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• Longitudinal single-cell transcriptomic study in patient-derived xenografts of pediatric T-ALL

  In this study, we conducted single cell full length total RNA sequencing (VASA-seq) on 13 matched pediatric T-ALL PDX samples at initial diagnosis and relapse, along with 5 non-relapsing PDX samples collected at initial diagnosis. We identified a subpopulation of T-ALL cells with stem-like cell features that expands substantially at relapse indicating resistance to first-line therapy. Chemotherapy resistance was further validated through functional testing: Two samples were subjected to in-vitro drug testing, treated with Cytarabine for three days, followed by single-cell transcriptomic analysis using 10x Genomics. Additionally, in-vivo drug testing was conducted on one sample, involving re-engraftment into mice and treatment with a combination of Vincristine, Doxorubicin, and Dexamethasone. Single-cell transcriptomic analysis using 10x Genomics was performed after 0, 15 and 30 days of treatment.

  Dataset EGAD50000000831

• EGAD00010000744

  Subset 2 of osteoarthritis cases genotyped on Illumina 610k from the arcOGEN Consortium (http://www.arcogen.org.uk/) with consent for osteoarthritis studies only.

  Dataset EGAD00010000744

• SNP arrays for chemotherapy response project

  In this study, a total of 300 patients with MIBC receiving chemotherapy were included; 62 received NAC before cystectomy and 245 received first-line chemotherapy upon detection of locally-advanced (T4b) or metastatic disease. Treatment response, defined as pathological downstaging (< pTa,CIS,N0) after NAC or complete or partial response after first-line treatment (RECIST criteria). Illumina SNP arrays (760k markers) were performed using DNA from 49 tumors and associated germline DNA (49x median coverage). Data provided here consist of 98 files.

  Study EGAS00001004519

• Targeted panel data for newly diagnosed myeloma patients.

  Genomic abnormalities in MM are common and can affect a patients outcome. Here we have performed targeted sequencing on xx patient tumor samples and matched control DNA. The targeted panel consists of ~160 genes and copy number regions, as well as key regions of chromosomal translocation including IGH, IGK, IGL and MYC. Using mutation, copy number, and translocation information we have been able to identify abnormalities that affect prognosis including bi-allelic inactivation of TP53 and rearrangements involving MYC.

  Study EGAS00001002859

• SNP genotyping in B cell receptor gene regions

  This dataset contains genotype information (vcf files) for genotyped SNPs within or near the BCR loci of 187 individuals (97 controls and 88 subjects with coeliac disease). SNPs were genotyped using an Axiom Human Genotyping SARS-CoV-2 Research Array (Thermo Fisher) and the data was processed with the Axiom Analysis Suite using the “Best Practices Workflow” pipeline. The genotyped SNPs include 1241 SNPs within/near IGH on Chr14, 157 SNPs within/near IGK on Chr2, and 608 SNPs within/near IGL on Chr22 passing quality control. The dataset also contains a metadata file (csv) describing sample phenotypes and providing links to genotype sample names.

  Dataset EGAD50000002729

• BAM files of total RNA-Seq data of POPS control samples (GRCh37)

  Placental biopsies (n = 64 female placentas, n = 67 male placentas) were selected from healthy pregnancies from the POPs cohort. A quality control process was also applied for the RNA-Seq datasets: reads were trimmed with Trim Galore!, which uses cutadapt internally and were mapped to the same version of human genome reference (hg19). TopHat2, a splice-aware mapper built on top of Bowtie2 short-read aligner, was used in the mapping process in which so-called two-pass (or two-scan) alignment protocol was applied to rescue unmapped reads from the initial mapping step. In the second mapping, previously unmapped reads were re-aligned to the exon-intron junctions detected in the first-mapping by TopHat2 and were combined across all 131 placenta samples. The initial and second mapped reads were merged by samtools

  Dataset EGAD00001003462

• ICGC PCAWG Dataset: PACA-CA_PCAWG_WGS_BWA

  ICGC PCAWG Dataset for WGS BAM aligned using BWA MEM. Project: PACA-CA.

  Dataset EGAD00001003162

• Constit Genome Sequencing

  WGS blood data (fastq raw read sequences) for French ICGC leiomyosarcoma cancer sequencing project, 67 samples representing 67 donors. Sequencing was performed on Illumina HiSeq. The libraries were then sequenced with a 2 x 100bp paired-end protocol to a minimum mean coverage of 30x.

  Dataset EGAD00001003190

• Leiomyosarcoma Cancer Genome Sequencing

  WGS cancer data (fastq raw read sequences) for French ICGC leiomyosarcoma cancer sequencing project, 78 samples representing 67 donors. Sequencing was performed on Illumina HiSeq. The libraries were then sequenced with a 2 x 100bp paired-end protocol to a minimum mean coverage of 50x.

  Dataset EGAD00001003191

• ICGC PCAWG Dataset: OV-AU_PCAWG_WGS_BWA

  ICGC PCAWG Dataset for WGS BAM aligned using BWA MEM. Project: OV-AU.

  Dataset EGAD00001003227

• Lung cancer organoids

  Organoids are self-organizing 3D structures grown from stem cells that recapitulate essential aspects of organ structure and function. Here we describe a method to establish long-term culture conditions of human airway epithelial organoids that contain all major cell populations and allow personalized human disease modelling. We collected macroscopically inconspicuous lung tissue from non-small-cell lung cancer (NSCLC) patients undergoing medically indicated surgery and isolated epithelial cells to engineer 3D organoids. We exploit the potential to derive sub-clones from AOs to demonstrate the feasibility of CRISPR gene editing. Finally, we show that AOs readily allow modelling of viral infections such as RSV and for the first time demonstrate the possibility to study neutrophil-epithelium interaction in an organoid model. Taken together, we anticipate that human AOs will find broad applications in the study of adult human airway epithelium in health and disease.

  Dataset EGAD00001004013

• Cancer Genomics of the Kidney

  The aim of CAGEKID is to carry out comprehensive detection of DNA markers for conventional (clear cell) renal carcinoma. The project includes complete analysis of somatic and constitutional DNA variation, methylation patterns and expression in a large number of constitutional/tumor pairs. CAGEKID is a part of the International Cancer Genome Consortium, ICGC.

  Dataset EGAD00001004018

• Exome sequencing of 142 gastric cancer and matched normal from Japanese cohorts (UT)

  As a contribution to the International Cancer Genome Consortium, exome sequencing of 142 Japanese gastric cancer with various histological subtypes have been conducted. This study aims to identify unique and common driver genes and molecular subtypes in Japanese gastric cancer. Please refer ICGC website for detail: http://icgc.org/icgc/cgp/69/420/1012357

  Dataset EGAD00001004041

• Exome sequencing of 102 gastric cancer and matched normal from Japanese cohorts (YCU)

  As a contribution to the International Cancer Genome Consortium, exome sequencing of 102 Japanese gastric cancer with various histological subtypes have been conducted. This study aims to identify unique and common driver genes and molecular subtypes in Japanese gastric cancer. Please refer ICGC website for detail: http://icgc.org/icgc/cgp/69/420/1012357

  Dataset EGAD00001004042

• A compendium of mutational signatures due to environmental exposures

  Whole-genome-sequencing (WGS) of human tumours has revealed distinct mutation patterns that hint at the causative origins of cancer. We examined mutational-signatures in 324 WGS of human induced pluripotent stem cells (iPSCs) following exposure to known or suspected environmental carcinogens. 79 agents were tested with or without metabolic activation at concentrations that produced measurable cytotoxicity; 41 yielded characteristic substitution mutational signatures. Some exhibit similarity with signatures found in human tumours. Additionally, 6 agents produced double-substitution signatures and 8 produced indel signatures. Investigating mutation asymmetries across genome topography reveals fully functional mismatch and transcription-coupled repair pathways in iPSCs. Primary adducts induced by environmental carcinogens can be resolved by disparate repair/replicative pathways, resulting in an assortment of signature outcomes even for a single mutagen. This compendium of experimentally-induced mutational-signatures permits further exploration of roles of environmental agents in cancer aetiology, and underscores how human stem cell DNA is directly vulnerable to environmental agents.

