3901 results for "*geneti*"

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• 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

• Solid_WXS_MET-XEN

  Whole-exome sequencing on AB 5500xl Genetic Analyzer of Patient-derived xenograft derived from colorectal cancer metastasis sample

  Dataset EGAD00001002106

• Blueprint: A human variation panel of genetic influences on epigenomes and transcriptomes in three immune cell types, (ChIP-Seq for CD14-positive, CD16-negative classical monocyte, on genome GRCh37)

  ChIP-Seq data for 172 CD14-positive, CD16-negative classical monocyte sample(s). 572 run(s), 345 experiment(s), 340 analysis(s) on human genome GRCh37. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/blueprint_Epivar/protocols/README_chipseq_analysis_ebi_20160816

  Dataset EGAD00001002672

• Genetics and Networks of Congenital Heart Defects

  Exome sequencing of families with Congenital Heart Defects of diverse sub-phenotypes. Comprises both parent-offspring trios for sporadic cases and multiplex families. Collaboration with David Brook, University of Nottingham. Funded by the British Heart Foundation.

  Dataset EGAD00001002251

• A comprehensive characterisation and analysis of human breast cancers through whole-genome sequencing

  We propose to definitively characterise the somatic genetics of breast cancer through generation of comprehensive catalogues of somatic mutations in breast cancer cases by high coverage genome sequencing.

  Dataset EGAD00001002740

• 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

• MutWP1: CRUK Grand Challenge Mutographs of Cancer: Kidney (1)

  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.

  Dataset EGAD00001006427

• Development, maturation and maintenance of human prostate inferred from somatic mutations

  Stem cells within prostate epithelium frequently undergo malignant transformation, but there is limited information on their clonal dynamics and mutation burden in healthy human prostates. We sequenced whole genomes from 409 microdissections of prostate epithelium across 8 donors, using phylogenetic reconstruction with spatial mapping in a 59-year-old man’s prostate to provide high-resolution reconstruction of tissue dynamics across the lifespan. Somatic mutation burden increases linearly with age, at ~16 mutations/year/clone, and is higher in peripheral than peri-urethral regions. The 24-30 independent glandular subunits are established as rudimentary ductal structures during fetal development by 5-10 embryonic cells each. Puberty induces formation of further side branches and terminal acini by local stem cells disseminated through the rudimentary ducts during development. During adult tissue maintenance, clonal expansions are small, with limited geographic scope and minimal migration. Driver mutations are rare in normal ageing prostate epithelium, but the one canonical driver we did observe generated a sizable intraepithelial clonal expansion. By resolving unbiased, continuously occurring lineage-marking mutations, we define stem cell dynamics through embryogenesis, puberty and ageing, with relevance for prostate cancer.

  Dataset EGAD00001006591

• 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

• 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

• 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

• 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

• IBD Whole Genome Sequencing (2019-04-01)

  We will sequence at 15X coverage the genomes of 1536 IBD patients. These samples are currently onsite at Sanger and made available for sequencing via our collaboration with the UK IBD Genetics consortium. 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 2019-04-01.

  Dataset EGAD00001004880

• 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

• 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

• Exome Sequencing to Identify Causes of Leukaemia Predisposing Congenital Neutropenias (2019-08-19)

  The objective of this study is to identify the causative genes in two unrelated congenital neutropenia families. We aim to whole exome sequence the affected individuals, unaffected siblings and parents in both cases in an effort to idenitfy the causative genetic mutation. Exome capture will be performed using Agilent SureSelect system. Subsequently, exome libraries will sequenced using the Illumina HiSeq platform. Sequence variant calling will be done in house and common variants excluded using public databases and data from unaffected family members. . This dataset contains all the data available for this study on 2019-08-19.

  Dataset EGAD00001005264

• Phylogenetic reconstruction of adult blood cancer reveals early origins and lifelong evolution - WGS

