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• Whole genome sequencing of AML samples at presentation, remission, and relapse

  Whole genome sequencing of AML blood or bone marrow at presentation and remission for 5 patients. Relapse samples are included for 2 patients, totaling 12 WGS BAM files.

  Dataset EGAD00001005120

• T-WGBS for Naive B Cell

  Tagged-WGBS for 3 Naive B Cell samples of the CancerEpiSys-PRECiSe project.

  Dataset EGAD00001005966

• University of Miami Study on Genetics of Autism and Related Disorders (AutismDisorders)

  Autism spectrum disorders (ASD) are neurodevelopmental in origin and characterized by impairments in reciprocal social interaction and communication accompanied by restricted and repetitive patterns of interest or behavior. With improved surveillance and a broadening of the diagnostic criteria, the most recent prevalence studies suggest that ASD may affect as many as 1/166 children in the US. Treatments are limited resulting in little impact on the profound morbidity. Little is known about the etiology of ASD, but there is a strong genetic component. Genetic studies over the past decade have failed to identify definitive ASD genes, but have clearly shown that the underlying genetics are more complex than anticipated with the likelihood that multiple genes are acting independently and/or interactively. With this realization the field of ASD genetics is at a critical juncture. To move forward we must embrace new and creative paradigms to successfully dissect the genetic etiology of this disease. Specifically the current study will: Extend our ascertainment to the full range of ASD. We will increase our ASD dataset by collecting 600 families who meet clinical diagnostic criteria for the three most common ASDs: autism (AUT), Asperger disorder (ASP) and Pervasive Developmental Disorder-NOS (PDD-NOS). Phenotype assessment will be expanded to include the Social Responsiveness Scale (SRS) and detailed seizure data. Ascertainment will focus on parent-child trios. Further characterize the ASD-associated variations in the Gamma-Aminobutyric Acid (GABA) receptor (GABR) subunits. We will complete our GABR subunit variant analysis, including coding, UTR, regulatory, and conserved intronic sequence, concentrating on GABRA4 and GABRB1. We will also investigate the role of variation in other GABR subunits. All AUT specific findings will be examined in the entire ASD dataset. Identify the chromosome 19p ASD gene. Multiple genome-wide screens have provided significant evidence for linkage to Chromosome 19p and we have found evidence for significant association in the linked families within an ~3 Mb region. We will genotype 768 SNPs spaced at ~4 kb to refine the candidate region and delineate specific candidate genes for further testing. We will screen the strongest associated candidate genes for additional variants and evaluate evidence for association in the entire ASD dataset (SA5). Develop and apply the Phenotypic Homogeneity Distinction (PHD) algorithm for identification of the phenotypic signature of linkage and/or association signals. The PHD algorithm identifies phenotypic covariates that discriminate a target sample subset (e.g. the positively linked families or families carrying the associated risk allele) from its complement. The resulting PHD discriminators will define a homogeneous subset from our newly-ascertained ASD dataset to use, as a confirmatory dataset and for localization within genes under study in our other aims. Test for gene-gene interactions. To fully explain the spectrum of autism risk, we will test for interactions between genetic variations associated with ASD (such as those in GABR subunit genes). We will build upon our experience using the MDR method and extend our analyses across biological pathways using the entire ASD data set.

  Study phs000436

• 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

• Integrated Analysis of Multimodal Single-Cell Datasets for SARS-CoV-2 Vaccination

  The study aimed to explore immune responses during a time course of BNT162b2 mRNA vaccination. To better characterize these responses, we utilize a suite of multi-modal single-cell sequencing technologies to identify and characterize antigen-specific CD8+ T cells. We leverage an integrative analysis strategy to characterize five molecular modalities in these cells. Our dataset enables the discovery of new subpopulations, molecular signatures, and developmental regulators of these cells. Moreover, we identify these cells in SARS-CoV-2 infected patients and demonstrate their positive predictive value for subsequent clinical recovery. The sequence data of CITE-seq, ASAP-seq and ECCITE-seq experiments are deposited in dbGaP. Peripheral blood mononuclear cell (PBMC) samples for CITE-seq and ASAP-seq were collected from six healthy donors at four time points: immediately before (Day 0) vaccination, after primary vaccination (Day 2, Day 10), and seven days after boost vaccination (Day 28). PBMC samples for ECCITE-seq were collected from eight healthy donors on Day 28.

