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• 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).

  Dataset EGAD00001001356

• Evaluation of Nuclear DNA from Rootless Hairs for Forensic Purposes

  The study aims to overcome current limitations in the recovery of DNA from small, difficult forensic samples. Particularly, our goal is to produce a robust laboratory protocol and the accompanying software to accelerate adoption, as well as to evaluate the reliability and robustness of both the laboratory and computational aspects of generating genotype files from minute and/or degraded DNA samples, such as single, rootless hairs.The data accompanying this study includes raw, paired-end reads from high-throughput sequencing of two panels of saliva, head hair, and pubic hair samples collected from anonymous volunteers at the University of California, Santa Cruz. The smaller set (Hair1.0) comprises 8 individuals, while the larger (Hair2.0) comprises 50 individuals, with 3 overlapping individuals between the two panels identified in post-collection analysis. We did not collect phenotype data or personally identifying information from the participants. For the Hair2.0 panel, only a subset of volunteers provided pubic hairs for DNA extraction and sequencing. Also included are saliva-derived genotype array data for all 8 individuals in the Hair1.0 panel and 44 of 50 individuals in the Hair2.0 panel.

  Study phs002979

• Genomic Data Archive From the Network for Pancreatic Organ Donors With Diabetes

  The Network for Pancreatic Organ Donors with Diabetes (nPOD) is the largest biorepository of human pancreata from organ donors with type 1 diabetes (T1D), maturity-onset diabetes of the young (MODY), cystic fibrosis-related diabetes (CFRD), type 2 diabetes (T2D), gestational diabetes, and islet autoantibody positive (AAb+)/pre-T1D. The mission of the nPOD is to distribute biospecimens and associated de-identified data/metadata to an international researcher network, and to promote the development of new treatments for these diabetes conditions. Here, we describe the release of high-parameter genotyping data for the nPOD cohort. Specifically, 372 subjects were genotyped using a customized precision medicine single nucleotide polymorphism (SNP) microarray (UFDIchip). These data were technically validated using published algorithms to evaluate donor relatedness, ancestry, imputed HLA, and T1D genetic risk score. Additionally, 207 subjects were queried for rare known and novel coding region variants via whole exome sequencing (WES). These data are now publicly available, enabling genotype-selected sample requests and the study of novel genotype : phenotype associations, ultimately to explain diabetes heterogeneity and inform precision medicine strategies to interrupt diabetes pathogenesis.

  Study phs002861

• Genetics of Cutaneous T-Cell Lymphoma

  Mycosis fungoides (MF) is a common extranodal T-cell lymphoma primarily arising in the skin. In early disease stages, MF presents as skin patches and plaques that in some cases may progress to tumor and disperse to lymph nodes and other internal organs. The 10-year overall survival is 50% in advanced stages. Early diagnosis is difficult as the histology overlaps with features of inflammatory skin diseases. Even when the diagnosis is established, there are no prognostic markers that predict whether the disease will be aggressive or indolent. Lastly, there are no curative treatments and MF will invariably relapse, even after aggressive chemotherapy. The disease is a diagnostic, prognostic and therapeutic challenge. The main objective of this study is to address the question of tumor heterogeneity in MF. To date, MF is considered to be monoclonal, derived from a transformed, mature memory T-cell. However, clinical observations and preliminary data suggest that MF comprises multiple subclones, which may be of importance for understanding disease evolution and resistance to therapy. We plan to address this objective using Whole Exome Sequencing (WES) of MF tissue prepared by laser microdissection (LMD).

  Study phs001877

• Transcriptomic Characterization of Human Innate T Cells

  We performed low input RNA-seq and single-cell RNA-seq on 7 lymphocyte populations with the objective of finding the common transcriptional programs shared among innate T cells. In brief, we drew blood from healthy donors and isolated CD4+ T cells, CD8+ T cells, Natural Killer cells, invariant natural killer T (iNKT) cells, mucosal-associated invariant T (MAIT) cells, and two γδ T cell populations: Vδ1 and Vδ2. We performed low input RNA-seq on samples with 1000 cells each, for 6 healthy individuals, in duplicate. We performed single-cell RNA-seq with DNA-barcoded hashing antibodies to identify the cell type of origin for each cell. We found a common transcriptional program across lymphocytes that is gradually turned on as lymphocytes have a more "innateness" state, promoting effector functions and sacrificing proliferative capacity. Additionally, we performed low input RNA-seq for Vδ3-expressing γδ T cells and δ/αβ T cells for one healthy individual in duplicate (1000 cells per sample). This revealed δ/αβ T cells are transcriptionally more adaptive-like and Vδ3 more innate-like.

  Study phs002007

• Development of CMT Peds Scale for Children with CMT

  Information about how different forms of CMT affect children is not readily available because there are not good methods to measure impairment of children with CMT. The purpose of this project is to develop and test such a method and to then test this scale to ensure that it is an effective measurement of impairment of CMT in children, that the children tolerate it well, that different investigators using this method obtain similar results and that changes over time with the scale allow measurement of progression of CMT in the children. Primary Objective: To develop and test the CMT Peds scale (CMTPedS) in children with CMT in order to refine the scoring for future natural history and therapeutic trials. Secondary Objective: We propose to test the sensitivity of the CMT Peds Scale in a longitudinal study and compare the CMT Peds Scale with the Children's Quality of Life scale CHQ-PF50. 2000 patients <21 years of age with various forms of CMT will be evaluated at baseline and at subsequent annual follow up visits when possible. This first study release makes available data of n=208 study participants.

