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• IDH- and H3-wildtype high-grade gliomas in teenagers and young adults

  Whole exome sequencing of high grade gliomas occurring in teenagers and young adults between the ages of 13 and 30. This study combines methylation array profiling, whole exome sequencing and fusion panels sequencing to provide and integrated diagnosis of tumours in this age group.

  Study EGAS50000000641

• Benchmark Dataset for Somatic Mutation Calling in Cell-Free DNA

  This study provides a comprehensive benchmarking resource for somatic variant detection in cell-free DNA (cfDNA) from cancer patients. Longitudinal plasma samples from colorectal and breast cancer cohorts were selected to create patient-matched dilution series spanning ultra-low to high circulating-tumour-DNA (ctDNA) fractions, while preserving each individual’s germline and clonal haematopoiesis background. Deep whole-genome sequencing (150×) and ultra-deep whole-exome sequencing (2,000×) generated a reference call set of ~37,000 single-nucleotide variants and ~58,000 insertions/deletions. These data enabled systematic evaluation of nine somatic variant callers across variable ctDNA levels and sequencing depths, and were further used to explore machine-learning–guided parameter tuning. The resulting dataset offers an openly accessible framework for developers and clinicians to assess and optimize somatic variant calling in liquid biopsy applications.

  Dataset EGAD50000001870

• Whole-genome sequencing of bladder cancers of various stages and grades to search for driver mutations, chromosome-scale somatic changes, mutation signatures and clonal structures.

  This discovery set of tumours cancers with whole-genome sequence data comprised 14 bladder cancers, paired with peripheral blood, that had been collected from unrelated individuals presenting to the Urology Department, Royal Hallamshire Hospital, Sheffield between June 2008 and September 2011. Four cancers were of low-grade papillary morphology (pTaG1-2), five were high grade invading the lamina propria (pT1G3, with two subsequently becoming muscle-invasive); and five were muscle-invasive (pT2-pT3). All tumours were sampled at transurethral resection or cystectomy and had not previously received any other therapy. The presence of a majority of cancer cells in the tumour specimens was confirmed by routine histological assessment. Genomic DNA was extracted from each tumour and paired blood sample using standard methods.

  Study EGAS00001000738

• Pancreatic islets PISA RNA-seq samples

  GWAS have identified more than 700 genetic signals associated with type 2 diabetes (T2D). To gain insight into the underlying molecular mechanisms, we created the Translational human pancreatic Islet Genotype tissue-Expression Resource (TIGER), aggregating >500 human islet RNA-seq and genotyping datasets. We imputed genotypes using 4 reference panels and meta-analyzed cohorts to improve coverage of expression quantitative trait loci (eQTL) and developed a method to combine allele-specific expression across samples (cASE). We identified >1 million islet eQTLs (56% novel), of which 53 colocalize with T2D signals (60% novel). Among them, a low-frequency allele that reduces T2D risk by half increases CCND2 expression. We identified 8 novel cASE colocalizations, among which an SLC30A8 T2D associated variant. We make all the data available through the open-access TIGER portal (http://tiger.bsc.es), which represents a comprehensive human islet genomic data resource to elucidate how genetic variation affects islet function and translate this into therapeutic insight and precision medicine for T2D.

  Study EGAS00001005535

• Detection of isoforms and genomic alterations by high-throughput full-length single-cell RNA sequencing in HGSOC

  Understanding the complex background of cancer requires genotype-phenotype information in single-cell resolution. Long-read single-cell RNA sequencing (scRNA-seq), capturing full-length transcripts, lacked the depth to provide this information so far. Here, we increased the PacBio sequencing depth to 12,000 reads per cell, leveraging multiple strategies, including artifact removal and transcript concatenation, and applied the technology to samples from three human ovarian cancer patients. Our approach captured 152,000 isoforms, of which over 52,000 were novel, detected cell type- and cell-specific isoform usage, and revealed differential isoform expression in tumor and mesothelial cells. Furthermore, we identified gene fusions, including a novel scDNA sequencing-validated IGF2BP2::TESPA1 fusion, which was misclassified as high TESPA1 expression in matched short-read data, and called somatic and germline mutations, confirming targeted NGS cancer gene panel results. With multiple new opportunities, especially for cancer biology, we envision long-read scRNA-seq to become increasingly relevant in oncology and personalized medicine.

  Study EGAS00001006807

• 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

• Regulation of T Cell CXCL13 Production

  This study evaluated the signals that regulate production of the B cell chemoattractant CXCL13 by human CD4 T cells. Single-cell and bulk RNA-seq datasets evaluated the gene expression changes induced by TGF-beta and the aryl hydrocarbon receptor (AHR), two signals that regulate CXCL13 production. Bulk ATAC-seq data evaluated the epigenetic changes in T cell stimulated with an AHR agonist or antagonist. Ex vivo bulk RNA-seq data of sorted T cell subsets from blood of patients with lupus and control donors interrogated the gene expression differences in sorted T cell subsets. Ex vivo ATAC-seq data allowed comparison of epigenetic profiles of PD-1hi Tph cells from rheumatoid arthritis synovial fluid and PD-1hi T follicular helper (Tfh) cells from tonsil to PD-1low CD4 T cells from the same samples. Single-cell RNA-seq data of T cells from lupus patients before and after treatment with anifrolumab (anti-IFNAR) allowed interrogation of T cell populations that change with anifrolumab treatment. These datasets allowed for genomic interrogation of changes induced by AHR, TGF-beta, and interferon and their relationship to CXCL13 production.

