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• North American Brain Expression Consortium (NABEC) Exome Sequencing

  A fundamental challenge in the post-genome era is to understand and annotate the consequences of genetic variation, particularly within the context of human tissues. We describe a set of integrated experiments designed to investigate the effects of common genetic variability on mRNA expression distinct human brain regions. We show that brain tissues may be readily distinguished based on expression profile. We find an abundance of genetic cis regulation mRNA expression. We observe that the largest magnitude effects occur across distinct brain regions. We believe these data, which we have made publicly available, will be useful in understanding the biological effects of genetic variation.

  Study EGAS00001002110

• Identification of cis-regulatory mutations generating de novo edges in personalized cancer gene regulatory networks

  The identification of functional non-coding mutations is a key challenge in the field of genomics. Here we introduce μ-cisTarget to filter, annotate and prioritize cis-regulatory mutations based on their putative effect on the underlying ‘personal’ gene regulatory network. We validated μ-cisTarget by re-analyzing the TAL1 and LMO1 enhancer mutations in T-ALL, and the TERT promoter mutation in melanoma. Next, we re-sequenced the full genome of ten cancer cell lines and used matched transcriptome data and motif discovery to identify master regulators with de novo binding sites that result in the up-regulation of nearby oncogenic drivers.

  Study EGAS00001002571

• Chracterising_cellur_pathways_underlying_CD3_CD28_activation_of_human_CD4__cells

  We devised an approach to disentangle the TCR and CD28 pathways upon stimulation in naive and memory primary human CD4+ T cells (Tcons) in response to defined stimulatory signals. Sorted Tcons were activated using a titration of anti-CD3 and anti-CD28 in combination as well as individually. As a control we cultured cells in the same conditions but without the stimuli. In total, we defined seven conditions from four individuals for sequencing. 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 EGAS00001004147

• Tissue-specific cell-free DNA degradation quantifies circulating tumor DNA burden

  Profiling of circulating tumor DNA (ctDNA) may offer a non-invasive approach to monitor disease progression. Here, we developed a quantitative method, exploiting local tissue-specific cell-free DNA (cfDNA) degradation patterns, that accurately estimates ctDNA burden independent of genomic aberrations. Nucleosome-dependent cfDNA degradation at promoters and first exon-intron junctions was strongly associated with differential transcriptional activity in tumors and blood. A quantitative model, based on just 6 regulatory regions, could accurately predict ctDNA levels in colorectal cancer patients. Strikingly, a model restricted to blood-specific regulatory regions could predict ctDNA levels across both colorectal and breast cancer patients.

  Study EGAS00001004657

• Comprehensive Deep Sequencing Atlas in HCC tumors

  Establishment of a comprehensive deep sequencing atlas focused on Hepatocellular Carcinoma (HCC) tumors, employing Whole Genome Sequencing (WGS), RNA Sequencing (RNAseq), and Whole Exome Sequencing (WES). The atlas aims to unravel the intricate genetic landscape of HCC, providing a detailed characterization of genomic alterations, transcriptomic profiles, and key mutations associated with this liver cancer. The integration of WGS, RNAseq, and WES data offers a holistic perspective, facilitating a deeper understanding of the molecular mechanisms driving HCC pathogenesis. The resulting atlas serves as a valuable resource for researchers, clinicians, and the broader scientific community, contributing to advancements in HCC diagnostics, prognostics, and therapeutic interventions.

  Study EGAS00001007694

• Targeted sequencing of follicular lymphoma tumour samples from the UK's Haematological Malignancy Research Network

  Follicular lymphoma displays morphological and clinical heterogeneity, underpinned by shared molecular pathogenesis. Mutations in epigenetic regulators alongside t(14;18) have been identified as disease initiating events. Additional mutational diversity suggests disease heterogeneity. Whether this resolves into mechanistically distinct subsets remains an open question. Targeted sequencing was applied to an unselected population-based FL cohort (n=548) diagnosed in a catchment population of ~4 million (14 centers), with full clinical follow-up (n=538) that included 96 DLBCL transformations. We investigated whether molecular subclusters of FL can be identified, and whether mutational data provide predictive information relating to transformation.

  Study EGAS00001005238

• 2014_Lung_sq_WES

  Purpose Lung squamous cell carcinoma (SqCC) is the second most prevalent type of lung cancer. Currently, no targeted-therapeutics are approved for treatment of this cancer, largely due to lack of systematic understanding of the molecular parthenogenesis of the disease. To identify therapeutic targets and comparatively analyze them in lung SqCC, we probed somatic alterations of Korean lung SqCC. Patients and Methods We performed massively parallel whole-exome sequencing of 104 Korean lung SqCC patients’ samples with matched normal samples. In addition, copy number analysis and transcriptome analysis were conducted for a subset of these samples. Clinical association with cancer-specific somatic alterations was investigated.

  Study EGAS00001002844

• Genomic and ecologic characteristics of the airway microbial-mucosal complex

  Lung diseases due to infection and dysbiosis affect hundreds of millions of people world-wide. Microbial communities at the airway mucosal barrier are conserved and highly ordered, reflecting symbiosis and co-evolution with human host factors. We show here the results of the first systematic culture and whole-genome sequencing of the principal airway bacterial species. We match the gene content of bacterial isolates to human transcripts and metabolites expressed late in airway epithelial differentiation, identifying pathways that can sustain host interactions with the microbiota. Our results provide a systematic basis for decrypting interactions between commensals, pathogens, and mucosal immunity in lung diseases of global significance.

  Study EGAS00001006689

• RNA sequencing of a glioblastoma PDX cohort

  Patient-derived xenograft (PDX) models represent an essential tool for the preclinical evaluation of novel targeted therapies and their combinations. In this project, we molecularly characterized a comprehensive panel of glioma PDX models with well conserved molecular and pathological features over multiple passages. PDX samples were subjected to next generation sequencing (NGS). Characterization of cancer-relevant features including driver mutations or cellular processes was performed using mutational and gene expression data in order to identify potential biomarker or treatment targets in glioblastoma. In summary, we reported a newly established and molecularly characterized panel of glioma PDX models with high relevance for translational preclinical research.

  Study EGAS00001007119

• Identification of point mutations, expression perturbations, and gene fusions in T-cell acute lymphoblastic leukemia by RNA-seq

  RNA-seq is a promising technology to re-sequence protein-coding genes for the identification of single nucleotide variants, while simultaneously obtaining information on structural variations and gene expression perturbations. T-cell acute lymphoblastic leukemia (T-ALL) is caused by a combination of gene fusions leading to the over-expression of transcription factors reinforced by point mutations in oncogenes and tumor suppressor genes. We asked whether RNA-seq is suitable for the detection of driver mutations in these leukemias. We analyzed 31 T-ALL patient samples and 18 T-ALL cell lines by high-coverage paired-end RNA-seq.

  Study EGAS00001000536