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• Building a Database of Genomic Structural Variants in Japanese population

  Purified genomic DNA was purchased from Japanese B cell DNA bank; We sequenced those genomic DNAs using PacBio Sequel and Sequel II and analyzed genomic structural variations.

  Study JGAS000286

• Single-cell genotype-to-phenotype mapping via co-capture of DNA mutations and mRNA transcripts

  We developed single-cell Genotype-to-Phenotype sequencing (scG2P) for high-throughput, highly-multiplexed, single-cell joint capture of recurrently mutated genomic regions and mRNA phenotypic markers in cells or nuclei isolated from solid tissues. We applied scG2P to aged esophagus samples from five individuals with high alcohol and tobacco exposure.

  Dac EGAC50000000833

• Liquid biopsy-based minimal residual disease monitoring for early risk stratification and decision-making in advanced non-small cell lung cancer - DEDICATION co-hort

  Liquid biopsies generated for minimal residual disease monitoring of non-small cell lung cancer. Ultra deep targeted sequencing of lung cancer related genes with UMIs. This dataset contains the dedication cohort

  Dataset EGAD50000002230

• Liquid biopsy-based minimal residual disease monitoring for early risk stratification and decision-making in advanced non-small cell lung cancer - Biobank co-hort

  Liquid biopsies generated for minimal residual disease monitoring of advanced non-small cell lung cancer. Ultra deep targeted sequencing of lung cancer specific genes, with UMIs. This dataset consists of the biobank cohort

  Dataset EGAD50000002231

• Whole genome sequencing identified biomarker of response to PD1 blockade in Natural-killer/T-cell lymphoma

  WGS data of 13 and TCS data of 8 NKTCL patients. Significant association of PD-L1 rearrangements with objective response to anti-PD1 (pembrolizumab).

  Study EGAS00001002420

• Sequencing data for oesophageal and related samples - Mourikis et al (RNA)

  Data supporting: "Patient-specific detection of cancer genes reveals recurrently perturbed processes in esophageal adenocarcinoma." Mourikis et al. RNAseq (BAM files) 137 samples

  Dataset EGAD00001004776

• A comprehensive characterisation and analysis of human breast cancers through whole-genome sequencing

  We propose to definitively characterise the somatic genetics of breast cancer through generation of comprehensive catalogues of somatic mutations in breast cancer cases by high coverage genome sequencing.

  Dataset EGAD00001002740

• WES data generated in multifocal ileal NETs study

  This dataset includes whole-exome sequencing data for multifocal ileal tumor samples from two patients. Exonic sequences were enriched using the Agilent V2 capture probe set and sequenced by 76-bp paired-end reads using the Illumina Genome Analyzer IIx system with a mean coverage of 80x for each base

  Dataset EGAD00001006408

• Frequent germline mutations of HAVCR2 in sporadic subcutaneous panniculitis-like T-cell lymphoma.

  Subcutaneous panniculitis-like T-cell lymphoma (SPTCL) is a rare subtype of peripheral T-cell lymphoma affecting younger cases and associated with hemophagocytic lymphohistiocytosis. To clarify the molecular pathogenesis of SPTCL, we analyzed paired tumor and germline DNAs from 13 patients by whole exome sequencing.

  Dataset EGAD00001004795

• Total RNA sequencing data from the Triple Negative Trial (TNT)

  BAM files from total RNA sequencing of samples from breast cancer patients in the TNT trial. Data includes 186 primary tumour samples and 13 matched recurrence samples.

  Dataset EGAD00001011141

• The British Autozygosity Populations BioResource

  This data set contains whole exome sequences of individuals with self-stated parental relatedness from the East London Genes & Health cohort. Rare frequency functional variants in these healthy individuals will be studied with respect to the genetic health of the participants and loss-of-function analysis of human genes.

  Dataset EGAD00001003215

• Epichaperome - Englander Institute for Precision Medicine - Weill Cornell Medicine DAC

  This dataset accompanies the publication of Sugita M et al. "Targeting the Epichaperome As an Effective Precision Medicine Approach in a Novel PML-SYK Fusion Acute Myeloid Leukemia" Npj Precision Oncology 2021

  Dataset EGAD00001006904

• Exome sequencing of tumor DNA samples from patients with Waldenstrom macroglobulinemia

  DNA extracted from sorted CD19+ tumor cells (18 samples - 16 patients) was used for exome capture with the SureSelect All Exon Kit following the standard protocols. Paired-end sequencing (2 x 100 bp) was performed using HiSeq2000 sequencing instruments. The files are in FASTQ format.

  Dataset EGAD00001005322

• smRNA-seq of human post-mortem brain data of frontal lobe (Tuebingen part)

  This dataset contains smRNA-seq data from post-mortem human brain tissue of the frontal lobe of patients with FTD and healthy controls. The smRNA-sequencing was done in two parts, this dataset depicts the data generated at the DZNE Tübingen.

  Dataset EGAD00001006846

• WGS of human colorectal cancer organoid exposed to genotoxic pks+ E. coli

  Organoid cultures were exposed to two different E.Coli strains and a dye control with three biological duplicates. Their original culture was harvested as a control. In total 10 organoid cultures were whole-genome sequenced using the Novaseq6000 platforms. The data is deposited as .bam format.

  Dataset EGAD00001005416

• Gene regulation of human CD4+ Treg ChM-seq

  This dataset maps gene expression regulation in human primary regulatory CD4+ T cells (Tregs). It includes whole genome sequence data for ChM-seq (118 H3K4me3, 118 H3K27ac and 6 inputs). The final quality filtered set included 91 individuals with H3K27ac ChM-seq and 88 with H3K4me3 ChM-seq.

  Dataset EGAD00001004828

• SCLC CTC genomic analysis data set

  The data set consists of low-pass whole genome sequence data of single CTCs, pools of CTCs and germline controls for a cohort of 31 SCLC patients at both baseline, and for 5 patients at relapse. In addition 9 CDX models and associated germline controls (where available) are included.

  Dataset EGAD00001002678

• Islet RFX6 Study Manuscript Data

  This submission includes raw FASTQ files (for bulk RNA-seq and 10X joint snATAC+snRNA multiome profiling experiments), sample phenotype files, and genotypes for the data included in the manuscript.

  Dataset EGAD00001008777

• Single cell RNAseq of PBMC from bladder cancer patients

  This dataset contains single cell RNA sequencing data of PBMC samples from 20 bladder cancer patients. cDNAs and single cell RNA libraries were prepared following manufacturer’s user guide (10x Genomics). Each library was sequenced in HiSeq4000 (Illumina) to achieve ~300 million reads following manufacturer’s sequencing specification.

  Dataset EGAD00001006182

• RNAseq data for 6 samples from the DEV cell line

  - Six samples from the DEV cell line: 2 controls, 2 transduced with IL4R WT and 2 transduced with IL4R mutant (I242N) - This DEV cell line is not commercially available and was acquired from a colleague in the Netherlands

  Dataset EGAD00001003908

• Single cell mRNA sequencing of primary GBM - SF 10281

  We collected fresh tissue from an untreated GBM (SF10281) directly from the operating room and subjected the biopsy to single-cell RNA-seq with the fluidigm C1 machine, resulting in sequencing libraries from 96 individual cells.

  Dataset EGAD00001003114

• Single-cell RNA-seq of matched pediatric AML tumors

  Single-cell RNA-seq of pediatric AML tumours from patients enrolled in the clinical trial AAML1031. Obtained using the 10X Chromium Single Cell 3’ Reagent Kit, v3.0. A total of 75 samples were obtained from biopsies at diagnosis, remission and relapse from 28 patients.

