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      New insights into the phylogenetics and population structure of the prairie falcon ( Falco mexicanus)

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          Abstract

          Background

          Management requires a robust understanding of between- and within-species genetic variability, however such data are still lacking in many species. For example, although multiple population genetics studies of the peregrine falcon ( Falco peregrinus) have been conducted, no similar studies have been done of the closely-related prairie falcon ( F. mexicanus) and it is unclear how much genetic variation and population structure exists across the species’ range. Furthermore, the phylogenetic relationship of F. mexicanus relative to other falcon species is contested. We utilized a genomics approach (i.e., genome sequencing and assembly followed by single nucleotide polymorphism genotyping) to rapidly address these gaps in knowledge.

          Results

          We sequenced the genome of a single female prairie falcon and generated a 1.17 Gb (gigabases) draft genome assembly. We generated maximum likelihood phylogenetic trees using complete mitochondrial genomes as well as nuclear protein-coding genes. This process provided evidence that F. mexicanus is an outgroup to the clade that includes the peregrine falcon and members of the subgenus Hierofalco. We annotated > 16,000 genes and almost 600,000 high-quality single nucleotide polymorphisms (SNPs) in the nuclear genome, providing the raw material for a SNP assay design featuring > 140 gene-associated markers and a molecular-sexing marker. We subsequently genotyped ~ 100 individuals from California (including the San Francisco East Bay Area, Pinnacles National Park and the Mojave Desert) and Idaho (Snake River Birds of Prey National Conservation Area). We tested for population structure and found evidence that individuals sampled in California and Idaho represent a single panmictic population.

          Conclusions

          Our study illustrates how genomic resources can rapidly shed light on genetic variability in understudied species and resolve phylogenetic relationships. Furthermore, we found evidence of a single, randomly mating population of prairie falcons across our sampling locations. Prairie falcons are highly mobile and relatively rare long-distance dispersal events may promote gene flow throughout the range. As such, California’s prairie falcons might be managed as a single population, indicating that management actions undertaken to benefit the species at the local level have the potential to influence the species as a whole.

          Electronic supplementary material

          The online version of this article (10.1186/s12864-018-4615-z) contains supplementary material, which is available to authorized users.

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          Most cited references71

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          Reconstructing mitochondrial genomes directly from genomic next-generation sequencing reads—a baiting and iterative mapping approach

          We present an in silico approach for the reconstruction of complete mitochondrial genomes of non-model organisms directly from next-generation sequencing (NGS) data—mitochondrial baiting and iterative mapping (MITObim). The method is straightforward even if only (i) distantly related mitochondrial genomes or (ii) mitochondrial barcode sequences are available as starting-reference sequences or seeds, respectively. We demonstrate the efficiency of the approach in case studies using real NGS data sets of the two monogenean ectoparasites species Gyrodactylus thymalli and Gyrodactylus derjavinoides including their respective teleost hosts European grayling (Thymallus thymallus) and Rainbow trout (Oncorhynchus mykiss). MITObim appeared superior to existing tools in terms of accuracy, runtime and memory requirements and fully automatically recovered mitochondrial genomes exceeding 99.5% accuracy from total genomic DNA derived NGS data sets in <24 h using a standard desktop computer. The approach overcomes the limitations of traditional strategies for obtaining mitochondrial genomes for species with little or no mitochondrial sequence information at hand and represents a fast and highly efficient in silico alternative to laborious conventional strategies relying on initial long-range PCR. We furthermore demonstrate the applicability of MITObim for metagenomic/pooled data sets using simulated data. MITObim is an easy to use tool even for biologists with modest bioinformatics experience. The software is made available as open source pipeline under the MIT license at https://github.com/chrishah/MITObim.
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            What is a population? An empirical evaluation of some genetic methods for identifying the number of gene pools and their degree of connectivity.

            We review commonly used population definitions under both the ecological paradigm (which emphasizes demographic cohesion) and the evolutionary paradigm (which emphasizes reproductive cohesion) and find that none are truly operational. We suggest several quantitative criteria that might be used to determine when groups of individuals are different enough to be considered 'populations'. Units for these criteria are migration rate (m) for the ecological paradigm and migrants per generation (Nm) for the evolutionary paradigm. These criteria are then evaluated by applying analytical methods to simulated genetic data for a finite island model. Under the standard parameter set that includes L = 20 High mutation (microsatellite-like) loci and samples of S = 50 individuals from each of n = 4 subpopulations, power to detect departures from panmixia was very high ( approximately 100%; P < 0.001) even with high gene flow (Nm = 25). A new method, comparing the number of correct population assignments with the random expectation, performed as well as a multilocus contingency test and warrants further consideration. Use of Low mutation (allozyme-like) markers reduced power more than did halving S or L. Under the standard parameter set, power to detect restricted gene flow below a certain level X (H(0): Nm < X) can also be high, provided that true Nm < or = 0.5X. Developing the appropriate test criterion, however, requires assumptions about several key parameters that are difficult to estimate in most natural populations. Methods that cluster individuals without using a priori sampling information detected the true number of populations only under conditions of moderate or low gene flow (Nm < or = 5), and power dropped sharply with smaller samples of loci and individuals. A simple algorithm based on a multilocus contingency test of allele frequencies in pairs of samples has high power to detect the true number of populations even with Nm = 25 but requires more rigorous statistical evaluation. The ecological paradigm remains challenging for evaluations using genetic markers, because the transition from demographic dependence to independence occurs in a region of high migration where genetic methods have relatively little power. Some recent theoretical developments and continued advances in computational power provide hope that this situation may change in the future.
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              Ensembl Genomes 2016: more genomes, more complexity

