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• PDAC organoid genomic heterogeneity

  The establishment of patient-derived pancreatic cancer organoid culture in recent years creates an exciting opportunity for researchers to perform a wide range of in vitro studies on a model that closely recapitulates the tumor. Among the outstanding questions in pancreatic cancer biology are the causes and consequences of genomic heterogeneity observed in the disease. However, to use pancreatic cancer organoids as a model to study genomic variations, we need to first understand the degree of genomic heterogeneity and its stability within organoids. Here, we used single-cell whole-genome sequencing to investigate the genomic heterogeneity of two independent pancreatic cancer organoids, as well as their genomic stability with extended culture. Clonal populations with similar copy number profiles were observed within the organoids, and the proportion of these clones was shifted with extended culture, suggesting the growth advantage of some clones. However, sub-clonal genomic heterogeneity was also observed within each clonal population, indicating the genomic instability of the pancreatic cancer cells themselves. Furthermore, our transcriptomic analysis also revealed a positive correlation between copy number alterations and gene expression regulation, suggesting the “gene dosage” effect of these copy number alterations that translates to gene expression regulation.

  Study EGAS00001006782

• Genomic_Advances_in_Sepsis__GAinS__genotyping

  This cohort comprises a subset of pateints enrolled in the Genomic Advances in Sepsis (GAinS) study, an established biobank of adult sepsis patients. Patients with sepsis due to community acquired pneumonia or faecal peritonitis were recruited from 35 hospitals across the UK from 2005-2018, with samples for functional genomics and detailed clinical information collected over the first five days of ICU admission. DNA was extracted from buffy coat or whole blood samples using the Qiagen DNA extraction protocol, the automated Maxwell Blood purification kit (Promega), or the QIAamp Blood Midi kit protocol (Qiagen). Genotyping data were generated using the Illumina HumanOmniExpress BeadChip (295 patients), the Infinium CoreExome BeadChip (655 patients), and the Infinium Global Screening Array BeadChip (307 patients). Genotyping QC and imputation into the Haplotype Reference Consortium was perfomed within each batch. The datasets were combined and following post-imputation filtering data were available on 1168 samples. 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/

  Study EGAS00001007786

• Data Quality Control

  Data Quality Control High-throughput sequencing techniques have become the leading method to study, decode and discover the genomic origins of biological phenomenons. EGA provides a secure archival of such identifiable genomics data with the purpose of data-upcycling, i.e. to re-use these data for research. High-quality data standards are essential to ensure the quality and credibility of the research. Moreover, a quality check report can assure a researcher beforehand about the data that they will request access, therefore saving time and effort. The EGA has developed a File Quality Control Report (QC Report) to provide generic quality control reports for Fastq, SAM/BAM/CRAM, and VCF files deposited at EGA. This QC Report will allow users to get information regarding the files submitted within a specific dataset. The data requesters will obtain information such as the quality of reads, mapped reads, number of variants, and other features before starting the requesting process, which will save the efforts and time.Accessing file quality control reportsIn each dataset page, the user can explore the files that it contains by clicking the "files" tab. The Quality Control report of a file has two sections. The first one, contains general information about the file, such as the inferred assembly, total reads, the dataset or study where it comes from, etc. The second section contains plots that summarise interesting information about the file, for example, the base coverage distribution, base quality or mapped reads. The description of each plot is accessible by clicking the "i" button at the top-right corner of each plot box. Technical Description For analysing the fastq, SAM/BAM/CRAM and VCF files, the EGA applies a set of tools widely used in the bioinformatics community. FASTQ: FastQC, recognised as the gold standard tool by the community.Per base sequence quality, per sequence quality scores, per base sequence content, per sequence GC content, sequence duplication levels, etc.SAM/BAM/CRAM: samtools, also the gold standard, generates results plots useful to get an overall idea of the quality of the file.base coverage distribution, base quality, % of mapped reads, % of both mates mapped, singletons, duplicates, etc.VCF: vcftools and bcftools, combined with a custom script to infer the genome assembly.site frequency distribution, Ts/Tv, base changes, indel distribution, etc.

  Documentation access/request-data/quality-control-reports

• Context-specific regulatory genetic variation in MTOR dampens neutrophil-T cell crosstalk in pneumonia-associated sepsis, modulating disease

  Sepsis is a heterogeneous clinical syndrome with a high mortality, requiring personalised stratification strategies. Here, we characterise genetic variation that modulates MTOR, a critical regulator of metabolism and immune responses in sepsis. The effects are highly context specific, involving a regulatory element that affects MTOR expression in activated T cells with opposite direction of effect in neutrophils. We show that the G-allele of the lead variant, rs4845987, associated with decreased risk of T2D, reduces MTOR expression in T cells and improves survival in sepsis due to pneumonia, with effects specific to sepsis endotype. Using ex vivo models, we demonstrate that activated T cells promote immunosuppressive sepsis neutrophils through released cytokines, a process dampened by hypoxia and the mTOR inhibitor rapamycin. Our work demonstrates a novel epigenetic mechanism that fine-tunes MTOR transcription and T cell activity via the variant-containing regulatory element, which further exhibits an allelic effect upon vitamin C treatment. These findings reveal how genetic variation interacts with disease state to modulate immune cell-cell communication, providing a patient stratification strategy to inform more effective sepsis treatment.

