3994 results for "*geneti*"

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• Northern Ireland COhort for the Longitudinal study of Ageing

  The Northern Ireland COhort for the Longitudinal study of Ageing (NICOLA) is a representative sample of ~8,500 people from across Northern Ireland. The study, which was set up in 2012, aims to understand what it is like to grow older in Northern Ireland. • NICOLA has a strong focus on molecular biomarkers so there is complementary genetic, epigenetic and transcriptomic data available for a subset of individuals. • We inherit much of our DNA from our parents while a small amount of this material changes as we get older. In NICOLA we have 551,839 directly genotyped and 18,148,478 imputed Single Nucleotide Polymorphisms (SNPs) currently available for 2969 participants. • Summary statistics for the association of these gene polymorphisms with ~30 phenotypes were generated. • Epigenetics provides a link between our inherited DNA and environmental influences from a person’s diet, medication and lifestyle. NICOLA has the epigenetic quality controlled profiles of 1984 individuals arising from variations in DNA methylation at 862,927 genetic sites.

  Study EGAS00001007915

• Epi2Diag

  Genomic DNA was extracted from whole blood and bisulfite converted using the EZ DNA Methylation Lightning Kit (Zymo research). DNA methylation profile was then derived using Illumina’s Infinium EPIC array v2.0. in accordance with the manufacturer’s protocol at the ASGARD-Rouen genomic platform (Inserm U1245, University of Rouen and Rouen University Hospital, Rouen France) on an Illumina NextSeq550 scanner.

  Study EGAS00001008070

• Transcriptomics-driven classification of ALAL

  Acute leukemia of ambiguous lineage (ALAL) is a rare, poor-prognosis subtype of acute leukemia that cannot be assigned to a single hematopoietic lineage. Although ALAL patients are typically treated with acute myeloid leukemia (AML) or acute lymphoblastic leukemia (ALL) regimens, optimal treatment choice is hindered by their lineage ambiguity. Therefore, we investigated the added value of transcriptomics for improving lineage assignment, currently based mainly on surface markers. First, we used an in-house pipeline to comprehensively detect genetic lesions in RNA-sequencing data (n=23) with a sensitivity >90%, as confirmed by targeted DNA sequencing. Second, we compared ALAL gene expression profiles (GEPs) with representative AML (n=145), B-ALL (n=223) and T-ALL (n=85) cases. In a principal component analysis, ALALs did not form a separate group, but clustered with AML, B-ALL or T-ALL. Accordingly, a machine learning classifier trained with GEPs of acute leukemias segregated 20/23 ALALs into myeloid-, B- or T-lymphoid leukemia. These 20 cases harbored genetic abnormalities consistent with the classifier-assigned leukemia. Furthermore, ALAL GEPs were deconvoluted with single-cell transcriptional profiles of normal hematopoietic cells using CIBERSORTx, revealing enrichment for signatures of lineages corresponding to the leukemic type predicted by our algorithm. The classifier was validated on an external ALAL cohort (n=24), assigning 75% of the patients to a lineage matching their immunophenotypic and methylation profiles. In conclusion, integrative analysis of RNA-sequencing data can accurately classify most ALAL cases. The pipeline and classifier developed in our study are valuable tools to improve ALAL diagnosis and guide therapeutic decisions.

  Study EGAS00001007967

• Single-cell atlas of > 1.5 million PBMC with multi-layer omics data in Japanese

  Osaka Atlas of Immune Cells (OASIS) is multi-omics immune cell atlas from 235 Japanese including COVID-19 patients and healthy subjects. The 5’ single-cell transcriptomics data profiled over 1,500,000 peripheral blood mononuclear cells (PBMCs). OASIS links these single-cell transcriptomics data with host genetics, plasma proteomics, and metagenomics data.