  Study phs003322

• Starting Treatment with Agonist Replacement Therapies (START): A Randomized Trial of Methadone vs Buprenorphine/Naloxone for the Treatment of Opioid Dependence

  The Starting Treatment with Agonist Replacement Therapy (START) study was a 24-week, open-label, randomized trial of methadone versus Suboxone (buprenorphine/naloxone) for the treatment of opioid dependence. Patients were over the age of 18 and met DSM-IV qualifications for opioid dependence. The primary goal of the study was to determine if either medicine was associated with liver toxicity issues in this vulnerable patient population. Liver enzymes were measured at four time points. Urinalysis for opioids, cocaine, cannabis, benzodiazepines, and methamphetamine were performed on a weekly basis. A flexible dosing scheme was used during which physicians could alter medication dose based on withdrawal symptoms and urinalysis results. Neither medication was found to be associated with liver enzyme levels. In version 2 of this study, a text file containing 7704 SNPs with large allele frequency discrepancy as compared to 1000 Genomes is included. Users have the option to exlude these 7704 SNPs.

  Study phs001135

• Control iPSC lines with clinically annotated genetic variants for versatile multi-lineage differentiation

  Induced Pluripotent Stem Cells (iPSC) derived from healthy individuals are important controls for disease modeling studies. To create a resource of genetically annotated iPSC, we reprogrammed footprint-free lines from four volunteers in the Personal Genome Project Canada (PGPC). Multilineage directed differentiation efficiently produced functional cortical neurons, cardiomyocytes and hepatocytes. Pilot users further demonstrated line versatility by generating kidney organoids, T-cells and sensory neurons. A frameshift knockout was introduced into MYBPC3 and these cardiomyocytes exhibited a hypertrophic phenotype as expected. WGS annotation of PGPC lines revealed on average 20 coding variants. Importantly, nearly all annotated PGPC and HipSci lines harboured at least one pre-existing or acquired variant with cardiac, neurological or other disease associations. Overall, PGPC lines were efficiently differentiated by multiple users into cell types found in six tissues for disease modelling, and clinical annotation highlighted variant-preferred lines for use as unaffected controls in specific disease settings.

  Study EGAS00001003684

• Full genome sequencing of a monozygotic twin discordant for schizophrenia

  We sequenced the genomes from a monozygotic twin discordant for schizophrenia and a tumor-normal pair of an ovarian cancer patient. Using whole-genome twin data to discriminate between correctly identified single nucleotide variants (SNVs) and errors a strategy for the accurate detection of SNVs was developed. By applying stringent sequencing quality measures, excluding error-prone regions and selecting SNVs identified by different mapping and variation calling algorithms, error rates were ~37-fold reduced. This enabled us to identify the first discordant SNVs in monozygotic twins using whole-genome sequencing. In addition, by showing that novel SNVs are highly enriched in errors, accurate estimates of the number of novel and rare SNVs occurring in unrelated Caucasian individuals were obtained. Finally, somatic mutations in coding and regulatory sequences were reliably identified in the highly rearranged ovarian tumor. Overall, our data demonstrate that strategies to reduce error rates in whole-genomes are required for disease gene discovery.

  Study EGAS00001000152

• APCDR Uganda GWAS: Genome-wide sequence variation and susceptibility loci for cardiometabolic traits in a sub-Saharan African population (UG2G component)

  Genomic studies in African populations provide unique opportunities to understand disease aetiology, human genetic diversity and population history in a regional and a global context. To leverage the relative benefits of different strategies, we undertook a combined approach of genotyping and whole-genome sequencing (WGS) in a population-based study of 6,400 individuals from a geographically defined rural community in South-West Uganda. We present data from 4,778 individuals with genotypes for ~2.2 million SNPs from the Uganda GWAS resource (UGWAS), and sequence data on up to 1,978 individuals spanning 41.5M SNPs and 4.5M indels (UG2G); 343 individuals overlap between the two datasets. We highlight the value of the largest sequence panel from Africa to date as a global resource for variant discovery, imputation and understanding the mutational spectrum and its clinical relevance in African populations. Alongside phenotype data, we provide a rich new genomic resource for researchers in Africa and globally.

  Study EGAS00001000545

• White blood cell and cell-free DNA analyses for detection of residual disease in gastric cancer

  Liquid biopsies are providing new opportunities for detection of residual disease in cell-free DNA (cfDNA) after surgery but may be confounded through identification of alterations arising from clonal hematopoiesis. Here, we identify circulating tumor-derived DNA alterations (ctDNA) through ultrasensitive targeted sequencing analyses of matched cfDNA and white blood cells from the same patient. We apply this approach to analyze samples from patients in the CRITICS trial, a phase III randomized controlled study of perioperative chemotherapy in patients with operable gastric cancer. After filtering alterations derived from matched white-blood cells, the presence of ctDNA predicts recurrence when analyzed within nine weeks after preoperative treatment and after surgery in patients eligible for multimodal treatment. These analyses provide a facile method for distinguishing ctDNA from other cfDNA alterations and highlight the utility of ctDNA as a predictive biomarker of patient outcome to perioperative cancer therapy and surgical resection in patients with gastric cancer.

  Study EGAS00001004114