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• Bone marrow single cell genomics from blood cancer samples

  The overall goal of this study was to characterize bone marrow cells based on their transcriptome, surface protein expression and BCR- and TCR VDJ-profile for accurate identification of clinically relevant cell states. This project has received funding from the European Union Horizon 2020 research and innovation programme under grant agreement No 824110 (EASI-Genomics)

  Study EGAS00001007332

• Blood plasma and FFPE derived total RNA seq dataset from DLBCL and PMBCL patients

  Blood plasma samples (n=168) and matched diagnostic formalin-fixed paraffin-embedded (FFPE) tissue samples (n=69) of DLBCL patients, PMBCL patients and healthy controls were collected between 2016-2021. Plasma samples were collected at diagnosis, at interim evaluation, after treatment, and in case of refractory or relapsed disease. RNA was extracted from 200 µl plasma using the miRNeasy serum/plasma kit and from FFPE tissue using the miRNeasy FFPE kit. RNA was subsequently sequenced on a NovaSeq 6000 instrument using the SMARTer Stranded Total RNA-seq pico v3 library preparation kit.

  Dataset EGAD00001011679

• Genome-Wide Association of Native and Post Aspirin Platelet Function Phenotypes

  The goal of this study was to identify genetic variants in a genome-wide association study (GWAS) that are associated with previously obtained platelet function phenotypes measured in each individual under baseline conditions and following 2 weeks of low dose aspirin (ASA). During this study we performed a high density 1 million-SNP genome scan on subjects from GeneSTAR (representing 800 2-generational families with a family history of premature coronary artery disease, 60% white and 40% African American, N=3232). We identified genomic loci associated with quantitative platelet phenotypes prioritized for their biological interest, determined associations between genomic loci and baseline platelet phenotypes (primary phenotypes are platelet aggregation in platelet rich plasma induced by collagen, adenosine diphosphate (ADP), arachidonic acid (AA), and epinephrine (Epi), determined associations between genomic loci and post-ASA platelet phenotypes, ie, measures of ASA "resistance" (primary phenotypes are as above, plus urinary levels of the prostaglandin metabolite, 11-dehydro-thromboxane B2 ), and compared peaks of association between genomic loci and three common baseline platelet phenotypes (collagen-, epinephrine-, and ADP-induced aggregation in platelet rich plasma) with associations found for these same phenotypes in the Framingham Heart Study. We also determined whether any significant genotype-phenotype associations in the 1 million SNP genome scan could be localized to any specific genes or potential genes of interest using publicly available databases and further examined whether candidate genes previously associated with a specific platelet phenotype are located in a genomic region of interest as determined from the SNP genome scan. We conducted replications of our findings, and are presently involved in larger scale meta-analysis of findings for pre-aspirin and post-aspirin associations. The study population is constituted of full siblings (SIBS) (ages 35-78 years) identified from The Johns Hopkins Sibling Study, now called GeneSTAR, the spouses of the SIBS, and their adult offspring (>21 years of age). They include 3200 individuals from approximately 300 African American and 500 white extended families. "Spouse" refers to the other parent of any SIB offspring, independent of marital status. Sibship sizes among families range from 1 to 16 (excluding index cases). On average, each SIB has 2 potentially eligible offspring. A family for this study is defined by all of the full sibships and the total numbers of offspring that come from all SIBS, rather than just the nuclear family.

