblastoma's clonal evolution with deep coverage whole-genome sequencing of diagnosis and relapse samples will lead to a better understanding of the molecular events associated with relapse. Samples were included in this study if sufficient DNA from constitutional, diagnosis and relapse tumors was available for WGS. Whole genome sequencing was performed on trios (constitutional, diagnose and relapse DNA) from eight patients using Illumina Hi-seq2500 leading to paired-ends (PE) 90x90 for 6 of them and 100x100 for two. Expected coverage for sample NB0175 100x100bp was 30X for tumor and constitutional samples. For the seven other patients expected coverage was 80X for tumor samples with PE 100x100, 100X in the other tumor samples and 50X for all constitutional samples (see table 1). Following alignment with BWA (Li et al., Oxford J, 2009 Jul) allowing up to 4% of mismatches, bam files were cleaned up according to the Genome Analysis Toolkit (GATK) recommendations (Van der Auwera et al., Current Protocols in Bioinformatics, 2013, picard-1.45, GenomeAnalysisTK-2.2-16). Variant calling was performed in parallel using 3 variant callers: GenomeAnalysisTK-2.2-16, Samtools-0.1.18 and MuTect-1.1.4 (McKenna et al., Genome Res, 2010; Li et al., Oxford J, 2009 Aug; Cibulskis et al., Nature, 2013). Annovar-v2012-10-23 with cosmic-v64 and dbsnp-v137 were used for the annotation and RefSeq for the structural annotation. For GATK and Samtools, single nucleotide variants (SNVs) with a quality under 30, a depth of coverage under 6 or with less than 2 reads supporting the variant were filter out. MuTect with parameters following GATK and Samtools thresholds have been used to filter our irrelevant variants. .SNVs within and around exons of coding genes overlapping splice sites.. Then,variants reported in more than 1% of the population in the 1000 genomes (1000gAprl_2012) or Exome Sequencing Project (ESP6500) have been discarded in order to filter polymorphisms. Finally, synonymous variants were filtered out. MuTect focuses on somatic by filtering with constitutional sample. Mpileup comparison between constitutional and somatic DNAs allowed us to focus also on tumor specific SNVs with GATK and Samtools. Finally, every SNV called by our pipeline and also supported in any constitutional samples were filtered our in order to prevent putative constitutional DNA coverage deficiency. Then we analyzed CNVs (copy number variants) with HMMcopy-v0.1.1 (Gavin et al., Genome Res, 2012) and control-FREEC-v6.7 (Boeva et al., Bioinformatics 2011) with a respective window of 2000bp and 1000 bp, and auto-correction of normal contamination of tumor samples for Control-FREEC. Finally we explored Structural variants (SVs) including deletions, inversions, tandem duplications and translocations using DELLY-v0.5.5 with standard parameters (Rausch et al., Oxford J, 2012). In tumors, at least 10 supporting reads were required to make a call and 5 supporting reads for the sample NB0175 with a coverage of only 40X (see table 2). To predict SVs in constitutional samples for subsequent somatic filtering, only 2 supporting reads were required in order not to miss one. To identify somatic events, all the SVs in each normal sample were first flanked by 500 bp in both directions and any SVs called in a tumor sample which was in the combined flanked regions of respective normal sample was removed (see graph 1). Deletions with more than 5 genes impacted or larger than 1Mb and inversions or tandem duplications covering more than 4 genes, were removed. We focused on exonic and splicing events for deletions, inversions, and tandem duplications. For translocation, we keep all SVs that occurred in intronic, exonic, 5'UTR, upstream or splicing regions. Bioinformatics detection of variations with Deep sequencing approach Once PE reads merged and adaptors trimmed by SeqPrep with default parameters, merged reads were aligned via the BWA (Li H. and Durbin R. 2009 PMID 19451168) allowing up to 1 differences in the 22-base-long seeds and reporting only unique alignments. Only reads having a mapping quality 20 or more have been further analysed. Variant calling software was not used, since we aimed to predict variations at low frequencies, observed in less than 1% of reads. Such variants require a custom approach. Using DepthOfCoverage functions of the Genome Analysis Toolkit (GATK) v2.13.2 (McKenna A, et al., 2010 Genome Research PMID: 20644199), we focused on high quality coverage of bases A, C, G and T at the targeted variant position. Depth of coverage of each base following a mapping quality higher than 20 and a base quality higher than 10 have been taken into account in order to focus only on high quality data. Aiming to determine the background level of variability at the studied regions, 10 control samples were included in the analysis. The same approach and filtering criteria have been applied as introduced above over the entire amplicons. In order to highlight variants, for each sample the frequencies of each bases at each amplicon position were then compared to those observed in the set of controls. Statistical analyses were performed with the R statistical software (http://www.R-project.org). Fisher’s exact two-sided tests with a Bonferroni correction were performed to compare percentages of bases between the data sets, i.e. for a given base between a case and the controls. Finally, significant variations were filtered-in once (i) a significant increase in the percentage of avariant base and (ii) a significant decrease in the percentage of it's reference base following our p.values criteria was observed (p.val < 0.05).

  Dataset EGAD00001001356

• Clonal tracing with somatic epimutations reveals dynamics of blood aging

  In this study, we generated comprehensive single-cell multi-omic datasets from bone marrow samples collected from 13 donors spanning a wide age range. We applied the scTAMseq protocol to profile DNA methylation and nuclear mutations obtained from 7 total bone marrow aspirates (donors A.1-A.7) and 6 CD34+-enriched bone marrow samples ((donors B.1-B.5 & X.1). Complementary surface marker expression data were acquired by integrating CITE-seq into the scTAMseq workflow (scTAMseq_prot). Targeted RNA sequencing (scTAMARA_rna) was performed alongside scTAMARA_DNA on one CD34+-enriched sample (X.1). Additionally, a dedicated mitochondrial panel (TAMITO_seq) was employed on a peripheral blood sample from a healthy donor (X.2) to assess mitochondrial heterogeneity and facilitate lineage tracing.

  Study EGAS00001008056

• Spatial and temporal genomic evolution in glioblastoma

  Tumor heterogeneity is a challenging barrier to successful targeted therapy in glioblastoma. Identifying the mechanisms that drive cancer cells as they genetically evolve and adapt in response to treatment is a vital goal of modern cancer research. Analysis of sequencing data provides a method for uncovering the mechanisms sustaining tumor heterogeneity and driving evolution. Here, we analyzed genomic profiles of GBM biopsies taken from pre- and post-treatment GBMs (with matched germline controls), to understand 1) the intratumoral clonal compositions of primary GBM and 2) how GBM responds to therapeutic intervention. Our results provide a molecular portrait of GBM recurrence.

