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• MNM - 16S rDNA amplicon dataset of 20 dense timeseries of fecal samples from Belgian women

  Fastq files for the 16S rDNA amplicon library of 714 fecal samples of 20 time series (as described in Vandeputte et al. 2021, Nature Communications)

  Dataset EGAD00001008275

• Single-cell RNA-seq of immune cells from Melanoma tumors (Li et al, 2018)

  Single-cell RNA-seq profiling of immune cells sorted from human Melanoma tumors (and several matching PBMC samples). Contains de-multiplexed FASTQ files per plate (MARS-seq amplification batch, total 204 samples) and also de-multiplexed FASTQ files of single-cell TCRb-seq.

  Dataset EGAD00001004497

• 340 human whole genome sequences from Angola and Mozambique

  CRAM files of 340 human genomes from Angola and Mozambique. Paired-end reads were generated in an Illumina-X Ten and were mapped against the human reference genome build hg19/GRCh37. More details about the sequencing and the samples in Tallman et al. 2023. Nature Communications.

  Dataset EGAD00001011992

• RNA-seq data from DMD patients and healthy controls

  This dataset comprises RNA-seq expression profiles from 57 subjects, of which 39 are DMD patients and 18 healthy controls. The data are described in the following article: Signorelli, Ebrahimpoor et al. (in review). Peripheral blood transcriptome profiling enables monitoring disease progression in dystrophic mice and patients.

  Dataset EGAD00001006826

• Fixed single-cell transcriptomic characterization of human radial glial diversity

  The human neocortex is created from diverse intermixed progenitors in the prenatal germinal zones. These progenitors have been difficult to characterize since progenitors - particularly radial glia (RG) - are rare, and are defined by a combination of intracellular markers, position and morphology. To circumvent these problems we developed a method called FRISCR (Fixed and Recovered Intact Single Cell RNA) for transcriptome profiling of individual fixed, stained and sorted cells. We developed and validated FRISCR on human embryonic stem cells. We then profiled primary human RG (96 - 132 days post conception) that constitute only 1% of the mid-gestation cortex. These RG could be classified into ventricular zone-enriched RG (vRG) that express ANXA1 and CRYAB, and outer subventricular zone-localized RG (oRG) that express HOPX. Our study identifies the first markers and molecular profiles of vRG and oRG cells, and provides an essential step for understanding molecular networks driving the lineage of human neocortical progenitors. Reprinted from Thomsen et. al. Nature Methods (2015), with permission from Nature Publishing. Human embryonic stem cell data may be obtained through NCBI's GEO database, using accession number GSE71858. Raw data from one human sample that was not consented to be released to dbGaP may be obtained directly from the authors of Thomsen et. al., 2015.

  Study phs001016

• Organoid BulkRNAseq

  Here, we aim to understand early determinants of brain organoid quality and generated a set of brain organoids from 12 different hPSC lines using an adaptation of the unguided Lancaster protocol (Lancaster & Knoblich, 2014). All cell lines were obtained from healthy donors. 12 donor hPSC lines were differentiated into brain organoids and a set of 72 individual organoids (6 per line) were randomly selected morphologically diverse organoids and subjected to bulk RNA sequencing for gene expression analysis. RNA was extracted using the RNeasy kit (Qiagen, Germany) according to the manufacturer’s instructions. A total of 1000 ng per sample was sent for RNA sequencing to Azenta Life Sciences (Genewiz Leipzig, Germany) for sequencing. Library preparation was performed using the NEBNext Ultra II RNA Library Prep Kit for Illumina following manufacturer’s instructions (NEB, Ipswich, MA, USA). mRNAs were first enriched with Oligo(dT) beads. The samples were sequenced using a 2x150 Pair-End (PE) configuration v1.5 at a depth of >20 million reads in each sample. Raw sequence data (.bcl files) generated from Illumina NovaSeq6000 was converted into fastq files and de-multiplexed using Illumina bcl2fastq program version 2.20. The raw sequence reads were aligned to the human reference genome GRCh38 using the STAR aligner (Dobin et al., 2013). Gene expression levels were quantified using the FeatureCounts tool (Liao et al., 2014).