  Dataset EGAD00001004583

• Whole exome and targeted DNA sequencing data for formalin-fixed paraffin embedded tissue from de novo small cell prostatic carcinoma cases

  This dataset consists of 44 compressed paired fastq files, 15 of which are generated from whole exome sequencing, and 29 of which are generated from DNA sequencing using a targeted gene panel capturing the exonic regions of 73 prostate cancer driver genes. Targeted DNA sequencing was performed on an Illumina MiSeq (v3 600 cycle kit), and exome sequencing was done using an Illumina HiSeq 2500 (v4 250 cycle kit) machine. The fastq files are named in accordance with the sample aliases provided, which reflect the pathology of interest to this study (small cell prostatic carcinoma--SCPC), whether it was sequenced using an exome or targeted gene panel, whether the FFPE sample was sourced from tumor or benign tissue (labeled T or B, respectively), and whether there exists multiple samples belonging to a single patient.

  Dataset EGAD00001004139

• Genotyping by OncoArray and Global Screening Array for colorectal cancer risk prediction

  The study was conducted to build a Polygenic risk scores (PRS) based on a reported set of 140 single nucleotide polymorphisms that were identified to be associated with a higher risk of colorectal cancer (CRC). Genotyping by OncoArray and Global Screening Array was performed using DNA extracted from blood samples collected at baseline of 187 participants who develop CRC and 176 randomly selected controls without diagnosis of CRC identified within 14 years of follow-up.

  Study EGAS00001005411

• Illumina RNA sequencing for HLA expression qauntification

  In this study, we quantified mRNA expression levels of HLA class I and II genes from peripheral blood samples of 50 healthy individuals. The gene- and allele-specific mRNA expression was assessed using unique molecular identifiers, which enabled PCR bias removal and calculation of the number of original mRNA transcripts. We identified differences in mRNA expression between different HLA genes and alleles. Our results suggest that HLA alleles are differentially expressed and these differences in expression levels are quantifiable using RNA sequencing technology.

  Study EGAS00001004931

• Transcriptomic predictors of survival for palbociclib + endocrine therapy vs. capecitabine in aromatase inhibitor-resistant breast cancer from GEICAM/2013-02 PEARL

  We examined transcriptomic tumor features associated with survival from GEICAM/2013-02 PEARL, a phase III trial of palbociclib + ET vs. capecitabine in aromatase inhibitor-resistant HR+/HER2- MBC. PAM50 intrinsic subtype predicted PFS differences between palbociclib + ET and capecitabine, and lower B-cell-associated gene expression predicted longer OS with palbociclib + ET vs. capecitabine. These features may help identify HR+/HER2- tumors resistant to further ET-based treatment with CDK4/6 inhibitors.

  Study EGAS00001008177

• Comparison of transcriptional response of induced pluripotent stem (iPS) cell-derived and monocyte-derived macrophages to bacterial lipopolysaccharide stimulation

  In the first part of this project, we will differentiate IPS cells from 5 human donors into macrophages, and extract RNA from unstimulated and LPS stimulated macrophages to perform RNA sequencing. We will also extract RNA before and after stimulation in blood- derived macrophages from 5 additional, unrelated healthy samples. In the second part of the project, RNA-seq data will be analysed to compare LPS response of these two macrophage populations. In summary, we will perform 75bp PE RNA-seq on 20 samples (10 pre and post stimulus), on the HiSeq 2500 platform. Samples will be multiplexed at 5 samples / lane, so we will require 4 flow cells in total.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 EGAD00001001106

• Targeted Sequencing of 173 genes

  Targeted sequencing of 173 genes in 2433 primary breast tumours. Data includes 2433 tumour samples, 523 adjacent normal (breast) samples and 127 blood samples. Libraries were prepared with Illumina's Nextera custom enrichment kit targetting all the exons of the most frequently mutated breast cancer genes. Libraries were multiplexed (48 libraries per lane) and sequenced on Illumina HiSeq 2000 (100bp paired-end reads). Somatic mutations were calling with a custom pipeline. We identified 40 mutation-driver (Mut-driver) genes, and determined associations between mutations, driver CNA profiles, clinical-pathological parameters and survival. We assessed the clonal states of Mut-driver mutations, and estimated levels of intra-tumour heterogeneity using mutant-allele fractions. The results emphasize the importance of genome-based stratification of breast cancer, and have important implications for designing therapeutic strategies. Referece: Pereira et al. (2016) The somatic mutation profiles of 2,433 breast cancers refines their genomic and transcriptomic landscapes. Nature Communications

  Dataset EGAD00001002115

• Next Generation Sequencing in an IBD Pedigree Whole Genome Data

  In 2009 we identified a four-generation family with over 700 members and 41 affected with Crohn's disease (CD). At the time we sequenced the exome of 6 affected individuals but did not identify any coding variants which appear to explain the high prevalence of disease. Since then we have collected DNA from a large number of additional family members, genotyped linkage arrays on the entire family to refine genomic regions shared by identity by descent and genotyped affected and unaffected members at known CD risk loci identified by Genome Wide Association Studies (GWAS). These analyses have confirmed that a significant unexplained excess of disease remains after accounting for all known genetic factors, and that several regions of the genome are shared by a large fraction of affected individuals. We therefore perform whole genomes sequencing from 8 individuals which will allow us to impute the complete sequence of nearly all the members of the two largest and most severely affected branches of the family.

  Dataset EGAD00001000399

• NIHR BioResource Rare Diseases WGS project - Steroid Resistant Nephrotic Syndrome (SRNS) Rare Disease domain

  Short read whole genome sequencing (WGS) CRAM files for the NIHR BioResource Rare Diseases WGS project – Participants from the Steroid Resistant Nephrotic Syndrome (SRNS) Rare Disease domain

  Dataset EGAD00001004518

• NIHR BioResource Rare Diseases WGS project - Cerebral Small Vessel Disease (CSVD) Rare Disease domain

  Short read whole genome sequencing (WGS) CRAM files for the NIHR BioResource Rare Diseases WGS project – Participants from the Cerebral Small Vessel Disease (CSVD) Rare Disease domain

  Dataset EGAD00001004513

• NIHR BioResource Rare Diseases WGS project - Hypertrophic Cardiomyopathy (HCM) Rare Disease domain

  Short read whole genome sequencing (WGS) CRAM files for the NIHR BioResource Rare Diseases WGS project – Participants from the Hypertrophic Cardiomyopathy (HCM) Rare Disease domain

  Dataset EGAD00001004514

• NIHR BioResource Rare Diseases WGS project - Intrahepatic Cholestasis of Pregnancy (ICP) Rare Disease domain

  Short read whole genome sequencing (WGS) CRAM files for the NIHR BioResource Rare Diseases WGS project.Participants from the Intrahepatic Cholestasis of Pregnancy (ICP) Rare Disease domain

  Dataset EGAD00001004515

• NIHR BioResource Rare Diseases WGS project - Neuropathic Pain Disorders (NPD) Rare Disease domain

  Short read whole genome sequencing (WGS) CRAM files for the NIHR BioResource Rare Diseases WGS project – Participants from the Neuropathic Pain Disorders (NPD) Rare Disease domain

  Dataset EGAD00001004516

• NIHR BioResource Rare Diseases WGS project - Primary Membranoproliferative Glomerulonephritis (PMG) Rare Disease domain

  Short read whole genome sequencing (WGS) CRAM files for the NIHR BioResource Rare Diseases WGS project – Participants from the Primary Membranoproliferative Glomerulonephritis (PMG) Rare Disease domain

