3334 results for "*geneti*"

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• Genomic landscape of oral cancers (Illumina RNA-Seq)

  Human papillomavirus (HPV) is a necessary but insufficient cause of a subset of oral squamous cell carcinomas (OSCC) that is increasing markedly in frequency. To identify contributory, secondary genetic alterations in these cancers, we used comprehensive genomics methods to compare 149 HPV-positive and 335 HPV-negative OSCC tumor/normal pairs. Different behavioral risk factors underlying the two OSCC types were reflected in distinctive genomic mutational signatures. In HPV-positive OSCC, the signatures of APOBEC cytosine deaminase editing, associated with anti-viral immunity, were strongly linked to overall mutational burden. By contrast, in HPV-negative OSCC, T>C substitutions in the sequence context 5’-ATN-3’ correlated with tobacco exposure. Universal expression of HPV E6*1 and E7 oncogenes was a sine qua non of HPV-positive OSCC. Significant enrichment of somatic mutations was confirmed or newly identified in PIK3CA, KMT2D, FGFR3, FBXW7, DDX3X, PTEN, TRAF3, RB1, CYLD, RIPK4, ZNF750, EP300, CASZ1, TAF5, RBL1, IFNGR1 and NFKBIA. Of these, many affect host pathways already targeted by HPV oncoproteins, including the p53 and pRB pathways, or disrupt host defenses against viral infections, including interferon and nuclear factor-B signaling. Frequent copy number changes were associated with concordant changes in gene expression. Chr. 11q (including CCND1) and 14q (including DICER1 and AKT1) were recurrently lost in HPV-positive OSCC, in contrast to their gains in HPV-negative OSCC. High-ranking variant allele fractions implicated ZNF750, PIK3CA and EP300 mutations as candidate driver events in HPV-positive cancers. We conclude that virus-host interactions cooperatively shape the unique genetic features of these cancers, distinguishing them from their HPV-negative counterparts.

  Study EGAS00001003237

• GCAT | Genomes for life: cohort study of the genomes of Catalonia

  The GCAT Study have recruited 20 000 participants aged 40–65 years. Participants who agreed to take part in the study completed a self-administered computer-driven questionnaire, and underwent blood pressure, cardiac frequency and anthropometry measurements. For each participant, blood plasma, blood serum and white blood cells are collected at baseline. A total of 5459 genomic profiles have been characterised by comprehensive genotyping. Genome-wide genotypes have been generated using Illumina Infinium SNP-bead array technology. We chose the Multi-Ethnic Global (MEGAEX, V.2) consortium array, a multipurpose, multiethnic genotyping array with two million selected markers (including previously described germline mutations, insertions-deletions (InDels) and SNPs).We have strictly followed the standard manufacturer recommended automated protocol for the Infinium HTS Assay scanned with a HiScan confocal scanner (Illumina, San Diego, California, USA). Genome Studio V.2011.1 has been used for raw data analysis. Genotyping was performed at the Genomics and Bioinformatics Unit of the PMPPC Institute for Health Science Research Germans Trias i Pujol, in Badalona, Spain. Future plans The first follow-up study started in December 2017 and will end by March 2018. Residences of all subjects will be geocoded during the following year. Several genomic analyses are ongoing, and metabolomic and genomic integrations will be performed to identify underlying genetic variants, as well as environmental factors that influence metabolites. http://dx.doi.org/10.1136/bmjopen-2017-018324

  Study EGAS00001003018

• Malignant mesothelioma EWAS on European prospective study

  Study EGAS00001006432

• 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

• HELIUS cohort gut microbiome batch2

  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 EGAD00001009732

• Atypical teratoid/rhabdoid tumoroids reveal subgroup-specific drug vulnerabilities - WGS

  We demonstrate that ATRT tumoroids retain subgroup-specific epigenetic and gene expression profiles

  Dataset EGAD00001009793

• Atypical teratoid/rhabdoid tumoroids reveal subgroup-specific drug vulnerabilities - RNA-Seq