  Study EGAS00001008016

• Patient-derived tumoroids from CIC::DUX4 rearranged sarcoma identify MCL1 as a therapeutic target

  High-risk sarcomas, such as metastasized and relapsed Ewing and CIC-rearranged sarcomas, currently lack effective curative systemic treatment options. Precision medicine approaches offer hope and among them ex vivo drug response profiling of patient-derived tumor cells emerges as a promising novel tool to identify effective drugs for individual patients. Here, we established ex vivo culture conditions to propagate Ewing and CIC::DUX4-sarcomas as tumoroids in a co-clinical manner. These models retained their original molecular and functional characteristics, including recurrent ARID1A mutations, and serve as tumor avatars suitable for large-scale drug testing. Indeed, screening a large drug library on a small living biobank of such tumors not only revealed distinct response differences between the two entities, but also identified an exceptional dependency of CIC::DUX4-sarcoma cells on MCL1. Mechanistically. MCL1 was identified as a direct target gene of the CIC::DUX4 fusion protein. Genetic and pharmacological inhibition of MCL1 induced rapid apoptosis in CIC::DUX4-sarcoma cells and inhibited tumor growth in a xenograft model. Thus, MCL1 represents a potential novel therapeutic target for CIC::DUX4-sarcoma. Overall, our study highlights the feasibility of co-clinical drug response profiling for individual sarcoma cases and suggests that prospective tests, to evaluate its clinical benefit are highly warranted.

  Study EGAS00001008039

• Genetic origins of the Kiritimati population from central-eastern Micronesia

  The migration of Austronesian-speaking populations through Oceania has intrigued researchers for decades. The Kiribati islands, situated along the boundaries of Micronesia and Polynesia, provide a crucial link in this migration. We analyzed the genome-wide data of the Kiritimati population of Kiribati to uncover their genetic origins and connections with other Oceanian groups. Our study reveals that the Kiritimati population primarily exhibits Remote Oceanian-related ancestry associated with ancient Lapita and present-day Polynesian populations. In addition, our identity-by-descent analysis identifies populations from Philippines as their closest relatives in Island Southeast Asia. The genetic links between Kiritimati, ancient Lapita, and modern Polynesians underscore the shared ancestry and continuous gene flow across these regions. This genetic continuity and ongoing links are supported by linguistic and cultural evidence, illustrating a complex history of migration and admixture in Oceania.

  Study EGAS00001008060

• Single cell TCRseq data fromTIL and non-TIL expanded TRACERx samples in the manuscript Bulk TCRseq from TRACERx samples from 'Subclonal immune evasion in non-small cell lung cancer'

  Immune checkpoint blockade in non-small cell lung cancer (NSCLC) rarely leads to complete tumour remission, suggesting that tumours harbour subpopulations of cancer cells that can escape immune predation. However, while tumours consist of multiple genetically distinct clones, the extent to which separate tumour subclones differ intrinsically in their functional capacity for immune evasion remains largely unexplored. This has been challenging to address due to an inability to isolate and propagate individual tumour subclones from human cancers. Here, we leverage the multi-region TRACERx lung cancer evolution study to generate a patient-derived platform that allows the functional analysis of immune escape at single clone resolution. We generated libraries of >20 separate NSCLC organoid lines per patient by isolating individual (clonal) organoids established from multiple spatially separated tumour regions. Each organoid subline was co-cultured with autologous tumour infiltrating lymphocytes (TIL) to evaluate their capacity to elicit a T cell response. Organoid lines derived from separate tumour regions, or from single clones within individual regions, differ vastly in their capacity to elicit a T cell response, showing the coexistence of intrinsically immune evading (‘cold) and non-evading (‘hot) clones in the same primary tumour. Organoid lines escaping T cell recognition represent genetically and transcriptionally unique subclones with a distinct evolutionary history, showing that evolutionary sculpting of subclonal diversity can have functional consequences for anti-tumour immunity. Notably, the identification of immune-evasive subclones would not have been possible using computational approaches alone, highlighting the unique value of functional co-culture platforms. This patient-derived functional co-culture platform reveals that tumour evolution can give rise to distinct cancer clones with intrinsic differences in immune evasion capacity and provides an approach to prospectively identify, isolate and characterise immune evading subclones from patients with cancer.

