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• The Celiac Gene Expression Data Access Committee

  This study presents RNA sequenced from several intestinal phenotypes such as from patients with damaged intestinal mucosa as well as from those without a damaged intestine but still an autoantibody response to tissue transglutaminase (“potential celiac disease”) or those with treated celiac disease. By combining phenotypes in a much larger number of tissue samples from both peripheral blood and mucosal biopsies, we found highly differentially expressed genes, but also identify genes involved in controlling and triggering celiac disease associated changes. This study identifies molecular mechanisms involved in celiac disease and new possible targets for treatment and for identification of individuals at risk.

  Dac EGAC50000000630

• Correction of FFPE artefacts in WGS data

  The ability to precisely characterise mutational signatures from FFPE-derived DNA has tremendous translational potential. However, sequencing of DNA derived from FFPE material is known to be riddled with artefacts. To correct for this, we introduce FFPEsig, a computational algorithm to rectify the formalin-induced artefacts in the mutational profile.

  Study EGAS00001005331

• LCM-ATACseq on human lung macrophages

  In this study we employed Laser Capture Microdissection (LCM) for the multimodal profiling of lung macrophages cell populations as a function of location within the healthy tissue. In detail, macrophage mini-bulks (~100 cells) were collected from 4 healthy human donors in 5 different locations of the airways (a total of 20 biopsies), including parenchyma (L1 – lower left lobe (LLL); L6 – 80% distance from LLL tip), trachea (L2), bronchi (L3 – 1st/2nd generation; L5 – 3rd/4th generation), and processed for ATAC-seq.

  Dataset EGAD00001008693

• LCM-RNAseq on human lung macrophages

  In the reported study, we employed Laser Capture Microdissection (LCM) for the transcriptome profiling of lung macrophages cells populations as a function of location within the healthy tissue. In detail, macrophage mini-bulks (100 cells each) were collected by LCM from 4 healthy human donors in 5 different locations of the airways (a total of 20 biopsies), including parenchyma (L1 – lower left lobe (LLL); L6 – 80% distance from LLL tip), trachea (L2), bronchi (L3 – 1st/2nd generation; L5 – 3rd/4th generation) and processed for RNA-seq.

  Dataset EGAD00001008694

• VCF file from 16 carriers of the BMPR2 p.Arg491Gln mutation in a family affected by HPAH

  VCF file 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). BAM files were processed at the CNAG (Barcelona) with their pipeline, including GATK v3.6 for genotyping and other tools such as snpEff for annotating variants, to produce this VCF file with a total of 9,643,070 variants, out of which 7,891,370 are SNVs.

  Dataset EGAD00001005758

• Whole genome sequencing libraries from the study "Histological Transformation and Progression in Follicular Lymphoma: a Clonal Evolution Study".

  Whole genome sequencing libraries from the study "Histological Transformation and Progression in Follicular Lymphoma: a Clonal Evolution Study". These are libraries from 41 patients. Specifically: 15 transformed follicular lymphoma (TFL), 6 early progressers (PFL), and 20 non-early progressers (NPFL). For TFL and PFL patients, trios consisting of diagnostic (T1), transformed/progressed (T2) and a matching normal are available (n = 63 libaries in total). For NPFL patients, a tumor-normal pair are available (n = 40 libraries).

  Dataset EGAD00001002897

• Integrating Genomic and Transcriptomic Data to Identify Breast Cancer Susceptibility Genes