  We demonstrate that ATRT tumoroids retain subgroup-specific epigenetic and gene expression profiles

  Dataset EGAD00001009794

• Distinct embryonic phylogenies and driver events of infant Wilms tumor - DNA

  Cancers of adults typically arise through progressive rounds of clonal diversification and intratumoral selective sweeps which generate a long mutational trunk with shorter subclonal branches. Here, we investigated whether tumors of young children exhibit the same phylogenetic configuration. We studied three infants, including two newborns, with the childhood kidney cancer, Wilms tumour, through whole genome sequencing of bulk tissues, of single cell derived organoids, and of microdissections. All three cancers exhibited unusual driver events, with tumours of newborns harbouring FOXR2 rearrangements, delineating a distinct variant of Wilms tumour. Phylogenetic analyses suggest that tumors were seeded in an early, possibly confined window of development. Unusually, following seeding there was extensive polyclonal diversification with little evidence of clonal sweeps, leading to a distinct phylogenetic configuration more reminiscent of normal tissues rather than of adult cancers. These findings indicate that some childhood cancers may diversify via unorthodox phylogenetic pathways.

  Dataset EGAD00001009812

• DNA-Methylation data for atypical teratoid/rhabdoid tumoroids study

  We demonstrate that ATRT tumoroids retain subgroup-specific epigenetic and gene expression profiles

  Dataset EGAD00010002400

• 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

• 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

• Genomic and transcriptomic data of glioma specimens

  Dataset consists of 207 glioma samples of WHO grades II, III and IV. Dataset consists 182 tumor derived genomic data of ~700 cancer-related and epigenetic-related genes with matched blood samples for 48 specimens. Dataset also consists transcriptomic data for 105 specimens. In total 335 bam files were deposited.

  Dataset EGAD00001006299

• 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

• 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

• 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

• Distinct embryonic phylogenies and driver events of infant Wilms tumor - RNA

  Cancers of adults typically arise through progressive rounds of clonal diversification and intratumoral selective sweeps which generate a long mutational trunk with shorter subclonal branches. Here, we investigated whether tumors of young children exhibit the same phylogenetic configuration. We studied three infants, including two newborns, with the childhood kidney cancer, Wilms tumour, through whole genome sequencing of bulk tissues, of single cell derived organoids, and of microdissections. All three cancers exhibited unusual driver events, with tumours of newborns harbouring FOXR2 rearrangements, delineating a distinct variant of Wilms tumour. Phylogenetic analyses suggest that tumors were seeded in an early, possibly confined window of development. Unusually, following seeding there was extensive polyclonal diversification with little evidence of clonal sweeps, leading to a distinct phylogenetic configuration more reminiscent of normal tissues rather than of adult cancers. These findings indicate that some childhood cancers may diversify via unorthodox phylogenetic pathways.

  Dataset EGAD00001009813

• 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

• The Natural History of Human Prostate Cancer

  Whole genome DNA sequencing was used to decrypt the phylogeny of multiple samples from distinct areas of cancer and morphologically normal tissue taken from the prostates of 3 men. For each of three different prostates, multiple tumour samples (4, 5, and 3 depending on the case) and one normal tissue sample were whole genome sequenced with a matched blood sample using the Illumiuna HiSeq platform. Tumour samples were sequenced to a target depth of 50X and normals and blood to a target depth of 30X. As of September 2020, some of the studies using these data include: Cooper et al, Nature Genetics 2015 (PMID: 25730763) Wedge et al, Nature Genetics 2018 (PMID: 29662167) Pan-Cancer Analysis of Whole Genomes, Nature 2020 (PMID: 32025007)

