3931 results for "*geneti*"

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• Dataset with genome-wide array data from Algerian Amazigh (Chaoui and Mozabite) and non-Amazigh individuals

  In this study we perform a genetic characterization of different Amazigh populations in Algeria and assess the impact of recent demography on their genomes.

  Study EGAS00001007235

• 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

• H3Africa - Deciphering Developmental Disorders in Africa

  Developmental disorders are typically rare conditions, causing an impairment in physical, learning, language, or behavioural areas. Genetic heterogeneity and highly variable clinical manifestations make diagnosing developmental disorders particularly challenging. Developmental disorders are increasing in prevalence in low- and middle-income countries, partly due to effective prevention and treatment of infectious diseases leading to a decrease in childhood mortality. New sequencing technologies are used effectively in the diagnosis of rare diseases and results can impact clinical practice significantly. Despite this international trend, very little implementation of these new approaches has taken place in low-resource settings, especially in Africa. The Deciphering Developmental Disorders in Africa (DDD-Africa) study aims to take advantage of an unbiased genotype-driven approach to improve healthcare services for patients. The study aims to recruit and perform detailed clinical phenotyping and exome sequencing (ES) on 500 African patients with a developmental disorder in whom a genetic diagnosis has not been confirmed. Where available, parents are also included in sequencing efforts. The project has two active research sites in Johannesburg (South Africa) and Kinshasa (Democratic Republic of Congo) representing diversity in geography, clinical, socio-economic, genetic and environmental factors.

  Study EGAS00001008319

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

  Study EGAS00001008250

• Osteosarcoma 3D patient derived cultures to test genome-informed personalized treatment options; a feasibility study

  Background: Improving osteosarcoma treatment beyond conventional (neo)adjuvant chemotherapy and resection remains challenging. An urgent need for novel therapeutic options, particularly personalized and targeted approaches, has emerged due to high inter-patient molecular heterogeneity. A lack of representative in vitro and in vivo models impedes therapeutic development, therefore we aimed to create 3D in vitro long term culture models directly from patient material. Methods: Tumour cells from seven osteosarcoma patients were propagated in monolayer or collagen hydrogels, while whole-exome sequencing of corresponding primary tumour tissue was performed to identify potential drug targets. Established cultures were subsequently used to assess efficacy of the identified personalized treatment options. Results: Three out of seven hydrogel cultures harboured the same genetic alterations as the corresponding primary tumours. Among these, the L6565 patient line exhibited homozygous CDKN2A loss with retained Rb expression, rendering tumour cells sensitive to CDK4/CDK6 inhibition via palbociclib. This patient line was used to evaluate genome-informed therapy and to compare cell culture models of increasing complexity. Our findings demonstrate feasibility of establishing long-term patient-derived osteosarcoma cultures with a success rate of 14%. Tumour heterogeneity was reflected in advanced culture methods producing more variability in treatment response. Conclusion: These results highlight the potential of genome-informed therapies in osteosarcoma and the importance of refining culture techniques to enhance translational research and therapeutic outcomes.

  Study EGAS50000001583

• Whole-exome variant calling of individuals from the study of sepsis and acute distress respiratory syndrome in Spain

  Research study of genetic susceptibility in sepsis and acute distress respiratory syndrome (ARDS). ARDS is a lethal condition, often derived from sepsis, lacking effective targeted treatments. Growing evidence indicates that the genetic component significantly influences susceptibility and severity of ARDS. We used whole-exome sequencing data in case-control studies to characterize genetic factors associated with an increase of ARDS risk.

