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• Molecular Characterization of Hemimegalencephaly

  Somatic mutations, in which a fraction of the cells in the body have a deleterious mutation, are well recognized in cancer but only recently appreciated in neurological disease. Given a somatic mutation in a population of progenitor cells, all daughter cells inherit the mutation and are able to express the resultant phenotype as a function of the differentiation program. We recently identified the first de novo somatic mutations in the developing brain in the condition hemimegalencephaly (HME), a catastrophic focal epilepsy condition associated with a malformation of cerebral cortical development (MCD). HME is one of the most severe MCD syndromes, characterized by massive hamartomatous overgrowth of either of the two cerebral hemispheres. Cerebral hemispherectomy is a frequent treatment for refractory epilepsy, allowing the sampling of diseased tissue. By comparing DNA from a diseased brain with DNA from blood/saliva, we identified de novo somatic mutations in PIK3CA, AKT3 or MTOR, part of the mTOR pathway. Mutations were present in 8-40% of sequenced alleles in various brain regions sampled during surgery and in some codons known to activate proteins.• Population informationPatient samples were collected from multiple centers. The population is Caucasian and Hispanic• Molecular technologies employedWhole-exome sequencing• Principal findings of the studyWe were the first to describe mTOR-related and non-mTOR mutations causing hemimegalencephaly, and we described two-hit mutational models to explain the genetic pathogenesis of hemimegalencephaly

  Study phs002156

• Mitochondrial Abnormalities in Schizophrenia and Bipolar Disorder

  Mitochondrial DNA structural variation is one proposed indicator of mitochondrial dysfunction. The large common deletion of mitochondrial DNA (mtDNA) increases with aging across multiple brain regions. We found other large deletions of mtDNA in brain at levels comparable to the common deletion (PMID: 30869147). Since mtDNA molecules replicate independently of nuclear division, the mtDNA copy number is a measure of mitochondrial health; levels are negatively correlated with age and all-cause morbidity. Complex I activity is another functional measure of mitochondria. We previously published a subset of this data from DLPFC (PMID: 29594135) for three indicators (common deletion, mtDNA copy number, Complex I activity). For this study, four indicators (common deletion, large deletions, mtDNA copy number, Complex I activity) were measured in four brain regions from subjects with schizophrenia (SZ) and bipolar disorder (BD) and compared to controls. The four brain regions were: the dorsolateral prefrontal cortex, superior temporal gyrus, primary visual cortex (V1), and nucleus accumbens.    

  Study phs002395

• The Multiomics Blueprint of the Individual with the Most Extreme Lifespan

  Although centenarians are becoming more common in the demography of human populations, the so-called supercentenarians (over 110 years old) are still a rarity. In Catalonia, the historic nation where the subject lived, the life-expectancy for women is 86 years old, so she exceeded more than 30 years the mean statistical value. In a similar manner that premature aging syndromes, such as Hutchinson-Gilford Progeria and Werner syndrome, can provide relevant clues about the mechanisms of aging; the study of supercentenarians might also shed light in the pathways involved in lifespan. To unfold the biological properties that exhibited such a remarkable human being, we developed a comprehensive multiomics analysis in different tissues of her genomic, transcriptomic, metabolomic, epigenomic and microbiomic landscapes , comparing the results with those observed in non-supercentenarian populations.

  Study EGAS50000000884

• Identification_of_synthetic_lethal_genes_by_CRISPR_Cas9_library

  Sequencing is performed on PCR products from the amplification of gRNA segments introduced into cell lines (some are commercial, some are derived by collaborators, as described in HMDMC 13/076). Cellular DNA or RNA are not sequenced. This data is defined as "Other Biological/Biochemical Assay Data" under the WTSI datasharing guidelines and consequently will be released at the time of publication and/or through faculty websites. SEQUENCING DETAILS: in October 2016 3 DNA samples will be submitted for PCR amplification and purification through CGP pipeline using Thompson's custom primer set and PCR settings and sequencing with Hiseq using a custom protocol (with 3 forward reads to read sgRNA1, sgRNA2 and the index, optimized with Illumina Bespoke Sanger team); read length 50bp. The following set of samples will be submitted in later 2016 and ealry 2017 as cell pellet to be processed through CGP Cas9 pipeline (Thompson's oligos and protocols) and sequences on Hiseq (same custom sequencing protocol described above) We are utilizing a custom CRISPR/Cas9 library to identify synthetic lethal gene pairs. Cells will be transduced with LV expressing Cas9, then infected with LV expressign the library of 42'000 sgRNA pairs. Cell pellet will be collected from the cell population at different timepoints. The samples will be processed by CGP pipeline customized for the specific protocol and then sequenced to identify the 19bp of the sgRNA and quantify their representation.