  Dataset EGAD00001011195

• RNA sequencing of control OM cells exposed to traffic-related air pollutants

  Total RNA sequencing of olfactory mucosa (OM) cells derived from cognitively healthy individuals exposed to traffic-related ultrafine particles (UFPs) for 24h and 72h in submerged cultures. The UFPs used for exposures were: A0, A20 and Euro6. Exposures were compared to the corresponding blank samples.

  Dataset EGAD00001011317

• Single-cell ATAC-seq of matched pediatric AML tumors

  Single-cell ATAC-seq of pediatric AML tumours from patients enrolled in the clinical trial AAML1031. Obtained using the 10X Chromium NextGEM Single Cell ATAC Reagent Kit, v1.1. A total of 64 samples were obtained from biopsies at diagnosis, remission and relapse from 25 patients.

  Dataset EGAD00001011194

• WES data of primary tumors and metastasis corresponding to three patients

  Fastq files of WES data. Primary tumor and/or metastasic samples of three chRCC patients. DNA libraries were produced using the SureSelect XT HumanAllExon V5 kit (Agilent Technologies), and sequencing was performed in a HiSeq instrument (Illumina) using a 100-bp paired-end mode.

  Dataset EGAD00001010173

• Panel sequencing data for Molecular Characterization of ETMRs

  This dataset contains panel sequencing data from 33 samples. Targeted sequencing was performed by creating libraries using the Agilent SureSelect XT technology. Libraries were sequenced using molecular barcode-indexed ligation-based sequencing using a NextSeq500 (Illumina) instrument. Between three and six lanes per sample have been sequenced resulting in 262 Fastq files (paired end).

  Dataset EGAD00001006208

• Single cell TCR Analysis of regulatory Tcells from blood, fat and skin

  Regulatory Tcells were FACS sorted and processed with 10x Genomics Chromium Next GEM SingleCell V(D)J Reagents Kits v1.1 sequencing. In total 17 samples were processed. Fastq files are supplied.

  Dataset EGAD00001007661

• CBD-KEY-CITESEQ-LINKER: Linker file for CITEseq sequencing data

  Linker file for COMBAT CITEseq sequencing data. Links COMBAT sample IDs with sequencing pools and their associated raw sequence data. Sequence data can be found in the following datasets: ADT data: EGAD00001007962 GEX data: EGAD00001008007 VDJ (B-cell): EGAD00001007964 VDJ (T-cell): EGAD00001007965

  Dataset EGAD00001008008

• Saliva microbiota and STI

  Excess sugar consumption is common among youth and can have adverse health effects. However, the relationship between saliva microbiota and sugar consumption remains sparsely studied. We aimed to explore diversity, composition and functional capacities of saliva microbiota in 11–13-year-old Finnish children with low and high sweet treat consumption.

  Dataset EGAD00001008780

• Understanding the multicellular dynamics of clear cell renal cell carcinoma - spatial transcriptomics

  The dataset comprises of transcriptomes of tissue sections derived from either the tumour normal interface or tumour core from clear cell renal cell carcinomas. 16 sections are sampled in total using 10x Genomics' Visium technology.

  Dataset EGAD00001008781

• Dataset for Ewing_sarcoma_PNET-EXON

  Rare cancer sequencing data of 30 runs in tumor/control pairs, which were uploaded to umbrella studies. The sequencing was always paired

  Dataset EGAD00001008873

• Clinical utility of combined low-pass whole genome and targeted sequencing in liquid biopsies for diagnosis and monitoring of pediatric solid tumors

  Low-pass whole genome sequencing samples from pediatric solid tumor patients who are deceased

  Dataset EGAD00001009972

• Dataset for urologic_cancer-WHOLE_GENOME

  Rare cancer sequencing data of 36 runs in tumor/control pairs, which were uploaded to umbrella studies. The sequencing was always paired

  Dataset EGAD00001008903

• Ewings Sarcoma Rearrangement Screen

  Cancer is driven by mutations in the genome. We will uncover the mutations that give rise to Ewing's sarcoma, a bone tumour that largely affects children. We will use second generation Illumina massively parallel sequencing, and bespoke software, to characterise the genomes and transcriptomes of Ewing's sarcoma tumours.

  Dataset EGAD00001000389

• RNA-seq cohort of normal weight women

  RNA-seq data of non-tumorous breast tissue. There are 32 samples in this cohort.

  Dataset EGAD00001007073

• Genomic (WGS) data for the validation of the glioblastoma progression study (GBMatch).

  43 low-coverage genomes derived from fresh-frozen glioblastoma tumor samples. These genomes have been produced for validation purposes and match the corresponding RRBS and RNA-seq profiles in that DNA and RNA was extracted from the same tumor samples.

  Dataset EGAD00001004077

• Sequencing data for oesophageal and related samples - Ng, Contino et al (RNA)

  Data supporting: "Interplay of processes shapes structural variations undergoing selection in oesophageal adenocarcinoma" Ng, Contino et al. RNAseq (BAM files) 214 oesophageal adenocarcinoma samples

  Dataset EGAD00001007809

• Whole Genome Sequencing of Mutifocal HCC tisue

  The differentiation of distinct multifocal hepatocellular carcinoma (HCC): multicentric disease vs. intrahepatic metastases, in which the management and prognosis varies substantively, remains problematic. We aim to stratify multifocal HCC and identify novel diagnostic and prognostic biomarkers by performing whole genome and transcriptome sequencing, as part of a multi-omics strategy.

  Dataset EGAD00001003348

• subset of 11 samples RRMM (RNA-Seq and WGS) from study EGAS00001005973 used also in study EGAS00001006538

  subset of 11 samples (RNA-Seq and WGS) from study EGAS00001005973, which was published earlier and are linked here to study EGAS00001006538

  Dataset EGAD00001009679

• Transcriptome (RNA-seq) data for the validation of the glioblastoma progression study (GBMatch).

  37 transcriptomes derived from fresh-frozen glioblastoma tumor samples. These transcriptomes have been produced for validation purposes and match the corresponding RRBS and WGS profiles in that DNA and RNA was extracted from the same tumor samples.

  Dataset EGAD00001004076

• Single cell mRNA sequencing of primary GBM - SF 10679

  We collected fresh tissue from an untreated GBM (SF10679) directly from the operating room and subjected the biopsy to single-cell RNA-seq with the fluidigm C1 machine, resulting in sequencing libraries from 96 individual cells.

  Dataset EGAD00001003113

• scRNAseq/snucRNAseq of human implantation sites, placenta and decidua

  This dataset is part of a study that aims to provide a spatially resolved single-cell multiomics map of human trophoblast differentiation in early pregnancy. This dataset contains snucRNAseq; from three human implantation sites (between 8 and 12 post-conceptional weeks, PCW) from medical hysterectomies.

  Dataset EGAD00001010037

• Multiomic snRNAseq/snATACseq of human implantation sites, placenta and decidua

  This dataset is part of a study that aims to provide a spatially resolved single-cell multiomics map of human trophoblast differentiation in early pregnancy. This dataset contains 10x multiome snRNA-seq/snATAC-seq from human implantation sites, decidual and placental samples from 8-9 PCW.

  Dataset EGAD00001010038

• scRNA-seq of nonhematopoietic cells in human lymph nodes and lymphoma

  Single-cell count data generated by the Cellranger (10X Genomics).

