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• 20 years after the first human genome release. Where are we heading?

  The genomic revolution equipped the scientists with millions of human genomes, entirely changing the way we envision, project and interpret science. Together with the amounts of data, it also evolved the need to respect the donors' right to privacy. Data protection laws flourished and, while they undeniably served to improve human rights and good practices in research, they added new layers of complication to the goal of data sharing. Nature Journal has dedicated a collection of remarkable articles to this 20th anniversary, where they portray how scientists did not fulfil the promise at the core of the HGP. The call for efficient sharing of human genomic data is nowadays more live than ever, with the animate issue regarding the faulty availability of data from COVID-19 patients, right when the pandemic is setting an unprecedented pressure on the scientific and medical community. Given its importance, this multi-faceted debate does not lack controversial opinions. Some researchers indeed consider that we should move toward more restrictive data access, giving more decisional power to the donors, despite that would inevitably diminish the usability and value of the data. Even if 20 years after we are still not there, at the EGA we are committed to make the dream behind the HGP a reality, working day by day to enable law-compliant data sharing.

  Blog 20-years-after-the-first-human-genome-release

• Fragmentomics analyses of urinary cell-free DNA permit multi-urologic cancer detection and reduction in tissue biopsies for prostate cancer

  This study demonstrated the close association between urinary cell-free DNA (cfDNA) methylation status and the fragmentation patterns in healthy controls and patients with various diseases. Fragmentomics-based methylation analysis (FRAGMA) enables accurate estimation of methylation levels in urinary cfDNA, which is proved by paired bisulfite sequencing and non-bisulfite sequencing data. FRAGMA showed high accuracy in deducing tissue-of-origin of urinary cfDNA in transplantation patients and pregnant women. Moreover, FRAGMA showed great potential in the detection and classification of multiple cancers from the urinary system, including bladder, kidney, and prostate cancer. This study demonstrated that FRAGMA could be applied to improve current diagnostic strategies based on urine samples.

  Study EGAS50000001431

• HTAS of CD34+ HSPCs in relation to evaluating gene editing outcomes for CGD-causing variants in CYBA and CYBB

  High-throughput amplicon sequencing were performed on CD34+ hematopoietic stem and progenitor cells (HSPCs) derived from 4 healthy donors and one unaffected heterozygous carrier of a CYBB c.252G>A variant causing X-linked granulomatous disease. Targeted genome editing were performed in the HSPCs of CYBA and CYBB genes using CRISPR-Cas9 and recombinant AAV6. To assess gene editing outcomes in CD34+ HSPCs, the targeted loci were amplified from genomic DNA and sequenced with 150-bp paired-end reads on an Illumina iSeq 100 or MiniSeq. Editing rates were determined with CRISPResso2 in HDR mode using standard parameters. The dataaset here contains paired raw fastq files of each sample.

  Study EGAS50000001155

• A human induced pluripotent stem cell toolbox for studying sex chromosome effects -transcriptional landscape

  We use state of the art reprogramming methods to generate panels of isogenic XXY, XX and XY iPSCs from XXY patient fibroblasts. We use CRISPR/Cas9 system to evict Y chromosome from XY cells and generate XO iPSCs. The generation and characterisation of panels of isogenic XXY, XX, XY and XO iPSCs will provide a foundational toolkit to study sex differences in vitro. As iPSCs can be differentiated into any somatic cell type, we can apply the model to any human disease. We have generated bulk RNA-Seq from 12 autosomally isogenic hiPSCs to investigate transcriptional landscape and any differences in those cells in pluripotent state.

  Study EGAS50000000931

• A Single-Cell and Spatial Atlas of Early Human Olfactory Development

  The human nasal region is a complex structure derived from neural crest and placodal lineages, but its development remains poorly understood due to limited fetal tissue access and its intricate architecture. To address this, we created a single-nucleus and spatial transcriptomic atlas of the human fetal nasal region using tissue from 10 fetuses between 7 and 12 post-conceptional weeks. Single-nucleus RNA sequencing (snRNA-seq) revealed 34 distinct cell types, including epithelial, cartilaginous, immune, neuronal, glial, muscular, and vascular cells. By integrating snRNA-seq with multiplexed error-robust fluorescence in situ hybridization (MERFISH), we tracked dynamic changes in cell composition and gene expression over time in the olfactory epithelium (OE) and surrounding nasal regions. We identified novel markers of olfactory sensory neuron development and key pathways regulating epithelial patterning and OE morphogenesis. Notably, we observed early molecular signatures consistent with the "one neuron-one receptor" model, with spatially organized expression of 171 olfactory receptor genes. Together, this study presents the first integrated molecular and spatial framework of early human nasal development. It offers an unprecedented molecular blueprint of olfactory system formation and serves as a foundational resource for embryologists and developmental biologists studying sensory neurogenesis, epithelial patterning, and congenital disorders.