  Study EGAS00001002117

• National Institutes of Health H3Africa African Collaborative Center for Microbiome and Genomics Research (ACCME)

  The African Collaborative Center for Microbiome and Genomics Research is a multi-institutional collaborative research project. The objectives of the project are to collaborate and implement high impact integrative epidemiology and genomics research into discovery of biomarkers associated with cervical carcinogenesis. Specifically ACCME links and leverages existing funded research and program activities at the collaborating institutions to study the interaction between vaginal microbiome, host genetic factors and molecular variants of Human Papilloma Virus (HPV) to determine correlates of viral persistence in the causal pathway of cervical cancer, a major cause of preventable mortality in Nigeria and other parts of sub-Saharan Africa. This research offers several opportunities to advance understanding of cervical carcinogenesis, viral oncogenesis, new biomarker discovery and risk stratification by genotype in a cohort of African women. Sponsorship: This project is sponsored by the National Institutes of Health (NIH)

  Study phs001945

• UK10K NEURO FSZ

  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. These Finnish schizophrenia samples have been collected from a population cohort using national registers. The entire sample collection consists of 2756 individuals from 458 families of whom 931 are diagnosed with schizophrenia spectrum disorder, each family having at least two affected siblings. 170 families originate from an internal isolate (Kuusamo) with a three-fold lifetime risk for the trait. The genealogy of the internal isolate is well documented and the individuals form a “megapedigree” reaching to the 17th Century. All diagnoses are based on DSM-IV and for a large fraction of cases there is cognitive data. For further details/descriptions with regard to this data set please contact Tiina Paunio (tiina.paunio@thl.fi)

  Study EGAS00001000118

• Analysis of error profiles in deep next-generation sequencing data

  BackgroundSequencing errors are key confounding factors for detecting low-frequency genetic variants that are important for cancer molecular diagnosis, treatment, and surveillance using deep next-generation sequencing (NGS). However, there is a lack of comprehensive understanding of errors introduced at various steps of a conventional NGS workflow, such as sample handling, library preparation, PCR enrichment, and sequencing. In this study, we use current NGS technology to systematically investigate these questions.ResultsBy evaluating read-specific error distributions, we discover that the substitution error rate can be computationally suppressed to 10-5 to 10-4, which is 10- to 100-fold lower than generally considered achievable (10-3) in the current literature. We then quantify substitution errors attributable to sample handling, library preparation, enrichment PCR, and sequencing by using multiple deep sequencing datasets. We find that error rates differ by nucleotide substitution types, ranging from 10-5 for A>C/T>G, C>A/G>T, and C>G/G>C changes to 10-4 for A>G/T>C changes. Furthermore, C>T/G>A errors exhibit strong sequence context dependency, sample-specific effects dominate elevated C>A/G>T errors, and target enrichment PCR led to aprox 6-fold increase of overall error rate. We also find that more than 70% of hotspot variants can be detected at 0.1% - 0.01% frequency with the current NGS technology by applying in-silico error suppression.ConclusionsWe present the first comprehensive analysis of sequencing error sources in conventional NGS workflows. The error profiles revealed by our study highlight new directions for further improving NGS analysis accuracy both experimentally and computationally, ultimately enhancing the precision of deep sequencing.

  Study EGAS00001003444

• Exome sequencing of early and late passage Patient Derived Xenogratf Tumoroids with matched Patient Derived Xenogratfs and matched normal liver

  The breadth and depth at which cancer models are interrogated contribute to successful translation of drug discovery efforts to the clinic. In colorectal cancer (CRC), model availability is limited by a dearth of large-scale collections of patient-derived xenografts (PDXs) and paired tumoroids from metastatic disease, the setting where experimental therapies are typically tested. XENTURION is a unique open-science resource that combines a platform of 129 PDX models and a sister platform of 129 matched PDX-derived tumoroids (PDXTs) from patients with metastatic CRC, with accompanying multidimensional molecular and therapeutic characterization. This specific dataset is focused on a comparison of early and late passage tumoroids transcriptomes. In this study we focused our attention on early (passage 3) and late (passage 8-12) PDXTs with their matched PDXs and normal liver

  Study EGAS50000000185

• Anaplastic Meningioma WGS-X10

  Anaplastic meningiomas are a rare, malignant variant of meningioma. At present there is no effective treatment for this cancer. The aim of the study is to identify somatic mutations in anaplastic meningiomas. We plan to sequence a set of 500 known cancer genes in 50 anaplastic meningioma and corresponding peripheral blood DNA samples. Bioinformatics will be used to analyse the results to assess the probability of these mutations being causal and so likely of critical importance for the tumour growth. Identification of these mutations will guide selection of appropriate compounds to effectively treat the disease.

  Dataset EGAD00001001267

• Inference of transcription factor binding from cell-free DNA enables tumor subtype prediction and early detection

  Deregulation of transcription factors (TFs) is an important driver of tumorigenesis, but non-invasive assays for assessing transcription factor activity are lacking. We Here we developed and validated a minimally invasive method for assessing TF activity based on cell-free DNA sequencing and nucleosome footprint analysis. We analyzed whole genome sequencing data for >1,000 cell-free DNA samples from cancer patients and healthy controls using a newly developed bioinformatics pipeline developed by us that infers accessibility of TF binding sites from cell-free DNA fragmentation patterns. We observe patient-specific as well as tumor-specific patterns, including accurate prediction of tumor subtypes in prostate cancer, with important clinical implications for the management of patients. Furthermore, we show that cell-free DNA TF profiling is capable of detection of early-stage colorectal carcinomas. Our approach for mapping tumor-specific transcription factor binding in vivo based on blood samples makes a key part of the noncoding genome amenable to clinical analysis.

  Study EGAS00001003206