4075 results for "*geneti*"

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• Genetic architecture of male infertility in India

  The dataset consists of whole exome and genome sequencing data from infertile males and his parent(s) and/or sibling(s)

  Dataset EGAD00001015606

• PacBio Rare Disease Study

  This study leverages PacBio HiFi long-read sequencing technology to comprehensively analyze the genomic architecture of rare diseases. By generating highly accurate, long-read sequences, we aim to resolve complex structural variants, repeat expansions, and other genomic features that are often missed by short-read sequencing. Our approach facilitates improved variant detection and interpretation, advancing the understanding of rare disease etiology and enabling more precise genetic diagnoses.

  Dataset EGAD00001015611

• Insights into non-crossover recombination from long-read sperm sequencing

  Meiotic recombination is a fundamental process that generates genetic diversity by creating new combinations of existing alleles. While crossovers in humans are well characterized, the more frequent non-crossovers that lead to gene conversion remain challenging to study. Here we show that single high-fidelity long sequencing reads from sperm can capture both crossovers and non-crossovers, allowing effectively arbitrary sample sizes for analysis from one male. Using fifteen sperm samples from thirteen donors we demonstrate variation between donors for the different types of recombination, even when they share the same PRDM9 genotype. Non-crossovers are less consistent with the genetic map and exhibit reduced association with meiotic double-strand break (DSB) sites identified by DMC1 binding. Where non-crossover gene conversions are close to PRDM9 sites they tend to occur upstream. We further provide evidence for two distinct non-crossover processes. One gives rise to the vast majority of non-crossovers with mean conversion tract length under 50bp, while ~1% of non-crossovers have much longer mean tract length. Applying the same analysis pipeline to public data from twelve blood samples, we also see non-crossover gene conversions, but very few crossover events. These non-meiotic events, not correlated with the genetic map, increase with age, consistent with double-strand break repair throughout life. We suggest that many of the non-crossover events seen in sperm also derive from non-meiotic repair prior to spermatogenesis.

  Dataset EGAD00001015736

• Understanding the development of resident memory T cells (Trm) in the human small intestine using integrative multiomic approaches: Adult RNA (2025-10-14)

  Animal studies have demonstrated that resident memory T (Trm) cells provide enhanced protective responses to a broad array of tissue-tropic pathogens, thus making Trm cells promising targets for novel vaccination strategies. However, the biological pathways that enable the long-term survival of Trm cells are poorly understood in humans. Here, we will employ a unique human intestinal transplantation setting that allows us to study the retention of persistent T cells in the grafts and the temporal development of resident T-cell populations from recruited recipient T cells. We will integrate high resolution transcriptomics, epigenetics, proteomics and immune repertoire single-cell data from purified intestinal T cells. These single-cell multiomics approaches will uncover the diversity and differentiation of the T cell populations in the human intestine, allowing us to temporally resolve the generation and maintenance of gut resident T cells. . This dataset contains all the data available for this study on 2025-10-14.

  Dataset EGAD00001015739

• DNMT3A-R882 mutations intrinsically drive dysfunctional neutropoiesis from human haematopoietic stem cells

  Clonal haematopoiesis (CH) arises from the expansion of hematopoietic stem cells (HSCs) carrying leukaemia-associated somatic mutations. CH is linked to pathological immune dysregulation and a greater risk of age-related inflammatory diseases. Yet, how CH mutations impact HSC differentiation into immune effector cells remains understudied. Here, we report a single-cell resolution functional and multi-omic investigation of HSC clonal and differentiation dynamics in individuals with DNMT3A-R882 CH. DNMT3A-R882 reshapes the clonal architecture of haematopoiesis towards an aged phylogenetic structure. Functionally, DNMT3A-R882 HSCs produce decreased monocytic output but more abundant and mature neutrophil progeny compared to WT HSCs in the same individual. Whereas DNMT3A-R882 myeloid progenitors display attenuated inflammatory transcriptional programmes, DNMT3A-R882 mature neutrophils acquire proinflammatory and immunomodulatory features typical of maladaptive immunity and CH co-morbidities. Our findings, validated in humanised mice, identify aberrant DNMT3A-R882 HSC-driven neutropoiesis as a key link between CH, immune dysregulation and risk of inflammatory disease.

