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• Genetic analysis of Hirschsprung disease

  Hirschsprung disease (HSCR) is a birth defect resulting from the absence of nerve (ganglion) cells in the gastrointestinal tract. Hirschsprung disease has a population incidence of 1/5,000 live births and most often occurs as an isolated condition. However, approximately 30% of HSCR cases are associated with other birth defects such as Down syndrome, deafness, hypopigmentation, and Congenital Central Hypoventilation syndrome (CCHS). Hirschsprung disease is a genetic condition with autosomal dominant, autosomal recessive, and multigenic patterns of inheritance described. The goal of the research study is to identify genes harboring causative HSCR mutations and to better understand the complex inheritance of HSCR in families using whole genome mapping and sequencing studies with functional follow-up of candidate genes and variants. We intend to ascertain the frequency with which mutations in any human gene lead to familial and isolated forms of HSCR. Clinical information is collected to allow investigation of possible genotype - phenotype correlations. The subject population consists of individuals diagnosed with HSCR and their unaffected relatives. Individuals/families are ascertained through support groups, web-based listings of research studies and genetic testing services, an educational study website, and referrals from genetic counselors and physicians. Blood, or tissue, samples are requested from affected individuals and their unaffected relatives.

  Study phs000497

• Count Me In (CMI): The Metastatic Prostate Cancer (MPC) Project (CMI-MPCproject)

  Count Me In - The Metastatic Prostate Cancer Project: A Patient-Driven Research Initiative to Accelerate Metastatic Prostate Cancer Research The Metastatic Prostate Cancer Project (MPCproject; http://mpcproject.org/) is a research study that empowers men with metastatic and advanced prostate cancer to partner directly with researchers by sharing their samples and clinical information, with the ultimate goal of accelerating scientific discoveries that have clinical impact. The MPCproject enables any man with metastatic or advanced prostate cancer in the US and Canada to participate in cutting-edge genomic and molecular research, regardless of where they live. Metastatic or advanced prostate cancer patients visit the project website and complete an online questionnaire of basic information about themselves and their cancer. Enrolled patients are mailed saliva and blood draw kits, which can be used to extract germline DNA and cell-free DNA (cfDNA), respectively. The study team contacts participants' healthcare institutions to obtain medical records and a portion of archived tumor samples. Whole exome sequencing is performed on tumor DNA, germline DNA, and cfDNA, and transcriptome sequencing is performed on tumor RNA. De-identified data, including linked genomic, clinical, and patient-reported data, are shared via public databases on a recurring pre-publication basis. Participants are regularly provided with updates on the study.

  Study phs001939

• Whole exome sequencing (WES) of EBV- primary central nervous system lymphoma (PCNSL)

  This dataset contains whole exome sequencing (WES) of 29 HIV- EBV- primary central nervous system lymphoma (PCNSL) tumors and 5 activated B-cell-like PCNSL (ABC-PCNSL) and activated B-cell-like diffuse large B-cell lymphoma (ABC-DLBCL) cell lines (TK, HKBML, OCI-Ly3, HBL-1, TMD-8). Cases with secondary involvement of the CNS were excluded. DNA was extracted with AllPrep DNA/RNA FFPE kit and libraries were prepared using the Agilent SureSelect Human All Exon v6 + UTR kit. Paired end reads were aligned to GRCh37 using bwa mem v.0.7.17, and reads were sorted and duplicated were marked in the final BAM files. Access to this data is controlled. There are a number of steps that a researcher must take to obtain access to this data, including execution of a Data Access Agreement between the institutions. The process is overseen by the Technology Development Office; please contact our general email address TDOadmin@phsa.ca. Please only click the "request data" button on the EGA website after a Data Access Agreement is fully executed.

