3955 results for "*geneti*"

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• Separation of chronic myeloid leukemia stem cells from normal hematopoietic stem cells at single-cell resolution

  We provide whole exome DNA sequening data in fastq format for 23 clinical samples of chronic myeloid leukemia stem cells (CML-SC) plus two buccal swipes derived normal samples. CML samples are comprised of 4 to 8 replicates from two patients, at diagnosis and after treatment. Single CML stem cells before treatment and single non-transformed hematopoietic stem cells (HSC) at remission were selected from bone marrow samples by FACS, according to newly identified genetic markers CD33+CD26+ at diagnosis and CD33+CD26-/CD33-CD26- at remission. WES libraries of colony forming assays derived CML-SC and HSC populations were prepared using Agilent SureSelect Human All Exon V6 kit and sequenced running 150 cycles (2x 75bp paired-end) on an Illumina NextSeq 500 platform.

  Dataset EGAD00001009847

• Population-based analysis of POT1 variants in a cutaneous melanoma case-control cohort

  Pathogenic germline variants in the protection of telomeres 1 gene (POT1) have been associated with predisposition to a range of tumor types, including melanoma, glioma, leukemia and cardioangiosarcoma. We sequenced all coding exons of the POT1 gene in 2,929 European-descent melanoma cases and 3,298 controls, identifying 43 protein-changing genetic variants. We performed functional studies on each of these variants and explored their possible contribution to disease risk.

  Dataset EGAD00001009848

• Genetic landscape of Extranodal NK/T-cell lymphoma

  Whole-exome sequence (WES) data of tumor-normal pairs from 40 ENKTCL patients and RNA sequence (RNA-seq) data of tumors from 20 ENKTCL patients.

  Dataset EGAD00001009852

• RNAseq data

  RNAseq FASTq files from 797 tumors from AVANT. Sequencing libraries were generated with the TruSeq Stranded Total RNA kit (Illumina) following ribosomal RNA (rRNA) depletion with the Ribo-Zero Gold kit (Illumina). The libraries were sequenced on the HiSeq4000 (Illumina) with a sequencing protocol of 75 bp paired-end sequencing. Note: 10 samples used in the original publication were excluded from this upload due to regulations from the Human Genetics Resources Administration of China (HGRAC).

  Dataset EGAD00001009728

• Cancers of Unknow Primary

  genetic data of 14 rigorously selected CUP samples

  Dataset EGAD00001009426

• 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

• Timing chromosomal amplification events using patterns of somatic mutations in high hyperdiploid acute lymphoblastic leukemia

  This dataset included 19 paired diagnostic and remission samples with high hyperdiploid acute lymphoblastic leukemia (ALL) that were collected from four different cohorts: the Division of Clinical Genetics, Lund University, Sweden. All samples were subjected to whole genome sequencing using the Illumina HiSeqX platform. Paired-end sequencing (2x150bp) was done to ~60x coverage for diagnostic samples and ~30x coverage for remission samples. The paired-end reads were aligned to the human reference genome GRCh37 (ftp://ftp.ncbi.nlm.nih.gov/genomes/refseq/vertebrate_mammalian/Homo_sapiens/all_assembly_versions/GCF_000001405.25_GRCh37.p13/GCF_000001405.25_GRCh37.p13_genomic.fna.gz) by the Burrows-Wheeler Aligner tool (version 0.7.17). Duplicate reads marking and local realignment were performed by GATK (version 4.0.11.0).

  Dataset EGAD00001010103

• 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

• Genetic determinants of monocyte splicing are enriched for disease susceptibility loci including for COVID-19

  These data correspond to samples used in the following papers: 1. GWAS and meta-analysis identifies 49 genetic variants underlying critical Covid-19 2. Genetic determinants of monocyte splicing are enriched for disease susceptibility loci including for COVID-19. 3. Identification of Genetic Determinants of Transcriptional Response to Metformin in Primary Human Monocytes. They are the raw RNA sequencing files as used in all downstream analysis.

