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• Longitudinal Assessment of Methylmercury and Gut Microbes During Pregnancy

  Methylmercury is a potent neurotoxin, and the fetal period is the most vulnerable exposure period. There is significant variability in methylmercury metabolism, which has been attributed to differences in the structure and function of the gut microbiome. Our main objective was to better understand the interplay between gut microorganisms and methylmercury metabolism during pregnancy. To address this aim, associations were investigated between maternal biomarkers (blood, hair, stool) for prenatal methylmercury exposure and maternal gut microbiota during early and late gestation.

  Study phs001768

• A Comprehensive Platform for Analyzing Longitudinal Multi-Omics Data

  PALMO (Platform for Analyzing Longitudinal Multi-omics data) is a platform for analyzing longitudinal data from bulk as well as single cell. It allows to identify inter-, intra-donor variations in genes over longitudinal time points. The analysis can be done on bulk expression dataset without known cell type information or single cell with cell type or user defined groups. It allows to infer stable and variable features in a given donor and each cell type or a user defined group. The outlier analysis can be performed to identify technical/biological perturbed samples in a donor or a participant. Further, differential analysis can be performed to decipher time-wise changes in gene expression in a cell type. The data that is available in the dbGaP is the demo longitudinal samples used in the study, which includes hashed raw fastq files for single-cell RNA-sequencing (scRNA-seq) and non-hashed fastq files for single-cell ATAC-sequencing (scATAC) experiment.

  Study phs003203

• Exploration of CNV’s and SNV’s in cancers with well-known genetic rearrangements: Identification of additional genetic changes in rearrangements-driven cancer

  Specific cancers are well known to have specific gene rearrangements. Representative cancer is chronic myeloid leukemia (CML) which is famous for BCR/ABL gene rearrangements. By the way, also genetic rearrangements are not infrequently found in acute leukemia, and those include CBFB/MYH11 rearrangements, PML/RARA rearrangements, AML/ETO rearrangements, and BCR/ABL rearrangements. The situation is same is for lung adenocarcinoma of non-smokers and prostate cancers, and ALK and RET gene rearrangements are recently found. However, not all these rearrangements are sufficient to develop cancer, and it is suggested that some genetic aberrations are required for the development and progression of cancer in addition to these genetic rearrangements. In this study, we have a plan to explore the existence of additional genetic changes including single nucleotide variants (SNV’s) and copy number variations (CNV’s) in cancers with specific genetic rearrangements so as to define additional genetic changes that confer full oncogenic potential to cancer cells. So as to look at SNV’s and small indels, we are going to use whole exome sequencing (WES) data. And as for CNV’s, we are going to use array-CGH data. Also, to check the functionality of these genetic changes, we are going to use whole transcriptome data (WTS). In addition, in samples with whole genome sequencing (WGS ) data, we are going to explore genetic changes in intronic regions also. In fact, we sequenced 10 AML samples which are known to have specific genetic rearrangements. Analysis of these WGS, WES and WTS data are under the way. If we have a chance to access WES, array-CGH and WTS data of other cancer samples with specific genetic rearrangements, we would be able to compare additional genetic changes required for oncogenesis in cancer cells with various genetic rearrangements. We hope this result will enlighten our understanding of cancer genetics further.

  Study EGAS00001000673

• PDAC Phenotype and Germline Genotype Data Access Committee

  This Data Access Committee (DAC) is responsible for reviewing and approving requests for access to controlled phenotype metadata and derived germline FUT2/FUT3 genotype data from patients with pancreatic ductal adenocarcinoma (PDAC). Access is granted to bona fide researchers for non-commercial research purposes only, subject to approval by the DAC and in accordance with the original informed consent and applicable ethical regulations.

  Dac EGAC50000000893

• GoDARTS T2D-GENES Exome Sequencing Study is a subset of the ~52,000 Type 2 diabetes exome sequencing project.

  The GoDARTS T2D-GENES Exome sequencing study is a subset of a larger Type 2 Diabetes Exome Sequencing project. This effort is a collaboration of six consortia with various funding mechanisms that have joined together to investigate genetic variants for type 2 diabetes (T2D) using the largest T2D case/control sample set compiled to date and includes samples from: T2D-GENES, GoT2D, ESP, SIGMA T2D, LuCAMP, and ProDIGY. This data generated from the Genetics of Diabetes and Audit Research Tayside Study (GoDARTS) cohort was part of the T2D-GENES (Type 2 Diabetes Genetic Exploration by Next-generation sequencing in multi-Ethnic Samples) consortium, which is a NIDDK-funded international research consortium that seeks to identify genetic variants for T2D through multiethnic sequencing studies. Sequencing for the GoDARTS study was performed at the Broad Institute using Illumina Rapid Capture on Illumina HiSeq machines.

  Study EGAS00001002937

• The landscape of Usher syndrome-associated transcript isoforms in the human neural retina

  Usher syndrome is an autosomal recessively inherited disorder characterized by the combination of progressive loss of visual function due to retinitis pigmentosa, sensorineural hearing loss and vestibular dysfunction in a subset of cases. Usher syndrome is clinically and genetically heterogeneous. To date, eleven genes have been identified that are associated with Usher syndrome. It is known that these genes express multiple isoforms, however, for most of the known isoforms their relative importance in the human retina is unknown. To fill this gap, using PacBio long-read mRNA sequencing we aimed to provide an overview of the Usher syndrome transcripts in the human retina.