  Study EGAS00001001033

• Prognostic and therapeutic significance of leukemia subtypes and minimal residual disease measurements in pediatric acute lymphoblastic leukemia treated with contemporary risk-directed trial: a cohort study

  Background Genomic analyses to identify leukemia subtypes and refinement of minimal residual disease (MRD) determination are two recent advances that would have substantial impact on the management of children with acute lymphoblastic leukemia (ALL). However, the combined application of these two approaches to determine the prognostic and therapeutic significance of MRD measurement and full spectrum of leukemia subtypes in the context of contemporary risk-directed therapy has not been studied comprehensively.MethodsBetween October 29, 2007 and March 26, 2017, 598 consecutive children with newly diagnosed ALL were enrolled in a clinical trial at St. Jude Children’s Research Hospital. Patients were provisional classified according to the presenting clinical and laboratory features including immunophenotype and cytogenetics. Patients with ETV6-RUNX1 and high hyperdiploid B-progenitor ALL were provisionally included in the low-risk groups; those with TCF3-PBX1, hypodiploidy and T-cell ALL in the standard (intermediate)-risk group; and patients with BCR-ABL1, KMT2A and early T-cell precursor ALL in the high-risk group. Final risk assignment was based primarily on MRD levels measured by flow cytometry on Day 15 (≥1%) and Day 42 (<0.01% or ≥1%) of remission induction. Using genomic classification based on cytogenetics and genomic analysis (single nucleotide polymorphism array analysis and transcriptome, exome, and genome sequencing), patients were classified into 17 subtypes. The primary aim was to determine the event-free survival, overall survival and cumulative risk of relapse according to specific leukemia subtypes and MRD levels on Days 8, 15 and 42 of remission induction. This clinical trial was registered at ClinicalTrials.gov, number NCT00549848.FindingsPatients with ETV6-RUNX1, high hyperdiploidy and DUX4-rearranged B-ALL all received low- or standard-risk therapy, and had the highest 5-year event-free survival rates: 98.4% (95% CI, 95.9-100), 95.3% (91.2-99.4), and 95.0% (84.2-100), respectively. All 142 patients with Day 8 MRD<0.01%, except two with KMT2A-rearranged ALL and one with TCF3-PBX1, were in continuous complete remission. The TCF3-PBX1, PAX5alt, T-cell, early T-cell precursor, iAMP21 and hypodiploid ALL had intermediate outcome with 5-year event-free survival rates ranging from 80.0% (39.4-100) to 88.2% (71.7-100). Patients with KMT2A-rearranged, BCR-ABL1, BCR-ABL1-like and ETV6-RUNX1-like ALL had the worst outcomes, with 5-year event-free survival rates between 64.1% (43.9-84.3) and 76.2% (51.9-100), despite most patients receiving standard- or high-risk therapy. Treatment intensification based on MRD and genotype improved outcome. Relapse did not occur in any of the patients with ETV6-RUNX1, DUX4-rearranged, TCF3-PBX1, iAMP21, ZNF384-rearranged, hypodiploid, or BCR-ABL1-like B-ALL who had day 15 MRD≥1% and received standard-risk therapy. However, day 42 MRD<0.01% did not preclude relapse in patients with intermediate-risk or unfavorable subtypes including TCF3-PBX1, PAX5alt, T-cell, iAMP21, BCR-ABL1, BCR-ABL1-like, ETV6-RUNX1-like, KMT2A-rearranged, and MEF2D-rearranged ALL, despite intensified treatment in the standard- or high-risk arms. InterpretationContemporary risk-directed treatment based on genotypes and MRD can cure virtually all patients with ETV6-RUNX1, hyperdiploid>50 and DUX4-rearranged ALL. While intensified treatment improve outcome for patients with high MRD during induction, substantial proportions of patients with intermediate-risk or unfavorable subtypes would still relapse even achieving negative MRD status at the end of induction and require novel therapeutics to improve outcome.

  Study EGAS00001004739

• Genomics and Epigenomics of the Elderly Response to Pneumococcal Vaccines

  Pneumococcal Vaccine Study: This is a study designed to develop a detailed transcriptional and cellular profile of the immune response to pneumococcal vaccination with conjugated and non-conjugated polysaccharide vaccines in the senescent immune system of older adults. In this study, 39 healthy adults ages 60 and older that have never received pneumococcal vaccination, have been randomized to receive Prevnar 13 (Pfizer), a conjugated 13-valent vaccine or Pneumovax 23 (Merck), a non-conjugated 23-valent vaccine. Four (4) study visits occurred over 70 days at Day -7 (baseline), day 1, day 10 and day 60 (± 5d) post vaccination.Bulk RNA-sequencing data are available on the 4 time points for 31 of the participants and 1 replicate. ATAC-Doublet Detector Study: We generated single nucleus ATAC-seq (snATAC-seq) data from PBMCs of 2 baseline blood samples from the pneumococcal study. Generated data was then used to benchmark a novel computational method for detecting multiplets in snATAC-seq data, namely, AMULET (https://github.com/UcarLab/AMULET). Multiplets confound downstream analyses by introducing combined epigenomic profiles from 2 or more cells/nuclei. AMULET detects multiplets by using unique snATAC-seq data features that allow it to reliably use read counts to detect multiplets for their removal from data analyses.

  Study phs002361

• Genomic evolution and transcriptional changes in the evolution of prostate cancer into neuroendocrine and ductal carcinoma types

  Prostate cancer is typically of acinar adenocarcinoma type but can occasionally present as neuro-endocrine and/or ductal type carcinoma. These are associated with clinically aggressive disease and the former often arises on a background of androgen deprivation therapy, although it can al-so arise de novo. Two prostate cancer cases were sequenced by exome capture from archival tis-sue. Case 1 was de novo small cell neuroendocrine carcinoma and ductal adenocarcinoma with 3 longitudinal samples over 5 years. Case 2 was a single time point after development of treatment related neuroendocrine prostate carcinoma. Case 1 showed whole genome doubling in all sam-ples and focal amplification of AR in all samples except the first time point. Phylogenetic analysis revealed a common ancestry for the ductal and small cell carcinoma. Case 2 showed 13q loss (involving RB1) in both adenocarcinoma and small cell carcinoma regions, and 3p gain, 4p loss, 17p loss (involving TP53) in the latter. By using highly curated samples, we demonstrate for the first time that small cell neuroendocrine and ductal prostatic carcinoma can have a common an-cestry and the process of evolution over time. We highlight whole genome doubling in a patient with prostate cancer relapse, reinforcing its poor prognostic nature.

