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• DNA methylation of peripheral blood leukocytes from patients with Li-Fraumeni syndrome

  Genomic DNA (~ 1 μg) from LFS patients was treated using sodium bisulfite (Qiagen) converting unmethylated cytosine to uracil but leaving methylated cytosine intact. These samples were then hybridized to the HumanMethylation450 BeadChip or HumanMethylationEPIC BeadChip from Illumina at the Centre for Applied Genomics (TCAG) at the Hospital for Sick Children using the manufacturer’s recommended protocol.

  Study EGAS00001007075

• Targeted_sequencing_of_blood_DNA_from_Human_twins (2019-05-31)

  The goals of this study is to investigate the prevalence and heritability of age-related clonal haemopoeisis (ARCH) in healthy elderly individuals.We will use a bespoke bait set to pull down DNA regions of interest in whole blood samples combined with HiSeq at a deep level . By correlating findings from each individual to their respective twin we hope to elucidate whether heritable traits influence the development of ARCH. a. This data is part of a pre-publication release. For information on the proper use of pre-publication data shared by the Wellcome Trust Sanger Institute (including details of any publication moratoria), please see http://www.sanger.ac.uk/datasharing/ . This dataset contains all the data available for this study on 2019-05-31.

  Dataset EGAD00001005055

• Whole exome sequencing of normal CD34+ cells

  The Genomic DNA Clean & Concentrator kit (ZYMO Research) was used to remove EDTA from the DNA samples. Sample libraries were prepared using 100 ng of input according to the KAPA HyperPlus Kit (Roche) using Unique Dual Index adapters (Integrated DNA Technologies, Inc.). Exomes were captured using the SeqCap EZ MedExome (Roche Nimblegen) according to SeqCap EZ HyperCap Library v1.0 Guide (Roche) with the xGen Universal blockers – TS Mix (Integrated DNA Technologies, Inc.). The amplified captured sample libraries were paired-end sequenced (2x100 bp) on the Novaseq 6000 platform (Illumina) and aligned to the hg19 reference genome using the Burrows-Wheeler Aligner (BWA)3, v0.7.15-r1140.

  Dataset EGAD00001007645

• Transcriptomic profiling of RIRCD patient skeletal muscle, comparing muscle during affected phase to healthy control, and affected patient with and without additional EARS2 mutations.

  Illumina Nextseq total RNA sequencing profiles of skeletal muscle biopsies of 5 affected patients (F3/2M, F4/1F, F5/1M, F2/2F, F2/1M) compared to 6 control (Control040500, Control3509, Control3934, Control3949, Control4994, Control5106) and comparing 3 patients with additional EARS2 mutations (F2/2F, F2/1M, F5/1M) to 2 patients without (F3/2M, F4/1F). Illumina MiSeq total RNA sequencing profiles of skeletal muscle biopsies from patient F3/1M during affected disease phase (4 replicates: F3-1M_Affected_1, F3-1M_Affected_2, F3-1M_Affected_3, F3-1M_Affected_4) compared to recovered phase (F3-1M_Recovered_1, F3-1M_Recovered_2, F3-1M_Recovered_3, F3-1M_Recovered_4).

  Dataset EGAD00001006381

• LLDeep DAG2+: scRNA-seq in PBMCs

  Single cell transcriptomics of PBMCs of 47 donors from the Lifelines Deep cohort (general population, Northern part of the Netherlands). Cells of five or six different donors were pooled together in one sample pool, resulting in eight different sample pools. In total, 28.855 cells were captured and their transcriptomes were sequenced to an average depth of 74k. Genotype data was available for each donor, which allowed us to use the Demuxlet method that uses variable SNPs between the pooled individuals to determine which cell belongs to which individual. Since genotype information is lacking of 2 individuals, the transcriptome of only 45 individuals could be retrieved.

  Dataset EGAD00001003459

• ESGI-Identification of novel genes and mechanisms leading to Primary Ciliary Dyskinesia

  Approximately 80% of clinically clearly diagnosed patients suffering from primary ciliary dyskinesia (PCD) cannot be assigned to a specific gene defect. Despite extensive research on PCD and despite the increasing number of PCD genes and knowledge about their sites of action as e.g structural component or cytoplasmic pre-assembly factor, the biology of motile cilia and the pathomechanism leading to PCD is largely unknown. The aim of this study is to identify novel PCD related genes and processes relevant for motile cilia function.We will perform exome sequencing, aiming on the analysis of family trios. In these families, the diagnosis of PCD is secured, but the underlying gene defects has so far not been identified.

  Dataset EGAD00001001092

• Role of Epigenetic Memory in Human Induced Pluripotent Stem Cells Pilot

  Fibroblasts have been shown to re-program into induced pluripotent stem (hiPS) cells, through over-expression of pluripotency genes. These hiPS cells show similar characteristics to embryonic stem cells including cell surface markers, epigenetic changes and ability to differentiate into the three germ layers. However it is unclear as to the extent of changes in gene expression through the re-programming process.. This data is part of a pre-publication release. For information on the proper use of pre-publication data shared by the Wellcome Trust Sanger Institute (including details of any publication moratoria), please see http://www.sanger.ac.uk/datasharing/

  Dataset EGAD00001000828

• Asian Indian Diabetic Heart Study (AIDHS) /Sikh Diabetes Study (SDS)