  Dataset EGAD00001015750

• Genomic and Functional Profiling of Acral Melanoma from the admixed Brazilian Population Reveals Disease Drivers and Targetable Vulnerabilities

  Acral melanoma, a subtype of melanoma characterized by its occurrence on palms, soles, and beneath the nails, presents unique challenges in diagnosis and treatment due to its distinct genetic and environmental factors. Despite recent advancements in targeted therapies for melanoma, the efficacy of treatments in acral melanoma remains limited, emphasizing the urgent need for a deeper understanding of its genetic landscape. CRISPR-based functional genomics screening has emerged as a powerful tool for uncovering genetic dependencies and potential therapeutic targets in various cancers. In this project, we present the results of CRISPR screening performed on acral melanoma cell lines to identify genes essential for cell survival and proliferation collectively termed “fitness". Through this screening approach, we aim to elucidate the molecular mechanisms underlying the pathogenesis of acral melanoma and identify novel therapeutic vulnerabilities. Our findings reveal key genetic drivers and pathways implicated in acral melanoma progression, offering potential targets for the development of precision therapies tailored to this aggressive subtype of melanoma

  Dataset EGAD00001015690

• A next-generation dual guide CRISPR system for genetic interaction library screening

  Raw sgRNA sequencing data from a pilot CRISPR screening library to test the dual guide vector system (8,914 guide pairs), and from a large scale genetic interaction screen (~100,136 guide pairs) in HT-29 cells. This data refers to Burgold et al. Nature Communications 2025.

  Dataset EGAD00001015754

• Ancestry and somatic profile predict acral melanoma origin and prognosis – WXS

  Acral melanoma, which is not ultraviolet (UV)-associated, is the most common type of melanoma in several low- and middle-income countries including Mexico. Latin American samples are significantly underrepresented in global cancer genomics studies, which directly affects patients in these regions as it is known that cancer risk and incidence may be influenced by ancestry and environmental exposures. To address this, we characterise the genome and transcriptome of 123 acral melanoma tumours from 92 Mexican patients, a population notable because of its genetic admixture. Compared with other studies of melanoma, we found fewer frequent mutations in classical driver genes such as BRAF, NRAS or NF1. While most patients had predominantly Amerindian genetic ancestry, those with higher European ancestry had increased frequency of BRAF mutations and a lower median number of structural variants. The tumours with activating BRAF mutations have a transcriptional profile more similar to cutaneous non-volar melanocytes, suggesting that acral melanomas in these patients may arise from a distinct cell of origin compared to other tumours arising in these locations. KIT mutations were found in a subset of these tumours, and quadruple wild-type samples (non BRAF/NRAS/NF1/KIT) differed from mutated samples in their structural genomic profile and overall and recurrence-free survival patterns. Transcriptional profiling defined three expression clusters; these characteristics were associated with recurrence-free and overall survival. We highlight potential novel low-frequency drivers, such as PTPRJ, NF2 and RDH5. Our study enhances knowledge of this understudied disease and underscores the importance of including samples from diverse ancestries in cancer genomics studies.

  Dataset EGAD00001015755

• Ancestry and somatic profile predict acral melanoma origin and prognosis – RNA

  Acral melanoma, which is not ultraviolet (UV)-associated, is the most common type of melanoma in several low- and middle-income countries including Mexico. Latin American samples are significantly underrepresented in global cancer genomics studies, which directly affects patients in these regions as it is known that cancer risk and incidence may be influenced by ancestry and environmental exposures. To address this, we characterise the genome and transcriptome of 123 acral melanoma tumours from 92 Mexican patients, a population notable because of its genetic admixture. Compared with other studies of melanoma, we found fewer frequent mutations in classical driver genes such as BRAF, NRAS or NF1. While most patients had predominantly Amerindian genetic ancestry, those with higher European ancestry had increased frequency of BRAF mutations and a lower median number of structural variants. The tumours with activating BRAF mutations have a transcriptional profile more similar to cutaneous non-volar melanocytes, suggesting that acral melanomas in these patients may arise from a distinct cell of origin compared to other tumours arising in these locations. KIT mutations were found in a subset of these tumours, and quadruple wild-type samples (non BRAF/NRAS/NF1/KIT) differed from mutated samples in their structural genomic profile and overall and recurrence-free survival patterns. Transcriptional profiling defined three expression clusters; these characteristics were associated with recurrence-free and overall survival. We highlight potential novel low-frequency drivers, such as PTPRJ, NF2 and RDH5. Our study enhances knowledge of this understudied disease and underscores the importance of including samples from diverse ancestries in cancer genomics studies.