  Dataset EGAD50000000451

• WGS data of patient derived organoids (PDO) generated from dMMR colorectal tumor subclones

  The dataset includes bam files from WGS of 26 monoclonal patient derived organoid (PDO) lines isolated from 6 independent tumor subclones of a dMMR colorectal tumor. These organoids were grown as part of an in vitro timecourse experiment for the duration of 9 weeks; bam files represent the mutational load at the start of the timecourse (t0) and the end of the timecourse (t1).

  Dataset EGAD50000000427

• Whole Exome Sequencing of Human Gastro-esophageal Cancer PDXs

  The dataset includes 51 whole exome sequencing datasets generated using Illumina paired-end sequencing technology. These data derive from 26 patient-derived xenograft (PDX) tumors and their matched normal tissues, which consist of either normal gastric mucosa or blood samples. In one case (GTR0607), the matched normal tissue data are unavailable. As a result, the dataset comprises 102 FASTQ files, providing raw sequencing reads for comprehensive genomic analysis.

  Dataset EGAD50000001407

• RNA-seq of atypical 3q26 samples

  RNA was isolated using phenol-chloroform extraction followed by DNase digestion or using the Qiagen Allprep DNA/RNA kit and protocol (Qiagen, #80204). cDNA synthesis was done using the SuperScript II Reverse Transcriptase kit (Invitrogen). Quantitative real-time PCR was performed by using primers as described previously13,21 on the 7500 Fast Real-time PCR System (Applied Biosystems). Relative levels of gene expression were calculated using the ΔΔCt method

  Dataset EGAD00001006106

• PYDP Papuan Y chromosome Diversity Panel

  The PYDP dataset includes 26 bam files of Y chromosome sequences for Papua New Guinean individuals from different locations, extracted from whole genome sequences. DNA was extrated from saliva samples (Oragen kit). Sequencing libraries were prepared using the TruSeq DNA PCR-Free HT kit. 150 bp paired-end sequencing was performed on the Illumina HiSeq X5 sequencer.

  Dataset EGAD00001008572

• Whole Genome Sequencing of Therapy-Related Myeloid Neoplasms

  The dataset consists of: 51 paired tumor/normal WGS samples (26 tumors and 25 normals), and 13 normal targeted samples.

  Dataset EGAD00001010026

• Geriatric Oncology Database of genotypes and methylation, gene expression, clinical data, and survey results on psychosocial and physical conditions in Japanese elderly cancer patients to establish truly effective treatment strategy

  Owing to the advent of super-aged society, cancer mortality in Japan is forecasted to become an all-time high. The management of elderly patients with cancer is a serious health issue and the need for specific care guidelines for this population is critical in Japan. The significant individual differences in comorbidity, physical and mental functioning, and social problems among aging individuals are obstacles to the progress. The response to cancer treatment varies significantly among patients, even in the same stage of the same type of cancer. Older aged patients are still less likely to be offered participation in clinical trials, thus the number of clinical evidences is limited. The molecular mechanisms regulating the physiological process of ageing and senescence, and cancer are far from understood. To establish a truly effective treatment algorithm, we attempted to develop a geriatric oncology database for genotypes and methylation, gene expression, clinical data, and survey results on psychosocial and physical conditions in Japanese elderly cancer patients in this retrospective study. The genomic analysis was performed in 62, 106, and 173 cases, respectively for gastric, colon and lung cancers. The clinical data and survey results on psychosocial and physical conditions were collected from 166, 313, and 344 patients respectively for gastric, colon and lung cancers, and also collected from 357, 49, and 300 benign cases respectively for cardiovascular disorder, respiratory dysfunction, diabetes and nephropathy as the analysis control.