  Mutations in cancer-associated genes drive tumour outgrowth. However, the timing of driver mutations and dynamics of clonal expansion that lead to human cancers are largely unknown. We used 580,133 somatic mutations from whole-genome sequencing of 1013 clonal haematopoietic colonies to reconstruct the phylogeny of haematopoiesis, from embryogenesis to clinical disease, in 12 patients with myeloproliferative neoplasms which are blood cancers more common in older age. JAK2V617F, the pathognomonic mutation driving the majority of these cancers, was acquired in utero or childhood, with upper estimates of age of acquisition from 33 weeks gestation to 10.8 years, in all 5 patients in whom JAK2V617F was either the only or the first driver event.  Driver mutations associated with age-related clonal haematopoiesis occurred prior to or following JAK2V617F,  as independent clonal expansions in JAK2V617F-mutated patients, and as large clonal expansions in JAK2V617F-unmutated patients . These mutations were also acquired in utero or childhood, with DNMT3A mutations occurring by 8 weeks of gestation to 7.6 years across 4 patients, and PPM1D mutation occurring by age 5.8yrs in a patient with MPN lacking phenotypic driver mutations. Sequential driver mutation acquisition was common, separated by decades across life, and often outcompeted ancestral clones. The mean latency between JAK2V617F acquisition and clinical presentation was 30 years (range 11-54 years). Rates of clonal expansion were inferred from phylogenetic trees and varied substantially (3% to 190% expansion/year), were affected by additional driver mutations, and were predictive of latency to clinical presentation. Driver mutations and rates of expansion would have been detectable in blood one to four decades before clinical presentation. This study reveals how driver mutation acquisition early in life with life-long growth and evolution underlie adult myeloproliferative neoplasms, providing opportunities for early detection and intervention and a new paradigm for cancer development.

  Dataset EGAD00001007714

• Epigenetic, transcriptome and TF analysis of human NK cell and T cells

  RNA-seq 10 subsets; 5 donors. ATAC-seq 9 subsets, 4 donors; Histone modification profiling 10 subsets, 2 donors all using human NK cell and T cell subsets. TF ChIP-seq Bcl11b, Bach2, Runx2, Gata3, PLZF. Illuminia sequencing platform, ATAC-seq is Paired-end, RNA-seq/ChIP-seq is Single-end

  Dataset EGAD00001008449

• Phylogenetic reconstruction of adult blood cancer reveals early origins and lifelong evolution - TGS

  Mutations in cancer-associated genes drive tumour outgrowth. However, the timing of driver mutations and dynamics of clonal expansion that lead to human cancers are largely unknown. We used 580,133 somatic mutations from whole-genome sequencing of 1013 clonal haematopoietic colonies to reconstruct the phylogeny of haematopoiesis, from embryogenesis to clinical disease, in 12 patients with myeloproliferative neoplasms which are blood cancers more common in older age. JAK2V617F, the pathognomonic mutation driving the majority of these cancers, was acquired in utero or childhood, with upper estimates of age of acquisition from 33 weeks gestation to 10.8 years, in all 5 patients in whom JAK2V617F was either the only or the first driver event.  Driver mutations associated with age-related clonal haematopoiesis occurred prior to or following JAK2V617F,  as independent clonal expansions in JAK2V617F-mutated patients, and as large clonal expansions in JAK2V617F-unmutated patients . These mutations were also acquired in utero or childhood, with DNMT3A mutations occurring by 8 weeks of gestation to 7.6 years across 4 patients, and PPM1D mutation occurring by age 5.8yrs in a patient with MPN lacking phenotypic driver mutations. Sequential driver mutation acquisition was common, separated by decades across life, and often outcompeted ancestral clones. The mean latency between JAK2V617F acquisition and clinical presentation was 30 years (range 11-54 years). Rates of clonal expansion were inferred from phylogenetic trees and varied substantially (3% to 190% expansion/year), were affected by additional driver mutations, and were predictive of latency to clinical presentation. Driver mutations and rates of expansion would have been detectable in blood one to four decades before clinical presentation. This study reveals how driver mutation acquisition early in life with life-long growth and evolution underlie adult myeloproliferative neoplasms, providing opportunities for early detection and intervention and a new paradigm for cancer development.

  Dataset EGAD00001007715

• Novel de novo pathogenic variant in the GNAI1 as a cause of severe disorders of intellectual development with autistic features

  Our probands A and B are boys-monozygotic twins with the clinical diagnosis of severe intellectual impairment, developmental stagnation, and dysphasia. They were diagnosed at the Department of Medical Genetics and Genomics (University Hospital Brno). Parents provided written informed consent, which was approved by the Research Ethics Committee of Masaryk University and Ethics Committee of University Hospital Brno. Peripheral blood samples were collected in sterile heparinized tubes for cytogenetic analysis. Genomic DNA samples were obtained from 1 ml peripheral blood in EDTA, according to the standard DNA isolation process using the MagNaPure system (Roche Diagnostics, Basel, Switzerland). Quality and quantity were checked using a DeNovix DS-11 Spectrophotometer (DeNovix Inc., Wilmington, DE, USA) and Qubit® 2.0 (Thermo Fisher Scientific, Inc., Waltham, MA, USA).