  Dataset EGAD00001015756

• Genomics Define Malignant Transformation in Myeloma Precursor Conditions

  Multiple myeloma (MM) is consistently preceded by monoclonal gammopathy of undetermined significance (MGUS) and smoldering multiple myeloma (SMM). While these precursor conditions are asymptomatic, they are not entirely benign and carry a lifelong risk of progression to MM. Unlike other cancers defined by pathology, malignant transformation from MGUS or SMM to MM has so far relied on demonstration of clinical end-organ damage as morphology and cytogenetics cannot reliably distinguish them. In this study, using genomic data from 374 patients with MGUS or SMM (277 training, 97 validation), to our knowledge, we demonstrate for the first time the ability to identify malignant transformation in MGUS and SMM. We introduce the concept of genomic MM and genomic MGUS to differentiate the subsets of MGUS and SMM that are biologically malignant with genomic features indistinguishable from MM from the subset that is premalignant and unlikely to progress to malignancy. Importantly, we find that most SMM has biological features of malignant transformation indistinguishable from MM. As expected, this subset that we consider having genomic MM is associated with a high risk of progression to MM although some patients remained progression-free beyond 5 years. Conversely, 60% of MGUS and 10% of SMM have no evidence of malignant transformation (genomic MGUS), with no progression during follow-up. Integration of genomic features with the 2/20/20 International Myeloma Working Group model significantly improved the prediction of progression among genomic MM. These findings support the use of genomic criteria to refine the classification and the risk stratification in myeloma precursor conditions.

  Dataset EGAD00001015768

• BIOCLOCK Phenotype Information Dataset

  This dataset contains phenotypic metadata from participants in the BIOCLOCK endurance exercise intervention and epigenetic aging study. It includes intervention status, cardiorespiratory fitness (VO2 max), body composition, estimated leukocyte proportions, and other relevant traits linked to epigenetic aging outcomes.

  Dataset EGAD00001015799

• Solve-RD multi-omics data chud-faivre cohort

  The dataset includes short-read whole-genome sequencing (SR-WGS) data, SR-RNAseq data, OGM (Bionano) data, LR-WGS data, Epigenetics (RBSS) data and deep-WES data generated within the project Solve-RD from biosamples submitted by the group chud-faivre. The cohorts consists of 111 individuals recruited as part of Solve-RD cohorts 2-4 and aligns with ERN-ITHACA related disease entities (for a description of the Solve-RD cohorts see www.solve-rd.eu/fact-sheet-solve-rd-cohorts).

  Dataset EGAD00001015811

• On-target mutations confer resistance to WRN helicase inhibitors in Microsatellite Unstable Cancer Cells

  This study investigates genetic dependencies and resistance mechanisms to Werner helicase inhibitors (WRNi) in microsatellite-unstable (MSI) cancer models. To define determinants of WRN dependency and acquired resistance, we performed genome-wide CRISPR-Cas9 knockout screens, CRISPR base-editing mutagenesis screens targeting WRN, targeted sequencing of resistance-associated variants, bulk RNA sequencing, and whole-genome sequencing. The datasets deposited in EGA comprise raw sequencing files from CRISPR-Cas9 knockout screens, CRISPR base-editing screens, targeted DNA sequencing, RNA-seq experiments, and whole-genome sequencing of parental and drug-treated cell populations, including models with spontaneously acquired resistance. These data enable investigation of WRN synthetic lethality, genetic modifiers of WRNi response, and genomic alterations emerging under selective pressure.

