3613 results for "*geneti*"

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• Mapping genetic variants underlying gene regulation in healthy intestinal cell types to identify novel IBD drug targets (2020-05-12)

  Biopsies from the terminal ileum and rectum of healthy individuals are digested on ice to single cells and processed for single-cell RNA-sequencing (10X Genomics and Illumina) 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/ . This dataset contains all the data available for this study on 2020-05-12.

  Dataset EGAD00001006139

• Profiling heterogeneity in Human derived IPSC-neurons (2020-05-18)

  The impact of genetic variants on molecular pathways that give rise to neurodegenerative diseases such as Alzheimer's and Parkinson's is best elucidated in the appropriate cell types and molecular contexts. Existing studies have focused on bulk profiling of mixed cell types, but have ignored assaying genetic effects across development and cell differentiation. At the core of this proposal is the idea to use single-cell assays to study genetic effects during differentiation of dopaminergic and cortical neurons to identify the sequence of molecular events from variants to healthy and diseased cell states in a cell-specific manner. 1) 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 please see http://www.sanger.ac.uk/datasharing/ . This dataset contains all the data available for this study on 2020-05-18.

  Dataset EGAD00001006157

• Hereditary Cancer Diagnostics with I2HCP gene panel

  Germline blood DNA sequencing data generated in routine diagnostics of hereditary cancer using the I2HCP gene panel (~135 genes). There are 130 samples sequenced in a MiSeq machine and 108 sequenced in a HiSeq machine. There is a partial overlap between those two sets, meaning that some samples were sequenced in both machines. There is a strong enrichment in samples with copy-number variants (CNV), both single- and multi-exon, since this dataset was compiled for a benchmarking effort of CNV calling tools for genetic diagnostics.

  Dataset EGAD00001006171

• Modulation of macrophage inflammatory function through selective inhibition of the epigenetic reader protein SP140

  Transcriptomic (N = 18) and epigenomic (N = 6) characterization of macrophages using RNA-sequencing and ChIP-sequencing (bait = SP140) in the presence of absence of SP140 inhibition.

  Dataset EGAD00001006186

• Competitive selection of somatic mutant clones in normal human skin varies with body site

  The risk of getting non-melanoma skin cancer varies over 40-fold across the body. Here we map mutations in normal skin in high and low risk sites in normal donors and those with an increased risk of skin cancer. The density of mutations varied widely, with evidence of positive and negative genetic selection.  Regional differences in mutational signatures in high and low cancer risk sites and preferential selection of mutants of TP53 in high risk skin and FAT1 in lower risk skin were observed. 10% of clones had copy number changes in cancer associated genes and the largest had multiple driver mutations with loss of heterozygosity. In hair follicles, a proposed site of origin of skin cancers, mutations in the upper follicle resembled adjacent skin, but the lower follicle was sparsely mutated. We conclude cancer risk reflects the efficiency of transformation of oncogenic mutants rather than the density of mutant clones.

  Dataset EGAD00001006194

• MassArray1-80

  234 samples genotyped at 40 loci using the MassArrayiPLEX genotyping assay using the iPLEX Gold genotyping kit (Agena Biosciences, cat. 10148-2) Gabriel et al. (2009) [Gabriel, S. , Ziaugra, L. and Tabbaa, D. (2009), SNP Genotyping Using the Sequenom MassARRAY iPLEX Platform. Current Protocols in Human Genetics, 60: 2.12.1-2.12.18. doi:10.1002/0471142905.hg0212s60]). Products were detected on a MassArray mass spectrophotometer and data were acquired in real time with MassArray RT software 4.0.0.2 (Agena Biosciences). SNP clustering and validation was carried out with Typer 4.0.26.75 software (Agena Biosciences).

  Dataset EGAD00010001906

• February 2020 data update (fastq) for reference epigenomes generated at Centre for Epigenome Mapping Technologies, Genome Sciences Center, B.C. Cancer Agency as part of the International Human Epigenome Consortium.

  February 2020 data update (fastq) for reference epigenomes generated at Centre for Epigenome Mapping Technologies (Canadian Epigenetics, Environment and Health Research Consortium), Genome Sciences Center, B.C. Cancer Agency, Vancouver, Canada as part of the International Human Epigenome Consortium.

  Dataset EGAD00001006220

• Analysis File for 87 Argentinean individuals

  VCF for 87 Argentinean samples. Only SNPs (no indels) that passed the Affymetrix QC. Data from Luisi et al. 2020. Plos One. Fine-Scale Genomic Analyses Of Admixed Individuals Reveal Unrecognized Genetic Ancestry Components In Argentina. Reference Allele column does NOT contain reference allele from genome assembly.