  Dataset EGAD00001000689

• Batches 1-3 prostatectomy analysis

  Whole Genome Sequencing Illumina HiSeq data from 95 men with prostate cancer. Samples were taken from primary tissue obtained at prostatectomy (target sequencing depth 50X) with matched blood control (target sequencing depth 30X). This data is from batches 1 to 3 and is the bulk of the data used in Wedge et al, Nature Genetics 2018 (PMID: 29662167). As of September 2020, some of the studies using these data include: Wedge et al, Nature Genetics 2018 (PMID: 29662167) Pan-Cancer Analysis of Whole Genomes, Nature 2020 (PMID: 32025007)

  Dataset EGAD00001001116

• Determination of cell specific regulatory enhancers in hematopoetic models

  The BLUEPRINT project is a large-scale project investigating epigenetic mechanisms involved in blood formation, in health and disease. The human variation workpackage (WP10, led by NS) 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. Units of 475 ml of AB will be obtained from consenting volunteers of the Cambridge BioResource (CBR), a panel of 10,000 healthy volunteers local to Cambridge who have already consented to participate in biomedical research and of whom biological samples (DNA, plasma, serum) and lifestyle data have been deposited in a repository and database, respectively. We are requesting funding from the Human Diversity project to sequence the genomes of the 200 CBR volunteers at low pass (6x coverage). Nuclei, DNA and RNA will be recovered from the purified cells and made available for RNA-seq, DNA-seq and ChIP-seq and genomic DNA for entire genome sequencing will be recovered from the DNA repository.

  Dataset EGAD00001002205

• Sequencing data for ICGC Oesophageal Adenocarcinoma tissue samples - 129_cohort

  Sequencing data for ICGC Oesophageal Adenocarcinoma tissue samples - 129_cohort EAC whole genomic sequencing data - Publication Secrier & Li et al., 2016, Nature Genetics

  Dataset EGAD00001002218

• 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

• DDD_1 hypermutated individual

  CRAM files and VCF for DDD_1 and their parents. Also de novo mutations file for hypermutated DDD_1 child as described in the manuscript ‘Genetic and chemotherapeutic influences of germline hypermutation’ by Kaplanis et al. which will be published in Nature shortly.

  Dataset EGAD00001008497

• Oropharyngeal Squamous Cell Carcinoma Mutanome

  This dataset comprises genetic variation data (as somatic indels and snvs VCFs) of 38 OPSCC tumors. WES was done using NextSeq 500 System running in 150 cycles (2x 75bp paired-end) mode. Sequence information was converted to FASTQ format using bcl2fastq v2.20.0.422. VCFs were generated using the Strelka package.

  Dataset EGAD00001009167

• Anthropological dataset 1 for The admixture histories of Cabo Verde

  Datasets used in the article "The genetic and linguistic admixture histories of the islands of Cabo Verde" by Laurent R et al. eLife 2023 (DOI: https://doi.org/10.7554/eLife.79827 - URL: https://elifesciences.org/articles/79827) File name "eGAdeposit_233CaboVerde_SampleInfo_FINAL_01062022.txt" Column 1 corresponds to individual alphanumeric codes as in the "eGAdeposit_233CaboVerde_GenotypeFile_FINAL_01062022.vcf" genotype file Column 2 corresponds to individual's biological sex as per genetic inference Column 3 corresponds to individual's self-reported age in years Column 4 corresponds to individual's self-reported cumulated number of years spent in academic or professional education

  Dataset EGAD00001008976

• Anthropological dataset 2 for The admixture histories of Cabo Verde

  Datasets used in the article "The genetic and linguistic admixture histories of the islands of Cabo Verde" by Laurent R et al. eLife 2023 (DOI: https://doi.org/10.7554/eLife.79827 - URL: https://elifesciences.org/articles/79827) File name "eGAdeposit_233CaboVerde_GEOcoordFULL_FINAL_01062022.txt" Column 1 corresponds to individual alphanumeric codes as in the "eGAdeposit_233CaboVerde_GenotypeFile_FINAL_01062022.vcf" genotype file Column 2-3 corresponds to X-Y GPS coordinates of individual's interview location in Cabo Verde Column 4-5 corresponds to X-Y GPS coordinates of individual's self-reported residence location at the time of the interview Column 6-7 corresponds to X-Y GPS coordinates of individual's self-reported birth-place location Column 8-9 corresponds to X-Y GPS coordinates of individual's self-reported paternal birth-place location Column 10-11 corresponds to X-Y GPS coordinates of individual's self-reported maternal birth-place location