  Dataset EGAD00001015822

• Molecular QTLs of Human umbilical vein endothelial cells (HUVECs)

  We aim to characterise the range of phenotypic variation in gene expression, epigenetic regulation and intermediate functional phenotypes and its underlying genetic determinants in primary Human umbilical vein endothelial cells (HUVECs) samples We will measure gene expression by RNA sequencing (RNA-seq), genome functionality by ATAC-sequencing (ATAC-seq, to determine which regions are in an open chromatin state) and by determining H3 lysine 27acetylation (H3K27ac), a marker of active transcriptional enhancers, localisation genome wide by chromatin immunoprecipitation coupled with sequencing (ChIP-seq).

  Dataset EGAD00001016140

• Association of OXTR and AVPR1A Genetic Variation with Empathy and Dark Triad Traits in a Non-Clinical Human Sample

  This study investigates associations between variation in OXTR and AVPR1A, empathy, and Dark Triad personality traits in 506 participants from a non-clinical human sample. OXTR rs53576 and rs2254298 were genotyped using TaqMan assays, while AVPR1A RS1 and RS3 microsatellites were characterized by capillary electrophoresis and fragment-length analysis. Empathy was assessed using the Interpersonal Reactivity Index (IRI), and Machiavellianism, narcissism, and psychopathy were assessed using the Short Dark Triad (SD3). The study evaluates direct genotype–phenotype associations and indirect associations involving specific dimensions of empathy.

  Study EGAS50000002171

• Genomic evolution and natural history of myeloproliferative neoplasms on therapy - triple-negative-ET

  Philadelphia-negative myeloproliferative neoplasms are chronic blood neoplasms. Treatments control blood counts but disease can progress to myelofibrosis or acute myeloid leukaemia. We performed longitudinal whole-genome and targeted sequencing in 30 patients, integrating clonal dynamics with 7,986 blood counts and clinical histories. Distinct evolutionary patterns distinguished stable from progressive disease, with leukaemic transformation arising via TP53 loss, stepwise driver mutation acquisition within complex clones, or emergence of independent leukaemic clones. In contrast, stable disease showed long-term clonal equilibrium without new drivers. Phylogenetic analysis using 203 whole-genomes of haematopoietic colonies revealed age-appropriate polyclonal haematopoiesis in triple-negative essential thrombocythaemia and germline predisposition to thrombocytosis, supporting non-neoplastic origins. Therapy-associated mutagenesis was observed, including C>G mutations following azacitidine and characteristic T>A/T>G after hydroxycarbamide exposure in blood cells, although not in skin where UV damage predominated. These findings demonstrate progression is genomically encoded years in advance and support serial monitoring and further study of treatment-related mutagenesis.

  Dataset EGAD00001016066

• Genomic evolution and natural history of myeloproliferative neoplasms on therapy - MPN_bulk

  Philadelphia-negative myeloproliferative neoplasms are chronic blood neoplasms. Treatments control blood counts but disease can progress to myelofibrosis or acute myeloid leukaemia. We performed longitudinal whole-genome and targeted sequencing in 30 patients, integrating clonal dynamics with 7,986 blood counts and clinical histories. Distinct evolutionary patterns distinguished stable from progressive disease, with leukaemic transformation arising via TP53 loss, stepwise driver mutation acquisition within complex clones, or emergence of independent leukaemic clones. In contrast, stable disease showed long-term clonal equilibrium without new drivers. Phylogenetic analysis using 203 whole-genomes of haematopoietic colonies revealed age-appropriate polyclonal haematopoiesis in triple-negative essential thrombocythaemia and germline predisposition to thrombocytosis, supporting non-neoplastic origins. Therapy-associated mutagenesis was observed, including C>G mutations following azacitidine and characteristic T>A/T>G after hydroxycarbamide exposure in blood cells, although not in skin where UV damage predominated. These findings demonstrate progression is genomically encoded years in advance and support serial monitoring and further study of treatment-related mutagenesis.