  Study EGAS00001007412

• Genomic evolution and transcriptional changes in the evolution of prostate cancer into neuroendocrine and ductal carcinoma types (RNAseq)

  Prostate cancer is typically of acinar adenocarcinoma type but can occasionally present as neuro-endocrine and/or ductal type carcinoma. These are associated with clinically aggressive disease and the former often arises on a background of androgen deprivation therapy, although it can al-so arise de novo. Two prostate cancer cases were sequenced by exome capture from archival tis-sue. Case 1 was de novo small cell neuroendocrine carcinoma and ductal adenocarcinoma with 3 longitudinal samples over 5 years. Case 2 was a single time point after development of treatment related neuroendocrine prostate carcinoma. Case 1 showed whole genome doubling in all sam-ples and focal amplification of AR in all samples except the first time point. Phylogenetic analysis revealed a common ancestry for the ductal and small cell carcinoma. Case 2 showed 13q loss (involving RB1) in both adenocarcinoma and small cell carcinoma regions, and 3p gain, 4p loss, 17p loss (involving TP53) in the latter. By using highly curated samples, we demonstrate for the first time that small cell neuroendocrine and ductal prostatic carcinoma can have a common an-cestry and the process of evolution over time. We highlight whole genome doubling in a patient with prostate cancer relapse, reinforcing its poor prognostic nature.

  Study EGAS00001007428

• WGS of all Patients Listed within this Study

  This dataset contains WGS from whole blood of patients II.2, II.3, III.1-4 and WGS from fibroblasts of patients III.2 and III.3. All WGS was performed on an Illumina NextSeq2000 to a minimum depth of 250 million read pairs (2x150nts).

  Dataset EGAD50000002362

• IL-17B uses IL-17RA and IL-17RB to induce Type-2 inflammation from human lymphocytes

  IL-17 family cytokines are critical to host defense responses at cutaneous and mucosal surfaces. Whereas IL-17A, IL-17F, and IL-17C induce overlapping inflammatory cascades to promote neutrophil-mediated immunity, IL-17E/IL-25 drives type 2 immune pathways and eosinophil activity. Genetic and pharmacological studies reveal the significant contribution these cytokines play in antimicrobial and autoimmune mechanisms. However, little is known about the related family member, IL-17B, with contrasting reports of both pro- and anti-inflammatory function in rodents. We demonstrate that in the human immune system, IL-17B is functionally similar to IL-25 and elicits type 2 cytokine secretion from innate type 2 lymphocytes, NKT, and CD4+ CRTH2+ Th2 cells. Like IL-25, this activity is dependent on the IL-17RA and IL-17RB receptor subunits. Furthermore, IL-17B can augment IL-33–driven type 2 responses. These data position IL-17B as a novel component in the regulation of human type 2 immunity.

  Study EGAS50000000579

• Transcriptome of (peripheral blood), from donor Sample A, replicate 2 Freezing replicates

  Freezing replicates

  Dataset EGAD00001010085

• Transcriptome of (peripheral blood), from donor Sample A, replicate 2 Technical replicates

  Technical replicates

  Dataset EGAD00001010083

• Single-Cell Mitochondrial Variant Profiling via TAMITO-seq

  This dataset focuses on mitochondrial variant detection using the TAMITO-seq protocol. A pre-designed mitochondrial panel (https://designer.missionbio.com/catalogpanels/Virtual-mtDNA) was spiked into the scTAMseq workflow targeting 200 CpGs and 167 genotyping loci. Data were generated from a peripheral blood sample of a healthy donor, donor X.2, multiplexed with data from another donor.

  Dataset EGAD00001015494

• Ovarian cancer sample size analysis

  The dataset contains exome sequencing fastq from 5 ovarian cancer patients, paired with tumor normal blood samples. Three tumor samples were sequenced from each patient: a biopsy sample ("-1" suffix in the file name), a local sample (multiple regions around the biopsy pooled together, with the "-2" suffix in the file name), and a global sample (multiple regions from the tumor pooled together, with a "-3" suffix in the file name).

  Dataset EGAD00001005947

• Clinical cancer panel sequencing (UCSF500) analysis of TERT promoter duplication in GBM.

  Dataset contains paired-end clinical cancer panel sequencing (UCSF500) data from 2 samples of an initial tumor and one sample of a recurrence from one GBM patient and one sample from a second GBM patient.

  Dataset EGAD00001009286

• Single-cell RNA-seq of peripheral blood mononuclear cells in classic Hodgkin lymphoma

  Abstract: Classic Hodgkin lymphoma (cHL) is a largely MHC class I-negative tumor with recurrent 9p24.1/ PD-L1/ PD-L2 copy gains and the highest reported response rates to PD-1 blockade. We utilized scRNA sequencing to characterize the peripheral immune response to PD-1 blockade and more broadly define non-CD8+ dependent mechanisms of immune evasion in cHL. Peripheral blood mononuclear cells were obtained from 20 patients with relapsed/refractory (R/R) cHL treated with PD-1 blockade (nivolumab) on the CheckMate 205 clinical trial (paired samples from cycle 1 day 1 [C1D1] and cycle 4 day 1 [C4D1]), 11 patients with newly diagnosed, previously untreated cHL and 13 healthy donors.

  Dataset EGAD00001011360

• Integrated Analysis of Multimodal Single-Cell Datasets for SARS-CoV-2 Vaccination

  The study aimed to explore immune responses during a time course of BNT162b2 mRNA vaccination. To better characterize these responses, we utilize a suite of multi-modal single-cell sequencing technologies to identify and characterize antigen-specific CD8+ T cells. We leverage an integrative analysis strategy to characterize five molecular modalities in these cells. Our dataset enables the discovery of new subpopulations, molecular signatures, and developmental regulators of these cells. Moreover, we identify these cells in SARS-CoV-2 infected patients and demonstrate their positive predictive value for subsequent clinical recovery. The sequence data of CITE-seq, ASAP-seq and ECCITE-seq experiments are deposited in dbGaP. Peripheral blood mononuclear cell (PBMC) samples for CITE-seq and ASAP-seq were collected from six healthy donors at four time points: immediately before (Day 0) vaccination, after primary vaccination (Day 2, Day 10), and seven days after boost vaccination (Day 28). PBMC samples for ECCITE-seq were collected from eight healthy donors on Day 28.

  Study phs003322

• Recurrent adeno-associated virus 2-related insertional mutagenesis in human hepatocellular carcinomas

  Hepatocellular carcinomas (HCC) are liver tumors related to various etiologies including alcohol intake, hepatitis B (HBV) or C (HCV) virus infection. Additional risk factors remain to be identified, particularly in patients who develop HCC without cirrhosis. We identified clonal integration of adeno-associated virus type 2 (AAV2) in 11 out of 193 HCC. These AAV2 integrations occurred within known cancer driver genes, namely, CCNA2 (Cyclin A2, 4 cases), TERT (Telomerase Reverse-Transcriptase, 1 case), CCNE1 (Cyclin E1, 3 cases), TNFSF10 (Tumor Necrosis Factor member 10, 2 cases) or KMT2B (Lysine (K)-Specific Methyltransferase 2B, 1 case) leading to over-expression of the target genes. Tumors with viral integration mainly developed in non-cirrhotic liver (9 out of 11 cases) and without known risk factors (6 out of 11) suggesting a pathogenic role of AAV2 in these patients. In conclusion, AAV2 is a DNA virus associated with oncogenic insertional mutagenesis in human HCC.