  Dataset EGAD00001007736

• 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

• 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

• 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

• Peripheral blood RNA-sequencing in 4,732 participants of the INTERVAL cohort

  We performed bulk RNA-sequencing on peripheral blood collected from 4,732 blood donors recruited as part of the INTERVAL study. Using these data, we mapped gene expression and splicing quantitative trait loci (QTLs). Then, we integrated these data with protein, metabolite and lipid QTLs in the same individuals. The study aimed to identify the shared genetic etiology across transcriptional phenotypes, molecular traits and health outcomes in humans.

  Dataset EGAD00001008015

• RNA sequencing of Human Organoid Lines

  The study will use RNA sequencing 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 are any clonal differences introduced when culturing these lines in different conditions.

  Dataset EGAD00001007971

• Investigating the genetics of immunity against Salmonella in humans (2019-09-05)

  This study entails whole genome sequencing of an interleukin (IL)-12 b-1 receptor-deficient individual who presented with a chronic systemic Salmonella Enteritidis infection that did not resolve with standard IFNg and antibiotic treatment. Whole genome sequencing of the patient's parents are also included. 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 2019-09-05.

  Dataset EGAD00001005311

• Small-molecule inhibitors in melanoma - Kenski / Kong - WES (2019-04-11)

  Small-molecule inhibitors targeting the most commonly activated pathway in melanoma, MAPK pathway (either alone or in combination) are already given to melanoma patients for few years, and initially reduce tumour burden dramatically, eventually melanomas become resistant and tumours progress while on treatment. Resistance to this treatment occurs by acquisition of additional mutations or other alterations that affect the mitogen-activated protein kinase (MAPK) pathway by either direct or indirect signalling. Many resistance mechanisms somehow lead to reactivation of extracellular signal-regulated kinase (ERK), thereby restoring signalling of the oncogenic BRAF/MEK/ERK pathway. In addition, PI3K pathway activation contributes to resistance to BRAF inhibition. Less frequent but equally important to the phenomenon of targeted drug resistance is the observation that B15-20% of BRAF mutant melanoma patients fail to respond to BRAF inhibition already early on treatment, owing to intrinsic resistance. These patients have little therapeutic options, unless immunotherapy can be given. To better understand the resistance mechanisms in MAPK inhibitor-treated melanoma patients and melanoma biology, our lab generated a big panel of MAPK inhibitor resistant melanoma cell lines by continuous drug exposure. The understanding of the genetic landscape and gene expression as well as cross resistance to other treatment regimens, and other aspects of melanoma biology such as phenotype switch, will allow us to better exploit new therapeutic strategies for melanoma patients. . This dataset contains all the data available for this study on 2019-04-11.

  Dataset EGAD00001004952

• 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

• RNA-seq data

  This dataset contains 200 RNA-seq bam files (142 SLE, 58 healthy individuals). RNA libraries were prepared with the Illumina TruSeq sample preparation kit and were sequenced on Illumina HiSeq2000. 49 bp paired-end reads were mapped to the GRCh37 reference human genome using the GEM mapper.This dataset was generated as part of the following study: Panousis et al (2019). Combined genetic and transcriptome analysis of patients with SLE: Distinct, targetable signatures for susceptibility and severity

  Dataset EGAD00001005037

• 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

• Assessment of genetic and epigenetic variation in human IPS cells

  In order to progress human induced pluripotent stem cells (hiPSCs) towards the clinic, several outstanding questions must be addressed. It is possible to reprogram different somatic cell types into hiPSCs but it is unlcear whether some cell types carry through fewer mutations through reprogramming (either due to mutations present in the primary cells, or mutations accumulated during reprogramming). Through in depth analysis of hiPSCs generated from different somatic cells, it will be possible to assess the variation in genetic stability of different cell types.

  Dataset EGAD00001000384

• 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

• Egypt Genome Project - high coverage whole genome sequencing

  All humans outside Africa are descendants of the same single exit, usually dated at 50-70 thousand years ago. However, the route taken out of Africa is still debated. The two main candidates are a northern route via Egypt and the Levant, or a southern route via Ethiopia and the Arabian Peninsula. We are generating genetic data to evaluate these two possibilities. In this study we propose to generate high-coverage sequencing data for 3 Egyptian samples.

  Dataset EGAD00001001380

• IKZF5 RNAseq samples for platelets, neutrophils, monocytes and CD4+ T-cells.