  Study phs000375

• Whole genome and transcriptome analysis of anaplastic thyroid carcinoma

  Whole genome and transcriptome analysis of anaplastic thyroid carcinoma

  Study EGAS00001001214

• Institut Curie Neuroblastoma Whole Genome Sequencing Diagnosis Relapse

  Neuroblastoma, a clinically heterogeneous pediatric cancer, is characterized by distinct genomic profiles but few recurrent mutations. As neuroblastoma is expected to have high degree of genetic heterogeneity, study of neuroblastoma's clonal evolution with deep coverage whole-genome sequencing of diagnosis and relapse samples will lead to a better understanding of the molecular events associated with relapse. Samples were included in this study if sufficient DNA from constitutional, diagnosis and relapse tumors was available for WGS. Whole genome sequencing was performed on trios (constitutional, diagnose and relapse DNA) from eight patients using Illumina Hi-seq2500 leading to paired-ends (PE) 90x90 for 6 of them and 100x100 for two. Expected coverage for sample NB0175 100x100bp was 30X for tumor and constitutional samples. For the seven other patients expected coverage was 80X for tumor samples with PE 100x100, 100X in the other tumor samples and 50X for all constitutional samples (see table 1). Following alignment with BWA (Li et al., Oxford J, 2009 Jul) allowing up to 4% of mismatches, bam files were cleaned up according to the Genome Analysis Toolkit (GATK) recommendations (Van der Auwera et al., Current Protocols in Bioinformatics, 2013, picard-1.45, GenomeAnalysisTK-2.2-16). Variant calling was performed in parallel using 3 variant callers: GenomeAnalysisTK-2.2-16, Samtools-0.1.18 and MuTect-1.1.4 (McKenna et al., Genome Res, 2010; Li et al., Oxford J, 2009 Aug; Cibulskis et al., Nature, 2013). Annovar-v2012-10-23 with cosmic-v64 and dbsnp-v137 were used for the annotation and RefSeq for the structural annotation. For GATK and Samtools, single nucleotide variants (SNVs) with a quality under 30, a depth of coverage under 6 or with less than 2 reads supporting the variant were filter out. MuTect with parameters following GATK and Samtools thresholds have been used to filter our irrelevant variants. .SNVs within and around exons of coding genes overlapping splice sites.. Then,variants reported in more than 1% of the population in the 1000 genomes (1000gAprl_2012) or Exome Sequencing Project (ESP6500) have been discarded in order to filter polymorphisms. Finally, synonymous variants were filtered out. MuTect focuses on somatic by filtering with constitutional sample. Mpileup comparison between constitutional and somatic DNAs allowed us to focus also on tumor specific SNVs with GATK and Samtools. Finally, every SNV called by our pipeline and also supported in any constitutional samples were filtered our in order to prevent putative constitutional DNA coverage deficiency. Then we analyzed CNVs (copy number variants) with HMMcopy-v0.1.1 (Gavin et al., Genome Res, 2012) and control-FREEC-v6.7 (Boeva et al., Bioinformatics 2011) with a respective window of 2000bp and 1000 bp, and auto-correction of normal contamination of tumor samples for Control-FREEC. Finally we explored Structural variants (SVs) including deletions, inversions, tandem duplications and translocations using DELLY-v0.5.5 with standard parameters (Rausch et al., Oxford J, 2012). In tumors, at least 10 supporting reads were required to make a call and 5 supporting reads for the sample NB0175 with a coverage of only 40X (see table 2). To predict SVs in constitutional samples for subsequent somatic filtering, only 2 supporting reads were required in order not to miss one. To identify somatic events, all the SVs in each normal sample were first flanked by 500 bp in both directions and any SVs called in a tumor sample which was in the combined flanked regions of respective normal sample was removed (see graph 1). Deletions with more than 5 genes impacted or larger than 1Mb and inversions or tandem duplications covering more than 4 genes, were removed. We focused on exonic and splicing events for deletions, inversions, and tandem duplications. For translocation, we keep all SVs that occurred in intronic, exonic, 5'UTR, upstream or splicing regions. Bioinformatics detection of variations with Deep sequencing approach Once PE reads merged and adaptors trimmed by SeqPrep with default parameters, merged reads were aligned via the BWA (Li H. and Durbin R. 2009 PMID 19451168) allowing up to 1 differences in the 22-base-long seeds and reporting only unique alignments. Only reads having a mapping quality 20 or more have been further analysed. Variant calling software was not used, since we aimed to predict variations at low frequencies, observed in less than 1% of reads. Such variants require a custom approach. Using DepthOfCoverage functions of the Genome Analysis Toolkit (GATK) v2.13.2 (McKenna A, et al., 2010 Genome Research PMID: 20644199), we focused on high quality coverage of bases A, C, G and T at the targeted variant position. Depth of coverage of each base following a mapping quality higher than 20 and a base quality higher than 10 have been taken into account in order to focus only on high quality data. Aiming to determine the background level of variability at the studied regions, 10 control samples were included in the analysis. The same approach and filtering criteria have been applied as introduced above over the entire amplicons. In order to highlight variants, for each sample the frequencies of each bases at each amplicon position were then compared to those observed in the set of controls. Statistical analyses were performed with the R statistical software (http://www.R-project.org). Fisher’s exact two-sided tests with a Bonferroni correction were performed to compare percentages of bases between the data sets, i.e. for a given base between a case and the controls. Finally, significant variations were filtered-in once (i) a significant increase in the percentage of avariant base and (ii) a significant decrease in the percentage of it's reference base following our p.values criteria was observed (p.val < 0.05).

