887 research outputs found

    A cancer cell-line titration series for evaluating somatic classification.

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    BackgroundAccurate detection of somatic single nucleotide variants and small insertions and deletions from DNA sequencing experiments of tumour-normal pairs is a challenging task. Tumour samples are often contaminated with normal cells confounding the available evidence for the somatic variants. Furthermore, tumours are heterogeneous so sub-clonal variants are observed at reduced allele frequencies. We present here a cell-line titration series dataset that can be used to evaluate somatic variant calling pipelines with the goal of reliably calling true somatic mutations at low allele frequencies.ResultsCell-line DNA was mixed with matched normal DNA at 8 different ratios to generate samples with known tumour cellularities, and exome sequenced on Illumina HiSeq to depths of >300×. The data was processed with several different variant calling pipelines and verification experiments were performed to assay >1500 somatic variant candidates using Ion Torrent PGM as an orthogonal technology. By examining the variants called at varying cellularities and depths of coverage, we show that the best performing pipelines are able to maintain a high level of precision at any cellularity. In addition, we estimate the number of true somatic variants undetected as cellularity and coverage decrease.ConclusionsOur cell-line titration series dataset, along with the associated verification results, was effective for this evaluation and will serve as a valuable dataset for future somatic calling algorithm development. The data is available for further analysis at the European Genome-phenome Archive under accession number EGAS00001001016. Data access requires registration through the International Cancer Genome Consortium's Data Access Compliance Office (ICGC DACO)

    Identification of genes expressed by immune cells of the colon that are regulated by colorectal cancer-associated variants.

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    A locus on human chromosome 11q23 tagged by marker rs3802842 was associated with colorectal cancer (CRC) in a genome-wide association study; this finding has been replicated in case-control studies worldwide. In order to identify biologic factors at this locus that are related to the etiopathology of CRC, we used microarray-based target selection methods, coupled to next-generation sequencing, to study 103 kb at the 11q23 locus. We genotyped 369 putative variants from 1,030 patients with CRC (cases) and 1,061 individuals without CRC (controls) from the Ontario Familial Colorectal Cancer Registry. Two previously uncharacterized genes, COLCA1 and COLCA2, were found to be co-regulated genes that are transcribed from opposite strands. Expression levels of COLCA1 and COLCA2 transcripts correlate with rs3802842 genotypes. In colon tissues, COLCA1 co-localizes with crystalloid granules of eosinophils and granular organelles of mast cells, neutrophils, macrophages, dendritic cells and differentiated myeloid-derived cell lines. COLCA2 is present in the cytoplasm of normal epithelial, immune and other cell lineages, as well as tumor cells. Tissue microarray analysis demonstrates the association of rs3802842 with lymphocyte density in the lamina propria (p = 0.014) and levels of COLCA1 in the lamina propria (p = 0.00016) and COLCA2 (tumor cells, p = 0.0041 and lamina propria, p = 6 × 10(-5)). In conclusion, genetic, expression and immunohistochemical data implicate COLCA1 and COLCA2 in the pathogenesis of colon cancer. Histologic analyses indicate the involvement of immune pathways

    A Cognitive Model of an Epistemic Community: Mapping the Dynamics of Shallow Lake Ecosystems

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    We used fuzzy cognitive mapping (FCM) to develop a generic shallow lake ecosystem model by augmenting the individual cognitive maps drawn by 8 scientists working in the area of shallow lake ecology. We calculated graph theoretical indices of the individual cognitive maps and the collective cognitive map produced by augmentation. The graph theoretical indices revealed internal cycles showing non-linear dynamics in the shallow lake ecosystem. The ecological processes were organized democratically without a top-down hierarchical structure. The steady state condition of the generic model was a characteristic turbid shallow lake ecosystem since there were no dynamic environmental changes that could cause shifts between a turbid and a clearwater state, and the generic model indicated that only a dynamic disturbance regime could maintain the clearwater state. The model developed herein captured the empirical behavior of shallow lakes, and contained the basic model of the Alternative Stable States Theory. In addition, our model expanded the basic model by quantifying the relative effects of connections and by extending it. In our expanded model we ran 4 simulations: harvesting submerged plants, nutrient reduction, fish removal without nutrient reduction, and biomanipulation. Only biomanipulation, which included fish removal and nutrient reduction, had the potential to shift the turbid state into clearwater state. The structure and relationships in the generic model as well as the outcomes of the management simulations were supported by actual field studies in shallow lake ecosystems. Thus, fuzzy cognitive mapping methodology enabled us to understand the complex structure of shallow lake ecosystems as a whole and obtain a valid generic model based on tacit knowledge of experts in the field.Comment: 24 pages, 5 Figure

    Mutations of AKT3 are associated with a wide spectrum of developmental disorders including extreme megalencephaly

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    Mutations of genes within the phosphatidylinositol-3-kinase (PI3K)-AKT-MTOR pathway are well known causes of brain overgrowth (megalencephaly) as well as segmental cortical dysplasia (such as hemimegalencephaly, focal cortical dysplasia and polymicrogyria). Mutations of the AKT3 gene have been reported in a few individuals with brain malformations, to date. Therefore, our understanding regarding the clinical and molecular spectrum associated with mutations of this critical gene is limited, with no clear genotype–phenotype correlations. We sought to further delineate this spectrum, study levels of mosaicism and identify genotype–phenotype correlations of AKT3-related disorders. We performed targeted sequencing of AKT3 on individuals with these phenotypes by molecular inversion probes and/or Sanger sequencing to determine the type and level of mosaicism of mutations. We analysed all clinical and brain imaging data of mutation-positive individuals including neuropathological analysis in one instance. We performed ex vivo kinase assays on AKT3 engineered with the patient mutations and examined the phospholipid binding profile of pleckstrin homology domain localizing mutations. We identified 14 new individuals with AKT3 mutations with several phenotypes dependent on the type of mutation and level of mosaicism. Our comprehensive clinical characterization, and review of all previously published patients, broadly segregates individuals with AKT3 mutations into two groups: patients with highly asymmetric cortical dysplasia caused by the common p.E17K mutation, and patients with constitutional AKT3 mutations exhibiting more variable phenotypes including bilateral cortical malformations, polymicrogyria, periventricular nodular heterotopia and diffuse megalencephaly without cortical dysplasia. All mutations increased kinase activity, and pleckstrin homology domain mutants exhibited enhanced phospholipid binding. Overall, our study shows that activating mutations of the critical AKT3 gene are associated with a wide spectrum of brain involvement ranging from focal or segmental brain malformations (such as hemimegalencephaly and polymicrogyria) predominantly due to mosaic AKT3 mutations, to diffuse bilateral cortical malformations, megalencephaly and heterotopia due to constitutional AKT3 mutations. We also provide the first detailed neuropathological examination of a child with extreme megalencephaly due to a constitutional AKT3 mutation. This child has one of the largest documented paediatric brain sizes, to our knowledge. Finally, our data show that constitutional AKT3 mutations are associated with megalencephaly, with or without autism, similar to PTEN-related disorders. Recognition of this broad clinical and molecular spectrum of AKT3 mutations is important for providing early diagnosis and appropriate management of affected individuals, and will facilitate targeted design of future human clinical trials using PI3K-AKT pathway inhibitors
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