  Dataset EGAD00001004517

• NIHR BioResource Rare Diseases WGS project - Inherited Retinal Disorders (IRD) Rare Disease domain

  Short read whole genome sequencing (WGS) CRAM files for the NIHR BioResource Rare Diseases WGS project – Participants from the Inherited Retinal Disorders (IRD) Rare Disease domain

  Dataset EGAD00001004520

• NIHR BioResource Rare Diseases WGS project - Multiple Primary Malignant Tumours (MPMT) Rare Disease domain

  Short read whole genome sequencing (WGS) CRAM files for the NIHR BioResource Rare Diseases WGS project – Participants from the Multiple Primary Malignant Tumours (MPMT) Rare Disease domain

  Dataset EGAD00001004521

• NIHR BioResource Rare Diseases WGS project - Neurological and Developmental Disorders (NDD) Rare Disease domain

  Short read whole genome sequencing (WGS) CRAM files for the NIHR BioResource Rare Diseases WGS project – Participants from the Neurological and Developmental Disorders (NDD) Rare Disease domain

  Dataset EGAD00001004522

• NIHR BioResource Rare Diseases WGS project - Primary Immune Disorders (PID) Rare Disease domain

  Short read whole genome sequencing (WGS) CRAM files for the NIHR BioResource Rare Diseases WGS project.Participants from the Primary Immune Disorders (PID) Rare Disease domain

  Dataset EGAD00001004523

• ICGC PCAWG Dataset: MALY-DE_PCAWG_WGS_BWA

  ICGC PCAWG Dataset for WGS BAM aligned using BWA MEM. Project: MALY-DE.

  Dataset EGAD00001002123

• ICGC PCAWG Dataset: EOPC-DE_PCAWG_WGS_BWA

  ICGC PCAWG Dataset for WGS BAM aligned using BWA MEM. Project: EOPC-DE.

  Dataset EGAD00001002124

• ICGC PCAWG Dataset: BOCA-UK_PCAWG_WGS_BWA

  ICGC PCAWG Dataset for WGS BAM aligned using BWA MEM. Project: BOCA-UK.

  Dataset EGAD00001002125

• ICGC PCAWG Dataset: PRAD-UK_PCAWG_WGS_BWA

  ICGC PCAWG Dataset for WGS BAM aligned using BWA MEM. Project: PRAD-UK.

  Dataset EGAD00001002126

• ICGC PCAWG Dataset: PBCA-DE_PCAWG_WGS_BWA

  ICGC PCAWG Dataset for WGS BAM aligned using BWA MEM. Project: PBCA-DE.

  Dataset EGAD00001002127

• ICGC PCAWG Dataset: PRAD-CA_PCAWG_WGS_BWA

  ICGC PCAWG Dataset for WGS BAM aligned using BWA MEM. Project: PRAD-CA.

  Dataset EGAD00001002128

• ICGC PCAWG Dataset: BRCA-EU_PCAWG_WGS_BWA

  ICGC PCAWG Dataset for WGS BAM aligned using BWA MEM. Project: BRCA-EU.

  Dataset EGAD00001002129

• ICGC PCAWG Dataset: CLLE-ES_PCAWG_WGS_BWA

  ICGC PCAWG Dataset for WGS BAM aligned using BWA MEM. Project: CLLE-ES.

  Dataset EGAD00001002130

• ICGC PCAWG Dataset: RECA-EU_PCAWG_WGS_BWA

  ICGC PCAWG Dataset for WGS BAM aligned using BWA MEM. Project: RECA-EU.

  Dataset EGAD00001002131

• ICGC PCAWG Dataset: PACA-AU_PCAWG_WGS_BWA

  ICGC PCAWG Dataset for WGS BAM aligned using BWA MEM. Project: PACA-AU.

  Dataset EGAD00001002132

• ICGC PCAWG Dataset: LIRI-JP_PCAWG_WGS_BWA

  ICGC PCAWG Dataset for WGS BAM aligned using BWA MEM. Project: LIRI-JP.

  Dataset EGAD00001002155

• ICGC PCAWG Dataset: ESAD-UK_PCAWG_WGS_BWA

  ICGC PCAWG Dataset for WGS BAM aligned using BWA MEM. Project: ESAD-UK.

  Dataset EGAD00001002156

• ICGC PCAWG Dataset: PAEN-IT_PCAWG_WGS_BWA

  ICGC PCAWG Dataset for WGS BAM aligned using BWA MEM. Project: PAEN-IT.

  Dataset EGAD00001002153

• ICGC PCAWG Dataset: PAEN-AU_PCAWG_WGS_BWA

  ICGC PCAWG Dataset for WGS BAM aligned using BWA MEM. Project: PAEN-AU.

  Dataset EGAD00001002154

• ICGC PCAWG Dataset: MELA-AU_PCAWG_WGS_BWA

  ICGC PCAWG Dataset for WGS BAM aligned using BWA MEM. Project: MELA-AU.

  Dataset EGAD00001002157

• Impact of mutational profiles on response of primary oestrogen receptor-positive breast cancers to oestrogen deprivation

  Presurgical studies allow study of the relationship between mutations and response of estrogen receptor positive (ER+) breast cancer to aromatase inhibitors (AIs) but have been limited to small biopsies. Here in Phase I of this study, we perform exome sequencing on baseline, surgical core-cuts and blood from 60 patients (40 AI treated, 20 Controls). In poor responders (based on Ki67 change) we find significantly more somatic mutations than good responders. Subclones exclusive to baseline or surgical cores   occur in approximately 30% of tumours. In Phase II we combine targeted sequencing on another 28 treated patients with Phase I. We find six genes frequently mutated: PIK3CA, TP53, CDH1, MLL3, ABCA13 and FLG with 71% concordance between paired cores. TP53 mutations are associated with poor response. We conclude that multiple biopsies are essential for confident mutational profiling of ER+ breast cancer and TP53 mutations are associated with resistance to oestrogen deprivation therapy.

  Dataset EGAD00001002651

• Lung cancer organoids addition

  Organoids are self-organizing 3D structures grown from stem cells that recapitulate essential aspects of organ structure and function. Here we describe a method to establish long-term culture conditions of human airway epithelial organoids that contain all major cell populations and allow personalized human disease modelling. We collected macroscopically inconspicuous lung tissue from non-small-cell lung cancer (NSCLC) patients undergoing medically indicated surgery and isolated epithelial cells to engineer 3D organoids. We exploit the potential to derive sub-clones from AOs to demonstrate the feasibility of CRISPR gene editing. Finally, we show that AOs readily allow modelling of viral infections such as RSV and for the first time demonstrate the possibility to study neutrophil-epithelium interaction in an organoid model. Taken together, we anticipate that human AOs will find broad applications in the study of adult human airway epithelium in health and disease.

  Dataset EGAD00001004943

• Pseudotime ordering of cell cycle state (2020-01-29)

  We will be using G&T method to sequence single cell genome and transcriptome derived from FS13B iPSCs cell line. The cell cycle state of each of the single cells is known. Hence, we will be analysing the genome and transcriptome of single cells from each of the cell cycle state to generate a copy number profile and transcriptome profile per given cell cycle stage: G1, S, G2, S. . This dataset contains all the data available for this study on 2020-01-29.

  Dataset EGAD00001005919

• Guardians of the genome: protecting DNA from endogenous sources of damage

  Mutational signatures are imprints of cell-intrinsic and extrinsic pathophysiological processes that have occurred through tumorigenesis. Experimental efforts to explore signature etiologies have produced a compendium of signatures of exogenous mutagens previously. Here, we unearth major sources of endogenous DNA damage and the genes that are critical to mitigating this innate stream of DNA damage under normal, physiological circumstances. We performed whole genome sequencing of 173 subclones of CRISPR-Cas9 knockouts of 43 genes in a human induced pluripotent stem cell system, in the absence of any added DNA damage. We reveal substitution and indel signatures that arise from those genes which are essential guardians of the genome. By detailed dissection and comparisons to cancer-derived signatures, we demonstrate interminable sources of constitutive DNA damage, and some mechanistic knowledge into how guardian genes preserve the genome. Based on these experimental insights, we develop and benchmark a tool for clinical classification of tumor samples.