  Dataset EGAD00001008977

• Linguistic utterance counts for The admixture histories of Cabo Verde

  Datasets used in the article "The genetic and linguistic admixture histories of the islands of Cabo Verde" by Laurent R et al. eLife 2023 (DOI: https://doi.org/10.7554/eLife.79827 - URL: https://elifesciences.org/articles/79827) File name "eGAdeposit_225CaboVerde_FreeSpeech_Utterance_counts_FINAL_01062022.txt" Column 1 corresponds to individual alphanumeric codes as in the "eGAdeposit_233CaboVerde_GenotypeFile_FINAL_01062022.vcf" genotype file. Note that only 225 unrelated Cabo Verdean-born individuals are considered here, out of the 233 individuals in the genotype file. See Material and Methods in Romain Laurent et al. 2022 - doi pending Each 4831 other column correspond to the respective individual's utterance count in the free speech transcribed in ALUPEC and provided as column header. See See Material and Methods in Romain Laurent et al. 2022 - doi pendingColumn 1 corresponds to individual alphanumeric codes as in the "eGAdeposit_233CaboVerde_GenotypeFile_FINAL_01062022.vcf" genotype file. Note that only 225 unrelated Cabo Verdean-born individuals are considered here, out of the 233 individuals in the genotype file. See Material and Methods in Romain Laurent et al. 2022 - doi pending Each 4831 other column correspond to the respective individual's utterance count in the free speech transcribed in ALUPEC and provided as column header. See Material and Methods in Laurent R et al. eLife 2023

  Dataset EGAD00001008978

• Genotype data for The admixture histories of Cabo Verde - genotype data

  Datasets used in the article "The genetic and linguistic admixture histories of the islands of Cabo Verde" by Laurent R et al. eLife 2023 (DOI: https://doi.org/10.7554/eLife.79827 - URL: https://elifesciences.org/articles/79827) As per Materials and Methods herein, the genotype data corresponds to 2,118,722 autosomal SNPs genotyped from the IlluminaOmni 2.5 Million BeadChip for 233 Cabo Verdean volunteer participants, family unrelated at the 2nd degree based on population genetics analyses (see Material and Methods). SNP rsID, Chromosome position and genetic position in (bp) are in Build GRCh38. Cabo Verdean individuals are designated with an alphanumeric unique code

  Dataset EGAD00001008979

• Epigenomic analysis of human dopaminergic neuron differentiation reveals LBX1, NHLH1 and NR2F1/2 as necessary for lineage specification

  Sample information: The 56 samples produced in this project come from the human iPSC line GM17602 (Coriell) where a tyrosine hydroxylase-T2A-mCherry reporter was inserted. A combination of epigenetic analysis (ATAC/ChIP) along transcriptomics.