  Dataset EGAD00001008311

• Dataset of whole genome bisulfite data of 4 different monocyte samples

  Regions of common inter-individual DNA methylation differences in human monocytes – potential function and genetic basis WGBS Data of Samples: 43_Hm03_BlMo_Ct, 43_Hm02_BlMo_Ct, 43_Hm05_BlMo_Ct, 43_Hm01_BlMo_Ct For details about sequencing or sample metadata check http://deep.dkfz.de/

  Dataset EGAD00001003259

• Ribosome Profiling of Macrophages during Salmonella Infection

  The aim of this study is to assess translational changes in macrophages over a time course of Salmonella infection.This data is part of a pre-publication release. For information on the proper use of pre-publication data shared by the Wellcome Trust Sanger Institute (including details of any publication moratoria), please see http://www.sanger.ac.uk/datasharing/

  Dataset EGAD00001001393

• RNA-seq data for 67 patient cohort

  This dataset includes RNA-seq data of samples from our paper titled "Dynamic phenotypic heterogeneity and the evolution of multiple RNA subtypes in Hepatocellular Carcinoma: The PLANET study." (National Science Review, nwab192. https://doi.org/10.1093/nsr/nwab192)

  Dataset EGAD00001008648

• WGS data for 67 patient cohort

  This dataset includes WGS data of samples from our paper titled "Dynamic phenotypic heterogeneity and the evolution of multiple RNA subtypes in Hepatocellular Carcinoma: The PLANET study." (National Science Review, nwab192. https://doi.org/10.1093/nsr/nwab192)

  Dataset EGAD00001008647

• Mitochondria Optimized 10x data

  Optimized 10x library to increase the coverage of the mitochondrial genome from 3’ 10x gene expression data. See details of the experimental method in the methods section of the manuscript

  Dataset EGAD00001010191

• Single Cell Transcriptomics of peripheral immune cells pre- and post-Immune Checkpoint Blockade

  This is raw sequencing data, analysis of which is presented in the paper "Sensitivity to Immune Checkpoint Blockade and Progression-Free Survival is associated with baseline CD8+ T cell clone size and cytotoxicity", DOI: https://doi.org/10.1101/2020.11.15.383786

  Dataset EGAD00001007942

• T cell receptors of pathogenic CD4 T cells isolated by using distinct phenotypic markers in celiac disease

  The dataset contains rearranged TCR‐α and TCR‐β genes of Ttet+/Tpat+, Ttet-/Tpat+ and Ttet-/Tpat- CD4+ cells from gut biopsies (exvivo) or that of T cell clones generated from gut biopsies (invitro) from 12 CeD patients.

  Dataset EGAD00001008098

• RNAseq of patients with Ewings sarcoma

  Cancer is driven my mutations in the genome. We will uncover the mutations that give rise to Ewing's sarcoma, a bone tumour that largely affects children. We will use second generation Illumina massively parallel sequencing, and bespoke software, to characterise the genomes and transcriptomes of Ewing's sarcoma tumours.

  Dataset EGAD00001000444

• Single cell mRNA sequencing of primary GBM - SF 10592

  We collected fresh tissue from an untreated GBM (SF10592) directly from the operating room and subjected the biopsy to single-cell RNA-seq with the fluidigm C1 machine, resulting in sequencing libraries from 96 individual cells.

  Dataset EGAD00001003112

• Bulk RNAseq of Neuroblastoma patient's tumors

  This dataset contains 9 bulk RNAseq of neuroblastoma patient's tumors used to compare with derived PDXs and/or single-cell data in the Thirant C et al, Nature Communications, 2023. They were intially produced for the Berlanga P., Cancer Discovery, 2022.

  Dataset EGAD00001010287

• Whole genome sequencing of single cells identifies stochastic aneuploidies, genome replication, states, and clonal repertoires for library for library A95728A

  Transposase-based amplification-free single-cell genome direct library preparation in nanowell chips; 844 samples; filetype=bam

  Dataset EGAD00001004758

• Exome data: Histone mutations in human Pre-Leukemic HSC and AML

  Exome sequencing was performed on samples from patients 064, 105, and 8760, including the remission sample for 105. Exomes were captured using the Agilent SureSelect All Exon kit v5 kit and libraries sequenced on HiSeq 2000 or 2500 or 4000.

  Dataset EGAD00001004436

• Bulk ATAC-Seq Illumina NextSeq 500 (10M reads)

  Human data for chromatin accessibility (ATAC-Seq) in eight B-cell precursors: HSC, CLP, pro-B, pre-B, Immature B, Transitional B, Naive B CD5-, Naive B CD5+ cells

  Dataset EGAD00001010908

• MCO colorectal cancer genomics at UNSW

  This dataset contains DNA sequencing data from 95 colorectal cancer and matched-normal samples. The dataset contains targeted deep sequencing of selected regulatory elements in 95 cancer and matched-normal samples, and data for one sample that was additionally whole-genome sequenced (cancer and matched-normal).

  Dataset EGAD00001004582

• cfDNA methylation profiling in Metastatic Cancer and Cancer of Unknown Primary

  This study contains methyl-binding domain sequencing and shallow whole genome sequencing from circulating cell-free DNA (cfDNA) for 143 patients with metastatic cancer of known type, 41 patients with Cancer of Unknown Primary (CUP) and 27 non-cancer controls.

  Dataset EGAD00001011178

• SG10K_Pilot Dataset: Whole genome sequencing data of 4810 individuals from Singapore

  Genomic data obtained from the joint processing and variant calling of 4,810 individuals from Singapore. VCF files are by Chromosome (chr. 1-22 plus X) for all 4,810 individuals. Self-reported ethnicity is found in the "Region" column of metadata file.

  Dataset EGAD00001005337

• V2 panel bait design test

  This study comprises of three different datasets. 1) 57 samples from the 1243 canapps cell line study,2) 91 FFPE normal samples and 3) 87 samples from the SCORT WS2 dataset. The aim is to sequence these 235 samples in order to test the new V2 Colorectal bait design.

  Dataset EGAD00001003242

• Genomic profiling of well-differentiated and dedifferentiated liposarcoma from the same patient

  Well-differentiated, dedifferentiated, and matched normal tissues from liposarcoma (51 specimens) from 17 patients were obtained for whole exome sequencing. Tumors were submitted from 9 patients were used for RNA sequencing. The bam files are made available in this dataset.

  Dataset EGAD00001003976

• Whole-genome, whole-exome and transcriptome sequencing of pancreatic ductal adenocarcinomas from young adults (NCT MASTER)

  Whole-genome, whole-exome and transcriptome sequencing of pancreatic ductal adenocarcinomas from young adults reveals recurrent NRG1-fusions in KRAS wild-type tumors.

  Dataset EGAD00001004068

• Sequencing data for oesophageal and related samples - Alex Frankell et al (RNA)

  Data supporting: "The landscape of selection in 551 Esophageal Adenocarcinomas defines genomic biomarkers for the clinic." Frankell et al. RNAseq (BAM files) 116 tumours

  Dataset EGAD00001004423

• Sequencing data of primary uveal melanomas and their matched metastases

  We performed targeted DNA sequencing of primary uveal melanomas and their matched metastases from 35 patients, analyzing a total of 124 tissues. Sequencing was performed on an Illumina HiSeq 2500 instrument using a panel of 538 genes commonly involved in cancer. 124 BAM files were generated.

  Dataset EGAD00001004453

• FASTQ file for paper titled "Discovery of immunotherapy targets for pediatric solid and brain tumors by exon-level expression"

  This data set includes 27 full-length transcript sequence generated from PacBio IsoSeq that were used for verify the cancer-specific exons identified in three genes: FN1, COL6A3 and TNC. The data were generated from PDX models of osteosarcoma patients.

  Dataset EGAD00001015356

• The South Asia Rheumatic Heart Disease Genetics Network Data

  This dataset comprises over 850 individuals recruited in Uttar Pradesh, India, including cases of rheumatic heart disease based on echocardiographic diagnosis and controls recruited on the basis of normal echocardiograms. For this analysis all available samples were genotyped using the Illumina HumanCore-24 BeadChip platform.