  Dataset EGAD00001006055

• Whole genome sequencing in prime-edited human organoids

  We performed whole genome sequencing to detect possible off-target mutations induced by prime editing. Liver organoids, derived from a healthy control, were transfected with either control (GFP) plasmids or prime editing plasmids (GFP+PE2+pegRNA+nickRNA) to induce a 6-bp deletion in CTNNB1. One control and two prime-edited organoid lines were clonally expanded from single cells. High-throughput sequencing was performed on the complete genomic DNA isolated from these clonal lines, as well as the starting culture (bulk). After correction for germline mutations in the starting culture, new mutations in the control and prime-edited lines were compared. The same approach was followed in small intestinal organoids, derived from a patient with disease-causing 3-bp deletion in DGAT1. In these small intestinal organoids, prime editing was used to insert the 3 missing nucleotides. Two corrected clones were compared to one control clone.

  Dataset EGAD00001006352

• Combinatorial CRISPR screen identifies fitness effects of paralogues FAM50A and FAM50B

  Genetic redundancy has evolved as a way for human cells to survive the loss of genes that are single copy and essential in other organisms, but also allows tumours to survive despite having highly rearranged genomes. In this study we CRISPR screen 1,191 gene pairs, including paralogues and known and predicted synthetic lethal interactions to identify 105 gene combinations whose co-disruption results in a loss of cellular fitness. 27 pairs influence fitness across multiple cell lines including the paralogues FAM50A/FAM50B, two genes of unknown function. Silencing of FAM50B occurs across a range of tumour types and in this context disruption of FAM50A reduces cellular fitness whilst promoting micronucleus formation and extensive perturbation of transcriptional programmes. This dataset includes CRISPR screening of cancer cell lines, RNA sequencing studies of cancer cell lines and also data from the sequencing of tumour xenografts collected from mice.

  Dataset EGAD00001006649

• MutWP5: CRUK Mutographs of Cancer: Lung: PD38233 (WG) (2021-02-02)

  Sequencing of LCM-derived microbiopsies from explanted lung from COPD patient. Goal to assess the mutational burden, spectrum, and clonal dynamics within the tissue. Deep sampling throughout multiple regions of the lung will determine whether there are differences in smoking-related mutation burden in different portions of the lung. Whole-genome sequencing will be conducted on samples identified as promising from the initial targeted data. Results from this portion of the study will be compared to other individuals with smoking-related diseases (COPD, pulmonary fibrosis, lung cancer), and normal, non-smoking lungs. . This dataset contains all the data available for this study on 2021-02-02.

  Dataset EGAD00001006930

• MutWP5: CRUK Mutographs of Cancer: Lung: PD43291_Novaseq (Exome) (2021-02-02)

  Sequencing of LCM-derived microbiopsies from explanted lung from COPD patient. Goal to assess the mutational burden, spectrum, and clonal dynamics within the tissue. Deep sampling throughout multiple regions of the lung will determine whether there are differences in smoking-related mutaiton burden in different portions of the lung. Whole-genome sequencing will be conducted on samples identified as promising from the initial targeted data. Results from this poriton of the study will be compared to other individuals with smoking-related diseases (COPD, pulmonary fibrosis, lung cancer), and normal, non-smoking lungs. . This dataset contains all the data available for this study on 2021-02-02.

  Dataset EGAD00001006932

• Leiomyosarcoma Whole Genome Sequencing

  DNA was extracted from fresh frozen LMS material for 29 untreated tumors (24 primary tumors, 5 metastatic 13 relapses) and 13 tumors treated with radiation (7 primaries, 6 metastatic relapses). DNA from matched blood was used as a normal reference. Whole-genome sequencing was performed using established protocols on Illumina instruments.

  Dataset EGAD00001007722

• Prediction of HLA genotypes using NGS data

  High-precision human leukocyte antigen (HLA) genotyping is crucial for anti-cancer immunotherapy, but existing tools predicting HLA genotypes using next-generation sequencing (NGS) data are insufficiently accurate. We compared the availability and accuracy of eight HLA genotyping tools (OptiType, HLA-HD, PHLAT, seq2HLA, arcasHLA, HLAscan, HLA*LA, and Kourami) using 1,275 cases from the 1000 Genomes Project data and created a new HLA-genotyping algorithm combining tools. Then, we assessed the new algorithm’s performance in 39 in-house samples with normal whole-exome sequencing (WES) data and polymerase chain reaction–sequencing-based typing (PCR-SBT) results.

  Dataset EGAD00001007733

• Dataset for cancer_of_unknown_primary-RNA

  Rare cancer sequencing data of 58 runs in tumor/control pairs, which were uploaded to umbrella studies. The sequencing was always paired

  Dataset EGAD00001008857

• Dataset for bone_cancer-WHOLE_GENOME

  Rare cancer sequencing data of 48 runs in tumor/control pairs, which were uploaded to umbrella studies. The sequencing was always paired

  Dataset EGAD00001008866

• Dataset for breast_cancer-EXON

  Rare cancer sequencing data of 94 runs in tumor/control pairs, which were uploaded to umbrella studies. The sequencing was always paired

  Dataset EGAD00001008868

• Dataset for cancer_of_unknown_primary-EXON

  Rare cancer sequencing data of 62 runs in tumor/control pairs, which were uploaded to umbrella studies. The sequencing was always paired

  Dataset EGAD00001008870

• Dataset for colorectal_cancer-EXON

  Rare cancer sequencing data of 119 runs in tumor/control pairs, which were uploaded to umbrella studies. The sequencing was always paired

  Dataset EGAD00001008871

• Dataset for GIST-EXON

  Rare cancer sequencing data of 64 runs in tumor/control pairs, which were uploaded to umbrella studies. The sequencing was always paired

  Dataset EGAD00001008875

• Dataset for GIST-WHOLE_GENOME

  Rare cancer sequencing data of 18 runs in tumor/control pairs, which were uploaded to umbrella studies. The sequencing was always paired

  Dataset EGAD00001008876

• Dataset for gynecologic_cancer-WHOLE_GENOME

  Rare cancer sequencing data of 38 runs in tumor/control pairs, which were uploaded to umbrella studies. The sequencing was always paired

  Dataset EGAD00001008878

• Dataset for head_and_neck_cancer-WHOLE_GENOME

  Rare cancer sequencing data of 56 runs in tumor/control pairs, which were uploaded to umbrella studies. The sequencing was always paired

  Dataset EGAD00001008879

• Dataset for liposarcoma-WHOLE_GENOME

  Rare cancer sequencing data of 48 runs in tumor/control pairs, which were uploaded to umbrella studies. The sequencing was always paired

  Dataset EGAD00001008888

• Dataset for melanoma-WHOLE_GENOME

  Rare cancer sequencing data of 22 runs in tumor/control pairs, which were uploaded to umbrella studies. The sequencing was always paired

  Dataset EGAD00001008889

• Dataset for melanoma-EXON

  Rare cancer sequencing data of 76 runs in tumor/control pairs, which were uploaded to umbrella studies. The sequencing was always paired

  Dataset EGAD00001008890

• Dataset for NSCLC-WHOLE_GENOME

  Rare cancer sequencing data of 34 runs in tumor/control pairs, which were uploaded to umbrella studies. The sequencing was always paired

  Dataset EGAD00001008894

• RNAseq data

  Bulk RNAseq of sigmoid colon biopsies from healthy volunteers and ulcerative colitis patients. Subjects were treated with Placebo or IL-22Fc at different doses, and biopsies were collected at day 0 and day 30 post treatment and prepared for RNA sequencing.