  Dataset EGAD00001010176

• Somatic L1 retrotransposition in normal colorectal epthelium

  Throughout an individual’s lifetime, genomic alterations accumulate in somatic cells. However, the mutational landscape induced by retrotransposition of long interspersed nuclear element-1 (L1), a widespread mobile element in the human genome, is poorly understood in normal cells. Here, we explored the whole-genome sequences of 406 normal colorectal clones, 12 MUTYH-associated adenomatous clones, and 19 matched colorectal cancer tissues. In addition, we analyzed promoter DNA methylation status of retrotransposition-competent L1 (in 139 clones) and read-through RNA expression profiles (in 116 clones) to investigate the epigenetic regulation of L1 activity.

  Dataset EGAD00001010183

• Genomic Analysis of a Metastatic Fusion-negative Embryonal Rhabdomyosarcoma

  Autopsy-derived, later snap-frozen tissue fragments from a 5-year-old female with recurrent metastatic fusion-negative embryonal rhabdomyosarcoma (RMS) primary tumor of the left thigh were analyzed. No quality matched tissue was available. Prior panel analysis identified 2 prominent genetic changes: NRAS Q61K, PIK3CA H1047R, CDKN2A/B loss, and ERBB3 overexpression.

  Dataset EGAD00001009973

• Human Origins array data for 1510 individuals

  Genotype data typed on the Human Origins array for 1510 individuals published in "Dense sampling of ethnic groups within African countries reveals fine-scale genetic structure and extensive historical admixture."

  Dataset EGAD00001010015

• CRUK-ICGC Prostate DNA Methylation Sequencing Dataset (Prostatectomy Batches 1-6)

  This dataset includes Illumina EPIC Capture Sequencing Data of 376 samples from 188 men with prostate cancer. Samples were taken from primary tissue obtained at prostatectomy, with matched pathologically assessed non-cancer control material. This DNA methylation data includes donors and samples included in previously published WGS datasets (from CRUK-ICGC batches 1 to 3 [EGAD00001001116] and batches 4 to 6 [EGAD00001003225]; including the majority of donors used in Wedge et al, Nature Genetics 2018 [PMID: 29662167]). The targeted DNA methylation sequencing data in this EGA dataset were generated using the Illumina TruSeq methyl capture method (EPICseq), covering over 3.3 million CpGs in the human genome, representing a total targeted hybridisation capture panel of 107Mbp. According to the EPICseq protocol, DNA samples extracted from prostatectomy tissue samples were enriched for target regions using hybridisation capture, prior to bisulfite conversion, amplification and sequencing in pools of 12 samples (150 single end reads over two Illumina HiSeq4000 lanes). This approach generated DNA methylation profiles from prostate cancer and control samples at base-pair resolution across millions of CpGs in the human genome.

  Dataset EGAD00001010184

• Tumour evolvability metrics predict recurrence in advanced localised prostate cancer (normal data)

  There is a need for quantitative measurements of evolutionary metrics in controlled clinical trials with long term follow-up information. This is particularly true in advanced localised prostate cancer, which can recur more than a decade after diagnosis. Here we mapped genomic intra-tumour heterogeneity in 642 tumour samples from 114 patients who took part in the IMRT and DELINEATE clinical trials, for which full clinical information and 12y median follow-up was available. We concomitantly assessed phenotypic (morphological) heterogeneity using Deep Learning in 1,923 histological sections from 250 IMRT patients (fully overlapping with the genetic set). This study shows that combining genomics with AI-aided histopathology in clinical trials leads to novel clinical biomarkers. This EGA repository contains data produced from tumour samples using low coverage whole genome sequencing and a prostate cancer specific gene panel data following compression of unique molecular identifiers.

