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• Type 1 Diabetes Genetics Consortium (T1DGC): Copy Number Variant (CNV) Study

  Type 1 Diabetes Genetics Consortium (T1DGC) was formed to address issues of limited sample size and consistency of phenotyping that had limited genetic investigations on risk of type 1 diabetes (T1D). The T1DGC first collected affected sib pair (ASP) families from four geographic networks (Asia-Pacific, Europe, North America, United Kingdom). In addition, T1D parent-offspring trios as well as cases and controls were ascertained from existing and de novo collections. For T1D, the genome-wide association study (GWAS) design has been successful at detecting ~50 loci that contribute disease risk. However, in the case of T1D as well as almost all other traits, the sum of these loci does not fully explain the heritability estimated from familial studies. One possibility for the undiscovered contribution to familial aggregation is that additional variants exist but have not yet been found because they have not effectively been targeted by the GWAS design. In this study, we focus on a specific class of large deletions/duplications -- copy number variants (CNVs) - and particularly to the subset of these loci that mutate rapidly, are not tagged by SNPs, and are highly polymorphic. The T1DGC assembled 2,601 T1D ASP families and 69 Parent-T1D offspring trios, that were eligible for this study. All samples included in this series have reported or self-declared European ancestry. All DNA samples were collected after approval from relevant institutional research ethics committees. Importantly, the source of DNA for CNV evaluation was uniform within a family (either all from PBMC or from EBV-transformed cell lines). We use a family based design that was optimized to capture these previously untested variants. We then perform a genome-wide scan to assess their contribution to T1D.

  Study phs000910

• Pathogenic Neurofibromatosis type 1 (NF1) RNA splicing resolved by targeted RNAseq

  Neurofibromatosis type 1 (NF1) is caused by loss-of-function variants in the NF1 gene. Approximately 10% of these variants affect RNA splicing and are either missed by conventional DNA diagnostics or are misinterpreted by in silico splicing predictions. Therefore, a targeted RNAseq-based approach was designed to detect pathogenic RNA splicing and associated pathogenic DNA variants. an in-house developed tool (QURNAS) was used to calculate the enrichment score (ERS) for each splicing event. RNA enrichment of NF1 and SPRED1 was done using SPET (NUGEN - NF1 only) and using SureSelect (Agilent - NF1 and SPRED1).

  Study EGAS00001005530

• Genomics and Epigenomics of the Elderly Response to Pneumococcal Vaccines

  Pneumococcal Vaccine Study: This is a study designed to develop a detailed transcriptional and cellular profile of the immune response to pneumococcal vaccination with conjugated and non-conjugated polysaccharide vaccines in the senescent immune system of older adults. In this study, 39 healthy adults ages 60 and older that have never received pneumococcal vaccination, have been randomized to receive Prevnar 13 (Pfizer), a conjugated 13-valent vaccine or Pneumovax 23 (Merck), a non-conjugated 23-valent vaccine. Four (4) study visits occurred over 70 days at Day -7 (baseline), day 1, day 10 and day 60 (± 5d) post vaccination.Bulk RNA-sequencing data are available on the 4 time points for 31 of the participants and 1 replicate. ATAC-Doublet Detector Study: We generated single nucleus ATAC-seq (snATAC-seq) data from PBMCs of 2 baseline blood samples from the pneumococcal study. Generated data was then used to benchmark a novel computational method for detecting multiplets in snATAC-seq data, namely, AMULET (https://github.com/UcarLab/AMULET). Multiplets confound downstream analyses by introducing combined epigenomic profiles from 2 or more cells/nuclei. AMULET detects multiplets by using unique snATAC-seq data features that allow it to reliably use read counts to detect multiplets for their removal from data analyses.