  Dataset EGAD50000001712

• Efficacy of two different FGFR-inhibitors in a patient with extrahepatic cholangiocarcinoma harboring an FGFR2 mutation

  Cholangiocarcinomas (CCAs) is a type of cancer with few effective systemic therapies. Elucidation of the molecular landscape of the disease from genomic studies based on next generation sequencing (NGS) has contributed to the introduction of new targeted therapies. One of these treatments consists of a class of small molecules that target members of the FGFR family of receptor tyrosine kinases. These drugs are effective and have been approved for cholangiocarcinomas with fusions or rearrangements of FGFR genes. In contrast, the role of these inhibitors in cholangiocarcinomas with mutations in FGFR genes is less well defined. We report here a patient with a cholangiocarcinoma bearing a FGFR2 p.Ser252Trp mutation. The patient was treated with two different FGFR inhibitors, as the first caused ocular toxicity. She obtained clinical benefit from both. This case illustrates the efficacy of FGFR inhibitors on cholangiocarcinoma with specific point mutations. This is the first case to report the clinical benefit of these drugs in FGFR2 p.Ser252Trp mutation. Clinical benefit can be sustained, as seen in our patient. Our case also shows that FGFR inhibitors-induced adverse effects, such as ocular toxicities, may not recur after re-challenge with an alternative drug of the same class.

  Dataset EGAD50000000021

• Raw naive T cell AIRR-seq data

  This dataset contains raw bulk adaptive immune receptor repertoire sequencing (AIRR-seq) data targeting the T cell receptor alpha (TRA) and beta (TRB) chains in peripheral blood naïve CD4+ T cells. The dataset contains raw demultiplexed fastq files from a total of 103 subjects with celiac disease and 103 controls, split into 8 sequencing libraries. The dataset also contains an accompanying metadata file (csv). Peripheral blood mononuclear cells were obtained from study participants, and naïve CD4+ T cells were FACS-sorted for RNA extraction and library preparation. Libraries were generated using a 5' RACE strategy incorporating unique molecular identifiers, combined with a semi-nested PCR approach to capture full V(D)J information and reduce amplification bias. Separate TRA and TRB libraries from each individual were constructed using unique dual indexes, and pooled before sequencing. Pooled libraries were sequenced on an Illumina NovaSeq 6000 platform using 250 bp paired-end reads. Raw paired-end FASTQ files were demultiplexed with the pRESTO tool suite.

  Dataset EGAD50000002733

• Whole genome sequencing of 198 epileptic individuals.

  This dataset includes whole genome sequencing of 198 epileptic individuals. Libraries preparation and whole-genome sequencing: gDNA was cleaned up using ZR-96 DNA Clean & ConcentratorTM-5 Kit (Zymo) prior to being quantified using the Quant-iTTM PicoGreen dsDNA Assay Kit (Life Technologies) and its integrity assessed on agarose gels. Libraries were generated using the TruSeq DNA PCR-Free Library Preparation Kit (Illumina) according to the manufacturer’s recommendations. Libraries were quantified using the Quant-iTTM PicoGreen dsDNA Assay Kit (Life Technologies) and the Kapa Illumina GA with Revised Primers-SYBR Fast Universal kit (Kapa Biosystems). Average size fragment was determined using a LabChip GX (PerkinElmer) instrument. The libraries were denatured in 0.05N NaOH and diluted to 8pM using HT1 buffer. The clustering was done on a Illumina cBot and the flowcell was ran on a HiSeq 2500 for 2x125 cycles (paired-end mode) using v4 chemistry and following the manufacturer's instructions. A phiX library was used as a control and mixed with libraries at 0.01 level. Bioinformatics: The Illumina control software was HCS 2.2.58, the real-time analysis program was RTA v. 1.18.64. Program bcl2fastq v1.8.4 was used to demultiplex samples and generate fastq reads. The filtered reads were aligned to reference Homo_sapiens assembly b37. Each readset was aligned to creates a Binary Alignment Map file (.bam).

