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      Dysfunction of NMDA receptors in neuronal models of an autism spectrum disorder patient with a DSCAM mutation and in Dscam-knockout mice

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          Abstract

          Heterogeneity in the etiopathology of autism spectrum disorders (ASD) limits the development of generic remedies, requires individualistic and patient-specific research. Recent progress in human-induced pluripotent stem cell (iPSC) technology provides a novel platform for modeling ASDs for studying complex neuronal phenotypes. In this study, we generated telencephalic induced neuronal (iN) cells from iPSCs derived from an ASD patient with a heterozygous point mutation in the DSCAM gene. The mRNA of DSCAM and the density of DSCAM in dendrites were significantly decreased in ASD compared to control iN cells. RNA sequencing analysis revealed that several synaptic function-related genes including NMDA receptor subunits were downregulated in ASD iN cells. Moreover, NMDA receptor (R)-mediated currents were significantly reduced in ASD compared to control iN cells. Normal NMDA-R-mediated current levels were rescued by expressing wild-type DSCAM in ASD iN cells, and reduced currents were observed by truncated DSCAM expression in control iN cells. shRNA-mediated DSCAM knockdown in control iN cells resulted in the downregulation of an NMDA-R subunit, which was rescued by the overexpression of shRNA-resistant DSCAM. Furthermore, DSCAM was co-localized with NMDA-R components in the dendritic spines of iN cells whereas their co-localizations were significantly reduced in ASD iN cells. Levels of phospho-ERK1/2 were significantly lower in ASD iN cells, suggesting a potential mechanism. A neural stem cell-specific Dscam heterozygous knockout mouse model, showing deficits in social interaction and social memory with reduced NMDA-R currents. These data suggest that DSCAM mutation causes pathological symptoms of ASD by dysregulating NMDA-R function.

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          Metascape provides a biologist-oriented resource for the analysis of systems-level datasets

          A critical component in the interpretation of systems-level studies is the inference of enriched biological pathways and protein complexes contained within OMICs datasets. Successful analysis requires the integration of a broad set of current biological databases and the application of a robust analytical pipeline to produce readily interpretable results. Metascape is a web-based portal designed to provide a comprehensive gene list annotation and analysis resource for experimental biologists. In terms of design features, Metascape combines functional enrichment, interactome analysis, gene annotation, and membership search to leverage over 40 independent knowledgebases within one integrated portal. Additionally, it facilitates comparative analyses of datasets across multiple independent and orthogonal experiments. Metascape provides a significantly simplified user experience through a one-click Express Analysis interface to generate interpretable outputs. Taken together, Metascape is an effective and efficient tool for experimental biologists to comprehensively analyze and interpret OMICs-based studies in the big data era.
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            Differential expression analysis for sequence count data

            High-throughput sequencing assays such as RNA-Seq, ChIP-Seq or barcode counting provide quantitative readouts in the form of count data. To infer differential signal in such data correctly and with good statistical power, estimation of data variability throughout the dynamic range and a suitable error model are required. We propose a method based on the negative binomial distribution, with variance and mean linked by local regression and present an implementation, DESeq, as an R/Bioconductor package.
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              Large-Scale Exome Sequencing Study Implicates Both Developmental and Functional Changes in the Neurobiology of Autism

              We present the largest exome sequencing study of autism spectrum disorder (ASD) to date (n = 35,584 total samples, 11,986 with ASD). Using an enhanced analytical framework to integrate de novo and case-control rare variation, we identify 102 risk genes at a false discovery rate of 0.1 or less. Of these genes, 49 show higher frequencies of disruptive de novo variants in individuals ascertained to have severe neurodevelopmental delay, whereas 53 show higher frequencies in individuals ascertained to have ASD; comparing ASD cases with mutations in these groups reveals phenotypic differences. Expressed early in brain development, most risk genes have roles in regulation of gene expression or neuronal communication (i.e., mutations effect neurodevelopmental and neurophysiological changes), and 13 fall within loci recurrently hit by copy number variants. In cells from the human cortex, expression of risk genes is enriched in excitatory and inhibitory neuronal lineages, consistent with multiple paths to an excitatory-inhibitory imbalance underlying ASD.
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                Author and article information