  Study EGAS00001001284

• The Ashkenazi Genome Consortium: Phase I

  Whole genome, high coverage, sequencing of 128 Ashkenazi Jewish controls

  Dataset EGAD00001000781

• T2D-GENES Consortium: San Antonio Mexican American Family Studies (SAMAFS)

  The Type 2 Diabetes (T2D) Genetic Exploration by Next-generation sequencing in Ethnic Samples (T2D-GENES) Consortium is a collaborative international effort to identify genes influencing susceptibility to type 2 diabetes in multiple ethnic groups using next generation sequencing. To fulfill this objective, T2D-GENES Consortium undertook two large sequencing studies, called T2D-GENES Projects 1 and 2. Project 1 has carried out whole exome sequencing of 12,940 individuals, 6,504 with T2D and 6,436 non-diabetic controls, equally divided among five continental ancestry groups: Europeans, East Asians, South Asians, Hispanic Americans, and African Americans. The goal of Project 1 is to identify all genetic variants in the complete coding regions of the genomes (i.e., whole exome) by sequencing, including rare variants. Project 2 (i.e., SAMAFS substudy 2) is a pedigree-based study designed to identify low frequency or rare variants influencing susceptibility to T2D, using whole genome sequence information from approximately 600 individuals in 20 Mexican American T2D-enriched pedigrees from San Antonio, Texas, augmented with family-based imputation into approximately 440 additional family members. The major objectives of Project 2 are to identify low frequency or rare variants in and around known common variant signals for T2D, as well as to find novel low frequency or rare variants influencing susceptibility to T2D. Both T2D-GENES Projects 1 and 2 involve the San Antonio Mexican American Family Studies (SAMAFS), which are composed of four San Antonio, Texas-based family studies: the San Antonio Family Heart Study (SAFHS), San Antonio Family Diabetes/Gallbladder Study (SAFDGS), Veterans Administration Genetic Epidemiology Study (VAGES), and Family Investigation of Nephropathy and Diabetes - San Antonio (FIND-SA) Component and its extension called the Extended FIND [E-FIND]. The SAFHS and SAFDGS began in 1991 and have followed participants with extensive clinical phenotyping related to T2D for over 20 years. The VAGES was initiated in 1994 and a large battery of T2D-related phenotypic data has been obtained from its participants. The FIND-SA began in 2000, a part of the multicenter FIND study which was designed to identify genetic determinants of diabetic kidney disease; data from its participants related to T2D were used for this project. Non-overlapping subsets of SAMAFS participants are part of the T2D-GENES Projects 1 and 2, henceforth referred to as SAMAFS substudies 1 and 2, respectively. The SAMAFS substudies 1 and 2 are part of one of the five awards funded by NIDDK under a cooperative agreement award mechanism, which is governed by the Steering Committee of the T2D-GENES Consortium. Since Project 1 relies on population based subsets of cases and controls, 491 unrelated participants are drawn from the four SAMAFS as part of the T2D-GENES Project 1 Mexican American sample (i.e., SAMAFS substudy 1). The whole exome sequencing was performed at the Broad Institute. For Project 2, 1048 individuals are drawn from two SAMAFS (SAFHS and SAFDGS), representing 20 large families for substudy 2. The substudy 2 strategy is to sequence approximately 600 individuals at an average of 50x coverage across the entire genome, then impute genome wide genotypes for about 440 additional family members. The 600 sequenced individuals are specifically chosen for their value in imputing sequence information into other family members. By studying large pedigrees, we expect to find multiple individuals carrying each genetic variant, even if this variant is very rare in the population at large. Thus, a pedigree-based approach provides an excellent opportunity for identifying rare novel variants influencing risk of T2D and quantitative variation in T2D-related phenotypes. The whole genome sequencing has been done commercially by Complete Genomics, Inc. (CGI). The available sample of 1,048 includes 5 sequenced individuals who do not belong to any of the 20 large pedigrees. The final family data of 1,043 individuals includes whole genome sequence data for 607 individuals. After quality control, 590 sequenced individuals provide data for family based imputation using Merlin linkage analysis software into approximately 440 additional family members for whom chip based genotypes are available to indicate which parental haplotype is transmitted. The complete SAMAFS data including phenotype, genotype, sequence, other T2D-related trait data utilized for Projects 1 and 2 are available. These data can readily be viewed by clicking on the substudy title shown below or in the box: "Substudies", located on the right hand side of this parent or top study page phs000847.v1.p1, titled T2D-GENES Consortium: San Antonio Mexican American Family Studies (SAMAFS). phs000849 T2D-GENES Project 1: San Antonio Mexican American Family Studies (SAMAFS), Substudy 1: Whole Exome Sequencing phs000462 T2D-GENES Project 2: San Antonio Mexican American Family Studies (SAMAFS), Substudy 2: Whole Genome Sequencing in Pedigrees

  Study phs000847

• Genome-wide identification of distinct miRNA-mRNA target regulation pairs in Non-Hodgkin lymphomas: a report from the ICGC MMML-Seq consortium

  We obtained miRNA profiles by miRnome sequencing from ICGC MMML-Seq patients diagnosed with Burkitt lymphoma, diffuse large B-cell lymphoma and follicular lymphoma and provide evidence of subtype-specific miRNA expression differences. We describe differentially expressed, mutated, edited and not previously annotated miRNAs. Addditionally, by performing argonaute-2 photoactivatable ribonucleoside-enhanced cross-linking and immunoprecipitation (PAR-CLIP) experiments, we obtained a set of biochemically-validated miRNA binding sites and identified miRNA-mRNA interaction pairs with a negative correlation in patient RNASeq data.

  Study EGAS00001001394

• Cancer sequencing for somatic variant calling

  This dataset includes WES and RNAseq for 11 patients with metastatic melanoma, lung, kidney, and stomach cancers, enrolled in phase I clinical trials of TIL ACT (NCT03475134 & NCT04643574). WES was performed on matched cancer and healthy tissues, whereas RNAseq was performed on cancer tissues, using Illumina HiSeq 2500/4000 and Illumina NextSeq 550 systems.

  Study EGAS00001007101

• Single cell RNA sequencing data in "Three-dimensional human alveolar stem cell culture models reveal infection response to SARS-CoV-2"

  This dataset includes a total of 5 single cell RNA sequencing (scRNAseq) data of SARS-CoV-2 infected human alveolar stem cell culture models. Two scRNAseq data were obtained from SARS-CoV-2 infection with MOI of 1.0 (1 for control and 1 for infected case) and the other three were obtained from SARS-CoV-2 infection with MOI of 0.1 in the study entitled "Three-dimensional human alveolar stem cell culture models reveal infection response to SARS-CoV-2". The 10x Chromium Single Cell 3' Reagent kits were used to generate libraries.