  Dataset EGAD00001009288

• RNAseq dataset for MALT1 in MCL

  Manuscript Title: Co-targeting of BTK and MALT1 overcomes resistance to BTK inhibitors in mantle cell lymphoma Journal: Journal of Clinical Investigation Authors Vivian Changying Jiang1, Yang Liu1, Junwei Lian1, Shengjian Huang1, Alexa Jordan1, Qingsong Cai1, Fangfang Yan3, Joseph Mitchell McIntosh1, Yijing Li1, Yuxuan Che1, Zhihong Chen1, Jovanny Vargas1, Maria Badillo1, JohnNelson Bigcal1, Heng-Huan Lee1, Wei Wang1, Yixin Yao1, Lei Nie1, Christopher Flowers1, and Michael Wang1, 2* Abstract Bruton’s tyrosine kinase (BTK) is a proven target in mantle cell lymphoma (MCL), an aggressive subtype of non-Hodgkin lymphoma. However, resistance to BTK inhibitors is a major clinical challenge. We here report that MALT1 is one of the top overexpressed genes in ibrutinib-resistant MCL cells, while expression of CARD11, which is upstream of MALT1, is decreased. MALT1 genetic knockout or inhibition produced dramatic defects in MCL cell growth regardless of ibrutinib sensitivity. Conversely, CARD11 knockout cells showed anti-tumor effects only in ibrutinib-sensitive cells, suggesting that MALT1 overexpression could drive ibrutinib resistance via bypassing BTK-CARD11 signaling. Additionally, BTK knockdown and MALT1 knockout markedly impaired MCL tumor migration and dissemination, and MALT1 pharmacological inhibition decreased MCL cell viability, adhesion, and migration by suppressing NF-κB, PI3K-ATK-mTOR, and integrin signaling. Importantly, co-targeting MALT1 with safimaltib and BTK with pirtobrutinib induced potent anti-MCL activity in ibrutinib-resistant MCL cell lines and patient-derived xenografts. Therefore, we conclude that MALT1 overexpression associates with resistance to BTK inhibitors in MCL, targeting abnormal MALT1 activity could be a promising therapeutic strategy to overcome BTK inhibitor resistance, and co-targeting of MALT1 and BTK should improve MCL treatment efficacy and durability as well as patient outcomes. Dataset description: The bulk RNA-seq dataset was generated for the cell lines below and used for two major purposes: 1. DEG analysis and GSEA analysis comparing IBN-R and IBN-S cells 2. DEG analysis and GSEA analysis comparing MCL cells with/without MI-2 treatment. sample Cell MI-2 Ibrutinib (IBN) Venetoclax (VEN) Used for IBN-R vs IBN-S comparison Used for MI-2 vs untreated (DMSO) H9 Granta519 - R S yes H21 Granta519 - R S yes H33 Granta519 - R S yes H10 Granta519-VEN-R - R R yes H22 Granta519-VEN-R - R R yes H34 Granta519-VEN-R - R R yes H3 JeKo BTK KD_1 - R R yes yes H15 JeKo BTK KD_1 - R R yes yes H27 JeKo BTK KD_1 - R R yes yes H5 JeKo BTK KD_2 - R R yes yes H17 JeKo BTK KD_2 - R R yes yes H29 JeKo BTK KD_2 - R R yes yes H1 JeKo-1 - S R yes yes H13 JeKo-1 - S R yes yes H25 JeKo-1 - S R yes yes H7 Mino - S S yes H19 Mino - S S yes H31 Mino - S S yes H8 Mino-VEN-R - S R yes H20 Mino-VEN-R - S R yes H32 Mino-VEN-R - S R yes H11 Rec-1 - S S yes H23 Rec-1 - S S yes H12 Rec-VEN-R - S S yes H24 Rec-VEN-R - S R yes H36 Rec-VEN-R - S R yes H35 Rec-1 -- S R yes H4 JeKo BTK KD_1 + MI-2 + yes H16 JeKo BTK KD_1 + MI-2 + yes H28 JeKo BTK KD_1 + MI-2 + yes H6 JeKo BTK KD_2 + MI-2 + yes H18 JeKo BTK KD_2 + MI-2 + yes H30 JeKo BTK KD_2 + MI-2 + yes H2 JeKo-1 + MI-2 + yes H14 JeKo-1 + MI-2 + yes H26 JeKo-1 + MI-2 + yes

  Dataset EGAD00001009771

• 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

• 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

• 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 (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

• 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

• 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

• Genetic architecture of autism spectrum disorder in India

  The dataset consists of whole exome sequencing data (fastq format) of 100 non-syndromic autism spectrum disorder patients from India. Whole exome sequencing data is generated using Agilent SureSelect v6 capture kit and Illumina HiSeq sequencing platform. Paired end fastq files are available.