  Study JGAS000061

• Atypical 3q26/MECOM rearrangements genocopy inv(3)/t(3;3) in acute myeloid leukemia

  Acute myeloid leukemia (AML) with inv(3)/t(3;3)(q21q26) is a distinct WHO recognized entity, characterized by its aggressive course and poor prognosis. In this subtype of AML, the translocation of a GATA2 enhancer (3q21) to MECOM (3q26) results in overexpression of the MECOM isoform EVI1 and monoallelic expression of GATA2 from the unaffected allele. The full-length MECOM transcript, MDS1-EVI1, is not expressed as the result of the 3q26 rearrangement. Besides the classical inv(3)/t(3;3), a number of other 3q26/MECOM rearrangements with poor treatment response have been reported in AML. Here we demonstrate, in a group of 33 AML patients with atypical 3q26 rearrangements, MECOM involvement with EVI1 overexpression, but no or low MDS1-EVI1 levels. Moreover, the 3q26 translocations in these AML patients often involve super-enhancers of genes active in myeloid development (e.g. CD164, PROM1, CDK6 or MYC). In more than 50% of these cases allele specific GATA2 expression was observed, either by copy number loss or by an unexplained allelic imbalance. Altogether, atypical 3q26 recapitulate the main leukemic mechanism of inv(3)/t(3;3) AML, namely EVI1 overexpression driven by enhancer hijacking, absent MDS1-EVI1 expression and potential GATA2 involvement. Therefore, we conclude that both atypical 3q26/MECOM and inv(3)/t(3;3) can be classified as a single entity of 3q26-rearranged AMLs. Routine analyses determining MECOM rearrangements, EVI1 and MDS1-EVI1 expression are required to recognize 3q-rearranged AML cases.

  Study EGAS00001004325

• Download Metadata

  Metadata Distribution Welcome to the realm of Metadata Distribution within the EGA ecosystem! Our Metadata REST API empowers you to effortlessly retrieve metadata from the expansive landscape of EGA. By utilising this API, you gain access to publicly available insights across various EGA domains, including studies, samples, experiments, runs, analyses, policies, DACs, and datasets. Furthermore, this API facilitates cross-referencing of objects, enabling you to gather, for example, all the datasets associated with a specific DAC, seamlessly. In addition, we have added the ability to query private data using the metadata API. If you possess the necessary permissions, you can access behind-the-login private data for a specified list of datasets. Metadata Distribution Index Identifiers Dataset Mappings Website Download Metadata API - Private Identifiers At the core of EGA's organisational structure are unique accessions that serve as essential tags for our diverse objects. Here's a quick overview of the accessions and their corresponding object types: EGA Accession ID EGA Object description EGAS EGA Study Accession ID EGAC EGA DAC Accession ID EGAP EGA Policy Accession ID EGAN EGA Sample Accession ID EGAR EGA Run Accession ID EGAX EGA Experiment ID EGAZ EGA Analysis Accession ID EGAD EGA Dataset Accession ID EGAB EGA Submission ID EGAF EGA File Unique Accession ID For further information check our metadata schema documentation. Dataset Mappings For authorised datasets, comprehensive mappings reveal meaningful connections: Sample_file: This file presents information about the linkage between samples and files available in the dataset. Study_experiment_run_sample: This file presents information about the linkage between studies, experiments, runs, and samples within the dataset. Study_analysis_sample: This file presents information about the linkage between studies, analyses, and samples contained within the dataset. Run_sample: This file presents information about the linkage between runs and samples within the dataset. Analysis_sample: This file presents information about the linkage between analyses and samples within the dataset. An empty file indicates the absence of corresponding information. Website Download Our website serves as your gateway to downloading metadata. Simply navigate to the dataset page, and you'll find a blue Metadata button. Once authenticated, you can click this button for authorised datasets. If you lack permissions for a particular dataset, request access by clicking the 'Request Access' button. For authorised datasets, choose your preferred metadata format: CSV, TSV, or JSON. Metadata API - Private Leverage the power of programmatic metadata downloads! Start by authenticating yourself with your credentials to obtain an access token. With this token, programmatically query private information. Queries mirror the structure of the Public Metadata API. However, behind the login, you can delve into specific mapping information (as mentioned above in dataset mappings) alongside object-level exploration. Authentication An active session is required to work with the API. Each time you log in with your credentials a new session is started, which is identified by an access_token. Below an example on how to obtain one using curl: curl https://idp.ega-archive.org/realms/EGA/protocol/openid-connect/token \ -d 'client_id=metadata-api' \ -d 'username=...' \ --data-urlencode 'password=...' \ -d 'grant_type=password' All responses from the API are in JSON format. A successful response should include a new token to be used for the session: {"access_token":"eyJhbGciOiJSUzI1NiIsInR5cCIgOiA...TNw", "expires_in":300, "refresh_expires_in":1800, "refresh_token":"eyJhbGciOiJIUzI1NiIsInR5cCIgOiA...pTX10", "token_type":"Bearer", ... } Save the access_token value and include it in the API call headers. Example query usage Below you can find some example of queries available behing authentication and authorisation. Querying study-experiment-run-sample mappings: curl https://metadata.ega-archive.org/datasets/{datasetID}/mappings/study_experiment_run_sample \ -H 'Authorization: Bearer access_token' Querying run-sample mappings: curl https://metadata.ega-archive.org/datasets/{datasetID}/mappings/run_sample \ -H 'Authorization: Bearer access_token' Querying study-analysis-sample mappings: curl https://metadata.ega-archive.org/datasets/{datasetID}/mappings/study_analysis_sample \ -H 'Authorization: Bearer access_token' Querying analysis-sample mappings: curl https://metadata.ega-archive.org/datasets/{datasetID}/mappings/analysis_sample \ -H 'Authorization: Bearer access_token' Querying sample-file mappings: curl https://metadata.ega-archive.org/datasets/{datasetID}/mappings/sample_file \ -H 'Authorization: Bearer access_token' You can get a different output format by adding one of these options to the curl command: -H 'Accept: text/tsv' -H 'Accept: application/json' -H 'Accept: text/csv' For more detailed information, refer to the Metadata API Specification.