  Study EGAS00001008161

• OMKar

  The whole genome karyotype refers to the sequence of large chromosomal segments that make up an individuals genotype. karyotype analysis, which includes descriptions of aneuploidies and other rearrangements is crucial for understanding genetic risk factors, for diagnosis, treatment decisions, and genetic counseling linked to constitutional disorders. The current karyotyping standard is based on microscopic examination of chromosomes, a complex process that requires high expertise and offers Mb scale resolution. Optical Genome Mapping (OGM) technology can identify large DNA lesions in a cost-effective manner. In this paper, we developed OMKar, a method that uses OGM data to create a virtual karyotype. OMKar processes Structural (SV) and Copy Number (CN) Variants as inputs and encodes them into a compact breakpoint graph. It recomputes copy numbers using Integer Linear Programming to maintain CN balance and then identifies constrained Eulerian paths representing entire donor chromosomes. In tests using 38 whole genome simulations of constitutional disorders, OMKar reconstructed the karyotype with 88% precision and 95% recall on SV concordance and 95% Jaccard score on CN concordance. We applied OMKar to 50 prenatal, 41 postnatal, and 63 parental samples from ten different sites. OMKar reconstructed the correct karyotype in 144 out of 154 samples, covering 25 of 25 aneuploidies, 32 of 32 balanced translocations, and 72 of 82 unbalanced variations. Detected constitutional disorders included Cri-du-chat, Wolf-Hirschhorn, Prader-Willi deletions, Down, and Turner syndromes. Importantly, it identified a plausible genetic mechanism for five cases of constitutional disorder that were not detected by other technologies. Together, these results demonstrate the robustness of OMKar for OGM-based karyotyping.

  Study EGAS00001008245

• Peruvian Population Genomics: Unraveling the Genetic Landscape and Admixture Dynamics of Urban Populations

  Genome-wide study of human populations living in Peruvian urban areas

  Study EGAS00001008264

• Genome-wide methylation detection and episignature analysis using PacBio long-read sequencing

  Study EGAS00001008250

• Differential Wnt/β-Catenin Signaling Activities Shape Distinct Tumor Cell Phenotypes

  By profiling patient-derived hepatoblastoma organoids via single-cell transcriptomics and chromatin dynamics, we identify subtype-specific transcriptional and epigenetic profiles. Using CUT&RUN, we show that β-catenin engages distinct genomic regions, which is dictated by differential association with TCF/LEF family transcription factors. TCF7L2 binds to a motif, distinct from the classical Wnt consensus sequence, which is found in the promoter of hepatic target genes.

  Study EGAS50000001229

• Full AfricanNeo ModernDNA Study

  With the largest genomic dataset to date of Bantu-speaking populations, including newly generated data of modern-day and ancient DNA from previously unsampled regions in Africa, we shed fresh light on the expansion of peoples speaking Bantu languages that started ~4000 years ago in western Africa. We have genotyped 1,763 participants, including 1,487 Bantu speakers from 143 populations across 14 African countries. Our comprehensive genetic analysis of the expansion of people speaking Bantu languages reveals a complex history of serial founder events, variable levels of contact with local groups, and spread-over-spread events.

  Study EGAS50000000006

• Integrating transcriptional regulatory networks with chromatin accessibility as markers of survival outcome and drug response in triple-negative breast cancer

  Patients with triple-negative breast cancer (TNBC), a highly aggressive and heterogeneous breast cancer subtype, have limited effective targeted therapy options and frequently develop resistance to chemotherapy. Transcription regulators (TRs) guided precision medicine, namely anti-estrogen receptor therapy, has proven successful in hormone-dependent breast cancer, but remains a challenge in TNBC. Here, we identified key TRs underlying TNBC identity by combining a transcriptional interaction network with chromatin accessibility and defined TR activity score metrics. We show that the activity scores of these TRs independently discriminate patient outcome across different clinical endpoints. Matching TR activity scores to drug sensitivity identified drug-TR pairs across independent datasets, including NFE2L3 and CBFB activity associated with sensitivity to mTOR inhibition, which we validated using a cohort of TNBC patient-derived xenografts. Collectively, we present methodology to promote TR-guided precision medicine that captures inter-tumor heterogeneity in TNBC and nominates drug sensitivities according to TR activity scores inferred from expression and chromatin accessibility data.