  Dataset EGAD00001008816

• Fecal 16S UC sequencing data

  Fecal 16S-V4 rRNA gene sequence data from NCT02749630 ulcerative colitis patients. Stool samples were collected at screening as well as on days 29, 43, 64, 85, and 134 processed for 16SV4 rRNA gene sequencing

  Dataset EGAD00001008818

• Fecal 16S HV sequencing data

  Fecal 16S-V4 rRNA gene sequence data from NCT02749630 healthy volunteers. Stool samples were collected at screening as well as on days 29, 43, 64, 85, and 134 processed for 16SV4 rRNA gene sequencing

  Dataset EGAD00001008840

• Fecal WMS HV sequencing data

  Fecal WMS data from NCT02749630 healthy volunteers. Stool samples were collected at screening as well as on days 29, 43, and 64 and prepared for whole metagenomic sequencing.

  Dataset EGAD00001008841

• Dataset for bone_cancer-RNA

  Rare cancer sequencing data of 55 runs in tumor/control pairs, which were uploaded to umbrella studies. The sequencing was always paired

  Dataset EGAD00001008848

• Dataset for breast_cancer-RNA

  Rare cancer sequencing data of 59 runs in tumor/control pairs, which were uploaded to umbrella studies. The sequencing was always paired

  Dataset EGAD00001008850

• OSTEOMICS_RNA

  RNA sequencing of 79 libraries were prepared, from sample of Osteosarcoma tumors biopsied at diagnosis, with TruSeq Stranded mRNA kit following recommendations: the key steps consist of PolyA mRNA capture with oligo dT beads using 1µg total RNA, fragmentation to approximately 400pb, DNA double strand synthesis, and ligation of Illumina adaptors amplification of the library by PCR for sequencing. Libraries sequencing was performed using Illumina sequencers (NextSeq 500 or Hiseq 2000/2500/4000) in 75 bp paired-end mode.

  Dataset EGAD00001008213

• DNA methylation sequencing profiles of 1538 breast tumors and 244 normal breast tissues

  DNA methylation sequencing profiles of 1538 breast tumors and 244 normal breast tissues. Libraries were prepared using a custom Reduced Representation Bisulfite Sequencing pipeline. Sequencing was performed on the Illumina HiSeq 2500 (v4 chemistry), with single-end reads of 125 bp length. Multiplexing was conducted at the level of 8 samples per lane. FASTQ files are provided for 1538 breast tumors and 244 normal breast tissues. Reference: Batra et al. (2021). DNA methylation landscapes of 1538 breast cancers reveal a replication-linked clock, epigenomic instability and cis-regulation.

  Dataset EGAD00001007976

• Spatial multi-omic map of human myocardial infarction

  We applied an integrative single-cell genomics strategy with single nucleus RNA sequencing (snRNA-seq) and single nucleus Assay for Transposase-Accessible Chromatin sequencing (snATAC-seq) together with spatial transcriptomics from the same tissue mapping human cardiac cells in homeostasis and after myocardial infarction (MI) at unprecedented spatial and molecular resolution. We profiled in total 31 samples from 23 patients including four non-transplanted donor hearts as controls and samples from tissues with necrotic tissue areas (ischemic zone, IZ), border zone (BZ), and the non-affected left ventricular myocardium (remote zone, RZ) of patients with acute MI.

  Dataset EGAD00001008952

• cfMethyl-Seq

  cfMethyl-Seq libraries were generated for 479 cfDNA samples and were sequenced with 150 bp paired-end reads.

  Dataset EGAD00001009003

• Garvan/St Vincent’s Prostate Cancer Tissue and Data

  The cohort (n=53) consists of prostate cancer patients from Australia. For each patient, a pair of blood and tumour samples were collected. The sequencing data was mapped to hg38 reference. Blood BAMs are named with “-B” as suffix and tumour BAMs are named with “-T” as suffix.

  Dataset EGAD00001009066

• Single nuclei RNA-Seq from 5 regions of the human fetal brain

  Data generated through single nuclei RNA sequencing on 5 regions of the brain (frontal cortex, ganglionic eminence, hippocampus, thalamus and cerebellum) from 3 fetuses (two of 14 and one of 15 post-conception weeks, all female). Tissue was acquired from the MRC-Wellcome Trust Human Developmental Biology Resource (HDBR) with ethical approval. snRNA-seq libraries were prepared from ∼10,000 nuclei from each sample using Chromium Single Cell 3ʹ (v3) reagents (10X Genomics). Quality control of libraries was performed using the Agilent 5200 Fragment Analyzer before sequencing on an Illumina NovaSeq 6000 to a depth of at least 865 million (median = 1.01 billion) read pairs per library. Raw sequencing data were converted into FASTQ files. For a full description of data generation, please see Cameron et al, Biological Psychiatry 2022, https://doi.org/10.1016/j.biopsych.2022.06.033.

  Dataset EGAD00001009303

• Roche Alzheimer's dataset

  The Roche Alzheimer’s disease dataset (Roche_AD) consists of 80 samples from 40 unique individuals (one sample from the temporal cortex and one from deep white matter for each individual, 12 cases, 25 controls, 3 dementia). A total of 12,000 estimated cells from each sample were loaded on the 10x Single Cell Next GEM G Chip. cDNA libraries were prepared using the Chromium Single Cell 3’ Library and Gel Bead v3 kit according to the manufacturer’s instructions. cDNA libraries were sequenced using the Illumina NovaSeq 6000 System and NovaSeq 6000 S2 Reagent Kit v1.5 (100 cycles), aiming at a sequencing depth of minimum 30K reads/nucleus.

  Dataset EGAD00001009166

• Organoid Derivation Project - GRCh38 - WGS (2023-06-22)

  Sequencing of tissue samples and their derived organoids from oesophageal, pancreatic and colorectal cancer patients. . This dataset contains all the data available for this study on 2023-06-22.

  Dataset EGAD00001011093

• Single-cell RNA sequencing of SarBC-01 treated with Dexamethasone vs DMSO, with or without Matrigel.

  This dataset contains raw FASTQ files from single cell RNA sequencing of SarBC-01 cells treated with Dexamethasone vs DMSO, with or without Matrigel, processed with MULTI-seq. Cells from 4 different culture conditions (+Mat/Dex, +Mat/DMSO, -Mat/Dex, -Mat/DMSO) were harvested, processed for multiplexing using the MULTI-seq protocol and loaded in a Chromium Single Cell 3ʹ GEM Library and Gel Bead Kit v3 (10x Genomics). Gene expression (cDNA) and MULTI-seq libraries were prepared according to the manufacturers’ protocol of Chromium Next GEM Single Cell 3’ reagents Kits v3.1 (Dual Index). Finally, cDNA and MULTI-seq libraries were analyzed using an Agilent Bioanalyzer (DNA High Sensitivity kit) and sequenced on a NovaSeq6000 (S2 flow cell) platform. MULTISEQ BARCODES: TTAGCCAG => Matrigel/DMSO CCACAATG => Matrigel/Dexamethasone GCACACGC => noMatrigel/DMSO AGAGAGAG => noMatrigel/Dexamethasone

  Dataset EGAD00001011155

• INSPIRE multi-timepoint cfMeDIP dataset

  This dataset contains raw sequencing data from multi-timepoint cell-free methylated DNA immunoprecipitation and sequencing (cfMeDIP-seq) of plasma samples from the INSPIRE study (NCT02644369). Details about the study, including inclusion/exclusion criteria and interventions are available at https://clinicaltrials.gov/study/NCT02644369. Briefly, five cohorts were included, INS-A (head & neck squamous cell carcinoma), INS-B (triple-negative breast cancer), INS-C (high-grade serous ovarian cancer), INS-D (melanoma), and INS-E (mixed solid tumors). All patients in the study were diagnosed with advanced cancer and received treatment with pembrolizumab. Plasma samples were collected at baseline and every 3 cycles until disease progression, death, loss of follow-up, or completion of the study. Plasma samples were first processed for cell-free DNA mutations and remaining samples were then processed by cfMeDIP-seq, prioritizing baseline and post-cycle 3 samples. In total, data from 204 timepoints from 87 distinct patients are deposited.

