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• Oral microbiota composition assessed with 16S rRNA sequencing from adults aged over 65 years old.

  This is a oral microbiota amplicon dataset derived from adult participants aged over 65 years old. It consists a total number of 491 samples, stored in 982 paired-end FASTQ files with sequence lengths of 200 nucleotides generated with a Illumina MiSeq. Of those 491 samples, 347 were used in analysis, the remaining 144 samples are control samples.

  Dataset EGAD00001007705

• CRUK Accelerator: Non-small cell lung cancer whole exome and RNA sequencing

  Whole exome and RNASeq raw sequencing data for a cohort 24 patients with non-small cell lung cancer, 15 adenocarcinoma (8 female, 7 male) and 9 squamous cell carcinoma(5 female, 4 male). Median age at diagnosis was 69. Tumour tissue and PBMCs were used for whole exome sequencing and RNA sequencing. This data was generated as part of a study funded by a Cancer Research UK Centres Network Accelerator Award Grant (A21998).

  Dataset EGAD00001007934

• Single-cell RNA-seq data of bronchoalveolar lavage fluid and extramedullary relapse of a multiple myeloma patient with sarcoidosis-like reactions after anti-BCMA CAR T-cell therapy

  We performed single-cell RNA-sequencing (scRNA-seq) of cells in the bronchoalveolar lavage (BAL) fluid at 3-month follow-up of a multiple myeloma patient experiencing sarcoidosis-like pulmonary reactions after anti-BCMA CAR T-cell therapy (Sample alias: A8_3, A9_3; technical replicates). In addition we performed scRNA-seq of a extramedullary relapse lesion at 6-month follow-up (Sample alias: B10_3).

  Dataset EGAD00001008649

• Comprehensive RNA repository of tissue and plasma from patients with esophageal cancer or precursor lesions

  A comprehensive RNA repository (both coding and non-coding) from 17 patients diagnosed with esophageal adenocarcinoma, high-grade dysplastic or non-dysplastic Barrett’s esophagus. Per patient, a blood plasma sample, and a healthy esophageal and disease tissue sample were collected. This dataset includes both mRNA and small RNA sequencing data (fastq.gz files) of all tissue and plasma samples. In total,102 RNA-seq libraries from 51 samples (17 plasma and 34 tissue samples) were sequenced (plasma mRNA libraries were sequenced twice).

  Dataset EGAD00001006857

• Ultra-deep sequencing of cell-free DNA derived from reference materials and a patient with asymmetric overgrowth

  This dataset contains: Ultra-deep sequencing data using the Duplex sequencing technology of: 1.) SeraSeq cfDNA reference materials with spike-in variants with allele frequencies from 0% to 5% 2.) One cfDNA sample from a CRC patient 3.) One cfDNA sample from a patient with asymmetric overgrowth Paired-end sequencing was performed with 2x151 bp reads on the NextSeq 500 system. Data is provided as mapped .bam files (aligned to GRCh38/hg38).

  Dataset EGAD00001009784

• DNA-seq BAM files from 16 carriers of the BMPR2 p.Arg491Gln mutation in a family affected by HPAH

  Paired-end DNA-seq BAM files from 16 carriers of the BMPR2 p.Arg491Gln mutation in a family affected by hereditary pulmonary arterial hypertension (HPAH). Whole genome sequencing of these samples was performed in an Illumina HiSeq 4000 instrument. Libraries were prepared using the Fisher PE Kit (Kapa Biosystems). FASTQ files were processed at the CNAG (Barcelona) using the GEM short-read aligner on the human genome version hs37d5, producing a total of 16 BAM files.

  Dataset EGAD00001005757

• Amplicon-based sequencing of drug resistant lung cancer cell lines (2017-07-05)

  A EGFR mutant NSCLC cell line which is sensitive to AZD9291 inhibition was mutagenised with the chemical mutagen ENU and then drug selected using a AZD9291. Single cell derived colonies were then manually picked and expanded in drug. Resistance was confirmed in a 14 day assay and DNA was collected. These then underwent targeted amplicon-based sequencing to confirm candidate resistance effectors hypothesised from currently available literature. This dataset contains all the data available for this study on 2017-07-05.