  Dataset EGAD00001006227

• RNA-Sequencing and Somatic Mutation Status of Adrenocortical Tumors: Novel Pathogenetic Insights

  RNA paired end sequencing of 59 adrenocortical tumors and 4 controls.

  Dataset EGAD00001006258

• Martin_Ravenscroft-AUS1

  Whole genome sequencing data on D19-0702 (AUS1), presented in Martin et al. 2020 (AUS1). WGS (Illumina HiSeq) was performed at Kinghorn Centre for Clinical Genetics, Garvan Institute of Medical Research. Data was analyzed using the Seave bioinformatic analysis pipeline (https://www.seave.bio).

  Dataset EGAD00001006276

• Epigenetic subtypes of neuroblastoma - ChIPseq

  In the absence of recurrent gene mutations, evidence accumulates that epigenetic deregulation plays a prominent role in neuroblastoma biology. Here we provide genome wide H3K27ac profiles in 60 primary neuroblastoma samples.

  Dataset EGAD00001006285

• Epigenetic subtypes of neuroblastoma - RNAseq

  In the absence of recurrent gene mutations, evidence accumulates that epigenetic deregulation plays a prominent role in neuroblastoma biology. Here we provide RNAseq profiles in 71 primary and relapse neuroblastoma samples.

  Dataset EGAD00001006286

• Survival Benefit and Genetic Profile of Pemetrexed as Initial Chemotherapy in Selected Chinese Patients with Advanced Lung Adenocarcinoma

  NGS data of 12 patients enrolled in the Chinese Patient Assistance Program from multiple centers who received pemetrexed alone or combined with platinum as initial chemotherapy and continued pemetrexed maintenance therapy for advanced lung adenocarcinoma from November 2014 to June 2017.

  Dataset EGAD00001006287

• Somatic mutations and single cell transcriptomes reveal the root of malignant rhabdoid tumours

  Like many childhood cancers, malignant rhabdoid tumours (MRT) are thought to arise from aberrant foetal development. Although MRT predominantly exhibit a mesenchymal phenotype, it has been suggested that the foetal root of MRT lies in neural crest development. Here, we combine phylogenetic analyses of MRT, single cell mRNA assays, and functional experiments in patient-derived MRT organoids, to define the embryological origin of MRT and explore therapeutic avenues that may drive MRT differentiation. Phylogenetic analyses from the distribution of somatic mutations revealed that MRT were related to neural crest-derived, but not to mesodermal tissues, providing direct evidence of the neural crest origin of MRT in humans. In MRT organoids, reversal of the principal driver event underpinning MRT, SMARCB1 loss, induced differentiation along mesenchymal pathways. Together, these findings placed MRT cells on a developmental trajectory of neural crest to mesenchyme conversion, and defined the transcriptional changes underpinning MRT differentiation. Searching perturbation databases for agents that mimic these mRNA changes, we identified HDAC and mTOR inhibition as potential differentiation agents. Treatment of MRT organoids with this drug combination induced proliferation arrest with transcriptional changes akin to SMARCB1 re-expression. Our study defines the embryological root of MRT and proposes a differentiation treatment for this often fatal childhood cancer.

  Dataset EGAD00001006296

• The Transcriptional Landscape of SHH Medulloblastoma

  To further understand the biology of Sonic hedgehog medulloblastoma and its molecular subtypes, we studied 250 human Shh-MB using strand-specific RNA sequencing. We identified novel alterations within the cAMP dependent pathway and found that 18% of tumors have genetic events that directly target the abundance and/or stability of MYCN. We also discovered an extensive network of fusions in focally amplified regions, and several loss-of-function fusions in tumor suppressor genes PTCH, SUFU and NCOR1. Molecular convergence on a core of specific genes by nucleotide variants, copy number aberrations, and gene fusions highlights key roles of specific pathways in the pathogenesis of Sonic hedgehog medulloblastoma.

  Dataset EGAD00001006305

• Whole genome sequencing of Xeroderma Pigmentosum leukemias samples

  In the current study we report for the first time the unique collection of 6 leukemias and two sarcomas from XP-C. Comprehensive WGS-based mutational analysis provides genetic explanation for the increased incidence of leukemia in XP-C and describes an unique mutational process in internal tumors associated with NER deficiency. Raw data are provided in FASTQ format and variant analysis as VCF files.