  Study EGAS00001001184

• Nanopore sequencing enables allelic phasing of FLG loss-of-function variants, intragenic copy number variation and methylation status in atopic dermatitis and ichthyosis vulgaris

  Loss-of-function (LoF) variants in the FLG gene are associated with ichthyosis vulgaris (IV) and atopic dermatitis (AD). IV and AD patients with two FLG LoF variants are reported to have a more severe disease course. However, subsets of compound heterozygous patients display phenotypic heterogeneity despite a prediction of a severe phenotype from their genotype. The underlying genetic mechanism of this phenotypic variability is unknown. One possibility is that two LoF FLG variants could be located in cis (on the same allele), thus altering the predicted gene dosage. To investigate the allelic contribution of compound heterozygous FLG LoF mutations to IV phenotypic variability, we employ long reads from Oxford Nanopore Technologies, utilising two methodologies to phase the entire coding region of FLG into parental alleles: an amplicon-sequencing approach and an adaptive-sampling strategy. We investigated the allelic phasing of FLG LoF variants and intragenic-repeat copy-number variations (CNV) of 21 subjects with known compound heterozygous genotypes and mixed IV severity. Our results suggest that IV severity is not linked to the presence of cis variants in our IV patient cohort. Nanopore reads enabled detection and accurate phasing of CNVs and LoF variants into parental alleles, providing a framework for future in-depth genetic analysis. These results highlight the usefulness of utilising long reads for interrogating the FLG gene and other highly repetitive genes for genetic stratification related to clinical phenotypes.

  Study EGAS50000000166

• CTSP: Clinical Trial Sequencing Project

  For the Clinical Trials Sequencing Project (CTSP), National Cancer Institute (NCI) will utilize whole genome sequencing and/or whole exome sequencing in conjunction with transcriptome sequencing to try to identify recurrent genetic alterations (mutations, deletions, amplifications, rearrangements) and/or gene expression signatures that would be important to the hypothesis(es) submitted by the investigators. The samples will be processed and submitted for genomic characterization using pipelines and procedures established within The Cancer Genome Analysis (TCGA) project. Data analysis will be performed as a collaboration between the National Clinical Trials Network (NCTN) Group and its investigators submitting the proposal. The investigators at the NCI-sponsored Genomic Data Analysis Center (GDAC) will characterize the samples. The NCTN Group will be responsible for providing the clinical data needed for the proposal to the open clinical system maintained by NCI CCG's Biospecimen Core Resource (BCR) at Nationwide Children's Hospital in Columbus, Ohio. The project team (Network Group/investigators and GDAC) will analyze the data together. Additionally, clinical and genomic data related to the analyses will also need to be registered by NCI and will be made available to qualified researchers via a controlled-access database (e.g., dbGaP) upon publication of the primary analysis described in the study proposal. A substudy description and its molecular data information are provided under its own page: phs001184 CTSP Diffuse Large B-Cell Lymphoma (DLBCL) CALGB 50303

  Study phs001175

• NINDS Family-Based Whole-Genome Sequencing to Find Modifiers of Age of Onset in Huntington's Disease

  The goal of our studies is to identify genetic modifiers of neurodegeneration in Huntington's disease (HD). HD is caused by expansion of CAG repeats in the huntingtin (Htt) gene, with longer stretches often leading to more rapid disease onset and progression. Yet, for a given number of repeats, the age of symptom onset can be variable, differing by up to decades. Thus, the age of onset of motor symptoms in HD is only partly explained by the length of the CAG expansion. Available evidence suggests that genetic modifiers contribute to the variation in HD onset. Identifying genetic modifiers is important because they may provide critical insights into HD pathogenesis and reveal key pathways that could be targeted by novel HD therapeutics. This is important since there are no disease-modifying therapies for HD, and mHtt is an unattractive small-molecule drug target. We recruited 21 HD families with varying characteristics of disease progression and age of onset and obtained medical histories, clinical records and DNA samples that were subjected to whole-genome sequencing (WGS). These WGS data describe families of 104 subjects, including HD patients and their unaffected family members. These individuals were selected based on individual clinical histories and family structures that best fit our criteria for expressing potential genetic modifiers. We are testing the hypothesis that novel, rare genetic variants contribute to HD and those genetic modifiers can be identified by WGS.

  Study phs001071

• MAITS in HCC

  Hepatocellular Carcinoma (HCC) is a leading cause of cancer-related death and can be considered a prototype of inflammation-derived cancer arising from chronic liver injury. The cell composition of the HCC tumor immune microenvironment (TiME) has a major impact on cancer biology as the TiME can have divergent capacities on tumor initiation, progress, and response to therapy. Recent development of multi-omics and single-cell technologies help us to comprehensively quantify the cellular heterogeneity and spatial organization of the TiME and to further our understanding of antitumor immunity. We investigated the cellular composition of liver cancer patient samples (n=8) using single-cell RNA-seq. For this purpose, mononuclear cells were isolated from human liver cancer samples. Three locations within the tumor-bearing liver were used: adjacent liver, rim and tumor core. Then, cells were FACS sorted (either CD45+ cells or MAIT cells) and subjected to 10X Chromium-based scRNA-seq. We investigated immune cell changes and the cellular heterogeneity of the HCC TiME with a focus on MAIT cells. Annotated H5 files are provided. Clinical metadata including TMN stage, sex, gender, ethnicity, pretreatment, and histopathological reports are available for all patient samples. Further details on the study can be obtained in our paper once it’s published.A complementary dataset derived from ultrahighplex CO-Detection by indEXing (CODEX) from paired patient samples can be accessed through The Cancer Imaging Archives (TCIA) under DOI: https://doi.org/10.7937/bh0r-y074.