  To identify novel causes of hereditary thrombocytopenia, we performed a genetic association analysis of whole-genome sequencing (WGS) data from 13,037 individuals enrolled in the NIHR BioResource, including 233 cases with isolated thrombocytopenia. We found an association between rare variants in the transcription factor (TF)-encoding gene IKZF5 and thrombocytopenia. We report five causal missense variants in or near IKZF5 zinc fingers (Znfs), of which two occurred de novo and three co-segregated in three pedigrees. A canonical DNA-Znf binding model predicts that three of the variants alter DNA recognition. Expression studies showed that chromatin binding was disrupted in mutant compared to wild-type (WT) IKZF5 and electron microscopy (EM) revealed a reduced quantity of alpha granules in normally sized platelets. Proplatelet formation (PPF) was reduced in megakaryocytes (MKs) from seven cases relative to six controls. Comparison of RNA-seq data from platelets, monocytes, neutrophils and CD4+ T-cells from three cases and 14 healthy controls showed 1,194 differentially expressed genes (DEGs) in platelets but only four DEGs in each of the other blood cell types. In conclusion, IKZF5 is a novel transcriptional regulator of megakaryopoiesis and the eighth transcription factor associated with dominant thrombocytopenia in humans.

  Dataset EGAD00001005107

• 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

• Convergent somatic evolution from early life in a germline ribosomopathy

  Clonal tracking of stem cells and their progeny by whole genome sequencing permits exploration of evolutionary genetics in human disease. In this study, we performed phylogenetic reconstruction of haematopoiesis using somatically acquired mutations in 323 single haematopoietic stem and progenitor cell-derived colonies from 10 individuals with an inherited disorder of ribosome assembly, Shwachman-Diamond syndrome. We observed numerous clonal expansions, with recurrent acquisition of mutually exclusive mutations (EIF6, TP53, RPL5, RPL22, PRPF8, chromosomes 7 and 15) in multiple different clones in utero or early childhood converging on the p53-dependent nucleolar surveillance pathway that monitors ribosome integrity. In contrast to clones carrying biallelic TP53 mutations, genomes derived from colonies carrying mono-allelic TP53 mutations displayed no increase in mutation burden or specific mutational signatures. Our study highlights striking loss of clonal diversity with convergent somatic evolution on the p53-dependent nucleolar surveillance pathway from early life to offset the deleterious effects of a germline mutation in a Mendelian haematopoietic disorder.

  Dataset EGAD00001009061

• 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

• Diagnostic utility of whole genome sequencing in adults with B-other acute lymphoblastic leukemia

  Genomic profiling at diagnosis of B-cell precursor Acute Lymphoblastic Leukemia (BCP-ALL) in adults is used to guide disease classification, risk stratification and treatment decisions. Patients for which diagnostic screening fails to identify disease defining or risk stratifying lesions are classified as B-other ALL. We screened a cohort of 652 BCP-ALL cases enrolled in UKALL14 to identify and perform whole genome sequencing (WGS) on paired tumor-normal samples. For 52 B-other patients we compared WGS findings to data from clinical and research cytogenetics. WGS identifies a cancer associated event in 51/52 cases, this includes an established subtype defining genetic alteration in 5/52 that were previously missed by standard-of-care genetics. Of the 47 true B-other ALL we identified a recurrent driver in 87% (41).  Complex karyotype by cytogenetics emerges as a heterogeneous group, underlied by distinct genetic alterations associated with either favorable (DUX4-r) or poor outcomes (MEF2D-r, IGK::BCL2). For a subset of 31 cases, we integrate findings from RNA-sequencing (RNA-seq) analysis to include fusion gene detection, and classification by gene expression. Compared to RNA-seq, WGS was sufficient to detect and resolve recurrent genetic subtypes, however RNA-seq can provide orthogonal validation of findings. In conclusion, we demonstrate that WGS can identify clinically relevant genetic abnormalities missed by standard-of-care testing and identify leukemia driver events in virtually all cases of B-other ALL.