  Dataset EGAD00001006322

• Mapping genetic variants underlying gene regulation in healthy intestinal cell types to identify novel IBD drug targets

  Biopsies from the terminal ileum and rectum of healthy individuals are digested on ice to single cells and processed for single-cell RNA-sequencing (10X Genomics and Illumina) 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 EGAD00001006331

• Somatic mutations reveal embryonic genetic bottlenecks generating placental mosaicism

  The human placenta harbours chromosomal aberrations that are absent from the fetus in one to two percent of pregnancies. This confined mosaicism suggests that embryonic genetic bottlenecks exist, which phylogenetically segregate placental tissue. Here, we studied the somatic genetic landscape of human placentas by whole genome sequencing of 86 placental biopsies and of 106 microdissections.

  Dataset EGAD00001006337

• Genomic characterisation of MGUS

  The hematological malignancy multiple myeloma (MM), also called Kahler's disease or plasma cell (PC) myeloma, is characterized by a clonal expansion of PCs originating in the bone marrow (BM). The expansion of these cells leads to an overproduction of antibodies and results in typical symptoms such as anemia, renal failure and bone lesions. All cases of MM are preceded by the asymptomatic, non-malignant pre-stage monoclonal gammopathy of undetermined significance (MGUS). Of all MGUS patients, only 1% per year will progress to MM. Despite efforts to elucidate the molecular mechanisms underlying the MGUS-to-MM progression, its pathogenesis still remains largely unknown. Additionally, the genetic profiles of MGUS patients have only been limitedly investigated due to the only incidental finding of MGUS, the difficulties in BM sampling and isolating a sufficient number of aberrant PCs from the BM aspirates of MGUS patients. Consequently, reliable biomarkers to individually predict which MGUS patients will progress to MM and which will not, are lacking. Therefore, it is highly required to study the molecular pathogenesis of MGUS and the role of genetic events in relation to the malignant transformation to MM.

  Dataset EGAD00001006363

• August 2020 data update (fastq) for reference epigenomes generated at Centre for Epigenome Mapping Technologies, Genome Sciences Center, B.C. Cancer Agency as part of the International Human Epigenome Consortium.

  August 2020 data update (fastq) for reference epigenomes generated at Centre for Epigenome Mapping Technologies (Canadian Epigenetics, Environment and Health Research Consortium), Genome Sciences Center, B.C. Cancer Agency, Vancouver, Canada as part of the International Human Epigenome Consortium.

  Dataset EGAD00001006383

• Genetic and transcriptomic landscape of DLBCL

  Affymetrix SNP6.0 data for 341 DLBCL patients

  Dataset EGAD00010001980

• Pre-clinical evolution of haematological malignancies_WGS

  Leukaemia and related blood cancers occur due to genetic changes that typically accumulate over many years. This study will employ targeted next-generation sequencing to retrace the preclinical evolution of several types of haematological malignancy. Investigating the progression of the earliest pre-malignant ancestral clones promises to offer valuable insights into early leukaemia evolution and therapeutic vulnerabilities of leukaemia stem cells.

  Dataset EGAD00001006423

• Pre-clinical evolution of haematological malignancies_TGS

  Leukaemia and related blood cancers occur due to genetic changes that typically accumulate over many years. This study will employ targeted next-generation sequencing to retrace the preclinical evolution of several types of haematological malignancy. Investigating the progression of the earliest pre-malignant ancestral clones promises to offer valuable insights into early leukaemia evolution and therapeutic vulnerabilities of leukaemia stem cells.

  Dataset EGAD00001006424

• Whole genome sequencing of retinoblastoma reveals the diversity of rearrangements disrupting RB1 and uncovers a treatment related mutational signature