  Dataset EGAD00001011312

• RNA-Seq dataset of Targeting the dark proteome to expand the lineage-retained antigen landscape in neuroblastoma

  This dataset contains bulk RNA-sequencing data generated to enable custom transcriptome assembly and to provide expression context for matched ribosome profiling in the discovery of lineage-retained neuroblastoma tumor antigens. RNA was sequenced from 183 neuroblastoma samples comprising cell lines, patient-derived tumor organoids, and primary patient tumors spanning the adrenergic (ADRN) and mesenchymal (MES) lineage states, with 101 samples prepared as rRNA-depleted (total RNA) libraries and 82 samples prepared as poly(A)-selected libraries. Libraries were sequenced paired-end (2x150 bp) on the Illumina NovaSeq 6000 platform. Raw data are provided as paired-end fastq.gz files.

  Dataset EGAD00001016124

• High-Risk Breast Cancer GWAS

  The GWAS includes High Risk Women from the following epidemiological studies of breast cancer, comprising a total of 3,719 cases and 3,642 controls (cases/controls: MEC, 0/200; ABCFR, 326/418; FCCC, 56/3; BCFR-UT, 66/32; CNIO-BC, 87/92; GESBC, 65/0; LIFE, 164/0; MARIE, 41/105; MAYO, 208/210; MNYR, 293/409; MSKCC, 310/0; NC-BCFR, 234/233; OFBCR, 553/560; POSH, 377/0; HBOC, 47/47; BBCS, 612/1333; UPENN, 280/0 This study was funded by a grant CA165038 to Christopher Haiman (University of Southern California) and John Hopper (University of Melbourne) from the National Cancer Institute, National Institute of Health. The contributing studies: Multiethnic Cohort (MEC). This study was supported by grant UM1 CA164973 from the National Cancer Institute, National Institute of Health. Ontario Familial Breast Cancer Registry, the Ontario site of the Breast Cancer Family Registry Cohort (OFBCR). This study was supported by grant UM1 CA164920 from the National Cancer Institute. Utah Breast Cancer Family Registry (BCFR-UT). This study was supported by grant UM1 CA164920 from the National Cancer Institute. New York site of the Breast Cancer Family Registry (MNYR). This study was supported by grant UM1 CA164920 from the National Cancer Institute. Northern California site of the Breast Cancer Family Registry (NC-BCFR). This study was supported by grant UM1 CA164920 from the National Cancer Institute. Australian Breast Cancer Family Registry (ABCFR). This study was supported by grant UM1 CA164920 from the National Cancer Institute. Breast Cancer Study (CNIO-BC). This study has been partially funded by The Spanish Network on Rare Diseases (CIBERER) and the Spanish National Genotyping Center (CEGEN). Genetic Epidemiologic Study of Breast Cancer (GESBC). The GESBC was supported by the Deutsche Krebshilfe e. V. [70492] and German Cancer Research Center (DKFZ). Mammary Carcinoma Risk Factor Study (MARIE). This study was supported by the Deutsche Krebshilfe e.V. [70-2892-BR I, 106332, 108253, 108419], the Hamburg Cancer Society, the German Cancer Research Center (DKFZ) and the Federal Ministry of Education and Research (BMBF) Germany [01KH0402]. Prospective study of Outcomes in Sporadic versus Hereditary breast cancer (POSH). Funding for the POSH study was provided by Cancer Research UK (grant refs A7572, A11699, C22524), the Breast Cancer Campaign (grant number: 2013MayPR044) and from 2003-2006 by a grant from The Wessex Cancer Trust. Prospective study of Outcomes in Sporadic versus Hereditary breast cancer (POSH). Funding for the POSH study was provided by Cancer Research UK (grant refs A7572, A11699, C22524), the Breast Cancer Campaign (grant number: 2013MayPR044) and from 2003-2006 by a grant from The Wessex Cancer Trust. Hereditary Breast and ovarian Cancer: Genetic and Molecular Studies (HBOC). This study was supported by National Cancer Institute grant CA58860 and The Lon V Smith Foundation: LVSF-44528. Mayo Clinic inherited breast and ovarian cancer study (MAYO). This study was supported by the Breast Cancer Research Foundation, NIH grants CA192393, CA176785, and an NIH CA116201 Specialized Program of Research Excellence (SPORE) in Breast Cancer. British Breast Cancer Study (BBCS); Mammographic oestrogens and growth factor study (MOG). The BBCS and the MOG study are funded by Cancer Research UK and Breakthrough Breast Cancer and acknowledge NHS funding to the NIHR Biomedical Research Centre, and the National Cancer Research Network (NCRN). Genotyping of non-BRCA1/2 mutation carriers (UPENN). The study is supported by the Basser Research Center at the University of Pennsylvania, Rooney Family Foundation, NIH grants CA176785 and CA192393, the Breast Cancer Research Foundation, the Susan G. Komen Foundation for the Cure and Macdonald Family Foundation. Clinical Significance of Germline BRCA Mutations (MSKCC). The study is supported by the Robert and Kate Niehaus Clinical Cancer Genetics Research Initiative, The Breast Cancer Research Foundation, and the Cancer Center Support Grant from the National Institute of Health, National Cancer Institute 5P30 CA08748-40. Women's Learning the Influence of Family and Environment (LIFE). This study was supported by grants CA17054 and CA74847 from the National Cancer Institute, National Institutes of Health, No. 4PB-0092 from the California Breast Cancer Research Program of the University of California. Philadelphia site of the Breast Cancer Family Registry at Fox Chase Cancer Center (FCCC). This study is supported by NIH grant CA164920.

  Study phs000929

• Determination of Cross-Reactive Immunological Material (CRIM) status and longitudinal follow-up of individuals with Pompe disease

  Infantile-onset Pompe disease is an inherited disorder that is normally diagnosed within the first months of life. It is caused by lack of or defect in an enzyme (a special protein that carries out normal chemical reactions within the body) called acid alpha-glucosidase (GAA). GAA normally breaks down glycogen (stored sugar) in lysosomes (the part of the cell that digests food and other chemicals). Pompe disease is one of many lysosomal storage diseases (LSDs). LSDs are diseases caused by the malfunction of the lysosome or one of their digestive enzymes. Patients with Pompe disease cannot break down lysosomal glycogen. This causes glycogen to build up and damage cells throughout the body, especially in the heart and muscles. Current treatment for Pompe disease involves enzyme replacement therapy (ERT). In this treatment, the drug alglucosidase alfa (Myozyme) is put into your blood. The drug provides a form of the GAA enzyme to replace the enzyme that is missing or not working properly in the patient's blood. This treatment has allowed babies to live longer and achieve developmental milestones. In this study, researchers will learn about the patient's ability to tolerate ERT. Cross-Reactive Immunological Material (CRIM) is a measurement of natural GAA production. A patient's CRIM status (either positive or negative) is an important factor that affects how he or she responds to ERT with Myozyme. Children who produce some natural GAA are classified as CRIM+, while children who do not produce any natural GAA are classified as CRIM-. Children who are CRIM+ generally tolerate ERT well. But, children who are CRIM-, and some children classified as CRIM+, have a poor response to ERT. Patients who have a poor response to ERT have complications because their body sees Myozyme as "foreign" and triggers an immune response to try to remove it from the body. Treatments are currently being developed to stop this immune response and prevent complications from ERT. We will enroll patients with Infantile Pompe disease in this longitudinal natural history (observational) study. The specific aims of this study are: To determine and correlate Cross-Reactive Immunological Material (CRIM) status with the GAA gene mutations found on these patients To validate an approach for determining CRIM status from whole blood sample, with the gold standard determination of CRIM status by skin fibroblasts and mutation analysis To explore the clinical treatment response and natural history of CRIM-positive and CRIM-negative Pompe disease patients with and without immune modulation To investigate the role of immune response to treatment