  Dataset EGAD00001004882

• Combination Therapies for Personalised Cancer Medicine in drug resistant EGFR mutant lung cancer (2019-06-10)

  This study involves mutagenizing a range of different cell lines with ENU to identify those mutations which engender resistance to targeted treatment. . This dataset contains all the data available for this study on 2019-06-10.

  Dataset EGAD00001005080

• Sequencing of patient samples who received immune checkpoint inhibition - WES - NKI (2019-08-07)

  DNA and RNA isolated from FFPE blocks of patients who received immune checkpoint inhibition (ICI) are sequenced with the aim to identify therapeutically tractable vulnerabilities in tumors to prevent ICI resistance. . This dataset contains all the data available for this study on 2019-08-07.

  Dataset EGAD00001005235

• Exome_Sequencing_of_Human_myeloid_malignancies (2019-08-28)

  This study involves exome sequencing of blood/bone marrow DNA from patients with myeloid malignancies. Blood DNA samples have been taken from patients at different timepoints of disease phenotype. We hope to elucidate mechanisms of clonal evolution in these patients. . This dataset contains all the data available for this study on 2019-08-28.

  Dataset EGAD00001005299

• PFA ependymoma study -WGS data

  WGS bam file for the 18 samples used in Michealraj et al. Cell 2020. The dataset includes PFA ependymoma tissue, derived line and blood samples of 6 patients WGS data were aligned with BWA to the hg38 human reference genome (igenome) and further processed according to the GATK best practice pipeline.

  Dataset EGAD00001006045

• WGS from PDAC samples

  Bam files from WGS of PDAC samples used in the PCSI mismatch repair study

  Dataset EGAD00001006262

• Single-Nuclei RNA-seq of healthy (post-mortem) and temporal lobe epilepsy (biopsy) subjects.

  To identify dysfunctional neuronal subtypes underlying seizure activity in the human brain, we have performed single-nucleus transcriptomics analysis of >110,000 neuronal transcriptomes derived from temporal cortex samples of multiple temporal lobe epilepsy and non-epileptic subjects.

  Dataset EGAD00001006575

• Whole Exome sequencing data from Shwachman-Diamond syndrome bone marrow samples

  This dataset includes paired WES from bone marrow samples of patients with SDS and paired bone marrow-derived fibroblasts as a germline reference. Some patients have multiple samples collected serially over time. There are 74 BAM files included in this dataset.

  Dataset EGAD00001006815

• AfricanNeo WGS aDNA Dataset

  This dataset includes WGS data of 12 ancient individuals (97–688 years BP) from Zambia and South Africa, presented in Fortes-Lima et al. Nature 2023. Further details like C14-dates and archaeological descriptions were reported elsewhere (Meyer et al. Azania 2021; Steyn et al. African Archaeological Review 2022).

  Dataset EGAD00001011320

• Single cell TotalSeqC protein data of 20 PMBC pools of HCC patients

  Single cell TotalSeqC protein data serial peripheral blood mononuclear cell (PBMC) samples taken from advanced HCC patients. TotalSeqC is available for 41 out of 72 PBMC samples included in the study, and were combined into 20 pools.

  Dataset EGAD00001011346

• Sequencing Data of Leukemic Samples

  Sequencing data of leukemic samples included in study. Including WES, WGS and targeted sequencing files from patients at diagnosis, remission and at relapse. The dataset includes samples from 52 pediatric patients, totaling 311 samples.

  Dataset EGAD00001015662

• eMERGE: Northwestern (NUgene) WGS

  The NUgene Project is a biorepository with longitudinal medical information from participating patients at Northwestern Medicine affiliated hospitals and outpatient clinics. Participants' DNA samples are coupled with data from a self-reported questionnaire (2 versions were used, 1 before and 1 after February 2006, both are included) and continuously updated data from our Electronic Medical Record (EMR) representing actual clinical care events. Northwestern has a state-of-the art, comprehensive inpatient and outpatient EMR system of over 3 million patients. NUgene has broad access to participant data for all outpatient visits as well as inpatient data via a consolidated enterprise data warehouse. NUgene participants consent to distribution and use of their coded DNA samples and data for a broad range of genetic research by third-party investigators. The electronic MedicalRecords and Genomics (eMERGE) Network is a consortium of 9 clinical sites with EMR linked DNA biobanks, including Northwestern University and its NUgene biobank, funded by the NHGRI (National Human Genome Research Institute) to investigate the use of electronic medical record systems for genomic research. The goal of eMERGE is to conduct genome-wide association studies in approximately 100,000 individuals using EMR-derived phenotypes and DNA from linked biorepositories. Using electronic phenotyping methods, the consortium has been and is using DNA samples from all participating sites to explore the genetic determinants of approximately 80 phenotypes, including both diseases and traits, for which the electronic phenotyping algorithms have or are being published on PheKB.org. Thus, for the eMERGE network, ~900 NUgene subjects were selected, as described in the study inclusion/exclusion criteria section below, to be genotyped using whole genome sequencing (WGS), for use in the eMERGE network as eMERGE subjects. The criteria used below were selected so that these subjects will likely meet the criteria to be cases and/or controls, of diverse races and/or ethnicities, for at least 1 of the ~80 phenotypes being studied within eMERGE, and could be recontacted for future research if needed.

  Study phs001191

• Drug Signatures for Prediction and Mitigation of Toxicity

  The overall goal of the drug signatures for prediction and mitigation of toxicity study is to use genomic and proteomic high-throughput measurements as the basis for computational analysis that integrates network analyses with structural constraints and dynamical models in multiple cell types to identify signatures that predict toxicity induced by 55 FDA-approved chemotherapeutic drugs and potential mitigation of this toxicity. Specifically, we have recruited and pre-screened healthy individuals to be included in our study. Ninety six male and female individuals that satisfied the initial pre-screening for the study and their sex, age, race/ethnicity recorded through an enrollment questionnaire were consented. Eighty five underwent a formal and thorough medical health screening. The evaluation involved assessment of all inclusion and exclusion criteria, a full medical history, measurement of weight, height, waist and hip circumference, heart rate, blood pressure, respiratory rate, and oxygen saturation, a physical exam and an electrocardiograph (ECG). Blood was drawn for analysis of clinical relevant parameters. A pregnancy test was included for female participants. All blood draws and pregnancy tests were sent to a certified clinical laboratory for clinical analysis. Of the 85 subjects that were screened 42 (48.3%) were deemed eligible for final inclusion. Of these 42, one declined to undergo skin biopsy and/or venesection and one subject didn’t show up for the scheduled biopsy, leaving 40 clinically healthy subjects on which a skin biopsy and venesection was performed. Fibroblast lines were established from the skin biopsies. Induced pluripotent cells (iPSC) were generated from the established fibroblast lines of these 40 clinically healthy racially diverse male and female study participants who ranged in age from 22 and 61 years through reprogramming using either the mRNA or Sendai-virus methods. One clone from each of the 40 iPSC line was fully characterized for normal karyotype, short-tandem repeat matching to the original fibroblast line (authentication), pluripotency by select pluripotent marker expression via immunocytochemistry and by mRNAseq-based PluriTest analysis, and whole-genome sequencing.

