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• LifeLines-DEEP population multi-omix cohort from the noth of the Netherlands.

  The LifeLines-DEEP cohort is a sub-cohort of the LifeLines cohort (167,729 participants) that employs a broad range of investigative procedures to assess the biomedical, socio-demographic, behavioral, physical and psychological factors that contribute to health and disease in the general Dutch population, (Scholtens 2015). A subset of approximately 1,500 participants also took part in LifeLines-DEEP. For these participants, additional biological materials were collected, including analysis of the gut microbiome composition. The phenotyping and processing of LifeLines-DEEP has been described in Tigchelaar (2015).

  Study EGAS00001001704

• Analysis of Donor Pancreata Defines the Transcriptomic Signature and Microenvironment of Early Neoplastic Pancreatic Lesions

  The adult healthy human pancreas has been poorly studied given lack of indication to obtain tissue from the pancreas in the absence of disease and rapid postmortem degradation. We obtained pancreata from brain dead donors thus avoiding any warm ischemia time. We found that neoplastic lesions occur frequently in healthy organs, in donors as young as in their 3rd decade of life. Using the 10X Genomics Platform, we performed single cell RNA sequencing on 7 donor pancreata, 6 of which we separately sequenced tissue from the pancreas head and tail, for a total of 11 sequencing runs. Of note, because one of our runs (containing sequencing from pancreas head and tail) did not pass qc, our final analysis in our study utilized 6 donor pancreata, 5 of which contained pancreas head and tail sequenced separately. This is a robust single-cell dataset of healthy, nonpathologic pancreas tissue and includes acinar, ductal, and non-epithelial cells (myeloid cells, fibroblasts, endothelial cells, lymphocytes).Briefly, the donor pancreas was dissected by a clinically-trained pancreatobiliary surgeon. The organ was dissected into head, body, and tail, with portions of each placed into DMEM media with 1% BSA/10µM Y27632. Tissue was minced into 1mm3 pieces, then digested with 1 mg/mL collagenase P for 20-30 min at 37°C with gentle agitation. Digested tissue was rinsed three times with DMEM/1% BSA/10µM Y27632, then filtered through a 40µm mesh. Resulting cells were submitted to the University of Michigan Advanced Genomics Core for single cell sequencing using the 10x Genomics Platform. FASTQ files of all sequencing runs along with clinical annotation of donors is available through this dbGaP submission.

  Study phs003229

• Molecular Phenotyping to Accelerate Genomic Epidemiology (MolPAGE)

  MolPAGE is an integrated EU project that aims to develop methods and tools for discovery of biomarkers associated with diabetes (see www.ocdem.ox.ac.uk for MolOBB and www.twinsuk.ac.uk for MolTWIN).

  Study EGAS00000000102

• Emergence of oncofetal plasticity is ubiquitous in early colorectal cancers

  Metastasis formation is classically considered a late-stage event in colorectal cancer (CRC) evolution. Yet, the time and patterning by which metastatic competence is acquired remain poorly understood. Here, we show that metastasis-associated oncofetal cell states already emerge at the earliest stages of CRC, concurrent with invasive front formation. However, while necessary for metastasis, we detect them ubiquitously among early non-metastatic cancers, highlighting additional bottlenecks like immune evasion. To understand how oncofetal cells first emerge, we generated multiregional organoid models that reflect successive tumor progression stages within individual early-stage CRCs. Whole-genome sequencing and growth factor-dependency assays exclude tumor cell-intrinsic acquired traits. In contrast, single-cell spatial atlases of the tumor-microenvironment before and after malignant transformation revealed stereotypic patterning of fibroblast subtypes resembling normal tissue architecture, resulting in distinct regional microenvironments. At the onset of malignant growth into the submucosa, the first cancer-associated fibroblasts (CAFs) to appear strongly resemble submucosal trophocytes and colocalize with oncofetal cell states at invasive fronts. Functionally, fibroblast-organoid co-cultures confirm that these trophocyte-like CAFs induce plastic transitioning to oncofetal states. Thus, interactions between tumor and submucosal fibroblasts directly following malignant transformation dictate the timing and location at which oncofetal plasticity first occurs during CRC progression.

  Study EGAS50000001532

• H3Africa - An integrated approach to the identification of genetic determinants of susceptibility to trypanosomiasis

  The objective of the TrypanoGEN project is to discover genetic variants associated with different responses to sleeping sickness infection. The project was designed in two phases:Phase 1) Variant discovery; 222 samples were sequenced to approximately 10X coverage on an Illumina 2500 with 2x150bp reads, at the University of Liverpool Center for Genomic Research. In addition, 77 samples from Cameroon and Zambia were sequenced to approximately 30X Coverage at Baylor College of Medicine. The sequenced reads were mapped onto the 1000 genomes project human_g1k_v37_decoy reference genome using BWA. The SNP calling on all the samples was done using the genome analysis tool kit GATK v3.4. Samples were selected from seven populations where Trypanosomiasis is endemic: Nilo-Saharan speakers from North-West Uganda and Niger-Congo speakers from South-East Uganda, DRC, Ivory Coast, Guinea, Cameroon and Zambia. The samples included 182 controls, 97 cases, 17 latent infections and 3 suspect cases. Phase 2) Variants discovered in Phase 1 will be used in the development of the H3Africa SNP chip. This chip will then be used in a GWAS study to identify variants associated with trypanosomiasis.

  Study EGAS00001002602

• The British Autozygosity Populations BioResource (2019-08-14)

  This data set contains whole exome sequences of individuals with self-stated parental relatedness from the East London Genes & Health cohort. Rare frequency functional variants in these healthy individuals will be studied with respect to the genetic health of the participants and loss-of-function analysis of human genes. 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 2019-08-14.

  Dataset EGAD00001005253

• The T cell receptor repertoire of tumor infiltrating T cells is predictive and prognostic for cancer survival

  Transcriptomic sequencing on pre-immunotherapy melanoma patients.

  Dataset EGAD00001007710

• WGS-Lung Cancer sample 30 pair

  This study includes 30 paired samples of Korean Lung Cancer paitients. 30 Lung Cancer samples are paired with each normal(Saliva derived for control) sequencing data.The results of this WGS study were analyzed by Mutect and GATK for ranking germline variants and cancer variants to make mutational profile matrix.

  Study EGAS00001001474

• Korean Lung Cancer - 36 pair WES data

  This study includes 36 paired samples of Korean Lung Cancer paitients.36 Lung Cnacer samples are paired with each normal(Saliva derived for control) sequencing data.The results of this WES study were analyzed by Mutect and GATK for ranking germline variants and cancer variants to make mutational profile matrix.

  Study EGAS00001002843

• Transgenerational Transmission of Post-Zygotic Mutations Suggests Symmetric Contribution of First Two Blastomeres to Human Germline

  Skin and blood samples were collected from four phenotypically normal individuals (mother, father, and children) from a randomly selected family. Whole genomes of the samples from these individuals were sequenced to a depth of 30X-200X. Sequencing data for the mother was previously analyzed and is available at NDA collection #2961. Sequenced reads from the children and father were aligned to the human reference genome (hg19) generating BAM files for each individual. We used post-zygotic mutations in the mother to trace cell lineages across human generations. Analysis of this family demonstrated that different cell lineages were transmitted to offspring. Coupled with analysis of publicly available data, this result revealed a fundamental difference between soma and germline in lineage allocation and suggested a 50:50 contribution of the first two blastomeres to the germline.

  Study phs003781