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      Neuromolecular responses to social challenge: common mechanisms across mouse, stickleback fish, and honey bee.

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          Abstract

          Certain complex phenotypes appear repeatedly across diverse species due to processes of evolutionary conservation and convergence. In some contexts like developmental body patterning, there is increased appreciation that common molecular mechanisms underlie common phenotypes; these molecular mechanisms include highly conserved genes and networks that may be modified by lineage-specific mutations. However, the existence of deeply conserved mechanisms for social behaviors has not yet been demonstrated. We used a comparative genomics approach to determine whether shared neuromolecular mechanisms could underlie behavioral response to territory intrusion across species spanning a broad phylogenetic range: house mouse (Mus musculus), stickleback fish (Gasterosteus aculeatus), and honey bee (Apis mellifera). Territory intrusion modulated similar brain functional processes in each species, including those associated with hormone-mediated signal transduction and neurodevelopment. Changes in chromosome organization and energy metabolism appear to be core, conserved processes involved in the response to territory intrusion. We also found that several homologous transcription factors that are typically associated with neural development were modulated across all three species, suggesting that shared neuronal effects may involve transcriptional cascades of evolutionarily conserved genes. Furthermore, immunohistochemical analyses of a subset of these transcription factors in mouse again implicated modulation of energy metabolism in the behavioral response. These results provide support for conserved genetic "toolkits" that are used in independent evolutions of the response to social challenge in diverse taxa.

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          Most cited references62

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          The genetic causes of convergent evolution.

          The evolution of phenotypic similarities between species, known as convergence, illustrates that populations can respond predictably to ecological challenges. Convergence often results from similar genetic changes, which can emerge in two ways: the evolution of similar or identical mutations in independent lineages, which is termed parallel evolution; and the evolution in independent lineages of alleles that are shared among populations, which I call collateral genetic evolution. Evidence for parallel and collateral evolution has been found in many taxa, and an emerging hypothesis is that they result from the fact that mutations in some genetic targets minimize pleiotropic effects while simultaneously maximizing adaptation. If this proves correct, then the molecular changes underlying adaptation might be more predictable than has been appreciated previously.
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            Gene regulatory networks in the evolution and development of the heart.

            Eric Olson (2006)
            The heart, an ancient organ and the first to form and function during embryogenesis, evolved by the addition of new structures and functions to a primitive pump. Heart development is controlled by an evolutionarily conserved network of transcription factors that connect signaling pathways with genes for muscle growth, patterning, and contractility. During evolution, this ancestral gene network was expanded through gene duplication and co-option of additional networks. Mutations in components of the cardiac gene network cause congenital heart disease, the most common human birth defect. The consequences of such mutations reveal the logic of organogenesis and the evolutionary origins of morphological complexity.
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              Is Open Access

              OrthoDB: a hierarchical catalog of animal, fungal and bacterial orthologs

              The concept of orthology provides a foundation for formulating hypotheses on gene and genome evolution, and thus forms the cornerstone of comparative genomics, phylogenomics and metagenomics. We present the update of OrthoDB—the hierarchical catalog of orthologs (http://www.orthodb.org). From its conception, OrthoDB promoted delineation of orthologs at varying resolution by explicitly referring to the hierarchy of species radiations, now also adopted by other resources. The current release provides comprehensive coverage of animals and fungi representing 252 eukaryotic species, and is now extended to prokaryotes with the inclusion of 1115 bacteria. Functional annotations of orthologous groups are provided through mapping to InterPro, GO, OMIM and model organism phenotypes, with cross-references to major resources including UniProt, NCBI and FlyBase. Uniquely, OrthoDB provides computed evolutionary traits of orthologs, such as gene duplicability and loss profiles, divergence rates, sibling groups, and now extended with exon–intron architectures, syntenic orthologs and parent–child trees. The interactive web interface allows navigation along the species phylogenies, complex queries with various identifiers, annotation keywords and phrases, as well as with gene copy-number profiles and sequence homology searches. With the explosive growth of available data, OrthoDB also provides mapping of newly sequenced genomes and transcriptomes to the current orthologous groups.
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                Author and article information

                Journal
                Proc. Natl. Acad. Sci. U.S.A.
                Proceedings of the National Academy of Sciences of the United States of America
                1091-6490
                0027-8424
                Dec 16 2014
                : 111
                : 50
                Affiliations
                [1 ] Institute for Genomic Biology, Departments of Entomology, Neuroscience Program, Department of Entomology, The Pennsylvania State University, University Park, PA 16802; and ccr22@illinois.edu generobi@illinois.edu ljstubbs@illinois.edu.
                [2 ] Institute for Genomic Biology, Illinois Informatics Institute.
                [3 ] Institute for Genomic Biology, Center for Biophysics and Computational Biology, and.
                [4 ] Institute for Genomic Biology, Cell and Developmental Biology.
                [5 ] Institute for Genomic Biology, Departments of Entomology.
                [6 ] Institute for Genomic Biology, Neuroscience Program.
                [7 ] Institute for Genomic Biology, Genomics Core, Lerner Research Institute, The Cleveland Clinic, Cleveland, OH 44195.
                [8 ] Institute for Genomic Biology, Neuroscience Program, Animal Biology, Program in Ecology, Evolution, and Conservation Biology, University of Illinois at Urbana-Champaign, Urbana, IL 61801;
                [9 ] Institute for Genomic Biology, Bioengineering, and.
                [10 ] Institute for Genomic Biology, Departments of Entomology, Computer Science.
                [11 ] Institute for Genomic Biology, Departments of Entomology, Neuroscience Program, Program in Ecology, Evolution, and Conservation Biology, University of Illinois at Urbana-Champaign, Urbana, IL 61801; ccr22@illinois.edu generobi@illinois.edu ljstubbs@illinois.edu.
                [12 ] Institute for Genomic Biology, Neuroscience Program, Cell and Developmental Biology, ccr22@illinois.edu generobi@illinois.edu ljstubbs@illinois.edu.
                Article
                1420369111
                10.1073/pnas.1420369111
                25453090
                1f5710ed-24dc-4b9d-a5a6-fc91dbdccd9c
                History

                NF-κB signaling,aggression,brain metabolism,genetic hotspot

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