  Study phs002088

• NIDDK IBD Genetics Consortium Crohn's Disease Genome-Wide Association Study

  This dataset contains data from a genome-wide association study performed with 968 Inflammatory Bowel Disease (IBD) affected cases and 995 unrelated controls using the Illumina HumanHap300 Genotyping BeadChip. Cases were selected to have Crohn's disease with ileal involvement, and controls were matched to cases based on sex and year of birth. Subjects were drawn from two cohorts: (1) persons with non-Jewish, European ancestry (561 cases and 563 controls), and (2) persons with Jewish ancestry (407 cases and 432 controls). Genotyping was performed at the Feinstein Institute for Medical Research. Seven-hundred fifty-four of the samples (468 cases and 286 controls) were taken from the NIDDK IBD Genetics Consortium cell line repository. These samples are identified in the IBD_Sample file. The subject IDs for these individuals may be used to request corresponding samples for follow-up research through the repository. In addition, complete phenotype data for these individuals are available, together with the Consortium's phenotyping manual and the forms used to collect the data. The remaining 1,209 samples were obtained from pre-existing collections ascertained through Cedars-Sinai Medical Center, Johns Hopkins University, University of Chicago, University of Montreal, University of Pittsburgh, University of Toronto, and the New York Health project (controls only). For these samples, only sex, cohort (Jewish vs. non-Jewish), and age at diagnosis (cases only) are available. Two-hundred three individuals from among the pre-existing samples did not provide consent to release their genotype data (designated as consent group 2 in the file IBD_Subject). Thus, individual genotype data are only provided for 1,760 samples. To compensate for this, we have provided summary results for each SNP. These are based on a stratified analysis testing case/control association. Fifty-one samples had a call rate less than 93% and were therefore excluded from this analysis, leaving an overall sample size of 1,963 - 51 = 1,912. X Chromosome Heterozygosity Nine samples have X chromosome heterozygosity that is neither consistent nor inconsistent with their phenotypic sex. One of these samples was found to have Turner Syndrome. The remaining 8 samples have heterozygosity ranging from 35-76%.

  Study phs000130

• CTN - 0051: Extended-Release Naltrexone vs. Buprenorphine for Opioid Treatment (X:BOT)

  The overarching goal of CTN-0051 is to foster adoption of new relapse-prevention pharmacotherapies in community-based treatment programs (CTPs) where these could have a substantial public health impact. To this end CTN-0051 will assess the comparative effectiveness of extended-release injectable naltrexone (XR-NTX, Vivitrol®), an opioid antagonist recently approved and indicated for the prevention of relapse to opioid dependence, versus buprenorphine-naloxone (BUP-NX, Suboxone®), a high affinity partial agonist indicated for maintenance treatment of opioid dependence, as pharmacotherapeutic aids to recovery. The study is conducted in 8 CTN-affiliated CTPs that provide or partner with detoxification services (inpatient/residential) which have the capacity to maintain participants opioid-free for approximately 3-7 days, have the capacity to provide medication-assisted therapy, and can provide a minimum of one group or individual counseling session per week during the 24-week treatment period. Up to 600 eligible participants will be randomized to treatment with XR-NTX or BUP-NX for 24 weeks (sufficient to include 350 participants who are randomized more than 72 hours after their last opioid). To maximize generalizability, the point of randomization is flexible, from shortly after program admission until just prior to program discharge. The primary goal of the study is to estimate the difference, if one exists, between XR-NTX and BUP-NX in the distribution of the time to relapse (i.e., loss of persistent abstinence) during the 6-month trial. The primary outcome measure is the time to the event, with the event called relapse. Secondary objectives are to: (1) compare outcome on XR-NTX versus BUP-NX across a range of clinical safety and secondary efficacy domains, (2) explore demographic, clinical, and genetic predictors of successful treatment and moderators of differential effectiveness (i.e., what variables may help clinicians choose which of these treatments is best for a given patient), and (3) collect a limited dataset to permit analyses of economic costs and benefits of the two treatments.

  Study phs002876

• Genome-Wide Pleiotropy Scan Across Multiple Cancers

  A whole-exome sequencing (WES) study was conducted in 3,233 cases diagnosed with multiple primary cancers and 3,229 matched cancer-free controls (90% non-Hispanic white, 3% African-American, 3% East Asian, and 4% Latino) selected from individuals in the Kaiser Permanente Research Bank (KPRB) who were members of the Kaiser Permanente Northern California (KPNC) health plan. Cancer-free controls were matched to cases on age at specimen collection (within 2 years), sex, genotyping array (which matched on self-reported race/ethnicity), closest distance using the first two principal components for genetic ancestry, and reagent kit. Cases and controls were drawn from two prospective KPRB cohorts: the Research Program on Genes, Environment and Health (RPGEH) and the ProHealth study. Participants were sequenced by the Regeneron Genetics Center using the Illumina NovaSeq 6000 platform, and sample preparation and quality control were performed using a high-throughput, fully-automated system [PMID: 33087929]. Reads were aligned to the GRCh38 reference genome, and variants were called using WeCall [PMID: 33087929]. Participants with sex discordance, 20x coverage at less than 80% of targeted sites, and/or contamination greater than 5% were excluded. After quality control, we retained n = 6,247 (3,111 cases, 3,136 controls) individuals for downstream analyses. Among participants selected for this WES study, n = 5,432 (2,299 cases; 3,133 controls) consented to deposition of data to the National Institutes of Health (NIH).Further quality control was applied to filter low quality variants. Genotype calls with low depth of coverage (DP) were updated to missing (DP < 7 for SNPs and DP < 10 for indels), after which sites with low allele balance (AB) - variants without at least one sample having AB ≥ 15% for SNPs or AB ≥ 20% for indels - were removed. Lastly, variants with missingness > 10% and Hardy-Weinberg equilibrium p-value < 10-15 were excluded. Further description of quality control and downstream single-variant and gene-based analyses is available in Cavazos et al, 2022 [medRxiv].

  Study phs002809

• Identifying transcriptional programs underlying anti-EGFR small molecule response and resistance with TraCe-seq

  Genetic and non-genetic heterogeneity within cancer cell populations represents a major challenge to anti-cancer therapies. We currently lack robust methods to determine how pre-existing and adaptive features affect cellular responses to therapies. Here, by conducting clonal fitness mapping and transcriptional characterization using expressed barcodes and single-cell RNA-sequencing, we have developed TraCe-seq, a method that captures at clonal resolution the origin, fate, and differential early adaptive transcriptional programs of cells in a complex population in response to distinct treatments. We used TraCe-seq to benchmark how next-generation dual EGFR inhibitors-degraders compare to standard EGFR kinase inhibitors in EGFR-mutant lung cancer cells. To QC the TraCe-seq strategy, single-cell RNA-seq libraries were generated from a variety of human cancer cell lines transduced with the TraCe-seq library to validate the TraCe-seq strategy. Specifically, 5 different cell lines (PC9, MCF-10A, MDA-MB-231, NCI-H358, and NCI-H1373) were each transduced with a unique TraCe-seq barcode. The transduced cells were selected with puromycin only, dissociated to single cell suspensions, and then mixed together. The complex mixture of the 5 cell lines was profiled by 10X scRNA-seq. Furthermore, transduced NCI-H1373 cells were sorted by FACS to enrich for the top 50% of eGFP positive cells, and sorted cells were cultured briefly and used to construct scRNA-seq libraries and profiled by 10x scRNA-seq. To carry out the full TraCe-seq experiment, ~600 PC9 cells carrying unique TraCe-seq barcodes were expanded over 12 doublings to establish the barcoded population. A subset of the barcoded PC9 population was used to generate scRNA-seq libraries and profiled by 10x scRNA-seq prior to treatment to establish a baseline transcription profile for each barcoded clone. The rest of the cells were then treated for four days with 1 µM erlotinib, 1 µM GNE-069, or 1 µM GNE-104 respectively. scRNA-seq libraries were then generated form the treated cells and profiled by 10x scRNA-seq.

