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      Foxp1 regulation of neonatal vocalizations via cortical development

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          Abstract

          Usui et al. show that deletion of Foxp1 in the developing forebrain leads to impairments in neonatal vocalizations as well as neocortical cytoarchitectonic alterations via neuronal positioning and migration. Sumoylation of Foxp1 affects neuronal differentiation and migration in the developing neocortex.

          Abstract

          The molecular mechanisms driving brain development at risk in autism spectrum disorders (ASDs) remain mostly unknown. Previous studies have implicated the transcription factor FOXP1 in both brain development and ASD pathophysiology. However, the specific molecular pathways both upstream of and downstream from FOXP1 are not fully understood. To elucidate the contribution of FOXP1-mediated signaling to brain development and, in particular, neocortical development, we generated forebrain-specific Foxp1 conditional knockout mice. We show that deletion of Foxp1 in the developing forebrain leads to impairments in neonatal vocalizations as well as neocortical cytoarchitectonic alterations via neuronal positioning and migration. Using a genomics approach, we identified the transcriptional networks regulated by Foxp1 in the developing neocortex and found that such networks are enriched for downstream targets involved in neurogenesis and neuronal migration. We also uncovered mechanistic insight into Foxp1 function by demonstrating that sumoylation of Foxp1 during embryonic brain development is necessary for mediating proper interactions between Foxp1 and the NuRD complex. Furthermore, we demonstrated that sumoylation of Foxp1 affects neuronal differentiation and migration in the developing neocortex. Together, these data provide critical mechanistic insights into the function of FOXP1 in the developing neocortex and may reveal molecular pathways at risk in ASD.

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          Most cited references102

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          Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2

          In comparative high-throughput sequencing assays, a fundamental task is the analysis of count data, such as read counts per gene in RNA-seq, for evidence of systematic changes across experimental conditions. Small replicate numbers, discreteness, large dynamic range and the presence of outliers require a suitable statistical approach. We present DESeq2, a method for differential analysis of count data, using shrinkage estimation for dispersions and fold changes to improve stability and interpretability of estimates. This enables a more quantitative analysis focused on the strength rather than the mere presence of differential expression. The DESeq2 package is available at http://www.bioconductor.org/packages/release/bioc/html/DESeq2.html. Electronic supplementary material The online version of this article (doi:10.1186/s13059-014-0550-8) contains supplementary material, which is available to authorized users.
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            Trimmomatic: a flexible trimmer for Illumina sequence data

            Motivation: Although many next-generation sequencing (NGS) read preprocessing tools already existed, we could not find any tool or combination of tools that met our requirements in terms of flexibility, correct handling of paired-end data and high performance. We have developed Trimmomatic as a more flexible and efficient preprocessing tool, which could correctly handle paired-end data. Results: The value of NGS read preprocessing is demonstrated for both reference-based and reference-free tasks. Trimmomatic is shown to produce output that is at least competitive with, and in many cases superior to, that produced by other tools, in all scenarios tested. Availability and implementation: Trimmomatic is licensed under GPL V3. It is cross-platform (Java 1.5+ required) and available at http://www.usadellab.org/cms/index.php?page=trimmomatic Contact: usadel@bio1.rwth-aachen.de Supplementary information: Supplementary data are available at Bioinformatics online.
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              STAR: ultrafast universal RNA-seq aligner.

