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      The Complex Demographic History and Evolutionary Origin of the Western Honey Bee, Apis Mellifera

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          Abstract

          The western honey bee, Apis mellifera, provides critical pollination services to agricultural crops worldwide. However, despite substantial interest and prior investigation, the early evolution and subsequent diversification of this important pollinator remain uncertain. The primary hypotheses place the origin of A. mellifera in either Asia or Africa, with subsequent radiations proceeding from one of these regions. Here, we use two publicly available whole-genome data sets plus newly sequenced genomes and apply multiple population genetic analysis methods to investigate the patterns of ancestry and admixture in native honey bee populations from Europe, Africa, and the Middle East. The combination of these data sets is critical to the analyses, as each contributes samples from geographic locations lacking in the other, thereby producing the most complete set of honey bee populations available to date. We find evidence supporting an origin of A. mellifera in the Middle East or North Eastern Africa, with the A and Y lineages representing the earliest branching lineages. This finding has similarities with multiple contradictory hypotheses and represents a disentangling of genetic relationships, geographic proximity, and secondary contact to produce a more accurate picture of the origins of A. mellifera. We also investigate how previous studies came to their various conclusions based on incomplete sampling of populations, and illustrate the importance of complete sampling in understanding evolutionary processes. These results provide fundamental knowledge about genetic diversity within Old World honey bee populations and offer insight into the complex history of an important pollinator.

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          Controlling the False Discovery Rate: A Practical and Powerful Approach to Multiple Testing

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            The Sequence Alignment/Map format and SAMtools

            Summary: The Sequence Alignment/Map (SAM) format is a generic alignment format for storing read alignments against reference sequences, supporting short and long reads (up to 128 Mbp) produced by different sequencing platforms. It is flexible in style, compact in size, efficient in random access and is the format in which alignments from the 1000 Genomes Project are released. SAMtools implements various utilities for post-processing alignments in the SAM format, such as indexing, variant caller and alignment viewer, and thus provides universal tools for processing read alignments. Availability: http://samtools.sourceforge.net Contact: rd@sanger.ac.uk
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              Fast gapped-read alignment with Bowtie 2.

              As the rate of sequencing increases, greater throughput is demanded from read aligners. The full-text minute index is often used to make alignment very fast and memory-efficient, but the approach is ill-suited to finding longer, gapped alignments. Bowtie 2 combines the strengths of the full-text minute index with the flexibility and speed of hardware-accelerated dynamic programming algorithms to achieve a combination of high speed, sensitivity and accuracy.
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                Author and article information

                Journal
                Genome Biol Evol
                Genome Biol Evol
                gbe
                Genome Biology and Evolution
                Oxford University Press
                1759-6653
                February 2017
                2 February 2017
                2 February 2017
                : 9
                : 2
                : 457-472
                Affiliations
                [1 ]Department of Evolution and Ecology, University of California, Davis
                [2 ]Department of Environmental Science, Policy, and Management, University of California, Berkeley
                Author notes

                Associate editor: Dan Graur

                Data deposition: This project has been deposited at the Sequence Read Archive under the accession PRJNA294105.

                [* ]Corresponding author: E-mail: jmcridland@ 123456ucdavis.edu .
                Article
                evx009
                10.1093/gbe/evx009
                5381634
                28164223
                d910a5f0-28e6-44a4-8516-f6b3a9e0d8c7
                © The Author(s) 2017. 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

                History
                : 30 January 2017
                Page count
                Pages: 16
                Funding
                Funded by: Berkeley Initiative for Global Change Biology, the Office of the Vice Chancellor for Research at UC Berkeley, the Gordon and Betty Moore Foundation
                Award ID: GBMF2983
                Funded by: Vincent Coates Genome Sequencing Facility
                Award ID: S10RR029668
                Award ID: S10RR027303
                Funded by: USDA National Institute of Food and Agriculture
                Award ID: CA-B-INS-0087-H
                Categories
                Research Article

                Genetics
                genomics,population genetics,ancestry,apis mellifera
                Genetics
                genomics, population genetics, ancestry, apis mellifera

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