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• NextGen Consortium: The iPSCORE (iPSC Collection for Omic Research) Resource for Studying the Impact of Genetic Variation on Molecular Phenotypes

  The iPSC Collection for Omic Research (iPSCORE) Resource was created as part of the Next-Gen Consortium funded by NHLBI. The overarching purpose of the resource is to provide a large collection of human induced pluripotent stem cells (iPSCs) for use in studying the impact of genetic variation on molecular and physiological phenotypes. The resource has been used in a number of studies in the Dr. Kelly A. Frazer's Lab examining both the characteristics of human iPSCs and a variety of iPSC-derived cell types including cardiovascular progenitor cells (iPSC-CVPCs), pancreatic precursor cells (iPSC-PPCs), and retina pigment epithelium cells (iPSC-RPEs). We have shown that the iPSCs, CVPCs, and PPCs are suitable surrogate models to identify genetic factors active in early developmental processes because they exhibit fetal-like molecular properties. A total of 273 individuals have participated in the study, of which 222 have had iPSCs generated from fibroblasts. Of the 273 individuals, 181 are part of 55 families that include 24 monozygotic twin pairs and 5 dizygotic twin pairs, allowing for the incorporation of familial relationships into genetic analyses. Germline DNA has been sequenced from blood or fibroblast samples for all 273 individuals (available through dbGaP phs001325) and other genomic data (RNA-seq, DNA methylation, genotype arrays, ATAC-seq, H3K27ac ChIP-seq, HiC-seq) have been generated from the 222 iPSCs as well as derived cell types (available through dbGaP phs000924). QTL analyses were conducted for multiple omics data types and summary statistics are available through dbGaP phs0001325. Important note: Of the 273 individuals, 268 are consented for general research use and 5 are consented for cardiac research only. For detailed information about iPSCORE Collection including samples, methods used to generate the data, and how to access the datasets visit the Frazer lab website.The 222 well characterized iPSC lines that constitute the iPSCORE resource are available, please contact Dr. Kelly A. Frazer (kafrazer@health.ucsd.edu) if you are interested in obtaining the collection.

  Study phs000924

• NextGen Consortium: The iPSCORE (iPSC Collection for Omic Research) Resource for Studying the Impact of Genetic Variation on Molecular and Physiological Phenotypes - Whole Genome Sequence

  The iPSC Collection for Omic Research (iPSCORE) Resource was created as part of the Next-Gen Consortium funded by NHLBI. The overarching purpose of the resource is to provide a large collection of human induced pluripotent stem cells (iPSCs) for use in studying the impact of genetic variation on molecular and physiological phenotypes. The resource has been used in a number of studies in the Dr. Kelly A. Frazer's Lab examining both the characteristics of human iPSCs and a variety of iPSC-derived cell types including cardiovascular progenitor cells (iPSC-CVPCs), pancreatic precursor cells (iPSC-PPCs), and retina pigment epithelium cells (iPSC-RPEs). We have shown that the iPSCs, CVPCs, and PPCs are suitable surrogate models to identify genetic factors active in early developmental processes because they exhibit fetal-like molecular properties.A total of 273 individuals have participated in the study, of which 222 have had iPSCs generated from fibroblasts. Of the 273 individuals, 181 are part of 55 families that include 24 monozygotic twin pairs and 5 dizygotic twin pairs, allowing for the incorporation of familial relationships into genetic analyses.Germline DNA has been sequenced from blood or fibroblast samples for all 273 individuals (available through dbGaP phs001325) and other genomic data (RNA-seq, DNA methylation, genotype arrays, ATAC-seq, H3K27ac ChIP-seq, HiC-seq) have been generated from the 222 iPSCs as well as derived cell types (available through dbGaP phs000924).QTL analyses were conducted for multiple omics data types and summary statistics are available through dbGaP phs0001325.Important note: Of the 273 individuals, 268 are consented for general research use and 5 are consented for cardiac research only.For detailed information about iPSCORE Collection including samples, methods used to generate the data, and how to access the datasets visit the Frazer lab website.The 222 well characterized iPSC lines that constitute the iPSCORE resource are available, please contact Dr. Kelly A. Frazer (kafrazer@health.ucsd.edu) if you are interested in obtaining the collection.

  Study phs001325

• Hyperdiploid Acute Lymphoblastic Leukemia RNA-Seq

  Few genetic drivers of children with hyperdiploid precursor B-cell acute lymphoblastic leukemia (ALL) have been identified to date. In an effort to detect novel genomic rearrangements that could be promoting leukemogenesis in this subset of patients, we sequenced ribosomal RNA-depleted transcriptomes isolated from 5 hyperdiploid acute lymphoblastic leukemia samples. In addition to looking for novel genomic rearrangements, we also sought to identify transcripts that could be created as a result of a novel posttranscriptional process. Surprisingly, we identified transcripts created as the result of exon circularization. The results of our studies are present in the paper "Circular RNAs Are the Predominant Transcript Isoform from Hundreds of Human Genes in Diverse Cell Types" published in PLoS ONE (PMID: 22319583).

  Study phs000522

• single-cell RNA-seq Case-Control study of children progressing to Type1 diabetes

  Single-cell RNA sequencing was carried out on four selected PBMC samples of Finnish children at risk of developing Type 1 diabetes and their gender age and HLA matched control children using 10X genomic platform. All four Case children were positive for multiple islet specific autoantibodies and two of them also progressed to clinical disease during the follow up whereas the control children remain negative for all autoantibodies. Age at seroconversion for Case 2, 3, 5, and 9 children is 12, 18, 24, and 18 months, respectively. Age at sampling, in months, for the pairs was as follows (Case/Control): pair 2:24/24; pair 3: 12/18; pair 5: 12/12; pair 9:24/18.