  Study EGAS50000001119

• Multi-omic analysis of Down Syndrome in thyroid

  Background: Down syndrome (DS) is a chromosomal disorder characterized by trisomy of chromosome 21 and is associated with various health problems. Congenital thyroid dysfunction is a common endocrine abnormality in DS, but its exact cause remains unknown. This work aimed at studying the etiology of congenital thyroid dysfunction in DS. Methods: Thyroid tissue of fetuses with DS (n=4) and fetuses without a genetic/developmental abnormality (n=5) were analyzed using histopathological evaluation, RNA sequencing (RNA-seq), and DNA methylation (DNAm) profiling. Results: Histological examination showed abnormally developed DS thyroid tissue compared to non-DS/healthy tissue. RNA-seq analysis showed numerous differences in gene expression between DS and healthy thyroid tissue, including significant downregulation of thyroid genes FOXE1, IYD and DIO2. Gene set enrichment analysis showed disruption of vital cellular processes and functions in DS fetal thyroid tissue. Analysis of DNAm and expression quantitative trait methylation (eQTM) analysis identified functional and biologically relevant associations, that can be linked to plausible disrupted pathways in DS. Conclusions: Based on these observations, we conclude that congenital non-autoimmune thyroid dysfunction in DS is probably a DS-specific form of thyroid dysfunction, characterized by abnormal thyroid development, altered expression of genes that regulate thyroid development and hormone production, and altered expression and DNAm of genes pertaining to numerous vital pathways leading to significant metabolic disturbances. The disturbances as investigated by multi-omics analyses (RNA-seq, DNAm and eQTM analyses) are widely spread over the genome, and presumably caused by the direct and downstream effects of overexpressed chromosome 21 genes (dosage effect), and (epi)genomic disturbances.

  Study EGAS00001007677

• Ultra-long sequencing for contiguous haplotype resolution of the human immunoglobulin heavy chain locus

  Genetic diversity within the human immunoglobulin heavy chain (IGH) locus influences the expressed antibody repertoire and susceptibility to infectious and autoimmune diseases. However, repetitive sequences and complex structural variation pose significant challenges for large-scale characterization. Here, we introduce a method that combines Oxford Nanopore ultra-long sequencing and adaptive sampling with a bioinformatic pipeline to produce haplotype-resolved, annotated IGH assemblies. Notably, our strategy overcomes prior limitations in phasing resolution, enabling single-contig haplotype assemblies that span the entire IGH locus. We applied this method to four individuals and validated the accuracy of the IGH assemblies using Pacific Biosciences HiFi reads, demonstrating near-complete sequence congruence, detecting only indels with a high degree of confidence. Moreover, when applied to the reference material HG002, our pipeline revealed no base differences and a limited number of indels compared with the Telomere-to-Telomere genome benchmark across the IGH region. Importantly, in the four individuals, our approach uncovered 30 novel alleles and previously uncharacterized large structural variants, including a 120 kb duplication spanning IGHE to IGHA1 and an expanded seven-copy IGHV3-23 gene haplotype. These findings underscore the power of our method to resolve the full complexity of the IGH locus and uncover previously unrecognized variants that may affect immune function and disease susceptibility. Thus, our method provides a strong basis for future immunological research and translational applications.

  Study EGAS50000001042

• MorphoITH: A Framework for Deconvolving Intra-Tumor Heterogeneity Using Tissue Morphology

  This study introduces MorphoITH, a framework for deconvolving intra-tumor heterogeneity (ITH) in clear cell renal cell carcinoma (ccRCC) based on tissue morphology from histopathological slides. The study tested MorphoITH's ability to capture different aspects of morphology and to reflect genetic ITH. The data deposited here is derived from a morphology guided multi-regional sequencing dataset used to study the relationship between morphology and genetic evolution. This dataset consists of whole exome sequencing of tumor from multiple sites and adjacent normal samples which were collected from two patients treated in affiliated hospitals of the University of Texas Southwestern Medical Center (UTSW), including Parkland Hospital.

  Study EGAS50000001064

• MutWP4__CRUK_Grand_Challenge_Mutographs_of_Cancer__Mutagen_treated_organoids

  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.

  Study EGAS00001004873

• MutWP4__CRUK_Grand_Challenge_Mutographs_of_Cancer__organoid_control_WGS

  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.

  Study EGAS00001005449

• MutWP1__CRUK_Grand_Challenge__normal_kidney_Nanoseq

  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. Non-tumour DNA is also studied for some cancer types. 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.