  Study EGAS00001005405

• Lindsey E. Jones et al. Patient-derived cells from recurrent tumors that model the evolution of IDH-mutant glioma. Neuro-Oncology Advances, 2020. We established robust, versatile, and well-characterized Patient Derived Cells (PDC) of an IDH1-mutant astrocytoma and an IDH1-mutant oligodendroglioma that represents defined evolutionary stages of chemotherapy-induced hypermutation. The PDCs retain tumor subtype defining features over time as well as classic hallmarks of cancer, including anchorage independent growth and cell immortality. The integrated phylogenies composed of PDCs,single-cell-derived PDCs, patient-derived xenografts, and corresponding spatiotemporal tumor tissue samples also provide new insight into the clonality, evolutionary pattern, and immense mutational load of hypermutated IDH mutant gliomas.

  IDH-mutant lower-grade gliomas can undergo malignant progression via temozolomide-driven hypermutation. Patient-derived cells (PDC) that model the genetically distinct hypermutated (HM) tumor subgroup are generally lacking, and few if any human brain tumor cell models are from defined evolutionary time points. Here, we characterize multiple PDC derived from independent surgical specimens of IDH1-mutant recurrences, including an ATRX and TP53-mutant astrocytoma and a 1p/19q co-deleted and TERT promoter-mutant oligodendroglioma. We determined the evolutionary time points represented by each PDC using exome sequencing and phylogenetic reconstruction, comparing the PDC and single cell clones of the PDC (scPDC) to multiple spatiotemporal tumor tissue samples, PDC-derived xenografts (PDX) and patient-matched blood. The tumor samples exhibited TMZ-induced mutagenesis and a branching pattern of evolution. We found clear evidence of two fully independent founder HM clones in the tumor tissue that are faithfully represented by independent PDC. The PDC, scPDC and PDX also shared the mutagenesis signature and represent the mid and later evolutionary time points of their corresponding tumors. The PDC maintained the tumor subtype-defining features over many passages, including heterozygosity of the IDH1 R132H mutation, production of 2-hydroxyglutarate (2-HG), and subtype-specific telomere maintenance mechanisms. The PDC from both tumors exhibited anchorage-independent growth in soft agar. The oligodendroglioma PDC formed infiltrative intracranial tumors with characteristic oligodendroglioma histology, initially with a long period to tumor formation. We conclude that the PDC, scPDC and PDX faithfully model the heterogeneous clonal origins of the corresponding tumor tissue. The multilevel analysis also provides new insight into the intratumoral heterogeneity and vast mutational load of HM glioma. The PDC from multiple evolutionary time points presented in the context of full clinical timelines may be useful to model evolution and intratumoral heterogeneity, important sources of therapeutic failure.

  Study EGAS00001003992

• A Genome-Wide Association Study in Patients Experiencing Drug-Induced Long-QT Syndrome and/or Torsades de Pointes; A Collaboration Between the NIH Pharmacogenomics Research Network and the RIKEN Yokohama Institute Center for Genomic Medicine

  The goal of this study was to identify genetic risk factors for drug-induced prolongation of the QT interval (diLQT) and the ventricular arrhythmia torsades de pointes (TdP). We conducted a genome-wide association study (GWAS) focusing on subjects with a history of long QT and/or TdP after taking medication. Controls for this study were individuals with a history of cardiac arrhythmias who had begun treatment with potentially QT-prolonging antiarrhythmics. An additional control group of normal volunteers were given ibutilide, a drug with documented proarrhythmic properties. All study participants were recruited and treated/evaluated at Vanderbilt University Medical Center. This study was conducted by the Pharmacogenomics of Arrhythmia Therapy subgroup of the Pharmacogenetics Research Network, a nationwide collaboration of scientists studying the genetic contributions to drug response variability. Genotyping was performed by the RIKEN research institute in Japan using the Illumina 610 Quad Beadchip platform.

  Study phs000331

• Dissecting Cell Composition and Drug Sensitivity in Human Adenoid Cystic Carcinomas (ACCs)

  The study reports the results of single-cell RNA sequencing (scRNA-seq), RNA sequencing (RNA-seq), and whole-exome sequencing (WES) experiments performed on malignant cells isolated by flow cytometry from seven patient-derived xenograft (PDX) lines established from human Adenoid Cystic Carcinomas (ACCs). Of these seven lines, five are characterized by well differentiated histology (ACCX5M1, ACCX6, ACCX14, ACCX22, SGTX6) and two by solid histology (ACCX9, ACCX11). Analysis by scRNA-seq of the well-differentiated PDX line ACCX22 led to identification of cell-surface markers (CD49f, KIT) that enabled the differential purification of the two major cellular components contained in well-differentiated ACCs: myoepithelial-like (CD49f-high/KIT-negative) and ductal-like (CD49f-low/KIT-positive) cells. The study reports the analysis by RNA-seq and WES of purified preparations of myoepithelial-like and ductal-like cells from well-differentiated PDX lines (ACCX5M1, ACCX6, ACCX14, ACCX22, SGTX6) and of ductal-like (CD49f-low/KIT-positive) cells from solid PDX lines (ACCX9, ACCX11).

  Study phs002764

• Transcriptome study of differential expression in schizophrenia

  Schizophrenia is a common and severe psychotic disorder. While some common SNPs and rare copy number variants have been identified as being significantly associated with disease risk, the biological mechanisms remain undefined. To identify gene expression abnormalities in schizophrenia, we generated whole-genome gene expression profiles using microarrays on lymphoblastoid cell lines from a total of 413 cases and 446 controls. Regression analysis identified 95 transcripts differentially expressed by affection status at a genome-wide false discovery rate of 0.05, while simultaneously controlling for confounding effects. These transcripts represented 89 genes with functions such as neurotransmission, gene regulation, cell cycle progression, differentiation, apoptosis, and immunity. The observed differential expression of extended major histocompatibility complex region genes converges with the genetic evidence from schizophrenia genome-wide association studies, which find the same region to be the most significant schizophrenia susceptibility locus. Our analysis also provides novel candidate genes for further study to assess their potential contribution to schizophrenia.

  Study phs000775

• Integrative Analysis for Multi-Omics Data in Non-Small-Cell Lung Cancer

  We conducted epigenetic and transcriptomic mapping of primary non-small cell lung tumors and non-neoplastic tissues. 20 non-neoplastic lung tissues and 18 non-small cell lung tumors were obtained from Biorepository and Tissue Technology Shared Resource at Moores Cancer Center, UC San Diego. All tumor samples were in pathological stages I and II. 8 pairs of samples were "matched", meaning that the tumor and normal tissues came from the same patient. Microfluidic oscillatory washing–based chromatin immunoprecipitation followed by sequencing (MOWChIP-seq) was used to profile the binding of H3K4me1, H3K4me3, H3K9me3, H3K27ac and H3K27me3. SmartSeq-2 was used to map mRNA expression. We identified a large number of differentially modified regions for both epigenetic and transcriptomic markers between tumors and normal tissues. Deep learning model showed extensive transcription factor network rewiring. Raw sequencing data of the ChIP-seq and RNA-seq libraries are available through this dbGaP submission.