  Study EGAS50000000504

• WES of adult intellectual disabilities with co-morbid psychiatric disorders (2019-08-07)

  ost adults with intellectual disabilities (ID) do not undergo genetic diagnostic investigation as part of their clinical care and have 'missed the boat' with regard to the WES and WGS genetic testing that is now being provided for children with ID. There is a dramatically increased risk of psychistric disorders in adults with ID, e.g. the risk of psychoses is 10X higher than in the general population. It remains an open question as to how much of adult ID is genetic in origin and how similar the genetic forms of adult ID are to those being diagnosed in children, in part due to survivor bias. There is also the opportunity to identify adults with treatable forms of ID, of which over 80 have been described, thus improving their clinical management. Furthermore, analysis of medical records of adults with genetic forms of ID can help to characterise the 'natural history' of individual disorders, resulting in more accurate prognoses for diagnosed children and identifying opportunities for improved management and possibly therapeutic intervention (e.g. optimal anti-epileptic therapy). Here we propose to exome sequence (to ~50X coverage) 200 adults with ID and co-morbid psychiatric disorders. This cohort has previously been assayed with chromosomal microarrays (Wolfe et al 2017 EJHG, 25, 66-72) identifying a diagnostic yield of ~11% which is comparable to the CNV diagnostic yield in various child ID cohorts (10-15%). The authors observed no substantive biases in diagnostic yield between different psychiatric diagnostic classes. The WES data will be analysed using the diagnostic workflows developed in the DDD study to ensure comparability between child and adult ID datasets. This study is intended as a pilot study to demonstrate the value of WES in adults with ID. This data is part of a pre-publication release. For information on the proper use of pre-publication data shared by the Wellcome Trust Sanger Institute (including details of any publication moratoria), please see http://www.sanger.ac.uk/datasharing/ . This dataset contains all the data available for this study on 2019-08-07.

  Dataset EGAD00001005236

• 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

• Gabriella Miller Kids First Pediatric Research Program in Bladder Exstrophy, Epispadias, Complex (BEEC)

  Urogenital anomalies account for 20-30% of prenatally detected structural defects. Bladder Exstrophy Epispadias Complex (BEEC) describes a subset of anomalies with a spectrum of developmental defects ranging from a mild form of epispadias, to classic bladder exstrophy, to omphalocele, exstrophy, imperforate anus, spinal anomalies (OEIS) complex. Patients with BEEC suffer substantial morbidity and mortality due to impaired genito-urinary dysfunction. The etiology of BEEC is largely unknown. Elucidating the underlying genetic component is critical to gaining a better understanding of the developmental signaling pathways and is likely the first step to developing targeted therapy.

  Study phs002173

• Targeted_sequencing_of_genes_recurrently_mutated_in_AML

  Background Massively parallel sequencing technology has transformed cancer genomics. It is now feasible, in a clinically relevant time-frame, for a clinically manageable cost, to screen DNA from patient tumours for mutations essentially genome-wide. The challenge for personalised medicine will be to increase the sample size to thousands or tens of thousands of well-characterised cases in order to attain sufficient statistical power to stratify patients accurately across the complexity and genomic heterogeneity expected for most of the common tumour types. Currently, whole genome sequencing on this scale is not feasible, and targeted sequencing of relevant portions of the genome will be required. Pilot data We have developed protocols for large-scale, multiplexed sequencing of 100-200 genes in thousands of samples. Essentially, using robotic technology, genomic DNA from the cancer specimen is processed into sequencing libraries with unique DNA barcodes, thereby allowing sequencing reads to be attributed to the sample they derive from. Currently, these sequencing libraries can be generated in a 96-well format using fully automated protocols, and we are exploring methods to expand this to a 384-well format. The sequencing libraries are pooled and hybridized to custom sets of RNA baits representing the genomic regions of interest. Sequencing of the pulled-down libraries is done in pools of 48-96 samples per lane of an Illumina Hi-Seq. This protocol is already implemented at the Sanger Institute. We have published proof that somatic mutations in novel cancer genes can be identified from exome-wide sequencing. In unpublished pilot data, we have established the feasibility of robotic library production, custom pull-down, and multiplexed sequencing of barcoded libraries for 100 known myeloid cancer genes across 760 myelodysplasia samples. Highlights of the data thus far analysed reveal that the coverage is remarkably even between samples; when 96 samples are run, average coverage per lane of sequencing is ~250, with 90-95% of targeted exons covered by >25 reads; known mutations can be discovered in the data set; and the protocol is amenable to whole genome amplified DNA. The bioinformatic algorithms for identification of substitutions and indels in pull-down data are well-established; we have pilot data proving that copy number changes, LOH and genomic rearrangements in specific regions of interest can also be identified by tiling of baits across the relevant loci. Proposal We propose to apply this methodology to 10000 samples from patients with AML enrolled in clinical trials over the last 10-20 years. Oncogenic point mutations and potentially genomic rearrangements will be identified, and linked to clinical outcome data, with a view to undertaking the following sorts of analyses: • Identification of co-occurrence, mutual exclusivity and clusters of driver mutations. • Correlation of prognosis with driver mutations and potentially gene-gene interactions • Exploration of genomic markers of drug response Ultimately, we would like to be in a position to release the mutation data together with matched clinical outcome data to genuine medical researchers via a controlled access approach, possibly within the COSMIC framework (www.sanger.ac.uk/genetics/CGP/cosmic/). The vision here is to generate a portal whereby a clinician faced with an AML patient and his / her mutational profile can obtain a ‘personalised’ prediction of outcome, together with a fair assessment of the uncertainty of the estimate. With a sufficient sample size, there would also be the potential to develop decision support algorithms for therapeutic choices based on such data.

  Study EGAS00001000408