              Accurate alignment of high-throughput RNA-seq data is a challenging and yet unsolved problem because of the non-contiguous transcript structure, relatively short read lengths and constantly increasing throughput of the sequencing technologies. Currently available RNA-seq aligners suffer from high mapping error rates, low mapping speed, read length limitation and mapping biases. To align our large (>80 billon reads) ENCODE Transcriptome RNA-seq dataset, we developed the Spliced Transcripts Alignment to a Reference (STAR) software based on a previously undescribed RNA-seq alignment algorithm that uses sequential maximum mappable seed search in uncompressed suffix arrays followed by seed clustering and stitching procedure. STAR outperforms other aligners by a factor of >50 in mapping speed, aligning to the human genome 550 million 2 × 76 bp paired-end reads per hour on a modest 12-core server, while at the same time improving alignment sensitivity and precision. In addition to unbiased de novo detection of canonical junctions, STAR can discover non-canonical splices and chimeric (fusion) transcripts, and is also capable of mapping full-length RNA sequences. Using Roche 454 sequencing of reverse transcription polymerase chain reaction amplicons, we experimentally validated 1960 novel intergenic splice junctions with an 80-90% success rate, corroborating the high precision of the STAR mapping strategy. STAR is implemented as a standalone C++ code. STAR is free open source software distributed under GPLv3 license and can be downloaded from http://code.google.com/p/rna-star/.
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                Author and article information

                Journal
                Genes Dev
                Genes Dev
                genesdev
                genesdev
                GAD
                Genes & Development
                Cold Spring Harbor Laboratory Press
                0890-9369
                1549-5477
                15 October 2017
                : 31
                : 20
                : 2039-2055
                Affiliations
                [1 ]Department of Neuroscience, University of Texas Southwestern Medical Center, Dallas, Texas 75390, USA;
                [2 ]Division of Development of Mental Functions, Research Center for Child Mental Development, University of Fukui, Fukui 910-1193, Japan;
                [3 ]Division of Developmental Higher Brain Functions, Department of Child Development, United Graduate School of Child Development, Osaka University, Kanazawa University, Hamamatsu University School of Medicine, Chiba University, and University of Fukui, Osaka 565-0871, Japan;
                [4 ]Mouse Imaging Centre (MICe), Hospital for Sick Children, Toronto, Ontario M5S 1A1, Canada;
                [5 ]Project for Schizophrenia Research, Department of Psychiatry and Behavioral Sciences, Tokyo Metropolitan Institute of Medical Science, Tokyo 156-8506, Japan;
                [6 ]Department of Medical Biophysics, University of Toronto, Toronto, Ontario M5S 1A1, Canada
                Author notes
                [7]

                Present Address: Department of Molecular and Cell Biology, University of California at Berkeley, Berkeley, CA 94720, USA.

                Article
                8711660
                10.1101/gad.305037.117
                5733496
                29138280
                deee7793-0f25-479f-9684-3756bf300980
                © 2017 Usui et al.; Published by Cold Spring Harbor Laboratory Press

                This article is distributed exclusively by Cold Spring Harbor Laboratory Press for the first six months after the full-issue publication date (see http://genesdev.cshlp.org/site/misc/terms.xhtml). After six months, it is available under a Creative Commons License (Attribution-NonCommercial 4.0 International), as described at http://creativecommons.org/licenses/by-nc/4.0/.

                History
                : 19 July 2017
                : 25 October 2017
                Page count
                Pages: 17
                Funding
                Funded by: Japan Society for the Promotion of Science Program for Advancing Strategic International Networks to Accelerate the Circulation of Talented Researchers
                Award ID: S2603
                Funded by: National Science Foundation , open-funder-registry 10.13039/100000001;
                Award ID: 2013162469
                Funded by: Howard Hughes Medical Institute Med , open-funder-registry 10.13039/100000011;
                Funded by: National Institutes of Health , open-funder-registry 10.13039/100000002;
                Award ID: TL1TR001104
                Award ID: T32GM109776
                Funded by: Ontario Brain Institute, Brain Canada , open-funder-registry 10.13039/100008914;
                Funded by: Canadian Institute for Health Research
                Funded by: Simons Foundation , open-funder-registry 10.13039/100000893;
                Award ID: SFARI 401220
                Funded by: NIH , open-funder-registry 10.13039/100000002;
                Award ID: DC014702
                Award ID: MH102603
                Categories
                Research Paper

                autism,behavior,neocortex,neurogenomics,neuronal migration,sumoylation

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