  Study phs003279

• International Consortium on the Genetics of Systemic Lupus Erythematosus (SLEGEN)

  The genetic makeup of an individual strongly influences the risk of developing systemic lupus erythematosus (SLE). The identification of genes that predispose an individual to SLE will lead to earlier and better diagnosis, better treatments, and possibly prevention. To this end, the International Consortium on the Genetics of Systemic Lupus Erythematosus (SLEGEN) was formed in 2005 and is composed of lupus researchers who agreed to pool their knowledge and resources to search for genes that predispose to lupus. Eight laboratories contributed DNA samples for genotyping at the Broad Institute and association with SLE was performed by the Data Coordinating Center (Wake Forest University), as part of a four stage study design. Stages one and two of this design were graciously funded by the Alliance for Lupus Research (www.lupusresearch.org). In this stage of the study, approximately 767 SLE patients (cases) were compared to approximately 383 non-SLE patients (controls) for differences among the Illumina HumanHap300. The affected individuals are all females of European decent. 82% of the cases are the index case from multiplex pedigrees for SLE and the remaining 18% have self-reported first degree relatives with SLE. A detailed summary of the methods and results can be found in the manuscript in Nature Genetics February 2008 by SLEGEN "Genome-wide association scan in women with systemic lupus erythematosus identifies susceptibility variants ITGAM, PXK, KIAA1542 and other loci". (Please see also Study Accession: phs000202.v1.p1)

  Study phs000216

• Whole Genome Sequencing Analysis in a Family of Discordant Twins With Non-Syndromic Microtia and Hemifacial Microsomia: Identification of Novel Candidate Genes and Variants

  This research is a non-NIH effort to discover the pathogenesis of non-syndromic microtia and to detect potential candidate genes. Microtia (OMIM 600674, 612290, 251800) is a spectrum of congenital anomalies and facial abnormalities, 90% of the cases followed by hearing loss. Two types of the disease are described in terms of connection to the affected syndromes: anomalies (syndromic) and only clinical manifestation (non-syndromic) associated with other symptoms. Though the exact pathogenesis of microtia remains unknown, pathogenic genes of majority of the microtia syndromic types have been identified. However, the genetic mutation of the non-syndromic microtia has not been confirmed. In this study, whole genome sequencing (WGS) was utilized to screen mutations in monozygotic discordant twins of congenital microtia-atresia and their family members. One of the twins, along with her grandfather, was discordant for microtia-atresia. By bioinformatic analysis of the WGS data from monozygotic twins with microtia and their non-microtia relatives, we proposed that among 28 identified potential genes, 4 of them (CNOT1, ODAD4, TBX15, and GIPC3) could be more responsible for non-syndromic microtia development and phenotypic features. Interested investigators may request to access the DNA genomic sequencing data of the study participants via dbGaP authorized access. In addition to raw genomic sequencing data, datasets of germline mutations and candidate gene mutations may also be available for investigators to request.

  Study phs003216

• Reference Standards for Mosaic Variant Detection

  After conception, postzygotic mutations continuously occur throughout life in humans, causing somatic mosaicism in an individual. The variant type, time of origination, and locations of the mosaic mutations result in unique mosaic patterns in a combinatorial manner and further affect phenotypes, including various noncancerous diseases. Several efforts have, thus, been made to identify the mutational landscape and mechanisms underlying the mosaic mutations. From a technical aspect, the accurate detection of mutations is at the core of the mosaicism research, and the construction of a standard reference is a critical first step to serve as the basis for analytical validation and benchmarks for germline and somatic mutation detection. Furthermore, a reference standard for mosaic mutations is urgently needed to enable more advanced research.Herein, we generated robust, large-scale, and cell line mixture-based reference standards that contain abundant mosaic SNVs and INDELs along with wild-type sites and germ line variants. Moreover, the whole reference standard set mimics the cumulative aspect of mosaic variant acquisition in the early developmental stage through a progressive cell line mixing with confirmed genotypes. It can be used for optimizing the current use of mosaic variant detection strategies, as well as developing algorithms for future improvements.We previously generated an NCBI BioProject (PRJNA758606) to release much of these data. Only the data that are subject to authorized access constraints have been included in this submission to dbGaP. The two data sources are thus, complementary to each other.