  Dataset EGAD00001010295

• Duplexseq of the interstrand crosslinks_WGS

  One of the most dangerous forms of DNA damage are interstrand crosslinks (ICLs), which covalently crosslink the two strands of the DNA double helix. The repair of these lesions is crucial for cellular survival due to their ability to block transcription and DNA replication. Initially, the major pathway that has been described in ICL repair involves a network of 22 genes that are mutated in a severe human genetic disease known as Fanconi Anemia (FA). Using synthetic lethality screens in the near-haploid human HAP1 cell line, we recently identified two potentially novel regulators of ICL repair, C1orf112 and THAP12. Loss of C1orf112 and THAP12 causes hypersensitivity to ICL-inducing DNA damaging agents, such as Mitomycin C (MMC). Additionally, C1orf112-depleted cells show elevated levels of micronuclei and accumulation of DNA damage in S-phase. To better understand how C1orf112 and THAP12 mediate the repair of ICLs, we want to perform mutational signature analysis, using the BotSeq method. Therefore, WT, C1orf112 and THAP12 knockout cells were cultured in vehicle or MMC treated conditions for 10 days and the genomic DNA was isolated. FANCA and FANCD2 knockout cells are taken along as controls in this experimental setting. . This dataset contains all the data available for this study on 2023-04-20.

  Dataset EGAD00001010298

• Raw data for "Spatial and temporal transcriptomics of medulloblastoma with chromothripsis identifies multiple genetic clones that resist to treatment and lead to relapse"

  FASTQ files from Illumina sequencing of 10x Visium experiments.

  Dataset EGAD00001010260

• Tumour evolvability metrics predict recurrence in advanced localised prostate cancer (tumour data)

  There is a need for quantitative measurements of evolutionary metrics in controlled clinical trials with long term follow-up information. This is particularly true in advanced localised prostate cancer, which can recur more than a decade after diagnosis. Here we mapped genomic intra-tumour heterogeneity in 642 tumour samples from 114 patients who took part in the IMRT and DELINEATE clinical trials, for which full clinical information and 12y median follow-up was available. We concomitantly assessed phenotypic (morphological) heterogeneity using Deep Learning in 1,923 histological sections from 250 IMRT patients (fully overlapping with the genetic set). This study shows that combining genomics with AI-aided histopathology in clinical trials leads to novel clinical biomarkers. This EGA repository contains data produced from tumour samples using low coverage whole genome sequencing and a prostate cancer specific gene panel data following compression of unique molecular identifiers.

  Dataset EGAD00001010274

• Influence of the Microbiome on Epigenetic Mechanisms in IBD

  Live CD4 T cells were sorted from inflamed and non-inflamed tissue samples of IBD patients or from healthy and IBD blood samples. ATAC-Seq libraries were generated from live CD4 T cells sorted from i) inflamed and non-inflamed tissue samples, ii) healthy and IBD blood samples, or from iii) CD4 T cell subsets polarised from healthy blood samples. After isolating crude nuclei, live CD4+ T cells were treated with Tagment DNA buffer and Tagment DNA Enzyme (Nextera DNA Library Prep Kit, Illumina), and then the DNA was purified by MinElute PCR Purification Kit (Qiagen). Transposed DNA fragments were amplified using specific adapters followed by purification with MinElute PCR Purification Kit (Qiagen). Fragments from 240-360pb were selected in the PippinHT system (Sage Science). The quality of the library and its DNA concentration were assessed by Bioanalyzer instruments (Agilent Technologies) and ultimately submitted for sequencing using Illumina HiSeq 2500 sequencer, V4 chemistry. On the other hand, single cell RNA-Seq libraries were generated exclusively from inflamed and non-inflamed tissue samples of Crohn’s disease patients. Briefly, live CD4 T cells were captured and encapsulated before cDNA amplification using the 10X Genomics Chromium Platform. Samples were prepared as outlined by 10x genomics Single Cell 3’ Reagent Kits v2 user guide. Samples were sequenced on a HiSeq 2500 with the following run parameters: Read 1 – 26 cycles, read 2 – 98 cycles, index 1 – 8 cycles.