  Dataset EGAD00001009304

• Genetic screening of GPI-anchor protein synthesis

  This study will analyse the guide sequence which were used for making mutations in the Cas9-expressing cells. We used GeCKO v2 library which were released by Feng Zhang, 2014. 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 EGAD00001001928

• Diagnostic utility of whole genome sequencing in adults with B-other acute lymphoblastic leukemia - RNA

  Genomic profiling at diagnosis of B-cell precursor Acute Lymphoblastic Leukemia (BCP-ALL) in adults is used to guide disease classification, risk stratification and treatment decisions. Patients for which diagnostic screening fails to identify disease defining or risk stratifying lesions are classified as B-other ALL. We screened a cohort of 652 BCP-ALL cases enrolled in UKALL14 to identify and perform whole genome sequencing (WGS) on paired tumor-normal samples. For 52 B-other patients we compared WGS findings to data from clinical and research cytogenetics. WGS identifies a cancer associated event in 51/52 cases, this includes an established subtype defining genetic alteration in 5/52 that were previously missed by standard-of-care genetics. Of the 47 true B-other ALL we identified a recurrent driver in 87% (41).  Complex karyotype by cytogenetics emerges as a heterogeneous group, underlied by distinct genetic alterations associated with either favorable (DUX4-r) or poor outcomes (MEF2D-r, IGK::BCL2). For a subset of 31 cases, we integrate findings from RNA-sequencing (RNA-seq) analysis to include fusion gene detection, and classification by gene expression. Compared to RNA-seq, WGS was sufficient to detect and resolve recurrent genetic subtypes, however RNA-seq can provide orthogonal validation of findings. In conclusion, we demonstrate that WGS can identify clinically relevant genetic abnormalities missed by standard-of-care testing and identify leukemia driver events in virtually all cases of B-other ALL.

  Dataset EGAD00001009305

• MutWP4: CRUK Grand Challenge Mutographs of Cancer: Gastric Organoids (2019-08-07)

  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 2019-08-07.

  Dataset EGAD00001005234

• The British Autozygosity Populations BioResource

  This data set contains whole exome sequences of individuals with self-stated parental relatedness from the East London Genes & Health cohort. Rare frequency functional variants in these healthy individuals will be studied with respect to the genetic health of the participants and loss-of-function analysis of human genes.

  Dataset EGAD00001003215

• Tracking the evolution of esophageal squamous cell carcinoma under dynamic immune selection by multi-omics sequencing

  Intratumoral heterogeneity (ITH) has been linked to decreased efficacy of clinical treatments. However, although genomic ITH has been characterized in genetic, transcriptomic and epigenetic alterations are hallmarks of esophageal squamous cell carcinoma (ESCC), the extent to which these are heterogeneous in ESCC has not been explored in a unified framework. Further, the extent to which tumor-infiltrated T lymphocytes (TILs) are directed against cancer cells, but how the immune infiltration acts as a selective force to shape the clonal evolution of ESCC is unclear. In this study, we perform multi-omic sequencing on 186 samples from 36 primary ESCC patients. Through multi-omics analyses, it is discovered that genomic, epigenomic, and transcriptomic ITH are underpinned by ongoing chromosomal instability. Based on the RNA-seq data, we observe diverse levels of immune infiltrate across different tumor sites from the same tumor. We reveal genetic mechanisms of neoantigen evasion under distinct selection pressure from the diverse immune microenvironment. Overall, our work offers an avenue of dissecting the complex contribution of the multi-omics level to the ITH in ESCC and thereby enhances the development of clinical therapy.

  Dataset EGAD00001009482

• 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

• Somatic mutation and clonal evolution normal breast tissue WGS

  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 2023-03-09.

  Dataset EGAD00001010123

• Capture-based NGS

  Capture-based NGS obtained using the "all-CLL" panel (also known as SOPHiA DDM (TM) Community CLL Clonality Solution). Library preparation was performed following SOPHiA GENETICS recommendations using 200 ng genomic DNA. Libraries were sequenced on a MiSeq instrument (2x300 bp, Illumina) aiming at a mean coverage of 1,000x.

  Dataset EGAD00001011151

• Type 2 Diabetes Genetic Exploration by Next-generation sequencing in multi-Ethnic Samples (T2D-GENES)

  The T2D-GENES/GoT2D 13K exome sequencing study includes ~13,000 samples, half T2D cases and half T2D controls, from five ancestries (~5K Europeans, ~2K each of African-American, East-Asian, South-Asian, and Hispanic). Samples underwent deep exome sequencing, with SNVs and INDEls called according to GATK best practices; variant sites were then filtered according to the GATK best practices, and then samples and variants underwent further filtering based on aggregate genotype quality as described in Fuchsberger et al. (e.g. low call rate, excess heterozygosity for samples, low call rate or coverage for variants). Please note that one of the samples in the T2D-GENES vcf does not have phenotype data.

  Dataset EGAD00001002246

• 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

• 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

• 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