  Dataset EGAD00001006242

• Targeted sequencing of patients affected by familial or sporadic Alzheimer's disease

  The study aimed at identifying variants related to familial cases of Alzheimer's disease by comparing the mutational state of approximately 4000 genes associated to many known diseases ("clinical exome") in members of a family (n=7) of with members with dementia (n=2) and unaffected members (n=5)

  Study EGAS00001003856

• Oxford Nanopore RNA sequencing for HLA typing

  A targeted RNA-based method for typing of 12 classical HLA genes using Oxford Nanopore sequencing. In the method, were enriched HLA genes from cDNA of 50 individuals using gene-specific reverse primers. The library molecules were then barcoded, pooled into 2 separate gene pools, and sequenced on MinION R9.4 SpotON flow cells.

  Study EGAS00001004918

• A genome-wide CRISPR screen identifies CALCOCO2 as a regulator of beta cell function influencing type 2 diabetes risk

  Identification of the genes and processes mediating genetic association signals for complex diseases represents a major challenge. As many of the genetic signals for type 2 diabetes (T2D) exert their effects through pancreatic islet-cell dysfunction, we performed a genome-wide pooled CRISPR loss-of-function screen in a human pancreatic beta cell line. We assessed the regulation of insulin content as a disease-relevant readout of beta cell function and identified 580 genes influencing this phenotype. Integration with genetic and genomic data provided experimental support for 20 candidate T2D effector transcripts including the autophagy receptor CALCOCO2. Loss of CALCOCO2 was associated with distorted mitochondria, less proinsulin-containing immature granules and accumulation of autophagosomes upon inhibition of late-stage autophagy. Carriers of T2D-associated variants at the CALCOCO2 locus further displayed altered insulin secretion. Our study highlights how cellular screens can augment existing multi-omic efforts to support mechanistic understanding and provide evidence for causal effects at genome-wide association studies loci.

  Dataset EGAD50000000518

• Genetic determinants of glycated hemoglobin levels in the Greenlandic Inuit population

  We recently showed that a common genetic variant leads to a remarkably increased risk of type 2 diabetes (T2D) in the small and historically isolated Greenlandic population. Motivated by this, we aimed at investigating the genetic determinants for glycated hemoglobin (HbA1C). We found no novel associations but saw that for 10 out of 15 known HbA1C loci that the effects in Greenlandic Inuit were similar to previously reported. One locus, ANK1, showed a significant ancestral population specific effect. Our results shed light on the genetics effects across ethnicites.

  Study EGAS00001002641

• Germline Genome Sequencing from Patients with Early-Onset Merkel Cell Carcinoma

  Merkel cell carcinoma (MCC) is a rare neuroendocrine skin cancer associated with advanced age. Approximately 5% of cases are early-onset MCC, occurring in individuals younger than 50 years. This study used genome sequencing to identify germline risk factors among patients with early-onset MCC. The available data in the database of Genotypes and Phenotypes (dbGaP) includes genome sequencing of peripheral blood mononuclear cell (PBMC) DNA from 37 patients with early-onset MCC (age ATM = 2, BRCA1 = 2, BRCA2 = 1, TP53 = 1, and MAGT1 = 1).

  Study phs003485

• RNA-Seq of human longitudinal whole blood samples from PCR-positive and PCR-negative recent household contacts of COVID-19 index cases.

  Little is known about the transcriptomic profile of individuals who are exposed to SARS-CoV-2 yet resist becoming PCR positive. To investigate this, longitudinal whole-blood samples were taken (0, 7, 14, and 28 days after enrolment) from PCR positive and PCR negative SARS-CoV-2-naïve household contacts who were recently exposed to a COVID-19 index. Samples were also taken from pre- and post-pandemic unexposed controls. Total RNA was extracted from PAXgene tubes before undergoing poly(A) selection followed by globin and rRNA depletion. DNA libraries were constructed using the NEBNext® Ultra™ II Directional RNA Library Prep Kit for Illumina. All samples were then sequenced across 2 flowcells of an Illumina HiSeq 4000.

  Dataset EGAD50000000684

• Whole Exome Sequencing for Familial Intracranial Aneurysm (FIA I-II) Study

  The goal of this study is to identify the genes underlying the risk of intracranial aneurysm (IA). The FIA Study initially recruited families appropriate for linkage analysis. Therefore, the recruitment focus was not only on probands with a family history of IA but also required that biological samples be obtained for at least two affected family members. Family members underwent detailed interviews for medical, social and family history, and provided blood samples for DNA extraction. Over 400 multiplex IA families were recruited and enrolled. The whole exome sequencing project aims to identify novel and rare (in the general population) genetic variants that are enriched in seven extended multiplex families with a strong familial aggregation of intracranial aneurysms.

  Study phs000636

• eMERGE Network Phase III: HRC SNV and 1000 Genomes SV Imputed Array Data of 105,000 Participants