  Study EGAS50000001691

• Molecular Landscape of Hypertrophic Cardiomyopathy Across Disease Stages and Genotypes

  Hypertrophic Cardiomyopathy (HCM) is marked by asymmetric cardiac wall thickening, enhanced contractility, diastolic dysfunction, and fibrosis. Pathogenic sarcomere gene variants cause HCM, but comparable abnormalities occur in patients with unexplained disease albeit with fewer adverse events. We applied single-nucleus RNA sequencing to investigate how genetic and unexplained HCM affect early disease mechanisms and to contrast HCM with dilated cardiomyopathy (DCM). This EGA dataset contains HCM and control data. DCM and additional control snRNA-seq data, integrated in this study, are available under the EGA dataset accession number: EGAD00001009292.

  Study EGAS50000001411

• Long-read single-cell genome, transcriptome and open chromatin profiling links genotype to phenotypes

  Current single-cell multiomics methods typically provide limited genomic information, constraining genotype-phenotype studies. To address this gap, we developed SPLONGGET (Single-cell Profiling of LONG-read Genome, Epigenome, and Transcriptome), which integrates 10X Genomics barcoding with Oxford Nanopore sequencing to simultaneously profile genome, chromatin accessibility, and full-length transcriptomes in thousands of single cells. By retaining all tagmentation fragments during library preparation, SPLONGGET delivers whole-genome coverage, supports target enrichment for effective single-cell genotyping, and remains backwards compatible with existing short-read workflows. We apply SPLONGGET to longitudinal samples from a case of pediatric B-cell acute lymphoblastic leukemia (B-ALL) to reveal clonal dynamics during therapy and the phenotypic effects of somatic variation, providing valuable insights into disease progression and relapse. In conclusion, SPLONGGET enables integrated high-throughput analysis of genetic variation and molecular phenotypes using off-the-shelf kits, offering a timely and powerful tool to study genetically heterogeneous samples, such as tumours but also ageing normal tissues.

  Study EGAS50000001278

• Comprehensive cancer predisposition gene testing in an adult multiple primary tumor series shows a broad range of deleterious variants and atypical tumor phenotypes

  Multiple primary tumors (MPT) affect a substantial proportion of cancer survivors and may result from various causes including inherited predisposition. Currently, germline genetic testing of MPT cases for cancer predisposition gene (CPG) variants is mostly targeted by tumor type. We ascertained pre-assessed MPT cases from genetics centers (defined as ≥2 primaries by age 60 years or ≥3 by 70) and performed whole genome sequencing (WGS) on 460 individuals from 440 families. Despite previous negative genetic assessment/molecular investigations, pathogenic variants in moderate and high-risk CPGs were detected in 67/440 (15.2%) of probands. WGS detected variants that would not be (or were not) detected by targeted resequencing strategies including structural variants at low frequency (6/440 (1.4%) of probands). In most individuals with a germline variant assessed as pathogenic or likely pathogenic (P/LP), at least one of their tumor types was characteristic of variants in the relevant CPG. However, in 29 probands (42.2% of those with a P/LP variant) the tumor phenotype appeared discordant. The frequency of individuals with truncating or splice site CPG variants and at least one discordant tumor type was significantly higher than a control population (χ2=43.642 P=<0.0001). 2/67 (3%) of probands with P/LP variants had evidence of multiple inherited neoplasia allele syndrome (MINAS) with deleterious variants in two CPGs. Summing together variant detection rates from a similarly ascertained previous MPT case series, the present results suggest that first-line comprehensive CPG analysis in a clinical genetics referral-based MPT cohort would detect a deleterious variant in about a third of cases.