  Study phs003113

• Epstein-Barr Virus status drives morphological and molecular intra-tumour heterogeneity in gastric cancer: insights from a case report and literature review

  This case report describes a rare case of bi-phenotypic gastric cancer with two distinct, but clonally related, histological components. The first component, associated with Epstein-Barr virus (EBV) infection, exhibited the morphological features of gastric carcinoma with lymphoid stroma, suggesting that EBV, as an effective immunogenic factor, may trigger a prominent immune response within the tumour microenvironment. The second component, which was EBV-negative, displayed tubular/papillary morphology and features of increased biological aggressiveness, such as high-grade areas and lymphatic invasion. Immunohistochemical and molecular studies confirmed that, despite the differing morphologies and immunophenotypes, both components were clonally related, with especially the EBV-negative area showing more complex DNA aberrations, reminiscent of Chromosomally instable (CIN) lesions. This case describes clonally related EBV-positive and negative components within a single gastric cancer, contributing to a better understanding of EBV role in tumour heterogeneity and progression and highlighting the impact of EBV loss on tumour behaviour.

  Study EGAS50000000706

• Bulk RNA sequencing of day 2 and day 7 biopsies from the tuberculin skin test in people with latent tuberculosis, and of day 2 biopsies from saline controls

  We used the tuberculin skin test (TST) as human challenge model to study the temporal evolution of the immune response to Mycobacterium tuberculosis (Mtb) antigens in vivo. Study participants comprised healthy HIV seronegative adults, 18-60 years of age. Latent tuberculosis (TB) infection was defined as immune memory for Mtb-specific antigens identified by positive peripheral blood IFNg release assays, but no clinical or radiological evidence of active TB. Two units tuberculin each were injected intradermally into the contralateral forearms of participants. After 2 days (n=216) or 7 days (n=158), 3 mm skin punch biopsies were taken from the injection sites and processed for whole genome transcriptional profiling by bulk RNA sequencing. The time points reflect maximum clinical inflammation (day 2) and maximum T cell infiltration (day 7) of the TST. TST samples were compared to skin biopsies taken two days after control injection of saline in a separate group of individuals (n=33), comprising healthy volunteers as well as patients with active or latent TB, ranging from 18-75 years of age. This dataset includes 407 samples from 256 individuals (n=33 saline, n=223 with Day 2 and/or Day 7 TST). Skin biopsies were collected into RNAlater (Qiagen) for RNA extraction. Total RNA was obtained with the Precellys Evolution homogenizer (Bertin Instruments) and Qiagen RNeasy mini kit. RNA was subjected to DNase treatment to remove contaminating genomic DNA using a TURBO DNA-free kit (Ambion, Life Technologies). The KAPA mRNA HyperPrep Kit (Roche Diagnostics) was used to construct stranded mRNA-Seq libraries from up to 500 ng intact total RNA. Paired-end sequencing was performed on the Illumina Nextseq using the Nextseq 500/550 High Output 75 cycle kit (Illumina). Runs were demultiplexed using bcl2fastq by Illumina.

  Dataset EGAD50000001208

• The spatial organization of intratumor heterogeneity andevolutionary trajectories of metastases in hepatocellular carcinoma

  Hepatocellular carcinoma (HCC) has one of the poorest survival amongst cancers. Using multi-regional sampling of nine resected HCC with different etiologies, we find that phylogenetic relationships of these sectors show diverse levels of genetic sharing spanning early to late diversification. Unlike the variegated pattern found in colorectal cancers, a large proportion of HCC display a clear Isolation-By-Distance pattern where spatially closer sectors are genetically more similar. Two resected intra-hepatic metastases showed genetic divergence occurring before and after primary tumor diversification respectively. Interestingly, metastatic tumors had much higher variability than their primary tumors, suggesting that intra-hepatic metastasis is accompanied by rapid diversification at the distant location. The presence of co-existing mutations offers the possibility of drug repositioning for HCC treatment. Taken together, these insights into intra-tumor heterogeneity allow for a comprehensive understanding of the evolutionary trajectories of HCC and suggest novel avenues for personalized therapy.

  Study EGAS00001001603

• A comprehensive assessment of somatic mutation detection in cancer using whole genome sequencing

  As whole genome sequencing for cancer genome analysis becomes a clinical tool, a full understanding of the variables affecting sequencing analysis output is required. Using tumor-normal sample pairs from two different types of cancer, chronic lymphocytic leukemia and medulloblastoma, we conducted a benchmarking exercise within the context of the International Cancer Genome Consortium. We compare sequencing methods, analysis pipelines, and even validation methods. Here we show that using PCR-free methods and increasing sequencing depth to ~100x showed benefits, as long as the tumor:control coverage ratio remains balanced. We observe widely varying mutation call rates and low concordance among analysis pipelines, reflecting the artifact-prone nature of the raw data and lack of standards for dealing with the artifacts. However, armed with the benchmark mutation set we have created, we show that many issues are in fact easy to remedy and have an immediate positive impact on mutation detection accuracy.

  Study EGAS00001001539

• Gut metagenome associations with extensive digital health data in a volunteer-based EstMB cohort

  Microbiome research is starting to move beyond the exploratory phase towards interventional trials and therefore well-characterized cohorts will be instrumental for generating hypothesis and providing new knowledge. As part of the Estonian Biobank, we established the Estonian Microbiome Cohort which includes stool, oral and plasma samples from 2,509 participants and is supplemented with multi-omic measurements, questionnaires, and regular linkages to national electronic health records. In this study, we analyzed stool data from deep metagenomic sequencing together with rich phenotyping, including 71 diseases, 136 medications, 21 dietary questions, 5 procedures, and 19 other factors. The data revealed numerous relationships with different microbiome features. Additionally, the long-term antibiotic usage, independent from recent administration, has a significant impact on the microbiome composition, partly explaining the common associations between diseases. Overall, this study extends the understanding of microbiome–host interactions and facilitates the development of microbiome-related studies.

  Study EGAS00001005900

• Comprehensive epigenomic profiling reveals the extent of disease-specific chromatin states and informs drug target discovery in ankylosing spondylitis

  Ankylosing spondylitis (AS) is a common, highly heritable inflammatory arthritis characterised by enthesitis of the spine and sacroiliac joints. Genome-wide association studies have revealed >100 genetic associations but their functional effects remain largely unresolved. Here, we present a comprehensive transcriptomic and epigenomic map of disease-relevant blood immune cell subsets from AS patients and healthy controls. We report differential disease signatures for specific genomic regions from individual -omic modalities and multi-omic integration, showing enrichment at genetically associated loci and evidence for altered monocyte function in AS. We link putative functional SNPs with cognate genes using high-resolution Capture-C at 10 loci, including PTGER4 and ETS1. We also show how disease-specific functional genomic data can be integrated with GWAS evidence to enhance therapeutic target discovery. This study combines multiple epigenetic and transcriptional analysis with GWAS to identify cell types, candidate drug target genes and transcriptional regulation of likely pathogenic relevance.

  Study EGAS00001006233

• Multi-omics identify falling LRRC15 as a COVID-19 severity marker and persistent pro-thrombotic signals in convalescence

  Patients with end-stage kidney disease (ESKD) are at high risk of severe COVID-19. Here, we perform longitudinal blood sampling of ESKD haemodialysis patients with COVID-19, collecting samples pre-infection, serially during infection, and after clinical recovery. Using plasma proteomics, and RNA-sequencing and flow cytometry of immune cells, we identify transcriptomic and proteomic signatures of COVID-19 severity, and find distinct temporal molecular profiles in patients with severe disease. Supervised learning reveals that the plasma proteome is a superior indicator of clinical severity than the PBMC transcriptome. We show that a decreasing trajectory of plasma LRRC15, a proposed co-receptor for SARS-CoV-2, is associated with a more severe clinical course. Strikingly, we observe that two months after the acute infection, patients still display dysregulated gene expression related to vascular, platelet and coagulation pathways, including PF4 (platelet factor 4), which may explain the prolonged thrombotic risk following COVID-19.