  Dataset EGAD00001003425

• Hip OA Functional Genomics RNAseq (2017-06-09)

  From 9 patients undergoing hip joint replacement surgery for osteoarthritis, we collected 3 cartilage samples each: a low-grade sample (no obvious evidence of damage or fibrillation); a high-grade sample (damaged and fibrillated cartilage); an osteophytic sample (overlaid bony protrusions mainly around the margins of the articular surface). Multiplexed libraries were sequenced on Illumina HiSeq 2000 (75bp paired-end read length) and a cram file was produced for each sample. This dataset contains all the data available for this study on 2017-06-09.

  Dataset EGAD00001003354

• Analysis of tumor periphery and center-specific mutations in renal cell carcinoma

  Renal cell carcinoma (RCC) is a genomically heterogeneous tumor. In the present project, the question whether intratumoral heterogeneity follows a zonal pattern indicating spatial niches was addressed. Whole exome sequencing of 16 paired samples from tumor periphery and center revealed a number of region-specific functional SNVs and Indels. Therefore, RCCs are not composed of evenly admixed tumor cells but show topological differences in their clonal composition.

  Dataset EGAD00001002067

• microRNA-seq of human serum from a longitudinal study of 66 women with no history of cancer

  This dataset includes microRNA sequencing data from 198 human serum samples, representing a subset of 66 women with no history of cancer who participated in the UKCTOCS study and with serum samples collected at three timepoints over a period of up to 5 years. Small RNA libraries prepared from the serum samples were sequenced with 50-bp single end reads on an Illumina HiSeq 2000 instrument. Data is provided as FASTQ files.

  Dataset EGAD00001004348

• Melanoma-Til Study RNAseq

  In this study, mutations present in a series of human melanomas (stage IV disease) will be determined, using autologous blood cells to obtain a reference genome. From each of the samples that are analyzed, tumour-infiltrating T lymphocytes have also been isolated. This offers a unique opportunity to determine which (fraction of) mutations in human cancer leads to epitopes that are recognized by T cells. The resulting information is likely to be of value to understand how T cell activating drugs exert their action.

  Dataset EGAD00001000325

• ENU-LS-411N-TripleTherapy

  BRAF V600E colorectal cancers do not respond to the only currently FDA approved targeted therapy for CRC. There is currently a trial underway in the UK recruiting V600E CRC patients for treatment with a triple therapy combination of Cetuximab, Trametinib and Dabrafenib. We have mutagenized a pool of V600E CRC cell lines and treated with this triple therapy to select out drug resistant clones. We will now sequence these drug resistant clones with the aim of identifying common point mutations engendering resistance to this new therapy.

  Dataset EGAD00001002051

• Whole exome sequencing of young onset Primary Sclerosing Cholangitis

  Primary sclerosing chloangitis is a rare autoimmune disease of the liver (prevalence =10/100,000) with a mean age of onset of 40 years. We are currently undertaking GWASand immunochip experiments to identify loci underlying PSC susceptibility. Through ourcollaborators at the University of Calgary we have access to DNA from three parent-offspringtrios where the children required liver transplants due to PSC before the age of 9. These areextremely rare cases indeed and we believe that exome-sequencing represents a powerfulmeans of identifying the causal mutation underlying this severe phenotype.

  Dataset EGAD00001000671

• RNASeq_EGAS00001001306

  RNASeq sequencing. Each library was sequenced using TruSeq SBS Kit v3-HS, in paired-end mode with a read length of 2 × 76 bp. We generated more than 20 million paired-end reads for each sample in a fraction of a sequencing lane on HiSeq2000 (Illumina Inc.) following the manufacturer’s protocol. Image analysis, base calling and quality scoring of the run were processed using the manufacturer’s software Real Time Analysis (RTA 1.13.48) and followed by generation of FASTQ sequence files.