  Dataset EGAD00001011066

• The Genetic Landscape of Ocular Adnexa MALT Lymphoma Reveals Frequent Aberrations in NFAT and MEF2B Signaling Pathways

  69 OAMZL patients were sequenced on the Illumina platform. The data files are available in BAM format.

  Dataset EGAD00001011067

• Clonal dynamics after allogeneic haematopoietic cell transplantation using genome-wide somatic mutations - WGS

  Allogeneic haematopoietic cell transplantation (HCT) replaces the stem cells responsible for blood production with those harvested from a donor, and is received by 40,000 patients worldwide each year. To quantify dynamics of long-term stem cell engraftment, we sequenced whole genomes of 2,824 single-cell-derived haematopoietic colonies from blood samples of 10 donor-recipient pairs taken 9-31 years after HLA-matched sibling HCT. With younger donors, 10,000-50,000 stem cells had engrafted and were still contributing to haematopoiesis at time of sampling, but estimates were 10-fold lower with older donors. Engrafted stem cells made multilineage contributions to myeloid, B-lymphoid and T-lymphoid populations, although individual clones often showed biases towards one or other mature cell type. Recipients had lower clonal diversity than matched donors, equivalent to ~10-15 years of additional ageing, arising from up to 25-fold greater expansion of stem cell clones. An HCT-related population bottleneck alone could not explain these differences: instead, phylogenetic trees evinced two distinct modes of HCT-specific selection. In 'pruning selection', cell divisions underpinning recipient-enriched clonal expansions had occurred in the donor, preceding transplant - their selective advantage derived from preferential mobilisation, harvest, survival ex vivo or initial homing. In 'growth selection', cell divisions underpinning clonal expansion occurred through proliferative advantage in the recipient's marrow after homing - clones with multiple driver mutations especially demonstrated this pattern. Uprooting stem cells from their native environment and transplanting them to foreign soil exaggerates selective pressures, distorting and accelerating the loss of clonal diversity compared to the unperturbed haematopoiesis of donors.

  Dataset EGAD00001010872

• Clonal dynamics after allogeneic haematopoietic cell transplantation using genome-wide somatic mutations - TGS

  Allogeneic haematopoietic cell transplantation (HCT) replaces the stem cells responsible for blood production with those harvested from a donor, and is received by 40,000 patients worldwide each year. To quantify dynamics of long-term stem cell engraftment, we sequenced whole genomes of 2,824 single-cell-derived haematopoietic colonies from blood samples of 10 donor-recipient pairs taken 9-31 years after HLA-matched sibling HCT. With younger donors, 10,000-50,000 stem cells had engrafted and were still contributing to haematopoiesis at time of sampling, but estimates were 10-fold lower with older donors. Engrafted stem cells made multilineage contributions to myeloid, B-lymphoid and T-lymphoid populations, although individual clones often showed biases towards one or other mature cell type. Recipients had lower clonal diversity than matched donors, equivalent to ~10-15 years of additional ageing, arising from up to 25-fold greater expansion of stem cell clones. An HCT-related population bottleneck alone could not explain these differences: instead, phylogenetic trees evinced two distinct modes of HCT-specific selection. In 'pruning selection', cell divisions underpinning recipient-enriched clonal expansions had occurred in the donor, preceding transplant - their selective advantage derived from preferential mobilisation, harvest, survival ex vivo or initial homing. In 'growth selection', cell divisions underpinning clonal expansion occurred through proliferative advantage in the recipient's marrow after homing - clones with multiple driver mutations especially demonstrated this pattern. Uprooting stem cells from their native environment and transplanting them to foreign soil exaggerates selective pressures, distorting and accelerating the loss of clonal diversity compared to the unperturbed haematopoiesis of donors.

  Dataset EGAD00001010874

• Clonal selection after gene therapy in sickle cell disease

  While gene therapy (GT) provides a potentially curative treatment option for patients with sickle cell disease (SCD), the occurrence of myeloid malignancies in clinical trials has prompted concern. To interrogate potential mechanisms underlying increased cancer risk, we used hematopoietic stem cell (HSC) clonal tracking by whole genome sequencing (WGS) to map the somatic mutation and clonal landscape of 2,592 gene modified as well as unmodified single stem and progenitor cells from six SCD patients undergoing gene therapy (7-26 years old, average 12.7× depth). Pre-GT phylogenetic trees in SCD were highly polyclonal and mutation burdens per cell were elevated in some, but not all, patients. Post-GT, no clonal expansions were identified. However, an increased frequency of driver mutations associated with myeloid neoplasms or clonal hematopoiesis (DNMT3A- and EZH2-mutated clones in particular) were seen in both genetically modified and unmodified cells suggested positive selection of mutant clones during gene therapy. This work sheds light on the mutation landscape and HSC clonal dynamics in gene therapy for SCD and highlights enhanced fitness of some HSCs harboring pre-existing driver mutations following gene therapy. Future studies should define the long-term fate of mutant clones including any contribution to expansions associated with myeloid neoplasms.