  Genetic factors play an important role in the etiology of both sporadic and familial breast cancer. Since 2007, common genetic variants in ~200 loci have been identified in genome-wide association studies (GWAS) in relation to breast cancer risk. However, it is often difficult to translate GWAS findings to disease prevention and treatment since causal genes in the large majority of GWAS-identified loci are unknown. Furthermore, a large fraction of breast cancer heritability remains unexplained. Recent studies suggest that nearly 80% of disease heritability can be explained by genetic variants regulating gene expression. Herein, we propose three well-powered transcriptome-wide association studies (TWAS) to systematically investigate the association of breast cancer risk with gene expression across the transcriptome of African, Asian and European descendants. In Aim 1, we will perform RNA sequencing and high-density genotyping assays using normal breast tissue samples, and build race-specific gene expression prediction models using data from 1000 women of African, Asian and European descent. These models will be applied to the GWAS data generated from approximately 320,000 breast cancer patients and controls to impute gene expression for association analyses of predicted gene expression with risk of breast cancer overall, and by estrogen receptor and HER2 status. In Aim 2, we will select the top 50 genes identified in Aim 1 for in vitro functional assays to assess their influence on major cell functions related to cancer biology. In Aim 3, we will evaluate whether TWAS-identified genes may express differently in normal breast tissues and breast cancer tissues collected from African, Asian, and European descendants to assess whether these genes may contribute to racial differences in breast cancer risk by molecular subtypes. With strong methodology and a large sample size, we believe that this proposed study should be able to identify and characterize a large number of novel genes related to breast cancer risk. Uncovering breast cancer susceptibility genes will greatly improve the understanding of the genetic and biological basis for breast cancer and accelerate the translation of genetic findings to disease prevention and patient care.

  Study phs003535

• Oesophageal adenocarcinoma scRNAseq from LUD2015-005 study (NCT02735239, EudraCT 2015-005298-19)

  This dataset contains single-cell RNA-seq generated from the LUD2015-005 study (NCT02735239, EudraCT 2015-005298-19) and additional donors with Barrett's oesophagus using the 5' Single Cell Gene Expression assay from 10x Genomics. Samples were generated from oesophageal tumours, Barrett's oesophagus, and normal oesophagus and gastric tissues, with the aim of generating a reference atlas for cell types found in normal and disease-associated tissue states in the upper GI tract. This reference atlas was used as the basis for a deconvolution workflow to estimate the cell composition of bulk transcriptomes from these tissues, and to assess cell type-specific expression patterns of potential predictive biomarkers for immunochemotherapy regimens in this setting.

  Dataset EGAD00001009401

• A developmental cell atlas of the human thyroid gland

  Thyroid hormones are essential for health, but human thyroid development and cellular heterogeneity are poorly understood. We generated a high-resolution, spatiotemporal transcriptional atlas of human fetal thyroid, and examined its perturbations in trisomy 21 (T21), where aberrant thyroid development is associated with congenital hypothyroidism, and in papillary thyroid carcinoma (PTC). Normal tissue revealed two functional follicular cell states (fTFC1, fTFC2) with divergent PAX8 expression levels, persisting into adulthood. Additionally, the rare C-cell population was comprehensively profiled at single-cell resolution for the first time. T21 fetal thyroid was hypoplastic, with disrupted follicular morphology and altered expression of genes mediating cellular topology and extracellular matrix interactions. Finally, the transcriptional signals of both fetal follicular cell states were found to be perturbed in PTC. Overall, we defined a reference atlas for normal human fetal thyrocyte heterogeneity and provided novel insights into thyroid disorders.

  Dataset EGAD00001015783

• Influence of culture media on airway differentiation at the Air-Liquid Interface

  Single-cell dataset of human airways after in vitro regeneration at the Air-Liquid Interface. Samples from 2 donors were used for the establishment of Human Bronchial Epithelial Cell cultures (HBECs) and were analyzed during proliferation, at the onset of differentiation (ALI0) and after full differentiation (ALI28), in 4 distinct culture media. Single-cell RNAseq was performed with 10x Genomics 3’ v2 RNA-seq using hashtag antibodies for multiplexing, and sequenced on a NextSeq 500. Samples from 3 additional donors were used for the establishment of Human Nasal Epithelial Cell cultures (HNECs) and were analyzed during proliferation in three distinct culture media. Single-cell RNAseq was performed with 10x Genomics 3’ v3 RNA-seq without multiplexing, and sequenced on a NextSeq 2000.

  Dataset EGAD00001011362