  Study EGAS50000000894

• Integrated Clinical and Transcriptomic Profiling to Characterize Disease Phenotype

  Personalized medicine requires that we first address the challenge of genetic heterogeneity, prominent in rare cancers to common disease. While current clinical DNA sequence data successfully identify novel genetic variants, the genomic data alone are insufficient biomarkers of clinical phenotype. There is an unmet need for systematic integration of specific functional genomic data with patient genetic data, in order to bridge the knowledge gap between genetic variation and clinical phenotype. This specific study is focused on functional genomic data from platelets as disease-specific cells that are also ideal for proof-of-principle transcriptomic investigation (being anucleate), and highly-relevant to multiple disease processes.

  Study phs002121

• Genome-Wide Environment Interaction Study on Neurodevelopment in Children from Mexico and Bangladesh

  Cognitive development is known to be highly heritable, but various genome wide association studies (GWAS) have failed to find common single nucleotide polymorphisms (SNPs) which can explain a large proportion of the variance in cognitive ability. We hypothesized that an interaction between genes and exposure to potentially toxic metals may account for some proportion of this missing heritability. We genotyped 749 infants in Mexico and 636 infants in Bangladesh. Criteria for inclusion into the study are given below. We then performed a Genome Wide Environmental Interaction Study (GWEIS) with neurodevelopment outcomes. There were 552,487 SNPs in common between the two cohorts.

  Study phs000996

• BIRC5 Upregulation Enhances DNMT3A-Mutant T-ALL Cell Survival and Pathogenesis

  The goal of this study was to determine how patients with T-ALL who have DNA methyltransferase 3 alpha (DNMT3A) mutations develop resistance to therapy. Since DNMT3A is a methyltransferase, we examined the effect of those mutations on epigenetic regulation using whole genome bisulfite sequencing (WGBS). We also assessed any changes in gene expression using RNA-sequencing. We found that T-ALL patients with DNMT3A mutations are resistant to apoptosis and some chemotherapies. WGBS showed that DNMT3A mutated patients clustered together by their epigenetic profile, which was associated with hypomethylation at TERT and HOX genes. RNA sequencing identified differences in JAK/STAT signaling.

  Study phs003623

• Transcriptomic Profiling after B-Cell Depletion Reveals Central and Peripheral Immune Cell Changes in Multiple Sclerosis

  We investigated the immunological effects of B cell depletion therapy using ocrelizumab in treatment-naïve relapsing-remitting multiple sclerosis (RRMS) patients. Our primary aim was to delineate transcriptomic alterations in immune cell populations in peripheral blood before and after therapy, using single-cell RNA sequencing (scRNAseq). This study included 18 newly diagnosed, treatment-naïve RRMS patients who provided matched pre- and 6-month post-treatment peripheral blood mononuclear cells (PBMCs). A secondary cohort of five patients also contributed paired cerebrospinal fluid (CSF) samples. All RRMS patients were treated with ocrelizumab, except one patient in the CSF cohort who received rituximab.

  Study phs003938

• Multi-omics analysis of treated cancer samples

  We treated patient-derived cell lines with effective drug inhibitors that we discovered. To understand the mechanisms behind how the inhibitor can effectively inhibit tumor growth, we performed a series of RNA-Seq, Histone ChIP-Seq, TF ChIP-Seq and ATAC-Seq profiling for samples with and without treatment with the inhibitor. There are 18 RNA-Seq, 20 ATAC-Seq and 182 ChIP-Seq experiments performed. This includes 2 biological replicates. Novaseq 6000 was used to sequence the samples. Library preparation was performed in house for ChIP-Seq and ATAC-Seq, using NEB indexes, while libraries for RNA-Seq were constructed by the sequencing company hired. Total RNA was sequenced. Sequencing parameters used are PE150, bi-directional sequencing. For ATAC-Seq, sequencing was performed up to 40M reads, for ChIP-Seq, sequencing was performed up to 20M reads and for RNA-Seq, sequencing was performed up to 20M to 40M reads. Fastq files are uploaded here.

  Dataset EGAD50000000349

• Single-cell transcriptomics identifies pathogenic T-helper 17.1 cells and pro-inflammatory monocytes in ICI-related pneumonitis

  ICI-pneumonitis is a frequent serious adverse event of cancer immunotherapy hinging on a cell-mediated immune response, though the exact pathophysiology is currently unknown. Using single-cell transcriptomics, an enrichment of pathogenic (TBX21, RORC, IFNG, IL17A, CSF2 expressing) T-helper 17.1 cells and pro-inflammatory (TNF, IL1B, IL6, IL23A expressing) monocytes was identified in ICI-pneumonitis bronchoalveolar lavage fluid, putatively engaging in a feedforward inflammatory loop. This finding yields several novel therapeutic targets for the treatment of ICI-pneumonitis. Most notably repurposing anti-IL-23 merits further research as a potential efficacious and safe treatment for ICI-pneumonitis.

  Study EGAS00001006762