  Dataset EGAD00001010913

• Clonal selection after gene therapy in sickle cell disease

  While gene therapy (GT) provides a potentially curative treatment option for patients with sickle cell disease (SCD), the occurrence of myeloid malignancies in clinical trials has prompted concern. To interrogate potential mechanisms underlying increased cancer risk, we used hematopoietic stem cell (HSC) clonal tracking by whole genome sequencing (WGS) to map the somatic mutation and clonal landscape of 2,592 gene modified as well as unmodified single stem and progenitor cells from six SCD patients undergoing gene therapy (7-26 years old, average 12.7× depth). Pre-GT phylogenetic trees in SCD were highly polyclonal and mutation burdens per cell were elevated in some, but not all, patients. Post-GT, no clonal expansions were identified. However, an increased frequency of driver mutations associated with myeloid neoplasms or clonal hematopoiesis (DNMT3A- and EZH2-mutated clones in particular) were seen in both genetically modified and unmodified cells suggested positive selection of mutant clones during gene therapy. This work sheds light on the mutation landscape and HSC clonal dynamics in gene therapy for SCD and highlights enhanced fitness of some HSCs harboring pre-existing driver mutations following gene therapy. Future studies should define the long-term fate of mutant clones including any contribution to expansions associated with myeloid neoplasms.

  Dataset EGAD00001010914

• Longitudinal RNA-seq datasets from patients after abdominal surgery

  This dataset consists of RNA-seq data of 126 whole-blood samples derived from patients after abdominal surgery. Total-RNA collected preoperatively and at 3-time points postoperatively (2-6, 24 and 48hrs) were analysed using RNA-sequencing. RNA was collected in PAXGene (Qiagen) tubes and extracted using the PAXGene RNA extraction kit, with a DNase step to remove contaminating DNA. Globin and ribosomal RNA were removed via a Ribo-zero kit (Illumina) and library preparation was carried out using the TruSeq Stranded Total RNA Library Prep Kit (Illumina). Next generation sequencing was performed on the NovaSeq sequencing platform (Illumina) at the Wellcome Centre for Human Genetics (WCHG) in Oxford.

  Dataset EGAD00001011102

• Whole blood RNA sequencing of individuals from Nepal

  This study utilized blood samples collected in Lalitpur, Nepal as part of the Strategic Typhoid Alliance across Africa and Asia (STRATAA) study. The dataset comprises whole blood RNAseq of 376 febrile individuals from Nepal. Blood was collected in PAXgene tubes and sent to Monash University (Melbourne, Australia) where RNA was extracted using the PAXgene Blood RNA kit before being sent to the Wellcome Sanger Institute (Hinxton, UK) for sequencing. Library prep used NEBNext Ultra II RNA custom kits on an Agilent Bravo WS automation platform with poly(A) pulldown. After PCR, plates were purified using Agencourt AMPure XP SPRI beads and libraries were quantified using Biotium Accuclear Ultra high sensitivity dsDNA Quantitative kits. Pooled libraries were normalised to 2.8 nM. Samples were globin depleted using KAPA RNA HyperPrep with RiboErase. Libraries were then subjected to 2x100bp paired-end sequencing on Illumina NovaSeq. Each library was sequenced to an average of 80 million reads. The STRATAA study was approved by the Nepal Health Research Council (NHRC, ref 283 306/2015) and OxTREC (Oxford Tropical Research Ethics Committee, ref 39-15). All participants provided informed consent for human genetic tests.

  Dataset EGAD00001011131