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      Transcriptome Analysis in Hippocampus of Rats Prenatally Exposed to Valproic Acid and Effects of Intranasal Treatment of Oxytocin

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          Abstract

          Autism spectrum disorder (ASD) is a heterogeneous disorder characterized by repetitive behaviors and social impairments, often accompanied by learning disabilities. It has been documented that the neuropeptide oxytocin (OXT) ameliorates core symptoms in patients with ASD. We recently reported that chronic administration of intranasal OXT reversed social and learning impairments in prenatally valproic acid (VPA)-exposed rats. However, the underlying molecular mechanisms remain unclear. Here, we explored molecular alterations in the hippocampus of rats and the effects of chronic administration of intranasal OXT (12 μg/kg/d). Microarray analyses revealed that prenatal VPA exposure altered gene expression, a part of which is suggested as a candidate in ASD and is involved in key features including memory, developmental processes, and epilepsy. OXT partly improved the expression of these genes, which were predicted to interact with those involved in social behaviors and hippocampal-dependent memory. Collectively, the present study documented molecular profiling in the hippocampus related to ASD and improvement by chronic treatment with OXT.

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          Most cited references73

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          Cytoscape: a software environment for integrated models of biomolecular interaction networks.

          Cytoscape is an open source software project for integrating biomolecular interaction networks with high-throughput expression data and other molecular states into a unified conceptual framework. Although applicable to any system of molecular components and interactions, Cytoscape is most powerful when used in conjunction with large databases of protein-protein, protein-DNA, and genetic interactions that are increasingly available for humans and model organisms. Cytoscape's software Core provides basic functionality to layout and query the network; to visually integrate the network with expression profiles, phenotypes, and other molecular states; and to link the network to databases of functional annotations. The Core is extensible through a straightforward plug-in architecture, allowing rapid development of additional computational analyses and features. Several case studies of Cytoscape plug-ins are surveyed, including a search for interaction pathways correlating with changes in gene expression, a study of protein complexes involved in cellular recovery to DNA damage, inference of a combined physical/functional interaction network for Halobacterium, and an interface to detailed stochastic/kinetic gene regulatory models.
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            limma powers differential expression analyses for RNA-sequencing and microarray studies

            limma is an R/Bioconductor software package that provides an integrated solution for analysing data from gene expression experiments. It contains rich features for handling complex experimental designs and for information borrowing to overcome the problem of small sample sizes. Over the past decade, limma has been a popular choice for gene discovery through differential expression analyses of microarray and high-throughput PCR data. The package contains particularly strong facilities for reading, normalizing and exploring such data. Recently, the capabilities of limma have been significantly expanded in two important directions. First, the package can now perform both differential expression and differential splicing analyses of RNA sequencing (RNA-seq) data. All the downstream analysis tools previously restricted to microarray data are now available for RNA-seq as well. These capabilities allow users to analyse both RNA-seq and microarray data with very similar pipelines. Second, the package is now able to go past the traditional gene-wise expression analyses in a variety of ways, analysing expression profiles in terms of co-regulated sets of genes or in terms of higher-order expression signatures. This provides enhanced possibilities for biological interpretation of gene expression differences. This article reviews the philosophy and design of the limma package, summarizing both new and historical features, with an emphasis on recent enhancements and features that have not been previously described.
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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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                Author and article information

                Contributors
                Journal
                Front Psychiatry
                Front Psychiatry
                Front. Psychiatry
                Frontiers in Psychiatry
                Frontiers Media S.A.
                1664-0640
                30 March 2022
                2022
                : 13
                : 859198
                Affiliations
                [1] 1Department of Pharmacology, Graduate School of Pharmaceutical Sciences, Tohoku University , Sendai, Japan
                [2] 2Division of Neurofunctional Genomics, Department of Immunobiology and Neuroscience, Medical Institute of Bioregulation, Kyushu University , Fukuoka, Japan
                Author notes

                Edited by: Juehua Yu, The First Affiliated Hospital of Kunming Medical University, China

                Reviewed by: Jan Bakos, Biomedical Research Center, Slovak Academy of Sciences, Slovakia; Chan Young Shin, Konkuk University, South Korea

                *Correspondence: Kohji Fukunaga, kfukunaga@ 123456tohoku.ac.jp

                This article was submitted to Autism, a section of the journal Frontiers in Psychiatry

                Article
                10.3389/fpsyt.2022.859198
                9005872
                35432011
                7b4c5b7e-1fdc-46dd-a169-b9ccc9a1dc63
                Copyright © 2022 Matsuo, Shinoda, Abolhassani, Nakabeppu and Fukunaga.

                This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

                History
                : 21 January 2022
                : 04 March 2022
                Page count
                Figures: 3, Tables: 1, Equations: 0, References: 74, Pages: 9, Words: 6231
                Funding
                Funded by: Japan Society for the Promotion of Science, doi 10.13039/501100001691;
                Award ID: 19H03406
                Award ID: 18J20651
                Categories
                Psychiatry
                Original Research

                Clinical Psychology & Psychiatry
                autism spectrum disorders,hippocampus,oxytocin,transcriptome analysis,valproic acid

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