  Dataset EGAD00001001443

• A small cell lung cancer genome reports complex tobacco exposure signatures

  Cancer is driven by mutation. Worldwide, tobacco smoking is the major lifestyle exposure that causes cancer, exerting carcinogenicity through 60 chemicals that bind and mutate DNA. Using massively parallel sequencing technology, we sequenced a small cell lung cancer cell line, NCI-H209, to explore the mutational burden associated with tobacco smoking. 22,910 somatic substitutions were identified, including 132 in coding exons. Multiple mutation signatures testify to the cocktail of carcinogens in tobacco smoke and their proclivities for particular bases and surrounding sequence context. Effects of transcription-coupled repair and a second, more general expression-linked repair pathway were evident. We identified a tandem duplication that duplicates exons 3-8 of CHD7 in-frame, and another two lines carrying PVT1-CHD7 fusion genes, suggesting that CHD7 may be recurrently rearranged in this disease. These findings illustrate the potential for next-generation sequencing to provide unprecedented insights into mutational processes, cellular repair pathways and gene networks associated with cancer.

  Study EGAS00000000051

• Comprehensive Omics Analysis of Pediatric Solid Tumors and Establishment of a Repository for Related Biologic Studies (10C0086)

  This study (10-C-0086) collected and analyzed tumor and circulating tumor omics of pediatric and young adult patients with relapsed rhabdomyosarcoma who were co-enrolled in and receiving treatment on the interventional study 17-C-0049. We sought to describe the summary genomic findings of tumors, and report on the detection of circulating tumor DNA (ctDNA) in serial samples. Tumor tissue and blood were collected and analyzed. Tumor samples were subjected to whole exome and/or whole genome sequencing paired with RNA-Seq. Cell free DNA (cfDNA) was extracted from serially collected blood samples and sequenced. Fusion status, mutations, and IGF1R and YES1 expression from tumor samples revealed the presence of a PAX3 fusion in most samples, a number of common mutations, and universal but heterogeneous expression of IGF-1R and YES1. ctDNA was detected above the 3% threshold in a majority of patients and analysis of cfDNA demonstrated an ability to monitor tumor clonal evolution.

  Study phs003243

• Blepharospasm in a Multiplex African-American Pedigree

  Blepharospasm (BSP) is a late-onset focal dystonia characterized by involuntary contractions of the orbicularis oculi muscles. Genetics plays an important role on the pathogenesis of BSP, especially in hereditary BSP families. In this project, a large African-American pedigree with BSP was phenotypically characterized and its relationship with known common dystonia genes was investigated with Sanger sequencing on dystonia genes such as THAP1, TOR1A and GNAL. And whole-exome sequencing (EXOME) of the proband was performed to identify all other dystonia-associated genes for potentially pathogenic SVs. A novel THAP1 SV (c.314T>C, p.L105S) was identified in the family, however, this SV did not co-segregate with blepharospasm in the pedigree. No pathogenic or likely pathogenic SVs in other dystonia-associated genes were identified with whole-exome sequencing. The current study makes available phenotype data and summary genotype data of n=12 family members (mutation absent/heterozygous for THAP1); whole exome sequencing data of one (het) subject are available through public SRA.

  Study phs001206

• A Whole Genome Association Scan for Myopia and Glaucoma Endophenotypes using Twin Studies

  Myopia and glaucoma are highly prevalent ophthalmic disorders worldwide and contribute significantly to ocular morbidity. There is substantial evidence that genetic factors play a significant role in the development of non-syndromic myopia and glaucoma. We propose to perform mapping studies for well-characterized twin populations in the United Kingdom and Australia in order to ultimately identify implicated genes for these disorders and related ocular parameters. This will provide a fundamental molecular understanding of how these disorders develop, and may lead to directed physiologic (i.e. pharmacologic, gene therapy) interventions. Our aim is to dissect the genetic basis of the eye disorders myopia and glaucoma. Instead of limited analyses of the trait/disease in a dichotomous manner, we are using continuous phenotypes of measures of refraction and intermediate phenotypes of glaucoma to analyze quantitative traits in unselected population samples of volunteer twins. Achievement of this goal requires cooperative efforts and large sample sizes. Thus, we have created an international collaboration of large complementary studies.

