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• Transcriptional profiling of tauopathies in human IPS-derived neurons (2019-08-21)

  This project is a pilot study, in collaboration with Maria Grazia Spillantini and Mariangela Iovino (Cambridge Centre for Brain Repair), to investigate the utility of IPS-derived neurons for the study of neurodegenerative disorders. Our aim is to characterise the transcriptional consequences of tauopathies using neurons derived from differentiated IPSCs as a model system. We will use IPS cells derived from six individuals, four with known mutations in the tau protein, 2 without. RNA will be extracted at Day 0 and Day 65 of differentiation by which time the neuronal tauopathy is apparent. RNA will be extracted and the transcriptome of each line characterised using RNAseq. We will then search for genes that are differentially expressed between the transcriptomes of individuals with tau mutations versus those in controls. My lab will analyse the RNAseq data, comparing both affected and controls and both time-points, to establish candidate genes. Darren Logan’s lab, along with our collaborators, will experimentally verify and further investigate these genes in additional lines and animal models. From this analysis we will generate a list of candidate genes that are differentially expressed between cases and controls. This study will not only help us understand the molecular basis of tauopathies, but also identify gene candidates for biomarkers of neurodegenerative disease. It will serve as a proof of principle for future planned studies into generating and transcriptomically analysing an allelic series of Tau mutations in IPSCs with a controlled genetic background. This data is part of a pre-publication release. For information on the proper use of pre-publication data shared by the Wellcome Trust Sanger Institute (including details of any publication moratoria), please see http://www.sanger.ac.uk/datasharing/ . This dataset contains all the data available for this study on 2019-08-21.

  Dataset EGAD00001005277

• GATA6 expression distinguishes classical and basal-like subtypes in advanced pancreatic cancer.

  PURPOSE: To determine the impact of basal-like and classical subtypes in advanced PDAC and to explore GATA6 expression as a surrogate biomarker. EXPERIMENTAL DESIGN: Within the COMPASS trial patients proceeding to chemotherapy for advanced PDAC undergo tumour biopsy for RNA sequencing. Overall response rate (ORR) and overall survival (OS) were stratified by subtypes and according to chemotherapy received. Correlation of GATA6 with the subtypes using gene expression profiling, in situ hybridization (ISH) were explored. RESULTS: Between December 2015-May 2019, 195 patients (95%) had enough tissue for RNA sequencing; 39 (20%) were classified as basal-like and 156 (80%) as classical. RECIST response data were available for 157 patients; 29 basal-like and 128 classical where the ORR was 10% vs. 33% respectively (p=0.02). In patients with basal-like tumours treated with modified FOLFIRINOX (mFFX) (n=22) the progression rate was 60% compared to 15% in classical PDAC (p= 0.0002). Median OS in the intention to treat population (n=195) was 9.3 months for classical vs. 5.9 months for basal-like PDAC (HR 0.47 95% CI 0.32-0.69, p=0.0001). GATA6 expression by RNAseq highly correlated with the classifier (p<0.001) and ISH predicted the subtypes with sensitivity of 89% and specificity of 83%. In a multivariable analysis, GATA6 expression was prognostic (p=0.02). In exploratory analyses, basal-like tumours, could be identified by keratin 5, were more hypoxic and enriched for a T cell inflamed gene expression signature. CONCLUSIONS: The basal-like subtype is chemoresistant and can be distinguished from classical PDAC by GATA6 expression.

  Dataset EGAD00001006081

• DAC for "Pyjacker identifies enhancer hijacking events in acute myeloid leukemia including MNX1 activation via deletion 7q"

  This is the DAC for the study "Pyjacker identifies enhancer hijacking events in acute myeloid leukemia including MNX1 activation via deletion 7q" of Christoph Plass (c.plass@dkfz.de).

  Dac EGAC50000000472

• Identify disease-related genes

  Raw data (idat file) analyzed by Illumina SNP array for patients in the 1st cohort and the 2nd cohort (51 diseases).

  Study JGAS000703

• Sensitive gene analysis of hereditary cardiovascular disease

  This research aims to identify disease sensitive genes and their gene variants by genome analysis for hereditary cardiovascular diseases.

  Study JGAS000295

• Whole-genome sequencing for 61 early-onset diabetes patients and 174 controls

  This dataset contains 241 paired FASTQ files for 61 early-onset diabetes patient and 174 controls sequenced with MGI Tech DNBSEQ-T10 and DNBSEQ-T7.

  Dataset EGAD50000001450

• PCA Atlas donor genotyping arrays (Axiom UK Biobank v2.0)

  Raw Axiom v2.0 UK Biobank Array CEL files for PCA Atlas donor buffy-coat DNA, used to generate SNP genotypes for demultiplexing single-cell and spatial transcriptomics libraries.

  Dataset EGAD00010002818

• Neuroblastoma Cell Line Circle-seq

  We generated Circle-seq data for 12 neuroblastoma cell lines to describe the landscape of extrachromosomal circular DNA in neuroblastoma.

  Study EGAS00001004796

• Chip-exo and Chip-nexus for five TFs in three colorectal cancer cell lines

  Chip-exo and Chip-nexus for FOXA1, HNF4A, KLF5, MYC, and TCF7L2 in colorectal cancer cell lines LoVo, GP5D, COLO320DM

  Dataset EGAD00001004099

• H3Africa H3AChipDesign MalSic

  The dataset includes BAM, FASTQ and decompressed gVCF files for 50 samples from Benin generated for the H3Africa Chip Design Study.

  Dataset EGAD00001004557