  Documentation access/download/metadata

• Identification of putative multiple myeloma (MM) susceptibility genes

  We sought to identify novel MM susceptibility genes using a collection of families with multiple cases of MM/MGUS, including 189 affected individuals from 40 families, and index cases from an additional 88 families, along with 170 early-onset (EO) MM cases (≤ 55 years). We analyzed a total of 347 affected individuals using whole exome (N=321) and whole genome (N=26) sequencing. Samples were identified and collected through nation-wide efforts in France, Sweden and Greece. We focused on rare (MAF<0.5%) germline protein truncating and likely deleterious missense variants in genes harboring variants in at least two families showing variant-disease segregation, and in additional index (≥2) and/or early-onset (≥2) cases.

  Study EGAS50000001259

• Single cell RNA sequencing data of advanced melanoma patients treated with checkpoint inhibitor immunotherapy

  Single cell RNA libraries were prepared using 10x Genomics Chromium Next GEM Single Cell 3’ v2 reagents. The samples were barcoded and each library were pooled with two samples at equimolar concentrations. The pooled libraries (n=4) were sequenced on the NextSeq 500 machine (Illumina) with paired-end sequencing and dual indexing as recommended in the manufacturer’s protocol; 26 and 98 cycles for the respective Read 1 and 2, and 8 cycles for i7 index.

  Dataset EGAD50000000493

• HERBY trial WES

  Whole exome sequencing of non-brainstem paediatric high grade glioma from the HERBY phase II randomised trial. DNA from 86 cases was subjected to Illumina paired end whole exome sequencing using a customised SureSelect Human All Exon V6 capture set. Germline DNA from whole blood was sequenced for 83 cases. 26 cases were sequenced from both fresh frozen tissue and FFPE material, 10 were sequenced from only fresh frozen material and 50 from only FFPE. Data is provided as bwa aligned BAM files

  Dataset EGAD00001004036

• A dataset compiled as a resource a for orthogonal assessment of exon CNV calling in NGS data

  The dataset includes high-quality sequencing data from a targeted NGS assay (the TruSight Cancer Panel) together with Multiplex Ligation-dependent Probe Amplification (MLPA) results for 96 independent samples. 66 samples contain at least one validated exon CNV and 30 samples have validated negative results for exon CNVs in 26 genes. The dataset includes 46 exon CNVs in BRCA1, BRCA2, TP53, MLH1, MSH2, MSH6, PMS2, EPCAM and PTEN, giving excellent representation of the cancer predisposition genes most frequently tested in clinical practice. Moreover, the validated exon CNVs include 25 single exon CNVs the most difficult exon CNV to detect. The full dataset includes FASTQ files, target BED file, and MLPA results.