  Dataset EGAD00001004062

• PPIL4 is essential for brain angiogenesis and implicated in intracranial aneurysm in humans

  Rupture of intracranial aneurysms (IAs) leads to subarachnoid hemorrhage (SAH), a sudden-onset disease often causing severe disability or death. Using whole exome sequencing, we identified significant enrichment of rare, deleterious mutations in PPIL4 in both index and familial IA cases. Ppil4 depletion causes intracerebral hemorrhage, defects in cerebrovascular morphology, and impaired Wnt signaling in vivo. Wild type, but not IA-mutant PPIL4, potentiates Wnt signaling by binding JMJD6, a known angiogenesis regulator and Wnt activator. These findings identify a novel PPIL4-dependent Wnt signaling mechanism involved in brain-specific angiogenesis and maintenance of cerebrovascular integrity, and implicate PPIL4 gene variation in the pathogenesis of human IA.

  Study EGAS00001005518

• A study of the molecular pathogenesis of Splenic Marginal Zone and Diffuse Large B-Cell Lymphoma

  We will perform exome sequencing on selected cases of splenic marginal zone lymphoma (SMZL) and diffuse large B-cell lymphoma (DLBCL) in order to characterise their genetic makeup and identify biomarkers for prognosis and prediction of treatment response.

  Dataset EGAD00001000410

• Use of Deep Sequencing to Dectect Clonal Mutations In Sun Exposed Skin Epidermis PART2

  This study aims to define the landscape of somatic mutations in sun exposed human skin by deep sequencing, analyse their frequency and use the data to infer the effect of mutations on proliferating cell behaviour. The frequency of each mutation will reflect the size of the clone of cells in the tissue sample. By analyzing small samples, clones with as few as 100 cells will be detectable. Allele frequency distributions for each mutation will be used to infer cell fate using published methods (Klein et al. 2010). This study will shed unprecedented light on the early clonal events that lead to the emergence of cancer.

  Dataset EGAD00001000825

• Targeted replication of LVOTO genes

  Non-syndromic cases of congenital heart defects (CHD) exhibit variable modes of inheritance (Mendelian and non-Mendelian). Several studies have identified strong candidates in humans by taking a candidate gene approach as well as by using whole exome next generation sequencing (NGS). So far these studies could only explain a minor fraction of the observed phenotype in humans, most of them in syndromic cases and no single study has focused on the subset of cases with left ventricular outflow tract obstruction (LVOTO). To discover novel disease-causing genes a large cohort of patients with LVOTO, approximately 100 cases, 25 families and 100 trios have been exome sequenced. This study based on NGS sequencing data yielded several known and novel compelling candidate genes, such as MYH6, NR2F2 and MYH11, but also novel ones, such as ITGB4. To evaluate the significance of our findings in a replication cohort we assembled another 1614 cases with an LVOTO phenotype from our collaborators in Toronto, Berlin and Amsterdam. Targeted resequencing in this additional cohort will help to find additional cases with mutations in the identified candidate genes to strengthen genotype-phenotype association. We will use control data from the INTERVAL project for case/control analyses The pulldowns will be performed as 24-plex ISC with 192 or greater indexes, and the sequencing will be performed with 192 samples per lane, requiring 9 lanes of sequencing.

  Dataset EGAD00001002212

• Whole genome sequencing of single cells identifies stochastic aneuploidies, genome replication, states, and clonal repertoires for library A73044A

  Transposase-based amplification-free single-cell genome direct library preparation in nanowell chips; 1340 samples; filetype=bam

  Dataset EGAD00001004719

• Whole genome sequencing of single cells identifies stochastic aneuploidies, genome replication, states, and clonal repertoires for library A73044B

  Transposase-based amplification-free single-cell genome direct library preparation in nanowell chips; 2057 samples; filetype=bam

  Dataset EGAD00001004720

• Whole genome sequencing of single cells identifies stochastic aneuploidies, genome replication, states, and clonal repertoires for library A73046B

  Transposase-based amplification-free single-cell genome direct library preparation in nanowell chips; 1970 samples; filetype=bam

  Dataset EGAD00001004721

• Whole genome sequencing of single cells identifies stochastic aneuploidies, genome replication, states, and clonal repertoires for library A73047D

  Transposase-based amplification-free single-cell genome direct library preparation in nanowell chips; 2091 samples; filetype=bam

  Dataset EGAD00001004722

• Whole genome sequencing of single cells identifies stochastic aneuploidies, genome replication, states, and clonal repertoires for library A73056B

  Transposase-based amplification-free single-cell genome direct library preparation in nanowell chips; 1267 samples; filetype=bam

