3311 results for "*geneti*"

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• The sanger result of LAM disease

  Tumor biopsies from LAM disease were analyzed by sanger to characterize the alterations in patients ,to elucidate the landscape of genetic/genomic alterations. The dataset include 21 samples.

  Dataset EGAD00010001761

• Preeclampsia InterPregGen Consortium: Whole Genome Sequencing of 100 unrelated Uzbeks (DNA samples from the Institute of Immunology, Uzbek Academy of Sciences, Tashkent, Uzbekistan; Republic Specialized Scientific Practical Medical Centre of Obstetrics and Gynecology, Tashkent, Uzbekistan)

  Whole genome sequencing of 100 unrelated Uzbeks in order to impute genotypes into PE cases and controls from Uzbekistan and to provide genetic data and infrastructure for future genetic studies in Uzbekistan and Central Asia more generally and to fill a gap in worldwide information as Central Asia is not adequately represented in available genomic data. This dataset is one component of the InterPregGen FP7 project. DNA samples for this component were collected by InterPregGen Consortium collaborators in Tashkent, Uzbekistan at the Institute of Immunology, Uzbek Academy of Sciences and at the Republic Specialized Scientific Practical Medical Centre of Obstetrics and Gynecology.

  Dataset EGAD00001005466

• Preeclampsia InterPregGen Consortium: Whole Genome Sequencing of 100 unrelated Kazakhs (DNA samples from the Scientific Center of Obstetrics, Gynecology and Perinatology, Almaty, Kazakhstan; Gulnara Svyatova, Principal Investigator

  Whole genome sequencing of 100 unrelated Kazakhs in order to impute genotypes into PE cases and controls from Kazakhstan and to provide genetic data and infrastructure for future genetic studies in Kazakhstan and Central Asia more generally and to fill a gap in worldwide information as Central Asia is not adequately represented in available genomic data. This dataset is one component of the InterPregGen FP7 project. DNA samples for this component were collected by InterPregGen Consortium collaborators at the Scientific Center of Obstetrics, Gynecology and Perinatology, Almaty, Kazakhstan (Gulnara Svyatova, Principal Investigator)

  Dataset EGAD00001005467

• Exome Sequencing of Spanish Patients with rare genetic diseases.

  Whole Exome sequencing of a set of Spanish patients suffering rare genetic diseases. The set consists of 3 patients, two were diagnosed with Aniridia (ANI-0006 and ANI-0023) and another one was diagnosed with Retinitis Pigmentosa (RP-0247).

  Dataset EGAD00001005498

• Mapping the breast cancer metastatic cascade onto circulating tumour DNA using genetic and epigenetic clonal tracking

  Dataset EGAD00001005507

• Single Cell RNAseq at various stages of HiPSCs differentiating toward definitive endoderm and endoderm derived lineages

  When comparing the differentiation capacities of pluripotent stem cell lines that have different genetic backgrounds, batch to batch experimental variablility poses a significant challenge, especially when trying to identify smaller effects. One way to address this issue is to differentiate several different lines in the same culture dish, thereby elimating experimental variation. In addition, it allows researchers to analyze many more lines with less experiments. Parallel single cell RNA-Seq exploits that individual cells are tagged and hence each cell can be reliably assigned to the donor of origin based on the genetic variants it contains. In addition, analyzing the genetic signature of single cells within a differentiating population can reveal differentation stages that are not easily detected in bulk RNAseq data. 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 EGAD00001005741

• Whole Exome Sequencing of Spanish Patients diagnosed with rare ophtalmogenetic disorders.

  Whole Exome sequencing of a set of Spanish patients suffering rare genetic diseases. The set consists of 4 patients, one was diagnosed with Retinitis Pigmentosa (RP-1629), another one was diagnosed with Macular Dystrophy (MD-0235) and two were diagnosed with Leber's Congenital Amaurosis (LCA-0081 and LCA-0103).

  Dataset EGAD00001005746

• RNA-seq study of longitudinal blood cell samples drawn from children at risk of type 1 diabetes

  The appearance of type 1 diabetes (T1D)-associated autoantibodies is the first and only measurable parameter to predict progression toward T1D in genetically susceptible individuals. However, autoantibodies indicate an active autoimmune reaction, wherein the immune tolerance is already broken. Therefore, there is a clear and urgent need for new biomarkers that predict the onset of the autoimmune reaction preceding auto-antibody positivity or reflect progressive b-cell destruction. Here we report the mRNA sequencing-based analysis of 306 samples including fractionated samples of CD4+ and CD8+ T cells as well as CD4, CD8 cell fractions and unfractionated PBMC samples longitudinally collected from seven children who developed beta-cell autoimmunity (case subjects) at a young age and matched control subjects.

  Dataset EGAD00001005767

• Phylogenetic development of childhood tumours

  The aim of this study is to reconstruct the phylogenetic development of childhood tumours

  Dataset EGAD00001005770

• The identification of genetic vulnerabilities in head and neck cancers for the development of novel therapies (2020-01-15)

  CRISPR/Cas9 lethality screens in a set of Asian head and neck cancer cell lines to identify novel targets. . This dataset contains all the data available for this study on 2020-01-15.

  Dataset EGAD00001005784

• Somatic mutation and clonal evolution in premalignant lung disease - WGS (2020-01-15)

  Cancer is a genetic disease caused by an accumulations of mutations, however many of these mutations have been identified in pathologically normal tissue. We aim to use laser-capture microscopy (LCM) to sample individual clones from the lung tissue of individuals with a variety of lung diseases (COPD, UIP, IPF, Emphysema, pulmonary hypertension). This will allow us to identify whether cancer-associated mutations appear in this normal tissue, assess the mutational burden present, and identify the mutational processes causing these mutations. Smoking is a large risk factor for developing many of these lung diseases so we are particularly keen to determining whether there is evidence of a smoking signature in these patients. . This dataset contains all the data available for this study on 2020-01-15.