  The Electronic Medical Records and Genomics (eMERGE) Network is a National Institutes of Health (NIH)-organized and funded consortium of U.S. medical research institutions. The primary goal of the eMERGE Network is to develop, disseminate, and apply approaches to research that combine biorepositories with electronic medical record (EMR) systems for genomic discovery and genomic medicine implementation research. eMERGE was announced in June 2007 and began its third phase in September 2015. eMERGE Phase III (June 2015 - June 2020) consists of 10 study sites, two central sequencing and genotyping facilities, and a coordinating center. Included in this study are: Human Reference Consortium (HRC) single nucleotide variants and 1000 Genomes structural variants imputed array data of 105,108 eMERGE participants from nine Phase III study sites and three Phase II study site collaborators. Corresponding demographics, body mass index measurements. Case/control status for the following phenotypes: Abdominal aortic aneurysm; Ace-Inhibitor/Cough; Attention Deficit Hyperactivity Disorder; Age-related macular disease; Appendicitis; Asthma; Atopic Dermatitis; Autism; Benign Prostatic Hyperplasia; Carotid artery disease as a Quantitative Measure; caMRSA; Cataract; Clostridium difficile colitis; Extreme Obesity; Chronic Kidney Disease; Chronic Kidney Disease and Type 2 Diabetes; Chronic Kidney Disease, Type 2 Diabetes and Hypertension; Colon Polyps; Cardiorespiratory Fitness; Dementia; Diverticulosis; Diabetic retinopathy; Gastroesophageal Reflux Disease; Glaucoma; Height; Heart failure; Hypothyroidism; Lipids; Ocular hypertension; Peripheral Arterial Disease; QRS duration; Red blood cell indices; Remission of Diabetes after ROUX-EN-Y gastric bypass surgery; Resistant hypertension; MACE while on Statins; Type 2 Diabetes; Venous Thromboembolism; White blood cell indices; and Zoster virus infection. Study sites and participants include: Boston Children's Hospital: The Gene Partnership (TGP) is a prospective longitudinal registry at Boston Children's Hospital (BCH) to study the genetic and environmental contributions to childhood health and disease, collect genetic information on a large number of children who have been phenotyped, and implement the Informed Cohort and the Informed Cohort Oversight Board (ICOB). The term "The Gene Partnership" reflects a partnership between researchers and participants. Children seen at BCH are offered enrollment, as are their parents and siblings. DNA is collected on all enrollees. BCH has a comprehensive EMR system, and virtually all inpatient and outpatient data are captured electronically. Clinical data in the BCH EMR is loaded in the i2b2 data warehouse which is available to investigators. Cases, phenotypes, and covariates are ascertained using the i2b2 database. Participants at BCH in TGP have consented to receive any research result and/or incidental finding that arises from studies using TGP that is approved by the Informed Cohort Oversight Board (ICOB) and is in accordance with the participants'preferences;results are returned through the Personally Controlled Health Record (PCHR). BCH and Cincinnati Children's Hospital Medical Center (CCHMC) have partnered as the Pediatric Alliance for Genomic and Electronic Medical Record (EMR) Research (PAGER) site for the eMERGE Phase II network for pediatric institutions, and the cohort for eMERGE at BCH is TGP. Children's Hospital of Pennsylvania (CHOP): The Center for Applied Genomics (CAG) at the Children's Hospital of Philadelphia (CHOP) is a high-throughput, highly automated genotyping and sequencing facility equipped with state-of-the-art genotyping and sequencing platforms. Children who are treated at the Children's Hospital Healthcare Network and their parents may be eligible to take part in a major initiative to collect more than 100,000 blood samples, covering a wide range of pediatric diseases. A large majority of participants consenting to prospective genomic analyses also consent to analysis of their de-identified electronic health records (EHRs). EHRs are longitudinal, with a mean duration of 6.5 years. Cincinnati Children's Hospital Medical Center/Boston's Children's Hospital (CCHMC/BCH): Cincinnati Children's Hospital Medical Center (CCHMC) is a pediatric institution dedicated to improving health and welfare of children and to the discovery and practical application of new genomic information to the ordinary care of children. CCHMC brings an extraordinary faculty to eMERGE III who are committed to gain a better understanding of the genesis of disease and to elucidate the mechanisms of diseases that afflict children, specifically pediatric disease phenotypes that will leverage the available eMERGE adult genomic data and electronic medical records (EMRs) to discover meaningful use results. Generation of EMR phenotype algorithms, informed by natural language processing, using heuristic and machine learning methods is ongoing. CCHMC has developed tools to evaluate adolescent return of results preferences, examined the ethical and legal obligations and potential to reanalyze results, and developed clinical decision support for phenotyping, test ordering, and returning sequencing results. The success of these eMERGE III studies is enhanced by the ongoing institutional investment made in the CCHMC Biobank, the comprehensive EMR (EPIC), the i2b2 de-identified medical record data warehouse, and hundreds of faculty and senior staff who make genomics or informatics an active focus of their research. Columbia University: Columbia University Medical Center/New York Presbyterian (CUMC/NYP) Hospital system is one of the nation's largest and most comprehensive hospital systems with over 2 million inpatient and outpatient yearly visits that serves a racially and ethnically diverse urban patient population. The Columbia University GENomic Integration with EHR (GENIE) research study contributed and shared phenotype and genotype data for individuals who were recruited as part of a diverse array of initiatives within the hospital, including Northern Manhattan Study (NOMAS), Pediatric Cardiac Genomic Consortium (PCGC), Caribbean Hispanics with Familial and Sporadic Late Onset Alzheimer's disease (AD), Alzheimer's Disease Sequencing Project (ADSP), and Genetics of Chronic Kidney Disease study. Some of these individuals had kidney or neurological problems, some were healthy adult volunteers with self-reported health status information from the medically underserved Northern Manhattan community, and others were pediatric patients with cardiac conditions. For the kidney disease cohort, patients with the diagnosis of Chronic Kidney Disease (CKD) and healthy controls were recruited to the Columbia University CKD biobank. For the NOMAS cohort, eligible participants were stroke-free, were 40 years old, and resided for at least 3 months in a Northern Manhattan household with a telephone. The PCGC study recruited parent-offspring trios with pediatric probands diagnosed with congenital heart defects (CHD). For the Caribbean Hispanics with Alzheimer's disease project, individuals from families affected by AD and with sporadic AD were recruited, along with unrelated controls. Samples for the ADSP study have been selected from well-characterized cohorts of individuals with AD diagnosis. Geisinger Health System: A research cohort of adult Geisinger Clinic patients was enrolled from community-based primary care clinics of the Geisinger Health System. Patients were eligible for enrollment if they were a primary care patient of a Geisinger Clinic physician and were scheduled for a non-emergent clinic visit. All participants provided written informed consent and HIPAA authorization. Consenting patients agreed to provide blood samples for broad biomedical research use, and permission to access data in their Geisinger electronic medical record for research. The enrollment rate was 90% of patients approached. The demographics of the cohort approximate those of the Geisinger Clinic outpatient population. Research blood samples were collected during an outpatient clinical phlebotomy encounter. Research blood samples are coded and stored in a central biorepository. Samples are linkable to clinical data in a de-identified manner for research via an IRB-approved data broker process. For genomic analysis, DNA is extracted from EDTA-anticoagulated whole blood. Partners Health Care (Harvard): The Partners HealthCare Biobank is a large research program designed to help researchers understand how people's health is affected by their genes, lifestyle, and environment. This large research data and sample repository provides access to high-quality, consented blood samples to help foster research, advance our understanding of the causes of common diseases, and advance the practice of medicine. For the Partners research community (Massachusetts General Hospital and Brigham and Women's Hospital), the Biobank provides: Banked samples (plasma, serum, and DNA) collected from consented patients Blood samples that were discarded after clinical testing in the Crimson Cores maintained in the Brigham and Women's Hospital and Massachusetts General Hospital Pathology Departments Sample handling and preparation services Link to the biobank data to the Partners Research Patient Data Registry (RPDR) a research instance of our electronic clinical chart Data access through our research portal. To date, over 60,000 Partners patients have given their consent to enroll, give a blood sample, receive research results and agreed to be re-contacted for additional research studies. The Biobank has enabled Partners investigators to compete for nationally recognized grants in personalized medicine such as a clinical electronic Medical Records and Genomics network (eMERGE) site and the national All of US program. The Biobank currently supports over 120 Partners investigators and over 100 million dollars in NIH research. Kaiser Permanente Washington with the University of Washington and the Fred Hutchinson Cancer Research Center: KPWA participants were enrolled in the eMERGE Network through the Northwest Institute of Genetic Medicine (NWIGM) biorepository, and provided the appropriate consent to receive clinically relevant genetic results (N~8,073.) NWIGM is based at the University of Washington and co-managed by the University of Washington and KPWA. The purpose of the NWIGM biorepository is to build infrastructure and resources to carry out a broad range of future genetic research. KPWA members enrolled in the biorepository are asked to provide informed consent to providing a DNA sample for storage in the NWIGM biorepository. The consent is purposefully broad to serve the dual purpose of reducing the burden on researchers who wish to use this biorepository and the IRB committees who will be responsible for reviewing these requests in the future. Participants were eligible if aged 50 - 65 years old at the time of their enrollment into the NWIGM repository, living, enrolled in KPWA's integrated group practice, and had completed an online Health Risk Appraisal. The selection algorithm was based on several data sources from the EHR at KPWA. 1) Demographics - participants with self-reported race as Asian ancestry were prioritized and selected to enrich for non-European ancestry. The KPWA eMERGE cohort includes n=1,245 members of Asian ancestry. 2) Participants were also selected for a history of colorectal cancer (n=1,002), in order to allow us to enrich germline pathogenic variants. Essentia Institute of Rural Health, Marshfield Clinic, Pennsylvania State University (Marshfield): The Marshfield Clinic Personalized Medicine Research Project is a population-based biobank in central Wisconsin with more than 20,000 adult subjects who provided written, informed consent to access their medical records and provided a blood sample from which DNA was extracted and plasma and serum stored. In addition to an average of 30 years of medical history data, a questionnaire about environmental exposures, including a detailed food frequency questionnaire, is available to facilitate gene/environment studies. Mayo Clinic: The Mayo Vascular Disease Biorepository is a disease-specific biobank for vascular diseases including peripheral arterial disease (PAD). PAD patients were identified from individuals referred to the non-invasive vascular laboratory for lower extremity arterial evaluation. Since 1997, laboratory findings have been recorded into an electronic database employing an in-house software package for data archiving and retrieval;this data becomes part of the Mayo EMR. Patients referred to the center with suspected PAD undergo a comprehensive non-invasive evaluation including the ankle-brachial index (ABI) - the ratio of blood pressure measured in the upper arms divided by blood pressure measured at the ankles. Controls subjects are identified from patients referred to the Cardiovascular Health Clinic for stress ECG. The prevalence of PAD in patients with normal exercise capacity who do not have inducible ischemia on the stress ECG , was <1%. Data regarding risk factors for atherosclerosis such as diabetes, dyslipidemia, hypertension, and smoking are ascertained from the EMR. Case control study of venous thromboembolism (PI John Heit) Controls from a case control study of pancreatic cancer (PI Gloria Petersen) Mayo Clinic Biobank. Icahn School of Medicine at Mount Sinai School (Mt. Sinai): The Institute for Personalized Medicine (IPM) Biobank Project is a consented, EMR-linked medical care setting biorepository of the Mount Sinai Medical Center (MSMC) drawing from a population of over 70,000 inpatients and 800,000 outpatient visits annually. MSMC serves diverse local communities of upper Manhattan, including Central Harlem (86% African American), East Harlem (88% Hispanic Latino), and Upper East Side (88% Caucasian/white) with broad health disparities. IPM Biobank populations include 28% African American (AA), 38% Hispanic Latino (HL) predominantly of Caribbean origin, 23% Caucasian/White (CW). IPM Biobank disease burden is reflective of health disparities with broad public health impact: average body mass index of 28.9 and frequencies of hypertension (55%), hypercholesterolemia (32%), diabetes (30%), coronary artery disease (25%), chronic kidney disease (23%), among others. Biobank operations are fully integrated in clinical care processes, including direct recruitment from clinical sites, waiting areas and phlebotomy stations by dedicated Biobank recruiters independent of clinical care providers, prior to or following a clinician standard of care visit. Recruitment currently occurs at a broad spectrum of over 30 clinical care sites. Northwestern University: The NUgene Project is a repository with longitudinal medical information from participating patients at affiliated hospitals and outpatient clinics from the Northwestern University Medical Center. Participants'DNA samples are coupled with data from a self-reported questionnaire and continuously updated data from our Electronic Medical Record (EMR) representing actual clinical care events. Northwestern has a state-of-the art, comprehensive inpatient and outpatient EMR system of over 2 million patients. NUgene has broad access to participant data for all outpatient visits as well as inpatient data via a consolidated data warehouse. NUgene participants consent to distribution and use of their coded DNA samples and data for a broad range of genetic research by third-party investigators. Vanderbilt University Medical Center: BioVU, Vanderbilt's DNA databank, was designed as an enabling resource for exploration of the relationships among genetic variation, disease susceptibility, and variable drug responses. BioVU acquires DNA from discarded blood samples collected from routine patient care. The biobank is linked to de-identified clinical data extracted from Vanderbilt's EMR, which forms the basis for phenotype definitions used in genotype-phenotype correlations. BioVU is currently the largest single site DNA collection world-wide, at >235,000 samples as of spring 2017.