  Study EGAS00001006778

• Comprehensive epigenomic profiling reveals the extent of disease-specific chromatin states and informs drug target discovery in ankylosing spondylitis

  Ankylosing spondylitis (AS) is a common, highly heritable inflammatory arthritis characterised by enthesitis of the spine and sacroiliac joints. Genome-wide association studies have revealed >100 genetic associations but their functional effects remain largely unresolved. Here, we present a comprehensive transcriptomic and epigenomic map of disease-relevant blood immune cell subsets from AS patients and healthy controls. We report differential disease signatures for specific genomic regions from individual -omic modalities and multi-omic integration, showing enrichment at genetically associated loci and evidence for altered monocyte function in AS. We link putative functional SNPs with cognate genes using high-resolution Capture-C at 10 loci, including PTGER4 and ETS1. We also show how disease-specific functional genomic data can be integrated with GWAS evidence to enhance therapeutic target discovery. This study combines multiple epigenetic and transcriptional analysis with GWAS to identify cell types, candidate drug target genes and transcriptional regulation of likely pathogenic relevance.

  Study EGAS00001006945

• Data Use Ontology (DUO) at EGA

  For those of you that follow the updates of GA4GH you will have seen the unanimous approval of the steering committee for DUO to be included in its suite of technical standards for the sharing of genomic and health related data. DUO has three main features: Each term has been generated by the community and includes a human readable definition that can be expanded where necessary. It is a machine-readable file that encodes how that data can be used and how a researcher intends to use the data. Can be implemented alongside an advanced search algorithm which would allow authenticated users to query and gain access to datasets pertaining to their research. e.g., an industry researcher working on cancer could potentially be matched to any dataset that is allowed for commercial use and for cancer research and offered the opportunity to fetch them automatically. So, what does this mean for EGA? EGA as a driver project has adopted this standard and will be utilizing it for two main purposes in the first instance. i) It will allow EGA users to instantly identify what terms they will need to agree to as part of any Data Access Agreements. This will save valuable time for both applicants and Data Access Committees alike - as you will be able to see if you are likely to be able to access the data based on your research intentions and working background. ii) In the future it will allow users to be able to search for data based on Data Use Ontology terms e.g., you could search for all data that can be used for General Research Use (GRU). As EGA moves forwards submitters will be asked to align their data access policies with DUO so that their dataset(s) can be tagged appropriately on our web pages. If you would like to add DUO to any of your existing datasets, or to any future datasets, do please just let us know.

  Blog data-use-ontology

• Fetal origins of malignant germ cell tumours

  Germ cell tumours (GCTs) are a collection of benign and malignant neoplasms derived from primordial germ cells (PGCs). They are uniquely able to generate embryonic and extraembryonic tissues, which in malignant GCTs carries prognostic and therapeutic significance. The developmental pathways underpinning GCT initiation and histogenesis are incompletely understood. Here, we studied the phylogenetic and transcriptional diversity of 15 malignant gonadal GCTs and four normal testis biopsies by sequencing 131 whole genomes and 416 transcriptomes from 14 gonadal histologies, excised by laser capture microdissection. Our findings demonstrate that tumours were initiated by whole genome duplication likely in embryogenesis, within ~5-8 cell divisions post-PGC specification, followed by chromosome 12p gains associated with invasive disease. Of note, 12p imbalances were not only generated through GCT-typical isochromosomes, but also through non-isochromosomic configurations. Whilst tumours developed along homogenous phylogenetic pathways, they spawned manifold tissues independent of genetic subclonal diversification. A key feature of GCT tissues was the expression of fetal-specific genes. The transcriptional diversity notwithstanding, we found universal transcriptional elements correlated with hallmark 12p gains. Overall, our study reveals stereotyped phylogenies and transcriptomes underpinning the development of GCT that originate in fetal life and may lend themselves to therapeutic manipulation.

  Dataset EGAD00001007037

• An isogenic human iPSC model unravels neurodevelopmental abnormalities in SMA

  Whether neurodevelopmental defects underlie the selective neuronal death that characterizes neurodegenerative diseases is becoming an intriguing question. To address it, we focused on the motor neuron (MN) disease Spinal Muscular Atrophy (SMA), caused by reduced levels of the ubiquitous protein SMN. Taking advantage of the first isogenic human induced pluripotent stem cell-derived SMA model that we have generated and a spinal cord organoid system, here we report that the relative and temporal expression of early neural progenitor and MN markers is altered in SMA. Furthermore, the corrected isogenic controls only partially reverse these abnormalities. These findings raise the relevant clinical implication that SMN-increasing treatments might not fully amend SMA pathological phenotypes. The approach we have taken demonstrates that the discovery of new disease mechanisms is greatly improved by using human isogenic models. Moreover, our study implies that SMA has a developmental component that might trigger the MN degeneration.

  Study EGAS00001007259

• The NCAA-DoD Concussion Assessment, Research, and Education (CARE) Consortium

  Study Description: Established in 2014, the U.S. Department of Defense (DoD) and the National Collegiate Athletic Association (NCAA) funded the Concussion Assessment, Research and Education (CARE) Consortium to inform science, clinical care and public policy related to concussion and repetitive head impact exposure (HIE) in U.S. Military Service Academy (MSA) cadets and collegiate student-athletes. The primary aims of the initial study were to: (1) establish a multisite research consortium to characterize the effects of concussion and repetitive head impact exposure on brain health, (2) characterize the clinical sequelae and natural history of concussion, (3) characterize the effect of concussion and repetitive head impacts on brain structure and brain function. The 30 member institutions of the CARE Consortium (26 civilian universities/colleges and 4 military service academies) agreed to invite all varsity athletes to undergo multimodal clinical assessments at preseason baseline, and at 5 additional timepoints after concussion diagnosis. At the service academies, non-varsity athlete cadets/midshipmen were also studied. Assessment Categories At Each Time Point Baseline: • Demographics • Personal and Family History • Neurocognitive Assessment • Neurological Status • Postural Stability • Symptoms ACUTE POST-INJURY FOLLOW-UP (CARE 1.0) (24 hrs; 48hrs; Asymptomatic; Unrestricted Return to Play (RTP); 6 mos) • Neurocognitive Assessment • Neurological Status • Postural Stability • Symptoms CUMULATIVE & PERSISTENT EFFECTS. (CARE 2.0) In-Person Exit Visit; Post-grad Online • Demographics • Personal and Family History • Neurocognitive Assessment • Neurological Status • Postural Stability • Symptoms • PROs • MROs (at academies only) LONG-TERM EFFECTS (CARE/SALTOS Integrated (CSI))Annual Online Assessment (at MSAs only); In-Person Research Visits • Demographics • Symptoms • Psychological health • PROs • MROs (at academies only)A subset of athletes at 6 of the CARE institutions underwent additional assessments including multimodal MRI, proteomic and genomic biomarker characterization, and head impact quantification (helmet-based sensors). Assessment time points for the ARC/pARC Neurocognitive and Behavioral Testing was done at Baseline, <48hrs Post-Injury, Cleared for Return to Play Progression (Asymptomatic), Unrestricted Return to Play, 7 days following Return to Play, and at >60 days after final game of junior year until end of collegiate career.Blood biomarker collection was done at Baseline, <48hrs Post-Injury, Cleared for Return to Play Progression (Asymptomatic), 7 days following Return to Play, and at >60 days after final game of junior year until end of collegiate career. Multi-modal MRI studies were done at Baseline, <48hrs Post-Injury, Cleared for Return to Play Progression (Asymptomatic), 7 days following Return to Play, and at >60 days after final game of junior year until end of collegiate career. However, please note that only athletes from one study performance site completed a multi-modal MRI study at baseline.

  Study phs002175