  The Punjabi Sikh population is a well-defined, carefully collected homogeneous sample from northern India and the US. It has unique characteristics, which are ideal for genetic studies. Sikhs are strictly a non-smoking population and about 50% of participants are life-long vegetarians. All subjects included in the genome-wide association studies (GWAS) were recruited from one geographical location. Our population demonstrates a strong familial clustering of type 2 diabetes and related cardio-metabolic disorders that may be genetic and we believe that the contribution of alleles at specific loci are likely to be unique to Punjabi Asians compared to Europeans. Our group first showed that the association of a common variant at rs9939609 in the FTO (fat mass and obesity) gene in South Asians was independent of BMI (PMID:18598350) in contrast to Europeans where the association of same variant with T2D is mediated through obesity (PMID:17434869). These findings were later confirmed in an independent sample of South Indians (PMID:19005641), Pakistanis (PMID:21294771), and even East and South Asians in a large meta-analyses study comprising 96,551 individuals (PMID: 22109280). Earlier reported association of MTNR1B with fasting glucose concentrations and type 2 diabetes in European GWAS could not be confirmed in our Sikh cohort. On the other hand, our study revealed, for the first time, a significant protective association of another less common variant in MTNR1B with fasting glucose levels that was modulated by obesity. Ours was the first report that suggested that the low CETP activity was associated with higher CAD risk (PMID:22143414) in South Asians and that the genetic effects are significantly modulated by environmental factors (alcohol consumption). Our recent GWAS on type 2 diabetes has identified a novel locus at chromosome 13q12 in the SGCG gene (p=1.82x10-8) associated with type 2 diabetes (PMID:23300278) in Punjabi Sikhs. From these findings, we are optimistic that our resource will provide new insights to gene functions in the diabetic pathway and better help researchers to understand and translate these insights to novel therapeutic treatment and early prevention to T2D that may be important beyond Indians.

  Study phs000583

• A Single Cell Atlas of Gene Regulatory Elements in the Human Heart

  Background: Cis-regulatory elements such as enhancers and promoters are crucial for directing gene expression in the human heart. Dysregulation of these elements can result in many cardiovascular diseases that are major leading causes of morbidity and mortality worldwide. In addition, genetic variants associated with cardiovascular disease risk are enriched within cis-regulatory elements. However, the location and activity of these cis-regulatory elements in individual cardiac cell types remains to be fully defined. Methods: We performed single nucleus ATAC-seq and single nucleus RNA-seq to define a comprehensive catalogue of candidate cis-regulatory elements (cCREs) and gene expression patterns for the distinct cell types comprising each chamber of four non-failing human hearts. We used this catalogue to computationally deconvolute dynamic enhancers in failing hearts and to assign cardiovascular disease risk variants to cCREs in individual cardiac cell types. Finally, we applied reporter assays, genome editing, and electrophysiogical measurements in in vitro differentiated human cardiomyocytes to validate the molecular mechanisms of cardiovascular disease risk variants. Results: We defined >287,000 candidate cis-regulatory elements (cCREs) in human hearts at single-cell resolution, which notably revealed gene regulatory programs controlling specific cell types in a cardiac region/structure-dependent manner and during heart failure. We further report enrichment of cardiovascular disease risk variants in cCREs of distinct cardiac cell types, including a strong enrichment of atrial fibrillation variants in cardiomyocyte cCREs, and reveal 38 candidate causal atrial fibrillation variants localized to cardiomyocyte cCREs. Two such risk variants residing within a cardiomyocyte-specific cCRE at the KCNH2/HERG locus resulted in reduced enhancer activity compared to the non-risk allele. Finally, we found that deletion of the cCRE containing these variants decreased KCNH2 expression and prolonged action potential repolarization in an enhancer dosage-dependent manner. Conclusion: This comprehensive atlas of human cardiac cCREs provides the foundation for not only illuminating cell type-specific gene regulatory programs controlling human hearts during health and disease, but also interpreting genetic risk loci for a wide spectrum of cardiovascular diseases.

  Study phs002204

• National Institutes of Health The Cancer Genome Atlas (TCGA)

  The Cancer Genome Atlas (TCGA) is a comprehensive and coordinated effort to accelerate our understanding of the molecular basis of cancer through the application of genome analysis technologies, including large-scale genome sequencing. TCGA is a joint effort of the National Cancer Institute (NCI) and the National Human Genome Research Institute (NHGRI), which are both part of the National Institutes of Health, U.S. Department of Health and Human Services. TCGA projects are organized by cancer type or subtype. Click here for a current list of cancer types selected for study in TCGA. Data from TCGA (e.g., gene expression, copy number variation and clinical information), are available via the Genomic Data Commons (GDC). Data from TCGA projects are organized into two tiers: Open Access and Controlled Access. Open Access data tier contains data that cannot be attributed to an individual research participant. The Open Access data tier does not require user certification. Data in Open Access tier are available in the TCGA Data Portal. Controlled Access data tier contains individual-level genotype data that are unique to an individual. Access to data in the Controlled Access data tier requires user certification through dbGaP Authorized Access. Controlled Access data types consist of the following: Individual germline variant data (SNP .cel files) Primary sequence data (.bam files), which are available at GDC Clinical free text fields Exon Array files (for Glioblastoma and Ovarian projects only) NOTE: TCGA strives to release most data in the open access tier. Individual genotype or sequence files are prominent exceptions. Commonly requested files such as descriptions of somatic mutations or clinical data are open access. Please go to this page: https://tcga-data.nci.nih.gov/docs/publications/ to access all data associated with TCGA tumor specific publications. The TCGA study is utilized in the following dbGaP substudies. To view genotypes and other molecular data collected in these substudies, please click on the following substudies below or in the "Substudies" section of this top-level study page phs000178 TCGA study. phs000854 Genome-wide Analysis of Noncoding Regulatory Mutations in Cancer

  Study phs000178