  Study EGAS00001002428

• Mitochondrial DNA sequencing of iPSC, parental cells, and iPSC derived cardiomyocytes

  The aim of this work was to analyze to which extent mitochondrial DNA (mtDNA) variants in human induced pluripotent stem cells (iPSC) originate from their parental cells or from de novo mutagenesis, and whether dynamics in variant heteroplasmy levels during prolonged expansion culture of iPSC are caused by inter- or intra-cellular selection or genetic drift. Hence, mtDNA of 26 early passage iPSC clones from, in total, 10 donors and the corresponding parental cell populations (here endothelial cells) were sequenced. Furthermore, 7 iPSC clones were expanded up to passage 50 and the change in variant heteroplasmy levels was monitored. Lastly, the effect of differentiation on the variant heteroplasmy levels was investigated during directed cardiomyocyte differentiation of 4 iPSC clones.

  Study EGAS00001005560

• 'IL-17A-Producing ILC3s and Duodenal Adenoma in FAP'

  Familial Adenomatous Polyposis (FAP) is a hereditary tumor syndrome that significantly enhances the risk of duodenal adenomas, with variations observed even among carriers of the same genetic variant. In this study, intestinal ILCs were isolated from 82 FAP and 26 non-FAP patients and analyzed through flow cytometry, qRT-PCR, and bulkRNA-sequencing. The data revealed a heightened frequency of ILC3s in FAP patients, and increased IL-17A production of duodenal NKp44(-)ILC3s was associated with FAP. Significant elevations in IL1B, IL23A, and DLL4 mRNA expression levels were found in FAP duodenal adenoma tissue, along with enhanced expression of DUOX2 and DUOXA2. The results suggest the involvement of IL-17A-producing NKp44(-)ILC3s in duodenal adenoma formation in FAP.

  Study EGAS00001007347

• Oncogenic fate conversion by PRDM16s causes acute myeloid leukemia

  Oncogenic mutations confer aberrant replicative capacity to cells with little or no replicative capacity, generating cancer stem cells that perpetuate the tumor through extensive self-replication and differentiation blockade. However, whether oncogenes disrupt the cellular identity ofcancer stem cell by altering the developmental potential is unknown. Fate conversion has been demonstrated by ectopic expression of master transcriptional regulators, such as PU.1 and C/EBP alpha that confers myeloid cell fate to other cell types, and PRDM16 that confers brown adipose fate to white adipocytes or myoblasts. Here we show that a transcriptional regulator overexpressed in human myeloid malignancies, PRDM16s, causes oncogenic fate conversion, by transforming cells fated to form platelets and erythrocytes into myeloid leukemia-initiating cells (LICs). Prdm16s expression in hematopoietic progenitor cells caused a myelodysplastic syndrome (MDS)-like disease that progressed to acute myelogenous leukemia (AML). The myeloid diseases caused by Prdm16s exhibited expansion of megakaryocyte-erythroid progenitors (MEPs) but not granulocyte-macrophage progenitors. MEPs from Prdm16s-induced leukemia possessed LIC potential, and expression of Prdm16s in normal MEPs was sufficient to convert them to myeloid LICs and blocked megakaryocytic/erythroid potential. Prdm16s induced the expression of myeloid master regulators, including PU.1 and C/EBP alpha, by interacting with their super enhancers. Ablation of myeloid master regulators attenuated the myeloid potential and reinstalled the megakaryocytic/erythroid potential of leukemic-MEPs in mouse models and in human AML with PRDM16 rearrangement. Our study demonstrates that oncogenic Prdm16 expression converts the fate of MEPs to a malignant myeloid fate by activating myeloid master transcription factors.