              Ensembl Genomes (http://www.ensemblgenomes.org) is an integrating resource for genome-scale data from non-vertebrate species, complementing the resources for vertebrate genomics developed in the context of the Ensembl project (http://www.ensembl.org). Together, the two resources provide a consistent set of programmatic and interactive interfaces to a rich range of data including reference sequence, gene models, transcriptional data, genetic variation and comparative analysis. This paper provides an update to the previous publications about the resource, with a focus on recent developments. These include the development of new analyses and views to represent polyploid genomes (of which bread wheat is the primary exemplar); and the continued up-scaling of the resource, which now includes over 23 000 bacterial genomes, 400 fungal genomes and 100 protist genomes, in addition to 55 genomes from invertebrate metazoa and 39 genomes from plants. This dramatic increase in the number of included genomes is one part of a broader effort to automate the integration of archival data (genome sequence, but also associated RNA sequence data and variant calls) within the context of reference genomes and make it available through the Ensembl user interfaces.
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                Author and article information

                Contributors
                410-704-2117 , jdoyle@towson.edu
                DBell@ebparks.org
                petebloom@bloombiological.com
                gavin_emmons@nps.gov
                afesnock@blm.gov
                tkatzner@usgs.gov
                lflapre@aol.com
                kleona3@students.towson.edu
                pmiguel@purdue.edu
                westerman@purdue.edu
                dewoody@purdue.edu
                Journal
                BMC Genomics
                BMC Genomics
                BMC Genomics
                BioMed Central (London )
                1471-2164
                4 April 2018
                4 April 2018
                2018
                : 19
                : 233
                Affiliations
                [1 ]ISNI 0000 0001 0719 7561, GRID grid.265122.0, Department of Biological Sciences, , Towson University, ; 8000 York Rd, Baltimore, MD 21212 USA
                [2 ]ISNI 0000 0004 1937 2197, GRID grid.169077.e, Department of Forestry and Natural Resources, , Purdue University, ; 715 W. State Street, West Lafayette, IN 47907 USA
                [3 ]East Bay Regional Park District, 2950 Peralta Oaks Court, Oakland, CA 94605 USA
                [4 ]ISNI 0000 0004 0461 6769, GRID grid.242287.9, Department of Ornithology and Mammalogy, , California Academy of Sciences, ; 55 Concourse Drive, Golden Gate Park, San Francisco, CA 94118 USA
                [5 ]Bloom Research Inc., 1820 S. Dunsmuir, Los Angeles, CA 90019 USA
                [6 ]National Park Service, Pinnacles National Park, 5000 Highway 146, Paicines, CA 95043 USA
                [7 ]GRID grid.462133.1, California State Office, , Bureau of Land Management, ; 2800 Cottage Way, Suite W-1928, Sacramento, CA 95825 USA
                [8 ]U.S. Geological Survey, Forest and Rangeland Ecosystem Science Center, 970 Lusk Street, Boise, ID 83706 USA
                [9 ]Bureau of Land Management, California Desert District, 22835 Calle San Juan De Los Lagos, Moreno Valley, CA 92553 USA
                [10 ]ISNI 0000 0001 0719 7561, GRID grid.265122.0, Department of Computer and Information Sciences, , Towson University, ; 8000 York Rd, Baltimore, MD 21212 USA
                [11 ]ISNI 0000 0004 1937 2197, GRID grid.169077.e, Department of Horticulture and Landscape Architecture, , Purdue University, ; West Lafayette, IN 47907 USA
                [12 ]ISNI 0000 0004 1937 2197, GRID grid.169077.e, Department of Biological Sciences, , Purdue University, ; 915 W. State Street, West Lafayette, IN 47907 USA
                Article
                4615
                10.1186/s12864-018-4615-z
                5885362
                29618317
                86ea8d0d-a417-41b3-9929-72728f90d1d4
                © The Author(s). 2018

                Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License ( http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided 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 Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.

                History
                : 15 August 2017
                : 22 March 2018
                Funding
                Funded by: FundRef http://dx.doi.org/10.13039/100007149, U.S. Bureau of Land Management;
                Award ID: L12AC20102, L11PX02237, L12AC2010
                Funded by: Provost's Office at Purdue University
                Award ID: University Faculty Scholar program
                Funded by: FundRef http://dx.doi.org/10.13039/100007516, National Park Service;
                Award ID: PINN645-21
                Award Recipient :
                Funded by: Save Mount Diablo
                Funded by: East Bay Regional Park District
                Funded by: Contra Costa County Fish and Wildlife Propagation Fund
                Funded by: Alameda County Birds of Prey Reserve Foundation
                Funded by: FundRef http://dx.doi.org/10.13039/100009503, California State University, Sacramento;
                Funded by: Wayman-McAuliffe Family Fund for Ornithology
                Funded by: XSEDE
                Award ID: BIO170038
                Award Recipient :
                Categories
                Research Article
                Custom metadata
                © The Author(s) 2018

                Genetics
                panmixia,hierofalcons,snp genotyping,avian genome assembly,molecular sexing,repeatability,selection,phylogenomics

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