  Study EGAS00001005451

• MutWP1__CRUK_Grand_Challenge__matched_blood_Nanoseq

  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. Non-tumour DNA is also studied for some cancer types. 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.

  Study EGAS00001006774

• Epigenetics Imagine Arrays

  Dac EGAC00001003633

• BE_screens_of_WRN_gene_in_MSI_models

  We will take advantage of a base-editing screening strategy to engineer mutations in the WRN gene by deep mutagenesis. Two MSI-H cell lines sensitive to WRNi will be genetically modified to express doxycycline-inducible ABE and CBE base editors through a knock-in strategy. Moreover, we will design a pooled library of ~4000 gRNAs targeting the WRN gene plus appropriate controls gRNAs. Library-transduced cells will be selected with WRNi to identify WRN mutations able to interfere with the activity of WRNi.

  Study EGAS00001006872

• Discordant_Monozygotic_Twins_ALS (Epigenetics)

  We conducted a multi-omics study on a monozygotic twin pair discordant for amyotrophic lateral sclerosis. Here, we submit epigenetic data from EPIC array.

  Study EGAS00001008053

• Discordant_Monozygotic_Twins_ALS (Epigenetics)

  We conducted a multi-omics study on a monozygotic twin pair discordant for amyotrophic lateral sclerosis. Data refers to 7 samples that are technical replicates from biological samples collected from the twins at two different time points (T1 and T2).

  Dataset EGAD00010002716

• Single-nuclei histone modification profiling of the adult human central nervous system unveils epigenetic memory of developmental programs

  Here, we profile the adult human CNS from distinct regions, sex and ages, for chromatin accessibility at the single-nuclei level. Tissue was collected from 20 different donors (10 male, 10 female) within the ages of 34 to 74 years old. Each donor donated fresh frozen white matter from the following three tissue regions: primary motor cortex (Brodmann area 4, BA4), arbor vitae cerebelli (CB) and fasciculi cuneatus and gracilis from and cervical spinal cord (CSC). Tissue was processed semi-randomly, ensuring that each batch of experiments had a representation of both sexes and all three tissue regions. Completed libraries were again randomly multiplexed during sequencing to minimize batch effects.

  Study EGAS50000000283

• Reference epigenomes generated as part of the International Human Epigenomics Consortium (IHEC)

  The Centre for Epigenome Mapping Technologies (CEMT) is an epigenome sequencing platform funded by the Canadian Institutes of Health Research (CIHR) and Genome BC as part of the Canadian Epigenetics, Environment and Health Research Consortium (CEEHRC). CEMT aims to produce 100 human reference epigenomes, each comprising the following datasets: whole genome; whole genome bisulfite and oxidative bisulfite; transcriptome; microRNA; and chromatin immunoprecipitation (ChIP)-seq for the core chromatin marks (H3K4me1, H3K4me3, H3K9me3, H3K27me3, H3K36me3, and H3K27ac).CEEHRC is a full member of the International Human Epigenomics Consortium (IHEC), which aims to coordinate the production of 1,000 reference maps of human epigenomes for key cellular states relevant to health and diseases. As such, all datasets submitted by the CEMT platform conform to IHEC assay standards and metadata guidelines.

  Study EGAS00001000552

• Genetic and Functional Drivers of Diffuse Large B Cell Lymphoma

  Diffuse large B cell lymphoma (DLBCL) is the most common hematologic malignancy and is characterized by a striking degree of heterogeneity. We enrolled a total of 1001 DLBCL patients and comprehensively defined the landscape of genetic mutations, copy number alterations and expression through whole-exome and transcriptome sequencing. We identified 150 genetic drivers of DLBCL including many novel, clinically relevant genes (e.g. SPEN, SETD1B and KLHL14). Genetic drivers were highly enriched among essential genes identified by CRISPR screening in DLBCL cell lines including those of immediate potential therapeutic relevance such as MTOR, SYK, SF3B1 and XPO1. RHOA emerged as a critical driver gene from our genetic analysis and CRISPR screen; we further delineated its functional role in vitro and in vivo models to define its role as an essential oncogene in DLBCL. Our work thus identifies the functional landscape of genetic drivers and their clinical and therapeutic relevance in DLBCL patients.