  Study EGAS00001003235

• GEDI: A Developmental Model of Gene-Environment Interplay in SUDs: Combined Genotype Dataset from the "Great Smoky Mountains Study" and the "Caring for Children in the Community Study".

  1. Great Smoky Mountains Study (GSMS; Costello et al. 1996, 1997) Three cohorts of boys and girls, aged 9, 11, and 13 years at intake in 1993, were selected from a rural population of some 20,000 children using a household equal probability design. A two-phase procedure was used for White and African-American youth to increase power by oversampling children at risk for psychiatric and SUDs. Parents (usually mothers) of the first stage random population sample completed a questionnaire about their child&#39;s behavioral problems. Of 4,195 subjects selected, 95% (N=3,896) of parents completed the screen. All children scoring above a predetermined threshold (the top 25% of the total scores), plus a 10% random sample of the remaining 75%, were recruited for detailed interviews. Results can be back-weighted to population levels for analyses. Half of the sample consists of females, and 6% are African Americans, reflecting the population of the study area. The interviewed sample of white and African-American subjects was 1,070 (80% of those recruited). American Indian youth were oversampled (100%) because they are an understudied group known to be at high risk for stressful events, substance disorders, and mood disorders. Of 431 age-eligible children, 350 (81% boys, 49% girls) participated. Thus, the size of total GSMS sample is 1,070 + 350 = 1,420. Data collection is complete for ages 9-26, and age 30 interviews are in progress. By age 26 a total of 9,858 interviews had been completed; the average number of interviews per subject was seven, and by age 26, 97.3% completed two or more interviews. 2. The Caring for Children in the Community Study (CCC; Angold et al., 2002) This representative study of psychiatric illness and service use in African-American and White youth took place in four rural counties in the southeastern USA. The two-stage sampling design and methods are similar to those used in the GSMS. Of 4,500 youth randomly selected from the 17,117 9- to 17-year-olds in the public school&#39;s database, 3,613 (80.0%) were successfully contacted and agreed to complete the behavioral screen. Of the 1,302 selected to participate in the study, 920 (70.7%) interviews were completed. Because CCC was also the only study in GEDI to contain more than a very few African-American participants, these were omitted from the multi-site analyses. Reprinted with permission from Cambridge University Press from Costello et al., 2013: PMID: 23461817 References: Costello et al., 1996: PMID: 8956679 Costello et al., 1997: PMID: 9184514 Angold et al., 2002: PMID: 12365876

  Study phs000852

• GEnetics of Nephropathy - an International Effort (GENIE) GWAS of Diabetic Nephropathy in the UK GoKinD and All-Ireland Cohorts

  Diabetic kidney disease, or diabetic nephropathy (DN), is one of the leading causes of end-stage renal disease in the United States and worldwide. DN is a common complication of long-standing type 1 and type 2 diabetes. The clinical course is characterized by development of proteinuria and gradual loss of kidney function. Although existing treatments that decrease proteinuria have been shown to moderately abate progression of diabetic kidney disease, many affected patients, who do not die from cardiovascular disease, go on to develop terminal renal failure, necessitating costly renal replacement therapies, such as dialysis and renal transplantation. Type 1 diabetes (T1D) can have its onset in childhood and affected individuals often develop end-stage renal disease in early adulthood, leading to further loss of quality of life. The genetic basis of the disease is not well understood. The GENIE (GEnetics of Nephropathy an International Effort) consortium was initiated to perform the most comprehensive and well powered DN susceptibility genome wide association study (GWAS) analysis to date, using the largest collection of type 1 diabetics with and without kidney disease across four study cohorts. The UK-ROI samples were genotyped as part of this project. UK-ROI Sample Description The UK-ROI collection consists of samples derived from the Republic of Ireland (Dr. Catherine Godson, PI, at University College, Dublin, Ireland) and the United Kingdom (Warren 3 and Genetics of Kidneys in Diabetes UK, UK GoKinD, Dr. Alexander P. Maxwell, PI, at Queen&#39;s University of Belfast, UK). All study subjects met the inclusion criteria: white individuals with T1D, diagnosed before 31 years of age, whose parents and grandparents were born in the British Isles.