  Study phs003582

• Novel regional age-associated DNA methylation changes within human common disease-associated loci

  Background: Advancing age progressively impacts on risk and severity of chronic disease. It also modifies the epigenome, with changes in DNA methylation, due to both random drift and variation within specific functional loci. Results: In a discovery set of 2,238 peripheral-blood genome-wide DNA methylomes (MeDIP-seq) aged 19-82 years, we identified 71 age-associated Differentially Methylated Regions (a-DMRs, p < 1.85 x 10-8) within the Linkage Disequilibrium (LD) blocks of the NIH Catalogue of published GWAS SNPs. This included 52 novel regions, 29 within loci not covered by 450k or 27k Illumina array, and with marked enrichment for Poised Promoters and Enhancers across multiple cell types. In a replication set of 2,084 DNA methylomes, 95.7% of the a-DMRs showed the same direction of ageing effect, with 80.3% and 53.3% replicated to p < 0.05 and p < 1.85 x 10-8, respectively. Conclusion: By analysing the functionally enriched disease and trait-associated regions of the human genome, we identified novel epigenetic ageing changes, which could be useful biomarkers or provide mechanistic insights into age-related common diseases.

  Study EGAS00001001910

• Whole genome sequencing of pheochromocytoma and paraganglioma arising from germline SDHB mutations

  Paired-end 150 basepair whole genome sequencing of 94 SDHB-deficient non-metastatic and metastatic pheochromocytoma and paraganglioma. Libraries were prepared using the Illumina® TruSeq™ DNA Nano library preparation method according to the manufacturer’s instructions at The University of Melbourne Centre for Cancer Research (UMCCR) using 200ng input DNA and a 550 base pair insert size. Samples were sequenced in separate batches on the Illumina® Nova-Seq 6000 according to manufacturer’s instructions (Illumina, USA). Included in this dataset are FASTQ format files containing raw read data, CRAM format files containing reads aligned to GRCh38, and VCF format files containing germline variants calls.

  Dataset EGAD50000000502

• Luminal progenitor cell line iHBEC(CD117)

  Basal-like breast cancer originates in luminal progenitors, frequently with an altered PI3K pathway, and focally in close association with genetically altered myoepithelial cells at the site of tumor initiation. The exact trajectory behind this bi-lineage phenomenon remains poorly understood. Here we used a breast cancer relevant transduction protocol including hTERT, shp16, shp53, and PIK3CA(H1047R) to immortalize FACS isolated luminal cells, and we identified a candidate multipotent progenitor. We found that the apparent luminal phenotype of these oncogene transduced progenitors was metastable giving rise to basal-like cells dependent on culture conditions. After culturing the cells for more than 60 passages, cells were subjected to scRNA-seq as well as bulk RNA sequencing of two subpopulations (CD271+ and CD271-).

  Dataset EGAD50000000723

• Naive TCR V, D and J gene usage frequencies

  This dataset contains gene usage matrices calculated from the processed productively rearranged bulk TCR sequences from peripheral blood CD4+ T cells from 103 subjects with celiac disease and 103 control donors. The files contain per sample V, D and J gene usage frequencies for TRA and TRB sequences. Unique rearrangements were quantified with Alakazam in gene mode. More details about processing steps are found in the linked publication. The dataset also contains an accompanying metadata file (csv).

  Dataset EGAD50000002726

• Naive BCR V, D and J gene usage frequencies

  This dataset contains gene usage matrices calculated from the processed productively rearranged bulk BCR sequences from peripheral blood B cells from 102 subjects with celiac disease and 102 control donors. The files contain per sample V, D and J gene usage frequencies for IGH, IGK and IGL sequences. Unique rearrangements were quantified with Alakazam in gene mode. More details about processing steps are found in the linked publication. The dataset also contains an accompanying metadata file (csv).

  Dataset EGAD50000002727

• High hyperdiploid ALL single cell whole genome sequencing

  This dataset was collected from viable bone marrow cells obtained at diagnosis from nine patients with high hyperdiploid ALL and one normal bone marrow sample. All samples were subjected to low pass single cell whole genome sequencing with the median sequencing coverage of 0.02x. Single nuclei in G0/G1 phase were isolated using a fluorescence-activated cell sorting (FACS) cytometer. DNA libraries were constructed and associated next-generation sequencing was carried out by European Research Institute for the Biology of Ageing (ERIBA), University of Groningen, University Medical Center Groningen, Groningen, The Netherlands. Further details regarding the DNA libraries construction are available by Bos et. al., 2019 (https://link.springer.com/protocol/10.1007/978-1-4939-8931-7_15).