  Study EGAS00001004070

• Single-nuclei histone modification profiling of the adult human central nervous system unveils epigenetic memory of developmental programs

  We profile the adult human CNS from distinct regions, sex and ages, for chromatin accessibility at the single-nuclei level. Tissue was collected from 20 different donors (10 male, 10 female) within the ages of 34 to 74 years old. Additionally we performed Single-cell nanoCUT&Tag H3K27ac and H3K27me3 profiling for 4 of the donors and multiome single cell assay (RNA-seq+ATAC-seq) for 2 of the donors. Each donor donated fresh frozen white matter from the following three tissue regions: primary motor cortex (Brodmann area 4, BA4), arbor vitae cerebelli (CB) and fasciculi cuneatus and gracilis from and cervical spinal cord (CSC). Tissue was processed semi-randomly, ensuring that each batch of experiments had a representation of both sexes and all three tissue regions. Completed libraries were again randomly multiplexed during sequencing to minimize batch effects. We also performed micro-C,2 replicates, of iPS human derived cell cultures of human oligodendrocyte precursor cells (hOPC).

  Dataset EGAD50000000410

• Whole genome bisufite sequencing of smoking and non-smoking mother-child pairsBisufite sequencing, RNA-seq and ChIP-Seq data of whole blood samples from smoking and non-smoking mothers and their children at gestation/birth and follow-up years.

  Whole-blood samples of 16 mother-child pairs with differing maternal smoking behaviour were bisulfite treated and sequenced with deep coverage to identify smoking-associated differentially methylated regions.RNA-sequencing and ChIP-sequencing of 4 chromatin marks complete the data set and allow for integrative analyses, functional region annotation and to study the impact of epigenetic changes on gene expression.Longitudinal data spanning several years provides the means to investigate the stability of observed differences of all data types.

  Study EGAS00001000455

• Upper cortical layer-driven network impairment in schizophrenia - 10x genomics v3 snRNA-seq and Visium spatial transcriptomics datasets

  This dataset contains 10x Genomics v3 3’ single nuclei RNA sequencing (24 human schizophrenia and control samples) and 10x Genomics Visium spatial transcriptomics (14 human schizophrenia and control samples) datasets. Files are in .bam format, output of the cellranger v3.1.0 (https://support.10xgenomics.com/single-cell-gene-expression/software/pipelines/3.1/using/count) for snRNA-seq and spaceranger v1.1.0 (https://support.10xgenomics.com/spatial-gene-expression/software/pipelines/1.1/using/count) for Visium samples. Reads were mapped against Release 97 of human genome from Ensembl (http://ftp.ensembl.org/pub/release-97/fasta/homo_sapiens/dna/Homo_sapiens.GRCh38.dna.primary_assembly.fa.gz http://ftp.ensembl.org/pub/release-97/gtf/homo_sapiens/Homo_sapiens.GRCh38.97.gtf.gz). More details on sample processing are available in the biorXiv pre-print (https://doi.org/10.1101/2020.11.17.386458) and upcoming publication in Science Advances. BAM files can be converted to fastq files using bamtofastq tool (https://support.10xgenomics.com/docs/bamtofastq) with downstream remapping using tools and genomes of choice.

  Dataset EGAD00001009173

• BLUEPRINT: Epigenetic programming during monocyte to macrophage differentiation and trained innate immunity

  Monocyte differentiation into macrophages represents a cornerstone process for host defense. Concomitantly, immunological imprinting of either tolerance or trained immunity determines the functional fate of macrophages and susceptibility to secondary infections. Transcriptomes (RNA-Seq) and epigenomes (ChIP-Seq H3K4me1,H3K4me3,H3K27ac) in four primary cell types: monocytes, in vitro differentiated naive, tolerized and trained macrophages were characterized. Inflammatory and metabolic pathways were modulated in macrophages, including decreased inflammasome activation, and pathways functionally implicated in trained immunity were identified. Strikingly, B-glucan training elicits an exclusive epigenetic signature, revealing a complex network of enhancers and promoters. Analysis of transcription factor motifs in DNase I hypersensitive sites at cell-type specific epigenetic loci unveiled differentiation and treatment specific repertoires. Altogether, this study provides a resource to understand the epigenetic changes that underlie innate immunity in humans.

  Dataset EGAD00001001011

• Merkel Cell Carcinoma Tissue and Data Repository

  Merkel cell carcinoma (MCC) is a rare, aggressive neuroendocrine skin cancer with increasing incidence in the United States. In this study we performed the first whole genome sequencing of three Merkel cell carcinomas with their matched normal tissues for somatic variant calling. From these data we describe the likely mechanism of Merkel cell polyomavirus integration and focal host genomic amplifications in two tumors and the dominance of UV-mediated mutagenesis in a virus-negative tumor. We also performed poly-A RNA sequencing on a total of six Merkel cell carcinomas to address expression differences between virus-positive and virus-negative MCC.

  Study phs002189

• The aim of this study was to identify underlying hub genes and dysregulated pathways associated with the development of HCC using bioinformatics analysis.

  In the present study, we identified differentially expressed protein-coding genes from RNA transcriptional profiling performed on 11 paired cancer tissues and adjacent non-cancerous tissues. Then, we conducted GO, KEGG, PPI network and centralities analyses to study and identify changes in pathways and hub genes. The aim of this study was to improve understanding of HCC carcinogenesis by providing information concerning the genetic changes that occur during disease progression and to uncover the expression of biomarkers with potential use for clinical diagnosis, treatment, and monitoring of disease progression.

  Study EGAS00001002526