  Study phs000142

• ZNF703 is a common Luminal B breast cancer oncogene that differentially regulates luminal and basal progenitors in human mammary epithelium.

  The telomeric amplicon at 8p12 is common in oestrogen receptor-positive (ER+) breast cancers. Array-CGH and expression analyses of 1172 primary breast tumours revealed that ZNF703 was the single gene within the minimal amplicon and was amplified predominantly in the Luminal B subtype. Amplification was shown to correlate with increased gene and protein expression and was associated with a distinct expression signature and poor clinical outcome. ZNF703 transformed NIH 3T3 fibroblasts, behaving as a classical oncogene, and regulated proliferation in human luminal breast cancer cell lines and immortalized human mammary epithelial cells. Manipulation of ZNF703 expression in the luminal MCF7 cell line modified the effects of TGFβ on proliferation. Overexpression of ZNF703 in normal human breast epithelial cells enhanced the frequency of in vitro colony-forming cells from luminal progenitors. Taken together, these data strongly point to ZNF703 as a novel oncogene in Luminal B breast cancer.

  Study EGAS00000000082

• MethylBERT enables read-level DNA methylation pattern identification and tumour deconvolution using a Transformer-based model

  DNA methylation (DNAm) is a key epigenetic mark that shows profound alterations in cancer. Read-level methylomes enable more in-depth DNAm analysis due to the broad coverage and preservation of rare cell-type signals, compared to array-based data such as 450K/EPIC array. Here, we propose MethylBERT, a novel Transformer-based model for read-level methylation pattern classification. MethylBERT identifies tumour-derived sequence reads based on their methylation patterns and genomic sequence and the method estimates tumour cell fractions within bulk samples. In our evaluation, MethylBERT outperforms existing deconvolution methods and demonstrates high accuracy regardless of methylation pattern complexity, read length and read coverage. Moreover, we show its applicability to cell-type deconvolution as well as non-invasive early cancer diagnostics using liquid biopsy samples. MethylBERT represents a significant advancement in read-level methylome analysis and enables accurate tumour purity estimation. The broad applicability of MethylBERT will enhance studies on both tumour and non-cancerous bulk methylomes.

  Study EGAS50000000806

• Efficient prediction of a spatial transcriptomics profile better characterizes breast cancer tissue sections without costly experimentation

  Spatial transcriptomics is an emerging technology requiring costly reagents and considerable skills, limiting the identification of transcriptional markers related to histology. Here, we show that predicted spatial gene-expressions in unmeasured regions and tissues can enhance biologists��� histological interpretations. We developed the Deep learning model for Spatial gene Clusters and Expression, DeepSpaCE and confirmed its performance using the spatial-transcriptome profiles and immunohistochemistry images of consecutive human breast cancer tissue sections. For example, the predicted expression patterns of SPARC, an invasion marker, highlighted a small tumor-invasion region that is difficult to identify using raw data of spatial transcriptome alone because of a lack of measurements. We further developed semi-supervised DeepSpaCE using unlabeled histology images and increased the imputation accuracy of consecutive sections, enhancing applicability for a small sample size. Our method enables users to derive hidden histological characters via spatial transcriptome and gene annotations, leading to accelerated biological discoveries without additional experiments.