  Study phs001555

• Disorders/Differences of Sex Development (DSD) Study Performed at UCLA in Collaboration with the DSD-Translational Research Network (DSD-TRN), with the Support of the Gabriella Miller Kids First Pediatric Research Program

  The Gabriella Miller Kids First Pediatric Research Program (Kids First) is a trans-NIH effort initiated in response to the 2014 Gabriella Miller Kids First Research Act and supported by the NIH Common Fund. This program focuses on gene discovery in pediatric cancers and structural birth defects and the development of the Gabriella Miller Kids First Pediatric Data Resource (Kids First Data Resource). Both childhood cancers and structural birth defects are critical and costly conditions associated with substantial morbidity and mortality. Elucidating the underlying genetic etiology of these diseases has the potential to profoundly improve preventative measures, diagnostics, and therapeutic interventions. Whole Genome Sequence (WGS) and phenotypic data from this study are accessible through dbGaP and kidsfirstdrc.org, where other Kids First datasets can also be accessed. Disorders/Differences of Sex Development (DSD) are congenital conditions in which development of chromosomal, gonadal, or anatomic sex is atypical. DSD are chronic medical conditions collectively affecting ~1% of the population, frequently requiring life-long care by multiple specialists, and carrying a significant public health burden. Some are associated with life-threatening events, such as adrenal crises in Congenital Adrenal Hyperplasia (CAH). DSD are also associated with increased infertility, cancer, gender dysphoria risks, psychosocial distress and pervasive challenges to health-related quality of life (HRQoL) for patients and families. DSD are broadly classified into three categories: sex chromosome DSD, 46,XY DSD and 46,XX DSD, and further classified according to the type of gonad found in the patient (ovary, testis, ovotestis). We were able to increase significantly the diagnostic success for DSD using Whole Exome Sequencing (WES), with the identification of disease-causing and likely pathogenic variants in a third of a cohort of 46,XY patients. We have therefore proposed a shift in the diagnostic approach to DSD to use next-gen sequencing as a first-line clinical test, which could lead to faster and more accurate diagnosis, and orient further clinical management, limiting unnecessary, costly, and often invasive endocrine testing and imaging. However many remain unexplained (over half of the XY cases, a significant minority of XX cases, including most ovotesticular DSD, and most syndromic cases). In addition, the very large phenotypic variability in cases with known variants in the same gene is unexplained. We here propose to use Whole-Genome Sequencing (WGS), which dramatically improves upon exome sequencing, covering both coding and non-coding parts of the genome more uniformly, as an approach to not only improve diagnostic yield, but also to identify novel genes and regulatory elements involved in DSD.

  Study phs001178

• Analysis of the Whole Transcriptomes of Human Testis with Complete Spermatogenesis and of Human Testes with Sertoli Cell-Only Syndrome

  Sertoli cell-only syndrome is severe form of human male infertility in which most seminiferous tubules appear to lack all spermatogenic cells, including spermatogonial stem cells (SSCs). However, a few small tubule segments of some patients have active spermatogenesis and, thus, functional stem cell niches and SSCs. Normally SSCs replicate, migrate and refill adjacent empty niches, but this does not appear to occur in SCO syndrome. We hypothesized that this failure occurs because most niches are dysfunctional. As Sertoli cells are essential to formation of these niches, we used RNAseq to compare the transcriptomes of human testes with qualitatively normal (complete) spermatogenesis (n=4) with the transcriptomes of human testes with SCO syndrome (n=7). We then focused our analysis on the expression of transcripts that bioinformatic analyses identified as Sertoli cell signature transcripts. Results show that Sertoli cells in SCO testes express abnormally low levels of GDNF, FGF8 and BMP4, all of which are important regulators of mouse SSCs and/or progenitor spermatogonia. Sertoli cells in SCO testes express significantly reduced levels of transcripts for proteins that polarize the Sertoli cell plasma membrane and regulate the trafficking of cell adhesion and gap junction proteins in and out of that plasma membrane.

  Study phs001777

• Relationship between low LDL cholesterol concentrations not due to statin therapy and risk of type 2 diabetes: a US-based cross-sectional observational study using electronic medical records

  Lipid lowering therapy using HMG-CoA reductase inhibitors (statins) is associated with an approximately 9-12% increase in the risk of new-onset type 2 diabetes (T2DM). The risk of diabetes could be increased by statins directly; however, genetic approaches have also implicated low LDL cholesterol (LDL-C) concentrations as a risk factor for T2DM. Mendelian randomization studies using functional variants in both HMGCR (GeneID:3156) and PCSK9 (GeneID:255738) genes found a higher risk of T2DM in individuals with variants associated with lower LDL-C concentrations. Since PCSK9 and HMGCR are involved in lipid metabolism through distinct molecular pathways, the altered glycemic effect associated with variants in both genes is likely to be the result of their common effect on LDL-C concentrations. Despite the findings from statin clinical trials and genetic studies, there is little direct evidence implicating low LDL-C concentrations with increased risk of T2DM. Individuals who have very low LDL-C concentrations not due to lipid lowering therapy can provide insights into the relationship between low LDL-C concentrations and T2DM. Here, we used de-identified electronic health records (EHRs) to test the hypothesis that low LDL-C concentrations are associated with T2DM.

  Study phs001588

• Predicting the Prevalence of Complex Genetic Diseases from Individual Genotype Profiles Using Capsule Networks

  Diseases with a complex genetic architecture, such as amyotrophic lateral sclerosis (ALS) as a most prominent example, are hard to disentangle. "Human mind-friendly" methods, such as linear approaches used in genome wide association studies (GWAS), remain blind to many genetic variants that matter. On the other hand, methods that are sufficiently sophisticated to entirely capture the characteristic interplay of genetic variants remain black boxes for the human mind. Here, we give this a decided, and as we argue, a very promising try. We present DiseaseCapsule, a capsule network-based approach that enables us to predict prevalence/occurrence of a genetically complex disease from individual genotype profiles. Importantly, capsule networks are considerably easier to decompose into their components than ordinary deep neural networks, which promotes the interpretability of their results. The data we used are from Project MinE, a large-scale study that aims to reveal the genetic and epigenetic mechanisms that underlie ALS in the framework of a globally concerted collaboration. Specifically, we used data from the Dutch cohort of the project, which contains 7213 healthy ('control') individuals and 3192 individuals affected with ALS. The cohort includes 5208 females and 5197 males. All participants of the study were genotyped using an Illumina 2.5M SNP array.

  Study phs003146

• Genome-Wide Assessment of DNA Methylation in Systemic Lupus Erythematosus-Related Autoantibodies

  Systemic lupus erythematosus (SLE) is a chronic autoimmune disease that can have debilitating effects on multiple organ systems. In SLE, the pivotal immunologic disturbance is the formation of autoantibodies directed against nuclear and cellular antigens. These autoantibodies are associated with specific organ manifestations. Our previous work has shown that certain single nucleotide polymorphisms (SNPs) are associated with the production of SLE-related autoantibodies. However, these genetic associations do not completely explain autoantibody development in SLE. Therefore, we examined whether epigenetic factors such as DNA methylation may be associated with the development of SLE-related autoantibodies. In this study, we examined whether differential DNA methylation is associated with anti-dsDNA, anti-SSA/Ro, anti-Smith, and anti-RNP autoantibodies. Using the Illumina HumanMethylation450 Beadchip, over 450,000 DNA methylation sites were characterized in 325 female SLE cases of European descent. Using a multivariable regression analyses, the methylation status of 16 CpG sites in 11 genes was found to be associated with the SLE-related autoantibodies under study. This study shows that epigenetic factors are associated with autoimmune disease phenotypes, and epigenetic studies are a complementary method to genetic association studies for understanding the biologic mechanisms contributing to autoimmune disease.