  Study phs003399

• Single cell transcriptomics in expanded Tregs of APS-1 patients

  Aim of study: Exploring single cell transcriptomics in expanded Tregs of with autoimmune polyendocrine syndrome type 1 (APS-1) patients (global gene expression, immune panel, TCR). N= 9 APS-1 patients and 9 healthy controls Protocol 1. Regulatory T cells (Tregs) were isolated from EDTA-blood, activated with anti-CD3/CD28 and IL2, expanded in cell culture for 14 days and stored at -150℃ in AB serum or FBS + 5% DMSO until use. 2. Cells were thawed, run through a Live/Dead column and carefully counted. 10000 Tregs were used as input for the 10x protocol. 3. cDNA was generated and amplified using Single Cell VDJ 5’ Gel Beads, Chromium Next GEM Chip K Single cell Kit, Next GEM Single Cell 5’ GEM Kit v2 and 5’ Feature Barcode Kit (all from 10x genomics). 4. Gene expression (GEX) libraries were generated by using the Library Construction Kit from 10x genomics. 5. T-cell receptor (TCR) libraries were generated using the Single Cell Human TCR Amplification Kit and the Library Construction Kit from 10x genomics. 6. 10x Genomics Target Hybridization Kit and Human Immunology Panel was used with GEX libraries. Only 8 patient samples and 8 control samples were used for the immune panel. 7. All libraries have a unique sample index (Dual Index TT Set A). 8. All samples were sequenced on Illumina NovaSeq 6000 on a NovaSeq S2 flow cell.

  Study EGAS50000000181

• Longitudinal Multi-Omic Immune Resource Reveals Dynamic Responses in Healthy Human Aging

  The generation and maintenance of protective immunity is a dynamic interplay between host and environment that is impacted by age. Understanding fundamental changes in the healthy immune system that occur over a lifespan is critical in developing interventions for age-related susceptibility to infections and diseases. Here, we use multi-omic profiling (scRNA-seq, proteomics, flow cytometry) to examine human peripheral immunity in over 300 healthy adults, with 96 young and older adults followed over two years with yearly vaccination. The resulting resource includes scRNA-seq datasets of >16 million PBMCs, interrogating 71 immune cell subsets from our new Immune Health Atlas. This study allows unique insights into the composition and transcriptional state of immune cells at homeostasis, with vaccine perturbation, under Cytomegalovirus (CMV) infection and across age. We find that T cells specifically accumulate age-related transcriptional changes more than other immune cells, independent from inflammation and chronic perturbation. Moreover, impaired memory B cell responses to vaccination are linked to a Th2-like state shift in older adults' memory CD4 T cells, revealing possible mechanisms of immune dysregulation during healthy human aging. This extensive resource is provided with a suite of exploration tools at https://apps.allenimmunology.org/aifi/insights/dynamics-imm-health-age/ to enhance data accessibility and further the understanding of immune health across age. Please note that the Sound Life Cohort raw data are spread across three dbGap submissions: phs003841.v1 (this study), phs003944.v1, and phs003400.v1.

  Study phs003841

• Systematic Growth Factor Profiling Platform for 3D Tumor Models Reveals EstradiolResponsive Cellular Mechanisms of Immunotherapy Resistance

  Epithelial ovarian cancer (EOC) exhibits significant molecular heterogeneity, which is thought to be influenced by the tumor microenvironment (TME). However, the specific factors driving this heterogeneity remain poorly understood. In this study, we integrated growth factoromics and genomic data to identify TME factors contributing to EOC heterogeneity and immunosuppression. Our analysis revealed distinct subgroups of EOC samples with differential responsiveness to specific growth factors, particularly estradiol and R-spondin. Notably, samples with high responsiveness to estradiol and Wnt (C1 cluster) were enriched in the Mesenchymal (MES) molecular subtype, while samples with high responsiveness to R-spondin (C2 cluster) were associated with the Differentiated (DIF) and Immunoreactive (IMR) subtypes. We discovered that the G protein-coupled estrogen receptor (GPER), rather than the classical estrogen receptor alpha (ERα), was the key mediator of estrogen responsiveness and a determinant of molecular subtype classification. Single-cell sequencing analysis identified subsets of estrogen-responsive malignant cell (MAL.PDCD5) and cancer-associated fibroblast (FB.TNFSF10), which were associated with immunosuppressive patterns in the TCGA cohort. Importantly, the interaction between these cell populations significantly increased upon estrogen treatment, suggesting a potential mechanism by which estrogen signaling may contribute to the development of an immunosuppressive TME. Our findings highlight the critical role of estrogen signaling in shaping the molecular heterogeneity and immunosuppressive TME of EOC and provide novel insights into potential therapeutic targets for overcoming immunosuppression in this malignancy.