  Background: The development of retinoblastoma is thought to require pathological genetic changes in both alleles of the RB1 gene. However, cases exist where RB1 mutations are undetectable suggesting alternative pathways to malignancy. Methods: We applied comprehensive whole genome sequencing (WGS) and transcriptomics to sporadic retinoblastomas derived from twenty patients attending our clinic, contrasting these results to that obtained through customary clinical testing. We sought RB1 and other driver mutations, investigated mutation burden, mutational signatures and phylogenetic relatedness in one case of bilateral retinoblastoma. Results: At least one RB1 mutation was identified in all retinoblastomas. We confirmed RB1 mutations previously identified by clinical screening, identified three new RB1 mutations and provided clarity to the mechanism behind a further six mutations. Eight tumours carried structural rearrangements involving RB1 ranging from relatively simple to extremely complex rearrangement patterns, including a chromothripsis-like pattern in one tumour. Potential driver mutations included mutations in BCOR (5/20) and amplification of MYCN (2/20) and MDM4 (1/20). We show that RB1 mutations are not mutually exclusive of MYCN amplifications, and further reveal that all tumours demonstrate increased MYCN expression suggesting a universal role in retinoblastoma tumorigenesis.  Bilateral tumours obtained from one patient harboured conserved germline but divergent somatic RB1 mutations, indicating independent evolution. In-keeping with previous WGS of paediatric cancers, the mutation burden in retinoblastomas was extremely low. Mutational signature analysis showed a predominance of signatures associated with cell division and an absence of ultraviolet-related DNA damage. In a tumour exposed to chemotherapy prior to enucleation, a profound platinum-related mutational signature was observed. Conclusions: WGS provides a complete picture of the genomic landscape of retinoblastomas, allowing the discovery of mutations otherwise undetected by conventional clinical screening approaches. The presence of at least one RB1 mutation in all retinoblastomas and the relative paucity of driver mutations in other genes suggests mutations beyond RB1, MYCN and BCOR are rare. Whilst most RB1 mutations are identifiable by clinical screening, the increased resolution and ability to detect otherwise elusive rearrangements of RB1 by WGS, confirming whether they are somatic or germline, has important repercussions on clinical management and advice on recurrence risks.

  Dataset EGAD00001006431

• The transition from quiescent to activated states in human hematopoietic stem cells is governed by dynamic 3D genome reorganization

  To elucidate the epigenetic changes which occur when human long-term hematopoietic stem cells (LT-HSC) become activated we performed Bulk ATAC-Seq on 13 sorted bulk hematopoietic populations from cord bloodas well as single-cell ATAC-Seq upon CD34+CD38-CD45RA- cells enriched for HSC as well as CD34+/CD38+ progenitor cells both from cord blood. These studies revealed gains of chromatin accessibility around CTCF binding sites during HSPC activation, as such we additionally performed Low-C to directly profile the 3D conformation of human cord-blood derived LT-HSC and Short-term hematopoietic stem cells (ST-HSC), as well as Hi-C , ATAC-Seq and CTCF ChIP-Seq upon the OCIAML-2 cell line in which CTCF sites gained during LT-HSC activation are enriched. Finally we transduced human cord-blood LT-HSC with an shCTCF vector; in-vitro cultured LT-HSC cells harbouring shCTCF were used to perform RNA-Seq, and scATAC-Seq was performed on CD34+/CD38- human CB cells transduced with shCTCF, four weeks post xeno-transplantation into mice. Collectively these studies have helped us demonstrate the role of 3D chromatin conformation changes during human LT-HSC activation.

  Dataset EGAD00001006447

• Paired-WGS-two-families-with-GBA-variants-and-Parkinsons-disease

  We performed whole- genome sequencing, rare variant filtering, segregation analysis and functional validation of PD cosegregating rare genetic variation in two families (6 samples) segregating PD associated GBA variants c.115+1G>A (ClinVar ID: 93445, ) and p.L444P (ClinVar ID: 4288) respectively. The paired WGS sequencing was run on HiSeq X Ten and the library preparation kit was Illumina TruSeq DNA nano.

  Dataset EGAD00001006561

• Cell of Origin and Early Evolution of Leukemia in Down Syndrome

  To investigate the mechanism by which GATA1s and STAG2 deficiency contribute to Down Syndrome leukemogenesis, specifically within the propagating CD34/CD117 cell fractions from primary xenografts, we carried out transcriptional and epigenetic profiling by RNAseq and ATACseq. The chromatin accessibility landscape was compared to bulk ATACseq of individually sorted N-FL HSPC subpopulations. To investigate the mechanism underlying the synergy between T21 and GATA1s in driving preleukemia development, we analyzed the binding occupancy of GATA1. We performed Cut&Run assays to profile genome-wide GATA1 binding sites and also to quantify binding changes upon GATA1s editing in N-FL and T21-FL CD34+ enriched HSPCs. Lastly, we profiled miRNAs from N-FL and T21-FL CD34+ enriched HSPCs by miRNA-Seq.

  Dataset EGAD00001006555

• Measurable residual disease in elderly acute myeloid leukemia: results from the PETHEMA-FLUGAZA phase III clinical trial

  In our study, we hypothetyzed that CD34progenitors from cases with undetectable Minimal residual Disease (MRD) by flow cytometry would contain cells with leukemic-initiating-potential that could be identified on genetic (rather than phenotypic) grounds by Whole Exome Sequencing.