  Dataset EGAD00001004088

• HELIUS cohort gut microbiome

  The gut microbiota composition is unique to every individual but is shaped by common factors including diet, lifestyle, medication use, early-life determinants, living environment or genetics. Most of these factors may be influenced by ethnicity. This study explored variations in fecal microbiota composition in 6048 individuals with different ethnic backgrounds living in the same geographical area (Amsterdam, the Netherlands). The HELIUS data are owned by the Amsterdam University Medical Centers, location AMC in Amsterdam, The Netherlands. To allow sharing of microbiome data collected in HELIUS with (inter)national researchers, 16s rRNA sequence analysis has been stored at the European genome-phenome archive (EGA; accession code EGAD00001004106). This requires that access needs to be granted, also because the HELIUS data are stored with relevant phenotypical variables. Access is granted to all researchers affiliated with an internationally recognized research institution who request to use the HELIUS data within the EGA context, after having signed the data transfer agreement. Any researcher can request the data by submitting a proposal to the HELIUS Executive Board as outlined at http://www.heliusstudy.nl/en/researchers/collaboration, by email: heliuscoordinator at amsterdamumc dot nl. The HELIUS Executive Board will check proposals if they do not conflict with ethical approvals and informed consent forms of the HELIUS study.

  Dataset EGAD00001004106

• Integrated Genomic, Epigenetic, and Expression Analyses of Ovarian Cancer Cell Lines

  In this dataset there are 55 whole genome sequencing samples of epithelial ovarian carcinoma (bam files).

  Dataset EGAD00001004532

• Comprehensive genetic analysis of uveal melanoma heterogeneity during metastatic progression

  Uveal melanoma (UM) is the most common primary intraocular malignancy in adults. Despite improvement of diagnosis and treatment of the primary tumor, there is no effective treatment of metastatic disease and approximately half of patients will die within one year or less following metastases detection. Tumor heterogeneity has been proposed as a key factor of drug resistance. However, it has been scarcely studied in UM. The present project aims searching for specific drivers of the metastatic progression, describing the genomic and transcriptomic landscape of metastatic UM, exploring tumor heterogeneity and investigating its role in drug resistance. Thus whole exome sequencing and transcriptomics have been performed on constitutional, primary tumor and metastatic samples from 28 UM patients.

  Dataset EGAD00001004554

• Exome sequencing of advanced hepatocellular carcinoma

  The aim of our project is to decipher the genomic of advanced hepatocellular carcinoma using whole exome sequencing. To this purpose, we aim to compare genetic landscape of advanced hepatocellular carcinoma with early tumor in order to understand the mechanisms of tumor progression. This work will also help to identify new therapeutic targets potentially useful to treat patients at advanced stage. This dataset contain whole exome sequencing aligned reads for 41 tumor with matched normal samples

  Dataset EGAD00001004555

• BLUEPRINT EpiVar ChIP-seq in lineage specifying transcription factors

  The BLUEPRINT project is a large-scale project investigating epigenetic mechanisms involved in blood formation, in health and disease. The human variation workpackage (WP10) of the project seeks to characterize the effect of common sequence variation on the epigenome status of a cell. To do this, the project will use highly purified blood cells to minimise "experimental noise" and therefore enhance the power to discover modest effects. Two peripheral blood cell types, the CD14+CD16- monocyte (an important central orchestrator of adaptive immunity and a bridge between innate and adaptive immunity) and the CD65+CD9- neutrophilic granulocyte (the frontline cell for innate immunity) have been selected for this purpose. The two types of cells will be obtained at high purity from adult blood (AB) of 200 healthy males and females, respectively. Cells will be purified by using already validated and fully operational protocols that are based on density gradient centrifugation of the buffy coat obtained from whole blood, followed by magnetic bead-based purification using monoclonal antibodies against Cluster of Differentiation (CD) lineage-specific cell surface markers. This data set contains functional genomics data for gene expression and chromatin state.