  Dataset EGAD00001004723

• Whole genome sequencing of single cells identifies stochastic aneuploidies, genome replication, states, and clonal repertoires for library A75616A

  Transposase-based amplification-free single-cell genome direct library preparation in nanowell chips; 230 samples; filetype=bam

  Dataset EGAD00001004724

• Whole genome sequencing of single cells identifies stochastic aneuploidies, genome replication, states, and clonal repertoires for library A75616B

  Transposase-based amplification-free single-cell genome direct library preparation in nanowell chips; 232 samples; filetype=bam

  Dataset EGAD00001004725

• Whole genome sequencing of single cells identifies stochastic aneuploidies, genome replication, states, and clonal repertoires for library A75616C

  Transposase-based amplification-free single-cell genome direct library preparation in nanowell chips; 239 samples; filetype=bam

  Dataset EGAD00001004726

• Whole genome sequencing of single cells identifies stochastic aneuploidies, genome replication, states, and clonal repertoires for library A75617A

  Transposase-based amplification-free single-cell genome direct library preparation in nanowell chips; 692 samples; filetype=bam

  Dataset EGAD00001004727

• Whole genome sequencing of single cells identifies stochastic aneuploidies, genome replication, states, and clonal repertoires for library A90553A

  Transposase-based amplification-free single-cell genome direct library preparation in nanowell chips; 612 samples; filetype=bam

  Dataset EGAD00001004728

• Whole genome sequencing of single cells identifies stochastic aneuploidies, genome replication, states, and clonal repertoires for library A90553C

  Transposase-based amplification-free single-cell genome direct library preparation in nanowell chips; 1700 samples; filetype=bam

  Dataset EGAD00001004729

• Whole genome sequencing of single cells identifies stochastic aneuploidies, genome replication, states, and clonal repertoires for library A95664B

  Transposase-based amplification-free single-cell genome direct library preparation in nanowell chips; 606 samples; filetype=bam

  Dataset EGAD00001004752

• Whole genome sequencing of single cells identifies stochastic aneuploidies, genome replication, states, and clonal repertoires for library A95670A

  Transposase-based amplification-free single-cell genome direct library preparation in nanowell chips; 615 samples; filetype=bam

  Dataset EGAD00001004753

• Whole genome sequencing of single cells identifies stochastic aneuploidies, genome replication, states, and clonal repertoires for library A95670B

  Transposase-based amplification-free single-cell genome direct library preparation in nanowell chips; 636 samples; filetype=bam

  Dataset EGAD00001004754

• Whole genome sequencing of single cells identifies stochastic aneuploidies, genome replication, states, and clonal repertoires for library A95722A

  Transposase-based amplification-free single-cell genome direct library preparation in nanowell chips; 968 samples; filetype=bam

  Dataset EGAD00001004755

• Whole genome sequencing of single cells identifies stochastic aneuploidies, genome replication, states, and clonal repertoires for library A95724A

  Transposase-based amplification-free single-cell genome direct library preparation in nanowell chips; 480 samples; filetype=bam

  Dataset EGAD00001004756

• Whole genome sequencing of single cells identifies stochastic aneuploidies, genome replication, states, and clonal repertoires for library A95724B

  Transposase-based amplification-free single-cell genome direct library preparation in nanowell chips; 561 samples; filetype=bam

  Dataset EGAD00001004757

• Whole genome sequencing of single cells identifies stochastic aneuploidies, genome replication, states, and clonal repertoires for library A95732A

  Transposase-based amplification-free single-cell genome direct library preparation in nanowell chips; 928 samples; filetype=bam

  Dataset EGAD00001004759

• Whole genome sequencing of single cells identifies stochastic aneuploidies, genome replication, states, and clonal repertoires for library A95732B

  Transposase-based amplification-free single-cell genome direct library preparation in nanowell chips; 635 samples

  Dataset EGAD00001004760

• Whole genome sequencing of single cells identifies stochastic aneuploidies, genome replication, states, and clonal repertoires for library A95736A

  Transposase-based amplification-free single-cell genome direct library preparation in nanowell chips; 1072 samples

  Dataset EGAD00001004761

• Whole genome sequencing of single cells identifies stochastic aneuploidies, genome replication, states, and clonal repertoires for library A96139A

  Transposase-based amplification-free single-cell genome direct library preparation in nanowell chips; 1436 samples; filetype=bam

  Dataset EGAD00001004762

• Whole genome sequencing of single cells identifies stochastic aneuploidies, genome replication, states, and clonal repertoires for library A96145A