  Dataset EGAD00001006585

• The genetic structure of Norway

  The genetic structure of Norway

  Dataset EGAD00010002032

• The mutational landscape of human somatic and germline cells

  During the course of a lifetime normal human cells accumulate mutations. Here, using multiple samples from the same individuals we compared the mutational landscape in 29 anatomical structures from soma and the germline. Two ubiquitous mutational signatures, SBS1 and SBS5/40, accounted for the majority of acquired mutations in most cell types but their absolute and relative contributions varied substantially. SBS18, potentially reflecting oxidative damage, and several additional signatures attributed to exogenous and endogenous exposures contributed mutations to subsets of cell types. The mutation rate was lowest in spermatogonia, the stem cell from which sperm are generated and from which most genetic variation in the human population is thought to originate. This was due to low rates of ubiquitous mutation processes and may be partially attributable to a low cell division rate of basal spermatogonia. The results provide important insights into how mutational processes affect the soma and germline.

  Dataset EGAD00001006641

• The mutational landscape of human somatic and germline cells

  During the course of a lifetime normal human cells accumulate mutations. Here, using multiple samples from the same individuals we compared the mutational landscape in 29 anatomical structures from soma and the germline. Two ubiquitous mutational signatures, SBS1 and SBS5/40, accounted for the majority of acquired mutations in most cell types but their absolute and relative contributions varied substantially. SBS18, potentially reflecting oxidative damage, and several additional signatures attributed to exogenous and endogenous exposures contributed mutations to subsets of cell types. The mutation rate was lowest in spermatogonia, the stem cell from which sperm are generated and from which most genetic variation in the human population is thought to originate. This was due to low rates of ubiquitous mutation processes and may be partially attributable to a low cell division rate of basal spermatogonia. The results provide important insights into how mutational processes affect the soma and germline.

  Dataset EGAD00001006642

• The mutational landscape of human somatic and germline cells

  During the course of a lifetime normal human cells accumulate mutations. Here, using multiple samples from the same individuals we compared the mutational landscape in 29 anatomical structures from soma and the germline. Two ubiquitous mutational signatures, SBS1 and SBS5/40, accounted for the majority of acquired mutations in most cell types but their absolute and relative contributions varied substantially. SBS18, potentially reflecting oxidative damage, and several additional signatures attributed to exogenous and endogenous exposures contributed mutations to subsets of cell types. The mutation rate was lowest in spermatogonia, the stem cell from which sperm are generated and from which most genetic variation in the human population is thought to originate. This was due to low rates of ubiquitous mutation processes and may be partially attributable to a low cell division rate of basal spermatogonia. The results provide important insights into how mutational processes affect the soma and germline.

  Dataset EGAD00001006643

• 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 EGAD00001006648

• 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

• Expression profiles and genetic makeup of agnospheres.

  WES performed on 15 CUP-derived samples

  Dataset EGAD00001006668

• CINECA_synthetic_cohort_EUROPE_UK1 referencing fake samples

  Please note: This synthetic data set (with cohort “participants” / ”subjects” marked with FAKE) has no identifiable data and cannot be used to make any inference about cohort data or results. The purpose of this dataset is to aid development of technical implementations for cohort data discovery, harmonization, access, and federated analysis. In support of FAIRness in data sharing, this dataset is made freely available under the Creative Commons Licence (CC-BY). Please ensure this preamble is included with this dataset and that the CINECA project (funding: EC H2020 grant 825775) is acknowledged. For any questions please contact isuru@ebi.ac.uk or cthomas@ebi.ac.uk This dataset (CINECA_synthetic_cohort_EUROPE_UK1) consists of 2521 samples which have genetic data based on 1000 Genomes data (https://www.nature.com/articles/nature15393), and synthetic subject attributes and phenotypic data derived from UKBiobank (https://journals.plos.org/plosmedicine/article?id=10.1371/journal.pmed.1001779). These data were initially derived using the TOFU tool (https://github.com/spiros/tofu), which generates randomly generated values based on the UKBiobank data dictionary. Categorical values were randomly generated based on the data dictionary, continuous variables generated based on the distribution of values reported by the UK Biobank showcase, and date / time values were random. Additionally we split the phenotypes and attributes into 4 main classes - general, cancer, diabetes mellitus, and cardiac. We assigned the general attributes to all the samples, and the cardiac / diabetes mellitus / cancer attributes to a proportion of the total samples. Once the initial set of phenotypes and attributes were generated, the data data was checked for consistency and where possible dependent attributes were calculated from the independent variables generated by TOFU. For example, BMI was calculated from height and weight data, and age at death generated by date of death and date of birth. These data were then loaded to the development instance of Biosamples (https://www.ebi.ac.uk/biosamples/) which accessioned each of the samples. The genetic data are derived from the 1000 Genomes Phase 3 release (https://www.internationalgenome.org/category/phase-3/). The genotype data consists of a single joint call vcf files with call genotypes for all 2504 samples, plus bed, bim, fam, and nosex files generated via plink for these samples and genotypes. The genotype data has had a variety of errors introduced to mimic real data and as a test for quality control pipelines. These include gender mismatches, ethnic background mislabelling and low call rates for a randomly chosen subset of sample data as well as deviations from Hardy Weinberg equilibrium and low call rates for a random selection of variants. Additionally 40 samples have raw genetic data available in the form of both bam and cram files, including unmapped data. The gender of the samples in the 1000 genomes data has been matched to the synthetic phenotypic data generated for these samples. The genetic data was then linked to the synthetic data in BioSamples, and submitted to EGA.

