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• M116 Microbiome data

  M116 stool was collected from 3 different days (3 biological replicates) and kept at -20ºC until DNA extraction (Biobanc IDIBGI and Goodgut®). Total genomic DNA was extracted from 150–200 mg of each stool sample after homogenisation using the DNeasy Powersoil Pro kit (Qiagen®) according to manufacturer’s instructions. Quality and quantity of DNA were evaluated using Qubit® BR kit on a Qubit®2.0 fluorimeter (ThermoFisher Scientific®) and on a Nanodrop ND-2000 UV-Vis spectrophotometer (ThermoFisher Scientific®). The v3-v4 region of the bacterial 16S rRNA gene was amplified and sequenced (paired-end 250-bp) following standard practices at external facilities (Novogene®) using previously described primers 515F. Files types included in this dataset are raw Fastq files.

  Dataset EGAD50000001288

• Gene expression profiles of single disseminated breast cancer cells

  A set of 56 EpCAM-positive cells derived from bone marrow aspirates of breast cancer patients or patients without a cancererous disease (30 cells from 21 M0-stage and 11 cells from five M1-stage breast cancer patients, 15 cells from seven non-cancer patients serving as controls). EpCAM-positive cells from breast cancer patients were considered disseminated tumor cells as they harbored copy number alterations and showed high expression of the epithelial marker EpCAM and the mammary luminal progenitor marker KIT in comparison to EpCAM-positive bone marrow cells from non-cancer patients. Paired-end RNA-Sequencing of the samples was performed on Illumina NovaSeq6000, raw data are provided in the Fastq format.

  Dataset EGAD00001006359

• Pharmacogenomic profiling reveals molecular features of chemotherapy resistance in IDH wild type primary glioblastoma

  We stratified 69 primary IDH-wt GBM patients into TMZ-resistant (n = 29) and sensitive (n = 40) groups, using TMZ screening of the corresponding patient-derived glioma stem-like cells (GSCs). Genomic and transcriptomic features were then examined to identify TMZ-associated molecular alterations. Subsequently, we developed a machine learning (ML) model to predict TMZ response from combined signatures. Moreover, TMZ response in multisector samples (52 tumor sectors from 18 cases) was evaluated to validate findings and investigate the impact of intra-tumoral heterogeneity on TMZ efficacy.

  Dataset EGAD00001010156

• LLD PhIPSeq

  LLD PhIP-Seq reads. Oligopeptides were designed at Eran's Segal group at Weizmann Institute of Science. Dataset include 1,783 plasma samples. In 340 participants, a second time point was taken after a 4-year follow-up.

  Dataset EGAD00001010104

• Genomic and immune signatures predict clinical outcome in newly diagnosed multiple myeloma treated with immunotherapy regimens

  In this study we performed whole genome sequencing on matched tumor-normal CD138+ bone marrow mononuclear cells from 60 patients with newly diagnosed multiple myeloma treated with daratumumab, carfilzomib, lenalidomide, and dexamethasone (NCT03290950-MANHATTAN trial). In addition, we performed 5’-single-cell RNA-sequencing (10X Genomics) coupled with V(D)J sequencing and capture of the surface protein markers (TotalSeq-C, Biolegend) of the CD138- bone marrow mononuclear cells to interrogate the composition of the immune microenvironment at baseline and after eight cycles of induction therapy in 22 patients with newly diagnosed multiple myeloma. Samples were multiplexed using hashtag oligo.

  Dataset EGAD00001011132

• Evolution of Chromatin Architecture and Transcriptional Regulation in Mammals

  Changes in gene expression are a critical force driving the evolution of form and function. As a result, the mechanisms by which gene expression evolves have become a subject of intense interest. A number of investigators have measured evolutionary changes in gene expression at the chromatin, mRNA, and protein levels, leading to new insights about how species evolve. However, studies of different stages in gene expression have not always been in agreement. For example, the extremely rapid rates of evolutionary changes that have been widely observed at enhancers appear to conflict with the slower rates observed in mRNA abundance. We recently completed a major comparative study in primates showing that this disparity between enhancer and mRNA evolution, in part, reflects extensive compensation at enhancers that jointly determine transcription at target genes. Likewise, related findings have demonstrated that post-transcriptional changes buffer protein abundance to relatively more common differences in mRNA expression. Together, these recent findings demonstrate that evolutionary changes affecting multiple stages of transcriptional regulation often have interdependent effects on gene expression. Here we propose to determine how stages early during transcriptional regulation work in concert, either to conserve gene expression through compensatory changes across stages, or, in rare cases, to change mRNA in ways that alter organism phenotypes. Our central hypothesis is that interactions between stages are common, especially at long evolutionary time-scales. To test this hypothesis we propose an ambitious plan to collect rich genomic data profiling distinct stages of gene expression in two cell types and three tissues from nine mammalian species. We have focused our study on several early rate-limiting steps in mRNA production, using molecular assays selected to provide orthogonal sources of information about chromatin architecture (Hi-C/Hi-ChIP), accessibility (ATAC-seq), transcription (PRO-seq), and mRNA levels (RNA-seq). This project will produce the largest resource of genomic data uniformly collected across mammals to date. We will integrate genomic data using a suite of new computational tools, which together will provide a new understanding of how distinct regulatory stages work in concert during regulatory evolution.

  Study phs002146

• Mitochondrial DNA mosaicism in human somatic cells

  Genomic alterations accumulate in the somatic cells throughout an individual’s lifetime. Recent sequencing studies have documented widespread mutations in the nuclear genome and the frequent clonal competition of normal cells carrying mutations. However, the landscape of mitochondrial DNA (mtDNA) heteroplasmy in normal human tissues is poorly understood. This study investigated the whole genome sequences (WGSs) of 2,096 clones established from non-neoplastic healthy single cells obtained from 31 donors. In addition, we analyzed 31 WGSs of neoplastic cells, including 12 clones established from adenomatous polyps from one individual with MUTYH-associated polyposis and 19 matched colorectal carcinomas from individuals who donated normal colorectal clones.

  Dataset EGAD50000000373

• Targeted sequencing of healthy individuals, aged individuals and AML patients

  Targeted sequencing using BD Rhapsody with 462 mRNA and 97 antibodies of healthy young and aged adult as well as AML bone marrow mononuclear cells from iliac crest aspirations. Please note raw and integrated gene expression data, cell type annotation, metadata and dimensionality reduction are available as Seurat v3 objects through figshare. Access link is https://figshare.com/s/0fda29b169c719223ee3.

  Dataset EGAD00001008188

• RNA-Seq data of hepatoma (Huh7 derived) and Ph5CH cells and primary hepatocytes

  The innate immune response of cells of hepatic origin (Huh7, Huh7.5, PH5CH and primary human hepatocytes (PHH), 66 samples) was analyzed by transcriptome analysis (RNAseq) upon supernatant delivery or transfection of synthetic dsRNA (poly(I:C)). Expression of TLR3 and RIG-I was reconstituted by lentiviral transduction in Huh7 and Huh7.5 cells. The sequencing is single RNA-Seq on an Illumina HiSeq 4000 with the Illumina TruSeq stranded mRNA kit.

  Dataset EGAD00001007083

• Genetic architecture of autism spectrum disorder in India

  The dataset consists of whole exome sequencing data (fastq format) of 100 non-syndromic autism spectrum disorder patients from India. Whole exome sequencing data is generated using Agilent SureSelect v6 capture kit and Illumina HiSeq sequencing platform. Paired end fastq files are available.

  Dataset EGAD00001008621