  Study phs002361

• Single-cell level characterization of B cell depletion and repopulation following rituximab in systemic lupus erythematosus

  Rituximab, a CD20+ B cell depletion therapy, is frequently used in the treatment of systemic lupus erythematosus (SLE). However, variability in patient response highlights the need for a deeper understanding of the underlying immune cell dynamics of B cell depletion and repopulation. In this study, we conducted longitudinal single-cell profiling of nine SLE patients treated with rituximab from pretreatment to up to 15 months post-treatment. These were compared to eight healthy controls. We profiled PBMCs via 10X Genomics single-cell RNA, surface protein (CITE-seq), B cell receptor (BCR), and T cell receptor (TCR) sequencing and sequenced bulk BCR repertoires in parallel. For single cell sequencing, 10 pools were created with an equal number of cells from 4 samples each. Samples collected at different timepoints from the same patient were distributed across different pools to allow demultiplexing of individuals using genotypes captured from the scRNA-seq data. Libraries were pooled using a ratio of GEX:CITE:TCR:BCR=9:2:1:1 and were sequenced across two lanes of the NovaSeq 6000. For bulk BCR sequencing, individual samples were demultiplexed using primer barcodes and paired-end BCR amplicon reads were merged prior to submission; data are provided as unmapped single-end reads.

  Study EGAS00001006798

• TenK10K Phase 1: scRNA-seq fastq format sequencing data

  Single cell RNA-sequencing data for PBMCs from the Tenk10k Phase 1 cohort (1925 individuals post-QC). Libraries were prepared using the 10x Genomics 3’ Chromium Next GEM Single Cell HT V3.1 kit and sequenced on the NovaSeq 6000 platform. This analysis consists of 4,768 fastq format files in 1,192 runs, and an analysis which provides the relationship of 298 library pool samples to 1,925 individual samples.

  Dataset EGAD50000002517

• RNAseq of pre- and post-5AZA-treated head and neck cancer patients refractory to anti-PD-1 therapy

  RNA sequencing (RNA-seq) was performed on baseline (before low-dose 5-aza treatment) and on-treatment (low-dose 5-aza treatment for 5 or 10 days) tumor samples from eight participants with head and neck cancer who were refractory to anti-PD-1 therapy. RNA library preparations, sequencing reactions, and initial bioinformatics analyses were conducted at GENEWIZ, LLC. In total, 16 150-bp pair-end RNAseq data were generated.

  Dataset EGAD50000001010

• Multi-region sequencing of 10 neuroblastoma cases

  To investigate intratumour heterogeneity and to better understand tumour evolution in neuroblastoma, we have performed a multi-region whole-exome sequencing on a total of 51 spatially separated tumor samples from 9 primary neuroblastomas (2 low-risk, 1 intermediate-risk and 6 high-risk) and 1 relapsed neuroblastoma. We also assessed the impact of chemotherapy on the clonal expansion by sequencing tumour regions from one medium risk and one high-risk tumour for which we had matched samples obtained at diagnosis and after chemotherapy.

  Dataset EGAD00001008020

• TenK10K Phase 1: Whole Genome Sequencing tandem repeats multi-sample VCFs

  Tandem repeat variants were called for 1,925 samples from phase 1 of the TenK10K project. Variant calling from WGS alignments to the GRCh38 reference assembly was completed with ExpansionHunter v5. This dataset is comprised of autosomal tandem repeat variants provided as multisample compressed VCF format files. SNV-derived principal component scores used in the manuscript (Tanudisastro et al.) are also provided in this dataset.

  Dataset EGAD50000002378

• TenK10K Phase 1: Whole Genome Sequencing Alignments

  Whole genome sequencing was performed for 1,925 samples from phase 1 of the TenK10K project. Sequencing was done with Illumina 2 x 150bp chemistry on a NovaSeq 6000 instrument to achieve mean 30x coverage. Sequence reads were aligned to the GRCh38 reference assembly with a fork of DRAGMAP v1.3.1. This dataset is comprised of 1,925 alignment files in cram format, and their corresponding index files.

  Dataset EGAD50000002466

• Chromatin Accessibility Landscape of Human Pancreatic Ductal Adenocarcinoma (PDAC)

  Therapeutic options in pancreatic ductal adenocarcinoma (PDAC) are largely limited to cytotoxic chemotherapy without the benefit of molecular markers predicting response. By ATAC-seq analyses of EpCAM+ PDAC malignant epithelial cells sorted from 54 freshly resected human tumors, we discovered a signature of 1092 chromatin loci displaying differential accessibility between patients with disease-free survival (DFS) < 1 year and patients with DFS > 1 year. Using this signature, we further develop a chromatin accessibility microarray methodology termed “ATAC-Array”, an easy-to-use platform obviating the time and cost of next-generation sequencing. PDAC prognosis can be predicted by ATAC-array, which represents a low-cost, clinically feasible technology for assessing chromatin accessibility profiles.

  Study phs002394