                Contributors
                irislkm@knu.ac.kr
                leeja@hnu.kr
                kaang@snu.ac.kr
                Journal
                Mol Psychiatry
                Mol Psychiatry
                Molecular Psychiatry
                Nature Publishing Group UK (London )
                1359-4184
                1476-5578
                12 July 2021
                12 July 2021
                2021
                : 26
                : 12
                : 7538-7549
                Affiliations
                [1 ]GRID grid.31501.36, ISNI 0000 0004 0470 5905, School of Biological Sciences, Seoul National University, ; Seoul, 08826 South Korea
                [2 ]GRID grid.410899.d, ISNI 0000 0004 0533 4755, Department of Pharmacology, , Wonkwang University School of Medicine, ; Jeonbuk, 54538 South Korea
                [3 ]GRID grid.411970.a, ISNI 0000 0004 0532 6499, Department of Biotechnology and Biological Sciences, , Hannam University, ; Daejeon, 34430 South Korea
                [4 ]GRID grid.31501.36, ISNI 0000 0004 0470 5905, Interdisciplinary Program in Bioinformatics, Seoul National University, ; Seoul, 08826 South Korea
                [5 ]GRID grid.258803.4, ISNI 0000 0001 0661 1556, Department of Anatomy, , School of Medicine, Kyungpook National University, ; Daegu, 41944 South Korea
                [6 ]GRID grid.15444.30, ISNI 0000 0004 0470 5454, Department of Pharmacology, , Yonsei University College of Medicine, ; Seoul, 03722 South Korea
                [7 ]GRID grid.289247.2, ISNI 0000 0001 2171 7818, Department of Life and Nanopharmaceutical Sciences, , Department of Oral Microbiology, Kyung Hee University School of Dentistry, ; Seoul, 02447 South Korea
                [8 ]GRID grid.31501.36, ISNI 0000 0004 0470 5905, Department of Physiology, , Biomedical Sciences, Neuroscience Research Institute, Seoul National University College of Medicine, ; Seoul, 03080 South Korea
                [9 ]GRID grid.258803.4, ISNI 0000 0001 0661 1556, Department of Pediatrics, , School of Medicine, Kyungpook National University, ; Daegu, 41944 South Korea
                [10 ]GRID grid.443020.1, ISNI 0000 0001 2295 3329, Present Address: Department of Pharmaceutical Sciences, , School of Health and Life Sciences, North South University, ; Dhaka-1229, Bangladesh
                Author information
                http://orcid.org/0000-0003-3407-0632
                http://orcid.org/0000-0002-5425-4212
                http://orcid.org/0000-0002-6757-8371
                http://orcid.org/0000-0001-7593-9707
                Article
                1216
                10.1038/s41380-021-01216-9
                8873012
                34253863
                c2eff319-ddf2-485e-a7d3-8c83273109ff
                © The Author(s) 2021

                Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.

                History
                : 7 March 2020
                : 15 June 2021
                : 25 June 2021
                Funding
                Funded by: FundRef https://doi.org/10.13039/501100003725, National Research Foundation of Korea (NRF);
                Award ID: NRF-2012R1A3A1050385
                Award ID: NRF-2016R1D1A1B03931525
                Award ID: NRF-2016R1D1A1B03931525
                Award ID: NRF-2012R1A3A1050385
                Award ID: NRF-2012R1A3A1050385
                Award ID: NRF-2012R1A3A1050385
                Award ID: NRF-2012R1A3A1050385
                Award ID: NRF-2012R1A3A1050385
                Award ID: NRF-2012R1A3A1050385
                Award ID: NRF-2012R1A3A1050385
                Award ID: NRF-2012R1A3A1050385
                Award ID: NRF-2012R1A3A1050385
                Award ID: NRF-2012R1A3A1050385
                Award ID: NRF-2012R1A3A1050385
                Award ID: NRF-2012R1A3A1050385
                Award ID: NRF-2012R1A3A1050385
                Award ID: NRF-2012R1A3A1050385
                Award ID: NRF-2017R1A3A1078210
                Award ID: NRF- 2019R1F1A1063932
                Award ID: NRF-2017R1D1A3B03030972
                Award Recipient :
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                © The Author(s), under exclusive licence to Springer Nature Limited 2021

                Molecular medicine
                stem cells,autism spectrum disorders
                Molecular medicine
                stem cells, autism spectrum disorders

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