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      Rescue of oxytocin response and social behavior in a rodent model of autism

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          Abstract

          One of the most fundamental challenges in developing treatments for autism-spectrum disorders is the heterogeneity of the condition. More than one hundred genetic mutations confer high risk for autism, with each individual mutation accounting for only a small fraction of autism cases 13 . Subsets of risk genes can be grouped into functionally-related pathways, most prominently synaptic proteins, translational regulation, and chromatin modifications. To possibly circumvent this genetic complexity, recent therapeutic strategies have focused on the neuropeptides oxytocin and vasopressin 46 which regulate aspects of social behavior in mammals 7 . However, whether genetic risk factors might predispose to autism due to modification of oxytocinergic signaling remains largely unknown. Here, we report that an autism-associated mutation in the synaptic adhesion molecule neuroligin-3 ( Nlgn3) results in impaired oxytocin signaling in dopaminergic neurons and in altered social novelty responses in mice. Surprisingly, loss of Nlgn3 is accompanied by a disruption of translation homeostasis in the ventral tegmental area. Treatment of Nlgn3 KO mice with a novel, highly specific, brain-penetrant inhibitor of MAP-kinase interacting kinases resets mRNA translation and restores oxytocin and social novelty responses. Thus, this work identifies an unexpected convergence between the genetic autism risk factor Nlgn3, translational regulation, and oxytocinergic signaling. Focus on such common core plasticity elements might provide a pragmatic approach to reduce the heterogeneity of autism. Ultimately, this would allow for mechanism-based stratification of patient populations to increase the success of therapeutic interventions.

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          Is Open Access

          STRING v11: protein–protein association networks with increased coverage, supporting functional discovery in genome-wide experimental datasets

          Abstract Proteins and their functional interactions form the backbone of the cellular machinery. Their connectivity network needs to be considered for the full understanding of biological phenomena, but the available information on protein–protein associations is incomplete and exhibits varying levels of annotation granularity and reliability. The STRING database aims to collect, score and integrate all publicly available sources of protein–protein interaction information, and to complement these with computational predictions. Its goal is to achieve a comprehensive and objective global network, including direct (physical) as well as indirect (functional) interactions. The latest version of STRING (11.0) more than doubles the number of organisms it covers, to 5090. The most important new feature is an option to upload entire, genome-wide datasets as input, allowing users to visualize subsets as interaction networks and to perform gene-set enrichment analysis on the entire input. For the enrichment analysis, STRING implements well-known classification systems such as Gene Ontology and KEGG, but also offers additional, new classification systems based on high-throughput text-mining as well as on a hierarchical clustering of the association network itself. The STRING resource is available online at https://string-db.org/.
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            Is Open Access

            REVIGO Summarizes and Visualizes Long Lists of Gene Ontology Terms

            Outcomes of high-throughput biological experiments are typically interpreted by statistical testing for enriched gene functional categories defined by the Gene Ontology (GO). The resulting lists of GO terms may be large and highly redundant, and thus difficult to interpret. REVIGO is a Web server that summarizes long, unintelligible lists of GO terms by finding a representative subset of the terms using a simple clustering algorithm that relies on semantic similarity measures. Furthermore, REVIGO visualizes this non-redundant GO term set in multiple ways to assist in interpretation: multidimensional scaling and graph-based visualizations accurately render the subdivisions and the semantic relationships in the data, while treemaps and tag clouds are also offered as alternative views. REVIGO is freely available at http://revigo.irb.hr/.
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              De novo gene disruptions in children on the autistic spectrum.

              Exome sequencing of 343 families, each with a single child on the autism spectrum and at least one unaffected sibling, reveal de novo small indels and point substitutions, which come mostly from the paternal line in an age-dependent manner. We do not see significantly greater numbers of de novo missense mutations in affected versus unaffected children, but gene-disrupting mutations (nonsense, splice site, and frame shifts) are twice as frequent, 59 to 28. Based on this differential and the number of recurrent and total targets of gene disruption found in our and similar studies, we estimate between 350 and 400 autism susceptibility genes. Many of the disrupted genes in these studies are associated with the fragile X protein, FMRP, reinforcing links between autism and synaptic plasticity. We find FMRP-associated genes are under greater purifying selection than the remainder of genes and suggest they are especially dosage-sensitive targets of cognitive disorders. Copyright © 2012 Elsevier Inc. All rights reserved.
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                Author and article information

                Journal
                0410462
                Nature
                Nature
                Nature
                0028-0836
                1476-4687
                02 February 2021
                01 August 2020
                05 August 2020
                15 February 2021
                : 584
                : 7820
                : 252-256
                Affiliations
                [1 ]Biozentrum of the University of Basel, Klingelberstrasse 50-70, CH-4056 Basel, Switzerland
                [2 ]Department of Biomedicine, University of Basel, Pestalozzistrasse 20, 4056 Basel, Switzerland
                [3 ]Centre for Psychiatric Neuroscience, Department of Psychiatry, Lausanne University Hospital, CH-1015, Lausanne, Switzerland
                [4 ] Neuroscience Division, School of Biosciences, Cardiff University, Cardiff CF10 3AX, United Kingdom
                [5 ]Experimental Drug Development Centre, 10 Biopolis Rd, Chromos #05-01, Singapore 138670
                Author notes
                Corresponding author: Correspondence to Peter Scheiffele, peter.scheiffele@ 123456unibas.ch
                [6]

                Present address: Stalicla, Avenue de Secheron 15, 1202 Genève, Switzerland

                Article
                EMS114606
                10.1038/s41586-020-2563-7
                7116741
                32760004
                3e281ff4-5641-450b-902a-cac696aea8e3

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