  Dataset EGAD00001016067

• Genomic evolution and natural history of myeloproliferative neoplasms on therapy - SCC_CALRmutated ET

  Philadelphia-negative myeloproliferative neoplasms are chronic blood neoplasms. Treatments control blood counts but disease can progress to myelofibrosis or acute myeloid leukaemia. We performed longitudinal whole-genome and targeted sequencing in 30 patients, integrating clonal dynamics with 7,986 blood counts and clinical histories. Distinct evolutionary patterns distinguished stable from progressive disease, with leukaemic transformation arising via TP53 loss, stepwise driver mutation acquisition within complex clones, or emergence of independent leukaemic clones. In contrast, stable disease showed long-term clonal equilibrium without new drivers. Phylogenetic analysis using 203 whole-genomes of haematopoietic colonies revealed age-appropriate polyclonal haematopoiesis in triple-negative essential thrombocythaemia and germline predisposition to thrombocytosis, supporting non-neoplastic origins. Therapy-associated mutagenesis was observed, including C>G mutations following azacitidine and characteristic T>A/T>G after hydroxycarbamide exposure in blood cells, although not in skin where UV damage predominated. These findings demonstrate progression is genomically encoded years in advance and support serial monitoring and further study of treatment-related mutagenesis.

  Dataset EGAD00001016068

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

  Biopsies from the terminal ileum and rectum of healthy individuals and terminal ileum and blood from Crohns disease patients are collected and processed single cells and processed for single-cell RNA-sequencing using 10X Genomics 3 v3 and v3.1 and Illumina sequencing. 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 EGAD00001016069

• Universidad Autónoma de Madrid Human Behavioural Genetics Data Access Committee

  Data Access Committee responsible for reviewing and managing access requests for controlled-access human genetic and behavioural phenotype data generated within research conducted at Universidad Autónoma de Madrid (UAM). The data originate from non-clinical research participants and include genetic polymorphism data and associated behavioural and psychological phenotype measures. The DAC will assess data access requests in accordance with participant consent, applicable data protection requirements, and the corresponding EGA Data Access Policy.

  Dac EGAC50000001178

• WES fastq files of IPDGC UK cohort

  As part of the International Parkinson's Disease Genomics Consortium, exomes of Parkinson's disease (PD) patients and healthy controls were sequenced to study the genetic etiology of PD. This UK cohort consists of 70 PD patients. Researchers can apply for access to fastq files for this cohort.

  Dataset EGAD00001003096

• December 2016 data update (bam/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.

  December 2016 data update (bam/fastq for WGBS on samples CEMT0062, CEMT0068, CEMT0072, CEMT0086, CEMT0087) 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 EGAD00001003122

• GeDi Dovetail Hi-C assay

  The Jackson Laboratory Genetic Discovery (GeDi) Human Induced Pluripotent Stem Cell (hiPSC) Resource provides a collection of well-characterized clonal hiPSC lines derived from genetically diverse, healthy male and female donors. These lines and their associated genomic and transcriptomic data are made available for unrestricted academic and commercial research. The initial release includes eight hiPSC lines with whole-genome sequencing, DNA methylation, RNA-seq, and genotyping data, with additional lines and data types to follow. This resource enables studies of how human genetic background and sex influence molecular phenotypes, differentiation potential, and drug responses.

  Dataset EGAD50000002871

• GeDi bulk RNAseq

  The Jackson Laboratory Genetic Discovery (GeDi) Human Induced Pluripotent Stem Cell (hiPSC) Resource provides a collection of well-characterized clonal hiPSC lines derived from genetically diverse, healthy male and female donors. These lines and their associated genomic and transcriptomic data are made available for unrestricted academic and commercial research. The initial release includes eight hiPSC lines with whole-genome sequencing, DNA methylation, RNA-seq, and genotyping data, with additional lines and data types to follow. This resource enables studies of how human genetic background and sex influence molecular phenotypes, differentiation potential, and drug responses.

  Dataset EGAD50000002872

• GeDi Short-read genomic processed data through DRAGEN

  The Jackson Laboratory Genetic Discovery (GeDi) Human Induced Pluripotent Stem Cell (hiPSC) Resource provides a collection of well-characterized clonal hiPSC lines derived from genetically diverse, healthy male and female donors. These lines and their associated genomic and transcriptomic data are made available for unrestricted academic and commercial research. The initial release includes eight hiPSC lines with whole-genome sequencing, DNA methylation, RNA-seq, and genotyping data, with additional lines and data types to follow. This resource enables studies of how human genetic background and sex influence molecular phenotypes, differentiation potential, and drug responses.

  Dataset EGAD50000002873