  Study EGAS50000000422

• CRISPR screening in human trophoblast stem cells reveals both shared and distinct aspects of human and mouse placental development

  The placenta serves as the interface between the mother and fetus, facilitating the exchange of gases and nutrients between their separate blood circulation systems. Trophoblasts in the placenta play a central role in this process. Our current understanding of mammalian trophoblast development relies largely on mouse models. However, given the diversification of mammalian placentas, findings from the mouse placenta cannot be readily extrapolated to other mammalian species, including humans. To fill this knowledge gap, we performed CRISPR knockout (KO) screening in human trophoblast stem cells (hTSCs). We targeted genes essential for mouse placental development and identified more than 100 genes as critical regulators in both human hTSCs and mouse placentas. Among them, we further characterized in detail two transcription factors, DLX3 and GCM1, and revealed their essential roles in hTSC differentiation. Moreover, a gene function-based comparison between human and mouse trophoblast subtypes suggests that their relationship may differ significantly from previous assumptions based on tissue localization or cellular function. Notably, our data reveal that hTSCs may not be analogous to mouse TSCs or the extraembryonic ectoderm (ExE) in which in vivo TSCs reside. Instead, hTSCs may be analogous to progenitor cells in the mouse ectoplacental cone and chorion. This finding is consistent with the absence of ExE-like structures during human placental development. Our data not only deepen our understanding of human trophoblast development but also facilitate cross-species comparison of mammalian placentas.

  Study JGAS000659

• Tumor-reactive heterotypic CD8 T cell clusters from clinical samples

  Emerging evidence suggests a correlation between CD8+ T cell-tumor cell proximity and anti-tumor immune response. However, it remains unknown whether these cells exist as functional clusters that can be isolated from clinical samples. By conventional and imaging flow cytometry, we show here that from 21/21 human melanoma metastases, we could isolate heterotypic clusters, comprising CD8+ T cells interacting with one or more tumor cells and/or antigen-presenting cells (APCs). Single-cell RNA-sequencing revealed that T cells from clusters were enriched for gene signatures associated with tumor reactivity and exhaustion. Clustered T cells exhibited increased TCR clonality indicative of expansion, while TCR-matched T cells showed more exhaustion and co-modulation when conjugated to APCs than to tumor cells. T cells that were expanded from clusters ex vivo exerted on average 9-fold increased killing activity towards autologous melanomas, which was accompanied by enhanced cytokine production. Upon adoptive cell transfer into mice, T cells from clusters showed improved patient-derived melanoma control, which was associated with increased T cell infiltration and activation. Together, these results demonstrate that tumor-reactive CD8+ T cells are enriched in functional clusters with tumor cells and/or APCs and that they can be isolated and expanded from clinical samples. Typically excluded by single cell gating in flow cytometry, these distinct heterotypic T cell clusters serve as a valuable source to decipher functional tumor-immune cell interactions, while they may also be therapeutically explored.

  Study EGAS50000000785

• Massively parallel nanowell-based single-cell gene expression profiling

  Technological advances have enabled transcriptome characterization of cell types at the single-cell level providing new biological insights. New methods that enable simple yet high-throughput single-cell expression profiling are highly desirable. Here we report a novel nanowell-based single-cell RNA sequencing system, ICELL8, which enables processing of thousands of cells per sample. The system employs a 5184-nanowell-containing microchip to capture ~1300 single cells and process them. Each nanowell contains preprinted oligonucleotides encoding poly-d(T), a unique well barcode, and a unique molecular identifier. The ICELL8 system uses imaging software to identify nanowells containing viable single cells and only wells with single cells are processed into sequencing libraries. Here, we report the performance and utility of ICELL8 using samples of increasing complexity from cultured cells to mouse solid tissue samples. Our assessment of the system to discriminate between mixed human and mouse cells showed that ICELL8 has a low cell multiplet rate (< 3%) and low cross-cell contamination. We characterized single-cell transcriptomes of more than a thousand cultured human and mouse cells as well as 468 mouse pancreatic islets cells. We were able to identify distinct cell types in pancreatic islets, including alpha, beta, delta and gamma cells. Overall, ICELL8 provides efficient and cost-effective single-cell expression profiling of thousands of cells, allowing researchers to decipher single-cell transcriptomes within complex biological samples.