  Study phs001584

• Control of Focal Adhesion Kinase Activation by RUNX1-regulated miRNAs in high-risk AML

  We recently described a 16-gene expression signature for improved risk stratification of acute myeloid leukemia (AML) patients called the AML Prognostic Score (APS). A subset of APS high-risk AML patients showed increased levels of focal adhesion kinase (FAK), encoded by the Protein Tyrosine Kinase 2 (PTK2) gene, which was correlated with RUNX1 mutations. RUNX1 mutant cells are more sensitive to PTK2 inhibitors. As we were not able to detect RUNX1 binding sites in the PTK2 promoter, we hypothesized that RUNX1 might regulate micro(mi)RNAs that repress PTK2, such that loss-of-function RUNX1 mutations would result in reduced miRNA expression and derepression of PTK2. Examination of paired RNA-seq and miRNA-seq data from 301 AML cases revealed two miRNAs that positively correlated with RUNX1 expression, contained RUNX1 binding sites in their promoters and were predicted to target PTK2. We show that the hsa-let7a-2-3p and hsa-miR-135a-5p promoters are regulated by RUNX1, and that PTK2 is a direct target of both miRNAs. Even in the absence of RUNX1 mutations, hsa-let7a-2-3p and hsa-miR-135a-5p regulate PTK2 expression, and reduced expression of these two miRNAs sensitizes AML cells to PTK2 inhibition. These data explain how RUNX1 regulates PTK2, and identify potential miRNA biomarkers for targeting AML with PTK2 inhibitors.