  Dataset EGAD00001006673

• An Integrated Approach to Patient Stratification and Therapy Selection in Acute Myeloid Leukemia

  As more clinically-relevant genomic features of myeloid malignancies are revealed, it has become clear that targeted clinical genetic testing is inadequate for risk stratification. Here, we developed and validated a clinical transcriptome-based assay for stratification of acute myeloid leukemia (AML). Comparison of RNA-Seq to whole genome and exome sequencing revealed that as a standalone assay, RNA-Seq offered the greatest diagnostic return, enabling identification of expressed gene fusions, single nucleotide and short insertion/deletion variants, and whole-transcriptome expression information. Expression data were used to develop a novel risk score which, when combined with molecular risk guidelines, allowed for the re-stratification of 22.1 to 25.3% of AML patients from three independent cohorts into correct risk groups. Within the adverse-risk subgroup, we identified a subset of patients characterized by dysregulated integrin signaling and RUNX1 or TP53 mutation. We show that these patients may benefit from therapy with inhibitors of focal adhesion kinase (PTK2), demonstrating additional utility of transcriptome-based testing for therapy selection in myeloid malignancy.

  Dataset EGAD00001006701

• Resequencing candidate genes for male spermatogenic impairment

  This study aims to identify novel candidate variants from human Y-chromosomal genes DAZ, BPY2 and CDY1/2 by resequencing the coding regions of these genes from male patients with spermatogenic impairment. The coding regions of the genes plus a selection of phylogenetically informative Y-chromosomal markers have been amplified by standard PCR, amplicon lengths range from 178 to 486 bp. Amplicons were quantified by gel electrophoresis and pooled in approx. equimolar concentrations per patient. For each of the 480 submitted samples, approx. 1 microgram of amplified DNA pool was provided in a total volume of 120 microlitres. The samples were indexed and libraries prepared for PE250bp Illumina MiSeq runs. 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 EGAD00001006784

• Whole Exome sequencing data from Shwachman-Diamond syndrome bone marrow samples

  This dataset includes paired WES from bone marrow samples of patients with SDS and paired bone marrow-derived fibroblasts as a germline reference. Some patients have multiple samples collected serially over time. There are 74 BAM files included in this dataset.

  Dataset EGAD00001006815

• Fine-mapping clustered GWAS hits enhances the identification of disease risk and protective genetic variants

  This dataset contains: 1) Raw FASTQ and BAM files for short reads. Here, DNA libraries were prepared using Nextera Rapid Capture Custom Enrichment kit (Illumina) and paired-end sequenced on a HiSeq2500 (Illumina). 2) Raw FASTQ and BAM files for long reads. Here, DNA libraries were prepared using 1D DNA ligation Sequencing Kit (SQK-LSK109, Oxford Nanopore) and single-end sequenced on a MinION device (Oxford Nanopore).