  Dataset EGAD00001004571

• The mutational landscape of skin tumours in CYLD cutaneous syndrome determined

  Patients with germline mutations in CYLD can develop hundreds of benign skin tumours called cylindromas. The development of multiple tumours within a single patient at sun-protected and sun-exposed sites, varying tumour histological patterns and grades of malignancy allow for the testing of several genetic hypothesis in relation to cutaneous carcinogenesis. By adopting the unprecedented approach of whole genome sequencing of multiple benign skin tumours within individuals in multigenerational families, we set out to study the impact of mutational diversity on models such as multistep carcinogenesis as well as non-sequential carcinogenesis. Using non-negative matrix factorisation (NMF) to discover mutational signatures, we found distinct mutational signatures in identical benign tumours (N=2 patients; n=11 tumours) at sun exposed and sun protected skin tumours within a mother and her daughter. We found recurrent mutations in epigenetic modifying genes in CCS tumours which are known to have an oncogenic dependency on Wnt signalling. We also demonstrate that cutaneous tumours that metastasize to the lung carry a a UV signature, supporting the origin from the skin. Distinct malignant tumours, such as BCC and malignant spiradenocarcinoma carried unique driver mutations. These findings add new dimensions to the existing paradigms of UV-induced skin cancer and highlight the utility of studying rare disease to gain novel insights into genetic mechanisms of tumour formation.

  Dataset EGAD00001004573

• The landscape of somatic mutation in normal colorectal epithelial cells

  The colorectal adenoma-carcinoma sequence has provided a paradigmatic framework for understanding the successive somatic genetic events and consequent clonal expansions leading to cancer. As for most cancer types, however, understanding of the earliest phases of colorectal neoplastic change, which may occur in morphologically normal tissue, is comparatively limited because of the difficulty of detecting somatic mutations in normal cells. Each colorectal crypt is a small clone of cells derived from a single recently-existing stem cell. Here, we sequenced hundreds of normal crypts from 42 individuals. Signatures of multiple mutational processes were revealed, some ubiquitous and continuous, others only found in some individuals, in some crypts or during some phases of the cell lineage from zygote to adult cell. Likely driver mutations were present in ~1% of normal colorectal crypts in middle-aged individuals, indicating that adenomas and carcinomas are rare outcomes of a pervasive process of neoplastic change across morphologically normal colorectal epithelium.

  Dataset EGAD00001004192

• The landscape of somatic mutation in normal colorectal epithelial cells

  The colorectal adenoma-carcinoma sequence has provided a paradigmatic framework for understanding the successive somatic genetic events and consequent clonal expansions leading to cancer. As for most cancer types, however, understanding of the earliest phases of colorectal neoplastic change, which may occur in morphologically normal tissue, is comparatively limited because of the difficulty of detecting somatic mutations in normal cells. Each colorectal crypt is a small clone of cells derived from a single recently-existing stem cell. Here, we sequenced hundreds of normal crypts from 42 individuals. Signatures of multiple mutational processes were revealed, some ubiquitous and continuous, others only found in some individuals, in some crypts or during some phases of the cell lineage from zygote to adult cell. Likely driver mutations were present in ~1% of normal colorectal crypts in middle-aged individuals, indicating that adenomas and carcinomas are rare outcomes of a pervasive process of neoplastic change across morphologically normal colorectal epithelium.

  Dataset EGAD00001004193

• Open Targets 020 Epigenomes of Cell Lines (2018-10-23)

  There is currently a drive to establish cell based assay systems of greater human biological and disease relevance through the use of well characterised transformed cell lines, primary cells and complex cellular models (e.g. co-culture, 3D models). However, although the field is gaining valuable experience in running more non-standard & complex cell assays for target validation and compound pharmacology studies, there is the lack of a systematic approach to determine if this expansion in cell assay models is reflected in increased human biological and disease relevance. The increasing wealth of publically available transcriptomic, and epigenome (ENCODE and Epigenome Roadmap) data represents an ideal reference mechanism for determining the relationship between cell types used for target & compound studies to primary human cells and tissues from both healthy volunteers & patients. The CTTV020 epigenomes of cell line project aims to generate epigenetic and transcriptomic profiles of cell lines and compare these with existing and newly generated reference data sets from human tissue and cell types. The aim is to identify assay systems which will provide greater confidence in translating target biology and compound pharmacology to patients. Multiple cell types commonly used within research have been grouped according to biology. Examples include erythroid, lung epithelial, hepatocyte cell types and immortalised models of monocyte / macrophage biology. 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 2018-10-23.

  Dataset EGAD00001004413