  Dataset EGAD00001008621

• 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

• GDAP - Genome Diversity in Africa Project (2021-02-12)

  The Genomic Diversity in Africa Project (GDAP) started with the plan to develop a genomic resource from African populations, characterise genomic diversity and population history, and facilitate clinical studies in Africa. Currently, 25 individuals from 24 ethnolinguistic groups have been whole-genome sequenced at high depth totalling 585 individuals. An additional 41 individuals have been sequenced with 10X Genomics libraries. At this stage, the initial curation of this dataset has been finished and we are performing the analysis in coordination with our collaborators. The current state of the GDAP represents a very diverse panel of African populations that maximizes geographical and ethnic variation and represents a great starting point to achieve the aforementioned goals. However, southern sub-Saharan countries, Bantu speakers and hunter gatherer groups are currently underrepresented, despite being crucial to understand the evolutionary history of the continent. After extensive effort to collate studies documentation, we finally have the opportunity to sequence 600 new individuals from these groups, including countries as Gabon, Rwanda and Zambia, and address these deficiencies. We aim to proceed with the same strategy: to sequence at high depth 25 individuals with standard PCR free libraries, with 2 additional individuals with 10X Genomics Chromium libraries per ethnolinguistic group. The former allows a good representation of variants down to low frequency in any given population, and the latter allows accurate phasing and the analysis of structural variation. By including these new populations, we want to investigate three crucial questions in African history in addition to the initial objectives: the Bantu expansion, the evolutionary history of hunter gatherers and the transatlantic slave trade. Additionally, the expanded dataset will help us better discover the genetic variation present in Africa and characterize the African pangenome. This data is part of a pre-publication release. For information on the proper use of pre-publication data shared by the Wellcome Trust Sanger Institute (including details of any publication moratoria), please see http://www.sanger.ac.uk/datasharing/ . This dataset contains all the data available for this study on 2021-02-12.

  Dataset EGAD00001006965

• 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

• Capture-based NGS

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

  Dataset EGAD00001011151

• 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

• 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

• Germline genome sequencing samples from the Hereditary Cancer Syndromes (ICCon) Cancer Flagship

  A prospective study of individuals with suspicion of a hereditary cancer syndrome for whom previous clinical targeted genetic testing was either not informative or was not available. To identify pathogenic disease-causing variants explaining participant presentation, germline whole-genome sequencing and a comprehensive cancer virtual gene panel analysis were undertaken.

  Dataset EGAD00001011260

• Clinical and genetic factors associated with tumor response to neoadjuvant (chemo)radiotherapy, survival and recurrence risk in rectal cancer

  Dataset consists of 216 samples, with each sample having a BAM, BAI and VCF file.

  Dataset EGAD00001011297

• Whole-genome sequencing of Tibetans from China

  Twenty-seven Tibetan samples from China were whole-genome sequenced to investigate high-altitude adaptation, population genetics and demographic history.

  Dataset EGAD00001004797

• Low-coverage whole genome sequencing for a highly selective cohort of severe COVID-19 patients

  We generated a dataset consisting of 79 VCF files, and respective FASTQ and CRAM files, methodically generated using the GLIMPSE1 imputation algorithm leveraging the 1000 Genomes Project Phase 3 dataset as the reference panel of haplotypes. In total this dataset is composed of approximately 325 GB of FASTQ data, 156 GB of CRAM data, and 6 GB of VCF data. Our samples were specifically derived from sequenced DNA from a highly selective cohort of patients, mostly comprised of Iberian Populations in Spain (IBS) individuals but also containing some individuals with other genetic backgrounds, who presented severe COVID-19 symptoms during the initial wave of the SARS-CoV-2 pandemic in Madrid, Spain. On average, each VCF file in this rich dataset contains 9.49 million high-confidence single nucleotide variants [95%CI: 9.37 million - 9.61 million].

  Dataset EGAD00001011363