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      Aberrant activation of the human sex-determining gene in early embryonic development results in postnatal growth retardation and lethality in mice

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      Scientific Reports
      Nature Publishing Group UK

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          Abstract

          Sexual dimorphisms are prevalent in development, physiology and diseases in humans. Currently, the contributions of the genes on the male-specific region of the Y chromosome (MSY) in these processes are uncertain. Using a transgene activation system, the human sex-determining gene hSRY is activated in the single-cell embryos of the mouse. Pups with hSRY activated (hSRY ON) are born of similar sizes as those of non-activated controls. However, they retard significantly in postnatal growth and development and all die of multi-organ failure before two weeks of age. Pathological and molecular analyses indicate that hSRY ON pups lack innate suckling activities, and develop fatty liver disease, arrested alveologenesis in the lung, impaired neurogenesis in the brain and occasional myocardial fibrosis and minimized thymus development. Transcriptome analysis shows that, in addition to those unique to the respective organs, various cell growth and survival pathways and functions are differentially affected in the transgenic mice. These observations suggest that ectopic activation of a Y-located SRY gene could exert male-specific effects in development and physiology of multiple organs, thereby contributing to sexual dimorphisms in normal biological functions and disease processes in affected individuals.

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          Most cited references65

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          Preparing for the first breath: genetic and cellular mechanisms in lung development.

          The mammalian respiratory system--the trachea and the lungs--arises from the anterior foregut through a sequence of morphogenetic events involving reciprocal endodermal-mesodermal interactions. The lung itself consists of two highly branched, tree-like systems--the airways and the vasculature--that develop in a coordinated way from the primary bud stage to the generation of millions of alveolar gas exchange units. We are beginning to understand some of the molecular and cellular mechanisms that underlie critical processes such as branching morphogenesis, vascular development, and the differentiation of multipotent progenitor populations. Nevertheless, many gaps remain in our knowledge, the filling of which is essential for understanding respiratory disorders, congenital defects in human neonates, and how the disruption of morphogenetic programs early in lung development can lead to deficiencies that persist throughout life. (c) 2010 Elsevier Inc. All rights reserved.
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            Sex differences in the brain: implications for explaining autism.

            Empathizing is the capacity to predict and to respond to the behavior of agents (usually people) by inferring their mental states and responding to these with an appropriate emotion. Systemizing is the capacity to predict and to respond to the behavior of nonagentive deterministic systems by analyzing input-operation-output relations and inferring the rules that govern such systems. At a population level, females are stronger empathizers and males are stronger systemizers. The "extreme male brain" theory posits that autism represents an extreme of the male pattern (impaired empathizing and enhanced systemizing). Here we suggest that specific aspects of autistic neuroanatomy may also be extremes of typical male neuroanatomy.
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              TCC: an R package for comparing tag count data with robust normalization strategies

              Background Differential expression analysis based on “next-generation” sequencing technologies is a fundamental means of studying RNA expression. We recently developed a multi-step normalization method (called TbT) for two-group RNA-seq data with replicates and demonstrated that the statistical methods available in four R packages (edgeR, DESeq, baySeq, and NBPSeq) together with TbT can produce a well-ranked gene list in which true differentially expressed genes (DEGs) are top-ranked and non-DEGs are bottom ranked. However, the advantages of the current TbT method come at the cost of a huge computation time. Moreover, the R packages did not have normalization methods based on such a multi-step strategy. Results TCC (an acronym for Tag Count Comparison) is an R package that provides a series of functions for differential expression analysis of tag count data. The package incorporates multi-step normalization methods, whose strategy is to remove potential DEGs before performing the data normalization. The normalization function based on this DEG elimination strategy (DEGES) includes (i) the original TbT method based on DEGES for two-group data with or without replicates, (ii) much faster methods for two-group data with or without replicates, and (iii) methods for multi-group comparison. TCC provides a simple unified interface to perform such analyses with combinations of functions provided by edgeR, DESeq, and baySeq. Additionally, a function for generating simulation data under various conditions and alternative DEGES procedures consisting of functions in the existing packages are provided. Bioinformatics scientists can use TCC to evaluate their methods, and biologists familiar with other R packages can easily learn what is done in TCC. Conclusion DEGES in TCC is essential for accurate normalization of tag count data, especially when up- and down-regulated DEGs in one of the samples are extremely biased in their number. TCC is useful for analyzing tag count data in various scenarios ranging from unbiased to extremely biased differential expression. TCC is available at http://www.iu.a.u-tokyo.ac.jp/~kadota/TCC/ and will appear in Bioconductor (http://bioconductor.org/) from ver. 2.13.
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                Author and article information

                Contributors
                chris.lau@ucsf.edu
                Journal
                Sci Rep
                Sci Rep
                Scientific Reports
                Nature Publishing Group UK (London )
                2045-2322
                23 June 2017
                23 June 2017
                2017
                : 7
                : 4113
                Affiliations
                ISNI 0000 0001 2297 6811, GRID grid.266102.1, Department of Medicine, VA Medical Center, and Institute for Human Genetics, , University of California, San Francisco, ; San Francisco, California USA
                Article
                4117
                10.1038/s41598-017-04117-6
                5482865
                28646221
                ac188091-bc14-4850-9460-e4436386e61d
                © The Author(s) 2017

                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/.

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                : 8 February 2017
                : 9 May 2017
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