The NHGRI GREGoR (Genomics Research to Elucidate the Genetics of Rare Disease) Consortium was established in June 2021 with the goal of developing novel tools and approaches to advance the discovery of the genetic basis of rare conditions. Numerous types of molecular data are generated in GREGoR and available on the AnVIL cloud platform via dbGaP application, including short- and long-read genome and exome sequencing, transcriptomics, metabolomics, methylomics, and proteomics. De-identified clinical and demographic data is obtained, with a focus on standardized ontologies.Visit the GREGoR Consortium data webpage for summary information about the GREGoR Dataset, including numbers of participants and data types, methods documentation, and Release Notes. The Consortium comprises five Research Centers (RCs - see below), a Data Coordinating Center (DCC), and various partner members and external collaborators.Baylor College of Medicine Research Center (BCM-GREGoR) The Baylor College of Medicine GREGoR program, which is part of the GREGoR consortium, enrolls individuals, families, and cohorts with suspected rare disease across a range of syndromic and non-syndromic phenotypes. Subjects are enrolled from national and international collaborating physician referrals. Subjects provide written informed consent for future re-contact. Data generated and shared include family structure, detailed phenotypes, exome or short-read genome data, and in some cases long-read genome or RNA-sequencing, and these are shared upon completion of standard quality control checks and annotation. Broad Institute (Broad) The Broad Center for Mendelian Genomics, part of the GREGoR consortium uses next-generation sequencing (exome, genome, transcriptome, and long read sequencing), computational approaches, and functional studies to discover the variants and genes that underlie Mendelian conditions with a particularly focus on neuromuscular, neurodevelopmental, and syndromic phenotypes. Samples come from collaborators and direct enrollment through the Rare Genomes Project and we are committed to rapid data sharing without an embargo period. University of California, Irvine (UCI-GREGoR) To accelerate the pace of Mendelian disease gene discovery and clinical implementation, we propose a Mendelian Genomics Research Center, part of the GREGoR Consortium, leveraging the broad pediatric and adult clinical and research expertise at Children's National Hospital and University of California, Irvine. Our goal is to develop best practices to increase the diagnostic yield of rare diseases, engage the community to reduce health disparities for complex diagnoses, while creating a dataset accessible to all. Our Center will unite world class experts combining basic and translational research with innovative approaches to phenotyping, variant identification and functional investigation of both coding and non-coding sequence changes with the goals of discovering novel Mendelian gene variations and identifying variants not detected on current sequencing pipelines, disambiguating uncertain variants into disease-causing versus benign categorizations, and sharing information by working collaboratively with the GREGoR community.GREGoR Stanford Site (GSS) The goal of the GREGoR Stanford Site (GSS) is to provide a platform for functional genomics research and validation to improve diagnosis in Mendelian disease. Participants included individuals with undiagnosed suspected Mendelian disease who had non-diagnostic exome sequencing and their immediate family members. Participants and their family members provided written, informed consent and biological samples from which DNA, RNA, plasma, fibroblasts, PBMCs and other cell types were generated and stored. Samples from research participants and their immediate family members may have undergone short and long-read genome sequencing, transcriptome sequencing, metabolomics and/or lipidomics profiling, methyl-capture-sequencing and ATAC-sequencing. De-identified clinical data extracted from participant medical records are linked to the samples. University of Washington Center for Rare Disease Research (UW-CRDR) The goals of the University of Washington Center for Rare Disease Research are to: (1) maximize novel gene discovery for Mendelian conditions by recruitment, short- and long-read whole genome sequencing, transcriptome sequencing and analysis of families with rare conditions for which the gene is either unknown or the gene is known but no pathogenic variant can be identified via clinical testing; (2) develop new strategies for gene discovery for Mendelian conditions caused by variants that are difficult to detect using conventional testing strategies, variants of unknown function effect (e.g., regulatory, structural variants) or have unusual modes of inheritance; and (3) implement high-throughput screening and targeted follow-up functional studies to prioritize and validate candidate non-coding variants. De-identified data and phenotypic information are shared via MyGene2, ClinVar, and AnVIL.
Cutaneous T cell lymphomas (CTCLs) are a clinically diverse collection of lymphomas of the skin-homing T cell. In the present study, we performed DNA and RNA sequencing on a cohort of CTCLs with representative samples from varying disease subtypes and stages. We characterized the landscape of putative driver genes, identified genetic relationships between CTCLs across disease stages, and inferred molecular subtypes in patients with stage-matched leukemic disease. Collectively, our findings clarify CTCL genetics and provide novel insights into pathways that drive diverse disease phenotypes. DNA and RNA sequencing was performed on 114 and 96 samples respectively. Tumor samples were obtained from University of Chicago (Chicago, IL), Northwestern University (Chicago, IL) and Yale University (New Haven, CT).
Circulating microRNA biomarkers for disease have been subject to extensive research. However, insufficient consideration of variability in the healthy population has led to few markers achieving the performance necessary in independent follow-up studies to be taken forward to clinical practice. To investigate the natural variation of circulating microRNA over time, we performed small RNA sequencing in a longitudinal study of 66 women with no history of cancer, and determined the distribution and dynamics (via intraclass correlation coefficients, ICCs) of the miRNA profile over 3 time points sampled across 2-5 years. We also investigate abundances in circulation, as well as the impact of normalization, age, BMI, and other sample collection factors on microRNA measurements from small RNA sequencing.
Monocyte derived macrophages were polarised into M1 or M2 using IFNg+ ILP or IL-4 respectively (n =4) . Pan T cells were cultured with or without IL-2 for 4 days (n=4 - 6). Pan T cells were co-cultured with THP1 tumour cells for 20 hours in the presence or absence of ImmTAC molecules and in the presence or absence of M2 macrophages. Sorted T cells and macrophage populations prior and post co-culture were analysed by bulk RNA sequencing (60 million reads per sample) using the Illumina NovaSeq system. Tumour biopsies were obtained from uveal melanoma patients (n = 35) pre and 16 days post treatment with tebentafusp. Biopsies, which were either snap frozen or put in RNA later, were analysed by bulk RNA sequencing (50 million reads per sample) using the Illumina NovaSeq system
This study investigates the total RNA expression profiles of fresh-frozen ovarian tumors, providing a comprehensive analysis of 112 samples from 111 women in Sweden, two samples being replicates. The dataset includes 18 benign and 94 malignant tumours, collected as part of the U-CAN initiative from Uppsala Biobank. The sequencing data offers valuable insights into ovarian tumour biology and can be used to enhance understanding of tumour classification and molecular characteristics.
To elucidate the biological pathways altered by sphingolipid modulation with N-(4-hydroxyphenyl) retinamide (4HPR) treatment in human HSPC that may contribute to the restraint in proliferation while promoting persistence of HSC self-renewal as well as determine the mechanism of synergy in enhancement of HSC self-renewal with CB CD34+ agonists UM171 and StemRegenin 1 (SR1), we performed RNA-sequencing (RNA-Seq) of 3 pools of lin-CB cells following 2 or 4 days with DMSO, 4HPR, UM171+SR1 or 3-Factor (4HPR+UM171+SR1). We identified modulation of sphingolipid metabolism regulates self-renewal through activating coordinated stress pathways that coalesce on endoplasmic reticulum stress and autophagy programs.
Exome Sequencing and RNA Sequencing Data for PDX Samples
Log2 gene expression count data from RNA sequencing.
epigenome profiling in tumor tissues and paired normal tissues of LUAD patients and transcriptome profiling in tumor tissues of LUAD patients.
