Primary bronchial epithelial cells derived from healthy donors and asthma patients were differentiated in Air-Liquid-Interface condition and infected with the respiratory syncytial virus. Single-cell RNA sequencing analysis of these cultures was used to study the transcriptomic response of the cells to RSV.
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.
We studied a unique autopsy case of metastatic urothelial carcinoma with both sensitivity and resistance to anti-PD-1 therapy. We performed multiregional analyses of 58 paired whole exome sequencing and RNA sequencing samples of 8 different bulk tumor masses, 8 matched whole genome sequencing samples to identify structural abnormalities of each mass. Furthermore, we performed 7 whole exome sequencing from metastatic urothelial carcinoma patients who received anti-PD-1 therapy.
This DAC handles access to data from the TenK10K project, which is comprised of matched whole-genome sequencing (WGS), single cell RNA-sequencing (scRNA-seq), single nuclei ATAC-sequencing, and single cell Multiome datasets.
To identify molecular subtypes and carcinogenesis in clear cell ovarian carcinomas by whole-exome sequencing, RNA-sequencing, and methylation array, and to characterize high-grade serous carcinomas by NGS-based, integrative genomic analyses, with focus on homologous recombination deficiency, molecular subtypes and prognositic factors.
In order to comprehensively investigate the genetic relationship between PTC tumors and benign nodules, we totally collected 127 fresh-frozen biopsies samples from 28 patients with concurrent thyroid benign nodule and PTC (n=20) or simple benign nodule (n=8). We carried out whole-exome sequencing on all the 127 biopsies samples and RNA-sequencing in total of 40 samples.
The parent longitudinal study evaluated the symptom experience of oncology outpatients receiving chemotherapy. Patients completed questionnaires in their homes a total of six times (assessments 1 through 6). The questionnaires were timed to evaluate symptoms associated with the receipt of two cycles of chemotherapy that were administered approximately a month apart. Assessments 1 and 4 evaluated symptoms prior to the receipt of chemotherapy. Assessments 2 and 5 evaluated symptoms in the week following the administration of chemotherapy. Assessments 3 and 6 evaluated symptoms two weeks following the administration of chemotherapy. For this analysis, morning and evening fatigue data from the enrollment assessment (i.e., prior to the second or third cycle of chemotherapy) and the assessment that was done approximately 1 week after administration of chemotherapy were evaluated. Patients completed the Lee Fatigue Scale to obtain information on morning and evening fatigue severity. For the morning fatigue assessment, patients were asked to describe how they “felt over the past week when they woke up in the morning”. For the evening fatigue assessment, they were asked to describe how they felt over the past week “before they went to bed at night”. Medical records were reviewed for disease and treatment information. Epigenome assays (microarray) were completed for 1170 patients. Whole transcriptome sequencing (bulk RNA-Seq) was completed for 651 patients.
Tissue-resident memory T (TRM) cells are a population of memory T cells that stably occupy tissues and play a key role in immunosurveillance, having been linked to favorable survival outcomes in various solid tumors. While TRM cells have been identified in lymph nodes, their phenotype and prognostic significance in B-cell non-Hodgkin lymphoma (B-NHL), including diffuse large B-cell lymphoma (DLBCL), remains poorly characterized. The frequency of CD103 expressing T cells in patient samples with DLCBL was quantified by immunofluorescence (IF) staining of tissue biopsies (n=306) and flow cytometry (n=252) of cell disaggregates, and linked with clinical outcome. The phenotype of TRM cells was characterized by spectral flow cytometry (n=10 DLBCL and 2 reactive lymph node (rLN) samples) and single-cell RNA sequencing (scRNAseq) (n=12 aggressive B cell lymphomas and 4 rLN samples). An additional 51 samples from an external dataset were included to verify the single cell transcriptome findings. The flow cytometry and scRNAseq findings in DLBCL were extrapolated to additional B-NHL entities. Through analysis of these datasets we were able to characterize CD103+ TRM-like cells in DLBCL and other B-NHL entities and identified them to represent a prognostically favorable population with an activated/cytotoxic T cell phenotype.
DAC to regulate access to RNA sequencing data of NERD patients with dupilumab treatment before and after aspirin provocation.