  Dataset EGAD00001008988

• BipEx_ODonovan_Cardiff

  "BipEx_EGAS000010058452_ODonovan_Cardiff Bipolar Disorder Exomes. This research project was a collaboration between Cardiff University, UK and the Stanley Center at the Broad Institute. In this project we sequenced and analyzed the whole exomes of Bipolar case/control samples from collaborators in UK. Genomic DNA from each sample was sequenced to a mean depth of 20x."

  Dac EGAC50000000130

• BipEx_Craddock_Cardiff

  "BipEx_EGAS00001005845_Craddock_Cardiff Bipolar Disorder Exomes. This research project was a collaboration between Cardiff University, UK and the Stanley Center at the Broad Institute. In this project we sequenced and analyzed the whole exomes of 2,458 Bipolar case/control samples from collaborators in UK. Genomic DNA from each sample was sequenced to a mean depth of 20x."

  Dac EGAC50000000135

• BipEx_Reif_Wurzburg

  "BipEx_EGAS00001005858_Reif_Wurzburg Bipolar Disorder Exomes. This research project was a collaboration between University Hospital Frankfurt and the Stanley Center at the Broad Institute. In this project we sequenced and analyzed the whole exomes of 823 Bipolar case/control samples from collaborators in Germany. Genomic DNA from each sample was sequenced to a mean depth of 20x."

  Dac EGAC50000000145

• BipEx_McQuillin_London

  "BipEx_EGAS00001005851_McQuillin_London Bipolar Disorder Exomes. This research project was a collaboration between University College London, UK and the Stanley Center at the Broad Institute. In this project we sequenced and analyzed the whole exomes of 3,046 Bipolar case/control samples from collaborators in UK. Genomic DNA from each sample was sequenced to a mean depth of 20x."

  Dac EGAC50000000136

• BipEx_Blackwood_Edinburgh

  "BipEx_EGAS00001005843_Blackwood_Edinburgh Bipolar Disorder Exomes. This research project was a collaboration between University of Edinburgh, UK and the Stanley Center at the Broad Institute. In this project we sequenced and analyzed the whole exomes of 932 Bipolar case/control samples from collaborators in UK. Genomic DNA from each sample was sequenced to a mean depth of 20x."

  Dac EGAC50000000134

• BipEx_Corvin_TCD

  BipEx_EGAS00001005844_Corvin_Dublin Bipolar Disorder Exomes. This research project was a collaboration between Trinity College Dublin, Ireland and the Stanley Center at the Broad Institute. In this project we sequenced and analyzed the whole exomes of 191 Bipolar case/control samples from collaborators in Ireland. Genomic DNA from each sample was sequenced to a mean depth of 20x.

  Dac EGAC50000000131

• BipEx_Ouwehand_Cambridge

  "BipEx_EGAS000010058454_Ouwehand_Cambridge Bipolar Disorder Exomes. This research project was a collaboration between Cambridge University, UK and the Stanley Center at the Broad Institute. In this project we sequenced and analyzed the whole exomes of 2,873 Bipolar case/control samples from collaborators in UK. Genomic DNA from each sample was sequenced to a mean depth of 20x."

  Dac EGAC50000000138

• BipEx_Owen_Cardiff

  "BipEx_EGAS000010058455_Owen_Cardiff Bipolar Disorder Exomes. This research project was a collaboration between Cardiff University, UK and the Stanley Center at the Broad Institute. In this project we sequenced and analyzed the whole exomes of 1,106 Bipolar case/control samples from collaborators in UK. Genomic DNA from each sample was sequenced to a mean depth of 20x."

  Dac EGAC50000000139

• BipEx_Adolfsson_Umea

  "BipEx_EGAS00001005842_Umea University Bipolar Disorder Exomes. This research project was a collaboration between Umea University, Sweden and the Stanley Center at the Broad Institute. In this project we sequenced and analyzed the whole exomes of 924 Bipolar case/control samples from collaborators in Sweden. Genomic DNA from each sample was sequenced to a mean depth of 20x."

  Dac EGAC50000000133

• Whole exome sequence analysis in sporadic amyotrophic lateral sclerosis

  To identify a susceptible gene for amyotrophic lateral sclerosis, exome sequence analysis was conducted in patients with amyotrophic lateral sclerosis and control subjects to perform whole genome association studies. In this data set, exome sequencing data of 11 patients with amyotrophic lateral sclerosis was included.

  Study JGAS000013

• Whole exome sequencing study for 8 pairs of primary NSCLCs and distant metastases

  Whole exome sequencing study for 8 pairs of primary NSCLCs and distant metastases. This dataset includes a total of 30 samples.

  Dataset EGAD00001005764

• RNAseq of ribosomal footprints

  Cancer genes can affect ribosomal RNA processing and this can underlie their essentiality to cells, making them cell-essential in the same way as ribosomal genes themselves. We want to confirm this, in order to understand the results of our CRISPR drop-out screens.NOTE FROM BESPOKE TEAM: Run a single read 1 (forward read) of 30 bases, then an index 1 read as normal. This would fit a 50cycle kit

  Dataset EGAD00001001930