  Study phs000947

• Genomic Sequencing of Cervical Cancers

  Cervical cancer is responsible for 10-15% of cancer related deaths in women worldwide. The etiological role of infection with high-risk human papilloma viruses (HPV) in carcinomas of the cervix is well established. In general, the development of cervical carcinomas follows a progression from persistent HPV infection through precancerous lesions to invasive cancer. Previous studies have implicated somatic mutations in PIK3CA, PTEN, TP53, STK11 and KRAS as well as chromosome-arm level copy number alterations in the pathogenesis of cervical carcinomas. Here, we report whole exome sequencing analysis of 118 cervical carcinoma-normal paired samples from patients in Norway and Mexico, as well as transcriptome sequencing of 80 cases and whole genome sequencing of 13 tumor-normal pairs. Novel somatic mutations include recurrent E322K substitutions in the MAPK1 gene encoding the ERK2 kinase and inactivating mutations in the HLA-B gene. In addition, recurrent somatic mutations in FBXW7, EP300, and NFE2L2 are novel in the context of primary cervical carcinomas. Analysis of HPV integration sites revealed recurrent integration into the RAD51B locus as well as co-occurrence of HPV genome integration and copy number gains within several genomic loci. These findings shed new light on the pathogenesis of cervical carcinomas and suggest potential novel therapeutic targets.

  Study phs000600

• Identification of Targetable FGFR Gene Fusions in Diverse Cancers

  In this study, patients with advanced cancer across all histologies were enrolled in our IRB approved clinical sequencing program, called MI-ONCOSEQ, to go through an integrative sequencing which includes whole exome sequencing of the tumor and matched normal, and transcriptome sequencing. Four index cases were identified which harbor gene rearrangements of FGFR2 including two cholangiocarcinoma cases, a metastatic breast cancer case, and a metastatic prostate cancer case. After extending our assessment of FGFR rearrangements across multiple tumor cohorts, including TCGA, we identified FGFR gene fusions with intact kinase domains of FGFR1, FGFR2, or FGFR3 in cholangiocarcinoma, breast cancer, prostate cancer, lung squamous cell cancer, bladder cancer, thyroid cancer, oral cancer, glioblastoma, and head and neck squamous cell cancer. All FGFR fusion partners tested exhibit oligomerization capability, suggesting a shared mode of kinase activation. Overexpression of FGFR fusion proteins in vitro induced cell proliferation, and bladder cancer cell lines that harbors FGFR3 fusion proteins exhibited enhanced susceptibility to pharmacologic inhibition in vitro and in vivo. Due to the combinatorial possibilities of FGFR family fusion to a variety of oligomerization partners, clinical sequencing efforts which incorporate transcriptome analysis for gene fusions are poised to identify rare, targetable FGFR fusions across diverse cancer types.

  Study phs000602

• International Multi-Center ADHD Genetics Project

  The goal of the project is to complete a 600,000 tag SNP genome-wide association scan of 958 parent-child trios from the International Multisite ADHD Genetics (IMAGE) project, in order to assess the association of SNP markers with ADHD, analyze quantitative ADHD phenotypes, complete copy number analyses, assess parent of origin effects and season of birth effects, and test for epistasis among apparently uncorrelated genes. Acquiring DNA Samples All consent forms stipulate that the samples can only be used by researchers who have been approved by the National Institute of Mental Health (NIMH), National Institutes of Health. All consent forms, except those used at the Zürich site (N=141 subjects), explicitly indicate that the samples may be used by researchers from commercial enterprises seeking to benefit financially from the analysis of the samples. The Zürich consent does not prohibit such use. The Zürich consent form also included an "opt out" that allowed the subjects to indicate that they did not want their samples stored at the NIMH repository or used by researchers external to the project. No subjects enrolled in the project opted out. Consent groups and participant set ADHD (ADHD): 2758 (924 trios)

  Study phs000016

• Autism Post-Mortem Brain RNA-Sequencing: SRRM4 Splicing Study

  Purpose: The goal of this study was to assess the status of splicing changes in microexons in the cortex of individuals with autism. Methods: We performed RiboZero Gold (rRNA depleted) 50bp PE RNA-seq in a larger set of case and control samples to define 12 autism and 12 control samples showing the greatest global differential gene expression change. These samples, which show differential expression of the splicing regulator SRRM4, were used to evaluate global splicing changes. Results: Within these samples, 126 of 504 (30%) detected alternative microexons display, a mean ΔPSI > 10 between ASD and control subjects of which 113 (90%) also display neural-differential regulation. By contrast, only 825 of 15,405 (5.4%) longer (i.e. > 27 nt) exons show such misregulation, of which 285 (35%) correspond to neural-regulated exons. Notably, we also observe significantly higher correlations between microexon inclusion and nSR100 mRNA expression levels across the stratified ASD samples and controls, for those microexons regulated by nSR100 relative to those microexons that are not regulated by this factor (p=1.4x10-7, Wilcoxon Sum Rank test). Conclusions: These data suggest microexon regulation is a potentially important mechanism underlying ASD and likely other neurodevelopmental disorders.

  Study phs000872

• Sporadic Amyotrophic Lateral Sclerosis (ALS): Parent-Offspring and Twin Sequencing Study

  Amyotrophic Lateral Sclerosis (ALS) is a neurodegenerative disease that affects the nerves in the brain and spinal cord, leading to muscle weakening and eventual paralysis and death. Ten percent of ALS cases are thought to be familial while the majority of cases are sporadic and the causative factors unknown. Dr. Roger Pamphlett of the University of Sydney has collected a unique cohort of consented trios where the child has ALS but the parents are unaffected. Since the age of onset is so late, it is very difficult to obtain this kind of trio. We have performed whole exome sequencing on these trios to identify de novo and recessive germline variants associated with sporadic ALS. In addition, Dr. Pamphlett has assembled a collection of consented discordant monozygotic twins, where one twin has ALS and the other is unaffected. We performed whole genome sequencing on these twin pairs to identify postzygotic variants that may contribute to sporadic ALS susceptibility. Finally, we have the opportunity to compare the sequence and gene expression in affected and unaffected tissues from blood, brain and/or spinal cord samples from consented ALS patients to look for somatic mutations or gene expression changes that may further our understanding of the disease.

  Study phs000831

• NextGen Consortium: GENESiPS Study: Identifying the Gene Networks of Insulin Resistance

  Variability in induced pluripotent stem cell (iPSC) lines remains a roadblock for disease modeling and regenerative medicine. Through linear mixed models we have described different sources of gene expression variability from RNA sequencing data in 317 human iPSC lines from 101 individuals. We found that ~50% of genome-wide expression variability is explained by variation across individuals and identified a set of expression quantitative trait loci that contribute to this variation. These analyses coupled with allele specific expression show that iPSCs retain a subject-specific gene expression pattern. Pathway enrichment and key driver analyses, based on predictive causal gene networks, found that Polycomb targets explain a significant part of the non-genetic variability present in iPSCs within and across individuals. These publically available iPSC lines and genetic datasets will be a resource to the scientific community and will open new avenues to reduce variability in iPSCs and improve their utility in disease modeling. SNP array data from individuals included in RNA-seq transcriptome profiling study of human induced pluripotent stem cells to characterize gene expression variation across individuals and within multiple iPSC lines from the same individual. Genotyping was performed on patient blood. Data availability: SNP-genotyping: dbGaP - current study RNA-seq counts: GEO - GSE79636 FASTQ files: SRA - SRP072417

  Study phs001139