  Dataset EGAD00001005786

• Somatic mutation and clonal evolution normal breast tissue TGS (2020-01-15)

  Cancer is a genetic disease caused by an accumulation of mutations, however many of these mutations have been identified in pathologically normal tissue. We aim to use laser-capture microscopy (LCM) to sample individual clones from breast tissue to identify whether cancer-associated mutations appear in this normal tissue, assess the mutational burden present, and identify the mutational processes causing these mutations. We will sample from a wide age range of individuals (<20 to >70 years old) to determine whether these processes differ in pre- and post-menopausal women. We will also be comparing the tissue from healthy individuals (samples from breast reduction surgery) to those at elevated risk of breast cancer (mastectomy from BRCA1/2 patients) and those who have breast cancer (adjacent normal, distal normal, and tumour tissue from mastectomy). This will allow us to determine how these processes are different between these groups of individuals, and gain insight into the earliest stages of tumour development. . This dataset contains all the data available for this study on 2020-01-15.

  Dataset EGAD00001005787

• subset of DEEP IHEC release 2016 (EGAS00001001937), as used in EGAS00001001656 (bidirectional promotors paper, Fatemeh et al. 2018)

  part of the DEEP project results resulted in the publication of 'Integrative analysis of single-cell expression data reveals distinct regulatory states in bidirectional promoters', Epigenetics & Chromatin (2018), Fatemeh et al., DOI: 10.1186/s13072-018-0236-7, PMID: 30414612, PMCID: PMC6230222. This dataset contains the subset of DEEP data related to that study.

  Dataset EGAD00001005953

• MutWP1: CRUK Grand Challenge Mutographs of Cancer: Colorectal_LCM (2020-02-20)

  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, the International Agency for Research on Cancer is coordinating the recruitment of 5000 individuals with cancer (colorectal, renal, pancreatic, oesophageal adenocarcinoma or oesophageal squamous cancers) across 5 continents to explore whether different mutational signatures explain marked variation in incidence. In brief, through an international network of collaborators around the world, biological materials are collected, along with demographic, histological, clinical and questionnaire data. Whole genome sequences of tumour-germline DNA pairs are generated at the Wellcome Trust Sanger Institute. Somatic mutational signatures are subsequently extracted by non-negative matrix factorisation methods and correlated with risk factors 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 2020-02-20.

  Dataset EGAD00001005994

• Whole Genome Sequencing of Human Organoid Lines (2020-02-20)

  The study will use WGS to aid in benchmarking different culture conditions in a set of genetically annotated human organoid lines. The data will be used to assess whether there is any clonal differences introduced when culturing these lines in different conditions. . This dataset contains all the data available for this study on 2020-02-20.

  Dataset EGAD00001005995

• Whole-genome sequencing of rare disease patients in a national healthcare system

  Most patients with rare diseases do not receive a molecular diagnosis and the aetiological variants and mediating genes for more than half such disorders remain to be discovered. We implemented whole-genome sequencing (WGS) in a national healthcare system to streamline diagnosis and to discover unknown aetiological variants, in the coding and non-coding regions of the genome. In a pilot study for the 100,000 Genomes Project, we generated WGS data for 13,037 participants, of whom 9,802 had a rare disease, and provided a genetic diagnosis to 1,138 of the 7,065 patients with detailed phenotypic data. We identified 95 Mendelian associations between genes and rare diseases, of which 11 have been discovered since 2015 and at least 79 are confirmed aetiological. Using WGS of UK Biobank1, we showed that rare alleles can explain the presence of some individuals in the tails of a quantitative red blood cell (RBC) trait. Finally, we reported 4 novel non-coding variants which cause disease through the disruption of transcription of ARPC1B, GATA1, LRBA and MPL. Our study demonstrates a synergy by using WGS for diagnosis and aetiological discovery in routine healthcare.

  Dataset EGAD00001006065

• BLEMD (arrays set)

  Circulating tumor cells for comprehensive and multiregional non-invasive genetic characterization of multiple myeloma (arrays set)

  Dataset EGAD00010001857

• MutWP1: CRUK Grand Challenge Mutographs of Cancer: Oesophageal adenocarcinoma

  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, the International Agency for Research on Cancer is coordinating the recruitment of 5000 individuals with cancer (colorectal, renal, pancreatic, oesophageal adenocarcinoma or oesophageal squamous cancers) across 5 continents to explore whether different mutational signatures explain marked variation in incidence. In brief, through an international network of collaborators around the world, biological materials are collected, along with demographic, histological, clinical and questionnaire data. Whole genome sequences of tumour-germline DNA pairs are generated at the Wellcome Trust Sanger Institute (40X and 20X depth respectively). Somatic mutational signatures are subsequently extracted by non-negative matrix factorisation methods and correlated with risk factors 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 2021-09-27.

  Dataset EGAD00001006083

• Phylogenetic reconstruction of breast cancer

  This dataset contains the fastq files used for this study

  Dataset EGAD00001006121

• 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

• Impact of genetic variants in clinical outcome of a cohort of patients with oropharyngeal squamous cell carcinoma

  Caracterization of somatic variants in patients with OpSCC

  Dataset EGAD00001006151

• 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

• 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

• 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

• 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