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      Ecological drivers of genetic connectivity for African malaria vectors Anopheles gambiae and An. arabiensis

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          Abstract

          Anopheles gambiae and An. arabiensis are major malaria vectors in sub-Saharan Africa. Knowledge of how geographical factors drive the dispersal and gene flow of malaria vectors can help in combatting insecticide resistance spread and planning new vector control interventions. Here, we used a landscape genetics approach to investigate population relatedness and genetic connectivity of An. gambiae and An. arabiensis across Kenya and determined the changes in mosquito population genetic diversity after 20 years of intensive malaria control efforts. We found a significant reduction in genetic diversity in An. gambiae, but not in An. arabiensis as compared to prior to the 20-year period in western Kenya. Significant population structure among populations was found for both species. The most important ecological driver for dispersal and gene flow of An. gambiae and An. arabiensis was tree cover and cropland, respectively. These findings highlight that human induced environmental modifications may enhance genetic connectivity of malaria vectors.

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          Arlequin suite ver 3.5: a new series of programs to perform population genetics analyses under Linux and Windows.

          LAURENT EXCOFFIER, HEIDI LISCHER (2010)
          We present here a new version of the Arlequin program available under three different forms: a Windows graphical version (Winarl35), a console version of Arlequin (arlecore), and a specific console version to compute summary statistics (arlsumstat). The command-line versions run under both Linux and Windows. The main innovations of the new version include enhanced outputs in XML format, the possibility to embed graphics displaying computation results directly into output files, and the implementation of a new method to detect loci under selection from genome scans. Command-line versions are designed to handle large series of files, and arlsumstat can be used to generate summary statistics from simulated data sets within an Approximate Bayesian Computation framework. © 2010 Blackwell Publishing Ltd.
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            genepop'007: a complete re-implementation of the genepop software for Windows and Linux.

            FRANÇOIS ROUSSET (2008)
            This note summarizes developments of the genepop software since its first description in 1995, and in particular those new to version 4.0: an extended input format, several estimators of neighbourhood size under isolation by distance, new estimators and confidence intervals for null allele frequency, and less important extensions to previous options. genepop now runs under Linux as well as under Windows, and can be entirely controlled by batch calls. © 2007 The Author.
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              Identification of single specimens of the Anopheles gambiae complex by the polymerase chain reaction.

              J Scott, W. BROGDON, F Collins (1993)
              A ribosomal DNA-polymerase chain reaction (PCR) method has been developed for species identification of individuals of the five most widespread members of the Anopheles gambiae complex, a group of morphologically indistinguishable sibling mosquito species that includes the major vectors of malaria in Africa. The method, which is based on species-specific nucleotide sequences in the ribosomal DNA intergenic spacers, may be used to identify both species and interspecies hybrids, regardless of life stage, using either extracted DNA or fragments of a specimen. Intact portions of a mosquito as small as an egg or the segment of one leg may be placed directly into the PCR mixture for amplification and analysis. The method uses a cocktail of five 20-base oligonucleotides to identify An. gambiae, An. arabiensis, An. quadriannnulatus, and either An. melas in western Africa or An. melas in eastern and southern Africa.
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                Author and article information

                Contributors
                Guiyun Yan: guiyuny@hs.uci.edu
                Journal
                Journal ID (nlm-ta): Sci Rep
                Journal ID (iso-abbrev): Sci Rep
                Title: Scientific Reports
                Publisher: Nature Publishing Group UK (London )
                ISSN (Electronic): 2045-2322
                Publication date (Electronic): 17 November 2020
                Publication date PMC-release: 17 November 2020
                Publication date Collection: 2020
                Volume: 10
                Electronic Location Identifier: 19946
                Affiliations
                [1 ]GRID grid.266093.8, ISNI 0000 0001 0668 7243, Department of Ecology and Evolutionary Biology and Program in Public Health, , University of California, ; Irvine, CA 92617 USA
                [2 ]GRID grid.33058.3d, ISNI 0000 0001 0155 5938, Center for Global Health Research, , Kenya Medical Research Institute, ; Kisumu, Kenya
                [3 ]GRID grid.449370.d, ISNI 0000 0004 1780 4347, School of Pure and Applied Sciences, , Pwani University, ; Kilifi, Kenya
                [4 ]GRID grid.442486.8, ISNI 0000 0001 0744 8172, School of Public Health and Community Development, , Maseno University, ; Kisumu, Kenya
                [5 ]GRID grid.94365.3d, ISNI 0000 0001 2297 5165, Laboratory of Malaria and Vector Research, , National Institutes of Health, ; Bethesda, MD 20892 USA
                [6 ]GRID grid.67105.35, ISNI 0000 0001 2164 3847, Present Address: Center for Global Health and Diseases, , Case Western Reserve University, ; Cleveland, OH 44106 USA
                Article
                Publisher ID: 76248
                DOI: 10.1038/s41598-020-76248-2
                PMC ID: 7673128
                PubMed ID: 33203917
                SO-VID: c666120e-f96f-416f-aa67-bbd9a72ff976
                Copyright © © The Author(s) 2020
                License:

                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 licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence 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 licence, visit http://creativecommons.org/licenses/by/4.0/.

                History
                Date received : 27 April 2020
                Date accepted : 15 October 2020
                Funding
                Funded by: FundRef http://dx.doi.org/10.13039/100000002, National Institutes of Health;
                Award ID: F32AI147460
                Award ID: U19AI129326
                Award ID: U19AI129326
                Award Recipient :
                Categories
                Subject: Article
                Custom metadata
                issue-copyright-statement © The Author(s) 2020

                ScienceOpen disciplines: Uncategorized
                Keywords: ecological genetics,malaria
                Data availability:
                ScienceOpen disciplines: Uncategorized
                Keywords: ecological genetics, malaria

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