  Study EGAS00001002606

• Human islet 3D chromatin maps provide insights into type 2 diabetes

  The transcriptional output of each cell type is controlled by thousands of enhancers, many of which contain genetic risk variants for common diseases such as type 2 diabetes (T2D). To gain insight into how enhancer variation influences diabetes risk, we created promoter capture Hi-C maps in human pancreatic islets. This linked diabetes-associated islet enhancers with their target genes, often located hundreds of kilobases away. We identified hubs that show spatial and functional connections between enhancersand target genes related to islet function and diabetes. We demonstrate that genetic variants distributed across hub enhancers have a major impact on T2D heritability, and use this knowledge to identify individuals in whom islet regulatory variation has a prominent role in T2D risk. Our results demonstrate the importance of 3D chromatin architecture for molecular interpretation of T2D genetic association signals, and define genomic spaces that harbor a distinct component of the T2D polygenic burden.

  Study EGAS00001002917

• Immune cell atlas of environmental and ancestral diversity in Indonesia [scRNAseq]

  Island Southeast Asia (ISEA) remains consistently underrepresented in large-scale human genomic resources despite its rich ancestral and lifestyle diversity. The region's complex population history and environmental/pathogen pressures could have shaped its populations' unique immune responses. Here, we generated single-cell PBMC profiles from 199 Indonesians sampled across four populations in the islands of Bali and New Guinea. The dataset consists of low-pass whole genome sequencing and pooled single-cell PBMC transcriptome sequencing. These groups capture diversity in regional genetic ancestries (West ISEA-like and Papuan-like) and lifestyle contrasts (urban versus rural communities in Bali; highland versus lowland communities in New Guinea), providing a window into how ancestry and environment jointly shape immune variation across ISEA. Together, this study provides the first large-scale single-cell immune atlas of ISEA, highlighting how ancestral and environmental diversity jointly shape human immunity in this globally important yet understudied region.

  Study EGAS50000001656

• Immune cell atlas of environmental and ancestral diversity in Indonesia [WGS]

  Island Southeast Asia (ISEA) remains consistently underrepresented in large-scale human genomic resources despite its rich ancestral and lifestyle diversity. The region's complex population history and environmental/pathogen pressures could have shaped its populations' unique immune responses. Here, we generated single-cell PBMC profiles from 199 Indonesians sampled across four populations in the islands of Bali and New Guinea. The dataset consists of low-pass whole genome sequencing and pooled single-cell PBMC transcriptome sequencing, including T-cell receptor (TCR). These groups capture diversity in regional genetic ancestries (West ISEA-like and Papuan-like) and lifestyle contrasts (urban versus rural communities in Bali; highland versus lowland communities in New Guinea), providing a window into how ancestry and environment jointly shape immune variation across ISEA. Together, this study provides the first large-scale single-cell immune atlas of ISEA, highlighting how ancestral and environmental diversity jointly shape human immunity in this globally important yet understudied region.

  Study EGAS50000001655

• Immune Cell Atlas of Environmental and Ancestral Diversity in Indonesia [TCR]

  This dataset contains single-cell TCR, individually reference-aligned data from 203 individuals representing four Indonesian populations: the general urban population of Denpasar and the traditional community of Pedawa Village in Bali, as well as the traditional community of Yoboi Village (in Lake Sentani) and Sereh Village (individuals from highland Papua residing near Lake Sentani) in Papua. The dataset was produced as part of the Immune Cell Atlas of Environmental and Ancestral Diversity in Indonesia, a study aimed at characterizing how genetic background and environmental context shape immune cell states across diverse Indonesian communities.

  Dataset EGAD50000002383