  Study phs001553

• Characterization of Autosomal CNV Among the Negrito from Peninsular Malaysia

  Copy number variation (CNV) has been recognized as a major contributor to human genome diversity. It plays an important role in determining phenotypes and has been associated with a number of common and complex diseases. However the CNV data from diverse populations is rather limited. Here we report the first investigation of copy number variation (CNV) in the indigenous populations from Peninsular Malaysia. We genotyped 34 Negrito genomes from Peninsular Malaysia using the Affymetrix SNP 6.0 microarray and identified 62 putative novel CNVs, consisting of 25 gains and 37 losses. These CNVs appear unique to the Negrito population and were absent in the DGV, HapMap3 and Singapore Genome Variation Project (SGVP) datasets. Analysis of gene ontology revealed that genes within these CNVs were enriched in the immune system (GO:0002376), response to stimulus mechanisms (GO:0050896), as well as the metabolic pathways (GO:0001852). Copy number gains in CNVRs enriched with genes were significantly higher than the losses (P value <0.001). Therefore, in view of the small population size, relative isolation and semi-normadic lifestyles of this community, we speculate that these CNVs may be attributed to recent local adaptation of Negritos from Peninsular Malaysia.

  Study phs000664

• Fred Hutchinson Cancer Research Center - Whole-Exome Sequencing of Hereditary Prostate Cancer Families

  The specific aim of this study is to identify hereditary prostate cancer (HPC) susceptibility genes using a novel study design, whereby whole-exome sequencing will be undertaken on multiple affected relatives from 19 HPC families, in which ≥ 3 affected relatives were diagnosed with clinically aggressive and/or early onset prostate cancer (PC). While whole-exome sequencing of unrelated affected individuals would result in hundreds of candidate disease variants, this family-based, aggressive/early onset phenotype approach will provide an enriched genetic background for discovery and significantly reduce the number of candidate mutations that will require follow-up. Findings from this pilot study will immediately be followed-up to confirm whether candidate mutations found in each family segregate with disease in the remaining unscreened relatives. As part of this pilot study, we aim to: Perform whole-exome sequencing on 80 affected and 11 unaffected relatives from 19 HPC families that have multiple men diagnosed with an aggressive and/or early onset disease phenotype using the Illumina HiSeq platform; and, Analyze sequencing data using BWA, SAMtools and SeattleSeq to prioritize candidate HPC mutations that segregate with aggressive and/or early onset disease in affected relatives.

  Study phs000350

• Genomics of Circulating Tumor Cells

  Comprehensive analyses of cancer genomes in clinical settings promise to inform prognoses and guide the deployment of precise cancer treatments. A major barrier, however, is the inaccessibility of adequate metastatic tissue for accurate genomic analysis in prostate and other cancers. A potential solution is to characterize circulating tumor cells (CTCs), but this requires overcoming multiple technical hurdles. Here, we report an integrated process to isolate, qualify, and sequence whole exomes of CTCs with high fidelity, using a census-based sequencing strategy. Power calculations suggest that mapping of over 99.995% of the territory accessible in bulk exome sequencing is possible in CTCs. We validated our sequencing process in two prostate cancer patients including one for whom we compared CTC-derived mutations to mutations found in a lymph node metastasis and nine cores of the primary tumor. 51 of 73 CTC mutations (70%) were observed in matched tissue. Moreover, we identified 10 early trunk mutations and 56 metastatic trunk mutations in the non-CTC tumor samples and found 90% and 73% of these, respectively, in CTC exomes. This study establishes a foundation for CTC genomics in the clinic.

  Study phs000717

• Mapping Genes for Mammographic Density

  We recruited 1,521 women from the Old Order Amish (OOA) population of Lancaster County, Pennsylvania, with the primary goal of identifying genetic factors that influence mammographic density. All women were between the ages of 40 and 88 years, with a mean of 54 years. Additional study design details, including eligibility criteria, are described elsewhere (Douglas et al., 2008). The present-day OOA of Lancaster County are the descendants of approximately 550 individuals from central Western Europe who immigrated to the U.S. in the early eighteenth century. All living individuals derive from a single, 14-generation pedigree (Lee et al., 2010). Although the OOA are a genetically closed founder population, allele frequencies and LD profiles are remarkably similar between the OOA and U.S. participants in the International HapMap project (HapMap CEU) for common SNPs (MAF>/=5%) (Van Hout et al., 2010). We recently completed genome-wide linkage and association analyses of mammographic density, including dense and non-dense areas of the breast and the ratio of dense to total area of the breast. Summary-level data from our GWAS are available here and through the Marker of DEnsity (MODE) Consortium.

  Study phs000604