  Transposase-based amplification-free single-cell genome direct library preparation in nanowell chips; 589 samples; filetype=bam

  Dataset EGAD00001004763

• Whole genome sequencing of single cells identifies stochastic aneuploidies, genome replication, states, and clonal repertoires for library A96150A

  Transposase-based amplification-free single-cell genome direct library preparation in nanowell chips; 656 samples; filetype=bam

  Dataset EGAD00001004764

• Whole genome sequencing of single cells identifies stochastic aneuploidies, genome replication, states, and clonal repertoires for library A96156A

  Transposase-based amplification-free single-cell genome direct library preparation in nanowell chips; 648 samples; filetype=bam

  Dataset EGAD00001004765

• Whole genome sequencing of single cells identifies stochastic aneuploidies, genome replication, states, and clonal repertoires for library A96156B

  Transposase-based amplification-free single-cell genome direct library preparation in nanowell chips; 375 samples; filetype=bam

  Dataset EGAD00001004766

• Whole genome sequencing of single cells identifies stochastic aneuploidies, genome replication, states, and clonal repertoires for library A96165A

  Transposase-based amplification-free single-cell genome direct library preparation in nanowell chips; 755 samples; filetype=bam

  Dataset EGAD00001004767

• Whole genome sequencing of single cells identifies stochastic aneuploidies, genome replication, states, and clonal repertoires for library A96171A

  Transposase-based amplification-free single-cell genome direct library preparation in nanowell chips; 492 samples; filetype=bam

  Dataset EGAD00001004768

• Whole genome sequencing of single cells identifies stochastic aneuploidies, genome replication, states, and clonal repertoires for library A96187A

  Transposase-based amplification-free single-cell genome direct library preparation in nanowell chips; 1222 samples; filetype=bam

  Dataset EGAD00001004770

• Tobacco exposure and somatic mutations in normal human bronchial epithelium

  That tobacco smoking causes lung cancer is well-established, but we lack quantitative understanding of its effects on genomes of normal bronchial epithelium. We sequenced whole genomes of 632 colonies derived from single bronchial epithelial cells across 16 subjects. Tobacco smoking is the major influence on mutation burden, adding 1000-10,000+ mutations/cell, massively increasing both between-subject and within-subject variance, and generating several distinct signatures of substitutions and indels. A population of cells in subjects with smoking history had mutation burdens equivalent to that expected for never-smokers: these cells lacked tobacco-specific mutational signatures, were four-fold more frequent in ex-smokers than current smokers, and had significantly longer telomeres than their more mutated counterparts. Driver mutations increased in frequency with age, affecting 4-14% of cells in middle-aged never-smokers. In current smokers, ≥25% of cells carried driver mutations and 0-6% cells had 2 or even 3 drivers. Thus, tobacco smoking increases mutation burden, cell-to-cell heterogeneity and driver mutations, but quitting promotes replenishment of bronchial epithelium from mitotically quiescent cells that have avoided tobacco mutagenesis.

  Dataset EGAD00001005193

• Interplay of somatic alterations and immune infiltration modulates response to PD-1 blockade in advanced clear cell renal cell carcinoma -- CA209-010

  Immune checkpoint inhibitors targeting the PD-1 pathway have transformed the management of many advanced malignancies, including clear cell renal cell carcinoma (ccRCC), but the drivers and resistors of PD-1 response remain incompletely elucidated. Here, we analyzed 592 tumors collected from advanced ccRCC patients enrolled in prospective clinical trials of treatment with PD-1 blockade (or mTOR inhibition as control arm) by whole-exome and RNA-sequencing, integrated with immunofluorescence analysis, to define the somatic alteration landscape of late-stage ccRCC and to uncover the immunogenomic determinants of therapeutic response. While conventional genomic markers (tumor mutation burden, neoantigen load) and degree of CD8+ T cell infiltration were not associated with clinical response, we discovered numerous chromosomal alterations in advanced ccRCC associated with response or resistance to PD-1 blockade. These advanced tumors were highly CD8+ T cell infiltrated, with only 22% and 5% with an immune desert and immune excluded phenotype, respectively. Our analysis revealed that CD8+ infiltrated tumors are depleted of favorable PBRM1 mutations and are enriched for unfavorable chromosomal losses of 9p21.3 when compared to non-infiltrated tumors. These data demonstrate how the interplay of somatic alterations and immunophenotypes impacts therapeutic efficacy.