  Study EGAS50000000659

• Genome-Wide Association Study of Hypertriglyceridemia in Mexicans

  Coronary artery disease (CAD) is the number one cause of death and mortality world-wide. High levels of serum triglycerides (TGs) and low levels of serum high-density lipoprotein cholesterol (HDL-C) are major risk factors for CAD. Previous epidemiological studies have shown that these two lipid disturbances are highly common dyslipidemias in Mexicans. However, the genetic factors underlying high serum TGs and low HDL-C are underinvestigated and poorly identified in Mexicans. As the Mexican-American and the genetically related Latin-American populations represent the fastest growing minority in the United States, elucidation of the unknown genetic factors influencing the increased susceptibility of Mexicans to these common dyslipidemias is of great relevance to these U.S. minorities and the American healthcare system. This study is a research collaboration between investigators at the University of California, Los Angeles (UCLA) and Instituto Nacional de Ciencias Médicas y Nutrición (INCMN), Mexico City, to perform a two-stage genome-wide association study (GWAS) for hypertriglyceridemia and low high-density lipoprotein cholesterol (HDL-C) in Mexicans (Weissglas-Volkov et al. 2013, PMID: 23505323). This study was funded by an RO1 grant from NIH/NHLBI (PI Paivi Pajukanta; PI of the subaward Teresa Tusie-Luna). In stage 1 of the GWAS, we tested all GWAS SNPs from the Illumina Infinium Human610-Quad platform that passed quality control for association in ~2,200 hypertriglyceridemia cases and controls. In stage 2, we genotyped the ~1,200 positive signals of stage 1 in additional ~2,200 hypertriglyceridemia cases and controls, and performed a combined analysis of the two stages to identify genome-wide significant variants. The subjects were recruited at the INCMN. The DNA isolation and clinical laboratory measurements of the case-control study samples were performed at INCMN using standardized procedures. Genotyping and statistical analyses of the data were performed at UCLA. A summary of this GWAS can be found in Weissglas-Volkov et al. 2013 Journal of Medical Genetics, PMID: 23505323. Briefly, using the two-stage GWAS design, we identified a novel Mexican-specific genome-wide significant locus for serum TG levels close to the Niemann-Pick type C1 protein (NPC1) gene (Weissglas-Volkov et al. 2013, PMID: 23505323). Of the European lipid GWAS loci, three TG loci (APOA5, GCKR, and LPL) and four HDL-C loci (ABCA1, CETP, LIPC and LOC55908) resulted in genome-wide significant signals in Mexicans. Furthermore, our cross-ethnic mapping narrowed three European TG GWAS loci, APOA5, MLXIPL, and CILP2 that exhibited long range LD and a large number of candidate SNPs in the European GWAS scan. In the apolipoprotein A1C3A4A5 gene cluster region, the cross-ethnic fine mapping and LD comparisons reduced the number of candidate variants to one SNP, rs964184. We also found that although 52% of the associations from European lipid GWAS meta-analysis could be generalized to Mexicans, in 82% of the European GWAS loci, a different variant other than the European lead SNP provided the statistically strongest evidence of association in the Mexican scan (Weissglas-Volkov et al. 2013, PMID: 23505323). Taken together, our Mexican GWAS for lipids identified a novel Mexican-specific locus for high serum TGs; restricted three European GWAS loci; and investigated which European lipid GWAS variants extend to the Mexican population (Weissglas-Volkov et al. 2013, PMID: 23505323). This NHLBI sponsored RO1 project aimed to identify genetic variants contributing to serum lipid levels in Mexicans. In addition to de-identified genome wide genotypic data, a selected list of de-identified phenotypic data related to hypertriglyceridemia and related metabolic traits are also available in dbGaP.

  Study phs000618

• Biology and Molecular Analysis of Human Hematopoiesis Genetics

  In this study we have performed exome sequencing using the hybrid capture method that has previously been described (Gnirke et al., Nature Biotechnology, 2009) on genomic DNA samples from patients with the congenital bone marrow failure syndrome that affects the erythroid lineage, specifically, Diamond-Blackfan anemia. This disease is characterized by a hypoplastic anemia and approximately 50% of cases are attributable to mutations in ribosomal protein gene subunits. The other 50% of cases do not have a known genetic etiology and the purpose of this study is to attempt to delineate such causes.

  Study phs000474

• NHLBI TOPMed: Diabetes Heart Study (DHS) African American Coronary Artery Calcification (AA CAC)

  The Diabetes Heart Study (DHS) is a family-based study enriched for type 2 diabetes (T2D). The cohort included 1443 European American and African American participants from 564 families with multiple cases of type 2 diabetes (Bowden et al., 2010. Review of Diabetic Studies 7:188-201. PMID: 21409311). The cohort was recruited between 1998 and 2006. Participants were extensively phenotyped for measures of subclinical CVD and other known CVD risk factors. Primary outcomes were quantified burden of vascular calcified plaque in the coronary artery, carotid artery, and abdominal aorta all determined from non-contrast computed tomography scans.

  Study phs001412

• Comparison of transcriptomics profile of stem cell-derived beta cells from HUES8 and RC9

  Stem cell-derived islet cells have a potential to be used to restore endogenous insulin production in people with diabetes. The goal of this experiment is to compare the transcriptomics profile of stem-cell derived beta cells from two different cell lines: HUES8 (non-clinical grade) and RC9 (clinical grade) in terms of beta cell identity and maturity. Stem cell-derived islets were produced using differentiation protocol detailed in Rajaei et al. 2025 (manuscript approved in Science Translational Medicine, pending pubmed ID). Single cell transcriptomics data were generated using 10x Genomics 3' Single Cell Gene Expression kit.

  Study EGAS50000000905