  Dataset EGAD00001006916

• MutWP4: CRUK Grand Challenge Mutographs of Cancer: Pancreatic Organoids (2021-02-02)

  The Mutographs project aims to advance our understanding of the causes of cancer through studies of mutational signatures. Led by Mike Stratton, together with Paul Brennan, Ludmil Alexandrov, Allan Balmain, David Phillips and Peter Campbell, this large-scale international research endeavour was awarded a Cancer Research UK Grand Challenge. Different patterns of somatic mutation are generated by the different environmental, lifestyle and genetic factors that cause cancer, many of them are still unknown. Within Mutographs, Kings College London will characterise the mutational signatures induced by putative human carcinogens in order to identify the origins of mutational signatures found in human cancers. To achieve this human organoid cell cultures will be exposed to a representative catalogue of known or suspected human carcinogens and mutagens and, using whole genome sequencing, the patterns of mutations induced by them will be determined. Somatic mutational signatures will be subsequently extracted by non-negative matrix factorisation methods and correlated with exposure data. Through an enhanced understanding of cancer aetiology, Mutographs unprecedented effort is anticipated to outline modifiable risk factors, lead to new approaches to prevent cancer, and provide opportunities to empower early detection, refine high-risk groups and contribute to further therapeutic development. . This dataset contains all the data available for this study on 2021-02-02.

  Dataset EGAD00001006933

• Dedifferentiated Melanoma (2021-02-02)

  De- and transdifferentiation of melanoma is a rare histopathological phenomenon that has not be characterised genetically. In this project we plan to sequence the genomes of de and transdifferentiated cases so as to define their genetic make-up. . This dataset contains all the data available for this study on 2021-02-02.

  Dataset EGAD00001006931

• STAT1 AM RNAseq

  The transcriptome of peripheral blood cells (PBMCs) from control or patients with an activation mutation on the STAT1 gene was analyzed. This analysis aimed to identify the major changes in the circulating immune cells of patients with STAT1 mutation and compare this with the result of the perturbation prediction tool huva (human variation, R).

  Dataset EGAD00001006962

• NIHR BioResource Common Disease Patients 2016

  NIHR BioResource Common Disease Patients 2016. The dataset includes 13489 samples from blood donors, they were not screened for any particular disease, and therefore they are representative of the general population. Genomic data includes 845487 snps collected using the UK BioBank V1 Affymetrix array. Phenotypic data includes gender, age, ethnicity and disease. According to our internal quality check there are 81 duplicates in this dataset.

  Dataset EGAD00010002059

• Genome Diversity in Africa Project: Benin (2021-02-16)

  Globally, human populations show structured genetic diversity as a result of geographical dispersion, selection and drift. Understanding this genetic variation can provide insights into the evolutionary processes that shape both human adaptation and variation in disease. Populations from SSA have the highest levels of genetic diversity. This characteristic, in addition to historical genetic admixture, can lead to complexities in the design of studies assessing the genetic determinants of disease and human variation. However, such studies of African populations are also likely to provide new opportunities to discover novel disease susceptibility loci and variants and refine gene-disease association signals. A systematic assessment of genetic diversity within SSA would facilitate genomic epidemiological studies in the region. The Genome Diversity in Africa Project (GDAP) aims to produce a comprehensive catalogue of human genetic variation in SSA, including single nucleotide polymorphisms (SNPs), structural variants, and haplotypes. This resource will make a substantial contribution to understanding patterns of genetic diversity within and among populations in SSA, as well as providing a global resource to help design, implement and interpret genomic studies in SSA populations and studies comprising globally diverse populations, complementing existing genomic resources. Specifically, we plan to carry out high depth whole genome sequencing of up to 2000 individuals across Africa (25 individuals from each ethnolinguistic group). Our scientific objectives are to: 1) develop a resource that provides a comprehensive catalogue of genetic variation in populations from SSA accessible to the global scientific community; 2) characterise population genetic diversity, structure, gene flow and admixture across SSA; 3) develop a cost-efficient, next-generation genotype array for diverse populations across SSA; and 4) facilitate whole genome-sequencing association studies of complex traits and diseases by developing a reference panel for imputation and resource for enhancing fine-mapping disease susceptibility loci. These scientific objectives will be supported by cross-cutting operational activities, including network and management of the consortium, research ethics, and research capacity building in statistical genetics and bioinformatics 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/ . This dataset contains all the data available for this study on 2021-02-16.