  Dataset EGAD00001006026

• Interplay of somatic alterations and immune infiltration modulates response to PD-1 blockade in advanced clear cell renal cell carcinoma -- CA209-009

  Immune checkpoint inhibitors targeting the PD-1 pathway have transformed the management of many advanced malignancies, including clear cell renal cell carcinoma (ccRCC), but the drivers and resistors of PD-1 response remain incompletely elucidated. Here, we analyzed 592 tumors collected from advanced ccRCC patients enrolled in prospective clinical trials of treatment with PD-1 blockade (or mTOR inhibition as control arm) by whole-exome and RNA-sequencing, integrated with immunofluorescence analysis, to define the somatic alteration landscape of late-stage ccRCC and to uncover the immunogenomic determinants of therapeutic response. While conventional genomic markers (tumor mutation burden, neoantigen load) and degree of CD8+ T cell infiltration were not associated with clinical response, we discovered numerous chromosomal alterations in advanced ccRCC associated with response or resistance to PD-1 blockade. These advanced tumors were highly CD8+ T cell infiltrated, with only 22% and 5% with an immune desert and immune excluded phenotype, respectively. Our analysis revealed that CD8+ infiltrated tumors are depleted of favorable PBRM1 mutations and are enriched for unfavorable chromosomal losses of 9p21.3 when compared to non-infiltrated tumors. These data demonstrate how the interplay of somatic alterations and immunophenotypes impacts therapeutic efficacy.

  Dataset EGAD00001006027

• Interplay of somatic alterations and immune infiltration modulates response to PD-1 blockade in advanced clear cell renal cell carcinoma -- CA209-025

  Immune checkpoint inhibitors targeting the PD-1 pathway have transformed the management of many advanced malignancies, including clear cell renal cell carcinoma (ccRCC), but the drivers and resistors of PD-1 response remain incompletely elucidated. Here, we analyzed 592 tumors collected from advanced ccRCC patients enrolled in prospective clinical trials of treatment with PD-1 blockade (or mTOR inhibition as control arm) by whole-exome and RNA-sequencing, integrated with immunofluorescence analysis, to define the somatic alteration landscape of late-stage ccRCC and to uncover the immunogenomic determinants of therapeutic response. While conventional genomic markers (tumor mutation burden, neoantigen load) and degree of CD8+ T cell infiltration were not associated with clinical response, we discovered numerous chromosomal alterations in advanced ccRCC associated with response or resistance to PD-1 blockade. These advanced tumors were highly CD8+ T cell infiltrated, with only 22% and 5% with an immune desert and immune excluded phenotype, respectively. Our analysis revealed that CD8+ infiltrated tumors are depleted of favorable PBRM1 mutations and are enriched for unfavorable chromosomal losses of 9p21.3 when compared to non-infiltrated tumors. These data demonstrate how the interplay of somatic alterations and immunophenotypes impacts therapeutic efficacy.

  Dataset EGAD00001006029

• The mutational landscape of human somatic and germline cells

  During the course of a lifetime normal human cells accumulate mutations. Here, using multiple samples from the same individuals we compared the mutational landscape in 29 anatomical structures from soma and the germline. Two ubiquitous mutational signatures, SBS1 and SBS5/40, accounted for the majority of acquired mutations in most cell types but their absolute and relative contributions varied substantially. SBS18, potentially reflecting oxidative damage, and several additional signatures attributed to exogenous and endogenous exposures contributed mutations to subsets of cell types. The mutation rate was lowest in spermatogonia, the stem cell from which sperm are generated and from which most genetic variation in the human population is thought to originate. This was due to low rates of ubiquitous mutation processes and may be partially attributable to a low cell division rate of basal spermatogonia. The results provide important insights into how mutational processes affect the soma and germline.

  Dataset EGAD00001006641

• 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

• Dataset for gynecologic_cancer-RNA

  Rare cancer sequencing data of 48 runs in tumor/control pairs, which were uploaded to umbrella studies. The sequencing was always paired

  Dataset EGAD00001008856

• Dataset for melanoma-RNA

  Rare cancer sequencing data of 49 runs in tumor/control pairs, which were uploaded to umbrella studies. The sequencing was always paired

  Dataset EGAD00001008858

• Dataset for hematopoietic_malignancy-RNA

  Rare cancer sequencing data of 47 runs in tumor/control pairs, which were uploaded to umbrella studies. The sequencing was always paired

  Dataset EGAD00001008860

• Dataset for soft_tissue_tumor-WHOLE_GENOME

  Rare cancer sequencing data of 142 runs in tumor/control pairs, which were uploaded to umbrella studies. The sequencing was always paired

  Dataset EGAD00001008900