  Study JGAS000290

• A tumor-associated photoreceptor signature unifies distinct central nervous system malignancies

  Pineoblastoma is a clinically aggressive childhood brain tumor composed of distinct molecular subgroups with divergent driver genes, demographics, and clinical outcomes. To identify developmental origins and mechanisms governing disease pathogenesis, we derive single-cell transcriptomes from pineal parenchymal tumors, aligning malignant cells with our atlas of pineal gland development to retrace cellular origins. Integrative computational analyses maps pineoblastoma origins to transient cycling pinealocyte progenitors during development. Lineage-specific perturbation of suspected drivers in the early pineal gland yields preclinical models representative of consensus molecular subgroups. Multi-omic characterization of patient tumors and these models uncovers a tumor-associated photoreceptor signature common to pineoblastoma, retinoblastoma, and Group 3 medulloblastoma. Transcriptional activity of this signature within respective cellular origins establishes a developmental basis for molecular similarities between entities. Photoreceptor signature constituents are selective dependencies across these anatomically distinct central nervous system malignancies, motivating future studies evaluating developmentally encoded programs of malignancy as potential therapeutic liabilities.

  Study EGAS50000001457

• Transcriptome changes in circulating immune cells of critical COVID-19 patients predict a specific metabolic and epigenetic imprint

  The progression to severe COVID-19 arises predominantly from a dysregulated host immune response, although the underlying regulatory mechanisms still remain partially elusive. This limits a prompt prediction of disease progression and restrains our understanding of “long COVID”. Here, we analyzed the transcriptomes of peripheral blood mononuclear cells collected from COVID-19 patients experiencing different degrees of the disease and control patients. In critical COVID-19 patients, we found an altered regulatory network involving microRNAs, long non-coding RNAs, and coding genes that control mRNA translation-related genes, epigenetics, and metabolism. We also observed an upregulation of tRNA aminoacylation genes and increased expression of coding genes enriched for the cognate amino acids. Collectively, our findings indicate a broad perturbation of the gene expression landscape that characterizes the aberrant host immune response in critical COVID-19 patients and is potentially coordinated by alterations in microRNA expression and tRNA metabolism.

  Study EGAS50000000965

• Full genome sequencing of a monozygotic twin discordant for schizophrenia

  We sequenced the genomes from a monozygotic twin discordant for schizophrenia and a tumor-normal pair of an ovarian cancer patient. Using whole-genome twin data to discriminate between correctly identified single nucleotide variants (SNVs) and errors a strategy for the accurate detection of SNVs was developed. By applying stringent sequencing quality measures, excluding error-prone regions and selecting SNVs identified by different mapping and variation calling algorithms, error rates were ~37-fold reduced. This enabled us to identify the first discordant SNVs in monozygotic twins using whole-genome sequencing. In addition, by showing that novel SNVs are highly enriched in errors, accurate estimates of the number of novel and rare SNVs occurring in unrelated Caucasian individuals were obtained. Finally, somatic mutations in coding and regulatory sequences were reliably identified in the highly rearranged ovarian tumor. Overall, our data demonstrate that strategies to reduce error rates in whole-genomes are required for disease gene discovery.

  Study EGAS00001000152

• Translation of non-canonical open reading frames as a cancer cell survival mechanism in childhood medulloblastoma

  A hallmark of high-risk childhood medulloblastoma is the dysregulation of RNA translation. Currently, it is unknown whether medulloblastoma dysregulates the translation of putatively oncogenic non-canonical open reading frames. To address this question, we performed ribosome profiling of 32 medulloblastoma tissues and cell lines and observed widespread non-canonical ORF translation. We then developed a step-wise approach to employ multiple CRISPR-Cas9 screens to elucidate functional non-canonical ORFs implicated in medulloblastoma cell survival. We determined that multiple lncRNA-ORFs and upstream open reading frames (uORFs) exhibited selective functionality independent of the main coding sequence. One of these, ASNSD1-uORF or ASDURF, was upregulated, associated with the MYC family oncogenes, and was required for medulloblastoma cell survival through engagement with the prefoldin-like chaperone complex. Our findings underscore the fundamental importance of non-canonical ORF translation in medulloblastoma and provide a rationale to include these ORFs in future cancer genomics studies seeking to define new cancer targets.

  Study EGAS00001007426