  Dataset EGAD00001006970

• Genome Diversity in Africa Project: Uganda (2021-02-17)

  Globally, human populations show structured genetic diversity as a result of geographical dispersion, selection and drift. Understanding this genetic variation can provide insights into the evolutionary processes that shape both human adaptation and variation in disease. Populations from SSA have the highest levels of genetic diversity. This characteristic, in addition to historical genetic admixture, can lead to complexities in the design of studies assessing the genetic determinants of disease and human variation. However, such studies of African populations are also likely to provide new opportunities to discover novel disease susceptibility loci and variants and refine gene-disease association signals. A systematic assessment of genetic diversity within SSA would facilitate genomic epidemiological studies in the region. The Genome Diversity in Africa Project (GDAP) aims to produce a comprehensive catalogue of human genetic variation in SSA, including single nucleotide polymorphisms (SNPs), structural variants, and haplotypes. This resource will make a substantial contribution to understanding patterns of genetic diversity within and among populations in SSA, as well as providing a global resource to help design, implement and interpret genomic studies in SSA populations and studies comprising globally diverse populations, complementing existing genomic resources. Specifically, we plan to carry out high depth whole genome sequencing of up to 2000 individuals across Africa (25 individuals from each ethnolinguistic group). Our scientific objectives are to: 1) develop a resource that provides a comprehensive catalogue of genetic variation in populations from SSA accessible to the global scientific community; 2) characterise population genetic diversity, structure, gene flow and admixture across SSA; 3) develop a cost-efficient, next-generation genotype array for diverse populations across SSA; and 4) facilitate whole genome-sequencing association studies of complex traits and diseases by developing a reference panel for imputation and resource for enhancing fine-mapping disease susceptibility loci. These scientific objectives will be supported by cross-cutting operational activities, including network and management of the consortium, research ethics, and research capacity building in statistical genetics and bioinformatics . This dataset contains all the data available for this study on 2021-02-17.

  Dataset EGAD00001006976

• KuwaitPopGenetics

  Genome-wide Genotyping of 620 Arab individuals using Illumina iSelect platform with HumanOmniExpress bead chips

  Dataset EGAD00010002063

• Genetic landscape of inherited retinal dystrophies

  In the context of research, this dataset contains 423 IRD samples; 411 of them analyzed with Clinical Exome Sequencing solutions, and 12 with Whole Exome Sequencing.

  Dataset EGAD00001007022

• Fetal origins of malignant germ cell tumours

  Germ cell tumours (GCTs) are a collection of benign and malignant neoplasms derived from primordial germ cells (PGCs). They are uniquely able to generate embryonic and extraembryonic tissues, which in malignant GCTs carries prognostic and therapeutic significance. The developmental pathways underpinning GCT initiation and histogenesis are incompletely understood. Here, we studied the phylogenetic and transcriptional diversity of 15 malignant gonadal GCTs and four normal testis biopsies by sequencing 131 whole genomes and 416 transcriptomes from 14 gonadal histologies, excised by laser capture microdissection. Our findings demonstrate that tumours were initiated by whole genome duplication likely in embryogenesis, within ~5-8 cell divisions post-PGC specification, followed by chromosome 12p gains associated with invasive disease. Of note, 12p imbalances were not only generated through GCT-typical isochromosomes, but also through non-isochromosomic configurations. Whilst tumours developed along homogenous phylogenetic pathways, they spawned manifold tissues independent of genetic subclonal diversification. A key feature of GCT tissues was the expression of fetal-specific genes. The transcriptional diversity notwithstanding, we found universal transcriptional elements correlated with hallmark 12p gains. Overall, our study reveals stereotyped phylogenies and transcriptomes underpinning the development of GCT that originate in fetal life and may lend themselves to therapeutic manipulation.

  Dataset EGAD00001007037

• Fetal origins of malignant germ cell tumours

  Germ cell tumours (GCTs) are a collection of benign and malignant neoplasms derived from primordial germ cells (PGCs). They are uniquely able to generate embryonic and extraembryonic tissues, which in malignant GCTs carries prognostic and therapeutic significance. The developmental pathways underpinning GCT initiation and histogenesis are incompletely understood. Here, we studied the phylogenetic and transcriptional diversity of 15 malignant gonadal GCTs and four normal testis biopsies by sequencing 131 whole genomes and 416 transcriptomes from 14 gonadal histologies, excised by laser capture microdissection. Our findings demonstrate that tumours were initiated by whole genome duplication likely in embryogenesis, within ~5-8 cell divisions post-PGC specification, followed by chromosome 12p gains associated with invasive disease. Of note, 12p imbalances were not only generated through GCT-typical isochromosomes, but also through non-isochromosomic configurations. Whilst tumours developed along homogenous phylogenetic pathways, they spawned manifold tissues independent of genetic subclonal diversification. A key feature of GCT tissues was the expression of fetal-specific genes. The transcriptional diversity notwithstanding, we found universal transcriptional elements correlated with hallmark 12p gains. Overall, our study reveals stereotyped phylogenies and transcriptomes underpinning the development of GCT that originate in fetal life and may lend themselves to therapeutic manipulation.

  Dataset EGAD00001007038