  Study EGAS00001002320

• Genome of the Netherlands

  The Genome of the Netherlands (GoNL) Project characterizes DNA sequence variation, common and rare, for SNVs, short insertions and deletions (indels) and larger deletions in 769 individuals of Dutch ancestry selected from five biobanks under the auspices of the Dutch hub of the Biobanking and Biomolecular Research Infrastructure (BBMRI-NL). The samples come from a representative sample of 250 trio-families from all provinces in the Netherlands. The parent-offspring trios include adult individuals ranging in age from 19 to 87 years (mean=53 years; SD=16 years) from birth cohorts 1910-1994. Sequencing was done on blood-derived DNA from uncultured cells and accomplished coverage was 14-15x. Samples where contributed by LifeLines (http://lifelines.nl/lifelines-research/general), The Leiden Longevity Study (http://www.healthy-ageing.nl; http://www.langleven.net), The Netherlands Twin Registry (NTR: http://www.tweelingenregister. org), The Rotterdam studies, (http://www.erasmus-epidemiology.nl/rotterdamstudy) and the Genetic Research in Isolated Populations program (http://www.epib.nl/research/geneticepi/research.html#gip). The sequencing was carried out in collaboration with the Beijing Institute for Genomics (BGI). The analysis was done by a consortium lead by UMCG, LUMC, Erasmus MC, VU university and UMCU, see http://www.nlgenome.nl. Funding for the project was provided by the Netherlands Organization for Scientific Research under award number 184021007, dated July 9, 2009 and made available as a Rainbow Project of the Biobanking and Biomolecular Research Infrastructure Netherlands (BBMRI-NL).

  Study EGAS00001000644

• Successful BRAF/MEK-inhibition in a young patient with BRAF V600E-mutated extrapancreatic acinar cell carcinoma (HIPO-021)

  Pancreatic acinar cell carcinoma (PAC) is a rare disease with a poor prognosis. Treatment options for metastatic PAC are limited and often follow chemotherapeutic regimens for pancreatic ductal adenocarcinoma. Although recurrent genomic alterations, such as BRAF fusions and defects in genes involved in homologous recombination DNA repair, have been described in PAC, data on the clinical efficacy of molecularly guided, targeted treatment are scarce. Here we describe the case of a 27-yr-old patient with BRAF V600E-mutated PAC who was successfully treated with a combination of BRAF and MEK inhibitors. The patient presented to our clinic with abdominal pain and weight loss. Imaging showed extensive retroperitoneal disease as well as mediastinal lymphadenopathy. Because of elevated alpha-fetoprotein (AFP) levels and inconclusive histologic findings, a germ cell tumor was suspected; however, PEI chemotherapy was unsuccessful. A repeat biopsy yielded the diagnosis of PAC and treatment with FOLFIRINOX was initiated. Comprehensive molecular profiling within the MASTER (Molecularly Aided Stratification for Tumor Eradication Research) precision oncology program revealed a somatic BRAF V600E mutation and a germline PALB2 stop-gain mutation. Therapy was therefore switched to BRAF/MEK inhibition, resulting in almost complete remission and disease control for 12 mo and a remarkable improvement in the patient's general condition. These results indicate that BRAF alterations are a valid therapeutic target in PAC that should be routinely assessed in this patient population.

  Study EGAS00001004282

• UK10K NEURO ASD BIONED

  In the UK10K project we propose a series of complementary genetic approaches to find new low frequency/rare variants contributing to disease phenotypes. These will be based on obtaining the genome wide sequence of 4000 samples from the TwinsUK and ALSPAC cohorts (at 6x sequence coverage), and the exome sequence (protein coding regions and related conserved sequence) of 6000 samples selected for extreme phenotypes. Our studies will focus primarily on cardiovascular-related quantitative traits, obesity and related metabolic traits, neurodevelopmental disorders and a limited number of extreme clinical phenotypes that will provide proof-of-concept for future familial trait sequencing. We will analyse directly quantitative traits in the cohorts and the selected traits in the extreme samples, and also use imputation down to 0.1% allele frequency to extend the analyses to further sample sets with genome wide genotype data. In each case we will investigate indels and larger structural variants as well as SNPs, and use statistical methods that combine rare variants in a locus or pathway as well as single-variant approaches. The BioNED (Biomarkers for Childhood onset neuropsychiatric disorders) study has been carrying out detailed phenotypic assessments evaluating children with an autism spectrum disorder. These assessments included ADI-R, ADOS, neuropsychology, EEG etc. There are 56 DNA samples from this study (25 extracted from blood). For further information with regard to this cohort please contact Patrick Bolton (patrick.bolton@kcl.ac.uk).