  Study phs000389

• DNA methylation database for gynecological cancer detection, classification and assay development

  MeD-seq data (fastq files) from gynecological cancers and associated healthy tissues. In total 292 fastq files generated by MeD-seq are deposited consisting of: healthy tissues (vulva n=11, cervix n=15, endometrium n=13, fallopian tube n=18 and ovary n=13), precursor lesions of cancer (vulva n=23 and cervix n=46) and cancer (vulva n=21, cervix n=45, endometrium n=26, fallopian tube n=8 and ovary n=33)

  Dataset EGAD50000000611

• Regulatory T cell transcriptomic reprogramming characterizes adverse events by checkpoint inhibitors in solid tumors

  Tregs were sorted as CD4+CD25+CD127- cells from peripheral blood of patients with advanced metastatic melanoma, stage III(B-D)-IV, who were receiving treatment with anti-PD1 (n =26); and patients with kidney, non-small cell lung, liver and bladder cancer who were receiving treatment with anti-PD1. RNA was extracted and polyA libraries were prepared using the Illumina Truseq sample preparation kit v.2. Single-end sequencing was performed on NextSeq500.

  Dataset EGAD00001006415

• BLUEPRINT release August 2016, ChIP-Seq for band form neutrophil, on genome GRCh38

  ChIP-Seq data for 4 band form neutrophil sample(s). 26 run(s), 23 experiment(s), 23 analysis(s) on human genome GRCh38. Part of BLUEPRINT release August 2016. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20160816/homo_sapiens/README_chipseq_analysis_ebi_20160816

  Dataset EGAD00001002454

• Mitochondrial DNA sequencing of human iPSC, parental cells, and iPSC derived cardiomyocytes

  Dataset contains whole mitochondrial DNA sequencing data in fastq format (Illumina MiSeq paired-end) of 62 samples, in total. Those samples include sequencing data of the endothelial cell populations of 10 different donors and of 26 early-passage iPSC clones derived thereof. Moreover, the dataset contains the data of 7 of those iPSC clones sequenced additionally in passage 30 and 50, each. Lastly, 4 iPSC clones were sequenced during directed cardiomyocyte differentiation, each at day 0, 5, and 15 of differentiation.

  Dataset EGAD00001008021

• Integrated single-cell profiling dissects cell-state-specific enhancer landscapes of human tumor infiltrating T cells.

  Despite extensive studies on the chromatin landscape of exhausted T cells, the transcriptional wiring underlying functional and dysfunctional states of human tumor infiltrating lymphocytes (TILs) is incompletely understood. Here, we identify tissue-specific and general gene-regulatory landscapes in the wide breadth of CD8+ TIL functional states covering four cancer entities using single-cell chromatin profiling. We map enhancer-promoter interactions in human TILs by integrating single-cell chromatin accessibility with single-cell RNA-seq data from tumor entity-matching samples and prioritize key elements by super enhancer analysis. Our analysis reveals a human core chromatin trajectory to TIL dysfunction and identifies key enhancers, transcriptional regulators, and deregulated target genes involved in this process. Finally, we validate enhancer regulation at loci encoding PD1, TCF1, and TIM3 by targeting non-coding regulatory elements with potent CRISPR activators and repressors. In summary, our study advances the understanding of molecular regulation of TIL (dys-)function and provides a framework for modulating immunotherapeutic relevant TIL genes via their enhancers.

  Dataset EGAD00001008662