35 research outputs found

    BOD1 Is Required for Cognitive Function in Humans and <i>Drosophila</i>

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    Here we report a stop-mutation in the BOD1 (Biorientation Defective 1) gene, which co-segregates with intellectual disability in a large consanguineous family, where individuals that are homozygous for the mutation have no detectable BOD1 mRNA or protein. The BOD1 protein is required for proper chromosome segregation, regulating phosphorylation of PLK1 substrates by modulating Protein Phosphatase 2A (PP2A) activity during mitosis. We report that fibroblast cell lines derived from homozygous BOD1 mutation carriers show aberrant localisation of the cell cycle kinase PLK1 and its phosphatase PP2A at mitotic kinetochores. However, in contrast to the mitotic arrest observed in BOD1-siRNA treated HeLa cells, patient-derived cells progressed through mitosis with no apparent segregation defects but at an accelerated rate compared to controls. The relatively normal cell cycle progression observed in cultured cells is in line with the absence of gross structural brain abnormalities in the affected individuals. Moreover, we found that in normal adult brain tissues BOD1 expression is maintained at considerable levels, in contrast to PLK1 expression, and provide evidence for synaptic localization of Bod1 in murine neurons. These observations suggest that BOD1 plays a cell cycle-independent role in the nervous system. To address this possibility, we established two Drosophila models, where neuron-specific knockdown of BOD1 caused pronounced learning deficits and significant abnormalities in synapse morphology. Together our results reveal novel postmitotic functions of BOD1 as well as pathogenic mechanisms that strongly support a causative role of BOD1 deficiency in the aetiology of intellectual disability. Moreover, by demonstrating its requirement for cognitive function in humans and Drosophila we provide evidence for a conserved role of BOD1 in the development and maintenance of cognitive features

    High-throughput Analysis of Locomotor Behavior in the Drosophila Island Assay

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    Item does not contain fulltextAdvances in next-generation sequencing technologies contribute to the identification of (candidate) disease genes for movement disorders and other neurological diseases at an increasing speed. However, little is known about the molecular mechanisms that underlie these disorders. The genetic, molecular, and behavioral toolbox of Drosophila melanogaster makes this model organism particularly useful to characterize new disease genes and mechanisms in a high-throughput manner. Nevertheless, high-throughput screens require efficient and reliable assays that, ideally, are cost-effective and allow for the automatized quantification of traits relevant to these disorders. The island assay is a cost-effective and easily set-up method to evaluate Drosophila locomotor behavior. In this assay, flies are thrown onto a platform from a fixed height. This induces an innate motor response that enables the flies to escape from the platform within seconds. At present, quantitative analyses of filmed island assays are done manually, which is a laborious undertaking, particularly when performing large screens. This manuscript describes the "Drosophila Island Assay" and "Island Assay Analysis" algorithms for high-throughput, automated data processing and quantification of island assay data. In the setup, a simple webcam connected to a laptop collects an image series of the platform while the assay is performed. The "Drosophila Island Assay" algorithm developed for the open-source software Fiji processes these image series and quantifies, for each experimental condition, the number of flies on the platform over time. The "Island Assay Analysis" script, compatible with the free software R, was developed to automatically process the obtained data and to calculate whether treatments/genotypes are statistically different. This greatly improves the efficiency of the island assay and makes it a powerful readout for basic locomotion and flight behavior. It can thus be applied to large screens investigating fly locomotor ability, Drosophila models of movement disorders, and drug efficacy

    From Rare Copy Number Variants to Biological Processes in ADHD

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    Systematic phenomics analysis deconvolutes genes mutated in intellectual disability into biologically coherent modules

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    Intellectual disability (ID) disorders are genetically and phenotypically extremely heterogeneous. Can this complexity be depicted in a comprehensive way as a means of facilitating the understanding of ID disorders and their underlying biology? We provide a curated database of 746 currently known genes, mutations in which cause ID (ID-associated genes [ID-AGs]), classified according to ID manifestation and associated clinical features. Using this integrated resource, we show that ID-AGs are substantially enriched with co-expression, protein-protein interactions, and specific biological functions. Systematic identification of highly enriched functional themes and phenotypes revealed typical phenotype combinations characterizing process-defined groups of ID disorders, such as chromatin-related disorders and deficiencies in DNA repair. Strikingly, phenotype classification efficiently breaks down ID-AGs into subsets with significantly elevated biological coherence and predictive power. Custom-made functional Drosophila datasets revealed further characteristic phenotypes among ID-AGs and specific clinical classes. Our study and resource provide systematic insights into the molecular and clinical landscape of ID disorders, represent a significant step toward overcoming current limitations in ID research, and prove the utility of systematic human and cross-species phenomics analyses in highly heterogeneous genetic disorders
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