  Study EGAS00001000111

• UK10K NEURO ASD GALLAGHER

  In the UK10K project we propose a series of complementary genetic approaches to find new low frequency/rare variants contributing to disease phenotypes. These will be based on obtaining the genome wide sequence of 4000 samples from the TwinsUK and ALSPAC cohorts (at 6x sequence coverage), and the exome sequence (protein coding regions and related conserved sequence) of 6000 samples selected for extreme phenotypes. Our studies will focus primarily on cardiovascular-related quantitative traits, obesity and related metabolic traits, neurodevelopmental disorders and a limited number of extreme clinical phenotypes that will provide proof-of-concept for future familial trait sequencing. We will analyse directly quantitative traits in the cohorts and the selected traits in the extreme samples, and also use imputation down to 0.1% allele frequency to extend the analyses to further sample sets with genome wide genotype data. In each case we will investigate indels and larger structural variants as well as SNPs, and use statistical methods that combine rare variants in a locus or pathway as well as single-variant approaches. This is an Irish sample set of individuals with ASD (approximately 50% with comorbid intellectual disability). Individuals have been diagnosed with ADI/ ADOS, measures of cognition/ adaptive function. They represent a more severe, narrowly defined cohort of ASD subjects. Family histories are available for some with measures of broader phenotype. For further information on this cohort please contact Nadia Bolshakova (bolshakn@tcd.ie).

  Study EGAS00001000112

• Persistent STAG2 mutation in recurrent pediatric glioblastoma

  Similar to their adult counterparts, the prognosis for pediatric patients with high-grade gliomas remains poor. At time of recurrence, treatment options are limited and remain without consensus. This report describes the genetic findings, obtained from whole exome sequencing of a pediatric patient with glioblastoma who underwent multiple surgical resections and treatment with standard chemoradiation, as well as a novel recombinant poliovirus vaccine therapy. Strikingly, despite the variety of treatments, there was persistence of a tumor clone, characterized by a deleterious STAG2 mutation, whose deficiency in pre-clinical studies can cause aneuploidy and aberrant mitotic progression, but remains understudied in the clinical setting. There was near elimination of an EGFR mutated and amplified tumor clone after gross total resection, standard chemoradiation, and poliovirus therapy, followed by the emergence of a persistently STAG2 mutated clone, with rare mutations in PTPN11 and BRAF, the latter composed of a novel deleterious mutation previously not reported in pediatric glioblastoma (p.D594G). This was accompanied by a mutation signature shift towards one characterized by increased DNA damage repair defects, consistent with the known underlying STAG2 deficiency. As such, this case represents a novel report following the clinical and genetic progression of a STAG2 mutated glioblastoma, including treatment with a novel and emerging immunotherapy. Although STAG2 deficiency comprises only a small subset of gliomas, this case adds clinical evidence to existing pre-clinical data supporting a role for STAG2 mutations in tumor formation and resistance to standard therapies.

  Study EGAS00001004340

• Combining transcription factor binding affinities with open chromatin data for accurate gene expression prediction

  The binding and contribution of transcription factors (TF) to cell specific gene expression is often deduced from open-chromatin measurements to avoid cost and labour intensive TF ChIP-seq assays.It is important to develop reliable and fast computational methods for accurate TF binding prediction in open-chromatin regions (OCRs). Here, we report a novel segmentation-based method, TEPIC, to predict TF binding by combining sets of OCRs with position weight matrices.TEPIC can be applied to various open-chromatin data, e.g. DNaseI-seq and NOMe-seq, using either peaks or footprints as input.In addition to open-chromatin data, also Histone-Marks (HMs) can be used in TEPIC to identify candidate TF binding sites.TEPIC computes TF affinities and uses open-chromatin/HM signal intensity as quantitative measures of TF binding strength.Using machine learning techniques, we show that incorporating low affinity binding sites improves our ability to explain gene expression variability compared to the standard presence/absence classification of binding sites.Further, we show that both footprints and peaks capture essential TF binding events and lead to a good prediction performance.In our application, gene-based scores computed by TEPIC with one open-chromatin assay nearly reach the quality of several TF ChIP-seq datasets.Finally, we show that these scores correctly predict known transcriptional regulators as illustrated by the application to novel DNaseI-seq and NOMe-seq data for primary human hepatocytes and CD4+ T-cells, respectively.

  Study EGAS00001002073

• The Southern African Human Genome Programme

  The Southern African Human Genome Programme (SAHGP) is a national and regional initiative that aims to unlock the unique genetic character of southern African populations. Its vision is to improve quality of life through understanding human genetic diversity. It is timely to advance the SAHGP initiative since global genomic initiatives are increasingly pointing to populations in Africa, more specifically the San and Khoe from southern Africa, as harbouring the most ancient genetic signatures among the living populations of the world. Studies on African populations have already generated a wealth of information upon which the SAHGP can build. This information will be used to promote and support genomic research programmes both nationally and regionally to address critical questions that would benefit the people of our region. The SAHGP aims to make a significant contribution to the understanding of DNA variation among southern Africans and how this impacts on the health of the people of this region. Aims of the SAHGP: To develop capacity for genomic research in southern Africa; To establish sustainable resources for genomic research in the region; and To translate knowledge and information into improvements in human health in the region. The objective is to derive the maximum benefit from the SAHGP, and that the data should be widely shared with the scientific community for the benefit of the people of the sub-continent and beyond.

  Study EGAS00001002639