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      Genomic Analyses Reveal Demographic History and Temperate Adaptation of the Newly Discovered Honey Bee Subspecies Apis mellifera sinisxinyuan n. ssp

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          Abstract

          Studying the genetic signatures of climate-driven selection can produce insights into local adaptation and the potential impacts of climate change on populations. The honey bee ( Apis mellifera) is an interesting species to study local adaptation because it originated in tropical/subtropical climatic regions and subsequently spread into temperate regions. However, little is known about the genetic basis of its adaptation to temperate climates. Here, we resequenced the whole genomes of ten individual bees from a newly discovered population in temperate China and downloaded resequenced data from 35 individuals from other populations. We found that the new population is an undescribed subspecies in the M-lineage of A. mellifera ( Apis mellifera sinisxinyuan). Analyses of population history show that long-term global temperature has strongly influenced the demographic history of A. m. sinisxinyuan and its divergence from other subspecies. Further analyses comparing temperate and tropical populations identified several candidate genes related to fat body and the Hippo signaling pathway that are potentially involved in adaptation to temperate climates. Our results provide insights into the demographic history of the newly discovered A. m. sinisxinyuan, as well as the genetic basis of adaptation of A. mellifera to temperate climates at the genomic level. These findings will facilitate the selective breeding of A. mellifera to improve the survival of overwintering colonies.

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          Most cited references36

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          Gene Ontology: tool for the unification of biology

          Genomic sequencing has made it clear that a large fraction of the genes specifying the core biological functions are shared by all eukaryotes. Knowledge of the biological role of such shared proteins in one organism can often be transferred to other organisms. The goal of the Gene Ontology Consortium is to produce a dynamic, controlled vocabulary that can be applied to all eukaryotes even as knowledge of gene and protein roles in cells is accumulating and changing. To this end, three independent ontologies accessible on the World-Wide Web (http://www.geneontology.org) are being constructed: biological process, molecular function and cellular component.
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            Hippo signaling: growth control and beyond.

            The Hippo pathway has emerged as a conserved signaling pathway that is essential for the proper regulation of organ growth in Drosophila and vertebrates. Although the mechanisms of signal transduction of the core kinases Hippo/Mst and Warts/Lats are relatively well understood, less is known about the upstream inputs of the pathway and about the downstream cellular and developmental outputs. Here, we review recently discovered mechanisms that contribute to the dynamic regulation of Hippo signaling during Drosophila and vertebrate development. We also discuss the expanding diversity of Hippo signaling functions during development, discoveries that shed light on a complex regulatory system and provide exciting new insights into the elusive mechanisms that regulate organ growth and regeneration.
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              Estimation of individual admixture: analytical and study design considerations.

              The genome of an admixed individual represents a mixture of alleles from different ancestries. In the United States, the two largest minority groups, African-Americans and Hispanics, are both admixed. An understanding of the admixture proportion at an individual level (individual admixture, or IA) is valuable for both population geneticists and epidemiologists who conduct case-control association studies in these groups. Here we present an extension of a previously described frequentist (maximum likelihood or ML) approach to estimate individual admixture that allows for uncertainty in ancestral allele frequencies. We compare this approach both to prior partial likelihood based methods as well as more recently described Bayesian MCMC methods. Our full ML method demonstrates increased robustness when compared to an existing partial ML approach. Simulations also suggest that this frequentist estimator achieves similar efficiency, measured by the mean squared error criterion, as Bayesian methods but requires just a fraction of the computational time to produce point estimates, allowing for extensive analysis (e.g., simulations) not possible by Bayesian methods. Our simulation results demonstrate that inclusion of ancestral populations or their surrogates in the analysis is required by any method of IA estimation to obtain reasonable results. (c) 2005 Wiley-Liss, Inc.
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                Author and article information

                Journal
                Mol Biol Evol
                Mol. Biol. Evol
                molbev
                molbiolevol
                Molecular Biology and Evolution
                Oxford University Press
                0737-4038
                1537-1719
                May 2016
                27 January 2016
                27 January 2016
                : 33
                : 5
                : 1337-1348
                Affiliations
                1Institute of Apicultural Research, Chinese Academy of Agricultural Sciences, Beijing, China
                2Key Laboratory of Pollinating Insect Biology, Ministry of Agriculture, Beijing, China
                3Novogene Bioinformatics Institute, Beijing, China
                4Apiculture Management Center of Xinjiang Uygur Autonomous Region, Urumqi, Xinjiang, China
                5Peking-Tsinghua Center for Life Sciences, Biodynamic Optical Imaging Center (BIOPIC) and School of Life Sciences, Peking University, Beijing, China
                Author notes
                [†]

                These authors contributed equally to this work.

                *Corresponding author: E-mail: shiweibri@ 123456126.com .

                Associate editor: Michael Rosenberg

                Article
                msw017
                10.1093/molbev/msw017
                4839221
                26823447
                0f413719-ca78-43f3-ac36-3230845e3eb3
                © The Author 2016. Published by Oxford University Press on behalf of the Society for Molecular Biology and Evolution.

                This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License ( http://creativecommons.org/licenses/by-nc/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial re-use, please contact journals.permissions@oup.com

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                Page count
                Pages: 12
                Categories
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                Molecular biology
                apis mellifera sinisxinyuan,new subspecies,temperate climates,population history,adaptation

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