  Study EGAS00001006491

• Pharmacogenomic Evaluation of Antihypertensive Responses (PEAR and PEAR-2)

  The primary aim of the Pharmacogenomic Evaluation of Antihypertensive Responses grant (funded by NIH Pharmacogenomic Research Network grant U01 GM074492) was to identify genetic determinants of blood pressure response and adverse events after antihypertensive treatments. Two different clinical trials with genomic information available were included: PEAR-1 and PEAR-2 studies. The PEAR-1 study (clinicaltrials.gov identifier NCT00246519) was a randomized controlled clinical trial evaluating genetic determinants of BP responses and adverse metabolic responses to atenolol and hydrochlorothiazide (HCTZ) monotherapy and in combination (PMID: 19249413). Briefly, PEAR-1 recruited 768 hypertension individuals with uncomplicated hypertension who were randomized to either monotherapy of atenolol 50 mg daily or HCTZ 12.5 mg daily for 3 weeks, followed by dose titration to 100 mg and 25 mg daily, then the combination therapy. BP and metabolic responses to monotherapy and combination therapy were assessed after an average of 9 weeks of antihypertensive treatment. BP was measured using three different methods: home, office and ambulatory. For the BP analysis, a composite weighted average of the office, home, ambulatory daytime and nighttime BP responses was calculated based on the row sums of the inverse of the inter-method covariance matrices. Genomic DNA from PEAR-1 participants was genotyped using the Illumina Human Omni1MQuad BeadChip (Illumina, San Diego, CA, USA). The PEAR-2 study was a multicenter sequential monotherapy clinical trial (clinicaltrials.gov identifier NCT01203852) evaluating genetic determinants of BP response to metoprolol monotherapy and chlorthalidone monotherapy. After a washout period (if necessary), eligible hypertensive patients with uncomplicated hypertension received metoprolol tartrate 50 mg twice daily for 3 weeks and the dose was increased to 100 mg twice daily for an additional six weeks if an inadequate response was observed (>120/70 mm Hg and heart rate >55 beats/min). After second washout period, patients received chlorthalidone monotherapy. Home and office BP measurements were collected in PEAR-2 study. We have previously demonstrated that home BP is the more informative single BP measurement compared to the office BP measurement. Therefore, home BP is the phenotype used for the genome-wide association analysis for PEAR-2. PEAR-2 samples were genotyped using the Illumina Human Omni2.5S Beadchip (Illumina, San Diego, CA, USA).

  Study phs000649

• Clonal cultures of T memory cells

  Sequence data (bam files) of two RRBS samples for paper "A comprehensive analysis of 195 DNA methylomes reveals shared and cell specific features of partially methylated domains". Short Description: CD4+ T memory cells (CD3+ CD4+ CD45RA- CD45RO+ CD25-) from donors were sorted by flow-cytometry either as a bulk culture ('ex vivo' sample) or in a single-cell format into 96 well-plates ('clone' sample) in the presence of a TCR stimulus.

  Dataset EGAD00001004303

• RNA Editing in breast cancer

  High-throughput sequencing screens suggest that RNA editing, which consists in the substitution of adenosine with inosine by the RNA-specific adenosine deaminase (ADAR) enzyme, occurs at several thousand positions across the human genome. Recent evidences have shown that RNA-editing could promote proliferation and carcinogenesis; however, the general principles of ADAR activity on the transcriptome and how ADAR is controlled in cancers remain to be established. The main aim of this project was to investigate the phenomenon of RNA editing in breast and other cancers. The frequency of A-to-I editing was evaluated in 58 breast cancers equally distributed among the different molecular subtypes and 10 normal breast tissues. The analysis was focused on defining: the relationship between the global amount of editing and ADAR expression; the ability to predict the level of editability of specific sites; the distribution of editing in normal and tumour samples and among different breast cancer subtypes; and the clinical, pathological and genomic factors affecting editing.

  Study EGAS00001000495

• MutWP5__CRUK_Mutographs_of_Cancer__Breast__Cancer_Mastectomy__Exome_

  Sequencing of LCM-derived microbiopsies from 30 women who underwent mastectomies due to a breast cancer diagnosis. Goal to assess the mutational burden, spectrum, and clonal dynamics within the tissue. Exome data will be used as a driver and clonality screen, highly clonal or driver-containing samples will subsequently be sent for whole-genome sequencing. Results from this portion of the study will be compared to women who had cosmetic breast reduction surgeries and those with germline BRCA 1/2 mutations.

  Study EGAS00001003319

• RRBS data of 48 individuals of the Dutch Hunger Winter Families Study

  The dataset entails 48 RRBS libraries of 24 siblings. 24 individuals are conceived during the Dutch Famine, a severe 6 month famine at the end of World War 2. A same sex sibling was added as a control, allowing partial matching for (early) familial environment and genetics.

  Dataset EGAD00001000733

• Deep multi-region WGS of lung cancer tumours

  Deep WGS (germline and 2-5 tumour regions) was performed on 20 patients: 13 lung adenocarcinoma, 5 squamous cell carcinoma, 2 small-cell lung cancers. A total of 68 BAM files are provided, where tumours were sequenced to 60x or 150x depth.

  Dataset EGAD00001005287

• Mixture of 2

  Mixture of 2 unrelated individuals sequenced by 10x as a scRNA-seq. The dataset was then processed by Cell Ranger and deconvoluted to yield each individuals genetic profile. The clustering of SNPs is submitted as the processed file. The Sequencing fastqs are submitted as unprocessed files.

  Dataset EGAD00001008726

• MB_450k_methylation

  450k methylation arrays of primary and relapse tumor of a single case of sonic hedgehog medulloblastoma with Li-Fraumeni syndrome

  Dataset EGAD00010002370

• National Heart, Lung, and Blood Institute (NHLBI) Heart Healthy Lenoir (HHL) Genomics Study

  The HHL genomics study uses a systems approach to develop models integrating clinical and genomic data. Previously we developed and tested an approach known as the SAMARA (Supporting A Multidisciplinary Approach to Research in Atherosclerosis) project that applied recent advances in biomedical and computational sciences at The University of North Carolina at Chapel Hill to develop a deeper understanding of human cardiovascular disease (CVD). The Heart-Healthy Lenoir Project expands these studies into the community, using this methodology to: 1) determine the prevalence of genomic risk signatures in high-risk community populations using genome-wide Single Nucleotide Polymorphism (SNP) analysis; 2) develop novel genomic models incorporating high-risk features in this population; and 3) determine whether genomic signatures can be used to predict responsiveness to interventions that underlie CVD disparities. DNA was obtained from participants enrolled in two of the HHL clinical trials, 1) Improving Care for Patients With High Blood Pressure (NCT01425515) or 2) Heart-Healthy Lenoir Lifestyle Study (NCT01433484). Participants could enroll in both trials concurrently.

  Study phs001471